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"Material/env/lib/python3.12/site-packages/nbgrader/server_extensions/formgrader/static/components/datatables.net-bs/Readme.md" + "Material/env/lib/python3.12/site-packages/nbgrader/server_extensions/formgrader/static/components/jquery/README.md" ] } \ No newline at end of file diff --git a/Gruppen/Engineering 1.md b/Gruppen/Engineering 1.md index 8b62ebb..c6a7c7b 100644 --- a/Gruppen/Engineering 1.md +++ b/Gruppen/Engineering 1.md @@ -7,13 +7,13 @@ tags: --- # Mitglieder -| Name | Punkte | Durchschnitt | Jupyter Kennung | Mail | -| -------------- | ------ | ------------ | -------------------------------------------------------------------------- | ------------------------------------------------------------------------- | -| Janna Heiny | | | | [j.heiny@tu-braunschweig.de](mailto:j.heiny@tu-braunschweig.de) | -| Milena Krieger | | | | [m.krieger@tu-braunschweig.de](mailto:m.krieger@tu-braunschweig.de) | -| Xiaowei Wang | | | 39dc5bd7686c3280247aacee82c9818e | [xiaowei.wang@tu-braunschweig.de](mailto:xiaowei.wang@tu-braunschweig.de) | -| | | | | | -| | | | | | +| Name | Punkte | Durchschnitt | Jupyter Kennung | Mail | +| -------------- | ------ | ------------ | -------------------------------- | ------------------------------------------------------------------------- | +| Janna Heiny | | | 3140c4b62381a2203803f8b237118244 | [j.heiny@tu-braunschweig.de](mailto:j.heiny@tu-braunschweig.de) | +| Milena Krieger | | | 8be9a4cc0b240a18171892b873dc2cb8 | [m.krieger@tu-braunschweig.de](mailto:m.krieger@tu-braunschweig.de) | +| Xiaowei Wang | | | 39dc5bd7686c3280247aacee82c9818e | [xiaowei.wang@tu-braunschweig.de](mailto:xiaowei.wang@tu-braunschweig.de) | +| | | | | | +| | | | | | # Notizen diff --git a/Gruppen/MeWi 2.md b/Gruppen/MeWi 2.md index 20e5b57..1768e09 100644 --- a/Gruppen/MeWi 2.md +++ b/Gruppen/MeWi 2.md @@ -12,7 +12,7 @@ tags: | Izabel Mike | 29.5 | | 8c710a24debf6159659d1e58dd975ce2 | [i.mike@tu-braunschweig.de](mailto:i.mike@tu-braunschweig.de) | | Lara Troschke | 20.5 | | 7b441c67713f2a49811625905612f19b | [l.troschke@tu-braunschweig.de](mailto:l.troschke@tu-braunschweig.de) | | Inga-Brit Turschner | 25.5 | | 72f0b5fd2cdf4dd808ca9a3add584c75 | [i.turschner@tu-braunschweig.de](mailto:i.turschner@tu-braunschweig.de) | -| | | | | | +| Yannik Haupt | | | f4f597c57d8a31960750e0647f917ed3 | | | | | | | | # Notizen diff --git a/Gruppen/MeWi 4.md b/Gruppen/MeWi 4.md index cc356d3..04193ad 100644 --- a/Gruppen/MeWi 4.md +++ b/Gruppen/MeWi 4.md @@ -7,13 +7,13 @@ tags: --- # Mitglieder -| Name | Punkte | Durchschnitt | Jupyter Kennung | Mail | -| ------------------ | ------ | ------------ | --------------------------------------------------------------------- | ----------------------------------------------------------------- | -| Nova Eib | 31 | | b313c08a73772a8237e0593ec5c3ee27 | [n.eib@tu-braunschweig.de](mailto:n.eib@tu-braunschweig.de) | -| Julia Renner | | | | [j.renner@tu-braunschweig.de](mailto:j.renner@tu-braunschweig.de) | -| Isabel Rudolf | | | 4306ac2b1bf2fe7189d53aad469 | [i.rudolf@tu-braunschweig.de](mailto:i.rudolf@tu-braunschweig.de) | -| Katharina Walz | 31 | | 6349002488dfe4343537174fb9381f95 | [k.walz@tu-braunschweig.de](mailto:k.walz@tu-braunschweig.de) | -| Unsichtbare Person | | | | | +| Name | Punkte | Durchschnitt | Jupyter Kennung | Mail | +| -------------- | ------ | ------------ | -------------------------------- | ----------------------------------------------------------------- | +| Nova Eib | 31 | | b313c08a73772a8237e0593ec5c3ee27 | [n.eib@tu-braunschweig.de](mailto:n.eib@tu-braunschweig.de) | +| Julia Renner | | | 9efda636813423536dfd581ebeae4edc | [j.renner@tu-braunschweig.de](mailto:j.renner@tu-braunschweig.de) | +| Isabel Rudolf | | | 4306ac2b1bf2fe7189d53aad46999f31 | [i.rudolf@tu-braunschweig.de](mailto:i.rudolf@tu-braunschweig.de) | +| Katharina Walz | 31 | | 6349002488dfe4343537174fb9381f95 | [k.walz@tu-braunschweig.de](mailto:k.walz@tu-braunschweig.de) | +| Cam Thu Do | | | dcccfe28b7e78cc77c118532574b1075 | | # Notizen diff --git a/Gruppen/MeWi 5.md b/Gruppen/MeWi 5.md index af9f320..cc51254 100644 --- a/Gruppen/MeWi 5.md +++ b/Gruppen/MeWi 5.md @@ -7,13 +7,13 @@ tags: --- # Mitglieder -| Name | Punkte | Durchschnitt | Jupyter Kennung | Mail | -| -------------- | ------ | ------------ | -------------------------------------------------------------------------- | --------------------------------------------------------------------- | -| Vikoria Litza | | | | [v.litza@tu-braunschweig.de](mailto:v.litza@tu-braunschweig.de) | -| Lea Noglik | | | f24ccc1cefe390cd1036419b89f31d4f | [l.noglik@tu-braunschweig.de](mailto:l.noglik@tu-braunschweig.de) | -| Donika Nuhiu | | | | [d.nuhiu@tu-braunschweig.de](mailto:d.nuhiu@tu-braunschweig.de) | -| Alea Unger | 30 | | f8c2ba8abf5b7d89a240902634a5c53a | [a.unger@tu-braunschweig.de](mailto:a.unger@tu-braunschweig.de) | -| Marie Wallbaum | | | eec48a6d211105d6f87267fbd428ab69 | [m.wallbaum@tu-braunschweig.de](mailto:m.wallbaum@tu-braunschweig.de) | +| Name | Punkte | Durchschnitt | Jupyter Kennung | Mail | +| -------------- | ------ | ------------ | -------------------------------- | --------------------------------------------------------------------- | +| Vikoria Litza | | | 055a44301e7b7281e0ee98815f99c4dd | [v.litza@tu-braunschweig.de](mailto:v.litza@tu-braunschweig.de) | +| Lea Noglik | | | f24ccc1cefe390cd1036419b89f31d4f | [l.noglik@tu-braunschweig.de](mailto:l.noglik@tu-braunschweig.de) | +| Donika Nuhiu | | | bb62dfd14ba80f21678bee50e4f69131 | [d.nuhiu@tu-braunschweig.de](mailto:d.nuhiu@tu-braunschweig.de) | +| Alea Unger | 30 | | f8c2ba8abf5b7d89a240902634a5c53a | [a.unger@tu-braunschweig.de](mailto:a.unger@tu-braunschweig.de) | +| Marie Wallbaum | | | eec48a6d211105d6f87267fbd428ab69 | [m.wallbaum@tu-braunschweig.de](mailto:m.wallbaum@tu-braunschweig.de) | # Notizen diff --git a/Gruppen/MeWi 6.md b/Gruppen/MeWi 6.md index c34e3f0..5089bc8 100644 --- a/Gruppen/MeWi 6.md +++ b/Gruppen/MeWi 6.md @@ -7,13 +7,13 @@ tags: --- # Mitglieder -| Name | Punkte | Durchschnitt | Jupyter Kennung | Mail | -| --------------- | ------ | ------------ | -------------------------------------------------------------------------- | ----------------------------------------------------------------------- | -| Nele Grundke | | | f61621cbe911f21ddd781c21e4528b07 | [n.grundke@tu-braunschweig.de](mailto:n.grundke@tu-braunschweig.de) | -| Julia Limbach | | | | [j.limbach@tu-braunschweig.de](mailto:j.limbach@tu-braunschweig.de) | -| Melina Sablotny | | | 4111400b4ae2c863a1c4b73a21f87093 | [m.sablotny@tu-braunschweig.de](mailto:m.sablotny@tu-braunschweig.de) | -| Lucy Thiele | | | 4c0ddab5bed6ff025cee04f8d73301a3 | [lucy.thiele@tu-braunschweig.de](mailto:lucy.thiele@tu-braunschweig.de) | -| | | | | | +| Name | Punkte | Durchschnitt | Jupyter Kennung | Mail | +| --------------- | ------ | ------------ | -------------------------------- | ----------------------------------------------------------------------- | +| Nele Grundke | | | f61621cbe911f21ddd781c21e4528b07 | [n.grundke@tu-braunschweig.de](mailto:n.grundke@tu-braunschweig.de) | +| Julia Limbach | | | | [j.limbach@tu-braunschweig.de](mailto:j.limbach@tu-braunschweig.de) | +| Melina Sablotny | | | 4111400b4ae2c863a1c4b73a21f87093 | [m.sablotny@tu-braunschweig.de](mailto:m.sablotny@tu-braunschweig.de) | +| Lucy Thiele | | | 4c0ddab5bed6ff025cee04f8d73301a3 | [lucy.thiele@tu-braunschweig.de](mailto:lucy.thiele@tu-braunschweig.de) | +| | | | | | # Notizen diff --git a/Gruppen/MeWi 7 (DiKum).md b/Gruppen/MeWi 7 (DiKum).md index 0fd8cc5..7fd470c 100644 --- a/Gruppen/MeWi 7 (DiKum).md +++ b/Gruppen/MeWi 7 (DiKum).md @@ -7,13 +7,13 @@ tags: --- # Mitglieder -| Name | Punkte | Durchschnitt | Jupyter Kennung | Mail | -| ------------------- | ------ | ------------ | -------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | -| Abdalaziz Abunjaila | 30.5 | | 79b388885f89954decaefc9e19aa8871 | [a.abunjaila@tu-braunschweig.de](mailto:a.abunjaila@tu-braunschweig.de) | -| Marleen Adolphi | | | | [m.adolphi@tu-braunschweig.de](mailto:m.adolphi@tu-braunschweig.de) | -| Alea Schleier | | | | [a.schleier@tu-braunschweig.de](mailto:a.schleier@tu-braunschweig.de) | -| Marie Seeger | | | f7017b11a2904a74302c9f4f217779fb | [marie.seeger@tu-braunschweig.de](mailto:marie.seeger@tu-braunschweig.de) | -| Lilly-Lu Warnken | | | | [lilly-lu.warnken@tu-braunschweig.de](mailto:lilly-lu.warnken@tu-braunschweig.de) | +| Name | Punkte | Durchschnitt | Jupyter Kennung | Mail | +| ------------------- | ------ | ------------ | -------------------------------- | --------------------------------------------------------------------------------- | +| Abdalaziz Abunjaila | 30.5 | | 79b388885f89954decaefc9e19aa8871 | [a.abunjaila@tu-braunschweig.de](mailto:a.abunjaila@tu-braunschweig.de) | +| Marleen Adolphi | | | bb549f9016ee05a07ce271c10482879d | [m.adolphi@tu-braunschweig.de](mailto:m.adolphi@tu-braunschweig.de) | +| Alea Schleier | | | beb3bcd7515400b58f6fab7567193cbf | [a.schleier@tu-braunschweig.de](mailto:a.schleier@tu-braunschweig.de) | +| Marie Seeger | | | f7017b11a2904a74302c9f4f217779fb | [marie.seeger@tu-braunschweig.de](mailto:marie.seeger@tu-braunschweig.de) | +| Lilly-Lu Warnken | | | 5fe894b59ff39da82ac4361dcb2d35b8 | [lilly-lu.warnken@tu-braunschweig.de](mailto:lilly-lu.warnken@tu-braunschweig.de) | # Notizen diff --git a/Material/wise_24_25/lernmaterial/Einrichtung/How to Jupyter.slides.html b/Material/3.Vorlesung.html similarity index 79% rename from Material/wise_24_25/lernmaterial/Einrichtung/How to Jupyter.slides.html rename to Material/3.Vorlesung.html index 461ffb2..0865276 100644 --- a/Material/wise_24_25/lernmaterial/Einrichtung/How to Jupyter.slides.html +++ b/Material/3.Vorlesung.html @@ -2,24 +2,8 @@ - - - -How to Jupyter slides - - - - + +V3 - @@ -7427,288 +7324,1545 @@ main { } init_mathjax(); - - - + + +
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- diff --git a/Material/3.Vorlesung.slides.html b/Material/Tutorial1_Lösungen.html similarity index 100% rename from Material/3.Vorlesung.slides.html rename to Material/Tutorial1_Lösungen.html diff --git a/Material/V3.ipynb b/Material/V3.ipynb index e6c3a87..fb2a52c 100644 --- a/Material/V3.ipynb +++ b/Material/V3.ipynb @@ -8,6 +8,14 @@ "# 3. Vorlesung" ] }, + { + "cell_type": "markdown", + "id": "a21df6bb-f501-474a-9e1a-7dd2a90cd92d", + "metadata": {}, + "source": [ + "### Einfache Zählschleife" + ] + }, { "cell_type": "code", "execution_count": 2, @@ -25,10 +33,11 @@ } ], "source": [ - "count = 1\n", - "while count < 4:\n", + "# Als While Loop\n", + "count = 1 # Zählvariable\n", + "while count < 4: # Bedingung\n", " print(count)\n", - " count += 1 " + " count += 1 # Hochzählen" ] }, { @@ -48,6 +57,7 @@ } ], "source": [ + "# Als For Loop\n", "for count in [1, 2, 3]:\n", " print(count)" ] @@ -57,6 +67,8 @@ "id": "daaa7cbe-0cb7-45c9-89a8-241561908db2", "metadata": {}, "source": [ + "Beispiel einer Zählschleife in C:\n", + "\n", "```C\n", "for (int i = 0; i < 4, i++) {}\n", "```" @@ -64,7 +76,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 2, "id": "3e461857-f366-46f8-ad51-9800348b4521", "metadata": {}, "outputs": [ @@ -73,18 +85,110 @@ "output_type": "stream", "text": [ "1\n", + "2\n", "3\n" ] } ], "source": [ - "for count in range(1,4,2):\n", + "# Zählschleife mittels range Funktion\n", + "for count in range(1,4):\n", " print(count)" ] }, + { + "cell_type": "markdown", + "id": "b572967d-7488-4be7-b8b7-8b0237eddc86", + "metadata": {}, + "source": [ + "`range` kann bis zu 3 Parameter nehmen.\n", + "\n", + "- 1 Parameter `range(4)` -> Zählt in 1er Schritten bis exklusive der eingegebenen Zahl *0,1,2,3*\n", + "\n", + "Der folgend genutzte Stern `*` sagt Python er soll den `iterator` entpacken." + ] + }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 4, + "id": "30d52051-cee6-4bcd-a622-c70bdd0cae1e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0 1 2 3\n" + ] + } + ], + "source": [ + "print(*range(4))" + ] + }, + { + "cell_type": "markdown", + "id": "8e2dbb80-5bfd-43ee-83b6-8ef299c70391", + "metadata": {}, + "source": [ + "- 2 Parameter `range(1,4)` -> Zählt in 1er Schritten von dem ersten Parameter bis exklusiv zum zweiten Parameter *1,2,3*" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "fe434e93-729b-466c-a530-125c668f2329", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1 2 3\n" + ] + } + ], + "source": [ + "print(*range(1,4))" + ] + }, + { + "cell_type": "markdown", + "id": "7d5d28a6-b873-4a2b-8e45-b02e75982c10", + "metadata": {}, + "source": [ + "- 3 Parameter `range(1,11,2)` -> Zählt in `2`er Schritten von dem ersten Parameter bis exklusiv zum zweiten Parameter " + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "03e36a0d-9d0f-4dcd-8e02-3d234da9fb52", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1 3 5 7 9\n" + ] + } + ], + "source": [ + "print(*range(1,11,2))" + ] + }, + { + "cell_type": "markdown", + "id": "698e2a24-d96e-4f39-b76a-bfa2b6d20297", + "metadata": {}, + "source": [ + "`For-Loops` itertieren über Iteratoren. Listen sind z.b. Iteratoren." + ] + }, + { + "cell_type": "code", + "execution_count": 7, "id": "4f4d9b6c-c262-45a0-ab7a-ac8d3f13d110", "metadata": {}, "outputs": [ @@ -94,7 +198,7 @@ "[0, 1, 2, 3, 4]" ] }, - "execution_count": 8, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -106,7 +210,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "fbcb9b7d-2850-41fe-82a5-09ad75191329", "metadata": {}, "outputs": [ @@ -129,7 +233,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "c1cb9b0a-170c-4b45-b329-e28b0f8ee818", "metadata": {}, "outputs": [ @@ -139,18 +243,18 @@ "5" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "len(l)" + "len(l) # Anzahl 'Länge' der Liste l" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 10, "id": "f595c1f5-4945-4ee4-89e7-cde25d2a7e41", "metadata": {}, "outputs": [ @@ -167,13 +271,14 @@ } ], "source": [ + "# range zählt bis 'exklusive' seines Eingabeparameters um folgendes verhalten zu emulieren\n", "for i in range(len(l)):\n", " print(i)" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 11, "id": "6902e5e5-0a49-4bce-a03a-f4c4d812ffa7", "metadata": {}, "outputs": [ @@ -190,13 +295,14 @@ } ], "source": [ + "# Iteration über die Indexe der Liste \n", "for i in range(len(l)):\n", - " print(l[i])" + " print(l[i]) # Zugriff über Index auf die Elemente der Liste" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 12, "id": "4e2f0c81-894d-424d-848f-3e7cc36bd70b", "metadata": {}, "outputs": [ @@ -214,13 +320,22 @@ } ], "source": [ + "# _ wird verwendet für Loops die einfach etwas immer und immer wiederholen sollen\n", "for _ in range(6):\n", " print(\"Hello\")" ] }, + { + "cell_type": "markdown", + "id": "c555a1d3-dc65-43e1-b19a-070653a34645", + "metadata": {}, + "source": [ + "Folgende Dict beispiele Eklären sich dementsprechend selber" + ] + }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 13, "id": "e1fbf047-ed8c-4a27-9729-6b05ed55140a", "metadata": {}, "outputs": [ @@ -230,7 +345,7 @@ "{'a': 5, 'b': 8, 'c': 10}" ] }, - "execution_count": 16, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -242,7 +357,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 14, "id": "faf3bea9-a308-4317-8a5d-ba4281a86671", "metadata": {}, "outputs": [ @@ -252,7 +367,7 @@ "dict_values([5, 8, 10])" ] }, - "execution_count": 17, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -263,7 +378,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 15, "id": "52262d79-76d2-4bf4-8f06-8ed55dcff7cc", "metadata": {}, "outputs": [ @@ -284,7 +399,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 16, "id": "280eb1d9-bfe8-4715-a54a-4b40ef542618", "metadata": {}, "outputs": [ @@ -305,7 +420,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 17, "id": "7a0fde62-9fa8-4089-b257-d2a2263b2b0d", "metadata": {}, "outputs": [ @@ -320,13 +435,14 @@ } ], "source": [ + "# Items gibt eine Liste mit tupeln zurück, jedes tuple wird in seine Elemente zerlegt und den Variablen k & v zugewiesen\n", "for k, v in d.items():\n", " print(f\"Key: {k} mit Wert: {v}\")" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 18, "id": "dc988e8a-135d-483f-9ae0-d20cc861c558", "metadata": {}, "outputs": [ @@ -336,12 +452,13 @@ "[0, 1, 4, 9, 16, 25]" ] }, - "execution_count": 22, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "# Liste füllen\n", "squared = []\n", "for i in range(6):\n", " squared.append(i*i)\n", @@ -350,7 +467,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 19, "id": "94f148fb-a1f3-4bd9-82b0-baa3ad0b9d35", "metadata": {}, "outputs": [ @@ -360,19 +477,20 @@ "[0, 1, 4, 9, 16, 25]" ] }, - "execution_count": 23, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "# List Comprehension \n", "sq = [n**2 for n in range(6)]\n", "sq" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 20, "id": "3e6d5db7-3cc1-4b21-9ad0-4d3402b4765b", "metadata": {}, "outputs": [ @@ -382,12 +500,13 @@ "{0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25}" ] }, - "execution_count": 25, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "# Dict füllen\n", "di = {}\n", "for n in range(6):\n", " di[n] = n**2\n", @@ -396,7 +515,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 21, "id": "6bd693d3-8e27-48c2-9fe4-8ecafb98b181", "metadata": {}, "outputs": [ @@ -406,16 +525,25 @@ "{0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25}" ] }, - "execution_count": 26, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "# Dictionary Comprehension\n", "dic = {n: n**2 for n in range(6)}\n", "dic" ] }, + { + "cell_type": "markdown", + "id": "bf09cbc2-c2c5-4f59-8ad7-c7c5e9e50f63", + "metadata": {}, + "source": [ + "## System Interaction" + ] + }, { "cell_type": "code", "execution_count": 27, @@ -511,9 +639,17 @@ "input(\"Gebe bitte eine Zahl ein:\")" ] }, + { + "cell_type": "markdown", + "id": "60afb4f7-e8c5-431e-a592-b9b719f9b68c", + "metadata": {}, + "source": [ + "## File Handling" + ] + }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 24, "id": "d47d956b-f131-4c4c-acad-4adc5ff1508e", "metadata": {}, "outputs": [ @@ -523,19 +659,19 @@ "<_io.TextIOWrapper name='test.txt' mode='r' encoding='UTF-8'>" ] }, - "execution_count": 34, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "f = open('test.txt')\n", + "f = open('test.txt') # Öffne File und gebe den Handler an f, Standard im Lesemodus\n", "f" ] }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 25, "id": "4d38875a-18f9-4ad6-991b-fc61ea1dd08a", "metadata": {}, "outputs": [ @@ -545,18 +681,18 @@ "['Super Secret Message\\n', 'Hallo Welt\\n', 'Geiler Kurs\\n', 'Freitag 15h yeah']" ] }, - "execution_count": 35, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "f.readlines()" + "f.readlines() # Lese den Inhalt aus f" ] }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 28, "id": "1c0610b1-b6c2-430f-94c0-e50def936b16", "metadata": {}, "outputs": [ @@ -566,19 +702,19 @@ "<_io.TextIOWrapper name='data.txt' mode='w' encoding='UTF-8'>" ] }, - "execution_count": 39, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "data = open('data.txt', 'w')\n", + "data = open('data.txt', 'w') # Öffne eine beschreibare File\n", "data" ] }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 29, "id": "1b74ffb0-487a-4ec7-9ed1-3e51b5c76450", "metadata": {}, "outputs": [ @@ -588,29 +724,30 @@ "18" ] }, - "execution_count": 40, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "data.write(\"Ich will nachhause\")" + "data.write(\"Ich will nachhause\") # Schreibe in die File " ] }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 31, "id": "f831efc1-b548-4a49-bbed-62c8018ecdfe", "metadata": {}, "outputs": [], "source": [ + "# Schliese die Files\n", "f.close()\n", "data.close()" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 32, "id": "4580acb8-cc79-440c-a463-140547883ded", "metadata": {}, "outputs": [ @@ -623,6 +760,7 @@ } ], "source": [ + "# Standard File handling\n", "f = open('test.txt')\n", "print(f.readlines())\n", "f.close()" @@ -630,7 +768,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 33, "id": "50f35e0c-5138-478c-abe9-dae163c467a4", "metadata": {}, "outputs": [ @@ -641,18 +779,18 @@ "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[44], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreadlines\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "Cell \u001b[0;32mIn[33], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreadlines\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# File ist geschlossen also ist lesen nicht möglich\u001b[39;00m\n", "\u001b[0;31mValueError\u001b[0m: I/O operation on closed file." ] } ], "source": [ - "f.readlines()" + "f.readlines() # File ist geschlossen also ist lesen nicht möglich" ] }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 35, "id": "999e5179-4d96-4b8b-bec6-3f8b0a857291", "metadata": {}, "outputs": [ @@ -670,15 +808,26 @@ "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[45], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mopen\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtest.txt\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(f\u001b[38;5;241m.\u001b[39mreadlines())\n\u001b[0;32m----> 3\u001b[0m \u001b[43mf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreadlines\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "Cell \u001b[0;32mIn[35], line 6\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(f\u001b[38;5;241m.\u001b[39mreadlines())\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m# File ist bereits geschlossen \u001b[39;00m\n\u001b[0;32m----> 6\u001b[0m \u001b[43mf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreadlines\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# Wirft Fehler\u001b[39;00m\n", "\u001b[0;31mValueError\u001b[0m: I/O operation on closed file." ] } ], "source": [ + "# Contexte nehmen einem die Arbeit ab\n", "with open('test.txt', 'r') as f:\n", " print(f.readlines())\n", - "f.readlines()" + "\n", + "# File ist bereits geschlossen \n", + "f.readlines() # Wirft Fehler" + ] + }, + { + "cell_type": "markdown", + "id": "d63dce40-9d51-4ab6-92e6-65fedb982dd8", + "metadata": {}, + "source": [ + "# Importing" ] }, { @@ -777,7 +926,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 37, "id": "c4c97328-95dd-4e6b-bc9c-857ee5d04e25", "metadata": {}, "outputs": [], @@ -785,6 +934,27 @@ "from math import sqrt" ] }, + { + "cell_type": "code", + "execution_count": 38, + "id": "1f29d236-0368-4fd4-97c1-a33a6adc7bf3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sqrt" + ] + }, { "cell_type": "code", "execution_count": 52, @@ -808,17 +978,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "id": "b83a73fe-8f6e-4b22-97bc-c9016206a6bd", "metadata": {}, "outputs": [], "source": [ - "from math import *" + "from math import * # Böse nicht mache führt nur zu unerklärbaren Fehlern" ] }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 40, "id": "d1568734-9077-4444-9c0e-5dbf385dc46a", "metadata": {}, "outputs": [], @@ -828,7 +998,7 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 41, "id": "718bb6e9-1cda-438d-909a-b51064471d0a", "metadata": {}, "outputs": [ @@ -838,7 +1008,7 @@ "np.float64(94.86832980505137)" ] }, - "execution_count": 54, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } @@ -849,11 +1019,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, "id": "806082c4-61fc-4345-bd85-aa4deec1414a", "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np" + ] } ], "metadata": { @@ -872,7 +1055,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.5" + "version": "3.12.7" } }, "nbformat": 4, diff --git a/Material/wise_23_24/lernmaterial/Random Numbers/zufallszahlen.ipynb b/Material/wise_23_24/lernmaterial/Random Numbers/zufallszahlen.ipynb index 244b4af..e815dce 100644 --- a/Material/wise_23_24/lernmaterial/Random Numbers/zufallszahlen.ipynb +++ b/Material/wise_23_24/lernmaterial/Random Numbers/zufallszahlen.ipynb @@ -1955,7 +1955,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.5" + "version": "3.12.7" } }, "nbformat": 4, diff --git a/Material/wise_24_25/lernmaterial/4.NP_MPL.ipynb b/Material/wise_24_25/lernmaterial/4.NP_MPL.ipynb new file mode 100644 index 0000000..a729404 --- /dev/null +++ b/Material/wise_24_25/lernmaterial/4.NP_MPL.ipynb @@ -0,0 +1,2792 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "40366dea-bec8-4128-b8e9-a7c10536a613", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-44b468fb46efb002", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "# 4. Programmierübung: NumPy\n", + "\n", + "
\n", + "
\n", + " Willkommen zur vierten Programmierübung Einführung in Python 3.\n", + "
\n", + " \n", + "
\n", + "\n", + "Wenn Sie Fragen oder Verbesserungsvorschläge zum Inhalt oder Struktur der Notebooks haben, dann können sie eine E-Mail an Phil Keier ([p.keier@hbk-bs.de](mailto:p.keier@hbk-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) oder Martin Le ([martin.le@tu-bs.de](mailto:martin.le@tu-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) schreiben.\n", + "\n", + "Link zu einem Python Spickzettel: [hier](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf)\n", + "\n", + "Der Großteil des Python-Tutorials stammt aus der Veranstaltung _Deep Learning Lab_ und von [www.python-kurs.eu](https://www.python-kurs.eu/python3_kurs.php) und wurde für _Signale und Systeme_, sowie _Einführung in die Programmierung für Nicht Informatiker_ angepasst.\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "4d4eed4c-36ff-4643-bbc8-6c5440f73065", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-5ac025a1f69e3f31", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "# Was ist NumPy\n", + "\n", + "NumPy steht für *Numerical Python*, ist OpenSource und wird mittlerweile von nahezu jedem Python Entwickeler verwendet. Dabei ist das Core Feature von NumPy seine effiziente Implementierung eines n-dimensionales Arrays in C, welches in Python verwendet werden kann. Hinzu kommt eine Hülle an Funktionen wie effiziente Zufallsalgorithmen und mathematische Funktionen aus den unterschiedlichten Bereichen der Statistik und numerischen Berechnung, welche alle für NumPy Arrays Optimiert sind. Im folgenden wollen wir den Umgang mit NumPy Arrays lernen. \n", + "\n", + "__Für dieses Notebook schauen Sie bitte in die [NumPy Docs](https://numpy.org/doc/stable/reference/index.html)!!!__ Dort sind alle Funktionen beschrieben die wir hier bearbeiten und noch mehr!\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "ee26bbc0-d6a6-4721-b371-5cade59879ea", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-d2be4b14819d46e9", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "# Was ist Matplotlib\n", + "\n", + "Matplotlib ist eine Python Bibliothek zum (interaktiven) Visualisieren von Daten. Die Bibliothek intergiert sich super mit anderen viel Benutzten Python Bibliotheken wie NumPy. Der Vorteil in Kombination mit Jupyter besteht in der direkten Ausgabe eines Plots auf dem Bildschirm.\n", + "\n", + "__Nutzen Sie für diese Aufgabe gerne die [Matplotlib Reference](https://matplotlib.org/stable/users/index.html)__\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "8f6a28a6-9ef0-4f80-9432-80375cf3876b", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-b8d545ee5d6cabe7", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "Das gesamte Internet importiert NumPy mit dem Kürzel `np` & das pyplot Objekt mit `plt`.\n", + "\n", + "Um uns diesen ungeschriebenen Gesetz anzuschließen importieren wir in nächster Zelle NumPy als np:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "20dc6e2f-9b96-4f0c-85a8-8763e6722ce8", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-3d1fe74859052932", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "markdown", + "id": "57f719db-3269-49e2-acd2-a676911c0470", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-39e898b8ebe45728", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "---" + ] + }, + { + "cell_type": "markdown", + "id": "9e008318-4d2a-4244-ac91-63d7b8806491", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-b910cff04746aa1d", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "# Was ist ein Array?\n", + "\n", + "Ein Array ist eine kontinuierliche Datenstrucktur. Dabei werden die Daten in Reihe im Arbeitsspeicher hinterlegt, vergleichbar mit der Python Liste.\n", + "\n", + "## Erstellen von Arrays\n", + "\n", + "Alle folgenden Beispiele finden Sie im [Beginners Guide](https://numpy.org/doc/stable/user/absolute_beginners.html).\n", + "\n", + "Für unser erstes Beispiel erstellen wir aus einer Python liste ein [NumPy Array](https://numpy.org/doc/stable/reference/arrays.html)." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "b44876d4-2376-4651-b489-9708a02f86bd", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-1adaa95f01483572", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arr = np.array([1,2,3,4,5])\n", + "arr" + ] + }, + { + "cell_type": "markdown", + "id": "a08e52ec-5148-4304-93da-064369cab9f8", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-ea5067ebbb1c99bc", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "Der Zugriff auf Elemente des Arrays erfolgt analog zu Pythons Liste:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "68679f58-495f-483e-a394-0cb3016dd488", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-cb73ac88e9fa5d93", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(5)" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arr[4]" + ] + }, + { + "cell_type": "markdown", + "id": "3f9f7d47-b9d6-47b2-85e3-bdb015cc72d8", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-ec0a814ecfda8547", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "NumPy Arrays sind n-dimensional, heißt Arrays in NumPy können aus geschachtelten Listen bestehen. Beispiel für ein 2-Dimensionales Array:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "04452b0d-ca06-4dd8-9b6a-47aa00b38011", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-ff72c8352626ac82", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3, 4, 5],\n", + " [6, 7, 8, 9, 8],\n", + " [7, 6, 5, 4, 3]])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arr = np.array(\n", + " [\n", + " [1,2,3,4,5],\n", + " [6,7,8,9,8],\n", + " [7,6,5,4,3],\n", + " ])\n", + "arr" + ] + }, + { + "cell_type": "markdown", + "id": "a4d10e8e-6856-4f14-a18c-b4d0d4cfee96", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-413fcd639649e39a", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "Diese Datenstrucktur wird Allgemein auch Matrix gennant. Der Zugriff auf ein Element einer Matrix folgt nach dem Prinzip \"Spalte->Reihe\". Die erste Spalte ist demnach:" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9539a428-4cb1-426e-9ff0-bb10f9e5dd75", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-c7a59ce293c8e402", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arr[0]" + ] + }, + { + "cell_type": "markdown", + "id": "eb7b82f2-c8ba-4336-b3f9-505d89010e3b", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-fb0cf79581b45e5e", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "Der zugriff auf ein einzelnes element erfolgt dann analog:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "c940ad92-43b4-4783-be50-687b2be51541", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-2f107dba2b747fbb", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(5)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arr[0][4]" + ] + }, + { + "cell_type": "markdown", + "id": "37cd7d69-9a6f-4136-95bc-3470ea512f45", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-617d777cf3216789", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "Oder mit der NumPys eigener Syntax `arr[, ]`" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "630ba433-c2e5-4faf-980a-ae34e57d470a", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-3e1e7323c57088ad", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(5)" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arr[0, 4]" + ] + }, + { + "cell_type": "markdown", + "id": "2b1ad36a-eeec-410f-82f1-768bb134accd", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-62701cdd045c7c4c", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Platzreservierung\n", + "\n", + "Falls bekannt ist wie viele Elemente ein Array im späteren Programmverlauf haben soll, bietet einem NumPy die möglichkeit diesen Platz im speicher gewissermaßen zu reservieren.\n", + "Hierfür gibt es einige Funktionen.\n", + "\n", + "### Ones\n", + "\n", + "1 Dimensionales NumPy Array der größe 10 mit 1 gefüllt:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "1da0eee9-4aa6-4a2e-91ab-7f9110ba5961", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-d3aeedf2a30a9b30", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.ones(10)" + ] + }, + { + "cell_type": "markdown", + "id": "dec9de1d-0415-4ce1-8182-cdf5f50cb8cd", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-6e683d4afe40b7ff", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "### Zeros\n", + "\n", + "Analog dazu mit 0 gefüllt:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "22b81912-0f2b-4ea6-b085-938e8f835daa", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-450f40270416767a", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.zeros(10)" + ] + }, + { + "cell_type": "markdown", + "id": "794bfa8c-2c62-4d13-b2cf-65165b9f66d8", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-ef1e55c1165e2de5", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "### Empty\n", + "\n", + "Analog mit zufälligen Werten (bzw. Werte die bereits an der Speicherstelle waren, meistens 0):" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "5bede573-fda6-4065-bc05-2238cdcd7dc5", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-896e48c096be9062", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.empty(10)" + ] + }, + { + "cell_type": "markdown", + "id": "f8543f2c-37a1-45c7-9e6f-387126d2e0c4", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-947ed3289815694d", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "### Arange\n", + "\n", + "Analog dazu die `arange` Funktion (die Paramter sind die selben wie bei der Python `range` Funktion):" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "57a83964-bf61-4db8-8358-d415d92e49bb", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-5329dd48e6129b33", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.arange(10)" + ] + }, + { + "cell_type": "markdown", + "id": "14461c48-a442-41d8-a9dc-bd411beb6b14", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-299417e99c41e05f", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "### Linspace\n", + "\n", + "Um später mit Matplotlib besser arbeiten zu können hat Numpy die [linspace](https://numpy.org/doc/stable/reference/generated/numpy.linspace.html#numpy-linspace) Funktion. Welche die Werte von einem Start und End Punkt Linear berechnet, zusätzlich kann noch die Anzahl der Elemete mit dem `num` Parameter angegeben werden:" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "1defeafc-b02a-4e84-a1d3-30878fc69071", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-036bdec449f35dc5", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0. , 2.5, 5. , 7.5, 10. ])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linspace(0,10, num=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "72416872-9e66-4ff8-88ad-9244b6e67827", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-9ac9d3f215fc0237", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + }, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 400. , 466.66666667, 533.33333333, 600. ,\n", + " 666.66666667, 733.33333333, 800. , 866.66666667,\n", + " 933.33333333, 1000. ])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linspace(400, 1000, num=10)" + ] + }, + { + "cell_type": "markdown", + "id": "53cd285e-fe83-4c8b-9ac5-ee65db57107d", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-522faf35a6c76300", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Aufgabe\n", + "\n", + "*1 Punkt*\n", + "\n", + "Erstellen Sie ein NumPy Array, welches 6 Nullen reserviert und speichern Sie das Array in der Variablen `only_zeros`. " + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "8f64d227-64cc-4b26-b076-b9ea3db3d798", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-176f6befb5f45c58", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "only_zeros = None\n", + "# BEGIN SOLUTION\n", + "only_zeros = np.zeros(6)\n", + "# END SOLUTION" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "ca435e4c-e686-4e64-b796-6f6884708ce3", + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-8ad1e3a41d459d55", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0. 0. 0. 0. 0. 0.]\n" + ] + } + ], + "source": [ + "print(only_zeros)\n", + "\n", + "# Check i length is correct\n", + "assert len(only_zeros) == 6\n", + "\n", + "# Check if every element contains a zero\n", + "for el in only_zeros:\n", + " assert el == 0" + ] + }, + { + "cell_type": "markdown", + "id": "07012ea7-35b0-4e24-83d4-5732853761bd", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-0108e88f3110e70f", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Aufgabe\n", + "\n", + "*1 Punkt*\n", + "\n", + "Erstellen Sie ein NumPy Array mit 11 Elementen mittels `linspace`, Dabei soll der Startwert = -4 und der Endwert = 17 sein. Speichern Sie das Ergbniss in der Variablen `x_scale`. " + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "41f68397-24db-44d8-a2cf-4e7aec431b57", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-3231ee937ba8ab7a", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "x_scale = None\n", + "# BEGIN SOLUTION\n", + "x_scale = np.linspace(-4, 17, num=11)\n", + "# END SOLUTION" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "2439440f-f8f6-4ee1-ae2b-3bca19992675", + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-e5d66ef7599f7b91", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[-4. -1.9 0.2 2.3 4.4 6.5 8.6 10.7 12.8 14.9 17. ]\n" + ] + } + ], + "source": [ + "# Hier werden ihre Lösungen getestet\n", + "print(x_scale)\n", + "\n", + "# Check if length is correct\n", + "assert len(x_scale) == 11\n", + "### BEGIN HIDDEN TESTS\n", + "s = np.linspace(-4, 17, num=11)\n", + "### END HIDDEN TESTS\n", + "\n", + "# Test if elements are correct\n", + "for el1, el2 in zip(x_scale, s):\n", + " assert el1 == el2" + ] + }, + { + "cell_type": "markdown", + "id": "dfdb02ea-44b4-4368-9b46-235ca1dca667", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-5d8e19cc802e33a4", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "---" + ] + }, + { + "cell_type": "markdown", + "id": "9276ba6e-30a0-4803-ace7-14147cd214ee", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-30de8243b097dfdc", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "# First plot\n", + "\n", + "Wie dem [Getting Started](https://matplotlib.org/stable/users/getting_started/index.html#getting-started) Beispiel zu entnehmen, wollen wir einmal die Sinus Funktion plotten.\n", + "\n", + "Dazu brauchen wir zwei Attribute:\n", + "1. Die x-Skala - Dies kann die Länge eines Datensets sein, oder ein allegemeiner Linespace. Aufjedenfall eine Liste bzw. Array.\n", + "2. Die y-Skala - Im Allgemeinen die Werte eines zu plottenden Datensets. Aufjedenfall auch eine Liste bzw. Array.\n", + "\n", + "Plotten wir im Folgenden die Sinus Funktion. Eine der schönen Eigenschaften der Sinus Funktion ist, dass diese sich nach dem Intervall $[0...2\\pi]$ wiederholt. Daher enthält die x-Skala einen linespace von $[0...2\\pi]$. Als Wert für $\\pi$ wird die NumPy Konstante [np.pi](https://numpy.org/doc/stable/reference/constants.html#numpy.pi) verwendet.\n", + "\n", + "Auf der y-Skala plotten wir im folgenden das zuvor berechnete Array mit den Sinus Werten. Die Hierfür verwendete Funktion ist [np.sin](https://numpy.org/doc/stable/reference/generated/numpy.sin.html). \n", + "\n", + "Das `plt` Objekt hat mehrere Funktionen die in einer bestimmten Reihenfolge aufgerufen werden müssen. Dabei können zuerst mehrere plots mit [plt.plot](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html) definiert werden. Zum Schluss wird zur Ausgabe [plt.show](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html) aufgerufen." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "63f7bd92-7a44-4fe0-b03e-d13b1374be1c", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-2eaf77b2d04abff1", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x = np.linspace(0, 2*np.pi, num=200) # Definiere einen linearen Bereich von 0 bis 2pi\n", + "y = np.sin(x) # Berechne den Sinus mit den Werten von x\n", + "\n", + "plt.plot(x, y) # Setze für die X-Achse x und für die Y-Achse y\n", + "plt.show() # Zeige den Plot" + ] + }, + { + "cell_type": "markdown", + "id": "9dc5f266-8956-431d-aa8e-cb33afc8fc34", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-1dd3b7172bc39b59", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "# Zwei Funktionen \n", + "\n", + "Wie bereits zuvor erwähnt lässt sich `plt.plot` mehr als einmal aufrufen. Wollen wir im folgenden den Kosinus mittels [np.cos](https://numpy.org/doc/stable/reference/generated/numpy.cos.html) dazu plotten. Dafür werden die Werte aus dem bereits definierten x wiederverwendet. Die Variabelen `y1 = np.sin(x)` & `y2 = np.cos(x)` enthälten die jeweiligen y werte. " + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "7f63b65d-875d-4ee2-998b-fc6f39935ab0", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-2e9cc2ce95f1e20e", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "y1 = np.sin(x) # Sinus Werte mittels x berechnen\n", + "y2 = np.cos(x) # Kosinus Werte mittels x berechnen\n", + "\n", + "plt.plot(x, y1) # Plotte den Sinus\n", + "plt.plot(x, y2) # Plotte den Kosinus\n", + "\n", + "plt.show() # Zeige das Diagramm" + ] + }, + { + "cell_type": "markdown", + "id": "c1e5749a-8f46-41ae-817a-19e5103a9a7a", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-d1d50ca1d203ac29", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Aufgabe - Erster eigener Plot Square Root\n", + "\n", + "Analog zu voheriger Erklärung Plotten Sie im folgenden die Funktion Square Root Mathematisch definiert als $f(x) = \\sqrt x; \\quad x \\geq 0$.\n", + "\n", + "Gehen Sie dabei wie folgt vor:\n", + "1. Definieren Sie einen **geeigneten** [Linespace](https://numpy.org/doc/stable/reference/generated/numpy.linspace.html#numpy-linspace) für die Zahlenraum 0...100. (Tipp: Achten Sie auf die Definition! Die Wurzel ist nur für positive Zahlen definiert.)\n", + "2. Berechnen Sie mittels der Funktion [np.sqrt](https://numpy.org/doc/stable/reference/generated/numpy.sqrt.html#numpy.sqrt) die Werte für die Wurzel.\n", + "3. Plotten Sie das Ergebnis" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "c36ff699-9c30-448c-9d97-0a75e00888fd", + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-bae73642cf0a866a", + "locked": false, + "points": 3, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# BEGIN SOLUTION\n", + "xs = np.linspace(0, 100, num=200)\n", + "ys = np.sqrt(xs)\n", + "plt.plot(xs, ys)\n", + "plt.show()\n", + "# END SOLUTION" + ] + }, + { + "cell_type": "markdown", + "id": "a98f7855-0bca-4769-aaf5-fa27f0404b23", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-998243908406c7d4", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "# Styling\n", + "\n", + "Da bei mehreren Plots der Überblick schnell verloren geht beschäftigen wir uns im folgenden mit dem Styling. Dabei gehen wir im Schnelldurchlauf durch alle Parameter.\n", + "\n", + "Die Grundlage für alle folgenden Plots werden in nächster Zelle gesetzt." + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "dd074404-20be-450e-a187-d992c9d804cf", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-a86ddac229c0bbbb", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [], + "source": [ + "x = np.linspace(0, 2*np.pi, num=200)\n", + "s = np.sin(x)\n", + "c = np.cos(x)" + ] + }, + { + "cell_type": "markdown", + "id": "7e541a27-5fb0-48a5-98a6-175842a59f31", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-e27c575962048d7b", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Farbe ändern\n", + "\n", + "Die Standard Farbe für den ersten Plot ist immer Blau. Um die Farbe zu verändern wird `plt.plot` der Parameter `color` übergeben. Dieser erwartet einen String. Für eine genauere Erläuterung lesen Sie die Dokumentation zu [Specifying color](https://matplotlib.org/stable/users/explain/colors/colors.html). Für dieses Notebook werden die Beispiele mit den \"Single Character Shorthands\" (Aus der Dokumentation zu entnehmen) ausgestattet.\n", + "\n", + "Plotten wir den Sinus nun in Rot:" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "01d03aa6-22c3-4843-8cf0-33155b78740e", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-1ec79feac73af81f", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, s, color='r') # Plot mit der Farbe Rot\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "e229b04c-8688-4457-982c-7a3f27c4254c", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-6d559d4604922bd9", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Titel für den Plot setzen\n", + "\n", + "Dafür wird [plt.title](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.title.html) der Paramter wird als String übergeben:" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "ca46e07c-2f69-40cb-b58b-5278e13a048e", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-106786a4fca81b67", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, s)\n", + "plt.title(\"Sinus Plot\") # Titel Setzen\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "6d0a0200-ac39-467c-a3e8-66e6a3ba3818", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-8d7bed3592e18530", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Legende und Labels\n", + "\n", + "Um eine Legende anzuzeigen muss vor `plt.show` die Funktion [plt.legend](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.legend.html) aufgerufen werden. Damit dies Wirkung zeigt braucht muss jeder Plot mit dem Parameter `label` (als String) ausgezeichnet werden. Plotten wir im Folgenden den Sinus und Kosinus mit entsprechenden Labels." + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "4d58a327-a11e-408b-a998-ef03c7cfaf87", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-b1d037b9a275622c", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, s, label=\"Sinus\") # Plotte Sinus mit label Sinus\n", + "plt.plot(x, c, label=\"Kosinus\") # Plotte Kosinus mit label Kosinus\n", + "plt.legend() # Füge die Legende ein\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "fb03ce2f-5639-402a-9b32-0b351113b5d6", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-63bbc82ff5e6892a", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Linestyle\n", + "\n", + "Die letze wichtige Eigenschaft ist das Setzen eines Linestyles. Dazu wird `plt.plot` der parameter `linestyle` als String übergeben. Entnehmen Sie die verschiednen Linestyles bitte der Dokumentation zu [Linestyles](https://matplotlib.org/stable/gallery/lines_bars_and_markers/linestyles.html).\n", + "\n", + "Sinus als `dashed` line:" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "90be449a-1d18-416f-b22b-782081d1b007", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-402e40ea2ceafc35", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, s, linestyle=\"dashed\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "b465a6e5-06ab-4fc0-8238-f4f05593a9d1", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-88e04ff7645c08cd", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Aufgabe - Multiplot\n", + "\n", + "*8 Punkte*\n", + "\n", + "In der nächsten Aufgabe wollen wir gleich zwei Funktionen Plotten. $f(x) = \\sqrt x; x \\geq 0$ und $g(x) = x^2$.\n", + "\n", + "Gehen Sie dabei wie folgt vor:\n", + "1. Definieren Sie einen geeigneten [Linespace](https://numpy.org/doc/stable/reference/generated/numpy.linspace.html#numpy-linspace) für die Zahlenraum 0...3. (Tipp: Achten Sie auf die Definition! Die Wurzel ist nur für positive Zahlen definiert.)\n", + "2. Berechnen Sie mittels der Funktion [np.sqrt](https://numpy.org/doc/stable/reference/generated/numpy.sqrt.html#numpy.sqrt) die Werte für die Wurzel.\n", + "3. Berechnen Sie mittels der Funktion [np.square](https://numpy.org/doc/stable/reference/generated/numpy.square.html#numpy-square) die Werte für die Quadrat Zahlen\n", + "4. Geben Sie den beiden Plots die Farben Grün & Rot. Nutzen Sie gerne die [Color Shorthands](https://matplotlib.org/stable/users/explain/colors/colors.html) aus der Dokumentation.\n", + "5. Plotten Sie die Square Funktion mit dem Linestyle `dashdot`, wie der Dokumentation zu entnehmen [Linestyles](https://matplotlib.org/stable/gallery/lines_bars_and_markers/linestyles.html)\n", + "6. Geben Sie den beiden Plots angemessene Labels.\n", + "7. Fügen Sie die Legende hinzu.\n", + "8. Plotten Sie das Ergebnis." + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "41c07973-1717-48f1-94a5-c6930b0089ec", + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-6bb6ab1d60fffde5", + "locked": false, + "points": 8, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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C19dXd7tmzZrik08+KfO9Pb5+HpoxY4Zo0aKF3nN88cUXesu0bdtWTJgwQQghRGJiogAgfvrpJ939ly5dEgBEfHx8qa9b1ueQiKiq7by6U/ddtOvaLqnj6Cnv+/txZjFiYeoGDx6M5ORkbNmyBb1798a+ffsQFhaGFStWAADi4+MRGBiImjVr6h4THh5u8Ouo1WrMnj0boaGh8PT0hLOzM2JjY3Hr1i295Vq3bq13+9y5c9i7d69udMXZ2RnBwcEAgGvXrpX7mgcPHkRcXJxu8vDwqHBeR0dH1K9fX3fb398f6enpAID09HQkJyfjpZdeqvDzPUmlUiE5ORkdO3bUm9+xY0fEx8frzWvevLlejocZiIhMxb2Cexjz+xgAwHvt3jPZi4w9i1nsvJk7LdfgxyhtlbrfI5tEIndaLuQy/R5144MbzxtNx97eHj169ECPHj0wffp0jB07FjNmzMAbb7xRocfL5dps4rErnhYX6x+zPG/ePCxatAgLFy5EaGgonJycEBUVhaKiIr3lnJyc9G7n5uZiwIABmDt37lOv+/BLtix169aFu7u7wVkBwM7OTu+2TCbTPcbBwaHc1zW2x7M83LNao9FUawYiovJM2DYBKbkpaOzVGF92/1LqOJVmFsXCSeH07IXKYSu3ha3i6bf6vM9bnpCQEN2OmU2aNEFSUhJSUlJ0X+THjh3TW75GjRoAgJSUFN2oQFxcnN4yhw8fxqBBg/Daa68B0H4xJiQkICQkpNwsYWFh2LRpE+rUqQNb2+f/T16RrM/i4uKCOnXqYM+ePejatWupy9jZ2UGtVpf5HK6urqhZsyYOHz6Mzp076+YfPnwY7dq1MygPEZGU1l5ci3WX1sFGZoOVkSvhaOcodaRK46aQ55SZmYlu3bph1apVOH/+PBITE7FhwwZ89dVXGDRoEACge/fuaNSoEUaPHo1z587h4MGD+OSTT/Sep0GDBggMDMTMmTNx9epVbNu2DfPnz9dbpmHDhti1axeOHDmC+Ph4jBs3Dmlpac/MOHHiRNy7dw8jRozAyZMnce3aNcTGxmLMmDHlfnGXpSJZK2LmzJmYP38+/v3vf+Pq1as4c+YMvv32W939D4tHamoqsrKySn2Ojz76CHPnzsW6detw5coVTJ06FXFxcfjggw8MzkNEJIUidRGm/Fe7Y/unnT5F21ptJU70fFgsnpOzszPat2+Pb775Bp06dUKzZs0wffp0vP322/jPf7R788rlcsTExKCgoADt2rXD2LFj8cUXX+g9j52dHdasWYM///wTzZs3x9y5c/H555/rLfPpp58iLCwMvXr1QpcuXeDn54eIiIhnZnz4r3q1Wo2ePXsiNDQUUVFRcHd3123WMERFslbE6NGjsXDhQnz33Xdo2rQp+vfvr3c0x/z587Fr1y4EBgaiVatWpT7H+++/j8mTJ+PDDz9EaGgodu7ciS1btqBhw4YG5yEikoLCRoFdo3bhzZZv4pMXP3n2A0ycTDy+obwaqFQquLm5ITs7W+/ES4D2cMrExETUrVsX9vb21RlLEjKZDDExMRUqB1R9rO1zSERUEeV9fz+OIxZEREQSOJd6Dodvme+lH8rCYkFERFTN8ovzMWLTCHRa0QlrL66VOo5RmcVRIZaqmrdCERGRidAIDdrWaousB1lme76KsrBYEBERVTNnhTOiI6KRnpcOb0dvqeMYFTeFEBERVZO8ojy90WofJx8J01QNg4qFWq3G9OnTUbduXTg4OKB+/fqYPXu20Yf0uYmApMTPHxFVBSEEhm0chgFrBiA9z3IvKWDQppC5c+fi+++/R3R0NJo2bYpTp05hzJgxcHNzw/vvv//cYWxsbAAARUVF1X7KZ6KH8vPzATx9SnIiouex5NQSbLu6DUobJdJy0yxytAIwsFgcOXIEgwYNQr9+/QBoz4y4Zs2apy7bXekwtrZwdHRERkYG7OzsKnXyJqLKEkIgPz8f6enpcHd31xVdIqLnFZ8Rjw//+yEA4MvuXyLUN1TiRFXHoGLRoUMHLF26FAkJCWjUqBHOnTuHQ4cOYcGCBWU+prCwEIWFhbrbKpWqzGVlMhn8/f2RmJiImzdvGhKNyGjc3d3h5+cndQwishBF6iKM/G0kCkoK0LN+T7zf/vlH+E2ZQcVi6tSpUKlUCA4Oho2NDdRqNb744guMHDmyzMfMmTMHs2bNqvBrKBQKNGzY8KkrdhJVBzs7O45UEJFRTf9jOs6mnoWXgxdWDFrx1JW2LY1BxWL9+vVYvXo1fv31VzRt2hRxcXGIiopCzZo1MXr06FIfM23aNEyePFl3W6VSITAwsNzXkcvlPJUyERGZvb2JezHvyDwAwE8Df4K/i7/EiaqeQcXio48+wtSpUzF8+HAAQGhoKG7evIk5c+aUWSyUSiWUSuXzJyUiIjIjWQVZeH3z6xAQeDvsbUQER0gdqVoYNB6Tn5//1A6VNjY20Gg0Rg1FRERkzoQQGLd1HG6rbqOhZ0N80+sbqSNVG4NGLAYMGIAvvvgCtWvXRtOmTXH27FksWLAAb775ZlXlIyIiMjvR56Kx4fIG2Mptsfrl1XBSOEkdqdoYVCy+/fZbTJ8+HRMmTEB6ejpq1qyJcePG4Z///GdV5SMiIjIrCZkJmLR9EgBgVpdZaFurrcSJqpdMVPNpBit6PXciIiJzNGDNAGxN2Iqudbpi16hdsJFbxpFmFf3+tuxjXoiIiKrZ8kHL8XqL17EycqXFlApD8OqmRERERuTt6I3oiGipY0iGIxZERETPKSUnBavOr+JFDMERCyIioueiERqMihmFPYl78Ne9vzCzy0ypI0mKIxZERETPQQiBbnW7wVXpiuHNhksdR3I8KoSIiMgI7hXcg6eDp9QxqgyPCiEiIqpCOYU5KCgu0N225FJhCBYLIiIiAwkh8M7Wd9Dup3a4nHFZ6jgmhTtvEhERGSj6XDTWXlwLG5kNVIUqqeOYFI5YEBERGeDK3SuYuH0iAGB219l4IeAFiROZFhYLIiKiCiosKcTwTcORX5yPbnW74R8d/yF1JJPDYkFERFRBU3dPRVxqHLwdva32lN3PwmJBRERUAdsStmHh8YUAgBWDVqCmS01pA5koFgsiIqJnuK26jdGbRwMAPmj/Afo16idxItPFYkFERFSOEk0JRmwagcyCTIT5h+HL7l9KHcmksVgQERGV4597/4lDtw7BVemK9a+sh72tvdSRTBqLBRERURl2/rUTcw7NAQD8NOAn1PesL3Ei08diQUREVIb/nPgPAGBCmwkY0nSIxGnMA8+8SUREVIbfhv2Gfx//Nya1myR1FLPBYkFERFQGhY0CUzpMkTqGWeGmECIiosf899p/MW33NJRoSqSOYpY4YkFERPQ/qkIVXvvtNWTkZ8DL0YujFZXAEQsiIqL/cVW6YnHfxegU1In7VVSSTAghqvMFVSoV3NzckJ2dDVdX1+p8aSIiogoRQkAmk0kdw6RU9PubIxZERGT1jt8+jpScFN1tlorKY7EgIiKrlpKTgoFrB6LlDy1xIe2C1HHMHosFERFZLbVGjVd/exXpeenwdfJFA88GUkcyeywWRERktT7b/xn23dgHJzsnbBiyAQ52DlJHMnssFkREZJV2XduF2QdmAwB+6P8DGns3ljiRZWCxICIiq5OUnYQRm0ZAQODtsLcxsvlIqSNZDBYLIiKyKkXqIgzZMASZBZkI8w/Dv/v8W+pIFoXFgoiIrMqU/07B8TvH4W7vjo1DNsLe1l7qSBaFxYKIiKzG2otr8e2JbwEAKyNXoq5HXYkTWR4WCyIisgrxGfEYu2UsAGDa36ahf6P+EieyTCwWRERk8XKLcvHKhleQV5yHrnW64rOun0kdyWLx6qZERGQVQn1CkVWQhTWD18BWzq+/qsI1S0REFs9Z4Yw1g9cgOScZvs6+UsexaNwUQkREFis5JxkPL+Itk8lQy7WWxIksH4sFERFZpLv5d/HCTy/glQ2vQFWokjqO1WCxICIii3Q06ShSc1N5xdJqxn0siIjIIg1oPAAHxxyEo50jXJWuUsexGiwWRERkUYQQkMlkAID2Ae0lTmN9uCmEiIgsxq3sWwj/ORxxqXFSR7FaLBZERGQRHpQ8wOD1g3H8znG8t+M93dEgVL1YLIiIyOwJITBh2wScSj4FTwdPrIxcqdscQtWLxYKIiMzeD6d/wPK45ZDL5Fg7eC3quNeROpLVYrEgIiKzdjTpKN7f8T4A4F/d/oUe9XtInMi6sVgQEZHZSslJweD1g1GsKcYrIa/gHx3/IXUkq8diQUREZqlIXYQhG4YgJTcFITVCsGzgMu5XYQJYLIiIyCxNjp2Mw0mH4ap0RcywGLgoXaSORGCxICIiMxQdF43FJxcDAFa/vBqNvBpJnIgeYrEgIiKzcjr5NMZtHQcAmNF5Bvo36i9xInociwUREZmVxScXo1BdiP6N+uOfnf8pdRx6Aq8VQkREZuXHAT+isVdjjGszDnIZ/31salgsiIjIrNjIbfDx3z6WOgaVgVWPiIhM3vpL6/Hu1ndRWFIodRR6Bo5YEBGRSbtXcA9jt4xFTlEOmvk0w6R2k6SOROXgiAUREZk0TwdPrHtlHYaEDMG7bd6VOg49g0xU83VlVSoV3NzckJ2dDVdX1+p8aSIiIqqkin5/c8SCiIhM0vwj83E967rUMchALBZERGRylp9djim7pqDdj+1wr+Ce1HHIACwWRERkUo4mHcW727T7UkxqNwmeDp4SJyJDsFgQEZHJuK26jch1kShSFyEyOJJn1jRDBheLO3fu4LXXXoOXlxccHBwQGhqKU6dOVUU2IiKyIgXFBYhYG4G0vDSE+oTil8hfeGZNM2TQeSyysrLQsWNHdO3aFTt27ECNGjVw9epVeHh4VFU+IiKyAkIIjP2/sTidchpeDl74ffjvcFY4Sx2LKsGgYjF37lwEBgZi+fLlunl169Y1eigiIrIu847Mw68XfoWt3BYbh25EXQ9+t5grg8aYtmzZgjZt2mDIkCHw8fFBq1at8OOPP5b7mMLCQqhUKr2JiIjooe1Xt2Pq7qkAgEW9F6FLnS7SBqLnYlCxuH79Or7//ns0bNgQsbGxGD9+PN5//31ER0eX+Zg5c+bAzc1NNwUGBj53aCIisgx/3v0TIzaNgIDAO2HvYHyb8VJHoudk0Jk3FQoF2rRpgyNHjujmvf/++zh58iSOHj1a6mMKCwtRWPjoojEqlQqBgYE88yYRkZW7/+A+2v/UHgmZCXix9ovY/fpuKGwUUseiMlTJmTf9/f0REhKiN69Jkya4detWmY9RKpVwdXXVm4iIiL448AUSMhNQ2602Ng7dyFJhIQzaebNjx464cuWK3ryEhAQEBQUZNRQREVm+2d1mI6coB+Naj4OPk4/UcchIDCoWf//739GhQwf861//wtChQ3HixAksXboUS5curap8RERkoext7bGk/xKpY5CRGbQppG3btoiJicGaNWvQrFkzzJ49GwsXLsTIkSOrKh8REVmQ/Tf2Y9ruadAIjdRRqIoYNGIBAP3790f//v2rIgsREVmw+w/uY/D6wcgsyISPkw/+Hv53qSNRFeC5UomIqFq427tjUe9F6BTUCe+2eVfqOFRFDDrc1BgqergKERFZJiEEZDKZ1DHIQFVyuCkREZEhhBCYf2Q+UnJSdPNYKiwbiwUREVWZb098iym7piD853DkFeVJHYeqAYsFERFViR1Xd+DvsdodNCe1mwQnhZPEiag6sFgQEZHRXUy/iGEbh0EjNHir1Vv4MPxDqSNRNWGxICIio0rPS0f/X/sjpygHnYM647t+33G/CivCYkFEREbzoOQBItZG4Gb2TTTwbIBNQzfxGiBWhsWCiIiMQgiBsVvG4ujto3C3d8fWEVvh5egldSyqZiwWRERkFF8c/AKrL6yGrdwWG4dsRGPvxlJHIgmwWBAR0XNbd3Edpu+dDgD4ru93eKneSxInIqmwWBAR0XM5dOsQRm8eDQD4+wt/x9ut35Y4EUmJxYKIiCpNCIEZ+2agUF2IiOAIzOsxT+pIJDEWCyIiqjSZTIaYYTH4MPxDrH55NWzkNlJHIokZfNl0IiKixy8k5qp0xdc9v5Y4EZkKjlgQEZFBNEKDEZtGYN7heajmC2STGWCxICIig2xN2Ip1l9bhkz8+QUJmgtRxyMRwUwgRERlkYOOBWNhrITwdPHmuCnoKiwURERnsgxc+kDoCmShuCiEiomeKS41DxNoI3H9wX+ooZOJYLIiIqFxJ2Uno92s//H7ld0zdPVXqOGTiWCyIiKhM9x/cR5/VfZCck4yQGiH4svuXUkciE8diQUREpXp4CfRLGZfg7+yP7a9uh7u9u9SxyMSxWBAR0VM0QoPXY17H/pv74aJwwY6ROxDkHiR1LDIDLBZERKRHCIHJsZOx4fIG2MntEDMsBi38Wkgdi8wEiwUREelZcHQBFh1fBABYEbGCl0Ang7BYEBGRzpoLazBl1xQAwLwe8/Bq6KsSJyJzw2JBREQAgD8S/8DozaMBAB+0/wAfhn8ocSIyRywWRESEc6nnELkuEsWaYgwJGYIFvRborl5KZAie0puIiGBvaw9PB0+09GuJXyJ/gVzGf3dS5bBYEBERGns3xtG3jkJpo4S9rb3UcciMsZISEVmp/OJ8HLp1SHfbz9kPHg4eEiYiS8BiQURkhYrVxRi6YSi6RnfFuovrpI5DFoTFgojICgkIuCpdYSu3RYBrgNRxyIJwHwsiIiuksFFg1curcCn9EkJ9Q6WOQxaEIxZERFZk9/Xd0AgNAEAuk7NUkNGxWBARWYnlZ5ejx8oeeHXTq1Br1FLHIQvFYkFEZAW2XNmCsf83FgAQ5BYEG7mNxInIUrFYEBFZuAM3D2DYxmHQCA3GtByDL7t/KXUksmAsFkREFuxc6jkMWDMAD0oeYGDjgVg6YClP1U1VisWCiMhCXc+6jl6rekFVqMKLtV/E2sFrYSvnwYBUtVgsiIgs0B3VHXT/pTvS8tLQ3Lc5tozYAgc7B6ljkRVgsSAisjB38++i56qeSLyfiPoe9bFz5E6427tLHYusBIsFEZEFURWq0HtVb1zOuIxaLrWw+/Xd8HfxlzoWWREWCyIiC1FQXIABawbgdMppeDt6Y/fru1HHvY7UscjKsFgQEVmIi+kXcSr5FFyVroh9LRbB3sFSRyIrxN2DiYgsRNtabbFr1C5ohAZh/mFSxyErxWJBRGTGhBBIyU1BTZeaAIAOgR0kTkTWjptCiIjMlBACU/47BS2XtMTZlLNSxyECwGJBRGS28ovzse/mPmTkZ+BC+gWp4xAB4KYQIiKz5aRwwh+v/4HYa7EY2nSo1HGIAHDEgojI7FzOuKz73c3ejaWCTAqLBRGRGYmOi0az75phwdEFUkchKhWLBRGRmVhzYQ3e3PImBARu3r8JIYTUkYiewmJBRGQGfov/DaNiRkEjNHgn7B0s7L2Qlz8nk8RiQURk4rYlbMPwjcOhFmqMbjEa3/f/nqWCTBaLBRGRCdt1bRcGrx+MYk0xhjUdhp8H/gy5jH+6yXTx00lEZKL239iPQWsHoVBdiIjgCKyMXAkbuY3UsYjKxWJBRGSCjiYdRb9f+6GgpAB9G/bF2sFrYWdjJ3UsomdisSAiMjGnk0+j9+reyCvOw0t1X8KmoZugtFVKHYuoQlgsiIhMyJmUM+ixsgdUhSq8WPtF/D78d9jb2ksdi6jCWCyIiEzIyTsnkfUgC+EB4dj66lY4KZykjkRkEF4rhIjIhIxrMw4eDh7o3aA3XJWuUschMhhHLIiIJHYh7QKyCrJ0t4c2HcpSQWbruYrFl19+CZlMhqioKCPFISKyLnGpcegS3QXdV3bHvYJ7Uschem6VLhYnT57EDz/8gObNmxszDxGRVbGV28JGZgM7uR1sZDxHBZm/ShWL3NxcjBw5Ej/++CM8PDyMnYmIyGo082mGg2MOIva1WLjZu0kdh+i5VapYTJw4Ef369UP37t2fuWxhYSFUKpXeRERkzc6nnce+G/t0txt7N2apIIth8FEha9euxZkzZ3Dy5MkKLT9nzhzMmjXL4GBERJbofNp5dIvuhvzifPwx+g+8EPCC1JGIjMqgEYukpCR88MEHWL16NeztK3bClmnTpiE7O1s3JSUlVSooEZG5O5tyFt2iuyGzIBPNfJoh2DtY6khERicTQoiKLrx582ZERkbCxubRDkZqtRoymQxyuRyFhYV695VGpVLBzc0N2dnZcHXl4VREZB1O3DmBXqt64f6D+2hXqx1iX4uFu7271LGIKqyi398GbQp56aWXcOHCBb15Y8aMQXBwMD7++ONnlgoiImt0JOkIeq/qjZyiHHQM7IjtI7fzPBVksQwqFi4uLmjWrJnePCcnJ3h5eT01n4iItJc+7/drP+QV56FLnS74vxH/B2eFs9SxiKoMz7xJRFRFdl/fjT6r+yCvOA896vXAtle3sVSQxXvua4Xs27fPCDGIiCzLjqs7ELkuEoXqQvRt2Bebhm7iVUrJKnDEgojIyLZc2YKIdREoVBdiUONB+G3obywVZDV4dVMiIiM6cecEBq8fjBJNCYaEDMHql1fDzsZO6lhE1YbFgojIiFr7t8awpsMgIBAdEQ1bOf/MknXhJ56IyAiEEJDJZLCR22BFxArIoP2dyNpwHwsiouc0/8h8jIoZBY3QAPjfFUtZKshKccSCiOg5XM28iql7pqJEU4JXQl5BRHCE1JGIJMViQUT0HBp6NcSqyFW4nnWdpYIILBZERAZTa9RIy0tDTZeaAIBhzYZJnIjIdHAfCyIiAxSpizBi0wh0+LkDbqtuSx2HyORwxIKIqIIKigsweP1g7PhrB+zkdjifdh4BrgFSxyIyKSwWREQVoCpUYeCagdh/cz8cbB0QMywGvRr0kjoWkclhsSAieoaMvAz0/bUvTiWfgqvSFVtHbMWLQS9KHYvIJLFYEBGV4+b9m+i5qicSMhPg5eCF2Ndi0bpma6ljEZksFgsiojJcSr+Enqt6IjknGbXdaiP2tVgEewdLHYvIpLFYEBGV4kjSEfT/tT+yHmQhpEYIYl+L5Y6aRBXAw02JiJ6w/ep2dP+lO7IeZCE8IBwHxxxkqSCqII5YEBE9ZudfOzFwzUCohRp9G/bFhiEb4GjnKHUsIrPBYkFE9JgOgR0Q6huKZj7NsGzgMtjZ2EkdicissFgQkdV7eMlzAHBVumLv6L1wVbpCLuPWYiJD8f8aIrJqxepijN0yFl8f+Vo3z93enaWCqJI4YkFEVu3/Ev4Py+KWwUZmg8jgSNT3rC91JCKzxmJBRFbt5SYvY9rfpiE8IJylgsgIWCyIyOokZCbAx8kH7vbuAIB/vfQvaQMRWRBuRCQiq3L41mGE/xyOl9e9jCJ1kdRxiCwOiwURWY3f4n9D95Xdca/gHvKK85BblCt1JCKLw2JBRFbh2+Pf4pX1r+BByQMMaDQAf7z+BzwdPKWORWRxWCyIyKJphAb/2PUPvL/zfQgIvNv6Xfw27Dc4KZykjkZkkbjzJhFZrAclDzDm9zFYe3EtAGDOS3PwccePdSfDIiLjY7EgIouUkZeBiHUROJJ0BLZyWywbuAyjWoySOhaRxWOxICKLE58Rj36/9kPi/US427tj09BN6Fa3m9SxiKwCiwURWZQ91/dg8PrByC7MRj2Petj26jYEewdLHYvIarBYEJHFKNGUYOL2icguzEaHwA7YPGwzajjVkDoWkVXhUSFEZDFs5bbYPHwz3gl7B3te38NSQSQBFgsiMmv5xfnYfX237nawdzB+GPAD7G3tJUxFZL1YLIjIbKkKVega3RV9VvfBnut7pI5DRGCxICIz5qJwQX2P+nBVusLOxk7qOEQE7rxJRGZIIzSQy+SQyWRYNmgZknOSUc+jntSxiAgcsSAiMyKEwOz9szFkwxBohAYAYG9rz1JBZEI4YkFEZiG/OB9vbH4DGy5vAADsuLoD/Rr1kzgVET2JxYKITF5SdhIGrR2Es6lnYSe3w3f9vmOpIDJRLBZEZNKOJh1F5LpIpOWlwdvRG78N/Q0vBr0odSwiKgOLBRGZrOi4aLyz9R0UqYvQ3Lc5fh/+O+q415E6FhGVgztvEpHJKdGUYMp/p+CN399AkboIkcGROPzmYZYKIjPAEQsiMil38+9ixKYRurNpTu80HTO7zIRcxn8HEZkDFgsiMhlnU84icl0kbmbfhJOdE5YNWoahTYdKHYuIDMBiQUQmoURTgqEbh+Jm9k3U96iPzcM3o5lPM6ljEZGBOLZIRCbBVm6LVZGrEBkciZNvn2SpIDJTLBZEJJm03DTE/hWru90+oD1+G/YbPBw8JExFRM+DxYKIJHHj/g2ELQ1D5LpIxKXGSR2HiIyExYKIJBHoGojmvs0R5B4EB1sHqeMQkZFw500iqjb5xfmQQQYHOwfYyG2wZvAayGVyuCpdpY5GREbCEQsiqhZXM68i/OdwTNo+STfP3d6dpYLIwnDEgoiq3MbLG/Hm728ipygHqbmpSM1NhZ+zn9SxiKgKcMSCiKpMkboIUTujMGTDEOQU5eDF2i/i7LizLBVEFowjFkRUJW5l38KwjcNw7PYxAMDHHT/G590+h62cf3aILBn/Dycio9v510689ttryCzIhLu9O36J+AUDGg+QOhYRVQMWCyIyGrVGjVn7Z+HzA59DQKC1f2tsGLIBdT3qSh2NiKoJiwURGcVt1W289ttr2H9zPwBgfJvxWNBrAext7SVORkTVicWCiJ7bgZsH8PK6l5FZkAlnhTOW9FuCkc1HSh2LiCTAYkFEzy3ILQhqoUaYfxjWDl6Lhl4NpY5ERBJhsSCiSrlXcA+eDp4AgCD3IOwdvRdNvJtAaauUOBkRSYnnsSAig60+vxp1FtbB9qvbdfNa+rVkqSAiFgsiMtzxO8eRU5SD5XHLpY5CRCaGm0KIqEI0QgO5TPtvka96fIVg72CMaz1O4lREZGoMGrGYM2cO2rZtCxcXF/j4+CAiIgJXrlypqmxEZALUGjW+PPQlXvrlJZRoSgAA9rb2mNB2AmzkNhKnIyJTY1Cx2L9/PyZOnIhjx45h165dKC4uRs+ePZGXl1dV+YhIQjfv30TX6K6Ytmca9t3Yh5j4GKkjEZGJkwkhRGUfnJGRAR8fH+zfvx+dOnWq0GNUKhXc3NyQnZ0NV1deLpnIFAkh8OuFXzFh+wSoClVwVjjj2z7fYnSL0ZDJZFLHIyIJVPT7+7n2scjOzgYAeHp6lrlMYWEhCgsL9YIRkenKKsjChO0TsPbiWgBAeEA4VkauRH3P+hInIyJzUOmjQjQaDaKiotCxY0c0a9aszOXmzJkDNzc33RQYGFjZlySiKrY3cS+aL2mOtRfXwkZmg8+6fIYDYw6wVBBRhVV6U8j48eOxY8cOHDp0CAEBAWUuV9qIRWBgIDeFEJmQwpJCfPrHp5h/dD4EBBp4NsCqyFVoH9Be6mhEZCKqdFPIpEmTsHXrVhw4cKDcUgEASqUSSiVPmkNkqk4nn8bozaNxKeMSAODtsLexoNcCOCucJU5GRObIoGIhhMB7772HmJgY7Nu3D3Xr8lLIROZs+9XtGLhmINRCjRqONbB0wFJEBEdIHYuIzJhBxWLixIn49ddf8fvvv8PFxQWpqakAADc3Nzg4OFRJQCKqOp2DOiPIPQit/Vtjcd/FqOFUQ+pIRGTmDNrHoqzDzJYvX4433nijQs/Bw02JpFOiKcHq86sxqsUo3Vk0M/Mz4eXoJXEyIjJ1VbKPxXOc8oKIJCaEQI+VPbDvxj6oClV4r/17AMBSQURGxYuQEVkJmUyGISFD4G7vzk0eRFRlnuvMm5XBTSFE1ed82nnkFuWiQ2AHANoLid3NvwsfJx+JkxGR0QgB5OUB9+4BmZnaqVs3QG7csYNqOfMmEZmmByUP8PmBzzH38FwEuAbg4viLcFI4QS6Ts1QQmbKSEv2C8PhU1vzMTKCoSP957t4FvKTZzMliQWRhDt06hLFbxuJKpvbKwy39WqKgpABOCieJkxFZESGAnJxnF4InS8P/LpVRKQqFtkx4egIFBcZ7LwZisSCyEKpCFabtnobvTn0HAPB18sXivosxOGSwxMmIzFxRUfnloLT77t0Diosr/5ru7tqS8OTk6Vn6fC8vwMkJMIGLBLJYEFmAbQnb8O62d3FbdRsA8GbLN/F1z6/h4eAhcTIiE/PggXYzQVlTaQUhJ6fyr2dvX7FS8PgyHh6Arfl+PZtvciJCel46onZGYc3FNQCAeh71sLT/UrxU7yWJkxFVg+Ji7Rd/eUXh7l0gI+PR73l5lXstmUz7hf+sUvDkPEdH475nM8BiQWSGNEKDpaeXYtqeabj/4D7kMjkmvzAZs7rOgqOd9f0hIwug0QD375ddCEqb7t+v3GvZ2gLe3k9P5ZUGNzfAxsaY79hisVgQmRkhBHqt6oXd13cDAFr5tcLSAUvRpmYbiZMR/c/DHRefNZLw5CYIjcbw15LJtCMFpRWFsiY3N5PYF8FSsVgQmRmZTIY+Dfrg+O3j+Lzb55jQdgJs5fxfmaqQEIBKpR1BSE/X/izv94yMpw9/rChX1/JLQY0a+rc9PDiSYGJ4giwiEyeEwMbLG+Hj5IPOdToD0F7zIyMvA/4u/hKnI7P0sChUpCSkp2tHFCpTFOzt9YvAk6WgtE0RCoXx3y8ZBU+QRWQhvj/1PSZun4hGXo1w/t3zUNoqYSu3ZamgR4TQnv+gIiXh4e+VORTSyQnw8dEWhIfT47efvM8Kd1wkFgsikzcydCTmHZmH4U2HSx2FqtODB9oikJb26OfD3x9Oj296qExRcHYuvRCUVRYcHIz/PsnisFgQmZCHmz1i/ozB6pdXQyaTwc3eDX9O/BNKW6XU8eh5PNyhsbSiUNrvKpXhr+HiUvHRBBYFqiIsFkQm4nzaeby/433sv7kfABAZHIkhTYcAAEuFqdJotEczVKQopKdrRyEMYWcH+PpqS4Gv76Pp8aLweGGwt6+a90lkABYLIoll5mfin3v/iSWnl0AjNLC3tcfUjlPRr1E/qaNZp5ISbQlITX12Wbh7F1CrDXt+Jyf9kvB4aXjyd3d3HhZJZofFgkgiao0aS08vxad7P8W9gnsAgCEhQzCvxzwEuQdJnM7CPNy5MTVVf0pJeXpeRoZ2eUN4ej67JDz86cSLwZFlY7EgksDexL2Iio3C+bTzAIBQn1D8u8+/0aVOF2mDmZuiIu3IQWkF4cl5hmyGkMu1mxb8/J5dGGrU4CGSRI9hsSCqRvEZ8fjH7n9ga8JWAICHvQdmd52NcW3G8SRXDwmhvf5DWSMKj8+7d8+w53Z11ZYFf3/tzyenh/O9vXnSJaJK4l8yomoghMD7O97H96e+h1qoYSu3xbjW4zCryyx4OXpJHa96CKG9tkNycvlTSophh07a2j5dDEorC76+PK8CUTVgsSCqBjKZDGqhhlqoEREcgS9f+hKNvRtLHcs4Hh5G+azCkJwMFBZW/Hk9PSs2uuDhod10QUQmgaf0JqoCao0aq86vQpuabdDUpykA7SXO/7z7JzoFdZI4nQHy8vRHEsoqDIZcitrTE6hZs+zJ3187uqDkIbZEpoSn9CaS0NTdU/H10a/Rp0EfbB+5HQDg4+QDHycfiZP9j0ajPVTy9m3gzh3tz4fTnTvaKTnZsJM0ubmVXxYe/uS5FogsGosFkZEUq4thZ2MHABjXZhyiz0Wja52u0AgN5LJqHKovKdHu2Ph4USitOFT0olJOTkCtWqUXhcdv8zBKIgKLBdFzO5d6Dp/88Qk8HTzxS+QvAIAGng1w6++3YG9r5H+dP3igHUl4sig8fjs1VTsi8SwymXaTQ0DAo6lWLe0UEPCoNLi4GPc9EJFFY7EgqqSEzATM2DcDay+uBQDYye3wVY+v4OfsBwCGlwq1Wrsfw61bQFKS9ufj0+3b2s0XFWFrqy0FT5aGx2/7+2tPGU1EZEQsFkQGSspOwmf7P8PyuOVQC+3pnIc3G47PunymKxWlys5+uiw8XiDu3NFuxngWe3v9glBaafDx4ZESRCQJFguiCkrOScZXh7/CklNLUKjWHjbZv1F/fN71c7TwbKItBpcOlF0eKrIjpK2tthgEBgK1az+aAgO1U0CA9vBKXj+CiEwUiwXRM9xW3caX+7/AT3HLUKjR7vDYWVMb/7oTjA67soCP+mn3e6jIkdteXk8Xhsdv+/nxjI9EZNZYLIgA7RESSUnAjRu6Ken2JcyxOYqfa6ai6H/f9X+7CczYD7x0/RZkuKX/HEpl6WXh4RQQwCMniMjisViQdSgufqo46KbERO1mjCdGHBLqAt+P1v7e+QYw46gCXWzqQxZcF+hdB6jzvykoSPuzRg1uoiAiq8diQZYjJwe4dk1/un5d+/PWLe1RF+W45qfAhaY1EKFoDtSpg25BQfi740EMatAfnce/zOJARFQBLBZkPoTQHo75eGF4fHrWoZhK5aNRhrp1H/1epw7OOKnQ9rfecLJT4UbUKng6eEIGYAE+rvK3RURkSVgsyLSUlAA3bwIJCU+POly/DhQUlP94b2+gfn3tVK/eo9/r19fuGPm/QzCFELiVfQtB7kEAgFZCoOnBpqjlWgvZD7Lh6eBZ1e+UiMgisVhQ9Xs48pCQoJ2uXn30+7Vr5V8yWy7X7tPwZGl4ePsZF7ZTa9TYFL8JXx3+Cjfu38DNqJtwUjhBJpPhyFtH4KxwNvKbJSKyLiwWVHWysh4VhidLRHlXw1QqgQYNgIYNnx55CAqq1NkiC4oLEH0uGl8f+RrXsq4BABxsHXAq+RQ61+kMACwVRERGwGJBz0et1m6iiI9/ND0sEOXt82Bjo93PoWFDoFEj/SkgwGhnjUzOScZ3J7/DD6d/wN18bR5PB0+81+49TGo3Cd6O3kZ5HSIi0mKxoIopLNQWhvh44PJl/RJRWFj242rVelQYHi8RdesCCkWVxT1x5wQWHV+E9ZfWo0SjPU12bbfa+DD8Q7zV6i04KXg+CSKiqsBiQfpycvRHHx4WievXy75ipoMD0Lgx0KSJdmrcWFseGjQAnKtv80Kxuhib4jdh0fFFOHb7mG7+32r/DVHtozAoeBBs5fzIExFVJf6VtVbFxdrRhgsX9KcbN8p+jLv7o/LQpAkQEqL9GRRkEhe8WnV+Fd7c8iYAQGGjwPBmw/FB+w8Q5h8mcTIiIuvBYmHphNCeVfLJAhEfrz2NdWn8/B6VhscnPz+TOUGUEAJHko4grzgPPev3BAAMazYM847Mw9CmQ/Fum3fLv9IoERFVCRYLS1JUpN1scfYscOYMcO4ccPGi9uiM0ri4AM2aAaGh+pOn6Z/DYdX5VXh98+to4t0ElyZcgkwmg6Odo+53IiKSBouFucrLA86f15aIh0Xi4sXSRyFsbLT7PYSGAs2bPyoQQUEmMwJRHiEETiafREFxge7Q0IGNB6KGYw2EB4QjvzhftzMmSwURkbRYLMxBfr62OJw4of155gxw5UrpO1O6uwOtWmmnli21RSI4WHtuCDNz/8F9rL24FktPL8XZ1LMI8w/D6XdOAwDc7N1we/JtKGyq7sgSIiIyHIuFqdFotPs/nDgBHD+unS5cKP0CWv7+j0pEWJj2Z506ZjEKURa1Ro1d13dhRdwKbP5zMwrV2kNZlTZKNK3RFAXFBXCwcwAAlgoiIhPEYiG15ORHJeLECeDkSe0hn0/y9wfatwfatHlUIvwsZ+fE+Ix4RJ+LxsrzK5Gck6yb38ynGca0HIPRLUbDy9FLwoRERFQRLBbVSQjtIZ4HDz6aEhOfXs7RUVsg2rfXTu3aac9GacYjEaXJKsjC2otrEX0uGsfvHNfN93TwxMjQkXij5Rto5deK+00QEZkRFouqpFZrj8w4eBA4cAA4dAhIT9dfRiYDmjZ9VCLat9ce6mlr2f9phBBosaQFklRJAAAbmQ36NuyLN1q+gX4N+0Fpa377hBAREYuFcQmhPdxz927ttH//05s1lErtCMSLL2qnDh2eeUVOc1esLsa2q9uw4+oOfN//e8hlcshkMgxsPBAHbh7AmJZj8Groq/B19pU6KhERPSeZEEJU5wuqVCq4ubkhOzsbrpbwhXrnDrBnD7Brl7ZMpKbq3+/qCnTs+KhItG1rlkdoPI/CkkL4fu2L7MJs7H9jPzoFddLN58gEEZF5qOj3N0csDKXRaHew3LpVO8XF6d9vbw906gR07w689BLQooX2PBJWoKC4ALuu70LMnzGIz4jH0beOQiaTQWmrxPg241GsKUYtl1q65VkqiIgsD4tFReTmakck/u//gG3b9PeTkMm0O1r26KEtE+Hh2nJhJbIKsrA1YSs2X9mMnX/tRH5xvu6+0ymn0aZmGwDAnO5zpIpIRETViMWiLLm52hGJdeuAHTv0Lw3u4gL07g0MGAD06QN4e0uXUwK3Vbfx+5+/I+bPGOy/uV93WXIACHILQkRwBCKDI9HSr6V0IYmISBIsFo8rLtaOSKxerf1ZUPDovnr1tEViwADtvhIK6zk5kxAC+2/ux46rO7Djrx24kH5B7/5Qn1C9MsHDQ4mIrBeLBaA9kmP5cuCXX/Q3c9SvDwwbBgwdqj01thV9Yd4ruAdPB+3FyGQyGSZsm4D4u/Ha25ChQ2AHRAZHYlDwIDTwbCBlVCIiMiHWWyxKSoCYGOCbb4CjRx/N9/UFRo0CRozQnt3SisoEAKTnpaNbdDck3k9E5j8yYW+r3V9kZOhIXMm8gj4N+qBn/Z48CyYREZXK+opFbq52dOKbbx6d9dLGBujfH3jzTe0+E3Z20masBvnF+Th86zD23tgLW7ktPuv6GQCghmMNZD3IwoOSB4hLjcMLAS8AAD7p9ImUcYmIyExYT7HIzQUWLAAWLgSysrTzvLyASZOAd9+1qOtulCa/OB8n7pzA3sS92HtjL47dPoZiTTEAbZmY1WUWZDIZZDIZYobFoIFnA92mECIiooqy/GKh0QA//gjMmAGkpWnnNWgATJ4MjB6tvS6HhRFC4Gb2TRxNOoojSUdw9PZRxKXGQS30r5Aa6BqIrnW7omudrijRlMDORjtS065WOyliExGRBbDsYnH5MjB27KN9KBo0AD7/HHjlFYs6aZUQQnckxsk7JzFo7SCk5KY8tVwtl1roFNQJ3ep2Q9c6XVHPox6P4CAiIqOy3GLx88/AhAlAURHg7Ax88QUwfrxF7T/x85mfseDYArzS5BXM6joLABDkHoSU3BTYym3Ryq8VOgR2QHhAODoEdkCgW6DEiYmIyNJZXrFQq4GPPwbmz9fe7tsXWLIECDSvL1WN0ODG/Ru4nHEZF9Mv4mzqWZxJOYP1r6xHK/9WAIAidREuZ1zGSbeTusf5OPng2FvH0Ny3ORzsHKSKT0REVsryisUnnzwqFTNmaCcTHu5Xa9S4nnUdlzMu43LGZVzKuITLGZfx590/UVBS8NTyZ1LO6IpF/0b9EeQehDD/ML1l2ge0r5bsRERET6pUsVi8eDHmzZuH1NRUtGjRAt9++y3atTOBHf5SU4FFi7S/L1sGjBkjbZ7/KSwpxF/3/kJ+cT7a1mqrm9/ux3Y4n3YeherCUh+ntFEi2DsYTWo0QSu/VgjzD9NdewMAAt0CuXmDiIhMisHFYt26dZg8eTKWLFmC9u3bY+HChejVqxeuXLkCHx+fqshYcfPmAQ8eAC+8ALzxRrW8ZGFJIVJyU3BHdQd3cu7ofvZv1B9d6nQBAOy9sRd9VvdBqE8ozo8//+ix6kIUqgvhYOuAJjWaIKRGCEK8Q7Q/a4Sgnkc92MgtZydTIiKyfAYXiwULFuDtt9/GmP+NBixZsgTbtm3DsmXLMHXqVKMHrLD0dOD777W/V3Lzh1qjxv0H91GkLoK/i79ufnRcNK5nXUdmQSbu5t9FZkEmMvIycCfnDu7m3y31udyUbrpiUd+jPtyUbnC3d9dbZmXkSrgoXBDkHgS5TG5wXiIiIlNjULEoKirC6dOnMW3aNN08uVyO7t274+jjp8V+TGFhIQofuzKoSqWqZNRn+PprzGpXgLR6Pigp3oSS39dDLdQo0ZToTYUlhcgrzkNuUS7yivLwUYeP8HbrtwEAx+8cR8dlHdHQsyES3kvQPfXC4wsRlxpX5ksrbZSo6VITtVxroZaLdgoPDNfd38CzAbI+znrq0M7mvs2Nuw6IiIgkZlCxuHv3LtRqNXx9ffXm+/r64s8//yz1MXPmzMGsWbMqn7BiwYDFi7HqLeAvr3TgzE8VfmhaXprud2eFMwDtWSof93LwywgPCIeXgxe8HL3g5eAFb0dvXZHwdPAs93wQPFcEERFZiyo/KmTatGmYPHmy7rZKpUKgsQ/99PQEfvkFk/Z9ifud+8FGbgvbMiY7uR2cFc5wUjjBWeGMuu51dU/TzKcZiqcXw1auv1qmd55u3LxEREQWyqBi4e3tDRsbG6SlpenNT0tLg18Z19pQKpVQKpWVT1gRcjkweDA+GDz4+Z5GJue+DkRERM/BoG9RhUKB1q1bY8+ePbp5Go0Ge/bsQXh4eDmPJCIiImtg8KaQyZMnY/To0WjTpg3atWuHhQsXIi8vT3eUCBEREVkvg4vFsGHDkJGRgX/+859ITU1Fy5YtsXPnzqd26CQiIiLrIxNCiOp8QZVKBTc3N2RnZ8PV1bU6X5qIiIgqqaLf39xTkYiIiIyGxYKIiIiMhsWCiIiIjIbFgoiIiIyGxYKIiIiMhsWCiIiIjIbFgoiIiIyGxYKIiIiMhsWCiIiIjKbKL5v+pIcn+lSpVNX90kRERFRJD7+3n3XC7movFjk5OQCAwMDA6n5pIiIiek45OTlwc3Mr8/5qv1aIRqNBcnIyXFxcIJPJjPa8KpUKgYGBSEpK4jVInoHrquK4rgzD9VVxXFcVx3VVcVW5roQQyMnJQc2aNSGXl70nRbWPWMjlcgQEBFTZ87u6uvKDV0FcVxXHdWUYrq+K47qqOK6riquqdVXeSMVD3HmTiIiIjIbFgoiIiIzGYoqFUqnEjBkzoFQqpY5i8riuKo7ryjBcXxXHdVVxXFcVZwrrqtp33iQiIiLLZTEjFkRERCQ9FgsiIiIyGhYLIiIiMhoWCyIiIjIasyoWixcvRp06dWBvb4/27dvjxIkT5S6/YcMGBAcHw97eHqGhodi+fXs1JZWeIetqxYoVkMlkepO9vX01ppXOgQMHMGDAANSsWRMymQybN29+5mP27duHsLAwKJVKNGjQACtWrKjynKbA0HW1b9++pz5XMpkMqamp1RNYQnPmzEHbtm3h4uICHx8fRERE4MqVK898nDX+zarMurLWv1nff/89mjdvrjv5VXh4OHbs2FHuY6T4TJlNsVi3bh0mT56MGTNm4MyZM2jRogV69eqF9PT0Upc/cuQIRowYgbfeegtnz55FREQEIiIicPHixWpOXv0MXVeA9ixtKSkpuunmzZvVmFg6eXl5aNGiBRYvXlyh5RMTE9GvXz907doVcXFxiIqKwtixYxEbG1vFSaVn6Lp66MqVK3qfLR8fnypKaDr279+PiRMn4tixY9i1axeKi4vRs2dP5OXllfkYa/2bVZl1BVjn36yAgAB8+eWXOH36NE6dOoVu3bph0KBBuHTpUqnLS/aZEmaiXbt2YuLEibrbarVa1KxZU8yZM6fU5YcOHSr69eunN699+/Zi3LhxVZrTFBi6rpYvXy7c3NyqKZ3pAiBiYmLKXeYf//iHaNq0qd68YcOGiV69elVhMtNTkXW1d+9eAUBkZWVVSyZTlp6eLgCI/fv3l7mMNf/NelxF1hX/Zj3i4eEhfvrpp1Lvk+ozZRYjFkVFRTh9+jS6d++umyeXy9G9e3ccPXq01MccPXpUb3kA6NWrV5nLW4rKrCsAyM3NRVBQEAIDA8ttwNbOWj9Xz6Nly5bw9/dHjx49cPjwYanjSCI7OxsA4OnpWeYy/GxpVWRdAfybpVarsXbtWuTl5SE8PLzUZaT6TJlFsbh79y7UajV8fX315vv6+pa5vTY1NdWg5S1FZdZV48aNsWzZMvz+++9YtWoVNBoNOnTogNu3b1dHZLNS1udKpVKhoKBAolSmyd/fH0uWLMGmTZuwadMmBAYGokuXLjhz5ozU0aqVRqNBVFQUOnbsiGbNmpW5nLX+zXpcRdeVNf/NunDhApydnaFUKvHuu+8iJiYGISEhpS4r1Weq2q9uSqYnPDxcr/F26NABTZo0wQ8//IDZs2dLmIzMWePGjdG4cWPd7Q4dOuDatWv45ptvsHLlSgmTVa+JEyfi4sWLOHTokNRRTF5F15U1/81q3Lgx4uLikJ2djY0bN2L06NHYv39/meVCCmYxYuHt7Q0bGxukpaXpzU9LS4Ofn1+pj/Hz8zNoeUtRmXX1JDs7O7Rq1Qp//fVXVUQ0a2V9rlxdXeHg4CBRKvPRrl07q/pcTZo0CVu3bsXevXsREBBQ7rLW+jfrIUPW1ZOs6W+WQqFAgwYN0Lp1a8yZMwctWrTAokWLSl1Wqs+UWRQLhUKB1q1bY8+ePbp5Go0Ge/bsKXPbUnh4uN7yALBr164yl7cUlVlXT1Kr1bhw4QL8/f2rKqbZstbPlbHExcVZxedKCIFJkyYhJiYGf/zxB+rWrfvMx1jrZ6sy6+pJ1vw3S6PRoLCwsNT7JPtMVemuoUa0du1aoVQqxYoVK8Tly5fFO++8I9zd3UVqaqoQQohRo0aJqVOn6pY/fPiwsLW1FV9//bWIj48XM2bMEHZ2duLChQtSvYVqY+i6mjVrloiNjRXXrl0Tp0+fFsOHDxf29vbi0qVLUr2FapOTkyPOnj0rzp49KwCIBQsWiLNnz4qbN28KIYSYOnWqGDVqlG7569evC0dHR/HRRx+J+Ph4sXjxYmFjYyN27twp1VuoNoauq2+++UZs3rxZXL16VVy4cEF88MEHQi6Xi927d0v1FqrN+PHjhZubm9i3b59ISUnRTfn5+bpl+DdLqzLrylr/Zk2dOlXs379fJCYmivPnz4upU6cKmUwm/vvf/wohTOczZTbFQgghvv32W1G7dm2hUChEu3btxLFjx3T3de7cWYwePVpv+fXr14tGjRoJhUIhmjZtKrZt21bNiaVjyLqKiorSLevr6yv69u0rzpw5I0Hq6vfwkMgnp4frZ/To0aJz585PPaZly5ZCoVCIevXqieXLl1d7bikYuq7mzp0r6tevL+zt7YWnp6fo0qWL+OOPP6QJX81KW08A9D4r/JulVZl1Za1/s958800RFBQkFAqFqFGjhnjppZd0pUII0/lM8bLpREREZDRmsY8FERERmQcWCyIiIjIaFgsiIiIyGhYLIiIiMhoWCyIiIjIaFgsiIiIyGhYLIiIiMhoWCyIiIjIaFgsiIiIyGhYLIiIiMhoWCyIiIjIaFgsiIiIymv8HBeQRHsC1GbsAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# BEGIN SOLUTION\n", + "xt = np.linspace(0, 3, num=200)\n", + "sqrt = np.sqrt(xt)\n", + "square = np.square(xt)\n", + "\n", + "plt.plot(xt, sqrt, color='r', label=\"Square Root\")\n", + "plt.plot(xt, square, color='g', label=\"Square Function\", linestyle=\"dashdot\")\n", + "plt.legend()\n", + "plt.show()\n", + "# END SOLUTION" + ] + }, + { + "cell_type": "markdown", + "id": "d33d372a-ed48-4a31-a1fc-4b325e910d27", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-6d0019ce99d7aacb", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "---" + ] + }, + { + "cell_type": "markdown", + "id": "7dd33f6a-1e5d-4c8f-8778-7820d13fa357", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-c7e6f6e837a94d41", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "# Warum Zufall?\n", + "\n", + "Für statistische Analysen jeglicher Art ist es wichtig seine Werkzeuge zu verstehen. Da nicht immer direkt ein Dataset vorliegt oder dieses zurzeit noch im Erstellungsprozess ist, gibt es die Möglichkeit die mathematischen und programmatischen Werzeuge zuvor an nachvollziebaren Zufallsdaten zu testen. Dabei wollen wir in dieser Übung lernen, was Zufall ist, wie Zufallsgeneratoren funktionieren und wie der Zufall auf bestimmte Art manipuliert werden kann.\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "6536feb0-7612-4bad-b797-3960ed3c832c", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-f387eeef09033ea3", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "# Was ist Zufall?\n", + "\n", + "Für Zufall gibt es viele Definitionen. Aber was genau ist Zufall? Das Würfeln eines Würfels zum Beispiel ist nicht zufällig. Jeder Würfelwurf kann vorhergesagt werden, vorausgesetzt, alle erforderlichen Daten sind vorhanden. Auch das Wetter ist nicht zufällig. Alle Ereignisse lassen sich vorhersagen, wenn genügend Daten vorhanden sind, das Problem ist nur, dass es nie genug Daten gibt. \n", + "\n", + "Jedes andere Beispiel kann mit der gleichen Argumentation als \"zufällig\" widerlegt werden. Daher werden diese Phänomene als pseudo-zufällig bezeichnet. \n", + "\n", + "Aber das nur am Rande. In der Physik gibt es ein Phänomen, das völlig unvorhersehbar ist. Wenn ein einzelnes Photon auf einen halbtransparenten Spiegel geschossen wird, kann __nie__ vorhergesagt werden, auf welchen der beiden Detektoren das Photon treffen wird. Diese Form der wirklich echten Zufalls wird von der Firma [ID Quntique](https://www.idquantique.com/random-number-generation/overview/) genutzt und verkauft Geräte, die das zuvor erklärte Quantenphänomen nutzen.\n", + "\n", + "Aber genug von der echten Koinzidenz und zurück zum Pseudo-Zufall und wie Computer damit umgehen.\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "73c86ab1-9f06-4dc5-861b-6558e8315bb3", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-fde25777024719e0", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "# Pseudo Randomness\n", + "\n", + "Zufallszahlen in Computern werden über Formeln berechnet. Einer dieser Generatoren ist der _Linear Congruent Generator (LCG)_, dessen mathematische Grundlage leicht verdaulich ist.\n", + "\n", + "$$ X_{n+1} = (aX_n + c) \\;mod\\; m; \\quad n \\geq 0 $$\n", + "\n", + "Wenn $ c = 0 $ dann nennt man den Generator auch _Multiplicative Congruent Generator (MCG)_.\n", + "\n", + "Die Werte haben folgenden nutzen in der Funktion:\n", + "\n", + "- $X_n$ ist der Startwert oder seed\n", + "- $X_{n+1}$ ist der folgewert der im nächsten schritt für $X_n$ eingesetzt wird\n", + "- $a$ ist der Vorfaktor vom Startwert dieser wird skaliert, deshalb wird er skalar gennant\n", + "- $c$ ist das hinzuaddierte Offset\n", + "- $m$ ist der Restklassenring oder auch Modulus genannt" + ] + }, + { + "cell_type": "markdown", + "id": "39b18b10-a831-4fbe-a50b-d8177108bca1", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-a1c6ad2b24a97f6b", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Aufgabe\n", + "\n", + "*6 Punkte*\n", + "\n", + "Schreibe einen _Linear Congruent Generator_ mit dem funktionsnamen `lcg`.\n", + "\n", + "- Nutze die oben gegebene Definition\n", + "- Checke auch das Werte nicht verwendet werden dürfen (Bsp. $n \\geq 0$)\n", + "- `lcg` muss ein unendlicher Generator sein" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "224134b7-6ab5-4438-ad46-6cb77261680c", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-d5c7ad13eb813b34", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# BEGIN SOLUTION\n", + "def lcg(seed: int, scalar: int, modulus: int, offset: int) -> int:\n", + " ''' \n", + " Linear Congruential Generators\n", + "\n", + " X(n+1) = (a X(n) + c) mod m; n >= 0\n", + "\n", + " m > 0; \n", + " 0 <= a < m;\n", + " c > 0; a > 0\n", + "\n", + " '''\n", + " assert modulus > 0, \"Modulus must be greater than 0\"\n", + " assert 0 <= scalar and scalar < modulus, \"Scalar must be in range 0 <= a < m\"\n", + "\n", + " while seed > 1:\n", + " seed = (scalar*seed+offset) % modulus\n", + " assert seed >= 0\n", + " yield seed\n", + "# END SOLUTION" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "853a70eb-7dd1-43b5-af99-ed1b3126846c", + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-35fbf31fbee439df", + "locked": true, + "points": 6, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Lcg using Cocktailshaker Numbers: 3089810780120156248\n", + "Correct should be: 3089810780120156248\n", + "\n", + "Lcg using Cocktailshaker Numbers: 8356396685252565260\n", + "Correct should be: 8356396685252565260\n", + "\n", + "Lcg using Cocktailshaker Numbers: 1921117399837525548\n", + "Correct should be: 1921117399837525548\n", + "\n", + "Lcg using Cocktailshaker Numbers: 14806858147081821235\n", + "Correct should be: 14806858147081821235\n", + "\n", + "Lcg using Cocktailshaker Numbers: 2557599628047639428\n", + "Correct should be: 2557599628047639428\n", + "\n", + "Lcg using Cocktailshaker Numbers: 16453652254840064460\n", + "Correct should be: 16453652254840064460\n", + "\n", + "Lcg using Cocktailshaker Numbers: 15995401842808378843\n", + "Correct should be: 15995401842808378843\n", + "\n", + "Lcg using Cocktailshaker Numbers: 681272290641816305\n", + "Correct should be: 681272290641816305\n", + "\n", + "Lcg using Cocktailshaker Numbers: 10955466795170118648\n", + "Correct should be: 10955466795170118648\n", + "\n", + "Lcg using Cocktailshaker Numbers: 13714992071537968180\n", + "Correct should be: 13714992071537968180\n", + "\n" + ] + } + ], + "source": [ + "# Hier werden ihre Lösungen getestet ...\n", + "\n", + "# Check if lcg is a properly defined\n", + "assert 'lcg' in dir()\n", + "\n", + "# Check if lcg is a generator\n", + "import types\n", + "assert isinstance(lcg(1,1,1,1), types.GeneratorType) # 1 Punkt\n", + "\n", + "# Using Cocktailshaker numbers :)\n", + "s = lcg(3935559000370003845, 3203021881815356449, 2**64-1, 11742185885288659963)\n", + "### BEGIN HIDDEN TESTS\n", + "def lcg_test(seed: int, scalar: int, modulus: int, offset: int) -> int:\n", + " assert modulus > 0, \"Modulus must be greater than 0\"\n", + " assert 0 <= scalar and scalar < modulus, \"Scalar must be in range 0 <= a < m\"\n", + "\n", + " while seed > 1:\n", + " seed = (scalar*seed+offset) % modulus\n", + " assert seed >= 0\n", + " yield seed\n", + "\n", + "t = lcg_test(3935559000370003845, 3203021881815356449, 2**64-1, 11742185885288659963)\n", + "### END HIDDEN TESTS\n", + "\n", + "# Check if Generator works\n", + "for _ in range(10):\n", + " stud = next(s)\n", + " instructor = next(t)\n", + " print(\"Lcg using Cocktailshaker Numbers:\", stud)\n", + " print(\"Correct should be:\", instructor, end='\\n\\n')\n", + " assert stud == instructor\n" + ] + }, + { + "cell_type": "markdown", + "id": "8e516bd4-c203-4b11-9880-31eabba13c2e", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-88eadd4386332f26", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "---\n", + "\n", + "# A Family of Better Random Number Generators\n", + "\n", + "
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\n", + " Melissa E. O’Neill\n", + "

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Linear Congruent Generators zeichnen sich durch ihre Stabilität und Geschwindigkeit als Hervorragende Zufallsgeneratoren. Doch 2014 gelang Melissa E. O'Neil ein neuer durchbruch in der Konzeption von Pseudozufallsgeneratoren. Das Problem mit existierenden Zufallsgeneratoren ist entweder ihre Stabilität (Wie vorhersehbar die Zufallszahlen sind) oder ihrer Geschwindigkeit (Wie lange der Zufallsgenerator braucht um die nächste Zufallszahl zu errechnen).

\n", + "

Ihr Durchbruch gelang indem Sie die Vorteile eines Linear Congruent Generators mit dem eines XorShift Generators verband. Dadurch erreichte Sie nicht nur eine Normalverteilung in den generierten Zufallszahlen (und eine damit einhergende Stabilität), Sie hatte auch eine Family von schnellen einfachen Algorithmen entwickeln. Diese nennen sich PCG - Permuted Congruential Generator.

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Die Implementierungsdetails lassen wir im nächsten Schritt aus, da diese sich nicht einfach in Python umzusetzen sind. Auf der Webseite pcg-random.org lassen sich implemtierungen für C & C++ finden. Als weiterführende Literatur ist PCG: A Family of Simple Fast Space-Efficient Statistically Good Algorithms for Random Number Generation - Melissa E. O’Neill als Literatur angegeben.

\n", + "
\n", + "
\n", + "\n", + "Zum Glück hat _Numpy_ eine Implementierung des _PCG_. Diese findet sich unter [Numpy PCG64](https://numpy.org/doc/stable/reference/random/index.html)" + ] + }, + { + "cell_type": "markdown", + "id": "81959fe2-2f2f-4f57-9360-4e96dc0674ba", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-3cfb52b705a8d147", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Aufgabe\n", + "\n", + "*6 Punkte*\n", + "\n", + "Plote die Zufallszahlen eines _Permuted Congruent Generators_ mittels NumPy & MatPlotLib.\n", + "\n", + "- Gegeben ist der Anfangszustand des Generators.\n", + "- Nutze die Dokumentation und rufe den `default_rng` aus dem `numpy.random` Modul, **20** mal auf speichere die Werte in der variablen `pcgs`. *(Tipp: Nutze ein NumPy Array)*\n", + "- Sortiere im nächsten Schritt die in `pcgs` gespeicherten Werte und speicher diese in `pcgs_sorted`\n", + "- Plotte sinnvoll beide Array, gestalte den Plott angemessen." + ] + }, + { + "cell_type": "code", + "execution_count": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "np.random.seed(42) # Setting a fixed start Value for the Generator\n", + "pcgs: np.array = None\n", + "pcgs_sorted: np.array = None\n", + "\n", + "# BEGIN SOLUTION\n", + "gen = np.random.default_rng()\n", + "pcgs = np.array([gen.random() for _ in range(20)])\n", + "pcgs_sorted = np.sort(pcgs)\n", + "\n", + "# Plot\n", + "plt.plot(np.arange(len(pcgs_sorted)), pcgs, color='r', label='PCGs')\n", + "plt.plot(np.arange(len(pcgs_sorted)), pcgs_sorted, color='g', label='Sortierte PCGs')\n", + "plt.title(\"PCG Random Numbers\")\n", + "plt.legend()\n", + "plt.show()\n", + "# END SOLUTION" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "91d763ff-71ac-4940-9cf8-54ca7ea6b8ca", + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-69197dfdc3015ec5", + "locked": true, + "points": 3, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "PCGs [0.83138478 0.46249136 0.44121926 0.42622691 0.42466013 0.3974171\n", + " 0.98723244 0.5836077 0.7404793 0.53513345 0.7691253 0.52569606\n", + " 0.87456503 0.78567245 0.44853762 0.95138405 0.65358711 0.33559832\n", + " 0.19727424 0.39672796]\n", + "Sorted PCGs [0.19727424 0.33559832 0.39672796 0.3974171 0.42466013 0.42622691\n", + " 0.44121926 0.44853762 0.46249136 0.52569606 0.53513345 0.5836077\n", + " 0.65358711 0.7404793 0.7691253 0.78567245 0.83138478 0.87456503\n", + " 0.95138405 0.98723244]\n" + ] + } + ], + "source": [ + "# Hier werden ihre Lösungen getestet ...\n", + "print(\"PCGs\", pcgs)\n", + "print(\"Sorted PCGs\", pcgs_sorted)\n", + "### BEGIN HIDDEN TESTS\n", + "np.random.seed(42)\n", + "test_gen = np.random.default_rng()\n", + "test_pcgs = np.array([gen.random() for _ in range(20)])\n", + "test_pcgs_sorted = np.sort(pcgs)\n", + "### END HIDDEN TESTS\n", + "\n", + "# Check if pcgs are correctly generated\n", + "assert test_pcgs.all() == pcgs.all()\n", + "\n", + "# Check if pcgs are correctly sorted\n", + "assert test_pcgs_sorted.all() == pcgs_sorted.all()\n", + "\n", + "# Plot is manually checked" + ] + }, + { + "cell_type": "markdown", + "id": "9283cd7a-b8a6-4090-84c3-da70e61b2d2e", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-486bea96505ad0a6", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "---\n", + "\n", + "# Plot Types\n", + "\n", + "Im folgenden Kapitel beschäftigen wir uns mit verschiedensten Plot typen." + ] + }, + { + "cell_type": "markdown", + "id": "8fe0a0f7-a836-4279-bc7c-e993004f97aa", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-79e43d78c9874975", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Line Plots\n", + "\n", + "Line Plots haben wir im voherigen Kapitel bereits kennengelernt. Diese können mittels `plt.plot` augerufen werden.\n", + "\n", + "Beispiel Sinus:" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "19b25d9b-0ee5-4eff-b290-8513f7948f50", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-b48b1eec8fe65537", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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zYMECuLi46I+AAH6E0hpkWcY/NxxHZa0WfYPdMC4qSHQkaiRJEt4a1R0udtY4nqvBsl3nRUciImpTRj3NZcWKFejRowf69evX5PGxY8fiwQcfRI8ePTBq1Chs2rQJBw4cwI4dO655nfj4eKjVav2RnZ3dBunN3w+HcrHrTBFsrBR4Z3RPKBT8aMqYeDnbYv7IbgCAT34/i3NF5YITERG1HYMWHA8PDyiVShQUFDR5vKCgAD4+Pjd8bkVFBdavX4/Jkyff9PuEhITAw8MD6enp1/y6SqWCs7Nzk4NuT2FZNd7YdAIAMCumEzp6OgpORNfycK/2GNzFE7VaHV796Tj3qiIii2HQgmNjY4PIyEgkJibqH9PpdEhMTER0dPQNn/vdd9+hpqYG48ePv+n3ycnJwaVLl+Dr63vbmal53tx0EuqqOtzh54wpg0JEx6HrkCQJrz/YHSorBfaeu4SfU/NERyIiahMG/4hq9uzZWL58OdasWYOTJ09i2rRpqKiowKRJkwAAcXFxiI+Pv+p5K1aswKhRo9CuXbsmj5eXl+PFF1/Evn37kJmZicTERDz00EMIDQ1FbGysoV8OAdibXoyNR/IgScA7j/Tkgn5GLrCdPZ4b0gkA8OavJ6CurBOciIjI8Ay+C+KYMWNQVFSEefPmIT8/HxEREUhISNAPPM7KyoJC0fQN8vTp09i9eze2bNly1fWUSiWOHj2KNWvWoLS0FH5+fhg6dCjeeOMNqFQqQ78ci1dbr8OrPzfsNTU+Kgg9/F0EJ6LmmDIoBBsO5yK9sBzvbT6Ftx7uIToSEZFBSbIFfiiv0Wjg4uICtVrN8TgttGTHObybcArtHGywbc5guNhbi45EzbTv/CWMXbYPkgT8MK0/N0IlIpPTkvdvfrZAzZZbWoWFjZs4/vP+riw3JubOkHZ4pHd7yDLwfxuOo55r4xCRGWPBoWZ7/Zc0VNVp0S/YHY/0bi86Dt2Cf97fFS52Dds4rEm6IDoOEZHBsOBQs2w/XYjNaQVQKiS8PuoObsdgojwcVXh5WBgA4OPfz6C4vEZwIiIiw2DBoZuqqdfitY1pAIBJ/YMR5sNxS6ZsTN8AdG/vjLLqenzYuAM8EZG5YcGhm1q1JxMXLlXCy0mFWfd1Fh2HbpNSIWH+yIbNONcfyMbxXLXgRERErY8Fh26oqKwGn25rWCH6pWFhcFQZfGUBagN9g90xMtwPsgz865c0rnBMRGaHBYdu6MMtp1FeU4+e/i54pBcHFpuT+OFhsLVW4EDmZWw6elF0HCKiVsWCQ9eVlqfGNwcbNiad90A3bqZpZvxc7TDt7lAAwIL/nkRVrVZwIiKi1sOCQ9ckyzJe/+UEZBl4oKcv+gS7i45EBvD3u0PQ3tUOeepqLN15TnQcIqJWw4JD17Q5rQD7M0qgslJg7vAw0XHIQGytlfjn/V0BAEt3nkNeaZXgRERErYMFh65SU6/F2/89CQCYelcI/N3sBSciQ7q/hw/6Bbujpl6HD7ecER2HiKhVsODQVVbvyURWScO08Gfu7ig6DhmYJEn454iGuzg/Hs7BiTyN4ERERLePBYeaKK2sxeLtDdPCX4ztAgdOC7cIEQGueKCnL2QZWPDbSdFxiIhuGwsONfGfHeegqa5HmI8THuntLzoOtaGXYsNgrZTwx9li7DpTJDoOEdFtYcEhvdzSKqzemwkAeHlYGJScFm5RAtvZ48k7gwEAC347Ba2Oi/8RkeliwSG9D7ecRm29DneGuGNwF0/RcUiAmfeGwsnWCicvarDhcK7oOEREt4wFhwAAJ/L+fEOLH96Vu4VbKDcHG0y/p2Hxvw+3nEZ1HRf/IyLTxIJDAID3Np+CLAMjevoiPMBVdBwSaGL/YLR3tcNFdTVW7skQHYeI6Jaw4BD2nivGjtNFsFJIeHFoF9FxSDBbayXmDG3YNX7pjnNQV9YJTkRE1HIsOBZOlmW889spAMC4qEAEezgITkTG4KGI9uji7QRNdT2W/cEtHIjI9LDgWLjNafk4mqOGg40SM4d0Eh2HjIRSIenv4qzcnYmishrBiYiIWoYFx4JpdbJ+af7JAzvAw1ElOBEZk/u6eSM8wBVVdVr94o9ERKaCBceC/XIkD2cLy+Fsa4XJg0JExyEjI0l/jsn6an8WcrkRJxGZEBYcC1Wn1eHfvzfcvfn73R3hYmctOBEZowGh7RAd0g61Wh0W/n5WdBwiomZjwbFQP6Tk4MKlSng42mDSgGDRcchISZKEf8Q23MX5/lAOzhWVC05ERNQ8LDgWqKZei4WJDf8anzY4FPY23FCTri8yyA0xXb2g1cn499YzouMQETULC44F+np/FvLU1fBxtsW4qEDRccgEzGkci7Pp6EWcyNMITkNEdHMsOBamqlaLT7c3rGsyc0gobK2VghORKejq64wHevoCAD5J5F0cIjJ+LDgWZm1SJorLaxDobo/H+wSIjkMm5PkhnSBJwOa0AqTlqUXHISK6IRYcC1JRU4/Pdp0HADw3pBOslfztp+br5O2EB3r6AQA+4YwqIjJyfIezIF/uu4CSiloEt7PHqAg/0XHIBD0/JBSSBGw5UYDjubyLQ0TGq00KzuLFixEcHAxbW1tERUUhOTn5uueuXr0akiQ1OWxtbZucI8sy5s2bB19fX9jZ2SEmJgZnz/JflDdSWVuPZY13b2bc2wlWvHtDtyDUywkjr9zFSeR/c0RkvAz+LvfNN99g9uzZmD9/Pg4dOoTw8HDExsaisLDwus9xdnbGxYsX9ceFCxeafP29997DwoULsXTpUuzfvx8ODg6IjY1FdXW1oV+OyVq3LwuXKmoRxLs3dJueaxyLs5V3cYjIiBm84Hz00UeYMmUKJk2ahG7dumHp0qWwt7fHypUrr/scSZLg4+OjP7y9vfVfk2UZH3/8MV555RU89NBD6NmzJ9auXYu8vDz89NNPhn45JqmqVovPdjXMnJp+Tyjv3tBtCfVyxIPhDSX5Y47FISIjZdB3utraWqSkpCAmJubPb6hQICYmBklJSdd9Xnl5OYKCghAQEICHHnoIaWlp+q9lZGQgPz+/yTVdXFwQFRV13WvW1NRAo9E0OSzJuv0XUFxeiwB3Ozzcq73oOGQGZt7bCQoJ+P0k7+IQkXEyaMEpLi6GVqttcgcGALy9vZGfn3/N53Tp0gUrV67Ezz//jC+//BI6nQ79+/dHTk4OAOif15JrLliwAC4uLvojIMBypkdX1WqxdGfD2JuZ93DmFLUO3sUhImNndO920dHRiIuLQ0REBO6++278+OOP8PT0xGeffXbL14yPj4dardYf2dnZrZjYuH2VnIXi8pqGuze9efeGWs/MxrE4v58swKl8y7orSkTGz6AFx8PDA0qlEgUFBU0eLygogI+PT7OuYW1tjV69eiE9PR0A9M9ryTVVKhWcnZ2bHJaguk6LpTsbx94MDuXdG2pVHT0dcX+PhtWNFzeujk1EZCwM+o5nY2ODyMhIJCYm6h/T6XRITExEdHR0s66h1Wpx7Ngx+Po2/EXaoUMH+Pj4NLmmRqPB/v37m31NS/HdwWwUldWgvasdHuntLzoOmaHpg0MBAL8ezUNGcYXgNEREfzL4P+lnz56N5cuXY82aNTh58iSmTZuGiooKTJo0CQAQFxeH+Ph4/fmvv/46tmzZgvPnz+PQoUMYP348Lly4gKeffhpAwwyrWbNm4c0338TGjRtx7NgxxMXFwc/PD6NGjTL0yzEZdVqdfuzNM3eHwMaKd2+o9XXzc8aQMC/oZGDJjnTRcYiI9KwM/Q3GjBmDoqIizJs3D/n5+YiIiEBCQoJ+kHBWVhYUij/ffC9fvowpU6YgPz8fbm5uiIyMxN69e9GtWzf9OS+99BIqKiowdepUlJaWYuDAgUhISLhqQUBLtjE1D7mlVfBwVOEx7jlFBjT93lAknirEj4dy8XxMZ7R3tRMdiYgIkizLsugQbU2j0cDFxQVqtdosx+PodDLu+/dOnCuqwNzhYXjm7o6iI5GZe2LZPiSdv4QJ0UH410PdRcchIjPVkvdvfm5hhracyMe5ogo421phXFSg6DhkAWbc2zAWZ/2BhnFfRESiseCYGVmW9TNaJvYPhpOtteBEZAn6d2yHiABX1NTr8Pnu86LjEBGx4JibP84W41iuGnbWSkwc0EF0HLIQkiRhxj0Nd3G+TLqA0spawYmIyNKx4JiZxdsbZrL8LSoQ7g42gtOQJRnS1QthPk6oqNVi9d5M0XGIyMKx4JiRg5kl2J9RAmulhCmDQkTHIQsjSRKmN97FWbUnE+U19YITEZElY8ExI//Z0TD25tFIf/i4cMo8tb37e/gixMMB6qo6fLX/gug4RGTBWHDMRFqeGttOFUIhAX+/i9PCSQylQsIzgxv+/C3/IwPVdVrBiYjIUrHgmIkljXdvRvT0Q7CHg+A0ZMke7tUe7V3tUFRWg+8OWs7GtkRkXFhwzMD5onL8euwiAODZwbx7Q2JZKxX4+90NY8CW/5GBeq1OcCIiskQsOGbgs53nIcvAkDAvdPU1v5WZyfQ8FhkAN3trZJVUIiEtX3QcIrJALDgmLl9djR8P5wAAnr2Hd2/IONjZKDGhfzCAKwXc4naEISLBWHBM3Kq9GajTyugX7I7IIHfRcYj04qKDYWutwLFcNZLOXxIdh4gsDAuOCSurrsNX+7IAAFPv4ro3ZFzcHWzweONO9p/t5PYNRNS2WHBM2PrkbJTV1KOjpwPuDfMSHYfoKk8PDIFCAnaeKcLJixrRcYjIgrDgmKg6rQ4r92QAaLh7o1BIghMRXS2wnT3u7+ELAFi2i3dxiKjtsOCYqF+O5OGiuhqeTiqM6tVedByi67qy8OQvR/KQW1olOA0RWQoWHBMky7L+X8MT+wdDZaUUnIjo+nr4u6B/x3ao18lYuTtDdBwishAsOCZo19linMovg72NEuOjgkTHIbqpv9/dcBfn6+QsqCvrBKchIkvAgmOClu1q2JZhbN9AuNhbC05DdHN3dfJAmI8TKmu1+JKbcBJRG2DBMTHHc9XYk34JSoWEpwYGi45D1CySJOm3b1i1J5ObcBKRwbHgmJgrY28e6OkLfzd7wWmImu+Bnn7wc7FFcXkNNhzOFR2HiMwcC44Jyblcqd9Ukwv7kamxVioweVDjJpy7zkOr4/YNRGQ4LDgmZMXuDGh1MgaGeuAOPxfRcYhabGzfADjbWuF8cQW2nigQHYeIzBgLjolQV9bhmwPZAHj3hkyXg8oK4+9smPnHKeNEZEgsOCbiy/0XUFmrRVdfZwzq5CE6DtEtm9A/GNZKCcmZJTiSXSo6DhGZKRYcE1BTr8XqvZkAgKl3dYAkcVsGMl3ezrYY2dMPQMPHrkREhsCCYwI2HbmIorIa+Djb4oHGNwYiU/bUwA4AgF+PXUQet28gIgNgwTFysizr/5Ub1z8I1kr+lpHp697eBdEh7aDVyVjTeHeSiKg18d3SyO07X4ITFzWwtVbgb/0CRcchajVPD2q4i/NVchbKa+oFpyEic8OCY+Su3L0Z3dsfrvY2gtMQtZ57unghxMMBZdX1+O5gtug4RGRmWHCMWGZxBRJPNawVcmXMApG5UCgk/Z/rlXsyuPAfEbWqNik4ixcvRnBwMGxtbREVFYXk5OTrnrt8+XIMGjQIbm5ucHNzQ0xMzFXnT5w4EZIkNTmGDRtm6JfR5lbtyYAsA/d08URHT0fRcYhaXcOdSWtkl1Rh64l80XGIyIwYvOB88803mD17NubPn49Dhw4hPDwcsbGxKCwsvOb5O3bswBNPPIHt27cjKSkJAQEBGDp0KHJzm+5dM2zYMFy8eFF/fP3114Z+KW1KXVWH71JyAACTB3JhPzJPdjZKjI9qWPjv8z84ZZyIWo/BC85HH32EKVOmYNKkSejWrRuWLl0Ke3t7rFy58prnr1u3Ds8++ywiIiIQFhaGzz//HDqdDomJiU3OU6lU8PHx0R9ubm6Gfiltan1yFiprtQjzccKA0Hai4xAZTFx0EKyVEg5euIzDWZdFxyEiM2HQglNbW4uUlBTExMT8+Q0VCsTExCApKalZ16isrERdXR3c3d2bPL5jxw54eXmhS5cumDZtGi5dunTda9TU1ECj0TQ5jFm9VqefOvvUAC7sR+bNy9kWI8O58B8RtS6DFpzi4mJotVp4e3s3edzb2xv5+c37vP3ll1+Gn59fk5I0bNgwrF27FomJiXj33Xexc+dODB8+HFqt9prXWLBgAVxcXPRHQEDArb+oNvDb8Xzkqavh4WiDByO4sB+Zv8mNg41/O56PnMuVgtMQkTkw6llU77zzDtavX48NGzbA1tZW//jYsWPx4IMPokePHhg1ahQ2bdqEAwcOYMeOHde8Tnx8PNRqtf7IzjbuKalX/hU7LioIttZKwWmIDO8OPxf078iF/4io9Ri04Hh4eECpVKKgoKDJ4wUFBfDx8bnhcz/44AO888472LJlC3r27HnDc0NCQuDh4YH09PRrfl2lUsHZ2bnJYaxSLlxGanYpbJQK/a7LRJbgysJ/65OzUVZdJzgNEZk6gxYcGxsbREZGNhkgfGXAcHR09HWf99577+GNN95AQkIC+vTpc9Pvk5OTg0uXLsHX17dVcou0svHuzUMRfvB0UglOQ9R2Bnf2QoinA8pq6vF94wxCIqJbZfCPqGbPno3ly5djzZo1OHnyJKZNm4aKigpMmjQJABAXF4f4+Hj9+e+++y5effVVrFy5EsHBwcjPz0d+fj7Ky8sBAOXl5XjxxRexb98+ZGZmIjExEQ899BBCQ0MRGxtr6JdjUDmXK/Hb8YsAgMmDuLAfWRaFQsKk/sEAgDV7M6Hjwn9EdBsMXnDGjBmDDz74APPmzUNERARSU1ORkJCgH3iclZWFixcv6s9fsmQJamtr8eijj8LX11d/fPDBBwAApVKJo0eP4sEHH0Tnzp0xefJkREZG4o8//oBKZdp3PNbszYROBgaEtkOYj/F+jEZkKI/09oeTrRUyL1Vi++lrr5VFRNQckizLFvfPJI1GAxcXF6jVaqMZj1NeU4/otxNRVlOPlRP74N4w75s/icgMvfXrCSz/IwMDQz3w5dNRouMQkRFpyfu3Uc+isiTfHcxGWU09QjwdMLizl+g4RMLERQdDIQG704txpqBMdBwiMlEsOEZAq5Oxak8mAGDSgA5QKLiwH1muAHd73Net4Q7mlf8uiIhaigXHCPx+sgBZJZVwsbPG6N7tRcchEm7SgIZB9hsO56C0slZwGiIyRSw4RuDKwn5/iwqEvY2V4DRE4kV1cEc3X2dU1+nwdbJxL8xJRMaJBUewtDw1kjNKoFRIiIvmwn5EACBJEiYNCAYAfJGUiXqtTmwgIjI5LDiCXVmWfnh3H/i62IkNQ2RERob7oZ2DDfLU1dicVnDzJxAR/QULjkAlFbX4KTUPAPT/WiWiBrbWSoyLCgQArNzDXcaJqGVYcAT6OjkLtfU69Gjvgt6BbqLjEBmd8XcGwVopIeXCZRzNKRUdh4hMCAuOIHVaHb7cdwEAMLF/MCSJU8OJ/peXsy1G9GjYY45TxomoJVhwBNmSVoCL6mp4ONrggXDT3ySUyFCuTBnfdDQPhZpqwWmIyFSw4Aiyem/j1PB+gVBZKQWnITJe4QGu6B3oijqtjC/3Z4mOQ0QmggVHgOO5ahzIvAwrhYRxd3JqONHNPDWw4S7OV/svoKZeKzgNEZkCFhwBVjdODb+/hy+8nW3FhiEyAbF3+MDXxRbF5bX45chF0XGIyASw4LSx4vIabGycGj6RU8OJmsVaqcCTjQthrtqTAVmWBSciImPHgtPG1idnoVarQ7i/C3oFuIqOQ2QynugbCFtrBdLyNDiQeVl0HCIyciw4bahOq8MXV6aGD+DUcKKWcHOwwcO9GjajXcWF/4joJlhw2lDC8XwUaGrg4ajC/T04NZyopSb2bxhsvDktHzmXKwWnISJjxoLThq4MLh4XxanhRLeii48TBoS2g06G/m4oEdG1sOC0kaM5pUi5cBnWSkm/vw4Rtdykxrs465OzUVXLKeNEdG0sOG3kyt2bET184cWp4US37J4wLwS620NdVYefUnNFxyEiI8WC0waKymqwqXHtjomNy84T0a1RKiTENU4ZX70nk1PGieiaWHDawNeNU8MjAlwRwanhRLftsT4BsLdR4nRBGZLOXxIdh4iMEAuOgdXW/7lr+CQu7EfUKlzsrDG6tz8A7jJORNfGgmNgvx2/iMKyGng6qTC8O6eGE7WWCf0bPqb6/WQBsks4ZZyImmLBMbArg4vHRwXBxoo/bqLWEurlhEGdPCDLwNqkTNFxiMjI8B3XgFKzS3E4qxTWSgl/49RwolZ35WPf9QeyUVFTLzYMERkVFhwDWtN492ZkTz94OqnEhiEyQ4M7eyG4nT3Kquux4TCnjBPRn1hwDKSwrBqbjjbsGj6hf7DYMERmSqGQ9P99rd7LKeNE9CcWHAP5an8W6rQyege6IpxTw4kM5tFIfzjYKJFeWI496ZwyTkQNWHAMoGFqeBYALuxHZGhOttZ4rE8AAGD1Xu4yTkQNWHAM4L/HLqK4vAbezioM7+4jOg6R2buysnHiqUJcuFQhOA0RGYM2KTiLFy9GcHAwbG1tERUVheTk5Bue/9133yEsLAy2trbo0aMH/vvf/zb5uizLmDdvHnx9fWFnZ4eYmBicPXvWkC+hRVb9ZWq4tZIdksjQQjwdMbiLJ2QZWLOXu4wTURsUnG+++QazZ8/G/PnzcejQIYSHhyM2NhaFhYXXPH/v3r144oknMHnyZBw+fBijRo3CqFGjcPz4cf057733HhYuXIilS5di//79cHBwQGxsLKqrqw39cm7qcNZlHMkuhY1SgSc4NZyozUxsHGz83cFslHPKOJHFk2QDTzuIiopC37598emnnwIAdDodAgICMHPmTMydO/eq88eMGYOKigps2rRJ/9idd96JiIgILF26FLIsw8/PD3PmzME//vEPAIBarYa3tzdWr16NsWPH3jSTRqOBi4sL1Go1nJ2dW+mVNnh+/WH8nJqH0b398eHj4a16bSK6Pp1ORsxHO3G+uAKvP3QH4qKDRUciolbWkvdvg97Bqa2tRUpKCmJiYv78hgoFYmJikJSUdM3nJCUlNTkfAGJjY/XnZ2RkID8/v8k5Li4uiIqKuu41a2pqoNFomhyGUKCpxq9HG3cN59RwojalUEiY2Ljw3+q9mdDpOGWcSIQzBWX4+xcHsU/wRrgGLTjFxcXQarXw9vZu8ri3tzfy8/Ov+Zz8/Pwbnn/lf1tyzQULFsDFxUV/BAQE3NLruZl1+7NQr5PRJ8gNPfxdDPI9iOj6HuntDyeVFc4XVeCP9GLRcYgs0uq9mdicVqBf7FYUixgBGx8fD7VarT+ys7MN8n0e7e2Ppwd2wNS7QgxyfSK6MUeV1Z9TxvdwyjhRW1NX1mHDoYZVxUUvcmvQguPh4QGlUomCgoImjxcUFMDH59rTp318fG54/pX/bck1VSoVnJ2dmxyGENjOHq880A1D7+DUcCJR4qKDIEnA9tNFOF9ULjoOkUX59mA2quq0CPNxQlQHd6FZDFpwbGxsEBkZicTERP1jOp0OiYmJiI6OvuZzoqOjm5wPAFu3btWf36FDB/j4+DQ5R6PRYP/+/de9JhFZjmAPB9zbxQsAsDaJU8aJ2opWJ2NNUiaAho1wJUkSmsfgH1HNnj0by5cvx5o1a3Dy5ElMmzYNFRUVmDRpEgAgLi4O8fHx+vOff/55JCQk4MMPP8SpU6fw2muv4eDBg5gxYwYAQJIkzJo1C2+++SY2btyIY8eOIS4uDn5+fhg1apShXw4RmYArg42/O5iNsuo6sWGILETiyQLkXK6Cq701HopoLzoOrAz9DcaMGYOioiLMmzcP+fn5iIiIQEJCgn6QcFZWFhSKP3tW//798dVXX+GVV17BP//5T3Tq1Ak//fQTunfvrj/npZdeQkVFBaZOnYrS0lIMHDgQCQkJsLW1NfTLISITMDDUA6FejkgvLMf3KTmYxC1TiAzuyt2bsX0DYWutFBsGbbAOjjEy5Do4RGQcvth3Aa/+dBzB7eyxbc5gKBRib5cTmbMzBWUY+u9dUEjAHy/fi/audgb5PkazDg4RkSije7eHk60VMi9VYueZItFxiMza6sYp4UO7+Ris3LQUCw4RmSV7GyuM7dswZXyV4PU4iMzZX6eGXxn/ZgxYcIjIbMVFB0OSgF1nipBeyCnjRIZgTFPD/4oFh4jMVoC7PWK6NkxoEL2qKpE5+uvU8In9xU8N/ysWHCIya5MaV1P94VAO1FWcMk7UmradKjSqqeF/xYJDRGYtumM7dPZ2RGWtFt8dNMw2LUSWavXehi1RxvQNgJ2N+Knhf8WCQ0RmTZIkTOzfsA7O2qQL0HKXcaJWcaagDHvSL0EhAU/eGSQ6zlVYcIjI7I3q5QcXO2tklVRi+6lC0XGIzMKav0wN93ezFxvmGlhwiMjs/XXK+GoONia6berKOvxoJLuGXw8LDhFZhCejg6CQgN3pxThbUCY6DpFJ+y7lz6nhd4YYz9Twv2LBISKL4O9mj6HdfABw4T+i2/HXqeETjGxq+F+x4BCRxbiyyuqPh3KgruSUcaJbse1UIbJLquBiZ41RRjY1/K9YcIjIYkR1cEeYjxOq63T45mCW6DhEJunK4OKx/YxvavhfseAQkcWQJAmTGu/irNnLKeNELXW2oAy704uNdmr4X7HgEJFFeSiiPVztrZFbWoXfTxaIjkNkUq7MQryvm7dRTg3/KxYcIrIottZKPNEvEACwek+m2DBEJqS0shY/HMoBAP3imcaMBYeILM6TdwZBqZCQdP4STuVrRMchMgnrD2Sjuk6Hrr7ORjs1/K9YcIjI4vi52mHYHQ1TxnkXh+jm6rU6rG38eGrSAOOdGv5XLDhEZJGuTBnfcDgXlytqxYYhMnKb0wqQp65GOwcbPBjuJzpOs7DgEJFF6hPkhjv8nFFTr8P6A9xlnOhGVu1p2DV8XFQgbK2Nd2r4X7HgEJFFathlPBgA8EVSJuq1OrGBiIzU0ZxSHLxwGdZKCeONfGr4X7HgEJHFGhnuB3cHG+Spq7H1BKeME13LqsZxag/09IOXs63YMC3AgkNEFsvWWom/NU4Z5/5URFcr1FRj09E8ANAvkmkqWHCIyKKNb5wynpxRgrQ8teg4REbly30XUKeVERnkhp7+rqLjtAgLDhFZNB8XWwzv3jBlfA3v4hDpVddpsW5/w55tTw0w/oX9/hcLDhFZvEmNf3n/lJqHS+U1gtMQGYeNR/JwqaIWfi62iL3DW3ScFmPBISKL1zvQFT39XVDLKeNEAABZlvWDi+P6B8NKaXp1wfQSExG1sqZTxi+gjlPGycLtzyjByYsa2ForMLZvgOg4t4QFh4gIwIievvBwtEG+phqb0/JFxyESauXuhoX9HuntD1d7G8Fpbg0LDhERAJWVEn+LaljEjPtTkSXLulSJrScb1oWa1Hhn0xSx4BARNRofFQgrhYSDFy7jWA6njJNlWpOUCVkGBnXyQCdvJ9FxbplBC05JSQnGjRsHZ2dnuLq6YvLkySgvL7/h+TNnzkSXLl1gZ2eHwMBAPPfcc1Crm/5FI0nSVcf69esN+VKIyAJ4OdtiRE9fAMBqThknC1ReU49vGwfaPzXQ9KaG/5VBC864ceOQlpaGrVu3YtOmTdi1axemTp163fPz8vKQl5eHDz74AMePH8fq1auRkJCAyZMnX3XuqlWrcPHiRf0xatQoA74SIrIUVwYb/3IkD0VlnDJOluX7g9koq6lHiIcD7u7kKTrObbEy1IVPnjyJhIQEHDhwAH369AEALFq0CPfffz8++OAD+Pldvd169+7d8cMPP+h/3bFjR7z11lsYP3486uvrYWX1Z1xXV1f4+PgYKj4RWahegW6ICHBFanYpvth3AbPv6yw6ElGb0OlkrEm6AACYOCAYCoUkONHtMdgdnKSkJLi6uurLDQDExMRAoVBg//79zb6OWq2Gs7Nzk3IDANOnT4eHhwf69euHlStXQpbl616jpqYGGo2myUFEdD1PD2q4Nf/lvguortMKTkPUNnacKURGcQWcbK0wure/6Di3zWAFJz8/H15eXk0es7Kygru7O/LzmzcFs7i4GG+88cZVH2u9/vrr+Pbbb7F161aMHj0azz77LBYtWnTd6yxYsAAuLi76IyDANOf0E1HbGHaHD9q72qGkohYbDueKjkPUJlY0Tg0f2zcADiqDfcDTZlpccObOnXvNQb5/PU6dOnXbwTQaDUaMGIFu3brhtddea/K1V199FQMGDECvXr3w8ssv46WXXsL7779/3WvFx8dDrVbrj+xsrlRKRNdnpVTod05esTsDOt317xATmYO0PDX2pF+CUiFhgglPDf+rFle0OXPmYOLEiTc8JyQkBD4+PigsLGzyeH19PUpKSm46dqasrAzDhg2Dk5MTNmzYAGtr6xueHxUVhTfeeAM1NTVQqVRXfV2lUl3zcSKi63m8bwA+/v0s0gvLsfNsEe7p4nXzJxGZqCt3b4Z394G/m73gNK2jxQXH09MTnp43H1kdHR2N0tJSpKSkIDIyEgCwbds26HQ6REVFXfd5Go0GsbGxUKlU2LhxI2xtbW/6vVJTU+Hm5sYSQ0StxtnWGmP6BmDF7gys3J3BgkNmq0BTjV+O5AEAnh4UIjhN6zHYGJyuXbti2LBhmDJlCpKTk7Fnzx7MmDEDY8eO1c+gys3NRVhYGJKTkwE0lJuhQ4eioqICK1asgEajQX5+PvLz86HVNgz0++WXX/D555/j+PHjSE9Px5IlS/D2229j5syZhnopRGShJvYPhkIC/jhbjFP5nJxA5mnN3kzUaWX0DW6YQWguDDqKaN26dZgxYwaGDBkChUKB0aNHY+HChfqv19XV4fTp06isrAQAHDp0SD/DKjQ0tMm1MjIyEBwcDGtrayxevBgvvPACZFlGaGgoPvroI0yZMsWQL4WILFCAuz2Gd/fFr8cuYsUfGXj/sXDRkYhaVWVtPdbtzwJgXndvAECSbzS/2kxpNBq4uLjop6ATEV3PoazLeOQ/e2GjVGD33Hvg5XTzj82JTMXapEzM+zkNQe3ssW3OYCiNfO2blrx/cy8qIqIb6B3oht6BrqjV6vBl4yJoROZAq5P1g4snD+xg9OWmpVhwiIhu4sqt+y+48B+Zkd9PFuDCpUq42Fnj0UjTX9jvf7HgEBHdxNBu3vB3s8Plyjr8eIgL/5F5+PyP8wCAcVGBsLcx/YX9/hcLDhHRTTQs/NewfcOK3ee58B+ZvNTsUhzIvAxrpfks7Pe/WHCIiJrh8T7+cFJZ4VxRBXaeKRIdh+i2XLl7MzLcD97O5jlwngWHiKgZnGytMbZfwz52yxvfHIhMUc7lSvx2vGFPyKcHmtfU8L9iwSEiaqaJAxpmmuw9dwnHc9Wi4xDdktV7MqHVyRgQ2g7d/Mx3qRQWHCKiZmrvaocHevoCAD7bxbs4ZHrKquuw/kDDhtPmtrDf/2LBISJqgal3Nbwp/Ho0D9kllYLTELXM+uRslNfUI9TLEXd3uvm+kqaMBYeIqAXu8HPBoE4e0Ml/7sBMZApq63X6P7NTBnWAwswW9vtfLDhERC30zN0dAQDrD2ShpKJWcBqi5vk5NRf5mmp4Oakwqld70XEMjgWHiKiF+ndshzv8nFFdp8MX3L6BTIBOJ2NZ47ixpwZ2gMpKKTiR4bHgEBG1kCRJ+HvjXZw1SZncvoGM3rZThThbWA4nlRX+FhUoOk6bYMEhIroF93f3gb+bHUoqavFdSo7oOEQ39NmucwCAv90ZCGdba8Fp2gYLDhHRLbBSKvD0wIbtG5bvOg8tt28gI5VyoQQHMi/DRqnAU41bjlgCFhwiolv0eN8AuNpbI6ukEgmNK8MSGZulOxvG3jzcq73ZbstwLSw4RES3yN7GCnHRwQCAZbvOQZZ5F4eMS3phGbaeKIAkAVPvNu+F/f4XCw4R0W2YEB0ElZUCR3LU2He+RHQcoiauzJy6r6s3Ono6Ck7TtlhwiIhuQztHFR7r4w/gz4GcRMYgX12NDYdzAQDPDO4oOE3bY8EhIrpNTw8MgUICdpwuwql8jeg4RACAVXsyUKeV0S/YHb0D3UTHaXMsOEREtynYwwHDuvsAAJbt5CacJJ66qg7r9mcBAJ4ZbFljb65gwSEiagVXtm/4+Qg34STx1u2/gPKaenTxdsI9XbxExxGCBYeIqBX09HfFoE4e0OpkLN3JsTgkTnWdFqv2ZAIApt4VAkky7001r4cFh4iolUy/JxQA8N3BHBRoqgWnIUv1fUoOispq4Otiiwcj/ETHEYYFh4iolUR1cEefIDfUanVYvotjcajt1Wl1WLKj4Q7i3+8KgbXSct/mLfeVExG1MkmSMP3ehrs46/ZnoaSiVnAisjQ/p+Yht7QKHo42GNvPMjbVvB4WHCKiVjS4sye6t3dGVZ0Wq/ZkiI5DFkSrk/Gf7ekAgCmDQmBrrRScSCwWHCKiViRJEqYPbriLs3pvJjTVdYITkaX477GLOF9cAVd7a4y7M0h0HOFYcIiIWlnsHT4I9XJEWXU9vki6IDoOWQCdTsan2xru3jw1oAMcVVaCE4nHgkNE1MoUCgnPNi6Nv3J3BqpqtYITkbn7/WQBTheUwUllhQn9g0XHMQosOEREBvBguB8C3O1wqaIWXydniY5DZkyWZXzaOPYmrn8QXOysBScyDgYtOCUlJRg3bhycnZ3h6uqKyZMno7y8/IbPGTx4MCRJanI888wzTc7JysrCiBEjYG9vDy8vL7z44ouor6835EshImoRK6VCv7rxsl3nUVuvE5yIzNWus8U4mqOGnbUSTw3oIDqO0TBowRk3bhzS0tKwdetWbNq0Cbt27cLUqVNv+rwpU6bg4sWL+uO9997Tf02r1WLEiBGora3F3r17sWbNGqxevRrz5s0z5EshImqxRyP94e2sQr6mGj8eyhEdh8yQLMtYlHgWAPC3qEC0c1QJTmQ8DFZwTp48iYSEBHz++eeIiorCwIEDsWjRIqxfvx55eXk3fK69vT18fHz0h7Ozs/5rW7ZswYkTJ/Dll18iIiICw4cPxxtvvIHFixejtpZrThCR8VBZKTFlUMNGh0t2nkO9lndxqHXtzyjBwQuXYaNUYOpdlrmp5vUYrOAkJSXB1dUVffr00T8WExMDhUKB/fv33/C569atg4eHB7p37474+HhUVv65cV1SUhJ69OgBb29v/WOxsbHQaDRIS0u75vVqamqg0WiaHEREbeFvUYFwd7DBhUuV2HT0oug4ZGauzJx6vK8/vJ1tBacxLgYrOPn5+fDyarqDqZWVFdzd3ZGfn3/d5/3tb3/Dl19+ie3btyM+Ph5ffPEFxo8f3+S6fy03APS/vt51FyxYABcXF/0REBBwqy+LiKhF7G2sMHlgw7iIRdvOQquTBScic3Eo6zJ2pxfDSiHh73d1FB3H6LS44MydO/eqQcD/e5w6deqWA02dOhWxsbHo0aMHxo0bh7Vr12LDhg04d+7Wd+eNj4+HWq3WH9nZ2bd8LSKiloqLDoKrvTXOFVVg09Ebf0RP1FyLG+/ePNyrPQLc7QWnMT4tXglozpw5mDhx4g3PCQkJgY+PDwoLC5s8Xl9fj5KSEvj4+DT7+0VFRQEA0tPT0bFjR/j4+CA5ObnJOQUFBQBw3euqVCqoVBx4RURiONlaY8qgELy/+TQ+STyLB3r6QamQRMciE3YsR43EU4VQSMC0wbx7cy0tLjienp7w9PS86XnR0dEoLS1FSkoKIiMjAQDbtm2DTqfTl5bmSE1NBQD4+vrqr/vWW2+hsLBQ/xHY1q1b4ezsjG7durXw1RARtY0J/YOx/I/zOF9UgV+O5GFUr/aiI5EJ+/fvZwAAoyLaI8TTUXAa42SwMThdu3bFsGHDMGXKFCQnJ2PPnj2YMWMGxo4dCz8/PwBAbm4uwsLC9Hdkzp07hzfeeAMpKSnIzMzExo0bERcXh7vuugs9e/YEAAwdOhTdunXDk08+iSNHjmDz5s145ZVXMH36dN6lISKj5aiy0s+oWpjIsTh06w5nXca2U4VQKiTMHNJJdByjZdB1cNatW4ewsDAMGTIE999/PwYOHIhly5bpv15XV4fTp0/rZ0nZ2Njg999/x9ChQxEWFoY5c+Zg9OjR+OWXX/TPUSqV2LRpE5RKJaKjozF+/HjExcXh9ddfN+RLISK6bRP6B8PN3hrniyuw8Uiu6Dhkov79e8O6Nw/3ao8OHg6C0xgvSZZli/tnhEajgYuLC9RqdZM1doiIDO0/O9LxXsJphHg4YMsLd8FKyR1zqPlSLpRg9JIkKBUSts8ZjMB2ljW4uCXv3/wvi4ioDcVF//UuDmdUUcv8e2vD3ZvHIv0trty0FAsOEVEbclRZYWrjmiWLtqVzdWNqtv3nL+nXvZl+T6joOEaPBYeIqI3FRQfB3cEGGcUV+PEQx+JQ81yZOfV43wCue9MMLDhERG3MQWWFZxvXLvn49zOoqdcKTkTGbu+5Yuw7XwIbpYJ3b5qJBYeISIDxdwbB18UWeepqfLU/S3QcMmKyLOODzacBAGP6BqC9q53gRKaBBYeISABbayWea1zDZPH2dFTU1AtORMbq95OFOJRVCltrBWbey7s3zcWCQ0QkyKOR/ghuZ4/i8lqs3pspOg4ZIa3uz7s3kwZ0gBd3DG82FhwiIkGslQq8cF9nAMDSneegrqwTnIiMzcYjuThdUAZnWys8wx3DW4QFh4hIoJE9/RDm44Sy6np8tuuc6DhkRGrrdfhoa8PMqWcGd4SLvbXgRKaFBYeISCCFQsKcoV0AAKv2ZKKwrFpwIjIW6w9kIbukCl5OKkzq30F0HJPDgkNEJFhMVy9EBLiiqk6LRYnpouOQEaisrcfCxj8LM4d0gp2NUnAi08OCQ0QkmCRJeHlYGADg6+QsnC8qF5yIRFu1JxPF5TUIamePsX0DRMcxSSw4RERGILpjO9wb5oV6nYz3Ek6LjkMCXa6oxdKdDeOxZt/XGdbckPWW8KdGRGQk5g4Pg0ICEtLycTCzRHQcEuSTxLMoq65HV19njOzpJzqOyWLBISIyEp29nfB4n4aPI97+70nIsiw4EbW1jOIKfLnvAgDglRFdoVBIghOZLhYcIiIj8sJ9nWFnrcShrFIkHM8XHYfa2Du/nUS9TsY9XTwxINRDdByTxoJDRGREvJ1tMWVQw5TgdxNOoU6rE5yI2kpyRgk2pxVAIQH/vL+r6DgmjwWHiMjITL27IzwcbZB5qZIbcVoInU7GW7+eAACM7ReITt5OghOZPhYcIiIj46iywvMxDVs4fJJ4FppqbuFg7n45mocjOWo42CjxQuPvPd0eFhwiIiM0tm8AOno6oKSiFosSz4qOQwZUXafVLw0wbXBHeDqpBCcyDyw4RERGyFqpwKsPdAPQsOjbOS7+Z7ZW7clEbmkVfJxtMXlgiOg4ZoMFh4jISA3u4qVf/O/NTSdExyEDKNBU49NtDXfoXoztwi0ZWhELDhGREXtlRFdYKyVsP12E7acKRcehVvbOb6dQUatFr0BXPNyrveg4ZoUFh4jIiIV4OmLSgIZp429sOoHaek4bNxcHM0uw4XAuJAl4beQdXNSvlbHgEBEZuZn3hsLD0QbniyuwNilTdBxqBVqdjPkb0wAAj0cGIDzAVWwgM8SCQ0Rk5JxsrfFSbMNu45/8fhbF5TWCE9Ht+uZANtLyNHCytcKLw7qIjmOWWHCIiEzAo5H+6NHeBWU19Xgv4ZToOHQb1JV1eH9zw+/hCzGd4eHIaeGGwIJDRGQCFAoJrz14BwDg24M5OMDdxk3WR1tP43JlHTp7O+LJ6CDRccwWCw4RkYmIDHLDE/0adhv/vw3HuE+VCUrLU+OLxt3CXxt5B6yVfBs2FP5kiYhMyMvDwuDuYIMzBeVYsTtDdBxqAa1ORvyPx6CTgRE9fdGfu4UbFAsOEZEJcbW30e80/cnvZ5FzuVJwImquL5IycTRHDSdbK8xvXKWaDMegBaekpATjxo2Ds7MzXF1dMXnyZJSXX3+58czMTEiSdM3ju+++0593ra+vX7/ekC+FiMhojO7dHlEd3FFVp8VrG7nCsSm4qK7C+5sb9pt6eVgYvJxtBScyfwYtOOPGjUNaWhq2bt2KTZs2YdeuXZg6dep1zw8ICMDFixebHP/617/g6OiI4cOHNzl31apVTc4bNWqUIV8KEZHRkCQJbz3cHdZKCb+fLMCWtHzRkegmXtuYhopaLXoHuuJv/QJFx7EIVoa68MmTJ5GQkIADBw6gT58+AIBFixbh/vvvxwcffAA/P7+rnqNUKuHj49PksQ0bNuDxxx+Ho6Njk8ddXV2vOpeIyFKEejlhyqAQ/GfHOby2MQ0DQj3goDLYX+l0G7ak5WNzWgGsFBIWPNKTKxa3EYPdwUlKSoKrq6u+3ABATEwMFAoF9u/f36xrpKSkIDU1FZMnT77qa9OnT4eHhwf69euHlStXQpbl616npqYGGo2myUFEZOpm3tsJAe52yFNX412ujWOUymvq9SsWT70rBF18nAQnshwGKzj5+fnw8vJq8piVlRXc3d2Rn9+826krVqxA165d0b9//yaPv/766/j222+xdetWjB49Gs8++ywWLVp03essWLAALi4u+iMgIKDlL4iIyMjY2SjxziM9AQBrky4g6dwlwYnof32w+TQuqqsR6G6P54Z0Eh3HorS44MydO/e6A4GvHKdO3f6/JKqqqvDVV19d8+7Nq6++igEDBqBXr154+eWX8dJLL+H999+/7rXi4+OhVqv1R3Z29m3nIyIyBgNCPfBE45iOl384israesGJ6Iqkc5ewem8mAOCth7vD1lopNpCFafEHtnPmzMHEiRNveE5ISAh8fHxQWFjY5PH6+nqUlJQ0a+zM999/j8rKSsTFxd303KioKLzxxhuoqamBSnX1ktcqleqajxMRmYN/3h+GnacLkVVSifc3n8b8kXeIjmTxKmrq8eL3RwAAT/QLxKBOnoITWZ4WFxxPT094et78Nyo6OhqlpaVISUlBZGQkAGDbtm3Q6XSIioq66fNXrFiBBx98sFnfKzU1FW5ubiwxRGSRnGytsWB0T0xYmYzVezNxfw9f9A12Fx3Lor3935PIuVyF9q52+L8RXUXHsUgGG4PTtWtXDBs2DFOmTEFycjL27NmDGTNmYOzYsfoZVLm5uQgLC0NycnKT56anp2PXrl14+umnr7ruL7/8gs8//xzHjx9Heno6lixZgrfffhszZ8401EshIjJ6d3f2xON9/CHLwEvfH0VVrVZ0JIv1x9kirNufBQB4/9GecOTsNiEMug7OunXrEBYWhiFDhuD+++/HwIEDsWzZMv3X6+rqcPr0aVRWNl2Jc+XKlfD398fQoUOvuqa1tTUWL16M6OhoRERE4LPPPsNHH32E+fPnG/KlEBEZvf8b0Q3ezipkFFfggy2nRcexSJrqOrz8/VEAQFx0ELdjEEiSbzS/2kxpNBq4uLhArVbD2dlZdBwiolaz/VQhJq0+AAD4YnI/jv1oYy99fwTfHsxBoLs9EmYNgr0N7960ppa8f3MvKiIiM3JPmBeevDMIADD72yO4VF4jOJHl2JKWj28P5kCSgA8eC2e5EYwFh4jIzPzfiK7o5OWIorIavPzD0RsuhEqtI6+0Ci82fjT19MAO6NeBg7xFY8EhIjIzttZKLHyiF2yUCvx+shBf7rsgOpJZq9fq8Pz6w1BX1aGnvwtejA0THYnAgkNEZJa6+jrj5eENb7Rv/noSZwrKBCcyXwu3peNA5mU4qqyw6IlesLHiW6sx4O8CEZGZmtQ/GHd39kRNvQ7PfX0Y1XWcOt7a9p2/hE+3nQXQsFpxUDsHwYnoChYcIiIzpVBI+OCxcLRzsMGp/DLM+/k4x+O0ossVtZi1PhU6GXg00h8PRbQXHYn+ggWHiMiMeTqp8MnYXlBIwLcHc7D+APfiaw1anYzZ36YiX1ONEE8H/OtBbo9hbFhwiIjM3MBOHpgztAsAYP7PaUjNLhUbyAz8e+sZbD9dBJWVAoue6AUHrlZsdFhwiIgswLODO2JoN2/UanV49ssUro9zG/577CI+3Z4OAHh3dE/c4eciOBFdCwsOEZEFkCQJHzwejhAPB+SpqzHz68Oo1+pExzI5p/I1+Md3DbuEPz2wA0b14rgbY8WCQ0RkIZxtrbH0yUjY2yix99wlvJtwSnQkk1JaWYupa1NQWavFgNB2mDuc690YMxYcIiIL0tnbCe892hMAsPyPDKzbz0UAm6Neq8PMrw8jq6QS/m52+PSJ3rBS8i3UmPF3h4jIwjzQ0w+zYjoBAF796Ti2nyoUnMi4ybKMV39Owx9ni2FnrcSyJ/vAzcFGdCy6CRYcIiIL9PyQTng00h86GZj+1SEcz1WLjmS0Fiam4+vkLEgS8O8xEejmd+NdrMk4sOAQEVkgSZLw9sM9MCC0HSprtZi0+gByS6tExzI665Oz8O/fzwAAXn+oO4Z19xGciJqLBYeIyELZWCmwZHwkung7oaisBpNWJUNdWSc6ltH4/UQB/rnhGABgxj2hePLOIMGJqCVYcIiILJizrTVWTuoLLycVzhSUI27lfmiqWXJSLlzGjK8PQScDj0X6Y87QzqIjUQux4BARWbj2rnZYO7kf3OytcSRHjQkrk1FmwSXncNZlTFyVjOo6He7p4om3H+kBSZJEx6IWYsEhIiKE+Tjjy6ej4GJnjcNZpZi06gAqaupFx2pzKRdK8OSKZJRV16NfsDsWj+sNa04HN0n8XSMiIgDAHX4uWPd0FJxtrXDwwmVMWn0AlbWWU3IOZJYgbkUyymvqcWeIO1Y/1Rf2NtxjylSx4BARkV739i74YnIUnFRWSM4owcRVByxiTM6+85cwYWUyKhpXKV41sR/LjYljwSEioibCA1yxZnI/fckZ+9k+FJWZ7+ac208VYtKqA6is1WJQJw+smNAXdjZK0bHoNrHgEBHRVXoHuuHrqXfCw9EGJy5q8OjSvThXVC46Vqtbn5yFp9ceRFWdFnd39sTyuD6wtWa5MQcsOEREdE3d27vg+2f6I8DdDhcuVeKR/+zF3nPFomO1Cq1OxrsJpzD3x2PQ6mQ80rs9y42ZYcEhIqLrCvZwwIZnB6BXoCvUVXWIW5GMtUmZkGVZdLRbpqmuw5S1B7FkxzkADYv4ffhYOGys+JZoTvi7SUREN+ThqMLXU+7EyHA/1OtkzPs5DbO/PWKSM6zS8tQY9ekebDtVCJWVAh+PicA/YrtwnRszxIJDREQ3ZWutxMKxEXhlRFcoFRI2HM7FyEW7TWaTTlmW8UVSJh7+z16cL66Ar4stvnsmGqN6tRcdjQxEkk35PuMt0mg0cHFxgVqthrMzd4UlImqJfecv4bmvD6OwrAbWSgmzYjpj6l0hRrsg3kV1FV7+4Rh2nSkCAAwJ88IHj4XDzcFGcDJqqZa8f7PgsOAQEbXY5YpazP3xKDanFQAAuvo6493RPdDT31VssL/Q6mR8tf8C3tt8GmXV9bCxUuCl2C6YPLADP5IyUSw4N8GCQ0R0+2RZxg+HcvHGphNQV9VBkoDHIwMwJ7YzvJxshWZLzijB65vScDxXA6BhbZ8PHwtHqJej0Fx0e1hwboIFh4io9RSX1+CNTSfwc2oeAMDBRomJA4Lx9MCQNv8Y6HiuGh9uOY3tpxs+jnKytcKLsV0wLioISgXv2pi6lrx/G+wD07feegv9+/eHvb09XF1dm/UcWZYxb948+Pr6ws7ODjExMTh79myTc0pKSjBu3Dg4OzvD1dUVkydPRnm5+S0+RURkKjwcVfhkbC/8MC0a4QGuqKjVYvH2cxj47ja8/ssJZBRXGPT763Qydp0pwpMr9uOBRbux/XQRlAoJT/QLxLY5gxEXHcxyY4EMdgdn/vz5cHV1RU5ODlasWIHS0tKbPufdd9/FggULsGbNGnTo0AGvvvoqjh07hhMnTsDWtuF25/Dhw3Hx4kV89tlnqKurw6RJk9C3b1989dVXzc7GOzhERIah08nYerIACxPPIi1Po398YKgHHozww7DuPnC2tW6V75VeWI5fj17EdynZyLlcBQBQSMADPf0wK6YTQjz5cZS5MaqPqFavXo1Zs2bdtODIsgw/Pz/MmTMH//jHPwAAarUa3t7eWL16NcaOHYuTJ0+iW7duOHDgAPr06QMASEhIwP3334+cnBz4+fk1KxMLDhGRYcmyjJ1nirBmbyZ2nCnClXcaa6WE3oFuuKuzJ3oFuqJ7e5dmFR5ZlpGnrkZqVikOZJZg19kinC/6886Qk8oKoyP9MXlgBwS42xvqZZFgLXn/NpqtUjMyMpCfn4+YmBj9Yy4uLoiKikJSUhLGjh2LpKQkuLq66ssNAMTExEChUGD//v14+OGHr3ntmpoa1NT8uVGcRqO55nlERNQ6JEnC4C5eGNzFC1mXKrHxSC5+Ss1DemE59meUYH9Gif5cb2cVAtzs4eWsgpPKGrbWCtTrZNTU61BSUYvCsmpkFFWgolbb5HtYKyVEd/TAqAg/DO/uyw0yqQmjKTj5+fkAAG9v7yaPe3t767+Wn58PLy+vJl+3srKCu7u7/pxrWbBgAf71r3+1cmIiImqOwHb2mHFvJ8y4txMyiyvwx9kiJJ2/hKM5auRcrkKBpgYFmpvvVm6lkNDJ2wn9gt3Qr0M73NXZA06t9HEXmZ8WFZy5c+fi3XffveE5J0+eRFhY2G2Fam3x8fGYPXu2/tcajQYBAQECExERWaZgDwcEezjgyehgAEBpZS0uXKpEVkklSipqUV5Tj+o6LZQKCdZKBdo52MDDUYWgdvYI9nAw2sUEyfi0qODMmTMHEydOvOE5ISEhtxTEx8cHAFBQUABfX1/94wUFBYiIiNCfU1hY2OR59fX1KCkp0T//WlQqFVQq1S3lIiIiw3G1t4GrvQ3CA1xFRyEz06KC4+npCU9PT4ME6dChA3x8fJCYmKgvNBqNBvv378e0adMAANHR0SgtLUVKSgoiIyMBANu2bYNOp0NUVJRBchEREZHpMdi9vqysLKSmpiIrKwtarRapqalITU1tsmZNWFgYNmzYAKBhQNqsWbPw5ptvYuPGjTh27Bji4uLg5+eHUaNGAQC6du2KYcOGYcqUKUhOTsaePXswY8YMjB07ttkzqIiIiMj8GWyQ8bx587BmzRr9r3v16gUA2L59OwYPHgwAOH36NNTqP3eifemll1BRUYGpU6eitLQUAwcOREJCgn4NHABYt24dZsyYgSFDhkChUGD06NFYuHChoV4GERERmSBu1cB1cIiIiEyCUWzVQERERCQKCw4RERGZHRYcIiIiMjssOERERGR2WHCIiIjI7LDgEBERkdlhwSEiIiKzw4JDREREZocFh4iIiMyOwbZqMGZXFm/WaDSCkxAREVFzXXnfbs4mDBZZcMrKygAAAQEBgpMQERFRS5WVlcHFxeWG51jkXlQ6nQ55eXlwcnKCJEmtem2NRoOAgABkZ2dzn6v/wZ/NjfHnc2P8+dwYfz7Xx5/NjZnSz0eWZZSVlcHPzw8KxY1H2VjkHRyFQgF/f3+Dfg9nZ2ej/4MiCn82N8afz43x53Nj/PlcH382N2YqP5+b3bm5goOMiYiIyOyw4BAREZHZYcFpZSqVCvPnz4dKpRIdxejwZ3Nj/PncGH8+N8afz/XxZ3Nj5vrzschBxkRERGTeeAeHiIiIzA4LDhEREZkdFhwiIiIyOyw4REREZHZYcFrR4sWLERwcDFtbW0RFRSE5OVl0JKOxa9cujBw5En5+fpAkCT/99JPoSEZjwYIF6Nu3L5ycnODl5YVRo0bh9OnTomMZjSVLlqBnz576Rciio6Px22+/iY5llN555x1IkoRZs2aJjmIUXnvtNUiS1OQICwsTHcuo5ObmYvz48WjXrh3s7OzQo0cPHDx4UHSsVsGC00q++eYbzJ49G/Pnz8ehQ4cQHh6O2NhYFBYWio5mFCoqKhAeHo7FixeLjmJ0du7cienTp2Pfvn3YunUr6urqMHToUFRUVIiOZhT8/f3xzjvvICUlBQcPHsS9996Lhx56CGlpaaKjGZUDBw7gs88+Q8+ePUVHMSp33HEHLl68qD92794tOpLRuHz5MgYMGABra2v89ttvOHHiBD788EO4ubmJjtY6ZGoV/fr1k6dPn67/tVarlf38/OQFCxYITGWcAMgbNmwQHcNoFRYWygDknTt3io5itNzc3OTPP/9cdAyjUVZWJnfq1EneunWrfPfdd8vPP/+86EhGYf78+XJ4eLjoGEbr5ZdflgcOHCg6hsHwDk4rqK2tRUpKCmJiYvSPKRQKxMTEICkpSWAyMkVqtRoA4O7uLjiJ8dFqtVi/fj0qKioQHR0tOo7RmD59OkaMGNHk7yBqcPbsWfj5+SEkJATjxo1DVlaW6EhGY+PGjejTpw8ee+wxeHl5oVevXli+fLnoWK2GBacVFBcXQ6vVwtvbu8nj3t7eyM/PF5SKTJFOp8OsWbMwYMAAdO/eXXQco3Hs2DE4OjpCpVLhmWeewYYNG9CtWzfRsYzC+vXrcejQISxYsEB0FKMTFRWF1atXIyEhAUuWLEFGRgYGDRqEsrIy0dGMwvnz57FkyRJ06tQJmzdvxrRp0/Dcc89hzZo1oqO1CovcTZzIWE2fPh3Hjx/nOIH/0aVLF6SmpkKtVuP777/HhAkTsHPnTosvOdnZ2Xj++eexdetW2Nraio5jdIYPH67//z179kRUVBSCgoLw7bffYvLkyQKTGQedToc+ffrg7bffBgD06tULx48fx9KlSzFhwgTB6W4f7+C0Ag8PDyiVShQUFDR5vKCgAD4+PoJSkamZMWMGNm3ahO3bt8Pf3190HKNiY2OD0NBQREZGYsGCBQgPD8cnn3wiOpZwKSkpKCwsRO/evWFlZQUrKyvs3LkTCxcuhJWVFbRareiIRsXV1RWdO3dGenq66ChGwdfX96p/JHTt2tVsPsZjwWkFNjY2iIyMRGJiov4xnU6HxMREjhOgm5JlGTNmzMCGDRuwbds2dOjQQXQko6fT6VBTUyM6hnBDhgzBsWPHkJqaqj/69OmDcePGITU1FUqlUnREo1JeXo5z587B19dXdBSjMGDAgKuWpDhz5gyCgoIEJWpd/IiqlcyePRsTJkxAnz590K9fP3z88ceoqKjApEmTREczCuXl5U3+1ZSRkYHU1FS4u7sjMDBQYDLxpk+fjq+++go///wznJyc9OO2XFxcYGdnJzidePHx8Rg+fDgCAwNRVlaGr776Cjt27MDmzZtFRxPOycnpqrFaDg4OaNeuHcdwAfjHP/6BkSNHIigoCHl5eZg/fz6USiWeeOIJ0dGMwgsvvID+/fvj7bffxuOPP47k5GQsW7YMy5YtEx2tdYiexmVOFi1aJAcGBso2NjZyv3795H379omOZDS2b98uA7jqmDBhguhowl3r5wJAXrVqlehoRuGpp56Sg4KCZBsbG9nT01MeMmSIvGXLFtGxjBanif9pzJgxsq+vr2xjYyO3b99eHjNmjJyeni46llH55Zdf5O7du8sqlUoOCwuTly1bJjpSq5FkWZYFdSsiIiIig+AYHCIiIjI7LDhERERkdlhwiIiIyOyw4BAREZHZYcEhIiIis8OCQ0RERGaHBYeIiIjMDgsOERERmR0WHCIiIjI7LDhERERkdlhwiIiIyOyw4BAREZHZ+X91i876sPsFoQAAAABJRU5ErkJggg==", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x = np.linspace(0, 2*np.pi, num=200)\n", + "y = np.sin(x) \n", + "\n", + "plt.plot(x, y) \n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "10d13d03-03f5-44c4-a62b-b68bf8dcaaf9", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-d81b654168ec4bc8", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Bar Charts\n", + "\n", + "Beliebt sind Barcharts. Dazu werden aber mehrere Parameter benötigt. Da einfache mathematische Funktionen bei dieser Art Plot keinen Sinn ergeben.\n", + "\n", + "Konsultieren wir dafür folgendes Beispiel.\n", + "\n", + "Wir wollen wissen wie viele Kinder an einer Grundschule in jeder Klassenstufe sind.\n", + "Dazu benötigen wir 2 Listen.\n", + "1. Die Klassenstufen\n", + "2. Die Anzahl an Kinder in der Klassenstufe" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "06b54439-c88c-438a-9870-896280151491", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-3767e976a92e292a", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [], + "source": [ + "classes = [\"1. Klasse\", \"2. Klasse\", \"3. Klasse\", \"4. Klasse\"]\n", + "kids = [42, 30, 26, 45]" + ] + }, + { + "cell_type": "markdown", + "id": "55022635-12f7-4666-991b-e802ce67c9a5", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-a702a6b994c5809e", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "Plotten wir die Werte nun als Bar Chart mit der Funktion `plt.bar`:" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "d73faeb6-2b83-495f-b246-2e4b4c6ff784", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-8c604c68ae96c752", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.bar(classes, kids)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "a641132d-cf1a-4e92-bdc3-55f5425b9388", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-c2444cb0f1af6626", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "### Bessere Datenrepresentation\n", + "\n", + "Da die Daten aus `classes` & `kids` miteinander eine Verbindung teilen wäre die Repräsentation mittels Dictionary die klügere Wahl um keine Fehler in den Plot zu bringen.\n", + "\n", + "Mittels der `.keys` & `.values` Funktion auf dem Dictionary lassen sich dann die Daten gezielt plotten.\n", + "\n", + "Schauen Sie sich daher folgendes Beispiel an:" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "d21c9c59-2b84-4e87-a2f2-1388070b2419", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-1777b8fcd5bd30c4", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Definiere ein Dictionary welches die Anzahl der Schüler ihrer Klasse zuweist \n", + "school = { \n", + " \"1. Klasse\": 42,\n", + " \"2. Klasse\": 30,\n", + " \"3. Klasse\": 26,\n", + " \"4. Klasse\": 45,\n", + "}\n", + "\n", + "plt.bar(school.keys(), school.values()) # Plotte mit den Werten des Dictionarys\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "a921963b-94df-4c6a-81f7-c3a3fb09b7c0", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-d2c659803a58f15e", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "### Styling\n", + "\n", + "Bar plots können auch gestyled werden. Hierzu wird dem Parameter `color` eine Liste mit farbwerten übergeben:" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "id": "00e9f1c6-5ccd-4ea3-bcec-b2265602917f", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-a3604899d50585d2", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "school = { \n", + " \"1. Klasse\": 42,\n", + " \"2. Klasse\": 30,\n", + " \"3. Klasse\": 26,\n", + " \"4. Klasse\": 45,\n", + "}\n", + "\n", + "bar_colors = [\"red\", \"blue\", \"green\", \"yellow\"] # Farben definieren\n", + "\n", + "plt.bar(school.keys(), school.values(), color=bar_colors) # Farben übergeben\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "a74afec9-34fd-4cfb-bcd3-db6be64ef35f", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-964f579ce46a2882", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "### Y-Label\n", + "\n", + "Mit `plt.ylabel` (als String) lässt sich die y-Achse beschriften:" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "e9f4c9a3-e39c-4eb8-95fd-77a3b40fa249", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-21cee3bf50f011e1", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "school = { \n", + " \"1. Klasse\": 42,\n", + " \"2. Klasse\": 30,\n", + " \"3. Klasse\": 26,\n", + " \"4. Klasse\": 45,\n", + "}\n", + "\n", + "bar_colors = [\"red\", \"blue\", \"green\", \"yellow\"]\n", + "\n", + "plt.bar(school.keys(), school.values(), color=bar_colors)\n", + "\n", + "plt.ylabel(\"Anzahl Kinder\") # Beschriften der Y-Achse\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "9d90f3b3-adc9-498e-9dbe-13e0c577b886", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-32dabb34444f6190", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "### X-Label\n", + "\n", + "Analog Dazu die Beschriftung der X-Achse mit `plt.xlabel`." + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "id": "2644cc38-238e-4cec-b951-3ff88b80011e", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-3737280b071f9d91", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "school = { \n", + " \"1. Klasse\": 42,\n", + " \"2. Klasse\": 30,\n", + " \"3. Klasse\": 26,\n", + " \"4. Klasse\": 45,\n", + "}\n", + "\n", + "bar_colors = [\"red\", \"blue\", \"green\", \"yellow\"]\n", + "\n", + "plt.bar(school.keys(), school.values(), color=bar_colors)\n", + "\n", + "plt.ylabel(\"Anzahl Kinder\") # Beschriften der Y-Achse\n", + "plt.xlabel(\"Klassenstufen\") # Beschriften der X-Achse\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "16e05c9d-80ef-47b8-a17f-df7a96398ab5", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-230328a26793cddb", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "### Aufgabe\n", + "\n", + "*5 Punkte*\n", + "\n", + "Ihnen ist ein Datenset `sec_school` einer Hauptschule gegeben, welches die Klassenstufen von 5 bis 9 auf die Anzahl ihrer Schüler im Jahrgang mappt. \n", + "\n", + "Definieren Sie einen Barplot. Gehen Sie dabei wie folgt vor:\n", + "1. Definieren Sie ein geeignetes Farbschema zur Darstellung der Daten.\n", + "2. Extrahieren Sie die Schlüssel und Werte aus dem Datenset und übergeben Sie diese zusammen mit den Farbwerten an die Funktion `plt.bar`.\n", + "3. Setzen Sie geeignete Werte für die X & Y-Achse.\n", + "4. Setzen Sie einen geeigneten Titel für den Plot.\n", + "5. Plotten Sie den Werte" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "id": "0608b1ea-6275-47c7-82a8-fed86e5e5973", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-b954e989a8bbc2fa", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [], + "source": [ + "sec_school = {\n", + " '5. Klasse': 29,\n", + " '6. Klasse': 35,\n", + " '7. Klasse': 25,\n", + " '8. Klasse': 28,\n", + " '9. Klasse': 31\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "id": "ae63d6f9-cd8c-4603-9a15-7ee336d905e9", + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-8caba57a6ad34b87", + "locked": false, + "points": 5, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# BEGIN SOLUTION\n", + "colors = [\"red\", \"blue\", \"green\", \"yellow\", \"pink\"]\n", + "plt.bar(sec_school.keys(), sec_school.values(), color=colors)\n", + "plt.xlabel(\"Klassenstufe\")\n", + "plt.ylabel(\"Anzahl Kinder\")\n", + "plt.title(\"Verteilung Kinder einer Hauptschule pro Klassenstufe\")\n", + "plt.show()\n", + "# END SOLUTION" + ] + }, + { + "cell_type": "markdown", + "id": "bf9e917c-6949-4bb1-8184-270747e8cb4e", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-42bf44a09515d0fd", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Horizontales Bar Chart\n", + "\n", + "Analog zum Barchart erzeugt `plt.barh` einen Horizontales Barchart.\n", + "\n", + "Beispiel:" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "id": "146615f7-1315-41a3-a690-73c98ee465e3", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-54166820b406e29e", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "school = { \n", + " \"1. Klasse\": 42,\n", + " \"2. Klasse\": 30,\n", + " \"3. Klasse\": 26,\n", + " \"4. Klasse\": 45,\n", + "}\n", + "\n", + "plt.barh(list(school.keys()), list(school.values()), color=\"maroon\") # barh statt bar\n", + "\n", + "plt.xlabel(\"Anzahl Kinder\") \n", + "plt.ylabel(\"Klassenstufen\") \n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "df9117c3-0ca8-4e0d-8779-9b8826044a3a", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-3adde3f53176bcb0", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Pie Chart\n", + "\n", + "Kommen wir als nächstes zu der besten, tollsten und schönsten Darstellung von Daten.\n", + "\n", + "![](https://flowingdata.com/wp-content/uploads/2014/12/Pie-Pyramid-620x311.png)\n", + "\n", + "Kuchendiagramme können mittels `plt.pie` erstellt werden. Nehmen wir dazu wieder das Beispiel aus voherigem Kapitel. Dabei verlangt das Pie Chart nur die Werte (`school.values`) des Datensets:" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "id": "bb311d1b-978d-41f8-9648-874b4a862bc5", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-46cde6d166912ad0", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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Nm4dvvvmm0vPUZKm9rCQv3x6en5+vrhHXxq233oqNGzdi8+bN6mnp6ekV1j6r814cNmwYhBCVftGyNmsniYmJyMnJwW+//aaedubMGXz11VfXvKyn3vP1TbNrCmXuuOMOzJ8/H+PHj8fQoUOxbNky+Pr6VjjfwIED1aX7SZMmIS8vD/Pnz0d0dDTOnDmjnm/hwoX497//jTvuuAOJiYnIzc3F/PnzERwcjFtvvRUA8MADDyAzMxN9+/ZFo0aNcPz4ccyePRudOnVCmzZtAACPP/44vv32WwwePFgdkpefn4/du3fjiy++wLFjxxAZGVnj+xsdHY0+ffpg5syZyM3Nxd13313u7yaTCe+88w5SU1PRrl07jBs3DnFxcTh16hRWrVqF4OBgddji1SQlJQEApk6diuTkZJjNZowcORK9e/fGpEmT8OKLL2Lnzp0YOHAgLBYL0tLSsHjxYrzxxhu46667qn1/xo8fj5kzZyI5ORkTJkzA+fPnMXfuXLRr1+6qJX81L7zwAm677Tb06NED48aNQ1ZWFubMmYP27dtXWpSXCw4OxltvvYX77rsPnTt3xsiRIxEVFYUTJ07gu+++Q48ePTBnzpxa5brcSy+9hFWrVqFr166YOHEi2rZti8zMTGzfvh0//vgjMjMza33dH330EVJSUnD77bcjNTUV/fv3R1hYGM6ePYsff/wRa9asqfYXPQcOHIjGjRtjwoQJePzxx2E2m/Hee++pj0ltTJs2DR9++CFSUlLwyCOPqENSExISyn0YV+e92KdPH9x333148803kZaWhpSUFLhcLqxduxZ9+vSp8XxHI0eOxBNPPIE77rgDU6dOVYcjt2zZssLO/yt56j1f7ySMeKq1smFwlQ1Re+211wQAMXjwYGG32ysdQvbtt9+Kjh07Cl9fX9GkSRPx8ssvi/fee6/cMLjt27eLUaNGicaNGwubzSaio6PF4MGDxdatW9Xr+eKLL8TAgQNFdHS0sFqtonHjxmLSpEnizJkz5W4vNzdXPPXUU6J58+bCarWKyMhI0b17d/Haa6+JkpISIcR/h1q++uqrFe4TADFjxowKp8+fP18AEEFBQaKwsLDSx2rHjh3izjvvFBEREcJms4mEhAQxYsQI8dNPP6nnKXuM0tPTK1ze4XCIP/3pTyIqKkooilLhsZw3b55ISkoSfn5+IigoSHTo0EFMmzZNnD59Wj1PdYakCiHERx99JJo1ayasVqvo1KmTWL58eZVDUqv7OC1atEi0bt1a2Gw20b59e/Htt9+KYcOGidatW1f6eF1p1apVIjk5WYSEhAhfX1+RmJgoxo4dW+51UNWQ1IcffrjC9V05fFEIIc6dOycefvhhER8fLywWi4iJiRH9+vUT8+bNK5cDgFi8eHG1cpcpLCwUr7/+urjppptEcHCw8PHxETExMWLw4MHi448/Ljec+lq3sW3bNtG1a1f1tT5z5swqh6QOGjSowuUrG3b822+/id69ewtfX18RFxcnnnvuOfHuu+/W+L0oROlr9dVXXxWtW7cWVqtVREVFidTUVLFt2zb1PDV5XlasWCHat28vrFaraNWqlfjoo4+qNSRViOq9572dIoSb9tAReblOnTohKirqqkOJiYxO0/sUiCpjt9srbL9dvXo1du3adc1pN4iMjmsKpDvHjh1D//79ce+99yI2Nhb79+/H3LlzERISgj179rhlSgMivdL8jmaiK4WFhSEpKQnvvPMO0tPTERAQgEGDBuGll15iIRBdA9cUiIhIxX0KRESkYikQEZGKpUBERCqWAhERqVgKRESkYikQEZGKpUBERCqWAhERqVgKRESkYikQEZGKpUBERCqWAhERqVgKRESkYikQEZGKpUBERCqWAhERqVgKRESkYikQEZGKpUBERCqWAhERqVgKRESkYikQEZGKpUBERCqWAhERqVgKRESkYikQEZGKpUBERCqWAhERqVgKRESkYikQEZGKpUBERCqWAhERqVgKRESkYikQEZGKpUBERCqWAhERqVgKRESkYikQEZGKpUBERCof2QGI3M3hdOF8bjHOXSxCdoEdBSVO5Jc4UFjiREGJEwUljku/nSiyO6EAMJuUij+KArNZgZ/FjFA/C0L9rQjxtyDUz4IwfytC/S0I9rXAZFJk32Uit2EpkOZkF5Tg0Pk8HE7Pw+nsIpzPLcK5i6UlcO5iETLzS+AS9ZPFpAAhfhbEhfkhPswf8eH+iA/zK/0d7o9GYX6w+ZjrJwyRGyhCiHp6+xDVzJmcQhw6n1fu53B6HjLySmRHqzZFAaKDbEiMCkSrmCC0iQlGq5ggtIoJgq+FZUHeh6VAXqGgxIFdf+Rg+4ks7DiRjZ1/ZCMjr1h2LI/xMSloHh2I9nEh6BAXgo6NSn/7mLmbj+RiKZAUf2QWYNPRTOy4VAIHzuXCWV/bfLxUgNWMzglh6NYsAt2aReC6RiwJqn8sBaoXhUXF+OVQFtampWPdoQwcv1AgO5LX87eakXRZSVwfH8qd2uRxLAXynIw04OAy4OBy2LNOosW5f8hOpGkRAVb0bR2Nge1i0KtFJPdJkEewFMi9jm8A9n0LHFwOZB4u96dx/nOwKjNcUjB98bea0atFJAa2jUG/NtEI9bfKjkQ6wVKgusv+A9j1aelP5pEqz7a80VRMOtStHoMZg49JQZem4Rh6XSwGXxeLQBtHmlPtsRSodkoKgL3fADs/Bo6tA3Dtl1FmTE90PjbF89kMzM9iRkr7GNyV1AjdEyOgKNwHQTXDUqDqEwI4vh7Y+WlpIZTk1uziPr7oVDwPOXYuydaHuFA/DOsch7uS4tE4wl92HNIIlgJdW9bx/24eyjpWp6v6Z/Q/MPtEU/fkompRFODGJuG4/6YEpLZvCDNHMNFVsBSoaqd3Autmle44Fi63XOXe+FG4NW2IW66Lai4u1A9juzfByC7xCPK1yI5DXoilQBUdXVNaBod/dvtVl4Q0RUsOTZUu0OaD4Tc0wvgeTREfzk1L9F8sBSolBLD/u9IyOLXVozd1t+9cbMoO9uhtUPWYTQoGtm2AB3o1Q1JCmOw45AVYCkbndAC7PwfWvwGk76+Xm/y20f9i6qEb6uW2qPp6tYjEYwNboVN8qOwoJBFLwahKCoDtHwAb5gA5f9TrTafH9sWNRx6o19uk6uvfJhp/HtAS7WJDZEchCVgKRuNyATs+AH5+HshPlxJBWAPQPv9t5Ds52Zu3UhQgtX0M/ndASzSPDpIdh+oRS8FIjq0Dlj0JnN0tOwmej3gZ75yKlx2DrsGkAEOvi8VjA1txh7RBsBSMIOs4sGJ66dBSL7Ez/n7cnpYiOwZVk83HhAdvboYptzSHn5UT8ekZS0HPSvKBtf8ENvwLcBTJTlNOUXgrtD49Q3YMqqG4UD88fWsbDOrYUHYU8hCWgh4JAexaBPz0LJB7RnaaKg2xzMfu3ADZMagWuidG4Jmh7dCyAfc36A1LQW/+2AIsewI4tU12kmtaHDsNjx/pJDsG1ZKPScF9NyXgzwNaIpjfjtYNloJeFOcBK/4P2LYQ1Zmx1BuciUvGTYfHyI5BdRQVZMMLd3TAgLYNZEchN2Ap6MGJjcBXk+o8WV19E7YQtMz9N+wuTtCmB3deH4cZQ9ohxJ9rDVrGgeJa5igBVs4AFqRqrhAAQCnOwfAG3rvPg2rmyx2nMGDWL/hp3znZUagOWApade53YH5fYP3rbpvBVIbbA/fJjkBudD63GBMWbsVjn+9CTqFddhyqBZaC1rhcwLrXgXm3AOfkfwmtrtoXbpEdgTxgyfaTSJ61BqsOnJcdhWqI+xS0JOsY8NVk4MQG2UncRkBBf9M7OFzgJzsKeciEnk3xZGprWMxcBtUCPktasW0h8FYPXRUCACgQGNvgsOwY5EHvrjuKu976FX9kFsiOQtXAUvB29kLgiwnA0qlASZ7sNB7R2/yb7AjkYbtO5uDWN9di+e9nZUeha+DmI2+WcwpYNBo4s1N2Eo9y+UUiMfsNCMGhqUYw6eZmmJbSmseK9lJcU/BWf2wG5vfRfSEAgKkwA7dHy5nGm+rf22uOYPT8jTif613zcVEploI32vEx8P5gIM84472HBXNoqpFsOpqJ2+asx97TF2VHoSuwFLyJywksewr4ZgrgLJadpl5dV+z9czWRe53JKcLwub/i5/3GWfjRApaCtyjMBj6+C9j4b9lJpAhM34E4X2MVIQH5JU5M/GAbFqw/KjsKXcJS8AbpB0u/nXz4Z9lJpFGEE2NjjsmOQRI4XQLPLt2LGd/sgdPFcS+ysRRkS/sReKcfkMmx+v18ODTVyBZuOI4JC7cgr9ghO4qhsRRk+v1r4NORQDF3tgFAQvZG2RFIstUH0nHXW7/i/EWOTJKFpSDLrs+AL8YDLk4aVsacdwbJkRdkxyDJ9p/NxfC3N+BkFr8BLQNLQYbtHwBfTwaEU3YSrzMi7IDsCOQFjl8owN1vb8SxjHzZUQyHpVDfNs8Hvp2q6emuPSnJzqGpVOpUdiGGv70BB8/lyo5iKCyF+vTrbOD7v0Arh8uUISR9GyKs3KRGpdJzizFy3kbsOZUjO4phsBTqyy+vAiumy07h9RRnCcbEnJAdg7xIZn4JRs3fiG3Hs2RHMQSWQn346Tlg1fOyU2hGsm2P7AjkZXKLHLj/3U3YeixTdhTdYyl42vL/A9a+JjuFpiTm6OuYEeQe+SVOjHt/C34/zU1JnsRS8KSVM4ANc2Sn0ByfiyfQKzxbdgzyQrlFDox5bzOOclSSx7AUPGXzfGD967JTaNbo8IOyI5CXysgrwb3vbMLZHH7BzRNYCp5w4Afghydkp9C0Ls4dsiOQFzuVXYh7392ErPwS2VF0h6Xgbie3lX5TmV9Mq5PwjC0I8uEcOFS1Q+fzMHbBZs6V5GYsBXfKPAp8ejdg59fz60qxF+DehidlxyAvt+tkDiYu3IoSB78M6i4sBXcpyCw9HkI+DyvpLrf6/i47AmnAhiMXMP3r3bJj6AZLwR3sRcCno4ALh2Qn0ZVWeZtlRyCN+HzrSbyz9ojsGLrAUqgrlwv46kHgD0777G7WrDR0DuG8N1Q9L/6wH6sOnJcdQ/NYCnW1Yjqw9xvZKXTrvsg02RFII5wugamf7MCh81yQqAuWQl1seRfY+C/ZKXStu9gpOwJpSG6xAw8s3IrsAg5VrS2WQm2d2g4se1J2Ct2LvrAJfmYO76XqO3ahAA99tB0OJ0ck1QZLoTYKs4DFYwAnl0Y8TSnOxYgGZ2THII3ZcOQCXvxhv+wYmsRSqCkhgK8eArI5vXN9GRqwV3YE0qB31x3FT/vOyY6hOSyFmlr/BnDwB9kpDKVtwRbZEUij/rJ4F+dIqiGWQk2c2AT8/JzsFIbje2EvWgfyW+JUc1kFdkxdtANOF492WF0sheoqygG+fABwcZ6V+qZAYGz0YdkxSKM2H83Emz9xaHN1sRSq6z9/5n4EiXopO2VHIA2bs+oQNh65IDuGJrAUqmPnJ8CeJbJTGFrDCxthVjjEkGrH6RJ4dNFOZHKq7WtiKVzLhcPA94/LTmF4pqIsDGvAKQyo9s5eLMJfv+bxv6+FpXA1QgBfTQZK8mQnIQB3BO2THYE07rvdZ7Bsz1nZMbwaS+Fqti0ATnKmTm/RsYhDU6nu/vrNHuQU2mXH8FosharkpQM/PiM7BV3GP+M3NPbjmHOqm/TcYjz/H34hsioshaosf7p0GCp5DUW4MC7mqOwYpAOLt53EmoM8IFZlWAqVObIa2P257BRUiT7mXbIjkE489eVu5PP4zhWwFK7kKAa+e0x2CqpCfNZGKAq/nUp1dyq7EK8uPyA7htdhKVxp3SweVtOLmfPPY1BkhuwYpBMLNxzDbyezZcfwKiyFy104DKydKTsFXcPwUE6JTO4hBPAcdzqXw1K43Hf/CziLZaega7i+ZJvsCKQjW45lYemu07JjeA2WQpnfFpfuYCavF5S+AzE2TldA7vPSD/tRZOcR/gCWQqmii6VDUEkTFJcd98cclx2DdORUdiHeWXtEdgyvwFIAgI3/BvI5r46WDLDulh2BdObfqw/j/EV+OZKlUJgFbPi37BRUQ02zN8iOQDpTUOLEy8s4RJWl8OscoJjfXNYan9xT6BuRKTsG6cyXO05i90ljfx4YuxQKMoFNc2WnoFoaGXZQdgTSGSGAf6409tqCsUth/eucFlvDbnRwaCq53+oD6dh+Ikt2DGmMWwp554HN82WnoDoITd+KMAvnriH3m7nCuGuhxi2FdbMAe4HsFFQHirMY9zXkcbPJ/dYdysCWY8bcZ2XMUrh4Btj6nuwU5AYptt9lRyCdevOnNNkRpDBmKaz9J+DgeGQ9aH5xo+wIpFNr0zKw649s2THqnfFKIecksH2h7BTkJtaco+gaelF2DNKp2T8bb8Zk45XCulmAk/Pm6Mm9EcbdKUie9dP+c0g7lys7Rr0yVikU5wK7FslOQW7WzbVDdgTSKSFKj7lgJMYqhV2L+L0EHYrM2IwAs0t2DNKpL7efwsUiu+wY9cZYpcARR7qk2PMxOuak7BikUwUlTny+5Q/ZMeqNcUrh+K/AeR5hSa8G+3NoKnnOhxuPw+UyxrHBjVMKW96VnYA8qFX+ZtkRSMeOXyjA6oPGmF7fGKWQlw7s+1Z2CvIg38wD6BCULzsG6dj7vxrjwE7GKIUdH3IYqgGMiTLemHKqP2vT0nE4Xf8DVfRfCi4XsG2B7BRUD3ooHJpKniMEsGiz/ufa0n8pHPoRyNb/E0lATMZG2Ewcmkqe883O07rf4az/UtjKHcxGoRRfxPAGZ2THIB07n1uM9YczZMfwKH2XQvYfQNoK2SmoHt0WuE92BNK5r3ackh3Bo/RdCnu/AQQ3JxhJu8ItsiOQzi3fcxaFJU7ZMTxG36Wwb6nsBFTP/DL2ING/UHYM0rH8EidW7D0rO4bH6LcU8s4DJ/mFJqNRIDC2wWHZMUjn9LwJSb+lsP87bjoyqFvMv8mOQDq3Li0DGXnFsmN4hH5LgZuODCvuwgaYFS4QkOc4XALL9uhzE5I+S6EoBzi6RnYKksRUeAG3RafLjkE69/N+fc6FpM9SOLgCcBln/nOqaFjwftkRSOd+PZyBIrv+RiHpsxQ4+Z3hXVe8VXYE0rkiuwvrD+nvi2z6KwV7EXDoJ9kpSLKA9J2I89XnjkDyHj/pcBOS/krh8M+AnVMoG50inBgbc1R2DNK5VSwFDdj/H9kJyEv089ktOwLp3JmcIuw9fVF2DLfSXylwriO6JCF7o+wIZAA/7z8nO4Jb6asUMg4B+RyKSKXMeWeQGqW/HYHkXX45qK/PHH2Vwh+bZCcgLzM89IDsCKRzu07moNihn6GpOisFbi6g8pJKtsmOQDpX4nDht5M5smO4jb5K4QTXFKi84IztiLLyi4zkWVuOZcqO4Db6KYXCLCDjoOwU5GUUZwnujzkuOwbp3NZjWbIjuI1+SuGPzQD0fexUqp2Btj2yI5DObTueBSH08fmjn1I4wf0JVLnEHL42yLNyCu04eC5Pdgy30E8p/MED6lDlfC6eQK/wbNkxSOf0sl9BH6XgtAOnOMqEqjY6nPubyLO2HdfHfgV9lMKZ3wAHj8tLVevi3C47AuncvjP6mO5CH6XAL63RNYSnb0GQj0N2DNKxI+n5cDi1f8Q/fZTCmV2yE5CXUxyFuC/mpOwYpGMlTheOZGh/hmZ9lELmYdkJSANS/X6XHYF0bv/ZXNkR6kwfpXCBpUDX1iqXmxnJsw6c1f5+Be2XQmEWUKiPoWDkWdbsQ+gcov0lOfJeB85q/7sK2i+FC0dkJyANuS8yTXYE0rED57imIB/3J1ANdBc7ZUcgHTuZVYj8Ym2PctNBKXBNgaovOmMj/Mz6mfuevIsQwPELBbJj1In2S4E7makGlJI8jGxwWnYM0rHT2dr+Iq32S4Gbj6iGhgTslR2BdOx0DktBLq4pUA21KdgiOwLp2CmuKUhUkAkUZctOQRrjd2Ev2gRqe7svea8z2UWyI9SJtkuBawlUS2Oi+dohz+A+BZkunpKdgDSql7JTdgTSKZaCTNx0RLXU8MJGWEz6OHwieZdzucVwurT72tJ4KeTITkAaZSrKwrAGZ2XHIB1yugTSc4tlx6g1jZeC9r9STvLcHrhPdgTSqdwiu+wItabxUuCaAtVeh0IOTSXPuFik3akuWApkWP4XdqOJn7aHD5J34pqCLMXcfES1pwgXxsYclR2DdCiXawqScE2B6ugWMw/lSu7HUpCFpUB1FJ+1EYqi3eGD5J3yirn5SA6OPqI6Muefx+CoDNkxSGe4piAL1xTIDYaH7JcdgXSGpSCDywmUaP94qCRfp+KtsiOQzhQ7tHsgJ+2Wgr0AALcFU90FZexAjK1EdgzSEZdLdoLa024pQJEdgHRCcTkwNuaY7BikI06h3QVW7ZaCot3o5H36W3fLjkA64tJwKfjIDlBrLAVNE1BgN1vg8LHCbvKB3ccKh9kKu9kMu9kCu+IDh9kHdrMP7CYz7CYzHCYf2E0mOExm2BVT6b8VE+yKArtigkNRYFeU0t8A7ArggAK7ImCHgAO49FvALlywwwWHKP33oFMWfP/7fNkPC+mENawXgE6yY9QKS0EHHIq59MPVbLnsg9Zy2YfqpQ9YxQy7uezD1QyHyVR6WtmHq8l06UPVBLsC2HHpA1ZB6W8hLn3Qln642uG69AEr4Lj0IWsXLjiEE/ZLPw7hgt3lKD3N5YDdZYfD5YRDVDU6QwAoufRzBdelHw948hcBJe2gZ66cDMe/XRvZEWpNu6VgMrv9KgUUOC59sJb+WOHwsZR+sJZbejWXftBeWoIt/YAtXXot/a1c9uFafum19PeVH67/XXpVl2KFCw64YHeVfbhe+qC97APW4XLAIRxwiao+KR2XfircUcB56YfQp7AJzLtZCORGZu0utGq6FF7uPLh0KVUp+3DFZZsG/rv06hCu8kuuwgG7y1nuw9V+6QO2cnKWXql+jNodLDsC6YxiYilI8XnOfpS4OJSQaq+xMxRha/dwcDO5lwe2ZNQX7dYZAJuPTXYE0rjJx5pBlHDBgtzL5O8vO0KtabsUzCwFqj2rMKPFqiOyY5AOmYODZEeoNZYCGdaEjLYQ6ZwMj9zPFKTd/VSaLgVfs6/sCKRhvTdw7izyDHNQoOwItabpUgixhciOQBrVv6ApTL+nyY5BOsU1BUki/SJlRyCNGrlbu9t8yftxn4IkLAWqjSaOUASv5VxH5DlcU5Akyj9KdgTSoMlHmwF27R4ukbwf1xQkifCNkB2BNMYmzGi++pDsGKRzXFOQhJuPqKYmpreDKyNTdgzSMZO/P8yBAbJj1BpLgQyl568XZUcgnbPExcqOUCcsBTKMlPxEmPZx0xF5liU2TnaEOtF0KYT7hsPE4ypQNY3Ypd35aEg7LHEsBWnMJjNCbaGyY5AGJDrCEbiew1DJ81gKksUExMiOQBow6UgTwFHV8TKI3IelIFliSKLsCOTlfIUPmq7ilBZUP7ijWbJmoc1kRyAvN+lcO4jMLNkxyCC4piBZ89DmsiOQl+v+KwuB6ofi7w+f8HDZMepE86WQGMrNR1S1wXmJUA7wQDpUP2xNm8qOUGeaL4W4wDj4+fjJjkFeatguvjao/tjatJYdoc40XwomxYQmwU1kxyAv1MIRgYBf98iOQQbi27qN7Ah1pvlSALhfgSo36VACh6FSvfLlmoJ34AgkulKgsCJh9UHZMchIFAW2ViwFr8A1BbrSg2fbQGRly45BBmKJj9f07KhlWAqkS93Wc3psql++rbW/lgDopBQaBTXiAXdIdVtucyDtqOwYZDB62J8A6KQUAKBzg86yI5CXuGOnTXYEMiBbG+2PPAJ0VApJDZJkRyAv0NoeCf8NHIZK9UxR4HfddbJTuIVuSuGGBjfIjkBe4MG0xoDTKTsGGYytZUv4hIXJjuEWuimFFmEtEGQNkh2DJApy2RC/er/sGGRA/l26yI7gNropBZNiwvXR18uOQRJNPtsGIofHYKb6F9CVpeCVuF/B2G5cly47AhmRosD/Bv1svmYpkC7cmdsSOHxcdgwyIFvr1jCHhsqO4Ta6KoW2EW05Y6pB3bbdR3YEMqiALjfKjuBWuioFi8mCjlEdZcegetbe3gB+GzkMleTw79pVdgS30lUpAECvuF6yI1A9m3ggFnC5ZMcgIzKZdLU/AdBhKfRt3Fd2BKpHIS5fxHIYKkni37kzzMHBsmO4le5KIT4oHi3DWsqOQfVk8pnWELm5smOQQQUNHCA7gtvprhQAoF/jfrIjUD25Ye152RHIwIL695cdwe1YCqRZIy62hjh6QnYMMijfdu1giY2VHcPtdFkKrcJboVFgI9kxyMOGbFNkRyADCxqgv7UEQKelAHBtQe86lcTAtvl32THIwIIG6G9/AqDnUkhgKejZ+AMNOQyVpLE2awZbYqLsGB6h21LoFNUJkX6RsmOQB4S5/NDwl32yY5CB6XEHcxndloKiKOgT30d2DPKAh061hsjNkx2DDCw4JVl2BI/RbSkAwOBmg2VHIDdTBHD92jOyY5CB2dq0gW/btrJjeIyuS6Fzg85IDNHndj+jGpXTBuL4SdkxyMBChw2THcGjdF0KADCspb6fQKNJ3SZkRyADU2w2hAzR9xYI3ZfC0MShsJltsmOQGySVNIRtC4ehkjxBAwbAHBIiO4ZH6b4UQmwh6J+g35ECRjJufwwguKZA8oTepf8tD7ovBQAY1kL/T6TeRboC0GD1XtkxyMAs8fG6O3ZCZQxRCjfG3IgmwU1kx6A6eOhkS4j8fNkxyMBCh90JRdH/1CqGKAUAuKvlXbIjUC0pAui45pTsGGRkZjNC7rhTdop6YZhSGJo4FFaTVXYMqoV7s9tA/HFadgwysKABA2BpEC07Rr0wTCmE+YZxPiSNStnKOY5IrogJE2RHqDeGKQUAGNdunOwIVENdiuNg2cYdzCSPf9eu8OvQXnaMemOoUmgT0Qa94nrJjkE1MHZfFIehklQRDxhnLQEwWCkAwKTrJsmOQNUU7QxE1Gp+WY3ksbVujcBexlqQNFwpXBd1HbrG6H+ssR48dLIFRGGh7BhkYBETxsuOUO8MVwoAMLHjRNkR6BrMUND+F058R/JYYmMRnJoqO0a9M2QpdG3YFZ2iOsmOQVdxX2ZbiFOcIpvkCR87BoqPj+wY9c6QpQBwbcHbDdxilx2BDMwcEYHQu4z5hVfDlsLNjW5Gm/A2smNQJboXxcNnO4ehkjyRkx6Eyd9fdgwpDFsKANcWvNV9e8NlRyAD84ltiNCRI2XHkMbQpdC/cX+uLXiZGGcgItdwGCrJE/Xw/8BkNe6UOIYuBUVR8ESXJ2THoMs8dKIlRGGR7BhkUNbERITcfpvsGFIZuhQAIKlBEgYmDJQdgwD4CBPa/nJcdgwysOi/PAbFbJYdQyrDlwIAPHbDYzxkpxcYk9UW4sw52THIoPy7dEFQnz6yY0jHUgAQGxiL+9veLzuG4fXfyM1GJImiIHraNNkpvAJL4ZIHOjyAaD9jzJfujXoVNYZ5137ZMcigQoYOhV/7drJjeAWWwiX+Fn88kvSI7BiGde+eMNkRyKDMISGIfoJrCWVYCpcZ0mwIOkR2kB3DcOKcwQhfy2GoJEfUXx6DTzi/G1OGpXAZRVEw7UYuMdS3h443hyji/gSqf35JSYadzqIqLIUrdIruhKGJQ2XHMAyrMKPV6mOyY5ARWSxo+OwzUBRFdhKvwlKoxLQbpyHCN0J2DEMYe6ENxLnzsmOQAUWMGwdb8+ayY3gdlkIlQmwhmN5tuuwYhtBnY4HsCGRAlvh4RE55SHYMr8RSqEL/hP4YkDBAdgxd61PYBObdB2XHIAOK+dtfYfL1lR3DK7EUruL/uv4fwmwcKukpo3YHy45ABhRy++2GO+5yTbAUriLCL4KbkTyksTMUYWv3yI5BBmNp3BgNpvM9fTUshWsY2GQgBjcbLDuG7kw+2gyipER2DDISHx/EvfIyzIEBspN4NZZCNTzd9WnEBMTIjqEbVmFGi9VHZMcgg4l8aDL8OnWSHcPrsRSqIcgahOd7PA8FHM/sDhMy2kKkZ8iOQQbi17kzIidPlh1DE1gK1dS1YVeMaz9Odgxd6L0hT3YEMhBTYCBiX3nF8MdJqC6WQg1MvX4qusZ0lR1D0/oXNIXp9zTZMchAYv72V1gbxcmOoRkshRowm8x4pfcr3L9QByN/C5IdgQwkeOgQhAzltDU1wVKooXDfcMzsPRNWk3EP7F1bTRyhCF63W3YMMghb2zZo+Pe/y46hOSyFWugQ1QFPdHlCdgzNmXy0GWC3y45BBmAOD0f8nDn81nItsBRqaUSrEbi9+e2yY2iGTZjRfPUh2THICHx8EPf6LFhiY2Un0SSWQh1M7zYdbcLbyI6hCRPT28GVkSk7BhlAg6eeRECXLrJjaBZLoQ5sZhtm9ZmFEFuI7Cher9evF2VHIAMIuWsYwu+5R3YMTWMp1FFcYBxeufkV+Cg+sqN4rdT8RCj7uOmIPMuvUyc0/NvfZMfQPJaCG3SP7Y5nezzLbzxXYfguf9kRSOd8YmIQ9+YbUKwcFVhXLAU3GZo4FH9O+rPsGF4n0RGOwPUchkqeYw4JQeN35sMSHS07ii6wFNxoXPtxGNN2jOwYXmXSkSaAwyE7BumU4u+P+Lfn8rCabsRScLPHbniMU21f4it80HQVp7QgD7FY0OiN1znzqZuxFNxMURT8vcff0SOuh+wo0k063w4iM0t2DNIjRUHsCy/wCGoewFLwAIvJgpm9Z6JDZAfZUaTqvp6FQJ7R4KmnEDKEa+SewFLwEH+LP/7V719oEtxEdhQpBuclQjnAA+mQ+0VMnoTw+++THUO3WAoeFOYbhnkD5iEu0HjT9g7b5Sc7AulQ2D33IPrRR2XH0DWWgoc1DGyIhSkLDbXG0MIRgYBf98iOQToTPm4cYv46XXYM3WMp1IMGAQ3wfsr7aBnWUnaUejH5UAKHoZJbRTw0GQ2emCY7hiGwFOpJhF8E3kt+D+0j2suO4lGBworGqw/KjkE6EvXoo4h+5BHZMQyDpVCPQmwhmD9wPjpHd5YdxWMePNsGIitbdgzSiegnn0Dk5EmyYxgKS6GeBVoDMXfAXNzU8CbZUTyi23pOj01uoCiImfE3RIwdKzuJ4bAUJPDz8cOcfnNwS/wtsqO41W25zYG0o7JjkNaZzWj4/PMIGzVKdhJDYilIYjVbMeuWWbi16a2yo7jNHTttsiOQxpkCAxE/dy5Ch90pO4phsRQk8jH54OWbX8aUTlM0P+12W3sU/DdwGCrVniU2FgmffIzAXj1lRzE0loIXeOi6h/DPW/4JPx/tfuFrYlojwOmUHYM0yrdjRzT5/DP4tjTGsG1vxlLwEgMSBmBhykLEBMTIjlJjQS4bGq0+IDsGaVRQcjISPlgIn8hI2VEILAWv0iaiDT4d9Ck6RnWUHaVGJp9tA5HDYzBTzUVMnIi412fB5OsrOwpdwlLwMpF+kViQvABDmg2RHaXablyXLjsCaYxitaLhP/6B6Mf+F4qi7f1pesNS8EJWsxUv9HoBj3Z+FCbFu5+iYbmtgMPHZccgDbEkNEaTzxZxhJGX8u5PHIOb0GECZvedjTBbmOwoVRq6zSw7AmlIUGoKmi75Er5t2siOQlVgKXi5mxvdjC9v+xLdY7vLjlJBe3sD+G3iMFS6NsVqRcyMv6HRrFkwBwbIjkNXwVLQgEi/SMztPxeP3/A4LCaL7DiqiQdiAZdLdgzycpbGjdFk0af8hrJGsBQ0QlEU3N/ufnwy6BM0C2kmOw5CXL6IXb1fdgzyckEpKWj65RL4tm0rOwpVE0tBY1qHt8Zngz/DiJYjpOaYfKY1RG6u1AzkvUyBgWj4/HNo9PosmAMDZcehGlCEEEJ2CKqdn0/8jGd+fQZZxVn1ftuLF8VCHD1R77dL3i+ge3c0/MfzsDRsKDsK1QLXFDSsb+O+WDJ0Sb3PtjoipxULgSowBQQg5pkZaPzeuywEDeOagk6sOrEKL25+EWfyz3j8tj5c1Qa2jbs9fjukHYG9eyPmmRksAx1gKehIoaMQc3fNxQd7P4DD5ZljJHcqicHTs05z1BEBAMzh4Wjw9NMIGTxIdhRyE5aCDh3KOoTnNz2Pbee2uf2639x9PWL+s8Xt10saYzYj7O4RiPzTn+AT5r1frqSaYyno2DeHvsHMbTORWeSeQ2SGufww798CIjfPLddH2hTQvTsaPPUkbC1ayI5CHsBS0Lmc4hy8vv11LDm4BAJ1e6qf/uN6dPqIawlGZU1IQPQTTyCobx/ZUciDWAoGcSDzAObsnIPVf6yu1eUVAXz+aQzE8ZNuzUXezxQUhMgpUxB+7z1QLN7zjXryDJaCwexO343ZO2Zjw5kNNbrc6Ow2uP0tjjgyFIsFocPuRNTUqfAJD5edhuoJS8Ggtpzdgtk7ZmPH+R3VOv+HP7WGbTMnvzMCxWJByB13IOLBB2FtFCc7DtUzloLBrTu1DrN3zMbeC3urPE9SSUM8MfMkwJeKrilWK0LvGoaIiRP5fQMDYykQAOCn4z9hzs45OJR9qMLf5vx2PaK/4w5mvVJsNoQOH46IiQ/A0qCB7DgkGUuBVEIIrD+9Hh/8/oG6zyHSFYC35jgg8vMlpyN3M/n7l5bBAxPgExUlOw55CZYCVSotKw0f7v0Q160+ibYf1mynNHk3a7NmCBs9GiG338YZTKkClgJdlSMzE9mLv0DWZ4vgOO35eZXIQ8xmBPXtg7DRoxFw002y05AXYylQtQinE3mrVyPrk0+Rv2ED5z7SCHNEBEKH34Wwu+/mzmOqFpYC1Zj93Hlc/O475CxdiuJ9+2THoSsoFgsCbr4ZIYNuRVD//lCsVtmRSENYClQnxWlpyPl2KXK++w83L8lkMsG/axeEDBqEoIEDYQ4Olp2INIqlQG4hhEDh1q3I+XYpclesgDMnR3YkQ/C77joEDxqE4NQUjiAit2ApkNsJpxOFu3Yhb/UvyFuzBsX798uOpBu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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "school = { \n", + " \"1. Klasse\": 42,\n", + " \"2. Klasse\": 30,\n", + " \"3. Klasse\": 26,\n", + " \"4. Klasse\": 45,\n", + "}\n", + "\n", + "plt.pie(school.values()) # Pie Chart\n", + "\n", + "plt.title(\"Klassenverteilung einer Grundschule\")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "76e19a82-7aa7-416d-beae-667b77497cf3", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-aec08dc408437049", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Styling\n", + "\n", + "Alle Parameter wie `title`, `color`, `xlabel`, `ylabel`, etc. lassen sich auch für das Pie Chart setzen. Die Beschriftung der einzelnen Stücke jedoch Funktioniert etwas anders.\n", + "\n", + "Dazu wird der Parameter `label` mit den dazugehörigen Werten ausgestattet:" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "id": "09124a3e-1f76-4f32-8638-19e7efc234b0", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-c742155fd484b71b", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "school = { \n", + " \"1. Klasse\": 42,\n", + " \"2. Klasse\": 30,\n", + " \"3. Klasse\": 26,\n", + " \"4. Klasse\": 45,\n", + "}\n", + "\n", + "plt.pie(school.values(), labels=school.keys()) # Setzen der Labels\n", + "\n", + "plt.title(\"Klassenverteilung einer Grundschule\")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "d3e68330-6319-4a87-acda-91abd4f98900", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-5336af155ef45527", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "Zum setzen von Prozentwerten wird der Parameter `autopct` verwendet. Dieser nutzt einen Format String oder eine Funktion zum definieren der Werte. Schaue dazu für mehr in die Dokumentation für [autpct](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.pie.html#matplotlib-pyplot-pie), eine Dokumentation zu Formatstrings findest du [hier](https://www.geeksforgeeks.org/format-specifiers-in-c/).\n", + "\n", + "Beispiel für Prozentwerte:" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "id": "974a71d0-552c-45d4-bb01-88edd6be608c", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-183044afa87a0492", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "school = { \n", + " \"1. Klasse\": 42,\n", + " \"2. Klasse\": 30,\n", + " \"3. Klasse\": 26,\n", + " \"4. Klasse\": 45,\n", + "}\n", + "\n", + "plt.pie(school.values(), labels=school.keys(), autopct='%1.1f%%') # Setzen von Prozentwerten\n", + "\n", + "plt.title(\"Klassenverteilung einer Grundschule\")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "a0a13fc0-3ae1-4ab5-a488-8c5247cf74c5", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-430a11a7f58f4fa5", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "Pie Charts haben auch einen Parameter `shadow`. Dieser ist Standardmässig `False`. Setzt man den Wert auf `True` sieht man einen Schatten:" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "id": "62971d68-8cdd-48c4-8f60-209bffe64e84", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-408e63a1464d64ea", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "school = { \n", + " \"1. Klasse\": 42,\n", + " \"2. Klasse\": 30,\n", + " \"3. Klasse\": 26,\n", + " \"4. Klasse\": 45,\n", + "}\n", + "\n", + "plt.pie(school.values(), labels=school.keys(), autopct='%1.1f%%', shadow=True) # Zeige einen Schatten\n", + "\n", + "plt.title(\"Klassenverteilung einer Grundschule\")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "59e8be26-c070-4205-8260-f4597074ec6f", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-376fc818f2a3d818", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "Zum herausnehmen von Kuchenstücken gibt es den Parameter `explode` dieser erwartet eine Liste mit Fließkommezahlen die zwischen 0.0 - Standardwert und 1.0 - absoluter Explode liegen.\n", + "\n", + "Beispiel Klasse 3 ist vom Ursprung 20% entfernt:" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "id": "bf1ea228-1547-4c1d-975e-d7f49111486c", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-e3921561732c3895", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "school = { \n", + " \"1. Klasse\": 42,\n", + " \"2. Klasse\": 30,\n", + " \"3. Klasse\": 26,\n", + " \"4. Klasse\": 45,\n", + "}\n", + "\n", + "plt.pie(school.values(), labels=school.keys(), autopct='%1.1f%%', explode=[0, 0, 0.2, 0]) # Zeige einen Schatten\n", + "\n", + "plt.title(\"Klassenverteilung einer Grundschule\")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "cbe9aba9-529d-4d4c-87fa-ff46e3a24e5b", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-ed3d080835960776", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "source": [ + "## Aufgabe\n", + "\n", + "*5 Punkte*\n", + "\n", + "Ihnen ist ein Datenset `sec_school` einer Hauptschule gegeben, welches die Klassenstufen von 5 bis 9 auf die Anzahl ihrer Schüler im Jahrgang mappt. \n", + "\n", + "Definieren Sie einen Pieplot. Gehen Sie dabei wie folgt vor:\n", + "1. Definieren Sie ein geeignetes Farbschema zur Darstellung der Daten.\n", + "2. Extrahieren Sie die Schlüssel und Werte aus dem Datenset und übergeben Sie diese zusammen mit den Farbwerten an die Funktion `plt.pie`. (Nutzen Sie zum Anzeigen der Prozentwerte autopct='%1.1f%%')\n", + "3. Lassen Sie die 6. Klasse 25% und die 9. Klasse 40% explodieren.\n", + "4. Setzen Sie einen geeigneten Titel für den Plot.\n", + "5. Plotten Sie den Werte." + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "id": "5a2e4c2b-051d-4e9d-ae93-0e6fe4b25003", + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-bf48088c515caf5c", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [], + "source": [ + "sec_school = {\n", + " '5. Klasse': 29,\n", + " '6. Klasse': 35,\n", + " '7. Klasse': 25,\n", + " '8. Klasse': 28,\n", + " '9. Klasse': 31\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "id": "fdebbc40-17eb-48e5-89fa-f8d12ec65688", + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-d201bd3e919fcf1c", + "locked": false, + "points": 5, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# BEGIN SOLUTION\n", + "plt.pie(\n", + " sec_school.values(),\n", + " labels=sec_school.keys(),\n", + " autopct='%1.1f%%',\n", + " explode=[0, 0.25, 0, 0, 0.4]\n", + ")\n", + "\n", + "plt.title(\"Klassenverteilung einer Grundschule\")\n", + "\n", + "plt.show()\n", + "# END SOLUTION" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/Material/wise_24_25/lernmaterial/Datenanalyse/data_analsys.ipynb b/Material/wise_24_25/lernmaterial/Datenanalyse/data_analsys.ipynb deleted file mode 100644 index 903f18d..0000000 --- a/Material/wise_24_25/lernmaterial/Datenanalyse/data_analsys.ipynb +++ /dev/null @@ -1,821 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "0362a1eb-1e46-462a-b22c-f972c398741d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e3006ef8308b2f34", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# 7. Programmierübung: Datenanalyse\n", - "\n", - "
\n", - "
\n", - " Willkommen zur siebten Programmierübung Einführung in Python 3.\n", - "
\n", - " \n", - "
\n", - "\n", - "Wenn Sie Fragen oder Verbesserungsvorschläge zum Inhalt oder Struktur der Notebooks haben, dann können sie eine E-Mail an Phil Keier ([p.keier@hbk-bs.de](mailto:p.keier@hbk-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) oder Martin Le ([martin.le@tu-bs.de](mailto:martin.le@tu-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) schreiben.\n", - "\n", - "Link zu einem Python Spickzettel: [hier](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf)\n", - "\n", - "Der Großteil des Python-Tutorials stammt aus der Veranstaltung _Deep Learning Lab_ und von [www.python-kurs.eu](https://www.python-kurs.eu/python3_kurs.php) und wurde für _Signale und Systeme_, sowie _Einführung in die Programmierung für Nicht Informatiker_ angepasst.\n", - "\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "0a97a824-bc2f-4f9d-a730-42ff05828cc8", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a5071e148ad2227c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Data Analysis\n", - "\n", - "This exercise serves as preparation for the exam.\n", - "\n", - "This notebook includes the dataset `survey.csv`, which contains the data from the survey you completed.\n", - "\n", - "The data was generated from the following this [Survey](https://forms.gle/JVKq6FrSUE8kN7Jq6).\n", - "\n", - "Your task is to read in the data set `survey.csv` and check the following 4 hypotheses.\n", - "\n", - "One calculation is not enough! Write a paragraph after each calculation in which you briefly explain your calculation. (How did you proceed?, Which data were relevant to confirm/disprove the hypothesis?) Present your results in a suitable way. You can use plotting tools, maps or text. The easier & more obvious the result is to interpret, the better.\n", - "\n", - "Also explain how you interpret your result (In German or English). Numbers don't mean anything, their interpretation does!\n", - "\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "602be29c-d586-41d2-8c25-660faa8a619d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-954c00c5bbcf2e7f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Setup\n", - "\n", - "In the next cell, import all the libraries & functions you use." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "0731fc85-90eb-477e-8dd5-d2bcc3eeb16c", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-36fdb907d2bc33b3", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "dd1c8fdc-a349-4a70-9335-c08bc00a676a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8e13f4b8f08d4cbb", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Next read in the dataset `survey.csv`. For testing puposes use the Variable Name `df`." - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "9e276245-83dc-460a-b81b-ddd7ad8e5978", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d4b0d9ce1f988100", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "df = pd.read_csv(\"survey.csv\")\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "fba07368-225f-42bf-82fa-85070d59eba0", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-a7ce1cba9e2fde7a", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "assert isinstance(df, pd.DataFrame)" - ] - }, - { - "cell_type": "markdown", - "id": "e81b8e60-b946-4822-8acb-6a63aefd51df", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d27e9df7f4255151", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "These next Cells you can use to analyse the dataset. Feel free to alter it to your needs." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "50e52cf6-ae36-4f80-b9a1-73a089939a69", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-928097dcba5a7f09", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d64a606c-68bb-4a46-8169-af34a07228f9", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-afd1d2c0d85ce40e", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "ad9d17d9-dd59-4766-bb46-de4df822ce0f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3da446eb91bdd35d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Hypothesis 1\n", - "\n", - "__The average age in the course is 25.34 years, with a surplus of females.__" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "8e24289e-a738-4ae4-a6d4-a936263120fc", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-a6a23c7c132e44d9", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Mean Age: 22.64\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "print(\"Mean Age:\", df[\"Age\"].mean())\n", - "c = df[\"Sex\"].value_counts()\n", - "plt.style.use('https://github.com/dhaitz/matplotlib-stylesheets/raw/master/pitayasmoothie-dark.mplstyle')\n", - "plt.title(\"Gender Distribution\")\n", - "plt.bar(c.keys(), c, color=[\"black\", \"white\"])\n", - "plt.show()\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "0058bf53-8169-4098-ad28-ad7036bcdaf7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f01beca6d16a140e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Use the next cell to write your Interpretation." - ] - }, - { - "cell_type": "markdown", - "id": "80cf1c27-644a-4538-abbc-7d5f524251d7", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-9cbb6c488a06eb18", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "source": [] - }, - { - "cell_type": "markdown", - "id": "171340b9-0302-4c7c-ac85-f81d1e57a9da", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3fc34b3f943dfa4b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Hypothesis 2\n", - "\n", - "__The most used voice assistant is Alexa.__" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "98fb0abc-0d50-4f4c-aeb0-16b056aeeabf", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-b28aca63b8048f70", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "c = df[\"Voice Assistent\"].value_counts()\n", - "plt.style.use('https://github.com/dhaitz/matplotlib-stylesheets/raw/master/pitayasmoothie-dark.mplstyle')\n", - "plt.title(\"Voice Assistent Distribution\")\n", - "plt.bar(c.keys(), c, color=[\"red\", \"green\", \"blue\"])\n", - "plt.show()\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "4a75600e-27e1-439e-820b-49a5340b22a3", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5db1eeca82b4c33b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Use the next cell to write your Interpretation." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5ee59b36-a147-4940-be03-d923c7131bfa", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-016f2b30651bea18", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "3b77bda1-5851-4394-81c7-fd649cb980e5", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-fae767f8aab85e92", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Hypothesis 3\n", - "\n", - "## Hypothesis 3.1\n", - "\n", - "__The least used smartphone operating system is iOS.__" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "0d74bd0d-e83e-4211-bc58-b9615e36b848", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-34a9cdeebcf2d7b9", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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AAIBxaQ6M6tWe1OYNszV5wuBkxzg7Zdfnq2dq/Oh+9zU5AACQNTmkZXDXTi3UpkU9Xbzkm+K4vr3ay83V+b4mBgAAsq40ncGIiopWvyFv6fIVv2THlCxRSE0b1tDWbT/d9+QAAEDWlKYzGBu+2HHPMaNe6akFn6zXYwXyys3N5R6j+bO+jxa+3sCjgWP94RaXqlFpCox7adu6gaKjb+mbb/eqT492KY51cvaQxS59rjGdP2NgumwXeBi8NPLjzJ4CHmLOrp6ZPQWkswhrQKrGGQuMXLnc1bdnew199d1UjY+MCBKVC2S8CGtgZk8BDylnV0++v2BjLDCGDeqir7Z8pwsXr6ZhrdSdZgFgEscd0sOdvzDyPQaDgfFM01oKCbWq/bONJElO2bPJYmenWk9XVKsOw0ztBgAAZAHGAqNdpxEJPu78fHPl8fLU3AVrTO0CAABkEWkKjF0+i+NXsreXJNX1qSJJatSiv677ByUYa7VGKod7VKLnAQDAwy9NgdGoRf9Uj12yYlNa5wIAAB4S/C0SAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4xzSukL1ak/qjTH99evhk3pzyoIEyxrUq6be3dvqsQJ5FBAQrNXrfPTVlu+NTRYAAGQNaQqMrp1aqE2Lerp4yTfRMu8yxTVxzAC98fZ87TtwRNWqlNP0Ka/o7wtXdeTon8YmDAAAHnxpeokkKipa/Ya8pctX/BIty5nDTctXbdaefYcVGxunn385pjNnL6hi+TIpbNGSTg8AyUuv447Ho/24U2bPhUfGfa2Tl6YzGBu+2JHssgMHj+rAwaO2j+3t7OTl5aGg4JAkxzs5e8hixyUgQEZzdvXM7CngIcb318MvwhqQqnFpvgYjtQYPeEFRUdH6dte+JJdHRgQpLSUEwIwIa2BmTwEPKWdXT76/YJMugTG4//Nq2rCGho2crsjIqBRGxqXH7gGkiOMO6eHOXxj5HoPhwLBYLBo/uq/KlimhAcOmyNcvdadRAADAw8VoYAx/qauKFnlMg4a/o9BQq8lNAwCALMRYYJQv97iaNn5a3fqMIy4AAHjEpSkwdvksjl/J3l6SVNeniiSpUYv+atWintzdXLVxzQcJ1jny+ymNeH2GibkCAIAswlK8bLOH7mqcpQvGZfYUgAdW78FTM3sKeChZ7riL5KH7sYL/gDeiAAAAxhEYAADAOAIDAAAYR2AAAADjCAwAAGAcgQEAAIwjMAAAgHEEBgAAMI7AAAAAxhEYAADAOAIDAAAYR2AAAADjCAwAAGAcgQEAAIwjMAAAgHEEBgAAMI7AAAAAxhEYAADAOIfMngAA/BfnOm3P7CkAD7Tia5tl6v45gwEAAIwjMAAAgHEEBgAAMI7AAAAAxhEYAADAOAIDAAAYR2AAAADjCAwAAGAcgQEAAIwjMAAAgHEEBgAAMI7AAAAAxhEYAADAOAIDAAAYR2AAAADjCAwAAGAcgQEAAIwjMAAAgHEEBgAAMI7AAAAAxqU5MKpXe1KbN8zW5AmDEy1r3LCG1iybpl0+i7Xykyl6qmo5I5MEAABZS5oCo2unFhoxtJsuXvJNtKxMqaKaMLqfFi/dqGfavqR1G7dr2uSXlcfLw9hkAQBA1pCmwIiKila/IW/p8hW/RMtatain/QePatf3BxUVFa3NW3/QX+cu6ZmmtYxNFgAAZA0OaRm84YsdyS4rU6qo9h34PcFzp06fl3fp4ils0ZKW3QMwguMOeDSk17Eel6pRaQqMlOTM4aaQUGuC50JCrSpRvFCS452cPWSx4xpTIKM5u3pm9hQAZID0OtYjrAGpGmcsMJLrmbi4pJdERgSJ36SAjBdhDczsKQDIAJl9rBsLjODgUOXM4ZrguVw53RUUHJrCWqk7zQLAJI474NGQuce6sdcoTp46pzKliiV4rqx3cZ04+ZepXQAAgCzCWGB8tfV7Va/2pBo3qK5s2RzVsV0TFSyQVz7f7jG1CwAAkEWk6SWSXT6L41eyt5ck1fWpIklq1KK/zp2/rMlTP9ag/s9r/Ov99fffVzR6wocKCgoxPGUAAPCgS1NgNGrRP8Xl3/90SN//dOi+JgQAALI+7hMFAADGERgAAMA4AgMAABhHYAAAAOMIDAAAYByBAQAAjCMwAACAcQQGAAAwjsAAAADGERgAAMA4AgMAABhHYAAAAOMIDAAAYByBAQAAjCMwAACAcQQGAAAwjsAAAADGERgAAMA4AgMAABhHYAAAAOMIDAAAYByBAQAAjCMwAACAcQQGAAAwjsAAAADGERgAAMA4AgMAABhHYAAAAOMIDAAAYByBAQAAjCMwAACAcQQGAAAwjsAAAADGERgAAMA4AgMAABhHYAAAAOMIDAAAYByBAQAAjCMwAACAcQ4mN1a6VFENHdhJpUsVU3R0tA4cPKY5C1YrJMRqcjcAAOABZ+wMhp2dRTOmvqpjf5xV6+eGqWvvccrtmVMjh/c0tQsAAJBFGAuM3J65lNszp7bv3Kdbt2IUGmrVD3t+VZlSRU3tAgAAZBHGAuO6f5BOnT6vZ1vWV/bs2ZQrp7vq16mqvfuPpLCWJZ0eAJKXXsddRj8ApCxzjz2j12BMmDxPH04fpU4dm0uSDv32hxZ+uiHJsU7OHrLYcY0pkNGcXT0zewoAMkB6HesR1oBUjTMWGI6ODpr+ziva9d3PWr5qs5ycs2v0iF56c+wAjZv0UaLxkRFB4rcQIONFWAMzewoAMkBmH+vGTiFUq1JOj+XPo0VLP1dE5E0FBYVoyfJNql+3mnLmcEtmrbh0egBIXnoddxn9AJCyzD32jAWGxSJZLAnPSNg72EuSYuP4nwEAAI8SY4Fx7I8zCo+IVN8e7ZUtm6Pc3VzUvXMr/X7stEJDeR8MAAAeJcYCIyTEqpFjP1CF8qX01frZWrPsXcXExmri2/NN7QIAAGQRRu8iOXHqnIa99p7JTQIAgCyI+0QBAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMc0iPjfbs1kYd2jaWi4uTjv9xVu99sFRXr/mnx64AAMADyPgZjHZtGqpOrcoaMPRtdej8qnz9AtTl+WdM7wYAADzAjJ/B6PpCC016Z6F8/QIkSdNmLElhtMX07gHcE8cd8GhIr2M9LlWjjAaGl1cu5cvrqUIF82ni2AHKkcNNvxw6rhlzVigkxJpgrJOzhyx2XAICZDRnV8/MngKADJBex3qENSBV44wGRl4vT8XFSXVrV9GAYW/LKXt2TXlziMa82lvjJn2UYGxkRJD4TQrIeBHWwMyeAoAMkNnHutFTCA4O9nJ0dNCCxesUEmKV3/VAfbLsC9WtXUXZHB2TWCMunR4Akpdex11GPwCkLHOPPaOBERIa/zJImDXc9ty1a/6ys7OTh4e7yV0BAIAHmNHAuHjJV2Fh4fIuVcz2XP78Xrp165b8/YNN7goAADzAjAZGTEyMNvv8oMH9X1AeLw95euRUnx5t5fPtXsXExprcFQAAeIAZv0114Sfr9fLgLlqx+G3FxMbqp32HNWfeatO7AQAADzDjgXHrVow+mPuZPpj7melNAwCALII3ogAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBx6RYYLw/uoj07l6XX5gEAwAMsXQKjVMkieqZZ7fTYNAAAyAKMB4bFYtGoV3rqf+u3md40AADIIowHRtvWDRR586a279yXitGWdHoASF56HXcZ/QCQssw99hzMfBLxPDxyqE+Pdho6Yto9xzo5e8hixzWmQEZzdvXM7CkAyADpdaxHWANSNc5oYLw8qIu+2vKdLly6pvz5vFIcGxkRJH4LATJehDUws6cAIANk9rFuLDCqVi4r7zLFNG3GkjSsFWdq9wBSjeMOeDRk7rFuLDCaN6mlvHk89cXaDyRJdpb4sxNbNs7VB3M/087dB0ztCgAAPOCMBcbcBWu0eOlG28d583hq0UdvqNeAiQoJtZraDQAAyAKMBUZoWLhCw8JtH9vb20uSrvsHmdoFAADIItLtNo5rvv6q3bhXem0eAAA8wLhPFAAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMYRGAAAwDgCAwAAGEdgAAAA4wgMAABgHIEBAACMIzAAAIBxBAYAADCOwAAAAMY5mNxY/nxeemVIV1UsX1oxMbHaf/CoZs9bpdCwcJO7AQAADzijZzDemzJcN0LC1KHLa+o54A0VK1JAQwZ2MrkLAACQBRgLDFdXZ508dU4LPlmviMibCgi8oa3b96hShTKmdgEAALIIYy+RWK0RmjZjSYLn8uX1VFBwaAprWUztHkCqcdwBj4b0OtbjUjXK6DUYd/IuXUzPt2+q8ZM+SnK5k7OHLHZcYwpkNGdXz8yeAoAMkF7HeoQ1IFXj0iUwypd7XNOnvKIFn6zXvp9/T3JMZESQ+E0KyHgR1sDMngKADJDZx7rxwKhds5ImjhmgmXNXavuOffcYnbrTLABM4rgDHg2Ze6wbDYwnn3hcE0b304S35ungoeMmNw0AALIQYxdB2NvZaczI3vro47XEBQAAjzhjZzCeLPe4ihctqNeG99Brw3skWNal5xj5+qXuohAAAJD1GQuMI0f/VO3GvUxtDgAAZGHcJwoAAIwjMAAAgHEEBgAAMI7AAAAAxhEYAADAOAIDAAAYR2AAAADjCAwAAGAcgQEAAIwjMAAAgHEEBgAAMI7AAAAAxhEYAADAOAIDAAAYR2AAAADjCAwAAGAcgQEAAIwjMAAAgHEEBgAAMI7AAAAAxhEYAADAOAIDAAAYR2AAAADjCAwAAGAcgQEAAIwjMAAAgHEEBgAAMI7AAAAAxhEYAADAOAIDAAAYR2AAAADjCAwAAGAcgQEAAIwjMAAAgHEEBgAAMI7AAAAAxhEYAADAOAIDAAAYR2AAAADjHExuLH8+L416pacqli+tyMib2rLtRy38ZIPi4uJM7gYAADzgjAbGtMnDdO7vy2rfeYQ8PHLqg3dfU2BQiNZu2GZyNwAA4AFn7CUS7zLFVbJEYc36aJVCw8J14eJVfbZmi9q1bmBqFwAAIIswdgajTKmiuubrr9BQq+25U6fPq0jhAnJxdlJ4RGQSa1lM7R5AqnHcAY+G9DrWU3fZg7HAyJnDXSEhYQmeC/knNnLlck8mMNLn2ozeg6emy3YBPDiKr22W2VMAHnCZe/2jwbtIkv9EuMgTAIBHi7HACAoOVY4cbgmey5XTXZIUHBxqajcAACALMBYYJ0+dU/58XsqRw9X2XFnv4jp3/rIiIm+a2g0AAMgCjAXG6bMXdOLUXxox9EW5ubqoRPFC6t65lTZs2mFqFwAAIIuwFC/bzNgFEnm8PDR6RC9VqeSt8IhIbfxyl5au/NLU5gEAQBZh9K3Cr/sHadT4WWrcaqDadBxOXDzE8uXNrV0+i1W4UL7MngqATNSudUNtWDXjP6+/Ztk0tWlZL8ll2RwdtWfnMlWu6P2ft4/MY/SdPPHo8PULUKMW/W0fFymUX727t1XVKk/I1cVJwTdCtWf/ES1d+aWCgkJs41xdndWvZ3vVqVVZnh45FBF5UydOntPCT9fr7F+XMuNTAR5J1auW06zpo/T5lzv1wZyVmTaPLr3GZtq+kb74Y2e4b6VKFtHieRPlHxCs3gMnqnGrgXrplanKns1RSxdOllfuXLax40b2VfFiBTV81HQ1bjVQL/YZLz//QM1+f7ScnbJn3icBPGJat6yvb3ftV9OGNZTN0TFd9mGx8KZujzICA/9J/nxe2rNzmYoULqARw17UgV+Oad6itQoIvCFJ8vUL1LQZS3Tl6nUN7v+Cbb2nqpbTZp8fdOXqdUlS8I1Qzf5oteYu+J8cHOwz5XMBHjU5criqTq3KWrx0o4JDwlSvThXbsvkfjlP3Lq00cewAfbt5gTaumanGDarblj/hXULLFr2lHV9/rA+nj5SHh7ttWeWK3vr264Xq2K6Jvv16ocqXe1yS1LZ1A61aMlXfbl6gJQsnqcZT5W3rbFg1Q+1aN5QkOTll06Txg/TNl/O1buV01a5ZKZ3/JZCeCAzcF0+PHKpYvrQ+T+Zuoc837VD9OlVlbxf/rXbxsq86tmuigo/ltY2Jio7Wth17FRoWniFzBh51LZrW1pkzF3T5ip+279in1i3+vQYiJiZWHdo2ls/2PWre9iVt37lfI4f3kCTZ2Vk05c0h+vmXY2rZfqgWL/tCz7ZqkGDbDvb2KlQwn1q1H6bfj51W7ZqVNLj/C5o+a5latB+q1Wt9NH3KcBUv+liiefXs1kaPlyysF/uOU78hk9W4YfVEY5B1EBi4L9HRtyRJFy5dS3L5hYvX5OycXR6eOSRJU95dJGen7Fq3crr+t/xdjR7RS3VqVpKdHadSgYzSukU9fbNjryRp2469qlKprPLn87ItP3r8jA4eOq7Y2Djt3H1AOXK4ycMjh7xLF1e+vLm1cvXXioqO1vE/zuqnvb8l2Ha2bI76cst3ioqOtu1r5+4DOnL0T926FaMduw/ozF+X1LB+4nioV7uqvvr6e/n7ByskxKpV/9uajv8KSG8EBu7L7TC4fYbibpbb4fDPzdDn/r6iXgMnqu/gSfpq6/fKm8dDU94cqkVz3+AaDCADlCtbUoUL5dfO3QckSVeuXtexP86o1TN1bGOu+frb/vtmVHwoZM+WTXnzeCosLDzB2cZLV/wS7cPXN8D23wXye+niZd8Ey69cva7HCnjdvZry5vFIsO+kto2sg7tIcF/i4qRbMTEqUriA/AOCEy0vXCi/wsLCFRh0I8HzJ/88r5N/ntfqtT4qUii/Pl04Sc80q60vvtqVQTMHHk1tWtaTvb2dNqz+99ZSRwcH5c3jqSUr4t9aIDY26bdHcnRM/CMjqV8ubt2Kuec8kvoTVY53XWya3C8uyBoIDNyXkFCrfjn0hzo/31y/Hj6RaHnHdk2087ufFRsbp+LFCqp9m4aaPW+1YmJjbWMuXLqmK1evK+ddf8sGgFnOTtnVuEF1vf/hch367USC5xfPm6hqVZ5IcX3/gGC5ubnI1dVZVmuEpPhfIlJy5YpfovfLKVwwn7778Zckt583r+e/43ifnSyNPMR9mz1vlco/8bheHfai7ZbUfHk9NWZkH3nlzqWPP90gSQoKClGTRk9r1Ku9lO+f/4m4ubqo03PNVLhQfv2499fM+hSAR0LjhjV0MypaW7f9pMtX/GyPM39d1E/7Die42DMpx0+c1Y2QML3YuaUcHR1U4clSerp6+RTX2bz1BzVpUEPlyz0uR0cHtWxeR0WLFNCOf16iudP+n3/Xsy3rK7dnTuXM4abOHZ+5r88XmYszGLhvFy5dU9+XJqtPj7b6ZP6bcndzUVBwqH7a+5v6vTRZN0LCJMXfkjpo2BT17tFWH899QzncXRUaFq6Tp87p5dfe4422gHTWukVdfbtzf5IvYWz55gdNnfyyLiZzwbYkRUVFa+zEORo5vIde6NBMR4+f0Zp136hrpxbJrrPv59+1ZOWXmjxhsNzdXXX+7ysa8foMXbrrugxJmr94ncaN6qvVS6cpJNSq2fNWqdbTFbmFPYsy+rdIAAAAJF4iAQAA6YDAAAAAxhEYAADAOAIDAAAYR2AAAADjCAwAAGAcgQEAAIwjMAAAgHEEBgAAMI7AAAAAxhEYAADAuP8DyXxnMdVl9GYAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "os_dict = {\n", - " \"iOS\": 0,\n", - " \"Android\": 0\n", - "}\n", - "\n", - "for data in df[\"Which Smartphone\"]:\n", - " if data == \"Apple\":\n", - " os_dict[\"iOS\"] += 1\n", - " else:\n", - " os_dict[\"Android\"] += 1\n", - "\n", - "plt.style.use('https://github.com/dhaitz/matplotlib-stylesheets/raw/master/pitayasmoothie-dark.mplstyle')\n", - "plt.title(\"Mobile OS Distribution\")\n", - "plt.bar(os_dict.keys(), os_dict.values(), color=[\"silver\", \"green\"])\n", - "plt.show()\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "66c12b57-0ae2-48eb-8c73-589949a2952d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2545dc88c22ab5c1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Use the next cell to write your Interpretation." - ] - }, - { - "cell_type": "markdown", - "id": "b9bb8c23-e161-492c-b1ee-9cc4c21c2325", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-81264718d58ae0f6", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "source": [] - }, - { - "cell_type": "markdown", - "id": "4481b1f2-a8af-4731-9890-17a4047e2f80", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8005ff19d1e616f6", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Hypothesis 3.2\n", - "\n", - "__The most used desktop operating system is Windows 10.__" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "id": "99f4c2ad-c162-461e-9632-fdc2cbc541fc", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-b706b4487a333142", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "os_dict = df[\"Which OS\"].value_counts()\n", - "\n", - "plt.style.use('https://github.com/dhaitz/matplotlib-stylesheets/raw/master/pitayasmoothie-dark.mplstyle')\n", - "plt.title(\"Desktop OS Distribution\")\n", - "plt.bar(os_dict.keys(), os_dict, color=[\"grey\", \"silver\", \"cyan\", \"yellow\"])\n", - "plt.show()\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "ea7ce7b6-5ba9-4185-b33b-c6e5f9e349f6", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-66d7fa91478051d4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Use the next cell to write your Interpretation." - ] - }, - { - "cell_type": "markdown", - "id": "93f04e29-58f3-4ea5-8af2-369061308915", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-4bf7225f7d1963f7", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "source": [] - }, - { - "cell_type": "markdown", - "id": "3fa617bb-77dd-4c43-b30b-b422eac770ef", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d532947366781d90", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Hypothesis 4\n", - "\n", - "## Hypothesis 4.1\n", - "\n", - "__The youngest people use an iPhone.__" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "id": "18467418-586b-4153-9066-0de730994e8e", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-5284bedc957436b3", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "age_mean = df[\"Age\"].mean()\n", - "youngest = {\n", - " \"ios\": 0,\n", - " \"Android\": 0,\n", - " \"n\": 0,\n", - " \"ratio iOS\": 0,\n", - " \"ratio Android\": 0\n", - "}\n", - "\n", - "oldest = {\n", - " \"ios\": 0,\n", - " \"Android\": 0,\n", - " \"n\": 0,\n", - " \"ratio iOS\": 0,\n", - " \"ratio Android\": 0\n", - "}\n", - "\n", - "\n", - "for index, row in df[[\"Age\", \"Which Smartphone\"]].iterrows():\n", - " if age_mean > row[\"Age\"]:\n", - " youngest[\"n\"] += 1\n", - " if row[\"Which Smartphone\"] == \"Apple\":\n", - " youngest[\"ios\"] += 1\n", - " else:\n", - " youngest[\"Android\"] += 1\n", - "\n", - " if age_mean < row[\"Age\"]:\n", - " oldest[\"n\"] += 1\n", - " if row[\"Which Smartphone\"] != \"Apple\":\n", - " oldest[\"Android\"] += 1\n", - " else:\n", - " oldest[\"ios\"] += 1\n", - "\n", - "\n", - "youngest[\"ratio iOS\"] = youngest[\"ios\"] / youngest[\"n\"] * 100\n", - "youngest[\"ratio Android\"] = youngest[\"Android\"] / youngest[\"n\"] * 100\n", - "\n", - "oldest[\"ratio iOS\"] = oldest[\"ios\"] / oldest[\"n\"] * 100\n", - "oldest[\"ratio Android\"] = oldest[\"Android\"] / oldest[\"n\"] * 100\n", - "\n", - "plt.style.use('https://github.com/dhaitz/matplotlib-stylesheets/raw/master/pitayasmoothie-dark.mplstyle')\n", - "plt.title(\"iOS Ratio between mean Age\")\n", - "plt.bar([\"Age under Mean iOS\", \"Age under Mean Android\", \"Age over mean iOS\", \"Age over mean Android\"], \n", - " [youngest[\"ratio iOS\"], youngest[\"ratio Android\"], oldest[\"ratio iOS\"], oldest[\"ratio Android\"]], color=[\"gold\", \"silver\"])\n", - "plt.show()\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "7b853c11-405a-470a-806f-da7851d86d12", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-492ea1226901c0e4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Use the next cell to write your Interpretation." - ] - }, - { - "cell_type": "markdown", - "id": "3f5dace2-5a13-4806-946c-0d0e4c9bc307", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-90f0108fe83268c7", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "source": [] - }, - { - "cell_type": "markdown", - "id": "c6fdcfa2-5507-4c85-b262-c83e6b1074ee", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-6ace0ffb9a32d3b1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Hypothesis 4.2\n", - "\n", - "__Older people use an Android-based smartphone.__" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5a76e273-a649-4bdf-ba8d-bc1351d0ec08", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-18c2e79244ca1beb", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "06313381-3ba3-4a0b-af75-2dfaf3d7acf2", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3a88641157327c7d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Use the next cell to write your Interpretation." - ] - }, - { - "cell_type": "markdown", - "id": "8bd2c8fa-801a-4c0a-8754-61bdc2f8127b", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-a421f0cc1a31c697", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/Datenanalyse/survey.csv b/Material/wise_24_25/lernmaterial/Datenanalyse/survey.csv deleted file mode 100644 index d1e8039..0000000 --- a/Material/wise_24_25/lernmaterial/Datenanalyse/survey.csv +++ /dev/null @@ -1,26 +0,0 @@ -Age,Sex,Scale Python Exp,Course,Has Voice Assistent Contact,Voice Assistent,Scale Study Satisfaction,Uses Smartphone,Which Smartphone,Has Computer,Which OS,Scale Programming Exp -22,Männlich,4,Medienwissenschaften,Ja,Apple Siri,4,Ja,Apple,Ja,Mac OS,2 -26,Weiblich,3,Medienwissenschaften,Ja,Amazon Alexa,2,Ja,Xiaomi,Ja,Windows 10,3 -21,Männlich,3,Medienwissenschaften,Ja,Google Now,4,Ja,Sonstige,Ja,Windows 10,3 -26,Weiblich,4,Medienwissenschaften,Ja,Apple Siri,4,Ja,Samsung,Ja,Windows 10,2 -24,Weiblich,4,Psychologie,Nein,,4,Ja,Apple,Ja,Windows 11,3 -23,Männlich,3,Medienwissenschaften,Ja,Amazon Alexa,4,Ja,Samsung,Ja,Windows 10,3 -21,Männlich,3,Medienwissenschaften,Ja,Amazon Alexa,4,Ja,Samsung,Ja,Windows 10,2 -22,Weiblich,4,Medienwissenschaften,Nein,,3,Ja,Samsung,Ja,Windows 10,2 -19,Weiblich,4,Medienwissenschaften,Ja,Apple Siri,3,Ja,Apple,Ja,Windows 11,2 -21,Weiblich,4,Medienwissenschaften,Ja,Google Now,3,Ja,Samsung,Ja,Windows 10,2 -20,Weiblich,4,Medienwissenschaften,Ja,Apple Siri,4,Ja,Apple,Ja,Mac OS,2 -21,Weiblich,4,Medienwissenschaften,Nein,Apple Siri,4,Ja,Apple,Ja,Mac OS,2 -21,Weiblich,4,Medienwissenschaften,Ja,Amazon Alexa,3,Ja,Samsung,Ja,Windows 11,4 -20,Männlich,4,Medienwissenschaften,Nein,,3,Ja,Samsung,Ja,Windows 10,3 -22,Weiblich,4,Medienwissenschaften,Ja,Apple Siri,2,Ja,Apple,Ja,Windows 11,2 -22,Weiblich,4,Medienwissenschaften,Ja,Amazon Alexa,3,Ja,Apple,Ja,Mac OS,1 -21,Weiblich,4,Medienwissenschaften,Nein,,3,Ja,Apple,Ja,Mac OS,4 -19,Männlich,3,Medienwissenschaften,Ja,Apple Siri,4,Ja,Apple,Ja,Windows 10,2 -30,Weiblich,3,Medienwissenschaften,Ja,Apple Siri,3,Ja,Apple,Ja,Mac OS,2 -27,Weiblich,4,Medienwissenschaften,Ja,Apple Siri,3,Ja,Apple,Ja,Windows 11,2 -22,Weiblich,5,Medienwissenschaften,Ja,Amazon Alexa,5,Ja,Xiaomi,Ja,Linux,1 -21,Männlich,5,Medienwissenschaften,Ja,Apple Siri,4,Ja,Apple,Ja,Windows 10,2 -30,Männlich,4,Medienwissenschaften,Ja,Amazon Alexa,3,Ja,Samsung,Ja,Windows 11,2 -23,Weiblich,5,Medienwissenschaften,Ja,Apple Siri,2,Ja,Apple,Ja,Mac OS,1 -22,Weiblich,3,Medienwissenschaften,Ja,Apple Siri,4,Ja,Apple,Ja,Mac OS,3 diff --git a/Material/wise_24_25/lernmaterial/Einführung/Tut_1.ipynb b/Material/wise_24_25/lernmaterial/Einführung/Tut_1.ipynb deleted file mode 100644 index ed2e9dd..0000000 --- a/Material/wise_24_25/lernmaterial/Einführung/Tut_1.ipynb +++ /dev/null @@ -1,2044 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "92fe3a94-61b2-47f9-9485-02aa8b103d5c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e72aa2f84c4b1cb7", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "# 1. Programmierübung: Python Tutorial\n", - "\n", - "
\n", - "
\n", - " Willkommen zur ersten Programmierübung Einführung in Python 3.\n", - "
\n", - " \n", - "
\n", - " \n", - "Python ist eine universelle Programmiersprache, die aufgrund ihrer Einfachheit sehr leicht zu lernen und zu bedienen ist. Die Funktionalität kann durch den Import von Bibliotheken erweitert werden. Im Folgenden werden wir Ihnen zeigen, wie man hier im Jupyter Notebook Python Code ausführen kann. Die grundlegenden Konzepte und Strukturen in Python werden mit Hilfe von externen Quellen gezeigt. Die Übungsaufgaben dienen zum Testen und der Hands-on-Praxis des gelernten Wissens. \n", - "\n", - "In diesem Jupyter Notebook werden die grundlegende Funktionen und Konzepte in Python vorgestellt. Dazu wird es kleine Programmierübungen um das gelernte Wissen in Beispielen anzuwenden. (Objekt Orientierte Programmierung werden wir in diesem Kurs nicht behandeln!)\n", - "\n", - "Das Jupyter Notebook ist in Zellen unterteilt, die durch Boxen gekennzeichnet sind, die einzeln ausgeführt werden können (entweder über `Shift + Enter` oder den `Run`-Knopf). Sie können auch alle Zellen im Notebook ausführen über `Kernel > Restart & Run All` oder dem \"Vorspulen\"-Zeichen.\n", - "\n", - "Bitte beachten Sie, dass alle Zellen im Notebook ein gemeinsamen Workspace nutzen. Das bedeutet, dass Bibliotheken nur einmal importiert werden müssen und dann innerhalb des Notebooks genutzt werden können. Es können jedoch auch Variablen überschrieben werden, wenn diese nicht richtig gekapselt werden (z.B. über Funktionen).\n", - "\n", - "Viel Spaß und Erfolg!\n", - "\n", - "Es gibt _sehr_ viele weitere Python-Tutorials online, z.B. auf [Youtube](https://youtu.be/kqtD5dpn9C8), mit denen Sie die benötigten Grundlagen für Python lernen können.\n", - "\n", - "Wenn Sie Fragen oder Verbesserungsvorschläge zum Inhalt oder Struktur der Notebooks haben, dann können Sie eine E-Mail an Phil Keier([p.keier@hbk-bs.de](mailto:p.keier@hbk-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) oder Martin Le ([le@tu-bs.de](mailto:martin.le@tu-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) schreiben.\n", - "\n", - "Link zu einem Python Spickzettel: [hier](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf)\n", - "\n", - "Der Großteil des Python-Tutorials stammt aus der Veranstaltung _Deep Learning Lab_ und von [www.python-kurs.eu](https://www.python-kurs.eu/python3_kurs.php) und wurden für _Signale und Systeme_, sowie _Einführung in die Programmierung für Nicht Informatiker_ angepasst.\n", - "\n", - "---\n" - ] - }, - { - "cell_type": "markdown", - "id": "6ac5a9e3-7190-4db6-859b-3cb1511fe29f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c8293a61ad8fb19c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "# Printing\n", - "\n", - "Für viele Anwendungsfälle ist es wichtig, dass der Computer mit uns als Mensch kommunizieren kann. Zu diesem Zweck lernen wir zuerst wie wir eine Ausgabe erzeugen können. Hierzu verwenden wir die Funktion `print()`.\n", - "\n", - "[print()](https://www.w3schools.com/python/ref_func_print.asp) ist eine BuiltIn Funktion, zu diesen später mehr. Es soll aber gesagt sein, dass keinerlei anstrengungen notwendig sind um die Print-Funktion zu verwenden, da Python sie von Haus aus kennt.\n", - "\n", - "## Hello World\n", - "\n", - "Schauen wir uns nun folgend ein einfaches Programm an:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "3733ea3b-12b5-4c1c-9b03-0f1c397babfc", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5f71f94cf9d603e2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hello World\n" - ] - } - ], - "source": [ - "print(\"Hello World\")" - ] - }, - { - "cell_type": "markdown", - "id": "708d34f1-a479-4277-90e7-14d67a8c688a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d49c16a44b1d3984", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Der Teil in den Klammern ist der Wert den wir ausgeben wollen in diesem Fall eine einfache Zeichenkette (auch dazu später mehr).\n", - "\n", - "Damit zu ersten **Aufgabe**: Geben Sie den Text `Hallo Python` aus. *1 Punkt*" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "88b8d4db-6f4c-411c-b8ad-d2d6ca0b427c", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-cd36c0330024bfe5", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hallo Python\n" - ] - } - ], - "source": [ - "# BEGIN SOLUTION\n", - "print(\"Hallo Python\")\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "ad8d06df-5d3d-4203-b17c-227a663c8e7b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-95b07b67b0ede718", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "# Datentypen und Variablen\n", - "\n", - "Python unterstützt verschiedene Datentypen. Zu diesen Zählen :\n", - "1. Integer (Ganze Zahlen) $$\\mathbb{Z} = \\{1,-1,2,-2,3,-3,\\dots\\}$$\n", - "2. Floatings Point Numbers (Fließkommazahlen) $$\\pi = 3.141592653589793$$\n", - "3. Strings (Zeichenketten)\n", - "> \"Ich bin eine Zeichenkette\"\n", - "\n", - "4. Listen\n", - "> [Objekt1, Objekt2, 42]\n", - "\n", - "5. Dictionaries\n", - "> {\"Schlüssel1\": \"Wert1\", \"Schlüssel2\": \"Wert2\",}\n", - "\n", - "6. Sets\n", - "> {\"Wert1\", 7, \"Zeichenkette\"}\n", - "\n", - "7. Tupel\n", - "> (42, 7)" - ] - }, - { - "cell_type": "markdown", - "id": "313d37b0-52ad-4de4-9fc5-0f362bfe7284", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-12a63250c85469f1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "## Zahlentypen (Floats, Integers)\n", - "\n", - "### Aufgabe 1-1: Zuweisungen von Variablen" - ] - }, - { - "cell_type": "markdown", - "id": "65dae625-2f0b-46d2-803c-c3d6c54000f7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-782aef1600674714", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Eine Definition und Zuweisung eines Wertes zu einer Variablen erfolgt über den `=` Operator." - ] - }, - { - "cell_type": "markdown", - "id": "fca50dd5-4a56-451a-9a1a-6cbd8d76519a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-7b71098cec169f0f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe** *2 Punkte*: \n", - "\n", - "Definieren Sie zunächst die zwei Variablen `a` und `b` und initialisieren diese mit einem Integerwert ungleich `0`:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "d7d24e44-8581-4c5c-a723-83b9f7e418ac", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-7be930fd387f1043", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "scrolled": true, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "a = 1\n", - "b = -2\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "8cfd850c-02c7-4b32-b20c-e37f5eb4fe8b", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-d44ec6114b65557c", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "assert isinstance(a, int)\n", - "assert isinstance(b, int)\n", - "\n", - "assert a != 0\n", - "assert b != 0" - ] - }, - { - "cell_type": "markdown", - "id": "337fbcc5-c960-4206-83d1-605d05a51d5d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2f79b7b52775db8b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe** *2 Punkte*:\n", - "\n", - "Definieren Sie zwei Variablen `s` und `t` und initialisieren diese mit einem Floatwert ungleich `0`:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "03b7469a-4f59-437f-aa8f-797d200b41a1", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-7d48f9bed0df944d", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "s = 1.5\n", - "t = -2.7\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "45404bbe-2026-491d-9aef-9d3ee8894adf", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-3b426f39262c1e03", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "assert isinstance(s, float)\n", - "assert isinstance(t, float)\n", - "\n", - "assert s != 0\n", - "assert t != 0" - ] - }, - { - "cell_type": "markdown", - "id": "5452589d-5997-4e8f-b8bb-363925c6166a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8690aecc1748ad4a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Aufgabe 1-2: Operationen auf Zahlen\n", - "\n", - "Aus der Schule sollten die folgenden Grunlegenden Operationen die sich auf Zahlen ausführen lassen bekannt sein:\n", - "\n", - "1. Addition $\\Rightarrow a+b=c$\n", - "2. Subtraktion $\\Rightarrow a-b=c$\n", - "3. Multiplikation $\\Rightarrow a\\cdot b=c$\n", - "4. Division $\\Rightarrow\\frac{a}{b} = c$\n", - "> Teilt man zwei Integer durcheinander werden diese erst in Floats umgewandelt und dann als Float gespeichert: $$10/3=3.3333333333$$\n", - "> Die Integer Division (Ganzzahl Division $\\lfloor\\frac{a}{b}\\rfloor$) (Notiert mit \"//\") zweier Zahlen schneidet den Rest nach dem Komma ab: $$10//3\\equiv 3$$\n", - "\n", - "5. Modulus $\\Rightarrow a\\mod b \\equiv c$\n", - "> \"Teilen mit Rest\" (in Python notiert mit \"%\" hat nichts mit Prozenten zutun) funktioniert genauso wie man die Uhr lesen würde. Ist es 15 Uhr sagt man im Sprachgebrauch 3 Uhr (Mittags). Der Modulus Operator funktioniert genauso. $$15 \\mod 12 \\equiv 3$$\n", - "\n", - "6. Exponentation $\\Rightarrow a^b = c$\n", - "> In Python notiert mit \"a**b\"" - ] - }, - { - "cell_type": "markdown", - "id": "9e408960-4180-4e92-ba88-ebf39441dfa7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c4551eabf148e18e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe** *2 Punkte*:\n", - "\n", - "Addieren Sie die Werte der Variablen `a` und `b` und speichern Sie das Ergebnis in der Variable `c`:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "6aaa0c05-ae16-4c48-b841-79931dae94bd", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-2ff97153b6652687", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "-1" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# BEGIN SOLUTION\n", - "c = a + b\n", - "# END SOLUTION\n", - "c" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "2fa4d7f2-235d-411e-956c-4ff335705124", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-3ba3833c7220bbb7", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "assert isinstance(c, int)\n", - "### BEGIN HIDDEN TESTS\n", - "assert a + b == c\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "9fccb90e-1f22-46b9-99a1-14b64274ece5", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f80a3165c27dc297", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe** *5 Punkte*:\n", - "\n", - "Nutzen Sie die Variablen `a` & `b` und Speichern Sie die Ergebnisse für die Multiplikation, Division, Ganzzahldivision, Exponentiation und den Modulo-Operator in den unten angegebenen Variablen:\n", - "\n", - "\\begin{align}\n", - "m &= a\\cdot b\\\\\n", - "d &= \\frac{a}{b}\\\\\n", - "i &= \\lfloor\\frac{a}{b}\\rfloor\\\\\n", - "e &= a^b\\\\\n", - "r &= a\\; \\textrm{mod}\\; b\n", - "\\end{align}\n", - "\n", - "\n", - "Die Ausführung der anderen arithmetischen Operationen in Python erfolgt analog. Eine Übersicht können Sie [hier](https://www.python-kurs.eu/operatoren.php) entnehmen." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "30ce28b3-b97d-4b3f-bac0-6d01356dcc60", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-3f3640eaf7ee2dd3", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "m = a*b\n", - "d = a/b\n", - "i = a//b\n", - "e = a**b\n", - "r = a%b\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "95108d9d-4cba-489b-bdbc-ed5c71316ac8", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-804a957c4a02e824", - "locked": true, - "points": 5, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "assert m == a*b\n", - "assert d == a/b\n", - "assert i == a//b\n", - "assert e == a**b\n", - "assert r == a%b\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "444c4633-9186-497f-88a7-e2ec0013dff4", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-7ac5c4d8e6463b16", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "## Sequentielle Datentypen\n", - "\n", - "Sequentielle Datentypen sind ein wichtiger Bestandteil in der Programmierung. Dazu gehören Listen, Tupel und Strings.\n", - "\n", - "Wichtige Eigenschaften dieser Datentypen sind:\n", - "- Die Elemente von Listen, Strings oder Tupeln sind in einer bestimmten Reihenfolge angeordnet (Diese entspricht der Ordnung in der die Elemente eingefügt worden).\n", - "- Der Zugriff (Lesen und Schreiben) dieser Objekte erfolgt über Indizes (Das erste Element eines Sequentiellen Datentypes ist immer `0`).\n", - "- Zugriff auf Elemente kann auch Rückwärts erfolgen das letzte Element wird dann mit `-1` ausgelesen. \n", - "\n", - "Beispiel für eine Liste:\n", - "`some_list = [\"a\", \"b\", \"c\"]`\n", - "\n", - "Beispiel für ein Tupel:\n", - "`some_tuple = (1, 2, 3)`\n", - "\n", - "Beispiel für ein String:\n", - "`some_string = \"Python ist cool!\"`\n", - "\n", - "### Aufgabe 2-1: Strings\n", - "\n", - "Zeichenketten, Text oder Strings lassen sich in Python mit `'Text'`, `\"Text\"` oder der Funktion `str()` definieren.\n", - "\n", - "**Aufgabe** *2 Punkte*:\n", - "\n", - "Ein String-Objekt (Text) können sie mit Hilfe von `'Some Text'` oder `\"Some Text2\"` definieren. Definieren sie die Variable `text` mit einem beliebigen Text." - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "f8028cf5-0dc4-4e72-a98e-3e18705c8c98", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-73a9beb04648359b", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "text = \"Hi Mom, I am on TV!\"\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "7a6832ae-e6c7-4230-b3ca-b1f1f90345fb", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-1677fa4f3b4eec12", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "assert isinstance(text, str)" - ] - }, - { - "cell_type": "markdown", - "id": "8e10cd2a-53dc-485f-bbdd-aa2709574660", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-05f0b0cd1211c396", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Python Strings lassen sich mit verschiedenen mitteln formatieren. Dazu zählt die [format-Funktion](https://www.w3schools.com/python/ref_string_format.asp) \n", - "\n", - "**Aufgabe** *1 Punkte*:\n", - "\n", - "Geben Sie die Variablen `a` & `b` aus Aufgabe 1 im format `\"a = 12 und b = 12\"` (Die Werte sollen dann den Werten aus ihrer Definition entsprechen. 12 ist hier nur ein Beispiel) aus." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "d3efbadb-3c33-40eb-9260-8f8b11faaf75", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-c94a5b5e9f73479e", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "a = 1 und b = -2\n" - ] - } - ], - "source": [ - "# BEGIN SOLUTION\n", - "print(\"a = {} und b = {}\".format(a, b))\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "d860edba-749c-41c0-827b-0c68ba6fd00a", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-e4c5420224d04f6a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Aufgabe 2-2: Listen \n", - "\n", - "Listen lassen sich mit der Funktion `list()` oder `[]` definieren und können eine \"unendliche\" Menge an Elementen unterschiedlichen Datentyps speichern. Die Liste `[420, \"Hallo Jupyter\", 0.222]` ist eine Korrekt definierte Liste. Im Allgemeinen ist es Ratsam listen mit gleichem Datentyp zu füllen, da dies bei der Verarbeitung zu Problemen führen kann." - ] - }, - { - "cell_type": "markdown", - "id": "51416edc-4c96-437c-a1ff-c458f06c9e8a", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-36d12824040df91e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe** *1 Punkte*: \n", - "\n", - "Definieren Sie die Variable `l` und weisen Sie dieser Variable eine Liste mit aufsteigenden Integerwerten von `0` bis `4` zu." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "b361ee09-cd48-4c16-89ea-714ee8ab541f", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-89d74b5c210fc331", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "l = list(range(5))\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "65fcfdb4-58ff-47d3-bebd-d3786a971af2", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-589caab43851d55a", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "assert isinstance(l, list)\n", - "assert l == [0, 1, 2, 3, 4]\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "a6dfba7d-4bb5-4530-bb75-689843a718a8", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-5ca56027cd6a5698", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe** *1 Punkte*:\n", - "\n", - "Hängen Sie der Liste `l` noch den Wert `42` an.\n", - "\n", - "Hinweis: Nutzen Sie dafür die Methode [.append](https://www.w3schools.com/python/ref_list_append.asp)." - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "e39e50dc-3d97-4579-aeb4-04ec2de3dbb3", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-853db222010bee68", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "l.append(42)\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "53000a6c-1187-48b0-b038-129d434cc45a", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-c1aca9603460d1de", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "assert l == [0, 1, 2, 3, 4, 42]\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "4510d2f3-3386-4d33-baa5-1d684ab52370", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c58e5530e380c09a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Zugriff auf Elemente eines Sequentiellen Datentypes lassen sich über `[]` realisieren.\n", - "\n", - "Beispiel - Zugriff auf das erste Element einer Liste:" - ] - }, - { - "cell_type": "code", - "execution_count": 114, - "id": "259d73e8-eca3-4172-8a0a-1efbbe3b527b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-cb1b7e8055910efc", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "0" - ] - }, - "execution_count": 114, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "l[0]" - ] - }, - { - "cell_type": "markdown", - "id": "bf6d1243-9650-4c27-b3dc-86a2d48b3abc", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1d8edfe975ed19bf", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe** *1 Punkte*:\n", - "\n", - "Geben Sie das dritte Element der Liste `l` aus.\n", - "\n", - "Hinweis: Achten Sie darauf das der erste Index immer `0` ist. " - ] - }, - { - "cell_type": "code", - "execution_count": 115, - "id": "358a0b51-3bfa-4e65-9cd4-ee2e7f8bc9d5", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-a386250119dc89fb", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2\n" - ] - } - ], - "source": [ - "# BEGIN SOLUTION\n", - "print(l[2])\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "2f25fa6d-9a72-464b-ada6-d2630dd03e92", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0ff369c64d2f8c24", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe** *1 Punkte*:\n", - "\n", - "Geben Sie das vorletzte Element der Liste `l` aus.\n", - "\n", - "Hinweis: Achten Sie darauf das der letzte Index mit `-1` ausgegeben wird" - ] - }, - { - "cell_type": "code", - "execution_count": 116, - "id": "16ec2e20-e28e-41de-8f85-1091e41bb401", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-2394235b49ebb749", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "4\n" - ] - } - ], - "source": [ - "# BEGIN SOLUTION\n", - "print(l[-2])\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "291522bc-9c4d-4348-b2cb-99f9653168fa", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c8fe8cb9d2ca1028", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Aufgabe 2-3: Dictionaries\n", - "\n", - "Das Dictionary ist ein Datentyp, welcher Schlüssel-Werte-Paare speichert. Dabei wird ein Dictionary mit `dict()` oder `{\"Schlüssel1\": \"Wert1\"}` initalisiert. Wichtig ist hierbei das ein Dictionary nicht mit `{}` initialisiert werden kann da dies die Notation für das **Set** Objekt ist.\n", - "\n", - "**Aufgabe** *1 Punkte*:\n", - "\n", - "Initialisieren Sie die Dictionary Variable `my_dict` mit folgendem Mapping:\n", - "\n", - "| Key | Value |\n", - "|:----|:------|\n", - "| `\"apple\"` | `\"Apfel\"` |\n", - "| `\"banana\"` | `\"Banane\"` |\n", - "| `\"cherry\"` | `\"Kirsche\"` |" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "c17338bb-c6df-493c-9d88-0e9ea36a755d", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-86ce3695bf3f6780", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "my_dict = {\"apple\": \"Apfel\", \"banana\": \"Banane\", \"cherry\": \"Kirsche\"}\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 118, - "id": "a367442e-2c8c-4d32-8acb-5bccf94d64fb", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-969a9415b60857a8", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "assert isinstance(my_dict, dict)\n", - "### BEGIN HIDDEN TESTS\n", - "assert my_dict == {\"apple\": \"Apfel\", \"banana\": \"Banane\", \"cherry\": \"Kirsche\"}\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "8ec10cc1-4b8b-4b53-b1d1-991d6287abda", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0f5df3b99a4774ba", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe** *1 Punkte*:\n", - "\n", - "Fügen Sie nun das Key-Value Paar `\"pear\": \"Birne\"` zu `my_dict` hinzu." - ] - }, - { - "cell_type": "code", - "execution_count": 119, - "id": "d3aac185-2d6e-4b30-b247-89be8aeeab7d", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-ed3cf3b9d6a8ad58", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "my_dict[\"pear\"] = \"Birne\"\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 120, - "id": "c377ec37-b382-4f83-a9cc-829a44b7682e", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-9735fc9ff4416c4c", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "assert my_dict == {\"apple\": \"Apfel\", \"banana\": \"Banane\", \"cherry\": \"Kirsche\", \"pear\": \"Birne\"}\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "2b3cfdf2-6864-402c-9ded-9fd0c7c489ee", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-957ca6c50c1cfb70", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Für gewisse Anwendungen reicht es nur die Schlüssel (oder Werte) aus einem Dictionary zu haben. Dazu bietet das Dictionary die Funktionen `.keys()` (für eine Liste der Schlüssel) und `.values()` (für eine Liste der Werte).\n", - "\n", - "**Aufgabe** *1 Punkte*:\n", - "\n", - "Geben Sie die nur die Werte des Dictionaries `my_dict` aus." - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "03f2c31a-04b4-4dc7-ab00-476cec6922ad", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-f190c63e28ae9e82", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "dict_values(['Apfel', 'Banane', 'Kirsche'])\n" - ] - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "print(my_dict.values())\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "6e774e49-895b-4bb2-9436-cddb75a3d46d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5bd0f8a189d6db1c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Wichtiger für die meisten Probleme ist die Dictionary Funktion `.items()` diese gibt eine Liste an Tupeln mit den Schlüssel Werte Paaren aus.\n", - "\n", - "**Aufgabe** *1 Punkte*:\n", - "\n", - "Geben Sie die Elemente des Dictionaries `my_dict` mit der Funktion `.items()` aus. " - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "a399cf66-43eb-4749-8864-18c5e4202f79", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-03afb00cc074d1ef", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "dict_items([('apple', 'Apfel'), ('banana', 'Banane'), ('cherry', 'Kirsche')])\n" - ] - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "print(my_dict.items())\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "a8d62b7e-ae53-4bd7-a930-84508c3948f9", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-83b1e45bc901dc68", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "# Funktionen\n", - "\n", - "Mit einigen Funktionen haben wir uns bereits befasst dazu zählen `print()`, `.keys()` und alle weiteren die diesem Schema folgen.\n", - "\n", - "In diesem Kapitel wollen wir uns mit dem Aufbau von Funktionen befassen. Dabei folgt jede Funktion folgendem Aufbaue:\n", - "\n", - "```python\n", - "def some_function_name(param1, param2):\n", - " a = do_something1(param1)\n", - " b = do_something2(a, param2)\n", - " do_something3(b)\n", - " return b\n", - "```\n", - "\n", - "Das `def`-Schlüsselwort leitet die Definition einer Funktion ein, gefolgt von dem Funktionsnamen, den Eingabeparametern der Funktion in runden Klammern und einem Doppelpunkt. Wichtig ist, dass die Anweisungen innerhalb der Funktion eingerückt sein müssen. Das Ergebnis (oder die Ergebnisse) werden mit Hilfe des `return`-Schlüsselworts gekennzeichnet.\n", - "\n", - "**Aufgabe** *1 Punkte*:\n", - "\n", - "Schreibe eine Funktion `successor` die auf jede Eingabe `+1` rechnet." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "1a151db2-617c-48f4-969b-3bafb45b1fd1", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-c6a731a4a13b2bbc", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "def successor(n):\n", - " return n+1\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 124, - "id": "615a98b6-139e-485b-874e-d0a70cd22517", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-00693d8d9c92af76", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "assert successor(1) == 2\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "d6f47a61-b692-4f46-8ccc-83af10189f93", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-9c358751403a1986", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe** *1 Punkte*:\n", - "\n", - "Schreibe eine Funktion `add` mit den Eingabeparametern `a` & `b`, welche die Werte von `a` & `b` miteinander addiert." - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "3f101d21-aa1a-4bf3-aadf-bb4e41d8fe12", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-2b72cf583fed9b8c", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "def add(a,b):\n", - " return a+b\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "1d155c26-0875-4a71-8564-a4a0e0e3bb70", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-7a24b5cfd7fc9990", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "assert add(1,2) == 3\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "d77ab363-9fe0-4504-b43b-6f7894666525", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0fd1dbfed99faa8a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "# Kontrollstruckturen\n", - "\n", - "## Aufgabe 3-1: Conditionals - If-Else\n", - "\n", - "Um Entscheidungen treffen zu können nutzt man in Python das Kommando `if ` ist der Ausdruck wahr wird der darauf folgende Code ausgeführt.\n", - "\n", - "Liste von möglichen Ausdrücken:\n", - "\n", - "- `a == b` checkt ob die Werte `a` & `b` gleich sind\n", - "- `a != b` checkt ob die Werte `a` & `b` **nicht** gleich sind\n", - "- `a > b` checkt ob der Wert `a` größer als `b` ist (Analog dazu \"größer gleich\" `a >= b`)\n", - "- `a < b` checkt ob der Wert `a` kleiner als `b` ist (Analog dazu \"kleiner gleich\" `a <= b`)\n", - "- `not ` invertiert das Ergebnis des Ausdruckes, also aus einem wahren Ausdruck wird ein falscher und andersherum.\n", - "\n", - "Zur Verkettung von Ausdrücken:\n", - "\n", - "- ` and ` checkt ob die Ausdrücke `ausdruck1` & `ausdruck2` wahr also erfüllt sind\n", - "- ` or ` checkt ob einer der Ausdrücke `ausdruck1` & `ausdruck2` wahr also erfüllt sind\n", - "\n", - "Beispiel:" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "4363cda5-98c5-4424-8fb3-7c92e1994993", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-020d46673782a358", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "You're the Number One\n" - ] - } - ], - "source": [ - "zahl = 1\n", - "if zahl == 1:\n", - " print(\"You're the Number One\")\n", - "\n", - "if zahl == 2:\n", - " print(\"You Lose\")" - ] - }, - { - "cell_type": "markdown", - "id": "21a23914-d0b7-492d-bcfe-8ecde9c20c85", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-aa2d59d677afd5a3", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Das Kommando `else` funktioniert nur zusammen mit dem `if` Kommando und bietet dem Programm eine Art \"Fall Back\":" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "3eaf3062-ae81-48c0-802d-88a72db587be", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f4124dd62687158f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "You're not the Number One\n" - ] - } - ], - "source": [ - "zahl = 5\n", - "if zahl == 1:\n", - " print(\"You're the Number One\")\n", - "else:\n", - " print(\"You're not the Number One\")" - ] - }, - { - "cell_type": "markdown", - "id": "7e35f339-3f59-4fd6-a162-e6eb0379c778", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-167fb232c7163fe6", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Um auf mehrere Ausdrücke zu checken kann das `elif` verwendet werden. Es findet seinen Platz zwischen `if` & `else`:" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "e37dd53c-e375-4548-9563-c8c6664dfdd0", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-0c0312666fa7648f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "You're the Number Two\n" - ] - } - ], - "source": [ - "zahl = 2\n", - "if zahl == 1:\n", - " print(\"You're the Number One\")\n", - "elif zahl == 2:\n", - " print(\"You're the Number Two\")\n", - "elif zahl == 2:\n", - " print(\"You're the Number Three\")\n", - "else:\n", - " print(\"You're not the Number One\")" - ] - }, - { - "cell_type": "markdown", - "id": "5248404d-4717-462d-a67f-57431e599945", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-060bd6eb927fa8b1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe** *1 Punkte*:\n", - "\n", - "Schreibe eine Funktion `is_odd` mit einem Eingabeparameter `n` die prüft ob die eingegebene Zahl ungerade ist.\n", - "\n", - "Wenn die Zahl gerade ist gebe den Text `\"Gerade Zahl\"` und bei ungerade `\"Ungerade Zahl\"` zurück." - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "d4b1cef3-6222-438d-bbc3-243431fad0cb", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-77afd241bc69d6b1", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "def is_odd(n):\n", - " if n % 2 == 0:\n", - " return \"Gerade Zahl\"\n", - " else:\n", - " return \"Ungerade Zahl\"\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "141d73da-90e6-401a-a651-ad14635de5b7", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-d8541ba8c61147c3", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "assert is_odd(2).lower() == \"Gerade Zahl\".lower()\n", - "assert is_odd(3).lower() == \"Ungerade Zahl\".lower()\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "c0086b8c-da02-4fdf-8341-9c0518bb6406", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-69409d8dcfe070e1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "## Aufgabe 3-2: Sequentielles - While Loop\n", - "\n", - "*7 Punkte*\n", - "\n", - "Schleifen sind wichtig um eine Aufgabe öfter zu wiederholen. \n", - "\n", - "Schauen wir uns dazu zunächst den `while`-loop an. Die Syntax schaut wie folgt aus:\n", - "\n", - "```python\n", - "while :\n", - " do_something()\n", - "```\n", - "\n", - "Solange der Ausdruck nach dem `while` wahr ist wird die Schleife ausgeführt. **!Vorsichtig!** solange der Ausdruck wahr bleibt und nie falsch wird hört die Schleife nie auf zu laufen.\n", - "\n", - "**Aufgabe**: Schreibe eine Funktion `fubar` mit Eingabeparameter `n`.\n", - "Die Funktion soll wie folgt definiert sein:\n", - "\n", - "- Der Eingabeparameter `n` ist ein Integer, Floats geben `False` zurück\n", - "- Negative zahlen & 0 beenden die Funktion und geben `False` zurück\n", - "- Die Funktion zählt bis einschließlich dem Eingabeparameter\n", - " bsp.: $n=9 \\rightarrow 1, 2, 3, \\dots, 9$\n", - "- Bei jedem Schleifendurchlauf soll die Zahl bei der sich die Schleife gerade befindet mittels `print` ausgegeben werden werden.\n", - "- Ist der zurzeitige Schleifendurchlauf durch `3` teilbar, gebe mittels `print` denn String `Foo` aus.\n", - "- Ist der zurzeitige Schleifendurchlauf durch `5` teilbar, gebe mittels `print` denn String `Bar` aus.\n", - "- Ist der zurzeitge Schleifendurrchlauf durch `3 & 5` teilbar, gebe mittels `print` den String `FooBar` aus.\n", - "\n", - "**Tipp**: Implementiere nicht alles aufeinmal sollte Schritt für Schritt und teste deine Lösung nach jedem Schritt.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "d1f074e2-c036-445c-97f6-618f5aa4cedb", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-0796f3b2cbac6f8e", - "locked": false, - "points": 4, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "def fubar(n: int):\n", - " if isinstance(n, float) or n < 1:\n", - " return False\n", - "\n", - " count = 1\n", - " while count <= n:\n", - " msg = count\n", - " if count % 3 == 0:\n", - " msg = \"Foo\"\n", - " if count % 5 == 0:\n", - " msg = \"Bar\"\n", - " if count % 15 == 0:\n", - " msg = \"FooBar\"\n", - " \n", - " count += 1\n", - " print(msg, end=', ')\n", - " \n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "22784528-9205-4575-84ef-0060732cd053", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-f7774d4246e958a6", - "locked": true, - "points": 3, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Fubar to 4\n", - "1, 2, Foo, 4, \n", - "Fubar to 6\n", - "1, 2, Foo, 4, Bar, Foo, \n", - "Fubar to 16\n", - "1, 2, Foo, 4, Bar, Foo, 7, 8, Foo, Bar, 11, Foo, 13, 14, FooBar, 16, \n", - "Fubar to 200\n", - "1, 2, Foo, 4, Bar, Foo, 7, 8, Foo, Bar, 11, Foo, 13, 14, FooBar, 16, 17, Foo, 19, Bar, Foo, 22, 23, Foo, Bar, 26, Foo, 28, 29, FooBar, 31, 32, Foo, 34, Bar, Foo, 37, 38, Foo, Bar, 41, Foo, 43, 44, FooBar, 46, 47, Foo, 49, Bar, " - ] - } - ], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "print(\"Fubar to 4\")\n", - "fubar(4)\n", - "print(\"\\nFubar to 6\")\n", - "fubar(6)\n", - "print(\"\\nFubar to 16\")\n", - "fubar(16)\n", - "print(\"\\nFubar to 200\")\n", - "fubar(50)\n", - "### BEGIN HIDDEN TESTS\n", - "assert fubar(-1) == False\n", - "assert fubar(0) == False\n", - "assert fubar(.1) == False\n", - "### END HIDDEN TESTS" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.7" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/Einführung/Tut_2.ipynb b/Material/wise_24_25/lernmaterial/Einführung/Tut_2.ipynb deleted file mode 100644 index c1cb76e..0000000 --- a/Material/wise_24_25/lernmaterial/Einführung/Tut_2.ipynb +++ /dev/null @@ -1,1504 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "079afb70-639e-4955-8ca7-1c290cbf08a9", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-7057e40105900012", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "# 2. Programmierübung: Python Tutorial\n", - "\n", - "
\n", - "
\n", - " Willkommen zur ersten Programmierübung Einführung in Python 3.\n", - "
\n", - " \n", - "
\n", - "\n", - "Wenn Sie Fragen oder Verbesserungsvorschläge zum Inhalt oder Struktur der Notebooks haben, dann können sie eine E-Mail an Phil Keier ([p.keier@hbk-bs.de](mailto:p.keier@hbk-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) oder Martin Le ([martin.le@tu-bs.de](mailto:martin.le@tu-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) schreiben.\n", - "\n", - "Link zu einem Python Spickzettel: [hier](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf)\n", - "\n", - "Der Großteil des Python-Tutorials stammt aus der Veranstaltung _Deep Learning Lab_ und von [www.python-kurs.eu](https://www.python-kurs.eu/python3_kurs.php) und wurde für _Signale und Systeme_, sowie _Einführung in die Programmierung für Nicht Informatiker_ angepasst." - ] - }, - { - "cell_type": "markdown", - "id": "85fd88de-a9ee-4149-8bed-1b8ebc0bbad4", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-26e0f96baeb79aac", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "# Kontrollstruckturen\n", - "\n", - "## Sequentielles - For Loop\n", - "\n", - "Python verwendet eine spezielle Form des 'for-loops' dabei handelt es sich sprachlich um den 'for-each loop'.\n", - "\n", - "Mittlerweile hat jede nennenswerte Programmiersprache das Konzept des 'for-each loops' auf seine Weise implementiert. Python hingegen nutzt diesen als Standard. Sprachen wie JavaScript, C/C++, etc. verwenden standardmässig eine 'Zählschleife', dabei wird meist von '0' angefangen bis zu einem Grenzwert 'n' gezählt.\n", - "\n", - "Ein schönes beispiel bietet hierfür JavaScript:\n", - "\n", - "```js\n", - "for (let i = 0; i < arr.length; i++) {\n", - " // do something\n", - "} \n", - "```\n", - "\n", - "Zu lesen ist dies wie folgt: \"Für ein i mit dem Wert 0 (let i = 0), zähle bis i größer die Länge von Array arr (i < arr.length) und erhöhe nach jedem Schleifendurchlauf den Wert von i um 1 (i++)\"\n", - "\n", - "In Python sehe selbiger Code wie folgt aus:\n", - "\n", - "```python\n", - "for i in range(0,len(arr)):\n", - " # do something\n", - "```\n", - "\n", - "Zu lesen ist dies wie folgt: \"Für jedes (for each) i in dem Intervall/Menge 0 bis arr.length mach etwas\"\n", - "\n", - "Der Unterschied besteht darin das Python jedes Element einer Menge durchläuft, der Catch liegt darin das es absolut unabhängig davon ist wie die Menge aussieht. Widmen wir uns zunächst einer Aufgabe:" - ] - }, - { - "cell_type": "markdown", - "id": "7215a3e7-a240-43ec-914c-10221d8b28b0", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-80add6da9914f961", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Aufgabe \n", - "\n", - "*3 Punkte*\n", - "\n", - "Schreibe eine Funktion `sum_up` mit Eingabeparameter `n`, welcher die Zahlen von `1...n` aufsummiert.\n", - "\n", - "Nutze dafür einen `for-loop`.\n", - "\n", - "**Beispiel**:\n", - "\n", - "$$n = 5$$ \n", - "$$sum\\_up(5) \\rightarrow 1 \\rightarrow 1 + 2 = 3 \\rightarrow 3 + 3 = 6 \\rightarrow 6 + 4 = 10 \\rightarrow 10 + 5 = 15$$\n", - "\n", - "Hinweis: die Funktion `range()` zählt standardmässig von `0...n-1`. Schauen Sie sich gerne dazu die offizielle Dokumentation an [PEP 204](https://peps.python.org/pep-0204/#list-ranges)." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "5426ddf1-2d2f-4c92-b007-2f6eca61703f", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-d43ef87a62b03cdf", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "def sum_up(n: int) -> int:\n", - " count = 0\n", - " for i in range(1,n+1):\n", - " count += i\n", - " return count\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "3c38a839-3ab0-466c-98f9-189c35fc5025", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-cff511e86dce0377", - "locked": true, - "points": 3, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "15\n" - ] - } - ], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "print(sum_up(5))\n", - "### BEGIN HIDDEN TEST\n", - "for n in range(3,12):\n", - " assert sum(range(n+1)) == sum_up(n)\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "id": "4e6dfa94-18b9-4fb2-830a-83202d034752", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-02370acddb67290d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Nachdem wir nun gelernt haben wie man mit der Built-In Funktion 'range' zählen kann, schauen wir uns folgend ein paar Beispiele an wie in Python eigentlich Iteriert werden soll.\n", - "\n", - "#### Beispiel 1 - Iterieren über eine Liste:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "db89c7c5-6efc-49bb-be92-414a7334ed84", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-dd3ea63dd3b1d927", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "square_numbers = [1,4,9,16,25,36]\n", - "for number in square_numbers:\n", - " print(number)" - ] - }, - { - "cell_type": "markdown", - "id": "6413a239-c334-491e-8062-7f78f75182fe", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-9bc7f123a8fb7680", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "#### Beispiel 2 - Iterieren über ein Dictionary:\n", - "\n", - "Erweitern wir Beispiel 1 und arbeiten nun mit einem Dictionary. Dieses Besteht wie Sie noch aus dem ersten Tutorial Wissen immer aus 'key-value' paaren. Mit der Built-In Funktion `.items()` bekommen wir ein Tuple an Werten zurück, welches erst entpackt werden muss. Dazu behilft uns der 'for-loop' indem einfach 2 variabeln gleichzeitig deklariert werden. (Achtung! Mit `.items()` werden die 'key-value' paare als '(key, value)' zurückgegeben)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "116ce552-a5c0-4c9c-8d89-fe1f3e40bdba", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-72122af8e519273b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "square_numbers_dict = {1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36}\n", - "\n", - "for key, value in square_numbers_dict.items():\n", - " print(key, \"->\" , value)" - ] - }, - { - "cell_type": "markdown", - "id": "b4e748de-0603-41c9-8282-86e92923e358", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-52b4d0167c7fb9ba", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "#### Beispiel 3 - Iteration mit Zählen:\n", - "\n", - "Die Built-In Funktion `enumerate()` [PEP 279](https://peps.python.org/pep-0279/) ermöglicht das Zählen und gleichzeitige iterieren über eine Liste.\n", - "Dabei wird wieder ein Tuple zurückgegeben welches die Form '(index, value)' annimmt." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8cbf9142-2cf3-4579-9e19-799ee9b25a54", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-29953c29ed4bcdcf", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "alphabet = [\"a\", \"b\", \"c\", \"d\"]\n", - "for index, buchstabe in enumerate(alphabet):\n", - " print(index, \"->\", buchstabe)" - ] - }, - { - "cell_type": "markdown", - "id": "4add1ce5-e462-4be3-8bd7-9960d86ae780", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-b64ce270167d3025", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Mit den traditionellen Mitteln lässt sich der absolut Selbe Output generieren. Das verwenden von `enumerate()` ist jedoch eleganter:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d2e8274b-00d4-4042-adbf-937aea8f0e7e", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-8b2e3cb4e0c977f2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "alphabet = [\"a\", \"b\", \"c\", \"d\"]\n", - "for index in range(len(alphabet)):\n", - " print(index, \"->\", alphabet[index])" - ] - }, - { - "cell_type": "markdown", - "id": "b504f072-53ce-4d03-9f72-b4d4ba85ae74", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5e8d9fc47a709ba4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Aufgabe\n", - "\n", - "*2 Punkte*\n", - "\n", - "Ihnen ist das Dictionary `dict2` gegeben. Ändern Sie jeden Wert in dem Dictionary nach der Formel $f(x) = x^3-1$ mittels `for-loop`.\n", - "\n", - "Tipp: Lassen Sie sich nicht von den Schlüsseln verwirren." - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "abd323c0-5e1b-4c14-a65a-9d54a06f3a80", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-0361320c63b2cb03", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "dict2 = {\"a\": 56, 5: 12, \"python\": 9, 3.14: 1.141414}\n", - "### BEGIN SOLUTION\n", - "dict2 = {key: value**3-1 for key, value in dict2.items()}\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "7e0f9ac4-c5d4-44b6-a2fc-db98e2b46356", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-82eec3cba623ab8f", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'a': 175615, 5: 1727, 'python': 728, 3.14: 0.48706374396146557}\n" - ] - } - ], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "print(dict2)\n", - "### BEGIN HIDDEN TEST\n", - "d = {\"a\": 56, 5: 12, \"python\": 9, 3.14: 1.141414}\n", - "d = {key: value**3-1 for key, value in d.items()}\n", - "assert d == dict2\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "id": "ecc21f6a-2ea0-41a0-9e56-04faae5a0fc6", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-9ffa970f1cdac592", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Mit dem Unterstrich `_` als Zählvariable werden `for`-loops gekennzeichnet die ihre Zählvariable nicht verwenden:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "786461b8-ecf9-4afb-8b93-6186f53f6e97", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-8316e1e4eaa0ea0b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Python is Nice!\n", - "Python is Nice!\n", - "Python is Nice!\n" - ] - } - ], - "source": [ - "for _ in range(3):\n", - " print(\"Python is Nice!\")" - ] - }, - { - "cell_type": "markdown", - "id": "7fd320aa-6bb5-4b9b-9593-2df69cb2ca1e", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-cb8f33d1ae55a6a4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "## List Comprehension\n", - "\n", - "Seit dem Proposal von [PEP 202](https://peps.python.org/pep-0202/) gibt es in Python die List Comprehension.\n", - "\n", - "Für diese Vorlesung ist es nicht nötig das Sie die Syntax anwenden können, Sie sollten zumindest verstehen wie diese funktioniert.\n", - "\n", - "Angenommen wir haben folgende Mathematische beschreibung einer Menge $$\\{x^2 \\vert x \\in \\mathbb{N}\\}$$\n", - "\n", - "Dies beschreibt die Funktion $f(x) = x^2$ für alle natürlichen Zahlen.\n", - "\n", - "In Python ist es möglich genau diese Menge in einer einzigen Zeile Abzubilden. Dazu wird die List Comprehension verwendet deren Syntax im allgemeinen folgende Form hat:\n", - "\n", - "```python\n", - "[ for value in ]\n", - "```\n", - "\n", - "Schauen wir uns dazu an wie wir die Quadrat Zahlen von `1...6` also `1...36` erzeugen." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7bcdc9d9-cc5b-49be-8cfb-ca40eb3b7796", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4fd6f801463c5ea6", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "squared = [n*n for n in range(1,7)]\n", - "print(squared)" - ] - }, - { - "cell_type": "markdown", - "id": "b6dcb24c-e01e-4522-8ac4-074adfe6105a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c6922240434c9d3a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Probieren Sie sich gerne selber aus.\n", - "\n", - "### Zusatzaufgabe \n", - "\n", - "*Keine Punkte*\n", - "\n", - "Erstellen Sie eine List mittels List Comprehension, welche die Zahlen `1...6` auf deren kubische Zahl `1...216` also der Funktion $f(x) = x^3$ abbildet." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "522f3228-1797-4ca2-9103-44fce48dfd4a", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-1dc645632c5f653a", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "cubics = []\n", - "### BEGIN SOLUTION\n", - "cubics = [n**3 for n in range(1,7)]\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "7dc19b9f-116b-4741-a798-a66d495d477e", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-4e441b6db861559e", - "locked": true, - "points": 0, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[1, 8, 27, 64, 125, 216]\n" - ] - } - ], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "print(cubics)\n", - "### BEGIN HIDDEN TEST\n", - "c = [n**3 for n in range(1,7)]\n", - "assert c == cubics\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "id": "5b1355f0-29ed-4318-92f2-51f151c7946e", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-7d9eebd920496d59", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "# System Interactions\n", - "\n", - "Im folgenden Abschnitt beschäftigen wir uns mit dem Eingeben von Daten in ein Programm. Dies geschieht entweder 'von Hand', also über den Benutzer, oder über Dateien." - ] - }, - { - "cell_type": "markdown", - "id": "976a7ad0-856d-4fb6-bba8-485668df22a2", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-e2df7221e04e8c54", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Im Normalfall wollen wir größere Datenmengen einlesen. Dazu nutzen wir die Built-In Funktion `open` ([Python Docs - Open](https://docs.python.org/3/library/functions.html?highlight=open#open)). Auch wenn in der Doku viele Parameter stehen benötigt man im Normalfall nur zwei. Der erste ist der Name der File, der zweite im welchem Modus die Datei geöffnet werden soll (Angegeben als String).\n", - "\n", - "Zum bearbeiten der Datei nutzen wir den Python Kontext Manager - das `with`-Statement. Bei externen Daten ist es immer wichtig die Datei auch wieder zu schließen, damit es nicht zu Datenverlust oder Arbeitsspeichermüll kommt. Daher ist der Lebenzyklus einer Datei in einem Programm immer `Datei öffnen` -> `Datei Bearbeiten` -> `Datei schließen`. Kommt es in einer der Drei schritte zu einem Fehler, bleibt die Datei im RAM hängen und der Computer muss neu gestartet werden um diesen Speicher wieder Frei zu geben.\n", - "\n", - "Daher gibt es Kontext Manager. Dieser versichert dem Programmierer, dass das schließen der Datei immer (!!) passiert. Die Syntax folgt folgender Strucktur:\n", - "\n", - "```python\n", - "with as :\n", - " # do something\n", - "```\n", - "\n", - "Dabei ist `` ein Objekt (für uns eine Datei) und `` die Zuweisung zu einer Variablen. Für die Funktion `open` (im Lesemodus) sieht der Kontext wie folgt aus:\n", - "\n", - "```python\n", - "with open(\"filename.txt\", \"r\") as f:\n", - " f.readlines() # do something with f\n", - "```" - ] - }, - { - "cell_type": "markdown", - "id": "a345cdf5-d1a0-4bd8-9f77-06e6d4562e00", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-58fb9b7e476f3ef2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Aufgabe\n", - "\n", - "*2 Punkte*\n", - "\n", - "Erstellen und Öffnen sie eine Datei `testfile.txt` mit der `open` Funktion, nutzen Sie dafür das `with`-Statement.\n", - "\n", - "Schreiben Sie in diese Datei 100 mal den String `\"Python\\n\"`. " - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "f11f7a0b-bcca-4db0-a6ca-bf95c70c7303", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-0735bb589edcc6a8", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "with open('testfile.txt', 'w') as f:\n", - " for _ in range(100):\n", - " f.write(\"Python\\n\")\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "c91e07bb-fc41-42c1-8b42-0aca56c57c35", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-2592f8b51914455e", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TEST\n", - "with open('testfile.txt', 'r') as f:\n", - " lines = f.readlines()\n", - " assert len(lines) == 100\n", - " for line in lines:\n", - " assert line == 'Python\\n'\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "id": "4adb5400-8749-4790-ae49-68a8622b4a3d", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-39769ee8cbf2157d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Aufgabe\n", - "\n", - "*2 Punkte*\n", - "\n", - "Öffnen Sie die zuvor erstellte Datei `testfile.txt` im Lesemodus und weißen Sie den Inhalt der `.readlines()` Funktion der Variabeln `lines` zu. " - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "adf300e9-ee63-4da1-a6f3-c768fa2b5fc9", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-0a3b9e01dd66e134", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "lines = None\n", - "# BEGIN SOLUTION\n", - "with open('testfile.txt', 'r') as f:\n", - " lines = f.readlines()\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "229499d6-bb33-492b-af5d-a26ab3b3f5d4", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-aa7c104b5f3f2572", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Anzahl der gelesenen Zeilen: 100\n" - ] - } - ], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "print(\"Anzahl der gelesenen Zeilen:\", len(lines))\n", - "### BEGIN HIDDEN TEST\n", - "with open('testfile.txt', 'r') as f:\n", - " assert f.readlines() == lines\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "id": "47d92dde-16a1-4c11-a452-cadd74255db2", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-be695e1423a6ccf4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "## Import Statement\n", - "\n", - " \n", - "\n", - "Da wir nicht immer das Rad neu erfinden wollen nutzen wir Bibliotheken von anderen Entwicklern.\n", - "\n", - "Dazu nutzt man das Keyword `import` gefolgt von dem Modul welches man Importieren möchte. Nutzen wir als Beispiel `numpy`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ced37c65-87d2-48d0-a0ba-4674dcaf104c", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-7d19506e181bcda9", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "import numpy" - ] - }, - { - "cell_type": "markdown", - "id": "f5506975-e1cd-434a-8ef1-05a7a06992df", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-b7d981325bea8b84", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Möchte man nun eine Funktion aus dem Modul nutzen folgt die Syntax der Strucktur `.`. Dazu folgendes Numpy Beispiel:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "69c68b31-d0f7-469b-ae54-eef871ec6ad6", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-25ad372a576a793e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "numpy.array(range(100))" - ] - }, - { - "cell_type": "markdown", - "id": "7c5d65db-d1e8-4cad-884e-bb595c57d445", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-0176c541098f7c21", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Aufgabe\n", - "\n", - "*3 Punkte*\n", - "\n", - "Importiere Python Built-In Library `random` und rufe zuerst aus dem Modul die Funktion `seed` auf mit dem Eingabewert `42`, und weiße danach der Variable `rand` den Wert des Funktionsaufrufes von `randint(1,100)` zu. " - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "0d80bc9f-6923-4e3f-8a70-909548e693a6", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-8ccc5fe1848176c8", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "rand = None\n", - "# BEGIN SOLUTION\n", - "import random\n", - "random.seed(42)\n", - "rand = random.randint(1,100)\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "ada0211b-03bf-463a-b932-2bad621d5559", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-d7817c3dd1ee34f9", - "locked": true, - "points": 3, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "82\n" - ] - } - ], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "print(rand)\n", - "### BEGIN HIDDEN TEST\n", - "assert rand == 82\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "id": "f7b3bdcc-825e-4607-8804-a5ce3d39ace5", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-2cc1d2ed682d1b0e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Das Keyword `as` ist bereits bekannt, dieses kann auch verwendet werden um Module beim import umzubennen. Dies ist dann Hilfreich wenn Module lange Namen haben.\n", - "\n", - "Numpy wird im Internet immer mit np abgekürzt. Beispiel:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f115eae9-500b-448e-a1be-e3b43ffad0fd", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-60f357d6dda4a8d3", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "import numpy as np\n", - "np.array(range(100))" - ] - }, - { - "cell_type": "markdown", - "id": "f7570244-0fea-4683-a19c-069f6ba619dd", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-94fb7e92492a12f7", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Aufgabe\n", - "\n", - "*1 Punkt*\n", - "\n", - "Importieren Sie die Built-In Library `datetime` als `dt`." - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "e7e6c246-6dc4-4555-a202-73887b5f8249", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-59dc2ded4f59471f", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "import datetime as dt\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "b03ee34b-8520-4106-a23f-4419e54dcfcc", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-d77ffdb7f9ba178d", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2024-11-01 19:32:22.691479\n" - ] - } - ], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "print(dt.datetime.now()) # UTC Time also Standard Greenwich Zeit\n", - "### BEGIN HIDDEN TEST\n", - "assert 'dt' in dir()\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "id": "1cc39ffb-1207-4aa8-a4fe-51df2335fea6", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-c55653efe0a77419", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Möchte man nur eine Bestimmte Funktion aus einem Modul haben nutzt man die `import from` Syntax. Beispiel Pretty Print:" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "638e6c20-7bba-4862-9acc-34031bae8514", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-f84e2596969633f5", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{0: 1,\n", - " 1: 2,\n", - " 2: 4,\n", - " 3: 8,\n", - " 4: 16,\n", - " 5: 32,\n", - " 6: 64,\n", - " 7: 128,\n", - " 8: 256,\n", - " 9: 512,\n", - " 10: 1024,\n", - " 11: 2048,\n", - " 12: 4096,\n", - " 13: 8192,\n", - " 14: 16384,\n", - " 15: 32768,\n", - " 16: 65536,\n", - " 17: 131072,\n", - " 18: 262144,\n", - " 19: 524288}\n" - ] - } - ], - "source": [ - "from pprint import pprint\n", - "pprint({n: 2**n for n in range(20)})" - ] - }, - { - "cell_type": "markdown", - "id": "c1e077c1-59a5-411b-bf71-32ea66dc731d", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-0ac2347c47ff5774", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Aufgabe\n", - "\n", - "*2 Punkte*\n", - "\n", - "Importieren Sie die Funktion `sqrt` aus dem Built-In Modul `math`.\n", - "Berechnen Sie $\\sqrt4$. Speichern Sie das Ergebnis in der variablen `s4`." - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "81838f9b-558c-49b3-90ef-647e28380a97", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-7c1ea8bca61d5c12", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "from math import sqrt\n", - "s4 = sqrt(4)\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "6d984a74-a93d-4865-b6d1-d2dec8586907", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-83c667de468e9ef8", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2.0\n" - ] - } - ], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "print(s4)\n", - "### BEGIN HIDDEN SOLUTION\n", - "assert 'sqrt' in dir()\n", - "assert int(s4) == 2\n", - "### END HIDDEN SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "6edf5dce-17d2-4a5f-9d96-2c7c3091de88", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-814b3bfa4b6e049a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Ein letzter Hinweis: Es gibt auch die Möglichkeit in der `import from` Syntax das Keyword `as` zu verwenden.\n", - "\n", - "Beispiel aus dem Modul `dataclasses` importiert `dataclass` als `dclass`:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "b707bf52-546f-4689-8216-c5ad0b9665a7", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-9961359e9d09d79b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "from dataclasses import dataclass as dclass\n", - "print(dclass)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.7" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/Einführung/Zusatz_Tut.ipynb b/Material/wise_24_25/lernmaterial/Einführung/Zusatz_Tut.ipynb deleted file mode 100644 index 5565362..0000000 --- a/Material/wise_24_25/lernmaterial/Einführung/Zusatz_Tut.ipynb +++ /dev/null @@ -1,1945 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "1ddc11f3-0a8a-47ee-b7b7-6dfd22ac40d9", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-8c0ecbebdebcad39", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "# Zusatz Programmierübung: Python Tutorial\n", - "\n", - "
\n", - "
\n", - " Willkommen zum Zusatz der ersten Programmierübung Einführung in Python 3.\n", - "
\n", - " \n", - "
\n", - "\n", - "Bei diesem Tutorial handelt es sich um Python Konzepte die nicht notwendig sind das Modul zu bestehen. Sie dürfen trotzdem alles hier gelernte gerne verwenden.\n", - "\n", - "Wenn Sie Fragen oder Verbesserungsvorschläge zum Inhalt oder Struktur der Notebooks haben, dann können sie eine E-Mail an Phil Keier ([p.keier@hbk-bs.de](mailto:p.keier@hbk-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) oder Martin Le ([martin.le@tu-bs.de](mailto:martin.le@tu-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) schreiben.\n", - "\n", - "Link zu einem Python Spickzettel: [hier](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf)\n", - "\n", - "Der Großteil des Python-Tutorials stammt aus der Veranstaltung _Deep Learning Lab_ und von [www.python-kurs.eu](https://www.python-kurs.eu/python3_kurs.php) und wurde für _Signale und Systeme_, sowie _Einführung in die Programmierung für Nicht Informatiker_ angepasst." - ] - }, - { - "cell_type": "markdown", - "id": "f47e9f08-663b-4c2f-85c7-8b6c7f654b45", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-40ca946ad65b66b6", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Konventionen\n", - "\n", - "Python hat einen Grundlegenden Styleguide 2001 von Guido van Rossum festgelegt in [PEP 8](https://peps.python.org/pep-0008/).\n", - "\n", - "Dazu nur ein paar Anmerkungen:\n", - "\n", - "1. Variabel- & Funktionsnamen werden immer kleingeschrieben und mittels \"snake case\" geschrieben. Bsp.: `is_alive`\n", - "2. Zum Einrücken sollten 4 Leerzeichen verwendet werden die mit Tab eingeleitet werden. (Jupyter macht dies Automatisch richtig)\n", - "3. Beim schreiben von Kommentaren folgt nach `#` immer ein Leerzeichen. Bsp.: `# Kommentar`\n", - "4. Importe aus Modulen sollen getrennt sein.\n", - "\n", - " Richtig:\n", - " ```python\n", - " import os\n", - " import sys\n", - " ```\n", - " \n", - " Falsch:\n", - " ```python\n", - " import os, sys\n", - " ```\n", - "\n", - "5. Mehrfach importe aus einem Modul sind dennoch mit `,` gern gesehen.\n", - "\n", - " Bsp.:\n", - " ```python\n", - " from dataclass import dataclass, field, asdict\n", - " ```\n", - "\n", - "6. Nach jedem `,`, `:`(außer beim slicing) und operator `+, =, etc.` folgt ein Leerzeichen.\n", - " \n", - " Bsp.:\n", - " ```python\n", - " x = 4 + 2\n", - " arr[5:10]\n", - " ```\n", - "\n", - "7. Kein unnötiges Ausrichten von Variablen.\n", - "\n", - " So nicht:\n", - " ```python\n", - " x = 4\n", - " y = 5\n", - " name = \"Lisa\"\n", - " ```\n", - "\n", - "8. Die Variablnamen `l` (Kleingeschriebenes L), `O` (Großes o) und `I` (Großes i) sollten niemals als Einzelvariablennamen verwendet werden, da diese Schwer von `i` (Kleines i), `0`(Die Zahl Null) und `L` (Großes L) in einigen Schriftarten zu unterscheiden sind. (Sollte mit Jupyter kein Problem darstellen)" - ] - }, - { - "cell_type": "markdown", - "id": "4abb5645-0172-4fd7-8f79-02af5140b234", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ef37f36145723997", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Generatoren\n", - "\n", - "Nachdem wir bereits Funktionen kennengelernt haben, welche einen Rückgabewert haben, lernen wir nun ein Python Konzept kennen, dass \"On the fly\" Daten zur Verfügung stellt.\n", - "\n", - "Einen häufig verwendeter Generator, denn wir bereits kennengelernt haben, ist die `range` Funktion.\n", - "\n", - "Mit einem einfachen `print` lässt sich dies auch bestätigen:" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "f8f4aee6-ce57-41f8-af18-7256b0126515", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1e78bfa1751878c9", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "range(0, 10)\n" - ] - } - ], - "source": [ - "print(range(10))" - ] - }, - { - "cell_type": "markdown", - "id": "dc9f0f52-0a0d-4e5c-8b6f-d7a2b7c5b2e3", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1c1a0f19a370c840", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Statt wie vielleicht zu erwarten die Liste von werten `0...9` als Ausgabe zu bekommen, gibt uns Python lediglich `range(0, 10)` zurück.\n", - "\n", - "Möchte man die Werte direkt evaluiert haben muss der `*`-Operator verwendet werden:" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "89986045-bb47-4bca-b561-bab9bb2b988b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-723d591c32fda1a7", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0 1 2 3 4 5 6 7 8 9\n" - ] - } - ], - "source": [ - "print(*range(10))" - ] - }, - { - "cell_type": "markdown", - "id": "2248b888-aa12-4367-b1f4-bb4befc43df4", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-19e02ebb63f72a88", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Dabei verändert `range(10)` die `print` Funktion indem es alle Generator Werte als Parameter einsetzt `print(0,1,2,3,4,5,6,7,8,9)` und danach aufruft.\n", - "\n", - "Um selber einen Generator zu definieren benötigt man das Python Keyword `yield`. Im Gegensatz zum Normalen `return` wird die Berechnung nur gestoppt und zu einem späteren Zeitpunkt ausgeführt. Sozusagen hat der Generator ein veränderbaren Zustand.\n", - "\n", - "Die Syntax hierzu ist im Allgemeinen:\n", - "\n", - "```python\n", - "def ():\n", - " # do something\n", - " yield \n", - "```\n", - "\n", - "Eine rudimentäre Funktion `count_to` lässt sich dementsprechend wie folgt definieren:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "e4686bab-6686-4464-9015-54d420087e5a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-795ddd785249ca9d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "This is a Generator: \n", - "This Generator evaluates to: 0 1 2 3 4 5 6 7 8 9\n" - ] - } - ], - "source": [ - "def count_to(n):\n", - " count = 0\n", - " while count < n:\n", - " yield count\n", - " count += 1\n", - "\n", - "print(\"This is a Generator:\", count_to(10))\n", - "print(\"This Generator evaluates to:\", *count_to(10))" - ] - }, - { - "cell_type": "markdown", - "id": "7cbdb90b-bedf-4197-97b8-8baf58c92190", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c2c489efaeeb75dd", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Schreibe einen Generator `square_count` mit einem Eingabeparameter `n`, welcher die Quadratzahlen von $0\\dots n^2$ ausgibt.\n", - "\n", - "Hinweis: Bei Eingabe von `5` soll die Ausgabe `0 1 4 9 16` sein." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "2df62e85-d5a5-4664-bdf6-c544ed8fb0d1", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-a037e576943e230b", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "def square_count(n):\n", - " for i in range(n):\n", - " yield i*i\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "234d782c-88f4-4bc2-a872-15a592ee1248", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-a6c43a5365ad736d", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TEST\n", - "for n in range(10): \n", - " assert [i*i for i in range(n)] == [i for i in square_count(n)]\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "id": "8e1cb8b2-cdaa-422a-9889-c4e0794d7d81", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5f6f32fed19a1933", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Generatoren können auch eine unendliche Menge an Daten zurückgeben. Dieses Ziel kann man erreichen indem der Generator unendlich oft ausgeführt wird. Da die Daten zur Laufzeit berechnet werden kann man von einer unendlichen Menge sprechen.\n", - "\n", - "Um eine Berechnung nie enden zu lassen muss die Bedingung der Schleife immer `wahr` bleiben.\n", - "Dies erreicht man durch die Syntax `while True:`, aber Python ist eben Python und die Syntax `while 1:` ist Laufzeit effizienter.\n", - "\n", - "Schauen wir uns nun das Beispiel eines unendlichen Generator an der Fortwährend die nächste Fakultät ausgibt:\n" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "e7a2e825-b67d-4618-9358-4ee06ef5cc38", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-55717dfe7800e3fb", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "def faktoriel_gen():\n", - " curr = 1\n", - " count = 1\n", - " while 1:\n", - " curr = count * curr\n", - " count += 1\n", - " yield curr" - ] - }, - { - "cell_type": "markdown", - "id": "496d59e9-e3c1-47d1-982d-8c5688cb7893", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-7d21c6426cee23f0", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Vorsicht (!!) wertet man diesen Generator nun aus würde die Berechnung niemals enden. Um den nächsten Wert der Berechnung zu erhalten hat Python die Funktion `next`, welche den nächsten Zustand des Generators ausgibt. Mit einem `for`-loop und `next` lassen sich dann die Fakultäten der Zahlen bis `5` einfach ausgeben:" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "4249c820-f03c-4393-bb8f-5078f9a9a0b8", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-166ede3f392e88e7", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1\n", - "2\n", - "6\n", - "24\n", - "120\n" - ] - } - ], - "source": [ - "gen = faktoriel_gen()\n", - "\n", - "for _ in range(5):\n", - " print(next(gen))" - ] - }, - { - "cell_type": "markdown", - "id": "8b0d160f-d445-4877-a634-2de69336e70a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2e5778830ac74399", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Da der Zustand des Generator gespeichert ist lässt sich mit einem weiteren aufruf in nächster Zelle auf $6! = 720$ ausgeben:" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "32e5eb93-507a-490e-9395-717bc7717973", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-30acb8e9a68a7794", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "720\n" - ] - } - ], - "source": [ - "print(next(gen))" - ] - }, - { - "cell_type": "markdown", - "id": "9901cb74-faf9-47f1-b87e-60d9683778d3", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3f6a4841c593371f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Schreibe einen Generator `naturals`, welcher mit jedem Aufruf die nächste natürliche Zahl ausgibt. (Angefangen mit 1)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "a8b2697c-706b-4744-a4b3-00682d6c95c3", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-09dd94e802cad9bc", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "def naturals():\n", - " curr = 1\n", - " while 1:\n", - " yield curr\n", - " curr += 1\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "403c70b9-3ac3-4a85-a302-d9c7d0585cbc", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-e065f7326fb561ad", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TEST\n", - "import random\n", - "test_n = random.randint(5, 17)\n", - "test_gen = naturals()\n", - "for i in range(1, test_n):\n", - " assert i == next(test_gen)\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "id": "75a1949d-d0b6-4ea2-83c9-c5f8f15ae4f0", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-701ee003544a4616", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Lambda - Anonyme Funktionen\n", - "\n", - "Ein eher kontroverses Feature ist das Keyword `lambda`, welche es ermöglicht \"anonyme Funktionen\" oder \"oneliner\" zu schreiben.\n", - "Eine `lambda` Funktion lässt sich auch einer Variablen zuweisen.\n", - "\n", - "Die Syntax hierfür:\n", - "```python\n", - "[ =] lambda : \n", - "```\n", - "\n", - "Möchte man beispielweise eine einfache Square Funktion schreiben, lässt sich dies wie bei der `List Comprehension` in einer Zeile erledigen:" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "7cae2e6e-47e8-46c5-97de-0d0da99ff03d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-60308748fe5798d1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number: 3 \n", - "Squared Number: 9\n" - ] - } - ], - "source": [ - "square = lambda n: n*n\n", - "print(\"Number:\", 3, \"\\nSquared Number:\", square(3))" - ] - }, - { - "cell_type": "markdown", - "id": "60f06fff-1f23-441b-af0c-6cfbb1c862e6", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-04db14786b869da9", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Die Funktion ist deshalb anonym da sie keinen Namen hat wie folgender Output veranschaulicht:" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "id": "3b7acada-ed40-4a72-b40f-7609e4989ba9", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f9dc9e005746fa88", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " at 0x7fe8b56093a0>\n" - ] - } - ], - "source": [ - "print(square)" - ] - }, - { - "cell_type": "markdown", - "id": "9f13c0d4-bd7c-42d8-b387-40d994348715", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ba511670b3205191", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Probieren Sie es gerne selber aus.\n", - "\n", - "**Aufgabe**: Schreibe eine `lambda`-Funktion die den Input auf die Funktion $f(x) = x^4+2$ abbildet, und weisen Sie dieser Funktion die variable `f` zu." - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "e5975460-4d13-4a7a-ab4c-e5a637ff11ee", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b6782b076b8e1363", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "f = lambda n: n**4+2\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "dcc8cad0-8582-471e-bccc-ea4516ee1121", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-837edeb5c7f4b83e", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TEST\n", - "import random\n", - "n = random.randint(2,90)\n", - "assert n**4+2 == f(n)\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "id": "41bb0337-7194-4482-a5b9-af1243d4809c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-bbe0bad0c47d41ae", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Type Hints\n", - "\n", - "Mit [PEP 484](https://peps.python.org/pep-0484/) wurden in Python die `type hints` eingeführt. Die Motivation dafür war es eine Standard Syntax zu definieren, welche einem die Möglichkeit gibt den In- und Output von Funktionen besser zu bestimmen. Unteranderem verbessert sich die Testbarkeit von Python Programmen ungemeinen wenn Type Hints vorhanden sind.\n", - "\n", - "(!!!) Type hints können nicht für `lambda`-Funktionen genutzt werden!\n", - "\n", - "Die Allgemeine Syntax dafür:\n", - "```python\n", - "def (: , : ) -> :\n", - " # do something\n", - " return \n", - "```\n", - "\n", - "Python ist eine dynamische typisierte Sprache. Das heißt, dass der Typ einer Variable immer wieder überprüft werden muss. So kann eine Ganzzahl `int` mit einer einfachen addition in eine Flieskommazahl `float` überführt werden:" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "d2148990-b5cb-4fe5-8751-bac8338fa581", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-560aa9d85c5a4383", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "3 \n", - "3.14 \n" - ] - } - ], - "source": [ - "number = 3\n", - "print(number, type(number))\n", - "number += 0.14\n", - "print(number, type(number))" - ] - }, - { - "cell_type": "markdown", - "id": "56c143f5-1c67-4999-8656-dc68d5912fb4", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a85903e6bffa1ff1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Um diese unerwünschten Typen wechsel zu vermeiden, kann man type hints verwenden. Type hints sind nur eine Info keine Garantie das der Typ einer Variable sich ändert!\n", - "\n", - "Eine nutzlose Funktion die den Eingabewert als `int` in einen `str` umwandelt sieht wie folgt aus:" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "642dc60b-fa8d-4655-bc47-815f39365506", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-94708ecde4287ff7", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number 42\n" - ] - } - ], - "source": [ - "def useless(number: int) -> str:\n", - " return \"Number {}\".format(number)\n", - "\n", - "print(useless(42))" - ] - }, - { - "cell_type": "markdown", - "id": "ccd50282-1132-40b2-8eea-b6e6e5e0e943", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-220685a52d6807ca", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Decoraters\n", - "\n", - "Das Konzept der Dekoratoren lässt sich am einfachsten mit \"Funktionen die als Eingabeparameter Funktionen haben\" erklären.\n", - "\n", - "Die Syntax hierfür ist die selber wie für Funktionen, nur das als Eingabe eine Funktion erwartet wird:\n", - "```python\n", - "def ():\n", - " # do something\n", - "```\n", - "\n", - "Dabei gibt es zwei möglichkeiten Dekoratoren zu nutzen.\n", - "\n", - "Methode 1 - Funktion ruft Funktion auf:\n", - "```python\n", - "()\n", - "```\n", - "\n", - "Methode 2 - Keyword `@`:\n", - "```python\n", - "@[]\n", - "def ():\n", - " # do something\n", - "```\n", - "\n", - "Schauen wir uns dazu ein Beispiel an. Der Debbug Decorator soll den Namen der aufgerufenen Funktion mittels `print` ausgeben und dann die Funktion (hier `f`) zurückgeben:\n", - "\n", - "Hinweis: Python speichert den namen einer Funktion in der versteckten (magischen) Variable `__name__` ab." - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "id": "08b50a8b-f410-4759-809c-e0301b2889b4", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-603f42aad9017a1e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "square " - ] - }, - { - "data": { - "text/plain": [ - "16" - ] - }, - "execution_count": 41, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def debug(f):\n", - " print(f.__name__, end=\" \")\n", - " return f\n", - "\n", - "@debug\n", - "def square(n):\n", - " return n*n\n", - "\n", - "square(4)" - ] - }, - { - "cell_type": "markdown", - "id": "777904ec-3567-41c8-a619-2c38ad6b6c51", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ea3aeed85ff0587c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Dataclasses \n", - "\n", - "Allgemein auf Klassen wird hier nicht eingegangen jedoch ein Konzept, welches mit [PEP 557](https://peps.python.org/pep-0557/) eingeführt wurde, soll folgend stärker beleuchtet werden.\n", - "\n", - "Datenstruckturen wie `dict`, `set`, `list`, etc. sind mächtige Werkzeuge und ermöglichen dem Programmierer Daten in vielen Formen akkurat dazustellen. Möchte man jedoch feste Datenstruckturen mit genau definierten Werten verwenden eignet sich das Modul `dataclasses`.\n", - "\n", - "Dazu wird eine Klasse mit dem Keyword `class` definiert und dem Decorator `dataclasses.dataclass` ausgesattet. Folglich können Feste Datenobjekte mit definierter Strucktur erstellt werden.\n", - "\n", - "Zunächst wird das Modul aus der Standard Bibliothek importiert:" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "24392aea-8ba8-4f9e-ba95-5bf5c99a127b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-fa6710d8dd259c2d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "from dataclasses import dataclass" - ] - }, - { - "cell_type": "markdown", - "id": "abb46684-015f-48c7-98b8-f2955e71de2d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-36842ee26321c3ec", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Danach kann eine Klasse erstellt werden. Erstellen wir zunächst eine Klasse `Person`, welche die Werte `vorname` und `nachname` als Strings bereitstellen soll:\n", - "\n", - "Wichtig: Python Klassen fangen immer mit einem Großbuchstaben an. Mit ausnahme der Standard Bibliothek. Die `range` Funktion lässt sich zwar verwenden wie eine Funktion, ist aber eigentlich eine Klasse!" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "b70f39ca-6e57-4b03-a3be-c3b5ac604a9c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8b8b2e316c36725c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "@dataclass\n", - "class Person:\n", - " vorname: str\n", - " nachname: str" - ] - }, - { - "cell_type": "markdown", - "id": "94901847-a849-463b-968a-b498a9f84edc", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-846dcecf70fd8d14", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Möchten wir nun eine Person erstellen sieht dies wie folgt aus:" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "27320011-ee5d-43c9-8e07-fbd3036680f7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1cf940f3240bf428", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Person(vorname='Eduard', nachname='Jorswieck') \n" - ] - } - ], - "source": [ - "person = Person(\"Eduard\", \"Jorswieck\")\n", - "print(person, type(person))" - ] - }, - { - "cell_type": "markdown", - "id": "be0c2b13-937e-4073-8dfa-a6d305ed9c6f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8338f70364284fc7", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Wie dem Output zu entnehmen ist die Variable `person` ein Objekt vom Typ `Person` und hält die Werte `vorname='Eduard'` und `nachname='Jorswieck'` vor.\n", - "\n", - "Auf die einzelnen Werte innerhalb der Dataclass kann nun per `.` Operator zugegriffen werden:" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "191bb87c-06ab-40a4-b5b3-56e9c533b930", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b6da422f93431723", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Vorname: Eduard\n", - "Nachname: Jorswieck\n" - ] - } - ], - "source": [ - "print(\"Vorname:\", person.vorname)\n", - "print(\"Nachname:\", person.nachname)" - ] - }, - { - "cell_type": "markdown", - "id": "3e85dee5-09ea-4c00-9730-05fb006ced2b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d80fa3ef35e81dab", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Dataclasses bieten auch den Vorteil, dass ihre Werte direkt über die Variablennamen definiert werden können. Dabei spielt die Reihenfolge dann keine Rolle mehr." - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "a5ea4ef9-dcba-4411-a2e8-1a1a811e6cac", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-20f0d6f2cb9ef5df", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Person(vorname='Martin', nachname='Le') \n" - ] - } - ], - "source": [ - "person2 = Person(nachname=\"Le\", vorname=\"Martin\")\n", - "print(person2, type(person2))" - ] - }, - { - "cell_type": "markdown", - "id": "dbc9c477-903b-4673-aab0-c8fe2b29a9bd", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-9f14c6d500ad6d08", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Erstelle eine Dataclass `Auto` welche die Attribute `beschleunigung` als `int` und `marke` als `str` beinhält." - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "92173deb-dff1-4853-a01e-4e633f3c3aee", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-571687935c72333a", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "@dataclass\n", - "class Auto:\n", - " marke: str\n", - " beschleunigung: int\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "68db3f9c-b6ad-4454-87be-71a78a209a40", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2489e8269aa6414d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Nicht immer sind alle Werte vorhanden und damit dies nicht zum Problem wird können Standardwerte vergeben werden:" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "ce05d4eb-747b-41ad-9fea-5430b8310e8c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-92f8a3cacfda2c15", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "@dataclass\n", - "class Person:\n", - " vorname: str = \"Max\"\n", - " nachname: str = \"Mustermann\"" - ] - }, - { - "cell_type": "markdown", - "id": "e4def98c-60a9-4dcf-a71b-6be49f853b3b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-009056608941f805", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Wird nun eine Dataclass ohne Eingabeparameter erstellt, werden ihr ihre Standardwerte zugewiesen:" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "6d5e0c5d-0f70-4303-83cb-234e9523500c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-dbc29451821056d9", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Aufruf mit print: Person(vorname='Max', nachname='Mustermann')\n" - ] - } - ], - "source": [ - "nameless_person = Person()\n", - "print(\"Aufruf mit print:\", nameless_person) " - ] - }, - { - "cell_type": "markdown", - "id": "f0f08b60-5f24-4325-89a4-896d73834515", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-9f1b7aa9c4607b43", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Die korrekte Behandlung von nicht vorhandenen Werten innerhalb Dataclasses, kann erreicht werden durch die Zuhilfename der Funktion `field` aus dem `dataclasses` Modul.\n", - "\n", - "Dazu wird diese Importiert, und als Standardwert für die Variable zugewiesen. Beim aufrufen von `field` muss dabei eine `default_factory` angegeben werden. Dies ist eine Funktion die einen Standardwert zurückgibt. Meist wird hierbei für String Typen die `str`-Funktion verwendet, etc.." - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "id": "0f1f5a8b-8c2b-42a7-a2be-771216552066", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f1cdd80f03fb05f4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Person(vorname='', nachname='')\n" - ] - } - ], - "source": [ - "from dataclasses import field\n", - "\n", - "@dataclass\n", - "class Person:\n", - " vorname: str = field(default_factory=str)\n", - " nachname: str = field(default_factory=str)\n", - "\n", - "print(Person())" - ] - }, - { - "cell_type": "markdown", - "id": "ccee5184-2f5e-4b90-99ae-2702405c0ec9", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1c171ff9c43179be", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Schreiben Sie eine Dataclass `Auto` mit den Werten `marke` als `str` und `beschleunigung` als `int`. Nutzen Sie für die Standardzuweisung die `field` Funktion aus dem Modul `dataclasses` mit ihren jeweiligen Typen als `default_factory`." - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "id": "d17b07db-7340-47c0-ab1d-38d75b3194c0", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-ac7d4ba80c4a0341", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "@dataclass\n", - "class Auto:\n", - " marke: str = field(default_factory=str)\n", - " beschleunigung: int = field(default_factory=int)\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "d2a16cf4-a0b8-4bcd-8fa4-4143be3ca566", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f17e7fb6600c6c87", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Dataclasses haben den Vorteil, dass sie sich leicht umwandeln lassen. Dazu bietet das Modul `dataclasses` einige Funktionen an zum Umwandeln einer Dataclass in ein `tuple` oder `dict`. Schauen wir uns im Folgenden an wie die Klasse Person in ein `dict` mit der Funktion `asdict` aus dem Modul `dataclasses` umgwandelt wird. Für mehr Funktionen und Möglichkeiten schauen Sie gerne in die Dokumentation zu [Dataclasses](https://docs.python.org/3.11/library/dataclasses.html)" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "id": "369599ab-87f1-4849-abfd-6af86d160975", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-899936f2048aa8bc", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Dataclass: Person(vorname='Ulrich', nachname='Reimers')\n", - "Als Dictionary: {'vorname': 'Ulrich', 'nachname': 'Reimers'}\n" - ] - } - ], - "source": [ - "from dataclasses import asdict\n", - "\n", - "person3 = Person(vorname=\"Ulrich\", nachname=\"Reimers\")\n", - "print(\"Dataclass:\", person3)\n", - "print(\"Als Dictionary:\", asdict(person3))" - ] - }, - { - "cell_type": "markdown", - "id": "35cf1031-9344-4cff-a13a-7674fceb4b4b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-64f568f2137fb4d0", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Structural Pattern Matching\n", - "\n", - "Eines der neueren Konzepte die mit Python 3.10 eingeführt wurde ist das Keyword `match` und das dem dazugehörige \"Structurals Pattern Matching\", wie in [PEP 622](https://peps.python.org/pep-0622/) beschrieben. Jedoch ist es nur teils vergleichbar mit dem aus anderen Programmiersprachen bekannten Konzept des `switch-case` (Bsp. C: [Switch Case in C](https://www.programiz.com/c-programming/c-switch-case-statement)). In C ersetzt `switch` das sukzessive Verwenden von `if-else` Anweisungen. In Python hingegen können Objekteigenschaften direkt geprüft werden, schauen sie sich dazu gerne das PEP 622 an.\n", - "\n", - "Im folgenden soll gezeigt werden, wie `if-else` Anweisungen mit `match` ersetzt werden können.\n", - "\n", - "Nutzen wir dafür das Beispiel der [HTTP Status Codes](https://en.wikipedia.org/wiki/List_of_HTTP_status_codes) mit denen Webserver mit Browsern kommunizieren. Der Bekannteste Status Code in der allgemeinen Bevölkerung ist `404 - Not Found`, welcher zurückgegeben wird wenn eine Resource im Internet (auf einem Server) nicht gefunden wurde.\n", - "\n", - "Die folgende Funktion soll einen kleinen Teil der Client Error Status Codes `4XX` für uns übersetzen.\n", - "\n", - "| Code | Explanation |\n", - "|------|--------------|\n", - "| 400 | Bad Request |\n", - "| 401 | Unauthorized |\n", - "| 403 | Forbidden |\n", - "| 404 | Not Found |\n", - "\n", - "\n", - "Klassisch und vollkommen richtig würde die Funktion wie folgt aufgebaut sein:\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "16e46879-62fe-426b-954b-902cc5049aed", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-306c298b8e352c32", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'Not Found'" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def http_400_errors(status: int) -> str:\n", - " if status == 400:\n", - " return \"Bad Request\"\n", - " elif status == 401:\n", - " return \"Unauthorized\"\n", - " elif status == 403:\n", - " return \"Forbidden\"\n", - " elif status == 404:\n", - " return \"Not Found\"\n", - " else:\n", - " return \"Unknown Status\"\n", - "\n", - "http_400_errors(404)" - ] - }, - { - "cell_type": "markdown", - "id": "09efac1e-f92a-4250-ac47-818284fbdca0", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-6c2e92150acdc4c5", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Mit dem `match` Statement spart man sich alle Ausdrücke mit der Strucktur `status ==`, der `else`-case würd in `match`-Statements mit `_` abgefangen.\n", - "\n", - "Damit hat selbige Funktion folgerichtig die Strucktur:" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "a6a89513-23bd-43b5-9f2d-869bac06150a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-cef2c7cb5bce1a40", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'Forbidden'" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def http_400_errors(status: int) -> str:\n", - " match status:\n", - " case 400:\n", - " return \"Bad Request\"\n", - " case 401:\n", - " return \"Unauthorized\"\n", - " case 403:\n", - " return \"Forbidden\"\n", - " case 404:\n", - " return \"Not Found\"\n", - " case _:\n", - " return \"Unknown Status\"\n", - "\n", - "http_400_errors(403)" - ] - }, - { - "cell_type": "markdown", - "id": "75e2e2bc-5653-4cd5-b8c8-0b606cbcbbcc", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-7381271e6bcda170", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Und bei unbekanntem Status Code:" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "b275aa3a-72eb-4725-b6ea-395b82f718cf", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-9f9a173d4193c09c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'Unknown Status'" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "http_400_errors(500)" - ] - }, - { - "cell_type": "markdown", - "id": "5faafbdb-ec5c-4f4a-aa89-03dccb6a9c1d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2b5a2381a1507c55", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Probieren Sie es selber aus.\n", - "\n", - "**Aufgabe**: Schreiben Sie eine Funktion `http_500_errors`, welche die Korresponierende Tabelle der HTTP `5XX - Server Errors` korrekt abbildet. Achten Sie darauf unbekannte Status Codes abzufangen.\n", - "\n", - "| Code | Explanation |\n", - "|------|---------------------------------|\n", - "| 500 | Internal Server Error |\n", - "| 501 | Not Implemented |\n", - "| 502 | Bad Gateway |\n", - "| 503 | Service Unavailable |\n", - "| 504 | Gateway Timeout |\n", - "| 511 | Network Authentication Required |" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "f339464a-bdde-4103-ac38-27ec6f2190b1", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-02286e2e124c39a9", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "def http_500_errors(status: int) -> str:\n", - " match status:\n", - " case 500:\n", - " return \"Internal Server Error\"\n", - " case 501:\n", - " return \"Not Implemented\"\n", - " case 502:\n", - " return \"Bad Gateway\"\n", - " case 503:\n", - " return \"Service Unavailable\"\n", - " case 504:\n", - " return \"Gateway Timeout\"\n", - " case 511:\n", - " return \"Network Authentication Required\"\n", - " case _:\n", - " return \"Unknown Status\"\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "7e74177e-e073-43ad-99a0-bb2ee56263fe", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-f6427af9d56311e2", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TEST\n", - "codes = [500, 501, 502, 503, 504, 511]\n", - "table = {\n", - " 500: \"Internal Server Error\",\n", - " 501: \"Not Implemented\",\n", - " 502: \"Bad Gateway\",\n", - " 503: \"Service Unavailable\",\n", - " 504: \"Gateway Timeout\",\n", - " 511: \"Network Authentication Required\",\n", - " }\n", - "for status in codes:\n", - " assert table[status] == http_500_errors(status)\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "id": "afe6543a-b41b-4d3c-9929-525a0463c6af", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a65f2c871406072c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Walrus Operator - Assingment Expressions\n", - "\n", - "Der Grund warum Guido van Rossum das Python Projekt verlassen hat, ist der Walrus Operator `:=`, zu finden unter [PEP 572](https://peps.python.org/pep-0572/). \n", - "\n", - "Das Offizielle Statement:\n", - "\n", - "> \"The straw that broke the camel's back was a very contentious Python enhancement proposal, where after I had accepted it, people went to social media like Twitter and said things that really hurt me personally. And some of the people who said hurtful things were actually core Python developers, so I felt that I didn't quite have the trust of the Python core developer team anymore.\"\n", - "> - Guido van Rossum\n", - "\n", - "Das Problem der Operator `:=` fügt keinerlei neue Funktionalität hinzu und erlaubt einzig und allein eine Zuweisung während einer Auswertung zu erlauben.\n", - "\n", - "Daher ein paar kurze Beispiele, lesen Sie ansonsten gerne PEP 572.\n", - "\n", - "Zuweisung mittels Walrus Operator: (Machen Sie das bitte nicht nach, Niemand wirklich Niemand möchte das sehen!)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "8055d0b2-eb9f-4a1a-ac74-4bfcd6cbee81", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-860f5501722f78aa", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "True\n", - "False\n" - ] - } - ], - "source": [ - "# Normale Zuweisung\n", - "walrus = True\n", - "print(walrus)\n", - "\n", - "# Walrus Zuweisung\n", - "(walrus := False)\n", - "print(walrus)" - ] - }, - { - "cell_type": "markdown", - "id": "af5f2aab-0e6d-41d8-b3e1-96969a5ad264", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2fb74418e2478ef5", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Berechnung und Zuweisung in einer Zeile.\n", - "\n", - "Walrus soll verwendet werden, wenn man vermeiden möchte das eine Berechnung zweimal ausgeführt wird.\n", - "\n", - "Beispiel Klassisch `n+1` wird zweimal berechnet:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "b41cae11-20f2-4500-b32a-77775502f6ea", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-85ffa763f1c26ced", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "5\n" - ] - } - ], - "source": [ - "n = 4\n", - "if (n + 1) > 3:\n", - " print(n+1)" - ] - }, - { - "cell_type": "markdown", - "id": "5ad0b0b7-5d85-4a1d-9083-30790c494035", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-da3163fec3bf5f09", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Mit Walrus lässt sich im `if` die Berechnung `n+1` der Variablen `out` zuweisen:" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "cde3f827-477c-46d4-8057-af35b694ebef", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-664ab7388a3cb90c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "5\n" - ] - } - ], - "source": [ - "n = 4\n", - "if (out := n + 1) > 3:\n", - " print(out)" - ] - }, - { - "cell_type": "markdown", - "id": "16375c7c-ef2e-44b7-a5f1-2156248f616c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-11c8ad1c8ab2ef15", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Ohne Walrus lässt sich dennoch immer vermeiden die Berechnung `n+1` zweimal auszuführen:" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "c1bf6d7e-8ce8-4770-8060-a6d18ab8d85e", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2dbb33acbcf4f8a4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "5\n" - ] - } - ], - "source": [ - "n = 4\n", - "out = n + 1\n", - "if out > 3:\n", - " print(out)" - ] - }, - { - "cell_type": "markdown", - "id": "302a6dfd-2e3d-401d-93c9-1335e081e837", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-3254f96c16f5c246", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Persönliche Meinung**: Ich rate davon ab Walrus `:=` zu verwenden. In meinen Augen macht es den Code Grundsätzlich unlesbar und spart im besten Fall 2-3 Zeilen Code. In meiner eigenen Programmiererfahrung gab es nie einen Grund den Operator zu verwenden, er fügte nie einen realen Nutzen in irgendeine meiner Berechnungen ein. Dennoch wollt ich ihnen einmal Demonstrieren wie Walrus funktioniert." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.0" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/Einführung/testfile.txt b/Material/wise_24_25/lernmaterial/Einführung/testfile.txt deleted file mode 100644 index 28bf81b..0000000 --- a/Material/wise_24_25/lernmaterial/Einführung/testfile.txt +++ /dev/null @@ -1,100 +0,0 @@ -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python -Python diff --git a/Material/wise_24_25/lernmaterial/Einrichtung/How to Jupyter.ipynb b/Material/wise_24_25/lernmaterial/Einrichtung/How to Jupyter.ipynb deleted file mode 100644 index a6d9663..0000000 --- a/Material/wise_24_25/lernmaterial/Einrichtung/How to Jupyter.ipynb +++ /dev/null @@ -1,536 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "965d3b35-ff65-4a31-93ac-0389e578772a", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "slide" - }, - "tags": [] - }, - "source": [ - "# How to Jupyter\n", - "\n", - "Jupyter Notebook is an open-source web application that allows you to create and share documents containing live code, equations, visualizations, and narrative text.\n", - "\n", - "It's widely used for interactive computing, data analysis, scientific research, education, and data visualization.\n", - "\n", - "Some key features and components of Jupyter Notebook includes:\n", - "\n", - "---\n", - "\n", - "**At the bottom left is a control pad with which you can navigate through the slides.**\n", - "\n", - "(How to create slides will be explained later.)" - ] - }, - { - "cell_type": "markdown", - "id": "263e7df3-97cc-4568-9d50-59d073d4a7d9", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "1. **Interactive Environment**\n", - "2. **Support for Multiple Programming Languages**\n", - "3. **Rich Text Support**\n", - "4. **Data Visualization**\n", - "5. **Equation Rendering**\n", - "6. **Easy Sharing**\n", - "7. **Notebook Extensions**\n", - "8. **Data Analysis and Exploration**\n", - "9. **Education and Learning**" - ] - }, - { - "cell_type": "markdown", - "id": "733cbe91-df68-44d1-b546-8c229fa0dc90", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "source": [ - "1. **Interactive Environment**: Jupyter Notebook provides an interactive environment where you can write and execute code in chunks called cells. This allows you to see the immediate results of your code as you work on it.\n", - "\n", - "2. **Support for Multiple Programming Languages**: While Jupyter was originally designed for Python, it supports various programming languages such as Julia, R, and more through language-specific kernels. Each kernel enables you to execute code written in a specific language." - ] - }, - { - "cell_type": "markdown", - "id": "01244173-08be-4c4c-9675-27f09620e34b", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "source": [ - "3. **Rich Text Support**: You can combine code cells with text cells to create a narrative that explains the code, its purpose, and the analysis being performed. This makes it a powerful tool for creating data-driven documents and reports.\n", - "\n", - "4. **Data Visualization**: Jupyter Notebook supports the integration of various data visualization libraries such as Matplotlib, Seaborn, Plotly, and more. This allows you to create charts, graphs, and other visualizations to better understand your data." - ] - }, - { - "cell_type": "markdown", - "id": "2d52825d-b8fa-456b-98f4-574585e3b3bb", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "source": [ - "5. **Equation Rendering**: It supports rendering mathematical equations using LaTeX notation, which is useful for scientific and mathematical documentation.\n", - "\n", - "6. **Easy Sharing**: Jupyter Notebooks can be easily shared with colleagues, collaborators, or the public. Notebooks can be exported to various formats such as HTML, PDF, and slideshows. There are also platforms like GitHub and JupyterHub that allow for collaborative editing and sharing." - ] - }, - { - "cell_type": "markdown", - "id": "2c1679b9-b0db-4bf4-9bbc-9d33ca7ffeb0", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "source": [ - "7. **Notebook Extensions**: Jupyter Notebook has a wide range of extensions that can be added to enhance functionality. These extensions can provide additional features like code linting, spell checking, and more.\n", - "\n", - "8. **Data Analysis and Exploration**: Jupyter Notebook is widely used for data analysis and exploration tasks. Analysts and researchers can import data, clean it, perform statistical analysis, and visualize the results all within the same document.\n", - "\n", - "9. **Education and Learning**: Jupyter Notebook is used in educational settings to teach programming, data science, and various scientific concepts. Its interactive nature helps learners experiment and grasp concepts more effectively." - ] - }, - { - "cell_type": "markdown", - "id": "10d93371-42d5-40df-8a30-2ff49dde94d5", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "source": [ - "---" - ] - }, - { - "cell_type": "markdown", - "id": "6bce7ad3-61cd-4087-b35e-bddcb8c9d3c8", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "slide" - }, - "tags": [] - }, - "source": [ - "## Install Python\n", - "\n", - "In this module we will learn the programming language Python. To do this, we need to install it on our system in order to be able to use Jupyter Notebook in advance.\n", - "\n", - "The [Python.org](https://www.python.org/) website contains a download link for each operating system. Under [www.python.org/downloads/](https://www.python.org/downloads/) you can download the latest Python version.\n", - "\n", - "After following the installation wizard (this depends heavily on which operating system you are using, so we do not show this here), you have successfully installed Python.\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "eec4a5bc-9c06-4680-9aae-d388f0a2bec1", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "slide" - }, - "tags": [] - }, - "source": [ - "## Opening a Terminal\n", - "\n", - "**Windows**: \n", - "\n", - "1. `Press Start` (⊞ - Windows Symbol) -> type and search for `cmd`\n", - "2. Or Press the Windows Symbol ⊞ + the R key `(Windows + R)` -> type `cmd` in the window that appeard -> press `Enter`\n", - "\n", - "**Mac**:\n", - "\n", - "Open launchpad and Search for `Terminal`\n", - "\n", - "**Linux**:\n", - "\n", - "It depends on your Environment. But `Ctrl + Alt + T` should do the Trick on every System." - ] - }, - { - "cell_type": "markdown", - "id": "50a7f663-3a14-4de7-bf03-edaf571681d8", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "slide" - }, - "tags": [] - }, - "source": [ - "## Upgrading Pip and Installing Jupyter\n", - "\n", - "---\n", - "\n", - "### Pip - Python Package Index\n", - "\n", - "pip is the de-facto and recommended package management programme for Python packages from the Python Package Index (PyPI). At the beginning, the project was called \"pyinstall\".\n", - "\n", - "It's website is found under [pypi.org](https://pypi.org/). Every Package you need, can and should be derived from PyPI.\n", - "\n", - "---\n", - "\n", - "After opening the terminal, pip should first be updated to the latest version. To do this, enter the command:\n", - "\n", - "`python3 -m pip install -U pip`" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "99fcae70-17c9-447d-afdb-1e2cd41c3457", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: pip in /home/phil/Desktop/einfuhrung-in-die-programmierung/env/lib/python3.11/site-packages (23.2.1)\n" - ] - } - ], - "source": [ - "!python3 -m pip install -U pip" - ] - }, - { - "cell_type": "markdown", - "id": "99db8dd0-cd07-4a13-a9e8-073188d7a492", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "source": [ - "---" - ] - }, - { - "cell_type": "markdown", - "id": "3f2a5398-4480-4db6-a4dd-7bba2bdf90a3", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "slide" - }, - "tags": [] - }, - "source": [ - "### Installing Jupyter\n", - "\n", - "Now we can install some software we only need two packages depending on your need.\n", - "\n", - "`virtualenv` is a tool to create isolated Python environments. You can read more about it in the [Virtualenv documentation](https://virtualenv.pypa.io/en/stable/)." - ] - }, - { - "cell_type": "markdown", - "id": "3a6b4743-7d3a-4e87-8e6a-108d526df1ca", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "1. We need to install the package `virtualenv` (venv)\n", - "\n", - "`python3 -m pip install virtualenv`" - ] - }, - { - "cell_type": "markdown", - "id": "9eaf8cf1-91e8-47cb-85a6-7687b641ecac", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "2. Now we can create an virtual environment in any folder we want. (A good practice is a venv for every project)\n", - "\n", - "`python3 -m venv env`\n", - "\n", - "the name `env` is the folder which has all of our environment information, it can be named everything, but for convinence `env` should be used." - ] - }, - { - "cell_type": "markdown", - "id": "810aa9c6-4a5d-4f85-8168-31497850f88b", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "3. After installing `virtualenv` we need to activate it\n", - "\n", - "**Windows**: `.\\env\\Scripts\\activate`\n", - "\n", - "**Linux / Mac**: `source env/bin/activate`\n", - "\n", - "your command prompt will be modified to reflect the change." - ] - }, - { - "cell_type": "markdown", - "id": "d9f09c52-1bea-41e7-a6f8-f19d73553687", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "4. Now you can install jupyter and other dependencies without tinkering with your system\n", - "\n", - "`pip install jupyterlab`\n", - "\n", - "-> We can use pip direct because we specified the python version with venv implicitly." - ] - }, - { - "cell_type": "markdown", - "id": "92bbebdf-2dd0-471e-a98d-74ebdf3e1926", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "source": [ - "---" - ] - }, - { - "cell_type": "markdown", - "id": "c889baa0-4202-4811-89b9-8b8bb578f05a", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "slide" - }, - "tags": [] - }, - "source": [ - "## Starting Jupyter for the first time\n", - "\n", - "the last thing we need to tab out of the command line is to start Jupyter\n", - "\n", - "therefor type `jupyter lab` and Enter. Do not close the command line it will stop jupyter!\n", - "\n", - "After a little waiting time jupyter prompts you with messages one of them should look like:\n", - "\n", - "`http(s):////lab`\n", - "\n", - "copy the url and open it in your Webbrowser of Choice. Now we can Proceed.\n", - "\n", - "**Note**: This step needs to be done everytime you want to start Jupyter!\n", - "\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "594997a1-37ed-42a4-835d-5a4ab92eea70", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "slide" - }, - "tags": [] - }, - "source": [ - "# Alternatives " - ] - }, - { - "cell_type": "markdown", - "id": "1a432129-1fcb-4ee8-a2eb-ebca101dd501", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "## (Mini)conda \n", - "\n", - "conda from Ananconda Inc. is an open source package and environment manager for many languages that encludes everything we needs.\n", - "\n", - "For most purposes miniconda should do the trick. You can download it here [conda docs](https://docs.conda.io/en/latest/miniconda.html)\n", - "\n", - "After installing you can change every `python3 -m pip` and `pip` command with `conda`." - ] - }, - { - "cell_type": "markdown", - "id": "31415a9f-6949-434a-b714-c1c36dddf99a", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "## Jupyter Lab Desktop \n", - "\n", - "As there description on [GitHub](https://github.com/jupyterlab/jupyterlab-desktop) stated \n", - "\n", - "**JupyterLab Desktop is the cross-platform desktop application for JupyterLab. It is the quickest and easiest way to get started with Jupyter notebooks on your personal computer, with the flexibility for advanced use cases.**\n", - "\n", - "its nothing else than a selfcontained webbrowser bundeld with Jupyter Lab. You can download a binary for your operating System under there [GitHub Releases](https://github.com/jupyterlab/jupyterlab-desktop/releases) page.\n" - ] - }, - { - "cell_type": "markdown", - "id": "a9d2fead-7d7e-427c-bf35-0f5d379f9ddc", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "## Note\n", - "\n", - "Every Process has its Advantages and Disadvantages and depends on your needs and workflow.\n", - "\n", - "The easiest way isn't always the best.\n", - "\n", - "If you have no command line experience try to get used to it and don't use Jupyter Lab Desktop." - ] - }, - { - "cell_type": "markdown", - "id": "68563ada-3ac1-421b-ab82-5be195a75f23", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "source": [ - "---" - ] - }, - { - "cell_type": "markdown", - "id": "e66d9571-a154-4e4b-b612-9ba9151cd6cd", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "source": [ - "# Jupyter Tricks\n", - "\n", - "## Package handeling\n", - "\n", - "Our course provides a requirements.txt file, take a look.\n", - "\n", - "This file can be created using `pip freeze > requirements.txt` and contains all of your environment data.\n", - "\n", - "To use the file we need to install the content. Thankfully pythons pip provides an easy way to this\n", - "\n", - "just start a new jupyter notebook and type in the first cell `!pip install -r requirements.txt` and run the cell.\n", - "\n", - "## Markdown \n", - "\n", - "Making notes in Jupyter is just as powerful. It uses a technology named Markdown which is just another way to write [HTML](https://en.wikipedia.org/wiki/HTML) (The Backbone of the Internet)\n", - "\n", - "Some good cheatSheets to learn this simple typewriter can be found under:\n", - "\n", - "1. [Markdown Guide](https://www.markdownguide.org/cheat-sheet/)\n", - "2. [Adam P Markdown Wiki](https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet)\n", - "3. [Markdown Table Generator](https://www.tablesgenerator.com/markdown_tables)\n", - "\n", - "## Slides and Presentations\n", - "\n", - "We have a whole Lesson for that but here is a quick example to look in [mljar.com](https://mljar.com/blog/jupyter-notebook-presentation/)\n", - "\n", - "## Debugging\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d0f136f2-5975-489d-819b-b6e6296286a6", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/Einrichtung/Install Python.ipynb b/Material/wise_24_25/lernmaterial/Einrichtung/Install Python.ipynb deleted file mode 100644 index 0f7a9f2..0000000 --- a/Material/wise_24_25/lernmaterial/Einrichtung/Install Python.ipynb +++ /dev/null @@ -1,33 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "id": "287561ee-f201-49ca-867c-dd8c2028b82e", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/Einrichtung/Jupyter Slideshow.ipynb b/Material/wise_24_25/lernmaterial/Einrichtung/Jupyter Slideshow.ipynb deleted file mode 100644 index 56a91ff..0000000 --- a/Material/wise_24_25/lernmaterial/Einrichtung/Jupyter Slideshow.ipynb +++ /dev/null @@ -1,33 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "id": "2316e04b-4795-443d-8370-57302600dc81", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/Einrichtung/encrypted.bin b/Material/wise_24_25/lernmaterial/Einrichtung/encrypted.bin deleted file mode 100644 index b326b3a..0000000 --- a/Material/wise_24_25/lernmaterial/Einrichtung/encrypted.bin +++ /dev/null @@ -1,2 +0,0 @@ -8ɵ -jΆKi$& =̺(NgT \ No newline at end of file diff --git a/Material/wise_24_25/lernmaterial/Ergebnisse_23/app.py b/Material/wise_24_25/lernmaterial/Ergebnisse_23/app.py deleted file mode 100644 index 34d6628..0000000 --- a/Material/wise_24_25/lernmaterial/Ergebnisse_23/app.py +++ /dev/null @@ -1,93 +0,0 @@ -from dash import Dash, html, dcc, dash_table -import dash_bootstrap_components as dbc -import plotly.graph_objects as go -from plotly.subplots import make_subplots -import pandas as pd -import numpy as np - -# Read Data -df = pd.read_excel('evaluation.xlsx', sheet_name='results') - -# Add graph data -course = ["{}
n={}".format(c,s) for c, s in zip(df['Course'], df['Submissions'])] -avg = df['Avg. Score'] -max = df['Max Score'] - -# Relative data -max_rel = df['Max Score'].sum() -avg_rel = np.array([c/s*100 for c, s in zip(df['Avg. Score'], df['Max Score'])]) -avg_rel_sum = df['Avg. Score'].sum() / max_rel * 100 - -# Make traces for graph -avg_trace = go.Bar(x=course, y=avg, xaxis='x1', yaxis='y1', - marker=dict(color='#0099ff'), - name='Average Score
over all Students') -max_trace = go.Bar(x=course, y=max, xaxis='x1', yaxis='y1', - marker=dict(color='#404040'), - name='Possible Max Score
Per Notebook') -avg_rel_trace = go.Scatter(x=course, y=avg_rel, xaxis='x1', yaxis='y2', - marker=dict(color='#e00030'), - name='Average Score (in %)
Per Notebook') - -perc_trace = go.Scatter(x=course, y=avg_rel, xaxis='x1', yaxis='y2', - mode="text+lines", - marker=dict(color='#e00030'), - name='Average Score (in %)
Per Notebook', - text=[str(n) for n in avg_rel], texttemplate='%{text:.0f}% ', - textposition=[ - 'top center', 'top right', 'middle left', - 'middle left', 'middle left', 'top left', - 'top left', 'bottom left' - ], - textfont={'size': 12}) - -def bar(): - fig = make_subplots(specs=[[{"secondary_y": True}]]) - - fig.update_layout(template="plotly_dark") - - # Y-Axis Title - fig.update_yaxes(title_text="Relative Score (in %)", secondary_y=True) - fig.update_yaxes(title_text="Score", secondary_y=False) - - # Add Plots - fig.add_trace(avg_trace) - fig.add_trace(max_trace) - fig.add_trace(perc_trace) - #fig.add_trace(avg_rel_trace) - return fig - - -# Create Dash -app = Dash(__name__, external_stylesheets=[dbc.themes.CYBORG, dbc.icons.FONT_AWESOME]) - -header = dbc.Row([ - html.H1('Einführung in die Programmierung für Nicht-Informatiker*innen', className="text-primary text-center fs-3"), - html.H2('WiSe 23/24 Results', className="text-secondary text-center fs-4") - ]) - - -app.layout = dbc.Container([ - header, - dbc.Row([dcc.Graph(figure=bar())]), - html.Br(), - dbc.Row([ - dbc.Alert([ - html.I(className="bi bi-info-circle-fill me-2"), - html.Big("{:.0f}% of all tasks were solved correctly.".format(avg_rel_sum), className="text-center") - ], - color='info', className="d-flex align-items-center") - ]) -]) - - - -if __name__ == '__main__': - #app.run(debug=True) - #from plotly.offline.offline import _plot_html - import plotly - plotly.offline.plot( - bar(), - show_link=False, - filename = 'eval.html' - ) \ No newline at end of file diff --git a/Material/wise_24_25/lernmaterial/Ergebnisse_23/course_evaluation.ipynb b/Material/wise_24_25/lernmaterial/Ergebnisse_23/course_evaluation.ipynb deleted file mode 100644 index bfcd27b..0000000 --- a/Material/wise_24_25/lernmaterial/Ergebnisse_23/course_evaluation.ipynb +++ /dev/null @@ -1,1796 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 160, - "id": "1afb1f4a-8280-49c2-95eb-a43dc0a9d991", - "metadata": {}, - "outputs": [], - "source": [ - "import plotly.express as px\n", - "import plotly.graph_objects as go\n", - "import plotly.figure_factory as ff\n", - "import pandas as pd\n", - "import numpy as np" - ] - }, - { - "cell_type": "code", - "execution_count": 196, - "id": "f2d590e0-5215-436c-9334-d7c5013d5ddf", - "metadata": {}, - "outputs": [], - "source": [ - "df = pd.read_excel('evaluation.xlsx', sheet_name='results')" - ] - }, - { - "cell_type": "code", - "execution_count": 248, - "id": "a3cce4f5-4feb-4fec-8c7c-05201254edec", - "metadata": {}, - "outputs": [], - "source": [ - "# Add graph data\n", - "course = [\"{}
n={}\".format(c,s) for c, s in zip(df['Course'], df['Submissions'])]\n", - "avg = df['Avg. Score']\n", - "max = df['Max Score']\n", - "\n", - "# Relative data\n", - "max_rel = df['Max Score'].sum()\n", - "avg_rel = np.array([c/s*100 for c, s in zip(df['Avg. Score'], df['Max Score'])])\n", - "avg_rel_sum = df['Avg. Score'].sum() / max_rel * 100\n", - "\n", - "# Make traces for graph\n", - "trace1 = go.Bar(x=course, y=avg, xaxis='x2', yaxis='y2',\n", - " marker=dict(color='#0099ff'),\n", - " name='Average Score
over all Students')\n", - "trace2 = go.Bar(x=course, y=max, xaxis='x2', yaxis='y2',\n", - " marker=dict(color='#e0e0e0'),\n", - " name='Possible Max Score
Per Notebook')\n", - "trace3 = go.Scatter(x=course, y=avg_rel, xaxis='x2', yaxis='y2',\n", - " marker=dict(color='#e00030'),\n", - " name='Average Score (in %)
Per Notebook')\n", - "\n", - "trace_text = go.Scatter(x=course, y=avg, xaxis='x2', yaxis='y2',\n", - " mode=\"text\",\n", - " marker=dict(color='#e00030'),\n", - " name='Average Score (in %)
Per Notebook',\n", - " text=[str(n) for n in avg_rel], texttemplate='%{text:.2f}% ', textposition='top left', textfont={'size': 15})" - ] - }, - { - "cell_type": "code", - "execution_count": 249, - "id": "41a46138-26e4-4567-8cd9-9097f5170f16", - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.plotly.v1+json": { - "config": { - "plotlyServerURL": "https://plot.ly" - }, - "data": [ - { - "colorscale": [ - [ - 0, - "#00083e" - ], - [ - 0.5, - "#ededee" - ], - [ - 1, - "#ffffff" - ] - ], - "hoverinfo": "none", - "opacity": 0.75, - "showscale": false, - "type": "heatmap", - "z": [ - [ - 0, - 0, - 0, - 0 - ], - [ - 0.5, - 0.5, - 0.5, - 0.5 - ], - [ - 1, - 1, - 1, - 1 - ], - [ - 0.5, - 0.5, - 0.5, - 0.5 - ], - [ - 1, - 1, - 1, - 1 - ], - [ - 0.5, - 0.5, - 0.5, - 0.5 - ], - [ - 1, - 1, - 1, - 1 - ], - [ - 0.5, - 0.5, - 0.5, - 0.5 - ], - [ - 1, - 1, - 1, - 1 - ] - ] - }, - { - "marker": { - "color": "#0099ff" - }, - "name": "Average Score
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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Initialize a figure with ff.create_table(table_data)\n", - "fig = ff.create_table(df, height_constant=60)\n", - "\n", - "# Add trace data to figure\n", - "fig.add_traces([trace1, trace2, trace_text])\n", - "\n", - "# initialize xaxis2 and yaxis2\n", - "\n", - "fig['layout']['xaxis2'] = {}\n", - "fig['layout']['yaxis2'] = {}\n", - "#fig['layout']['yaxis3'] = {}\n", - "\n", - "\n", - "# Edit layout for subplots\n", - "fig.layout.yaxis.update({'domain': [0, .45]})\n", - "fig.layout.yaxis2.update({'domain': [.6, 1], 'side': 'left'})\n", - "#fig.layout.yaxis3.update({'domain': [.6, 1], 'side': 'left', 'range': [0, 100]})\n", - "\n", - "# The graph's yaxis2 MUST BE anchored to the graph's xaxis2 and vice versa\n", - "fig.layout.yaxis2.update({'anchor': 'x2'})\n", - "fig.layout.xaxis2.update({'anchor': 'y2'})\n", - "fig.layout.yaxis2.update({'title': 'Score'})\n", - "#fig.layout.yaxis3.update({'anchor': 'x2'})\n", - "#fig.layout.yaxis3.update({'title': 'Relative Score (in %)'})\n", - "\n", - "# Update the margins to add a title and see graph x-labels.\n", - "fig.layout.margin.update({'t':75, 'l':50})\n", - "fig.layout.update({'title': 'WiSe 23/24 Results for Einführung in die Programmierung für Nicht-Informatiker*innen', 'title_font_size': 30})\n", - "\n", - "# Update the height because adding a graph vertically will interact with\n", - "# the plot height calculated for the table\n", - "fig.layout.update({'height':800})\n", - "\n", - "fig.update_layout(template=\"plotly_dark\")\n", - "\n", - "# Add Text\n", - "fig.add_annotation(text=\"{:.2f}% of all tasks were solved correctly.\".format(avg_rel_sum),\n", - " xref=\"paper\", yref=\"paper\",\n", - " x=0.1, y=0.5, showarrow=False)\n", - "\n", - "fig.add_annotation(text=\"Optional Exercise\", xref=\"x2\", yref=\"y2\", x=2, y=6, showarrow=True)\n", - "\n", - "fig.update_annotations(font_size=18)\n", - "\n", - "# Plot!\n", - "fig.show()\n" 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-ziafont==0.6 -ziamath==0.8.1 -zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1677313463193/work -zstandard==0.19.0 diff --git a/Material/wise_24_25/lernmaterial/Extras/to do.ipynb b/Material/wise_24_25/lernmaterial/Extras/to do.ipynb deleted file mode 100644 index d1510ae..0000000 --- a/Material/wise_24_25/lernmaterial/Extras/to do.ipynb +++ /dev/null @@ -1,77 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "3069696b-bbe6-4fd6-ba13-2affa071d865", - "metadata": {}, - "source": [ - "# Was ist das eigentliche Lernziel? \n", - "\n", - "- Arbeiten mit Daten\n", - "- Daten interpretieren \n", - " - Visuell (Karten, Graphen, Tabellen)\n", - " - Mittels Stochastischer Analyse (Mittelwert, Median)\n", - " - Zufallszahlen (Zum generieren von Testdaten)?\n", - "- Googlen lernen\n", - "- Dokumentationen Lesen\n", - "\n", - "# TO DO\n", - "\n", - "- [] Slideshow erklären\n", - "- [] Mehr Bilder\n", - "- [] Python einführung?\n", - "- [] Folium als eigene Lerneinheit -> Projekt schwieriger machen?\n", - "- [] SciPy Funktionen und/oder arbeiten mit Statistic Daten?" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "313bf238-67bc-4cb4-8331-6e183427bf70", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Note: you may need to restart the kernel to use updated packages.\n" - ] - } - ], - "source": [ - "pip freeze > requirements.txt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3fa17fc4-29a7-4e97-9836-50e85693cec1", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.16" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/Folium & Pandas/Einführung Folium.ipynb b/Material/wise_24_25/lernmaterial/Folium & Pandas/Einführung Folium.ipynb deleted file mode 100644 index bd5d053..0000000 --- a/Material/wise_24_25/lernmaterial/Folium & Pandas/Einführung Folium.ipynb +++ /dev/null @@ -1,6246 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "11ce8688-2dd2-4a18-aa6c-bce96a801782", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1720c646ec279d2e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# 5. Programmierübung: Folium\n", - "\n", - "
\n", - "
\n", - " Willkommen zur fünften Programmierübung Einführung in Python 3.\n", - "
\n", - " \n", - "
\n", - "\n", - "Wenn Sie Fragen oder Verbesserungsvorschläge zum Inhalt oder Struktur der Notebooks haben, dann können sie eine E-Mail an Phil Keier ([p.keier@hbk-bs.de](mailto:p.keier@hbk-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) oder Martin Le ([martin.le@tu-bs.de](mailto:martin.le@tu-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) schreiben.\n", - "\n", - "Link zu einem Python Spickzettel: [hier](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf)\n", - "\n", - "Der Großteil des Python-Tutorials stammt aus der Veranstaltung _Deep Learning Lab_ und von [www.python-kurs.eu](https://www.python-kurs.eu/python3_kurs.php) und wurde für _Signale und Systeme_, sowie _Einführung in die Programmierung für Nicht Informatiker_ angepasst.\n", - "\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "ebd295cc-8e6d-435e-a91a-881bf3798b5b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-275178a1d9bade57", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Geospatial Data\n", - "\n", - "In the following we will look at how maps can be displayed using Python & the Folium API.\n", - "\n", - "[Folium](https://python-visualization.github.io/folium/) is a Python wrapper that binds the open source library [Leaflet.js](https://leafletjs.com/).\n", - "\n", - "In this way, the developers aim to combine the advantages of data processing with Python, as well as the visualization advantages of the Web.\n", - "\n", - "Objectives of this exercise:\n", - "1. create simple maps with different terrain options\n", - "2. set and adjust markers\n", - " 1. creating a marker\n", - " 2. popup & tooltip\n", - " 3. icons & colors\n", - " 4. circle marker\n", - " 5. setting own markers\n", - "3. layer groups\n", - "4. plugins\n", - "5. handling GeoJSON data\n", - "\n", - "\n", - "__For the entire exercise, all parameters are basically given for illustrative purposes. Unless explicitly requested, you do not have to do this.__" - ] - }, - { - "cell_type": "markdown", - "id": "22adfbb3-e71d-4228-ac02-b8c7135a8943", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d928ae513b1e6ce0", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Import Folium\n", - "\n", - "First we need to Import Folium as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "2725fd60-dbe5-4739-8cbf-3ef9a585032f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a22fce114edbd7bf", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Execute this cell everytime you restart the notebook!!!\n", - "import folium" - ] - }, - { - "cell_type": "markdown", - "id": "4a676854-ebc9-439f-8414-5fe39e65dc13", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d18e7620cb44ddf4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Creating maps\n", - "\n", - "The default object of every Folium App is the [Map](https://python-visualization.github.io/folium/modules.html#module-folium.map).\n", - "\n", - "### Location\n", - "To create it, you only need the _location_ parameter which takes a tuple (or list) of two floats.\n", - "The first value is the latitude (lat) and the second the longitude (lon). (For Braunschweig this would be lat: 52.264150 & lon: 10.526420)\n", - "\n", - "### Tiles\n", - "Folium supports the display of different types of maps. These are specified as a string for the tiles parameter when creating the map.\n", - "\n", - "Possible maps are:\n", - "\n", - "1. _OpenStreetMap_ (default)\n", - "2. _Stamen Terrain_\n", - "3. _Stamen Toner_\n", - "\n", - "### Zoom\n", - "The default _zoom_ setting of the map can be adjusted by the following 3 parameters:\n", - "\n", - "- _zoom_start_ (default: 10) creates the map with a zoom setting between _min_zoom_ & _max_zoom_.\n", - "- _min_zoom_ (default: 0) & _max_zoom_ (default: 18) limits the possible zoom radius. Generally not necessary.\n", - "\n", - "### Optimization\n", - "If one of the following cells has excessive computation times, the parameter _prefer_canvas=True_ should be specified for the map object. This will force the web browser to use the web graphics library ([WebGL](https://github.com/KhronosGroup/WebGL)) and will result in a speed bonus, e.g. thousands of markers. By default _prefer_canvas_ is set to _False_ and should only be used if you really want to display lots of data!\n", - "\n", - "The following example illustrates the creation of the map object:" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "ecd035c9-c1bc-4393-8681-2c058caca527", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1a3da7284c8a4450", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m = folium.Map(\n", - " location=(52.264150, 10.526420),\n", - " tiles='OpenStreetMap',\n", - " #iles='Stamen Toner',\n", - " zoom_start=13,\n", - " prefer_canvas=False\n", - " )\n", - "\n", - "m" - ] - }, - { - "cell_type": "markdown", - "id": "94976e7f-1354-428e-ba9d-32ad696e27f4", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-bbb8367d84f43da2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Exercise 1: Create a map\n", - "\n", - "Create a map with the coordinates of your hometown, or your favorite city (Braunschweig does not count as a solution). Save your Solution in the variable `my_map`.\n", - "\n", - "Adjust the _zoom_start_ parameter so that your place is visible in the center. To find out which coordinates your place has you can use the online tool [latlong.net](https://www.latlong.net/).\n", - "\n", - "Use _CartoDB Positron_ as tileset.\n", - "\n", - "Set the _prefer_canvas_ parameter to _True_.\n", - "\n", - "Also please add your city as a comment.\n", - "\n", - "In case of problems, please check the Folium API [Map](https://python-visualization.github.io/folium/modules.html#module-folium.map) object.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "a05ad147-1990-4d96-983d-c128b60125b5", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-6099ccde55688a94", - "locked": false, - "points": 4, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Your City: \n", - "### BEGIN SOLUTION\n", - "# Your City: Braunschweig\n", - "my_map = folium.Map(\n", - " location=(52.264150, 10.526420),\n", - " tiles='cartodb positron',\n", - " zoom_start=13,\n", - " prefer_canvas=True\n", - " )\n", - "my_map\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "b554a2ec-d32e-4ea6-a91f-a1fe554804cd", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-1b94f6587760b8e8", - "locked": true, - "points": 3, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Your Solutions are tested here...\n", - "assert isinstance(my_map, folium.Map)\n", - "assert isinstance(my_map.location, list)\n", - "assert len(my_map.location) == 2" - ] - }, - { - "cell_type": "markdown", - "id": "d057d2a5-9699-4a88-bea7-46adaa096f54", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ad368f2ba205c714", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Marker \n", - "\n", - "The quintessence of any GeoSpatial Data project is the visualization of data.\n", - "\n", - "The [Marker](https://python-visualization.github.io/folium/modules.html#folium.map.Marker) object expects the following parameters:\n", - "- _location_ (Mandatory) Tuple of Floats (Like Map Object) to set a marker.\n", - "- _popup_ (String or folium.Popup object) small info box that can be customized using HTML\n", - "- _tooltip_ (String) hover text with instruction\n", - "- _icon_ (folium.Icon) to customize the marker\n", - "- _dragable_ (bool, default False) allows the user to move the marker\n", - "\n", - "To set a simple marker it is first created with a location.\n", - "Then the marker has to be added to the map with the function _add_to()_. \n", - "\n", - "In the following the HBK BS should be marked on the map." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "59a91300-1dc7-4d27-826c-14a94fa13a45", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3b289b02455e2512", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m = folium.Map(\n", - " location=(52.264150, 10.526420),\n", - " tiles='OpenStreetMap',\n", - " zoom_start=14,\n", - " prefer_canvas=False\n", - " )\n", - "\n", - "my_marker = folium.Marker(\n", - " location=(52.25802230834961, 10.503097534179688)\n", - " )\n", - "\n", - "my_marker.add_to(m)\n", - "\n", - "m" - ] - }, - { - "cell_type": "markdown", - "id": "179b1901-ac37-4724-aa59-c76345c61805", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d9ba7c4b83368403", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "After executing the code you should see a marker at the address Johannes-Selenka-Platz 1, 38118 Braunschweig.\n", - "\n", - "Since this is relatively boring we will now try to adapt the marker to our needs." - ] - }, - { - "cell_type": "markdown", - "id": "071b4725-8f13-4d38-9ea6-8f62826baf17", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0fd8e8915f7f9613", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "### Popup & Tooltip\n", - "\n", - "The marker accepts strings as _tooltip_ & _popup_ parameters, as the following example demonstrates.\n", - "This is the most primitive form of how a simple marker can be created with information.\n", - "\n", - "To understand what the _tooltip_ parameter does, run the next example and hover over the marker. Clicking on the marker will display the contents of the _popup_ parameter." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "33a5ffa1-7f39-46d4-9a17-35b3c8eb26ef", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8b6f8ca79a9a05c3", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m = folium.Map(\n", - " location=(52.264150, 10.526420),\n", - " tiles='OpenStreetMap',\n", - " zoom_start=16,\n", - " prefer_canvas=False\n", - " )\n", - "\n", - "# Schloss Braunschweig\n", - "castle_popup = \"Ritterbrunnen 1, 38100 Braunschweig\"\n", - "castle_tooltip = \"More about the castle\"\n", - "\n", - "\n", - "castle_marker = folium.Marker(\n", - " location=(52.2643, 10.529),\n", - " popup=castle_popup,\n", - " tooltip=castle_tooltip\n", - " )\n", - "castle_marker.add_to(m)\n", - "\n", - "m" - ] - }, - { - "cell_type": "markdown", - "id": "cadd0223-d6d5-445a-ac7b-ead3b010260f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-cfc72d893f2572ff", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "### HTML Popups\n", - "\n", - "To do justice to the inner artist as well, markers can also be designed in Folium using the tools of the modern internet.\n", - "\n", - "The Folium object [Popup](https://python-visualization.github.io/folium/modules.html#folium.map.Popup) can be used to display simple HTML strings. \n", - "\n", - "Before we get to the main features of HTML for Folium, we will first take a look at the other optional parameters of the Popup object.\n", - "\n", - "These include:\n", - "\n", - "- _parse_html_ (bool, default False) not normally needed, forces Folium to interpret the HTML string first. Useful for any customization via JavaScript.\n", - "- _max_width_ (int or str, default '100%') sets the maximum width of the popup. For the str parameter it is important to include the '%' character.\n", - "- _show_ (bool, default False) if this parameter is set to _True_, the popup will load when the map is opened.\n", - "- _sticky_ (bool, default False) if this parameter is set to _True_, the popup will not be closed.\n", - "\n", - "\n", - "Mandatory for creating a popup is the _html_ parameter. This parameter requires a (multi-)string containing HTML code.\n", - "\n", - "As an example we will create a HBK BS popup which renders the following HTML:\n", - "\n", - "---\n", - "

\n", - "\"HBK\n", - "

\n", - "

Johannes-Selenka-Platz 1

\n", - "

38118 Braunschweig

\n", - "

Germany, DE

\n", - "

Visit: hbk-bs.de

\n", - "\n", - "---\n", - "\n", - "\n", - "and the associated HTML:\n", - "\n", - "\n", - "```html\n", - "

\n", - "\"HBK\n", - "

\n", - "

Johannes-Selenka-Platz 1

\n", - "

38118 Braunschweig

\n", - "

Germany, DE

\n", - "

Visit: hbk-bs.de

\n", - "```\n", - "\n", - "\n", - "Do not let this confuse you. The statements in between `<> & ` are HTML tags, for example `

` represents a 'Paragraph' & `` represents a hyperlink. \n", - "For the text semantic elements I recommend the following [reference](https://www.w3.org/html/wiki/Elements).\n", - "\n", - "In Python, no HTML can be displayed directly. For this, the entire HTML must be within a string. To simplify the readability Python offers the multiline string notated with 3 `'''`:\n", - "\n", - "\n", - "\n", - "'''\n", - "hi I am\n", - "\n", - "\n", - "a\n", - "\n", - "multiline string\n", - "'''\n", - "\n", - "\n", - "And as with the already known string, this one supports all string format options. But more about that later in the Factory Patterns part.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "db9725a6-c438-4a23-9e5b-5b401d412832", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b683105305025808", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# HBK Braunschweig\n", - "hbk_popup_html = folium.Popup(\n", - " '''\n", - "

\n", - " \"HBK\n", - "

\n", - "

Johannes-Selenka-Platz 1

\n", - "

38118 Braunschweig

\n", - "

Germany, DE

\n", - "

Visit: hbk-bs.de

\n", - " ''',\n", - " show=True\n", - " )\n", - "\n", - "hbk_tooltip = \"More about the university\"" - ] - }, - { - "cell_type": "markdown", - "id": "2773d557-e6ca-406c-9de1-b9c0675e0604", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-cf6a889f7ebf8a54", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "### Icon\n", - "\n", - "The last step to complete the marker is the [Icon](https://python-visualization.github.io/folium/modules.html#folium.map.Icon) object.\n", - "\n", - "Unlike the other objects discussed, this one has no mandatory parameters.\n", - "\n", - "As usual, here is an explanation of the parameters:\n", - "- _color_ (str, default 'blue') sets the color of the marker.\n", - "\n", - " Possible colors are: \n", - " - red, blue, green,\n", - " - purple, orange, darkred,\n", - " - lightred, beige, darkblue,\n", - " - darkgreen, cadetblue, darkpurple,-\n", - " - white, pink, lightblue,\n", - " - lightgreen, gray, black,\n", - " - lightgray\n", - " \n", - " \n", - " or any hexadecimal value noted with '#XXXXXX'.\n", - "\n", - "- _icon_color_ (str, default 'white') sets the color of the glyphicon. The possible color values are the same as for _color_.\n", - "- _angle_ (int, default 0) sets the rotation of the glyphicon. The possible values are limited to the range 0-359 integer.\n", - "- _prefix_ (str, default 'glyphicon) can take two values 'fa' for the icons of the website [Font Awesome](https://fontawesome.com/icons) (Attention not all icons are free) and 'glyphicon' for the icons of the website [Bootstrap](https://getbootstrap.com/docs/3.3/components/) (All icons behind this link are free). The value in _prefix_ specifies which website is queried. \n", - "- _icon_ (str, default 'info-sign') specifies the name of the icon to be displayed and is therefore dependent on the _prefix_ parameter. The default icon is 'glyphicon glyphicon-info-sign'.\n", - "\n", - "To design a reasonable icon for the HBK marker the following example should be understood:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "8f79bd13-82f0-478c-8409-1e97d79d4b26", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5e1cf782bc0512c1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "hbk_icon = folium.Icon(\n", - " color='black',\n", - " icon_color='#deddda',\n", - " prefix='glyphicon',\n", - " icon='glyphicon-home',\n", - " angle=0\n", - " )" - ] - }, - { - "cell_type": "markdown", - "id": "4a2ffb76-8045-4cba-a416-5555f521889b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8d4b5a5cb9cc90cc", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "After successfully creating the three variables _hbk_tooltip_, _hbk_html_popup_ & _hbk_icon_, we now display the customized marker:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "852785cc-0dff-4c2c-b6bb-20d08e26349f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-62068ff221befbb2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m = folium.Map(\n", - " location=(52.258, 10.5),\n", - " tiles='OpenStreetMap',\n", - " zoom_start=16,\n", - " prefer_canvas=False\n", - " )\n", - "\n", - "hbk_marker = folium.Marker(\n", - " location=(52.257770, 10.502490),\n", - " popup=hbk_popup_html,\n", - " tooltip=hbk_tooltip,\n", - " icon=hbk_icon\n", - " )\n", - "\n", - "hbk_marker.add_to(m)\n", - "\n", - "m" - ] - }, - { - "cell_type": "markdown", - "id": "6a7a1f4d-720b-4152-a90b-c9a194494cbe", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a6152b205ccf50ed", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Exercise 2: Design your own Marker\n", - "\n", - "In the following exercise you will design your own marker.\n", - "\n", - "In case of problems, please check the Folium API:\n", - "- [Marker](https://python-visualization.github.io/folium/modules.html#folium.map.Marker)\n", - "- [Popup](https://python-visualization.github.io/folium/modules.html#folium.map.Popup)\n", - "- [Icon](https://python-visualization.github.io/folium/modules.html#folium.map.Icon)\n", - "- [Tooltip](https://python-visualization.github.io/folium/modules.html#folium.map.Tooltip)" - ] - }, - { - "cell_type": "markdown", - "id": "093f0526-114f-45da-947a-550f2163030a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d5aa18ce07303756", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "### 2.1: Defining a Tooltip\n", - "\n", - "Define a tooltip variable named `tooltip` with the text `More about TU Braunschweig`." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "725abb1e-f8c4-4cca-be6f-326f23126062", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-04f53b3f7eb6c201", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "tooltip = \"More about TU Braunschweig\"\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "d0c93b34-79de-4a90-b595-dec419b3a930", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-bfcb53d3e2aba304", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Your Solutions are tested here...\n", - "assert tooltip == \"More about TU Braunschweig\"" - ] - }, - { - "cell_type": "markdown", - "id": "97aa8013-defd-408d-8b80-2389ff92904c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e943331e564dd5c6", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "### 2.2: Defining a Popup\n", - "\n", - "Define a popup object with HTML text named `tu_popup_html` and the [TU BS Logo](https://www.google.com/url?sa=i&url=https%3A%2F%2Fde.m.wikipedia.org%2Fwiki%2FDatei%3ASiegel_TU_Braunschweig_transparent.svg&psig=AOvVaw3PFFLWsIPyXrT81Jo4F6ot&ust=1669222516763000&source=images&cd=vfe&ved=0CA8QjRxqFwoTCIjR-MqgwvsCFQAAAAAdAAAAABAE).\n", - "\n", - "Address: _Universitätspl. 2, 38106 Braunschweig_\n", - "\n", - "Logo URL: https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Siegel_TU_Braunschweig_transparent.svg/1200px-Siegel_TU_Braunschweig_transparent.svg.png\n", - "\n", - "You can also use the Template from the Explanation.\n", - "\n", - "You can find a HTML reference [here](https://www.w3.org/html/wiki/Elements). If you write better in Markdown I recommend the following [converter](https://markdowntohtml.com/) and this [Markdown reference](https://www.markdownguide.org/cheat-sheet/)." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "599b4313-9d53-46d8-be0e-dbf0ab707105", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-1f5f10be1f0c3e95", - "locked": false, - "points": 1, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "tu_popup_html = folium.Popup(\n", - " '''\n", - "

\n", - " \"TU\n", - "

\n", - "

Universitätspl. 2

\n", - "

38106 Braunschweigg

\n", - "

Germany, DE

\n", - "

Visit: tu-bs.de

\n", - " ''',\n", - " show=False\n", - " )\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "541653fa-f882-4f15-90bb-2ad7665d380f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d0ad985cc098c85f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "### 2.3 Defining an Icon\n", - "\n", - "Next, a _red_ icon named `tu_icon` should be defined.\n", - "\n", - "The color for the glyphicon should be a gray hexcode that you can choose freely. To make the color selection easier you can use the [Color Picker](https://htmlcolorcodes.com/color-picker/).\n", - "\n", - "As glyph, _glyphicon-education_, should be used." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "7adb36ce-9012-4a9a-b025-2b7a91b4d2ac", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-3ec775c00a9d80a2", - "locked": false, - "points": 4, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "tu_icon = None\n", - "### BEGIN SOLUTION\n", - "tu_icon = folium.Icon(\n", - " color='red',\n", - " icon_color='#eeeeee',\n", - " prefix='glyphicon',\n", - " icon='glyphicon-education',\n", - " angle=0\n", - " )\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "287924de-5810-4f3c-8b36-e3308798b3ea", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b16e407b56f6a000", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "### 2.4 Defining a Marker\n", - "\n", - "All previously created objects should now be combined into one marker named `tu_bs_marker`.\n", - "\n", - "As the location data use `(52.273460, 10.529231)`." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "c7dd4f94-e7d2-4c11-9426-f911462e122c", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-43ce13ffa68645bc", - "locked": false, - "points": 4, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "tu_bs_marker = None\n", - "### BEGIN SOLUTION\n", - "tu_bs_marker = folium.Marker(\n", - " location=(52.273460, 10.529231),\n", - " popup=tu_popup_html,\n", - " tooltip=tooltip,\n", - " icon=tu_icon\n", - " )\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "13fa1a0f-f06e-4042-bae6-254fc99640e7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-365a8eef0b32decd", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 60, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Your Solutions are tested and displayed here...\n", - "m = folium.Map(\n", - " location=(52.274, 10.53),\n", - " tiles='OpenStreetMap',\n", - " zoom_start=17,\n", - " prefer_canvas=False\n", - " )\n", - "\n", - "tu_bs_marker.add_to(m)\n", - "m" - ] - }, - { - "cell_type": "markdown", - "id": "6639280d-2c23-421b-9170-418895482fb3", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8cf61a16719f867b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "### Circle & Circle Marker\n", - "\n", - "Another possibility to mark places on maps is the [Circle](https://python-visualization.github.io/folium/modules.html#folium.vector_layers.Circle) and the [CircleMarker](https://python-visualization.github.io/folium/modules.html#folium.vector_layers.CircleMarker). The only difference between the two is the parameter _radius_ which is not fixed for the circle and has a default value of 10 for the circle marker which is specified in pixels, the circle marker scales with the map when zooming. Otherwise the objects _popup_ & _tooltip_ can be set with the marker. For the coloring the parameters _color_ & _fill_color_ are to be assigned. _color_ describes the color of the outer ring of the circle, while _fill_color_ specifies the fill color of the circle, whose default value is copied from the parameter_color_. to use _fill_color_ the parameter _fill_ must also be set to _True_.\n", - "\n", - "Here is an example.\n", - "\n", - "The HBK is marked with a red filled circle marker, which has the radius 100 pixel. To highlight the area inside the HBK, black is used as fill color.\n", - "Also here a tooltip, as well as the usual HBK popup is specified." - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "id": "511b9c23-f335-4639-8120-289ee9d4fee2", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-06a4d0cb95f20d93", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 62, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Map Setup\n", - "m = folium.Map(\n", - " location=(52.258, 10.5),\n", - " tiles='OpenStreetMap',\n", - " zoom_start=16,\n", - " prefer_canvas=False\n", - " )\n", - "\n", - "# HBK Braunschweig\n", - "hbk_popup_html = folium.Popup(\n", - " '''\n", - "

\n", - " \"HBK\n", - "

\n", - "

Johannes-Selenka-Platz 1

\n", - "

38118 Braunschweig

\n", - "

Germany, DE

\n", - "

Visit: hbk-bs.de

\n", - " ''',\n", - " show=False\n", - " )\n", - "\n", - "# Defining tooltip\n", - "hbk_tooltip = \"More about the university\"\n", - "\n", - "# Create Circle Marker\n", - "hbk_circle_marker = folium.Circle(\n", - " location=(52.2572, 10.501),\n", - " popup=hbk_popup_html,\n", - " tooltip=hbk_tooltip,\n", - " radius=100,\n", - " fill=True,\n", - " fill_color='black',\n", - " color='red'\n", - " )\n", - "\n", - "# Attach Circle Marker to map\n", - "hbk_circle_marker.add_to(m)\n", - "\n", - "m" - ] - }, - { - "cell_type": "markdown", - "id": "c8bcbdc6-3b3a-4421-b78f-8c62f7f03d34", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-90296cc00bae2968", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "### Rectangle \n", - "\n", - "Rectangles can also be defined in the same way. Instead of a location with a radius, the two corner points must be specified. The data structure used for this is a list of tuples (_[tuple, tuple]_).\n", - "\n", - "Consider the following example:" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "id": "eee0d9ff-1ada-4f62-9675-39064b68fa32", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-641478b6b1df4ae5", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 65, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Map Setup\n", - "m = folium.Map(\n", - " location=(52.258, 10.5),\n", - " tiles='OpenStreetMap',\n", - " zoom_start=16,\n", - " prefer_canvas=False\n", - " )\n", - "\n", - "# HBK Braunschweig\n", - "hbk_popup_html = folium.Popup(\n", - " '''\n", - "

\n", - " \"HBK\n", - "

\n", - "

Johannes-Selenka-Platz 1

\n", - "

38118 Braunschweig

\n", - "

Germany, DE

\n", - "

Visit: hbk-bs.de

\n", - " ''',\n", - " show=False\n", - " )\n", - "\n", - "# Defining tooltip\n", - "hbk_tooltip = \"More about the university\"\n", - "\n", - "# Create Rectangle Marker\n", - "hbk_rectangle_marker = folium.Rectangle(\n", - " bounds=[(52.258077, 10.498424), (52.255896, 10.504092)], # List of tuples defining the Corner Points\n", - " popup=hbk_popup_html,\n", - " tooltip=hbk_tooltip,\n", - " fill=True,\n", - " fill_color='black',\n", - " color='red'\n", - " )\n", - "\n", - "# Attach Rectangle Marker to map\n", - "hbk_rectangle_marker.add_to(m)\n", - "\n", - "m" - ] - }, - { - "cell_type": "markdown", - "id": "09574eea-8007-4740-b3f5-e81a40c28cbd", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5d436ff9290eb683", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Builder Pattern\n", - "\n", - "To simplify working with Folium, certain techniques can be used to simplify the creation of objects. \n", - "\n", - "Design patterns are known from the technical literature that lead to a simpler, error-free and clearer way of developing software. \n", - "One of these design patterns, the creation pattern, will be presented below and used for future tasks.\n", - "\n", - "The technical literature states freely quoted:\n", - "\"The creation pattern serves to decouple the construction of objects from their representation!\" - [_Design Patterns: Elements of Reusable Object-Oriented Software\n", - "by Erich Gamma, Ralph Johnson, Richard Helm, Ralph E. Johnson, John Vlissides_](https://books.google.de/books?hl=de&lr=&id=tmNNfSkfTlcC&oi=fnd&pg=PR11&dq=software+design+patterns&ots=e_iImZT2d3&sig=DtkhOov5t0Ot6lf7QubDGNhWzz0#v=onepage&q=software%20design%20patterns&f=false)\n", - "\n", - "A builder is a function (function of an object) that is used to create new objects. In our case, these will be markers and popups." - ] - }, - { - "cell_type": "markdown", - "id": "5f27eaae-3e5b-4f6c-854a-2c37c9fbffac", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-6473594d5d9882b0", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "### A simple Popup Factory\n", - "\n", - "Anyone who remembers the HTML popups in the previous chapter will quickly realise that with a larger data set, setting individual HTML tags for images, addresses or other information soon becomes a tedious task.\n", - "\n", - "Assuming we want to plot all the universities in Lower Saxony on a map, a separate popup would have to be created for each marker. To change this, the following function will be introduced:" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "id": "ec9a37e4-1dd3-4673-b36f-122adafadeb2", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-069cd8284c5bc36c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "def popup_factory(adr: str, zipc: str, country: str, pic: str):\n", - " html = '''\n", - "

\n", - "

{}

\n", - "

{}

\n", - "

{}

\n", - " '''.format(pic, adr, zipc, country)\n", - " return folium.Popup(html)" - ] - }, - { - "cell_type": "markdown", - "id": "1740ce5e-f7a8-47f9-8211-7a62b19cf08b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-de4c7e1824c4e5a6", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "The _popup_factory_ function just defined takes the four string parameters _adr_ (address), _zipc_ (postcode), _country_ & _pic_ (picture URL) and generates an HTML-compliant string with the given information from the string specified in the _html_ variable. The return value of the function is a Folium popup object.\n", - "\n", - "To get closer to the goal of plotting all universities in Lower Saxony, a few objects are still missing.\n", - "\n", - "The _hbk_icon_ I created above is to be used as the standard icon. It is defined as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "id": "9dddf885-ffa7-4e3b-b948-43ded7f3bd7b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a700169d2ec58d8c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "def icon_factory(is_public=True):\n", - " icon = folium.Icon(\n", - " color='black' if is_public else 'white',\n", - " icon_color = 'white' if is_public else 'black',\n", - " icon='glyphicon-home'\n", - " )\n", - " return icon" - ] - }, - { - "cell_type": "markdown", - "id": "d4f4be32-8d71-41b0-9d8e-5ec2e32416a8", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3fd735bc0f0cba70", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "The only thing missing in the next step is the factory for creating markers.\n", - "\n", - "This is defined as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "id": "07a0df3e-92f9-4e25-89f3-3e27048d2c6b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-393cf1e2b37be7a6", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "def marker_factory(loc, popup, is_public=True):\n", - " std_tooltip = 'Click for more information'\n", - " std_icon = icon_factory(is_public)\n", - " return folium.Marker(loc, popup=popup, icon=std_icon, tooltip=std_tooltip)" - ] - }, - { - "cell_type": "markdown", - "id": "1e7f7f3a-d234-427d-ad06-3026c00312a4", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2b6d551c3e806181", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "With these two functions it is now easy to replicate the map created in the previous chapter:" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "id": "6a60ccee-4728-4bf1-93db-1158deae037f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-7166c54f214ed13e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 72, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Create Map\n", - "m = folium.Map(\n", - " location=(52.258, 10.5),\n", - " tiles='OpenStreetMap',\n", - " zoom_start=16,\n", - " prefer_canvas=False\n", - " )\n", - "\n", - "# Define popup\n", - "pp = popup_factory(\n", - " adr='Johannes-Selenka-Platz 1',\n", - " zipc='38118 Braunschweig',\n", - " country='Germany, DE',\n", - " pic=\"https://www.hbk-bs.de/fileadmin/_processed_/5/1/csm_HBK_Logo_9f3f898a2b.png\",\n", - " )\n", - "\n", - "# Define Marker\n", - "marker = marker_factory(\n", - " loc=(52.257770, 10.502490),\n", - " popup=pp\n", - " )\n", - "\n", - "# Attach Marker to Map\n", - "marker.add_to(m)\n", - "\n", - "# Display Map\n", - "m" - ] - }, - { - "cell_type": "markdown", - "id": "1110a947-36cb-43c8-9348-fe3bafabe185", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a1045f8d87d79df5", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Exercise 3: Mapping the Universties in Lower Saxony\n", - "\n", - "## 3.1: Reading the Dataset\n", - "The data set for this notebook is *unis_nd.csv*.\n", - "\n", - "Read this into the variable `df` using the _pandas_ `read_csv` function.\n", - "\n", - "(I recommend that you take a look at the data set)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b50d076d-4b5f-4137-93df-846144b119b7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c55c41f6b9c03dd6", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "import pandas as pd" - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "id": "16c81c07-5893-42a7-9b1d-a081deea998c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d58de9c13e900a3b", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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University nameType of universitySponsorshipRight of promotionFounding yearNumber of studentsAddresslatlonplzpic
0Hochschule für Bildende Künste BraunschweigArtistic universitypublicyes1963976.000Johannes-Selenka-Platz 152.25773810.50231538118 Braunschweighttps://www.hbk-bs.de/fileadmin/_processed_/5/...
1Technische Universität Carolo-Wilhelmina zu Br...Universitypublicyes174517709.000Universitätspl. 252.27355010.53009738106 Braunschweighttps://upload.wikimedia.org/wikipedia/commons...
2Hochschule 21University of Applied Sciencesprivatno20051084.000Harburger Str. 653.4776509.70465021614 Buxtehudehttps://upload.wikimedia.org/wikipedia/commons...
3Technische Universität ClausthalUniversitypublicyes17753446.000Adolph-Roemer-Straße 2A51.80484010.33411038678 Clausthal-Zellerfeldhttps://www.presse.tu-clausthal.de/fileadmin/T...
4Hochschule Emden/LeerUniversity of Applied Sciencespublicno20094481.000Constantiapl. 453.3681607.18141026723 Emdenhttps://sta-hisweb.hs-emden-leer.de/QIS/images...
5PFH – Private Hochschule GöttingenUniversity of Applied Sciencesprivatno19954226.000Weender Landstraße 3-751.5389109.93322037073 Göttingenhttps://goettingen-campus.de/fileadmin/_proces...
6Georg-August-Universität GöttingenUniversitypublicyes173728614.000Wilhelmsplatz 151.5340709.93785037073 Göttingenhttps://upload.wikimedia.org/wikipedia/commons...
7Fachhochschule für die Wirtschaft HannoverUniversity of Applied Sciencesprivatno1996641.000Freundallee 1552.3662009.77247030173 Hannoverhttps://upload.wikimedia.org/wikipedia/commons...
8Hochschule HannoverUniversity of Applied Sciencespublicno19719209.000Ricklinger Stadtweg 12052.3541909.72238030459 Hannoverhttps://upload.wikimedia.org/wikipedia/commons...
9Hochschule für Musik, Theater und Medien HannoverArtistic universitypublicyes18971409.000Neues Haus 152.3773809.75392030175 Hannoverhttps://upload.wikimedia.org/wikipedia/commons...
10Leibniz-FachhochschuleUniversity of Applied Sciencesprivatno1920589.000Expo Plaza 1152.3211509.81868030539 Hannoverhttps://www.visit-hannover.com/var/storage/ima...
11Medizinische Hochschule Hannover (MHH)Universitypublicyes19633778.000Carl-Neuberg-Straße 152.3840509.80603030625 Hannoverhttps://upload.wikimedia.org/wikipedia/commons...
12Stiftung Tierärztliche Hochschule HannoverUniversitypublicyes17782381.000Bünteweg 252.3546809.79773030559 Hannoverhttps://upload.wikimedia.org/wikipedia/de/thum...
13Gottfried Wilhelm Leibniz Universität HannoverUniversitypublicyes183128935.000Welfengarten 152.3822509.71777030167 Hannoverhttps://www.uni-hannover.de/fileadmin/_process...
14Fachhochschule für Interkulturelle Theologie H...University of Applied Sciencesprivatno201291.000Missionsstraße 3-552.70884310.14071029320 Südheidehttps://cdn.max-e5.info/damfiles/logo/fh_herma...
15Universität HildesheimUniversitypublicyes19788378.000Universitätspl. 152.1340109.97469031141 Hildesheimhttps://www.uni-hildesheim.de/media/_processed...
16HAWK Hochschule für angewandte Wissenschaft un...University of Applied Sciencespublicno19716495.000Hohnsen 452.1424609.95798031134 Hildesheimhttps://upload.wikimedia.org/wikipedia/commons...
17HAWK Hochschule für angewandte Wissenschaft un...University of Applied Sciencespublicno19716495.000Haarmannpl. 351.8272609.45069037603 Holzmindenhttps://upload.wikimedia.org/wikipedia/commons...
18HAWK Hochschule für angewandte Wissenschaft un...University of Applied Sciencespublicno19716495.000Von-Ossietzky-Straße 9951.5217509.96967037085 Göttingenhttps://upload.wikimedia.org/wikipedia/commons...
19Leuphana Universität LüneburgUniversitypublicyes19466497.000Universitätsallee 153.22853110.40171021335 Lüneburghttps://upload.wikimedia.org/wikipedia/commons...
20Norddeutsche Hochschule für Rechtspflege – Nie...University of Administrationpublicno20076409.000Godehardspl. 652.1448409.94923031134 Hildesheimhttps://static.studycheck.de/media/images/inst...
21Kommunale Hochschule für Verwaltung in Nieders...University of Administrationpublicno20071570.000Wielandstraße 852.3705009.72239030169 Hannoverhttps://www.nsi-hsvn.de/fileadmin/user_upload/...
22Carl von Ossietzky Universität Oldenburg\\nUniversitypublicyes197315635.000Uhlhornsweg 49-5553.1473408.17902026129 Oldenburghttps://upload.wikimedia.org/wikipedia/commons...
23Hochschule OsnabrückUniversity of Applied Sciencespublicno197113620.000Albrechtstraße 3052.2826808.02501049076 Osnabrückhttps://login.hs-osnabrueck.de/nidp/hsos/image...
24Universität OsnabrückUniversitypublicyes197313640.000Neuer Graben 2952.2713708.04454049074 Osnabrückhttps://www.eh-tabor.de/sites/default/files/st...
25Hochschule Braunschweig/Wolfenbüttel, Ostfalia...University of Applied Sciencespublicno197111577.000Salzdahlumer Str. 46/4852.17683010.54865038302 Wolfenbüttelhttps://www.ostfalia.de/export/system/modules/...
26Hochschule Wolfsburg, Ostfalia Hochschule für ...University of Applied Sciencespublicno197111577.000Robert-Koch-Platz 8A52.42595010.78711038440 Wolfsburghttps://www.ostfalia.de/export/system/modules/...
27Hochschule Suderburg, Ostfalia Hochschule für ...University of Applied Sciencespublicno197111577.000Herbert-Meyer-Straße 752.89761010.44659029556 Suderburghttps://www.ostfalia.de/export/system/modules/...
28Hochschule Salzgitter, Ostfalia Hochschule für...University of Applied Sciencespublicno197111577.000Karl-Scharfenberg-Straße 55/5752.08724010.38055038229 Salzgitterhttps://www.ostfalia.de/export/system/modules/...
29Hochschule für Künste im Sozialen, OttersbergUniversity of Applied Sciencesprivatno1967342.000Große Str. 10753.1066809.16310028870 Ottersberghttps://upload.wikimedia.org/wikipedia/commons...
30Private Hochschule für Wirtschaft und Technik ...University of Applied Sciencesprivatno1998558.000Rombergstraße 4052.7212508.27891049377 Vechtahttps://www.phwt.de/wp-content/uploads/2020/09...
31Private Hochschule für Wirtschaft und Technik ...University of Applied Sciencesprivatno1998558.000Schlesier Str. 13A52.6117108.36334049356 Diepholzhttps://www.phwt.de/wp-content/uploads/2020/09...
32Universität VechtaUniversitypublicyes19954.551Driverstraße 2252.7211708.29380049377 Vechtahttps://upload.wikimedia.org/wikipedia/commons...
33Hochschule WeserberglandUniversity of Applied Sciencesprivatno2010485.000Am Stockhof 252.0987509.35542031785 Hamelnhttps://upload.wikimedia.org/wikipedia/commons...
34Jade Hochschule – WilhelmshavenUniversity of Applied Sciencespublicno20096789.000Friedrich-Paffrath-Straße 10153.5478708.08804026389 Wilhelmshavenhttps://www.jade-hs.de/fileadmin/layout2016/as...
35Jade Hochschule – OldenburgUniversity of Applied Sciencespublicno20096789.000Ofener Str. 16/1953.1417908.20213026121 Oldenburghttps://www.jade-hs.de/fileadmin/layout2016/as...
36Jade Hochschule – ElsflethUniversity of Applied Sciencespublicno20096789.000Weserstraße 5253.2424408.46651026931 Elsflethhttps://www.jade-hs.de/fileadmin/layout2016/as...
37Steuerakademie Niedersachsen RintelnUniversity of Administrationpublicno2006500.000Wilhelm-Busch-Weg 2952.2069609.09112031737 Rintelnhttps://www.steuerakademie.niedersachsen.de/as...
38Steuerakademie Niedersachsen Bad EilsenUniversity of Administrationpublicno2006500.000Bahnhofstraße 552.2398109.10423031707 Bad Eilsenhttps://www.steuerakademie.niedersachsen.de/as...
\n", - "
" - ], - "text/plain": [ - " University name \\\n", - "0 Hochschule für Bildende Künste Braunschweig \n", - "1 Technische Universität Carolo-Wilhelmina zu Br... \n", - "2 Hochschule 21 \n", - "3 Technische Universität Clausthal \n", - "4 Hochschule Emden/Leer \n", - "5 PFH – Private Hochschule Göttingen \n", - "6 Georg-August-Universität Göttingen \n", - "7 Fachhochschule für die Wirtschaft Hannover \n", - "8 Hochschule Hannover \n", - "9 Hochschule für Musik, Theater und Medien Hannover \n", - "10 Leibniz-Fachhochschule \n", - "11 Medizinische Hochschule Hannover (MHH) \n", - "12 Stiftung Tierärztliche Hochschule Hannover \n", - "13 Gottfried Wilhelm Leibniz Universität Hannover \n", - "14 Fachhochschule für Interkulturelle Theologie H... \n", - "15 Universität Hildesheim \n", - "16 HAWK Hochschule für angewandte Wissenschaft un... \n", - "17 HAWK Hochschule für angewandte Wissenschaft un... \n", - "18 HAWK Hochschule für angewandte Wissenschaft un... \n", - "19 Leuphana Universität Lüneburg \n", - "20 Norddeutsche Hochschule für Rechtspflege – Nie... \n", - "21 Kommunale Hochschule für Verwaltung in Nieders... \n", - "22 Carl von Ossietzky Universität Oldenburg\\n \n", - "23 Hochschule Osnabrück \n", - "24 Universität Osnabrück \n", - "25 Hochschule Braunschweig/Wolfenbüttel, Ostfalia... \n", - "26 Hochschule Wolfsburg, Ostfalia Hochschule für ... \n", - "27 Hochschule Suderburg, Ostfalia Hochschule für ... \n", - "28 Hochschule Salzgitter, Ostfalia Hochschule für... \n", - "29 Hochschule für Künste im Sozialen, Ottersberg \n", - "30 Private Hochschule für Wirtschaft und Technik ... \n", - "31 Private Hochschule für Wirtschaft und Technik ... \n", - "32 Universität Vechta \n", - "33 Hochschule Weserbergland \n", - "34 Jade Hochschule – Wilhelmshaven \n", - "35 Jade Hochschule – Oldenburg \n", - "36 Jade Hochschule – Elsfleth \n", - "37 Steuerakademie Niedersachsen Rinteln \n", - "38 Steuerakademie Niedersachsen Bad Eilsen \n", - "\n", - " Type of university Sponsorship Right of promotion \\\n", - "0 Artistic university public yes \n", - "1 University public yes \n", - "2 University of Applied Sciences privat no \n", - "3 University public yes \n", - "4 University of Applied Sciences public no \n", - "5 University of Applied Sciences privat no \n", - "6 University public yes \n", - "7 University of Applied Sciences privat no \n", - "8 University of Applied Sciences public no \n", - "9 Artistic university public yes \n", - "10 University of Applied Sciences privat no \n", - "11 University public yes \n", - "12 University public yes \n", - "13 University public yes \n", - "14 University of Applied Sciences privat no \n", - "15 University public yes \n", - "16 University of Applied Sciences public no \n", - "17 University of Applied Sciences public no \n", - "18 University of Applied Sciences public no \n", - "19 University public yes \n", - "20 University of Administration public no \n", - "21 University of Administration public no \n", - "22 University public yes \n", - "23 University of Applied Sciences public no \n", - "24 University public yes \n", - "25 University of Applied Sciences public no \n", - "26 University of Applied Sciences public no \n", - "27 University of Applied Sciences public no \n", - "28 University of Applied Sciences public no \n", - "29 University of Applied Sciences privat no \n", - "30 University of Applied Sciences privat no \n", - "31 University of Applied Sciences privat no \n", - "32 University public yes \n", - "33 University of Applied Sciences privat no \n", - "34 University of Applied Sciences public no \n", - "35 University of Applied Sciences public no \n", - "36 University of Applied Sciences public no \n", - "37 University of Administration public no \n", - "38 University of Administration public no \n", - "\n", - " Founding year Number of students Address \\\n", - "0 1963 976.000 Johannes-Selenka-Platz 1 \n", - "1 1745 17709.000 Universitätspl. 2 \n", - "2 2005 1084.000 Harburger Str. 6 \n", - "3 1775 3446.000 Adolph-Roemer-Straße 2A \n", - "4 2009 4481.000 Constantiapl. 4 \n", - "5 1995 4226.000 Weender Landstraße 3-7 \n", - "6 1737 28614.000 Wilhelmsplatz 1 \n", - "7 1996 641.000 Freundallee 15 \n", - "8 1971 9209.000 Ricklinger Stadtweg 120 \n", - "9 1897 1409.000 Neues Haus 1 \n", - "10 1920 589.000 Expo Plaza 11 \n", - "11 1963 3778.000 Carl-Neuberg-Straße 1 \n", - "12 1778 2381.000 Bünteweg 2 \n", - "13 1831 28935.000 Welfengarten 1 \n", - "14 2012 91.000 Missionsstraße 3-5 \n", - "15 1978 8378.000 Universitätspl. 1 \n", - "16 1971 6495.000 Hohnsen 4 \n", - "17 1971 6495.000 Haarmannpl. 3 \n", - "18 1971 6495.000 Von-Ossietzky-Straße 99 \n", - "19 1946 6497.000 Universitätsallee 1 \n", - "20 2007 6409.000 Godehardspl. 6 \n", - "21 2007 1570.000 Wielandstraße 8 \n", - "22 1973 15635.000 Uhlhornsweg 49-55 \n", - "23 1971 13620.000 Albrechtstraße 30 \n", - "24 1973 13640.000 Neuer Graben 29 \n", - "25 1971 11577.000 Salzdahlumer Str. 46/48 \n", - "26 1971 11577.000 Robert-Koch-Platz 8A \n", - "27 1971 11577.000 Herbert-Meyer-Straße 7 \n", - "28 1971 11577.000 Karl-Scharfenberg-Straße 55/57 \n", - "29 1967 342.000 Große Str. 107 \n", - "30 1998 558.000 Rombergstraße 40 \n", - "31 1998 558.000 Schlesier Str. 13A \n", - "32 1995 4.551 Driverstraße 22 \n", - "33 2010 485.000 Am Stockhof 2 \n", - "34 2009 6789.000 Friedrich-Paffrath-Straße 101 \n", - "35 2009 6789.000 Ofener Str. 16/19 \n", - "36 2009 6789.000 Weserstraße 52 \n", - "37 2006 500.000 Wilhelm-Busch-Weg 29 \n", - "38 2006 500.000 Bahnhofstraße 5 \n", - "\n", - " lat lon plz \\\n", - "0 52.257738 10.502315 38118 Braunschweig \n", - "1 52.273550 10.530097 38106 Braunschweig \n", - "2 53.477650 9.704650 21614 Buxtehude \n", - "3 51.804840 10.334110 38678 Clausthal-Zellerfeld \n", - "4 53.368160 7.181410 26723 Emden \n", - "5 51.538910 9.933220 37073 Göttingen \n", - "6 51.534070 9.937850 37073 Göttingen \n", - "7 52.366200 9.772470 30173 Hannover \n", - "8 52.354190 9.722380 30459 Hannover \n", - "9 52.377380 9.753920 30175 Hannover \n", - "10 52.321150 9.818680 30539 Hannover \n", - "11 52.384050 9.806030 30625 Hannover \n", - "12 52.354680 9.797730 30559 Hannover \n", - "13 52.382250 9.717770 30167 Hannover \n", - "14 52.708843 10.140710 29320 Südheide \n", - "15 52.134010 9.974690 31141 Hildesheim \n", - "16 52.142460 9.957980 31134 Hildesheim \n", - "17 51.827260 9.450690 37603 Holzminden \n", - "18 51.521750 9.969670 37085 Göttingen \n", - "19 53.228531 10.401710 21335 Lüneburg \n", - "20 52.144840 9.949230 31134 Hildesheim \n", - "21 52.370500 9.722390 30169 Hannover \n", - "22 53.147340 8.179020 26129 Oldenburg \n", - "23 52.282680 8.025010 49076 Osnabrück \n", - "24 52.271370 8.044540 49074 Osnabrück \n", - "25 52.176830 10.548650 38302 Wolfenbüttel \n", - "26 52.425950 10.787110 38440 Wolfsburg \n", - "27 52.897610 10.446590 29556 Suderburg \n", - "28 52.087240 10.380550 38229 Salzgitter \n", - "29 53.106680 9.163100 28870 Ottersberg \n", - "30 52.721250 8.278910 49377 Vechta \n", - "31 52.611710 8.363340 49356 Diepholz \n", - "32 52.721170 8.293800 49377 Vechta \n", - "33 52.098750 9.355420 31785 Hameln \n", - "34 53.547870 8.088040 26389 Wilhelmshaven \n", - "35 53.141790 8.202130 26121 Oldenburg \n", - "36 53.242440 8.466510 26931 Elsfleth \n", - "37 52.206960 9.091120 31737 Rinteln \n", - "38 52.239810 9.104230 31707 Bad Eilsen \n", - "\n", - " pic \n", - "0 https://www.hbk-bs.de/fileadmin/_processed_/5/... \n", - "1 https://upload.wikimedia.org/wikipedia/commons... \n", - "2 https://upload.wikimedia.org/wikipedia/commons... \n", - "3 https://www.presse.tu-clausthal.de/fileadmin/T... \n", - "4 https://sta-hisweb.hs-emden-leer.de/QIS/images... \n", - "5 https://goettingen-campus.de/fileadmin/_proces... \n", - "6 https://upload.wikimedia.org/wikipedia/commons... \n", - "7 https://upload.wikimedia.org/wikipedia/commons... \n", - "8 https://upload.wikimedia.org/wikipedia/commons... \n", - "9 https://upload.wikimedia.org/wikipedia/commons... \n", - "10 https://www.visit-hannover.com/var/storage/ima... \n", - "11 https://upload.wikimedia.org/wikipedia/commons... \n", - "12 https://upload.wikimedia.org/wikipedia/de/thum... \n", - "13 https://www.uni-hannover.de/fileadmin/_process... \n", - "14 https://cdn.max-e5.info/damfiles/logo/fh_herma... \n", - "15 https://www.uni-hildesheim.de/media/_processed... \n", - "16 https://upload.wikimedia.org/wikipedia/commons... \n", - "17 https://upload.wikimedia.org/wikipedia/commons... \n", - "18 https://upload.wikimedia.org/wikipedia/commons... \n", - "19 https://upload.wikimedia.org/wikipedia/commons... \n", - "20 https://static.studycheck.de/media/images/inst... \n", - "21 https://www.nsi-hsvn.de/fileadmin/user_upload/... \n", - "22 https://upload.wikimedia.org/wikipedia/commons... \n", - "23 https://login.hs-osnabrueck.de/nidp/hsos/image... \n", - "24 https://www.eh-tabor.de/sites/default/files/st... \n", - "25 https://www.ostfalia.de/export/system/modules/... \n", - "26 https://www.ostfalia.de/export/system/modules/... \n", - "27 https://www.ostfalia.de/export/system/modules/... \n", - "28 https://www.ostfalia.de/export/system/modules/... \n", - "29 https://upload.wikimedia.org/wikipedia/commons... \n", - "30 https://www.phwt.de/wp-content/uploads/2020/09... \n", - "31 https://www.phwt.de/wp-content/uploads/2020/09... \n", - "32 https://upload.wikimedia.org/wikipedia/commons... \n", - "33 https://upload.wikimedia.org/wikipedia/commons... \n", - "34 https://www.jade-hs.de/fileadmin/layout2016/as... \n", - "35 https://www.jade-hs.de/fileadmin/layout2016/as... \n", - "36 https://www.jade-hs.de/fileadmin/layout2016/as... \n", - "37 https://www.steuerakademie.niedersachsen.de/as... \n", - "38 https://www.steuerakademie.niedersachsen.de/as... " - ] - }, - "execution_count": 87, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "df = pd.read_csv('unis_nd.csv')\n", - "df\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 93, - "id": "a30598a7-c7d4-42cc-a9b8-dc6356d060aa", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-3e80e16a38e85d29", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Your Solutions are tested here..\n", - "assert isinstance(df, pd.DataFrame)" - ] - }, - { - "cell_type": "markdown", - "id": "da44f50f-0c2d-404d-8083-289742c5497a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-237bfc25448676b2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## 3.2: Defining the Map\n", - "\n", - "Before we plot the dataset, define a map with the name `lower_saxony`. \n", - "\n", - "- The location should be the georaphic centre of Lower Saxony in _Wehrenberg 27318 Hoyerhagen_ `(52.806390, 9.135110)`.\n", - "- Use a suitable tileset from the documentation\n", - "- Use a suitable zoom setting" - ] - }, - { - "cell_type": "code", - "execution_count": 88, - "id": "bfe04668-a597-4f93-b6e4-11ef17d18dcd", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0d7c995b3fcc368e", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "lower_saxony = folium.Map(\n", - " location=(52.806390, 9.135110), # Georaphical centre Point of Lower Saxony Wehrenberg 27318 Hoyerhagen\n", - " tiles='OpenStreetMap',\n", - " zoom_start=7\n", - " )\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "id": "a2f05ce6-7942-4c71-b1e2-a709c88b0f36", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-77f8257bb3c1308f", - "locked": true, - "points": 4, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Your Solutions are tested here..\n", - "assert isinstance(lower_saxony, folium.Map)\n", - "assert len(lower_saxony.location) == 2" - ] - }, - { - "cell_type": "markdown", - "id": "357c71bb-923a-4de6-bcbd-b9d2741498fc", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d66a439bbfb3778a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## 3.3 Plotting the Dataset\n", - "\n", - "Write a for loop which reads the values from the dataset `df` and add the markers to the map `lower_saxony` using the already defined functions `popup_factory` and `marker_factory`. " - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "id": "b392f48f-f0ae-4158-806f-859e71009c04", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-b744358aaaa7db44", - "locked": false, - "points": 5, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 94, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "for index, row in df.iterrows():\n", - " pp = popup_factory(\n", - " adr=row['Address'],\n", - " zipc=row['plz'],\n", - " country='Germany, DE',\n", - " pic=row['pic'],\n", - " )\n", - " location = (float(row['lat']), float(row['lon']))\n", - " \n", - " is_public = False\n", - " if row['Sponsorship'] == 'public':\n", - " is_public = True\n", - " \n", - " marker = marker_factory(location, pp, is_public) \n", - " marker.add_to(lower_saxony)\n", - " \n", - "lower_saxony\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 95, - "id": "ab37a764-3718-4327-976c-146e5531a048", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-49864685eac331d1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 95, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Your Solutions are tested and displayed here..\n", - "lower_saxony" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.0" - }, - "toc-autonumbering": false - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/Folium & Pandas/description/description-geomapper.tex b/Material/wise_24_25/lernmaterial/Folium & Pandas/description/description-geomapper.tex deleted file mode 100644 index 87ec9ac..0000000 --- a/Material/wise_24_25/lernmaterial/Folium & Pandas/description/description-geomapper.tex +++ /dev/null @@ -1,19 +0,0 @@ -\section{Project Proposal - Geomapping} - -\begin{figure}[h] -\includegraphics[width=0.9\textwidth]{fig/geomapping.png} -\centering -\end{figure} - -Geomapping involves using geographic data to create maps that illustrate how features or phenomena are related spatially. There are a number of reasons why this skill is important. One advantage of geomapping is that it can help people better understand and analyze spatial patterns. For example, geomapping can be used to show how the distribution of certain resources, such as water or vegetation, varies across a region. This can help people make more informed decisions about how to manage those resources. - -As part of the exercise, students will learn how to create simple maps by working with data sets. For example, if you want to show how the distribution of universities in Lower Saxony looks like, this can be shown with conventional methods of data analysis, but it hides certain data that only become visible through the spatial representation. In the exercise, the universities of Lower Saxony are plotted and the students are instructed to write a short text about how they interpret data or what they see. Thereby it becomes obvious that most of the universities are located in Hannover or that there are preferred locations for universities that are concentrated in the eastern part of Lower Saxony. All in all, the ability of geomapping should help to look at data(-sets) differently. \\ - -\textbf{What will You Learn from This Python Project?} -\begin{itemize} - \item Create maps in Python - \item Visualization of coordinates with different kinds of marker (dot, circle, rectangle) - \item Customization of markers (color, symbol) - \item Add popup information to markers - -\end{itemize} diff --git a/Material/wise_24_25/lernmaterial/Folium & Pandas/description/description.pdf b/Material/wise_24_25/lernmaterial/Folium & Pandas/description/description.pdf deleted file mode 100644 index 274e9b02286831b44c6efcb51698a9a26611168f..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 962797 zcmd42WmsI@)+I`?;3NS;fB+SoAcecTySux)6CgmaAi*7iyBDs(-QC^Yt#{6Q&evae z-~M~=<=H${dso$}+H>#i(@G3nkJtGJ#17ZMymHxh& znT{UB!-HgOWAt}K(EqD{NG$*DMwHy`j6q;E1!EK7HjHgdoy-GB?sASRZ7&P{BA*XTeBAh3e1trLj#pXZ8zK|##G*8{`3{9`7D|J^iT zaUqZf>BucXEII?)x 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\n", - " Willkommen zur fünften Programmierübung Einführung in Python 3.\n", - "
\n", - " \n", - "\n", - "\n", - "Wenn Sie Fragen oder Verbesserungsvorschläge zum Inhalt oder Struktur der Notebooks haben, dann können sie eine E-Mail an Phil Keier ([p.keier@hbk-bs.de](mailto:p.keier@hbk-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) oder Martin Le ([martin.le@tu-bs.de](mailto:martin.le@tu-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) schreiben.\n", - "\n", - "Link zu einem Python Spickzettel: [hier](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf)\n", - "\n", - "Der Großteil des Python-Tutorials stammt aus der Veranstaltung _Deep Learning Lab_ und von [www.python-kurs.eu](https://www.python-kurs.eu/python3_kurs.php) und wurde für _Signale und Systeme_, sowie _Einführung in die Programmierung für Nicht Informatiker_ angepasst.\n", - "\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "8af16cfd-827f-4e7d-91a3-970e920ad212", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-fa7bc65ef436bf2f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Was ist Pandas\n", - "\n", - ">_pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real-world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis/manipulation tool available in any language. It is already well on its way toward this goal._\n", - "\n", - "Pandas Keyfeature sind die beiden Datenstruckturen [Series](https://pandas.pydata.org/docs/reference/series.html) und [DataFrame](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame).\n", - "\n", - "Diesem Notebook liegt zu Lernzwecken das Datenset `unis_nd.csv` bei, mit dem die Grundlegenden Funktionen Pandas gezeigt werden.\n", - "\n", - "__Für dieses Notebook schauen Sie bitte in die [Pandas Docs](https://pandas.pydata.org/docs/)!!!__ Dort sind alle Funktionen beschrieben die wir hier bearbeiten und noch mehr!\n", - "\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "8c6fa552-7e9c-4561-b7c3-e72268db9afb", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-430939b1ccd3736f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Import\n", - "\n", - "Pandas wird vom Internet mit der Abkürzung `pd` importiert.\n", - "\n", - "Führen Sie die nächste Zelle beim neustart des Notebooks bitte immer aus." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "64315664-4ab4-46db-9600-b0dd58f95174", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-44f74bf2f8803769", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "import pandas as pd" - ] - }, - { - "cell_type": "markdown", - "id": "2ea5a1da-05f7-41a1-96cc-aaba1c74cf0d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-53884904925c1212", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Data Frame\n", - "\n", - "Ein Pandas Data Frame `pd.DataFrame` ist eine 2-Dimensionale Datenstrucktur, vergleichbar mit einer Excel Tabelle.\n", - "\n", - "![](https://pandas.pydata.org/docs/_images/01_table_dataframe.svg)\n", - "\n", - "Um aus einem Dictionary einen Pandas DataFrame zu erstellen wird das Objekt `pd.DataFrame` verwendet. Dabei ist es wichtig das das Dicitionary einer Ordnung folgt, bei dem die Schlüssel die Namen der Spalten sind. Die Reihe im Data Frame wird dann einem Schlüssel als Liste mit Werten zugeordnet.\n", - "\n", - "Schauen Sie sich dazu Folgendes Dictionary an, welches ein Subset aus dem beiliegenden Datenset `unis_nd.csv`:" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "30d2f79a-3f54-4397-a1f3-626b58fdf67e", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e30f1b0549eb4481", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "unis_data = {\n", - " \t\"University name\": [ \n", - " \"Hochschule für Bildende Künste Braunschweig\",\n", - " \"Technische Universität Carolo-Wilhelmina zu Braunschweig\",\n", - " \"Hochschule 21\",\n", - " \"Technische Universität Clausthal\",\n", - " \"Hochschule Emden/Leer\",\n", - " \"PFH – Private Hochschule Göttingen\",\n", - " \"Georg-August-Universität Göttingen\"\n", - " ],\n", - " \n", - " \"Type of university\": [\n", - " \"Artistic university\",\n", - " \"University\",\n", - " \"University of Applied Sciences\",\n", - " \"University\",\n", - " \"University of Applied Sciences\",\n", - " \"University of Applied Sciences\",\n", - " \"University\"\n", - " ]\n", - "}" - ] - }, - { - "cell_type": "markdown", - "id": "ba23542f-9030-45a3-a7bc-9c3841ae843e", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-08a43ccd460568f5", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Um aus dem Dictionary ein DataFrame zu erstellen, wird es einfach als Input für `pd.DataFrame` verwendet.\n", - "\n", - "Anschließend lassen wir es ausgeben. Nehmen Sie sich gerne die Zeit uns inspizieren Sie die Strucktur des beispielhaften DataFrames:" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "074d682c-e936-40c3-97e1-2208b4e86a79", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b519f770ad46c82b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " University name \\\n", - "0 Hochschule für Bildende Künste Braunschweig \n", - "1 Technische Universität Carolo-Wilhelmina zu Br... \n", - "2 Hochschule 21 \n", - "3 Technische Universität Clausthal \n", - "4 Hochschule Emden/Leer \n", - "5 PFH – Private Hochschule Göttingen \n", - "6 Georg-August-Universität Göttingen \n", - "\n", - " Type of university \n", - "0 Artistic university \n", - "1 University \n", - "2 University of Applied Sciences \n", - "3 University \n", - "4 University of Applied Sciences \n", - "5 University of Applied Sciences \n", - "6 University " - ] - }, - "execution_count": 48, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "unis = pd.DataFrame(unis_data)\n", - "unis" - ] - }, - { - "cell_type": "markdown", - "id": "e732d3ff-463e-4411-b023-47f2fe02e4c5", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-6ed4bfb85a3f95bb", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Zugriffs Operationen\n", - "\n", - "Wie bereits vom Dicitonary bekannt lässt sich mittels Schlüssel (im Beispiel `University name`) auf eine Spalte zugreifen. Dabei ist wichtig zu erwähnen das jede Spalte in einem `DataFrame` eine `Series` ist. Eine `Series` ist dabei das 1-Dimensionale äquivalent zum 2-Dimensionales `DataFrame`.\n", - "\n", - "Im Folgenden Beispiel Selektieren wir die Series `University name` aus dem DataFrame `unis_nd`:" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "cfa48421-7e56-4c10-a4fc-3d907f429309", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ef292cd51db1030b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "0 Hochschule für Bildende Künste Braunschweig\n", - "1 Technische Universität Carolo-Wilhelmina zu Br...\n", - "2 Hochschule 21\n", - "3 Technische Universität Clausthal\n", - "4 Hochschule Emden/Leer\n", - "5 PFH – Private Hochschule Göttingen\n", - "6 Georg-August-Universität Göttingen\n", - "Name: University name, dtype: object" - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "unis[\"University name\"]" - ] - }, - { - "cell_type": "markdown", - "id": "62a92dad-506a-434f-b343-c020f89b19a1", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-dfdff5bf7e9be2ad", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Um eine `Series` manuel zu definieren wird `pd.Series` verwendet. Dabei kann mittels Parameter `name` ein label für die Series gesetzt werden:" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "7d54c159-119d-4350-9cf9-081ecc8f5712", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2a1d8c078f0249d8", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "0 Hochschule für Bildende Künste Braunschweig\n", - "1 Technische Universität Carolo-Wilhelmina zu Br...\n", - "2 Hochschule 21\n", - "3 Technische Universität Clausthal\n", - "4 Hochschule Emden/Leer\n", - "5 PFH – Private Hochschule Göttingen\n", - "6 Georg-August-Universität Göttingen\n", - "Name: University name, dtype: object" - ] - }, - "execution_count": 50, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "uni_names = pd.Series([ \n", - " \"Hochschule für Bildende Künste Braunschweig\",\n", - " \"Technische Universität Carolo-Wilhelmina zu Braunschweig\",\n", - " \"Hochschule 21\",\n", - " \"Technische Universität Clausthal\",\n", - " \"Hochschule Emden/Leer\",\n", - " \"PFH – Private Hochschule Göttingen\",\n", - " \"Georg-August-Universität Göttingen\"\n", - " ], name=\"University name\")\n", - "\n", - "uni_names" - ] - }, - { - "cell_type": "markdown", - "id": "97930782-3e33-4036-8be2-f40c10f18794", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e989fac8445abfe4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Wie Sie sehen ist der Output identisch.\n", - "\n", - "Um auf einzelne Elemente in der `Series` zuzugreifen werden, wie bereits bekannt von Listen, Index zugriffe verwendet.\n", - "\n", - "Beispiel; Selektion des 2 Elementes:" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "id": "3947baa1-1a3d-41fa-866d-a8acbd07a89a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-07bcadf8f88e6603", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'Technische Universität Carolo-Wilhelmina zu Braunschweig'" - ] - }, - "execution_count": 51, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "uni_names[1]" - ] - }, - { - "cell_type": "markdown", - "id": "d8541372-36fa-4f59-b131-9c737b1e3457", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0662b5716d2ffbf6", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Analog dazu für den Data Frame. Bei dem zuerst die Spalte und dann Reihe selektiert wird:" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "69e57b94-06ea-445b-a8ae-63952dd95358", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d17cf7e2161c24e3", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'Technische Universität Carolo-Wilhelmina zu Braunschweig'" - ] - }, - "execution_count": 53, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "unis[\"University name\"][1]" - ] - }, - { - "cell_type": "markdown", - "id": "720262aa-1d99-469b-896e-1bf5da4b712b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a5f5d2b918c6704b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Wie beim Dictionary lassen sich auch die bekannten Funktionen `.values`, `.keys` & `.items` ausgeben.\n", - "\n", - "Beispiel `.keys`:\n", - "\n", - "Achtung die Ausgabe ist keine Liste auch wenn es den Anschein erwirkt!" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "id": "84809ffa-64a2-4c9d-b3b1-3ff792ebda86", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0a4876a0ab9f0672", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Schlüssel:\n", - "Index(['University name', 'Type of university'], dtype='object')\n", - "\n", - "Rückgabetype:\n", - "\n" - ] - } - ], - "source": [ - "print(\"Schlüssel:\", unis.keys(), \"\\nRückgabetype:\", type(unis.keys()), sep='\\n')" - ] - }, - { - "cell_type": "markdown", - "id": "88957f18-bbc0-4ce3-981d-9b6735ea437b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-7708becc41b11601", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe - Erstellen eines Dataframes\n", - "\n", - "Erstellen Sie einen Pandas Data Frame mit dem namen `uni_addr`, nachdem Schema folgender Tabelle:\n", - "\n", - "| Address | plz |\n", - "|--------------------------|----------------------------|\n", - "| Johannes-Selenka-Platz 1 | 38118 Braunschweig |\n", - "| Universitätspl. 2 | 38106 Braunschweig |\n", - "| Harburger Str. 6 | 21614 Buxtehude |\n", - "| Adolph-Roemer-Straße 2A | 38678 Clausthal-Zellerfeld |\n", - "| Constantiapl. 4 | 26723 Emden |\n", - "| Weender Landstraße 3-7 | 37073 Göttingen |\n", - "| Wilhelmsplatz 1 | 37073 Göttingen |" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "2a6555ac-97ce-4d78-8d19-359b1eeb5a1a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-6ea306cdf2a57ea3", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "uni_addr = None\n", - "\n", - "### BEGIN SOLUTION\n", - "uni_addr = pd.DataFrame({\n", - " \"Address\": [\"Johannes-Selenka-Platz 1\", \"Universitätspl. 2\", \"Harburger Str. 6\", \"Adolph-Roemer-Straße 2A\", \"Constantiapl. 4\", \"Weender Landstraße 3-7\", \"Wilhelmsplatz 1\"],\n", - " \"plz\": [\"38118 Braunschweig\", \"38106 Braunschweig\", \"21614 Buxtehude\", \"38678 Clausthal-Zellerfeld\", \"26723 Emden\", \"37073 Göttingen\", \"37073 Göttingen\",]\n", - "})\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "1936705b-949b-47ad-95e1-67d987662efc", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-daa317b892c6c606", - "locked": true, - "points": 5, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden ihre Lösung gestestet ...\n", - "assert isinstance(uni_addr, pd.DataFrame)\n", - "assert len(uni_addr[\"Address\"]) == 7\n", - "assert len(uni_addr[\"plz\"]) == 7\n", - "### BEGIN HIDDEN TESTS\n", - "uni_addr_test = pd.DataFrame({\n", - " \"Address\": [\"Johannes-Selenka-Platz 1\", \"Universitätspl. 2\", \"Harburger Str. 6\", \"Adolph-Roemer-Straße 2A\", \"Constantiapl. 4\", \"Weender Landstraße 3-7\", \"Wilhelmsplatz 1\"],\n", - " \"plz\": [\"38118 Braunschweig\", \"38106 Braunschweig\", \"21614 Buxtehude\", \"38678 Clausthal-Zellerfeld\", \"26723 Emden\", \"37073 Göttingen\", \"37073 Göttingen\",]\n", - "})\n", - "\n", - "for el1, el2 in zip(uni_addr[\"Address\"], uni_addr_test[\"Address\"]):\n", - " assert el1 == el2\n", - "\n", - "for el1, el2 in zip(uni_addr[\"plz\"], uni_addr_test[\"plz\"]):\n", - " assert el1 == el2\n", - "\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "8f25a6fb-3f9b-497a-a966-3e53c2f86b9c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8871c67f03f141dd", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe - Extrahieren einer Series\n", - "\n", - "Exthahieren Sie die Series `plz` aus dem zuvor erstelltem Data Frame `uni_addr` und speichern Sie ihr Ergebnis in `uni_plz`.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "2de2487d-158e-4dec-a5fa-ccd7478c161c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-240ce62f624ce706", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "uni_plz = None\n", - "\n", - "### BEGIN SOLUTION\n", - "uni_plz = uni_addr[\"plz\"]\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "613f9082-d963-4129-a70c-acfab56759e0", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-dbd86892a80c1f08", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden ihre Lösungen getestet\n", - "uni_plz\n", - "assert isinstance(uni_plz, pd.Series)\n", - "### BEGIN HIDDEN TESTS\n", - "uni_plz_test = pd.Series([\"38118 Braunschweig\", \"38106 Braunschweig\", \"21614 Buxtehude\", \"38678 Clausthal-Zellerfeld\", \"26723 Emden\", \"37073 Göttingen\", \"37073 Göttingen\",], name=\"plz\")\n", - "for el1, el2 in zip(uni_plz, uni_plz_test):\n", - " assert el1 == el2\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "f308563d-e961-40a8-bf11-79d137b02e88", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-02f5ee7a60d555b6", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Reading Data\n", - "\n", - "Die unweiten des Internets ermöglichen es uns Daten auf die unterschiedlichsten Arten zu Archivieren. \n", - "\n", - "Für die Speicherung und Darstellung von (Roh-)Daten werden Datenbanken ([SQL](https://en.wikipedia.org/wiki/SQL)), Transportformate ([JSON](https://en.wikipedia.org/wiki/JSON), [XML](https://en.wikipedia.org/wiki/XML)), Tabellenformate ([Excel](https://en.wikipedia.org/wiki/Microsoft_Excel), [CSV](https://en.wikipedia.org/wiki/Comma-separated_values)) und noch viele mehr verwendet.\n", - "\n", - "Ein beliebtes Betriebsystemunabhängiges Dateiformat für kleine Datensätze (bis 10GB) werden `.csv` Dateien verwendet. Jedes gängige Tabellenkalkulations- und Umfragentool kann seine Daten als _Comma-seperated values_ kurz _CSV_ Exportieren. Schauen Sie dazu gerne in das Datenset `unis_nd.csv`. Im folgenden wird sich ausschließlich auf das Einlesen von CSV-Dateien bezogen. Welche Funktionen und Dateienformate Pandas unterstüzt entnehmen Sie bitte der Dokumentation zu [input/output](https://pandas.pydata.org/docs/reference/io.html).\n", - "\n", - "Da ich ihnen Die Spannung nicht nehmen möchte lösen Sie für die folgenden Beispiele bitte nächste Aufgabe." - ] - }, - { - "cell_type": "markdown", - "id": "a6d7e62b-df8e-4da5-8f74-6c81be0f00df", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-7bf6c58e48e58743", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe - Read CSV\n", - "\n", - "Nutzen sie die Funktion `pd.read_csv` um das Datenset `unis_nd.csv` in die Variable `unis_nd` einzulesen.\n", - "\n", - "Falls Sie hilfe benötigen lesen Sie gerne die Dokumentation im [Getting Started](https://pandas.pydata.org/docs/getting_started/intro_tutorials/02_read_write.html) Guide.\n", - "\n", - "_Hinweis: Die Datei liegt in keinem Ordner, sondern im selben wie dieses Notebook!_" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "b08cc0c4-277b-4e9f-b6e7-a607b912febe", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3cdc8afd6dc12d44", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "unis_nd = None\n", - "\n", - "### BEGIN SOLUTION\n", - "unis_nd = pd.read_csv(\"unis_nd.csv\")\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "e5760557-ddec-4502-b2d3-e8cc2ef70348", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-fd974b3aa3563ca0", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden ihre Lösungen getestet\n", - "assert isinstance(unis_nd, pd.DataFrame)" - ] - }, - { - "cell_type": "markdown", - "id": "ffcf5c5c-1e35-42f9-b35b-2494ff4c421f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-614d1dc9c4566861", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Ausgabe Operationen\n", - "\n", - "Um den gesamten Data Frame auszugeben nutzen Sie einfach die Syntax aus nächster Zelle.\n", - "\n", - "Achtung die Ausgabe ist vergleichweise Groß! Nehmen Sie sich gerne Zeit und schauen Sie sich das Dataset an." - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "c9b8b9a0-0a62-4887-b6e8-c1da6086d7e4", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ec7681e1a54af790", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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University nameType of universitySponsorshipRight of promotionFounding yearNumber of studentsAddresslatlonplzpic
0Hochschule für Bildende Künste BraunschweigArtistic universitypublicyes1963976.000Johannes-Selenka-Platz 152.25773810.50231538118 Braunschweighttps://www.hbk-bs.de/fileadmin/_processed_/5/...
1Technische Universität Carolo-Wilhelmina zu Br...Universitypublicyes174517709.000Universitätspl. 252.27355010.53009738106 Braunschweighttps://upload.wikimedia.org/wikipedia/commons...
2Hochschule 21University of Applied Sciencesprivatno20051084.000Harburger Str. 653.4776509.70465021614 Buxtehudehttps://upload.wikimedia.org/wikipedia/commons...
3Technische Universität ClausthalUniversitypublicyes17753446.000Adolph-Roemer-Straße 2A51.80484010.33411038678 Clausthal-Zellerfeldhttps://www.presse.tu-clausthal.de/fileadmin/T...
4Hochschule Emden/LeerUniversity of Applied Sciencespublicno20094481.000Constantiapl. 453.3681607.18141026723 Emdenhttps://sta-hisweb.hs-emden-leer.de/QIS/images...
5PFH – Private Hochschule GöttingenUniversity of Applied Sciencesprivatno19954226.000Weender Landstraße 3-751.5389109.93322037073 Göttingenhttps://goettingen-campus.de/fileadmin/_proces...
6Georg-August-Universität GöttingenUniversitypublicyes173728614.000Wilhelmsplatz 151.5340709.93785037073 Göttingenhttps://upload.wikimedia.org/wikipedia/commons...
7Fachhochschule für die Wirtschaft HannoverUniversity of Applied Sciencesprivatno1996641.000Freundallee 1552.3662009.77247030173 Hannoverhttps://upload.wikimedia.org/wikipedia/commons...
8Hochschule HannoverUniversity of Applied Sciencespublicno19719209.000Ricklinger Stadtweg 12052.3541909.72238030459 Hannoverhttps://upload.wikimedia.org/wikipedia/commons...
9Hochschule für Musik, Theater und Medien HannoverArtistic universitypublicyes18971409.000Neues Haus 152.3773809.75392030175 Hannoverhttps://upload.wikimedia.org/wikipedia/commons...
10Leibniz-FachhochschuleUniversity of Applied Sciencesprivatno1920589.000Expo Plaza 1152.3211509.81868030539 Hannoverhttps://www.visit-hannover.com/var/storage/ima...
11Medizinische Hochschule Hannover (MHH)Universitypublicyes19633778.000Carl-Neuberg-Straße 152.3840509.80603030625 Hannoverhttps://upload.wikimedia.org/wikipedia/commons...
12Stiftung Tierärztliche Hochschule HannoverUniversitypublicyes17782381.000Bünteweg 252.3546809.79773030559 Hannoverhttps://upload.wikimedia.org/wikipedia/de/thum...
13Gottfried Wilhelm Leibniz Universität HannoverUniversitypublicyes183128935.000Welfengarten 152.3822509.71777030167 Hannoverhttps://www.uni-hannover.de/fileadmin/_process...
14Fachhochschule für Interkulturelle Theologie H...University of Applied Sciencesprivatno201291.000Missionsstraße 3-552.70884310.14071029320 Südheidehttps://cdn.max-e5.info/damfiles/logo/fh_herma...
15Universität HildesheimUniversitypublicyes19788378.000Universitätspl. 152.1340109.97469031141 Hildesheimhttps://www.uni-hildesheim.de/media/_processed...
16HAWK Hochschule für angewandte Wissenschaft un...University of Applied Sciencespublicno19716495.000Hohnsen 452.1424609.95798031134 Hildesheimhttps://upload.wikimedia.org/wikipedia/commons...
17HAWK Hochschule für angewandte Wissenschaft un...University of Applied Sciencespublicno19716495.000Haarmannpl. 351.8272609.45069037603 Holzmindenhttps://upload.wikimedia.org/wikipedia/commons...
18HAWK Hochschule für angewandte Wissenschaft un...University of Applied Sciencespublicno19716495.000Von-Ossietzky-Straße 9951.5217509.96967037085 Göttingenhttps://upload.wikimedia.org/wikipedia/commons...
19Leuphana Universität LüneburgUniversitypublicyes19466497.000Universitätsallee 153.22853110.40171021335 Lüneburghttps://upload.wikimedia.org/wikipedia/commons...
20Norddeutsche Hochschule für Rechtspflege – Nie...University of Administrationpublicno20076409.000Godehardspl. 652.1448409.94923031134 Hildesheimhttps://static.studycheck.de/media/images/inst...
21Kommunale Hochschule für Verwaltung in Nieders...University of Administrationpublicno20071570.000Wielandstraße 852.3705009.72239030169 Hannoverhttps://www.nsi-hsvn.de/fileadmin/user_upload/...
22Carl von Ossietzky Universität Oldenburg\\nUniversitypublicyes197315635.000Uhlhornsweg 49-5553.1473408.17902026129 Oldenburghttps://upload.wikimedia.org/wikipedia/commons...
23Hochschule OsnabrückUniversity of Applied Sciencespublicno197113620.000Albrechtstraße 3052.2826808.02501049076 Osnabrückhttps://login.hs-osnabrueck.de/nidp/hsos/image...
24Universität OsnabrückUniversitypublicyes197313640.000Neuer Graben 2952.2713708.04454049074 Osnabrückhttps://www.eh-tabor.de/sites/default/files/st...
25Hochschule Braunschweig/Wolfenbüttel, Ostfalia...University of Applied Sciencespublicno197111577.000Salzdahlumer Str. 46/4852.17683010.54865038302 Wolfenbüttelhttps://www.ostfalia.de/export/system/modules/...
26Hochschule Wolfsburg, Ostfalia Hochschule für ...University of Applied Sciencespublicno197111577.000Robert-Koch-Platz 8A52.42595010.78711038440 Wolfsburghttps://www.ostfalia.de/export/system/modules/...
27Hochschule Suderburg, Ostfalia Hochschule für ...University of Applied Sciencespublicno197111577.000Herbert-Meyer-Straße 752.89761010.44659029556 Suderburghttps://www.ostfalia.de/export/system/modules/...
28Hochschule Salzgitter, Ostfalia Hochschule für...University of Applied Sciencespublicno197111577.000Karl-Scharfenberg-Straße 55/5752.08724010.38055038229 Salzgitterhttps://www.ostfalia.de/export/system/modules/...
29Hochschule für Künste im Sozialen, OttersbergUniversity of Applied Sciencesprivatno1967342.000Große Str. 10753.1066809.16310028870 Ottersberghttps://upload.wikimedia.org/wikipedia/commons...
30Private Hochschule für Wirtschaft und Technik ...University of Applied Sciencesprivatno1998558.000Rombergstraße 4052.7212508.27891049377 Vechtahttps://www.phwt.de/wp-content/uploads/2020/09...
31Private Hochschule für Wirtschaft und Technik ...University of Applied Sciencesprivatno1998558.000Schlesier Str. 13A52.6117108.36334049356 Diepholzhttps://www.phwt.de/wp-content/uploads/2020/09...
32Universität VechtaUniversitypublicyes19954.551Driverstraße 2252.7211708.29380049377 Vechtahttps://upload.wikimedia.org/wikipedia/commons...
33Hochschule WeserberglandUniversity of Applied Sciencesprivatno2010485.000Am Stockhof 252.0987509.35542031785 Hamelnhttps://upload.wikimedia.org/wikipedia/commons...
34Jade Hochschule – WilhelmshavenUniversity of Applied Sciencespublicno20096789.000Friedrich-Paffrath-Straße 10153.5478708.08804026389 Wilhelmshavenhttps://www.jade-hs.de/fileadmin/layout2016/as...
35Jade Hochschule – OldenburgUniversity of Applied Sciencespublicno20096789.000Ofener Str. 16/1953.1417908.20213026121 Oldenburghttps://www.jade-hs.de/fileadmin/layout2016/as...
36Jade Hochschule – ElsflethUniversity of Applied Sciencespublicno20096789.000Weserstraße 5253.2424408.46651026931 Elsflethhttps://www.jade-hs.de/fileadmin/layout2016/as...
37Steuerakademie Niedersachsen RintelnUniversity of Administrationpublicno2006500.000Wilhelm-Busch-Weg 2952.2069609.09112031737 Rintelnhttps://www.steuerakademie.niedersachsen.de/as...
38Steuerakademie Niedersachsen Bad EilsenUniversity of Administrationpublicno2006500.000Bahnhofstraße 552.2398109.10423031707 Bad Eilsenhttps://www.steuerakademie.niedersachsen.de/as...
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" - ], - "text/plain": [ - " University name \\\n", - "0 Hochschule für Bildende Künste Braunschweig \n", - "1 Technische Universität Carolo-Wilhelmina zu Br... \n", - "2 Hochschule 21 \n", - "3 Technische Universität Clausthal \n", - "4 Hochschule Emden/Leer \n", - "5 PFH – Private Hochschule Göttingen \n", - "6 Georg-August-Universität Göttingen \n", - "7 Fachhochschule für die Wirtschaft Hannover \n", - "8 Hochschule Hannover \n", - "9 Hochschule für Musik, Theater und Medien Hannover \n", - "10 Leibniz-Fachhochschule \n", - "11 Medizinische Hochschule Hannover (MHH) \n", - "12 Stiftung Tierärztliche Hochschule Hannover \n", - "13 Gottfried Wilhelm Leibniz Universität Hannover \n", - "14 Fachhochschule für Interkulturelle Theologie H... \n", - "15 Universität Hildesheim \n", - "16 HAWK Hochschule für angewandte Wissenschaft un... \n", - "17 HAWK Hochschule für angewandte Wissenschaft un... \n", - "18 HAWK Hochschule für angewandte Wissenschaft un... \n", - "19 Leuphana Universität Lüneburg \n", - "20 Norddeutsche Hochschule für Rechtspflege – Nie... \n", - "21 Kommunale Hochschule für Verwaltung in Nieders... \n", - "22 Carl von Ossietzky Universität Oldenburg\\n \n", - "23 Hochschule Osnabrück \n", - "24 Universität Osnabrück \n", - "25 Hochschule Braunschweig/Wolfenbüttel, Ostfalia... \n", - "26 Hochschule Wolfsburg, Ostfalia Hochschule für ... \n", - "27 Hochschule Suderburg, Ostfalia Hochschule für ... \n", - "28 Hochschule Salzgitter, Ostfalia Hochschule für... \n", - "29 Hochschule für Künste im Sozialen, Ottersberg \n", - "30 Private Hochschule für Wirtschaft und Technik ... \n", - "31 Private Hochschule für Wirtschaft und Technik ... \n", - "32 Universität Vechta \n", - "33 Hochschule Weserbergland \n", - "34 Jade Hochschule – Wilhelmshaven \n", - "35 Jade Hochschule – Oldenburg \n", - "36 Jade Hochschule – Elsfleth \n", - "37 Steuerakademie Niedersachsen Rinteln \n", - "38 Steuerakademie Niedersachsen Bad Eilsen \n", - "\n", - " Type of university Sponsorship Right of promotion \\\n", - "0 Artistic university public yes \n", - "1 University public yes \n", - "2 University of Applied Sciences privat no \n", - "3 University public yes \n", - "4 University of Applied Sciences public no \n", - "5 University of Applied Sciences privat no \n", - "6 University public yes \n", - "7 University of Applied Sciences privat no \n", - "8 University of Applied Sciences public no \n", - "9 Artistic university public yes \n", - "10 University of Applied Sciences privat no \n", - "11 University public yes \n", - "12 University public yes \n", - "13 University public yes \n", - "14 University of Applied Sciences privat no \n", - "15 University public yes \n", - "16 University of Applied Sciences public no \n", - "17 University of Applied Sciences public no \n", - "18 University of Applied Sciences public no \n", - "19 University public yes \n", - "20 University of Administration public no \n", - "21 University of Administration public no \n", - "22 University public yes \n", - "23 University of Applied Sciences public no \n", - "24 University public yes \n", - "25 University of Applied Sciences public no \n", - "26 University of Applied Sciences public no \n", - "27 University of Applied Sciences public no \n", - "28 University of Applied Sciences public no \n", - "29 University of Applied Sciences privat no \n", - "30 University of Applied Sciences privat no \n", - "31 University of Applied Sciences privat no \n", - "32 University public yes \n", - "33 University of Applied Sciences privat no \n", - "34 University of Applied Sciences public no \n", - "35 University of Applied Sciences public no \n", - "36 University of Applied Sciences public no \n", - "37 University of Administration public no \n", - "38 University of Administration public no \n", - "\n", - " Founding year Number of students Address \\\n", - "0 1963 976.000 Johannes-Selenka-Platz 1 \n", - "1 1745 17709.000 Universitätspl. 2 \n", - "2 2005 1084.000 Harburger Str. 6 \n", - "3 1775 3446.000 Adolph-Roemer-Straße 2A \n", - "4 2009 4481.000 Constantiapl. 4 \n", - "5 1995 4226.000 Weender Landstraße 3-7 \n", - "6 1737 28614.000 Wilhelmsplatz 1 \n", - "7 1996 641.000 Freundallee 15 \n", - "8 1971 9209.000 Ricklinger Stadtweg 120 \n", - "9 1897 1409.000 Neues Haus 1 \n", - "10 1920 589.000 Expo Plaza 11 \n", - "11 1963 3778.000 Carl-Neuberg-Straße 1 \n", - "12 1778 2381.000 Bünteweg 2 \n", - "13 1831 28935.000 Welfengarten 1 \n", - "14 2012 91.000 Missionsstraße 3-5 \n", - "15 1978 8378.000 Universitätspl. 1 \n", - "16 1971 6495.000 Hohnsen 4 \n", - "17 1971 6495.000 Haarmannpl. 3 \n", - "18 1971 6495.000 Von-Ossietzky-Straße 99 \n", - "19 1946 6497.000 Universitätsallee 1 \n", - "20 2007 6409.000 Godehardspl. 6 \n", - "21 2007 1570.000 Wielandstraße 8 \n", - "22 1973 15635.000 Uhlhornsweg 49-55 \n", - "23 1971 13620.000 Albrechtstraße 30 \n", - "24 1973 13640.000 Neuer Graben 29 \n", - "25 1971 11577.000 Salzdahlumer Str. 46/48 \n", - "26 1971 11577.000 Robert-Koch-Platz 8A \n", - "27 1971 11577.000 Herbert-Meyer-Straße 7 \n", - "28 1971 11577.000 Karl-Scharfenberg-Straße 55/57 \n", - "29 1967 342.000 Große Str. 107 \n", - "30 1998 558.000 Rombergstraße 40 \n", - "31 1998 558.000 Schlesier Str. 13A \n", - "32 1995 4.551 Driverstraße 22 \n", - "33 2010 485.000 Am Stockhof 2 \n", - "34 2009 6789.000 Friedrich-Paffrath-Straße 101 \n", - "35 2009 6789.000 Ofener Str. 16/19 \n", - "36 2009 6789.000 Weserstraße 52 \n", - "37 2006 500.000 Wilhelm-Busch-Weg 29 \n", - "38 2006 500.000 Bahnhofstraße 5 \n", - "\n", - " lat lon plz \\\n", - "0 52.257738 10.502315 38118 Braunschweig \n", - "1 52.273550 10.530097 38106 Braunschweig \n", - "2 53.477650 9.704650 21614 Buxtehude \n", - "3 51.804840 10.334110 38678 Clausthal-Zellerfeld \n", - "4 53.368160 7.181410 26723 Emden \n", - "5 51.538910 9.933220 37073 Göttingen \n", - "6 51.534070 9.937850 37073 Göttingen \n", - "7 52.366200 9.772470 30173 Hannover \n", - "8 52.354190 9.722380 30459 Hannover \n", - "9 52.377380 9.753920 30175 Hannover \n", - "10 52.321150 9.818680 30539 Hannover \n", - "11 52.384050 9.806030 30625 Hannover \n", - 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" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "unis_nd" - ] - }, - { - "cell_type": "markdown", - "id": "586d1ac8-2030-48e2-a662-531c4de9b9cf", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-dff62291b3fc7ab4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Um die Ausgabe auf ein wenige Elemente zu beschränken können die Funktion `head` und `tail` verwendet werden, die jeweils einen Eingabeparameter nehmen zu welcher Zeile Sie von oben bzw. unten den DataFrame anzeigen sollen:" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "a0243d3a-1f2f-4fe9-b134-f13b37d8fc59", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3fd0f85fb2983ec4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "unis_nd.tail(3)" - ] - }, - { - "cell_type": "markdown", - "id": "7573347e-593f-4dd8-a508-5037eb422628", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-cfdfb8a099225918", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Um zu prüfen welche Typen pandas den einzelnen Spalten gegeben hat könne Sie das Attribut `dtypes` verwenden." - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "36d674fe-56ff-4610-8086-adae93bdae62", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-900e418ddc2a0b14", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "University name object\n", - "Type of university object\n", - "Sponsorship object\n", - "Right of promotion object\n", - "Founding year int64\n", - "Number of students float64\n", - "Address object\n", - "lat float64\n", - "lon float64\n", - "plz object\n", - "pic object\n", - "dtype: object" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "unis_nd.dtypes" - ] - }, - { - "cell_type": "markdown", - "id": "093b47e6-7d60-4507-b1d4-e17be1409bed", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-502b1bd3f4ce3db1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Um eine gesamt Übersicht des Dataframes zu bekommen nutzen Sie die Funktion `info`.\n", - "\n", - "Aus dieser können Sie entnehmen in welcher Spalte _#_ wie viele Elemente _Non-Null Count_ vorhanden sind; den Namen der Spalte _Column_ und wie Pandas die Werte der Spalte _dtype_ interpretiert." - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "2ea51488-4dcb-4840-aae8-95bf54c226d0", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c47dd110d6a97b52", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "RangeIndex: 39 entries, 0 to 38\n", - "Data columns (total 11 columns):\n", - " # Column Non-Null Count Dtype \n", - "--- ------ -------------- ----- \n", - " 0 University name 39 non-null object \n", - " 1 Type of university 39 non-null object \n", - " 2 Sponsorship 39 non-null object \n", - " 3 Right of promotion 39 non-null object \n", - " 4 Founding year 39 non-null int64 \n", - " 5 Number of students 39 non-null float64\n", - " 6 Address 39 non-null object \n", - " 7 lat 39 non-null float64\n", - " 8 lon 39 non-null float64\n", - " 9 plz 39 non-null object \n", - " 10 pic 39 non-null object \n", - "dtypes: float64(3), int64(1), object(7)\n", - "memory usage: 3.5+ KB\n" - ] - } - ], - "source": [ - "unis_nd.info()" - ] - }, - { - "cell_type": "markdown", - "id": "46bdc364-7bd2-4b50-bb74-b90d92312465", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d64d555865daff61", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Selecting Subsets\n", - "\n", - "![](https://pandas.pydata.org/docs/_images/03_subset_rows.svg)\n", - "\n", - "Wie Sie bereits aus dem ersten Kapitel Wissen können Sie einzelne Spalten mittels Schlüsselzugriff selektieren. Um mehr als eine Spalte zu Selektieren geben Sie dem Dataframe eine Liste der Schlüssel die sie auswählen möchten mit. Für alle weiterführenden Operationen zum Selektieren von Subsets lesen Sie gerne den [Getting started](https://pandas.pydata.org/docs/getting_started/intro_tutorials/03_subset_data.html) Guide zu Subset Data.\n", - "\n", - "Beispiel Selektion der Spalten _Sponsorship_ & _Founding year_: " - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "id": "4078322c-7354-41ae-a9fa-3af389e37d41", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d98a6a7763f9ebc7", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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27public1971
28public1971
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32public1995
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34public2009
35public2009
36public2009
37public2006
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" - ], - "text/plain": [ - " Sponsorship Founding year\n", - "0 public 1963\n", - "1 public 1745\n", - "2 privat 2005\n", - "3 public 1775\n", - "4 public 2009\n", - "5 privat 1995\n", - "6 public 1737\n", - "7 privat 1996\n", - "8 public 1971\n", - "9 public 1897\n", - "10 privat 1920\n", - "11 public 1963\n", - "12 public 1778\n", - "13 public 1831\n", - "14 privat 2012\n", - "15 public 1978\n", - "16 public 1971\n", - "17 public 1971\n", - "18 public 1971\n", - "19 public 1946\n", - "20 public 2007\n", - "21 public 2007\n", - "22 public 1973\n", - "23 public 1971\n", - "24 public 1973\n", - "25 public 1971\n", - "26 public 1971\n", - "27 public 1971\n", - "28 public 1971\n", - "29 privat 1967\n", - "30 privat 1998\n", - "31 privat 1998\n", - "32 public 1995\n", - "33 privat 2010\n", - "34 public 2009\n", - "35 public 2009\n", - "36 public 2009\n", - "37 public 2006\n", - "38 public 2006" - ] - }, - "execution_count": 38, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "unis_nd[[\"Sponsorship\", \"Founding year\"]]" - ] - }, - { - "cell_type": "markdown", - "id": "bef4ece8-00b0-486d-bba2-7f19e885cf6a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-289af023470b6b19", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe\n", - "\n", - "Selektieren Sie die Spalten _University name_, _Founding year_ & _Number of students_, speichern sie ihr Ergebnis in der Variablen `select`.\n", - "\n", - "Geben Sie danach die ersten 5 Werte von Oben der Selektion aus." - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "040fa689-6062-44db-a6ea-b58113e41b65", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2d560e3a83f1c48a", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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0Hochschule für Bildende Künste Braunschweig1963976.0
1Technische Universität Carolo-Wilhelmina zu Br...174517709.0
2Hochschule 2120051084.0
3Technische Universität Clausthal17753446.0
4Hochschule Emden/Leer20094481.0
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" - ], - "text/plain": [ - " University name Founding year \\\n", - "0 Hochschule für Bildende Künste Braunschweig 1963 \n", - "1 Technische Universität Carolo-Wilhelmina zu Br... 1745 \n", - "2 Hochschule 21 2005 \n", - "3 Technische Universität Clausthal 1775 \n", - "4 Hochschule Emden/Leer 2009 \n", - "\n", - " Number of students \n", - "0 976.0 \n", - "1 17709.0 \n", - "2 1084.0 \n", - "3 3446.0 \n", - "4 4481.0 " - ] - }, - "execution_count": 39, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "select = None\n", - "\n", - "### BEGIN SOLUTION\n", - "select = unis_nd[[\"University name\", \"Founding year\", \"Number of students\"]]\n", - "select.head(5)\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "5bd633ac-afd9-4731-9c00-b494331d2dfb", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-108386a4387dbcc7", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden ihre Lösungen getestet\n", - "assert isinstance(select, pd.DataFrame)\n", - "assert list(select.keys()) == [\"University name\", \"Founding year\", \"Number of students\"]" - ] - }, - { - "cell_type": "markdown", - "id": "e9751208-b181-4764-b436-a57c5313d288", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4fa720449b4af62e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Statistische Funktionen\n", - "\n", - "Wie in der Dokumentation beschrieben unterstützt Pandas verschiendene Statistische Funktion, welche direkt auf einen Data Frame angewendet werden können.\n", - "\n", - "Als Beispiel wird die Funktion `value_counts` auf die Spalte _Type of university_ gezeigt und im darauffolgenden Schritt als Kuchendiagramm geplottet. Das Ergebnis in der Variablen `count` ist eine `pd.Series`.\n", - "\n", - "Editor Side Note: Für den Plot verwende ich das Stylesheet von dhaitz, eines meiner absoluten Favouriten, dieses und mehrere finden Sie unter [github.com dhaitz](https://github.com/dhaitz/matplotlib-stylesheets). Mittels `plt.style.use` lassen sich extene Stylesheets verwenden." - ] - }, - { - "cell_type": "code", - "execution_count": 99, - "id": "14cc37af-13fa-49ce-af37-d327b16bda73", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-daa584941e3d78fe", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "Type of university\n", - "University of Applied Sciences 22\n", - "University 11\n", - "University of Administration 4\n", - "Artistic university 2\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 99, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "count = unis_nd[\"Type of university\"].value_counts()\n", - "count" - ] - }, - { - "cell_type": "code", - "execution_count": 118, - "id": "d8eff47d-e2e7-46c1-94ae-d344b3b62e0f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ea7ef2c3a9ada940", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "format = lambda s: f'Quantity: %d\\n' % s + f'In Percent: %1.1f%%' % s\n", - "\n", - "plt.style.use('https://github.com/dhaitz/matplotlib-stylesheets/raw/master/pitayasmoothie-dark.mplstyle') # Using my favourite Style\n", - "plt.pie(count, labels=count.keys(), autopct=format, startangle=45, explode=[0, 0, 0, 0.2])\n", - "plt.title(\"Types of Universities in lower Saxony (in %)\")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "1104848a-c149-4ef0-8835-aee9f4ad9f36", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1c947f45fd0b2759", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe\n", - "\n", - "Nutzen Sie die Funktion `value_counts` und erstellen Sie ein Balkendiagramm, mittels matplotlib, über die Anzahl an Staatlichen und Privaten Hochschulen Niedersachsen.\n", - "\n", - "Die dazugehörige Spalte im Datenset ist _Sponsorship_. Finden Sie eine geeignete Darstellung." - ] - }, - { - "cell_type": "code", - "execution_count": 117, - "id": "1892e3fc-4d89-4966-bb36-b691a3d16ea4", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-fa553fbf09ed469b", - "locked": false, - "points": 3, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "c = unis_nd[\"Sponsorship\"].value_counts()\n", - "plt.style.use('https://github.com/dhaitz/matplotlib-stylesheets/raw/master/pitayasmoothie-dark.mplstyle')\n", - "plt.bar(c.keys(), c, color=[\"black\", \"white\"])\n", - "plt.show()\n", - "### END SOLUTION" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.0" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/Folium & Pandas/requirements.txt b/Material/wise_24_25/lernmaterial/Folium & Pandas/requirements.txt deleted file mode 100644 index 2ce4f82..0000000 --- a/Material/wise_24_25/lernmaterial/Folium & Pandas/requirements.txt +++ /dev/null @@ -1,88 +0,0 @@ -alembic==1.8.1 -anyio==3.6.2 -appnope==0.1.3 -argon2-cffi==21.3.0 -argon2-cffi-bindings==21.2.0 -asttokens==2.1.0 -attrs==22.1.0 -Babel==2.11.0 -backcall==0.2.0 -beautifulsoup4==4.11.1 -bleach==5.0.1 -branca==0.6.0 -certifi==2022.9.24 -cffi==1.15.1 -charset-normalizer==2.1.1 -debugpy==1.6.3 -decorator==5.1.1 -defusedxml==0.7.1 -entrypoints==0.4 -executing==1.2.0 -fastjsonschema==2.16.2 -folium==0.13.0 -greenlet==2.0.1 -idna==3.4 -ipykernel==6.17.1 -ipython==8.6.0 -ipython-genutils==0.2.0 -ipywidgets==8.0.2 -jedi==0.18.1 -Jinja2==3.1.2 -json5==0.9.10 -jsonschema==4.17.0 -jupyter-server==1.23.2 -jupyter_client==7.4.6 -jupyter_core==5.0.0 -jupyterlab==3.5.0 -jupyterlab-pygments==0.2.2 -jupyterlab-widgets==3.0.3 -jupyterlab_server==2.16.3 -Mako==1.2.4 -MarkupSafe==2.1.1 -matplotlib-inline==0.1.6 -mistune==2.0.4 -nbclassic==0.3.7 -nbclient==0.6.3 -nbconvert==7.2.5 -nbformat==5.7.0 -nbgrader==0.8.1 -nest-asyncio==1.5.6 -notebook==6.4.12 -notebook_shim==0.2.2 -numpy==1.23.4 -packaging==21.3 -pandocfilters==1.5.0 -parso==0.8.3 -pexpect==4.8.0 -pickleshare==0.7.5 -platformdirs==2.5.4 -prometheus-client==0.15.0 -prompt-toolkit==3.0.32 -psutil==5.9.4 -ptyprocess==0.7.0 -pure-eval==0.2.2 -pycparser==2.21 -Pygments==2.13.0 -pyparsing==3.0.9 -pyrsistent==0.19.2 -python-dateutil==2.8.2 -pytz==2022.6 -pyzmq==24.0.1 -rapidfuzz==2.13.2 -requests==2.28.1 -Send2Trash==1.8.0 -six==1.16.0 -sniffio==1.3.0 -soupsieve==2.3.2.post1 -SQLAlchemy==1.4.44 -stack-data==0.6.1 -terminado==0.17.0 -tinycss2==1.2.1 -tomli==2.0.1 -tornado==6.2 -traitlets==5.1.1 -urllib3==1.26.12 -wcwidth==0.2.5 -webencodings==0.5.1 -websocket-client==1.4.2 -widgetsnbextension==4.0.3 diff --git a/Material/wise_24_25/lernmaterial/Folium & Pandas/unis_nd.csv b/Material/wise_24_25/lernmaterial/Folium & Pandas/unis_nd.csv deleted file mode 100644 index 214381c..0000000 --- a/Material/wise_24_25/lernmaterial/Folium & Pandas/unis_nd.csv +++ /dev/null @@ -1,41 +0,0 @@ -University name,Type of university,Sponsorship,Right of promotion,Founding year,Number of students,Address,lat,lon,plz,pic -Hochschule für Bildende Künste Braunschweig,Artistic university,public,yes,1963,976,Johannes-Selenka-Platz 1,52.2577384,10.5023145,38118 Braunschweig,https://www.hbk-bs.de/fileadmin/_processed_/5/1/csm_HBK_Logo_9f3f898a2b.png -Technische Universität Carolo-Wilhelmina zu Braunschweig,University,public,yes,1745,17709,Universitätspl. 2,52.27355,10.530097,38106 Braunschweig,https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Siegel_TU_Braunschweig_transparent.svg/1200px-Siegel_TU_Braunschweig_transparent.svg.png -Hochschule 21,University of Applied Sciences,privat,no,2005,1084,Harburger Str. 6,53.47765,9.70465,21614 Buxtehude,https://upload.wikimedia.org/wikipedia/commons/thumb/b/bd/Hochschule_21_logo.svg/2560px-Hochschule_21_logo.svg.png -Technische Universität Clausthal,University,public,yes,1775,3446,Adolph-Roemer-Straße 2A,51.80484,10.33411,38678 Clausthal-Zellerfeld,https://www.presse.tu-clausthal.de/fileadmin/TU_Clausthal/images/CorporateDesign/Logo/Logo_TUC_en_RGB_gross.gif -Hochschule Emden/Leer,University of Applied Sciences,public,no,2009,4481,Constantiapl. 4,53.36816,7.18141,26723 Emden,https://sta-hisweb.hs-emden-leer.de/QIS/images//logo_el.jpg -PFH – Private Hochschule Göttingen,University of Applied Sciences,privat,no,1995,4226,Weender Landstraße 3-7,51.53891,9.93322,37073 Göttingen,https://goettingen-campus.de/fileadmin/_processed_/d/7/csm_logopfh_20f8eee765.jpg -Georg-August-Universität Göttingen,University,public,yes,1737,28614,Wilhelmsplatz 1,51.53407,9.93785,37073 Göttingen,https://upload.wikimedia.org/wikipedia/commons/c/c0/Logo_Uni_G%C3%B6ttingen_2022.png -Fachhochschule für die Wirtschaft Hannover,University of Applied Sciences,privat,no,1996,641,Freundallee 15,52.3662,9.77247,30173 Hannover,https://upload.wikimedia.org/wikipedia/commons/5/5c/Fachhochschule_f%C3%BCr_die_Wirtschaft_logo.svg -Hochschule Hannover,University of Applied Sciences,public,no,1971,9209,Ricklinger Stadtweg 120,52.35419,9.72238,30459 Hannover,https://upload.wikimedia.org/wikipedia/commons/thumb/0/0e/HsH_Logo.svg/1200px-HsH_Logo.svg.png -"Hochschule für Musik, Theater und Medien Hannover",Artistic university,public,yes,1897,1409,Neues Haus 1,52.37738,9.75392,30175 Hannover,https://upload.wikimedia.org/wikipedia/commons/thumb/7/78/HMTM-Logo-2010.svg/1200px-HMTM-Logo-2010.svg.png -Leibniz-Fachhochschule,University of Applied Sciences,privat,no,1920,589,Expo Plaza 11,52.32115,9.81868,30539 Hannover,https://www.visit-hannover.com/var/storage/images/_aliases/image_full/media/01-data-neu/bilder/redaktion-hannover.de/portale/initiative-wissenschaft/leibniz-fh/leibniz-fachhochschule-logo/8135360-1-ger-DE/Leibniz-Fachhochschule-Logo.jpg -Medizinische Hochschule Hannover (MHH),University,public,yes,1963,3778,Carl-Neuberg-Straße 1,52.38405,9.80603,30625 Hannover,https://upload.wikimedia.org/wikipedia/commons/thumb/3/3d/Medizinische_Hochschule_Hannover_logo.svg/2560px-Medizinische_Hochschule_Hannover_logo.svg.png -Stiftung Tierärztliche Hochschule Hannover,University,public,yes,1778,2381,Bünteweg 2,52.35468,9.79773,30559 Hannover,https://upload.wikimedia.org/wikipedia/de/thumb/5/59/Tier%C3%A4rztliche_Hochschule_Hannover_logo.svg/1200px-Tier%C3%A4rztliche_Hochschule_Hannover_logo.svg.png -Gottfried Wilhelm Leibniz Universität Hannover,University,public,yes,1831,28935,Welfengarten 1,52.38225,9.71777,30167 Hannover,https://www.uni-hannover.de/fileadmin/_processed_/1/5/csm_luh-logo-3x2_8dea6c08fc.jpg -Fachhochschule für Interkulturelle Theologie Hermannsburg,University of Applied Sciences,privat,no,2012,91,Missionsstraße 3-5,52.708843,10.14071,29320 Südheide,https://cdn.max-e5.info/damfiles/logo/fh_hermannsburg/fh_hermannsburg/Kopfgrafik/Logo-FIT--weiss.jpg-b5f510cb468ab8840e0f2e62b703208e.jpg -Universität Hildesheim,University,public,yes,1978,8378,Universitätspl. 1,52.13401,9.97469,31141 Hildesheim,https://www.uni-hildesheim.de/media/_processed_/d/8/csm_Bildkombo_Logo_Uni_Hildesheim-1850_8fd99cc21e.jpg -HAWK Hochschule für angewandte Wissenschaft und Kunst Hildesheim,University of Applied Sciences,public,no,1971,6495,Hohnsen 4,52.14246,9.95798,31134 Hildesheim,https://upload.wikimedia.org/wikipedia/commons/0/02/HAWK-Logo.jpg -HAWK Hochschule für angewandte Wissenschaft und Kunst Holzminden,University of Applied Sciences,public,no,1971,6495,Haarmannpl. 3,51.82726,9.45069,37603 Holzminden,https://upload.wikimedia.org/wikipedia/commons/0/02/HAWK-Logo.jpg -HAWK Hochschule für angewandte Wissenschaft und Kunst Göttingen,University of Applied Sciences,public,no,1971,6495,Von-Ossietzky-Straße 99,51.52175,9.96967,37085 Göttingen,https://upload.wikimedia.org/wikipedia/commons/0/02/HAWK-Logo.jpg -Leuphana Universität Lüneburg,University,public,yes,1946,6497,Universitätsallee 1,53.228531,10.40171,21335 Lüneburg,https://upload.wikimedia.org/wikipedia/commons/thumb/9/93/Leuphana_Universit%C3%A4t_L%C3%BCneburg_Logo_2020.svg/2560px-Leuphana_Universit%C3%A4t_L%C3%BCneburg_Logo_2020.svg.png -Norddeutsche Hochschule für Rechtspflege – Niedersachsen,University of Administration,public,no,2007,6409,Godehardspl. 6,52.14484,9.94923,31134 Hildesheim,https://static.studycheck.de/media/images/institute_logos/small/hr-nord.jpg -Kommunale Hochschule für Verwaltung in Niedersachsen,University of Administration,public,no,2007,1570,Wielandstraße 8,52.3705,9.72239,30169 Hannover,https://www.nsi-hsvn.de/fileadmin/user_upload/02_Studium/big-hsvn_logo.png -"Carl von Ossietzky Universität Oldenburg -",University,public,yes,1973,15635,Uhlhornsweg 49-55,53.14734,8.17902,26129 Oldenburg,https://upload.wikimedia.org/wikipedia/commons/thumb/2/22/Carl_von_Ossietzky_Universit%C3%A4t_Oldenburg_logo.svg/1200px-Carl_von_Ossietzky_Universit%C3%A4t_Oldenburg_logo.svg.png -Hochschule Osnabrück,University of Applied Sciences,public,no,1971,13620,Albrechtstraße 30,52.28268,8.02501,49076 Osnabrück,https://login.hs-osnabrueck.de/nidp/hsos/images/hsos-logo.png -Universität Osnabrück,University,public,yes,1973,13640,Neuer Graben 29,52.27137,8.04454,49074 Osnabrück,https://www.eh-tabor.de/sites/default/files/styles/width980px/public/logo-universitaet-osnabrueck.png?itok=DmZEq9ka -"Hochschule Braunschweig/Wolfenbüttel, Ostfalia Hochschule für angewandte Wissenschaften",University of Applied Sciences,public,no,1971,11577,Salzdahlumer Str. 46/48,52.17683,10.54865,38302 Wolfenbüttel,https://www.ostfalia.de/export/system/modules/de.ostfalia.module.template/resources/images/logo/Ostfalia_German.png_230952558.png -"Hochschule Wolfsburg, Ostfalia Hochschule für angewandte Wissenschaften",University of Applied Sciences,public,no,1971,11577,Robert-Koch-Platz 8A,52.42595,10.78711,38440 Wolfsburg,https://www.ostfalia.de/export/system/modules/de.ostfalia.module.template/resources/images/logo/Ostfalia_German.png_230952558.png -"Hochschule Suderburg, Ostfalia Hochschule für angewandte Wissenschaften",University of Applied Sciences,public,no,1971,11577,Herbert-Meyer-Straße 7,52.89761,10.44659,29556 Suderburg,https://www.ostfalia.de/export/system/modules/de.ostfalia.module.template/resources/images/logo/Ostfalia_German.png_230952558.png -"Hochschule Salzgitter, Ostfalia Hochschule für angewandte Wissenschaften",University of Applied Sciences,public,no,1971,11577,Karl-Scharfenberg-Straße 55/57,52.08724,10.38055,38229 Salzgitter,https://www.ostfalia.de/export/system/modules/de.ostfalia.module.template/resources/images/logo/Ostfalia_German.png_230952558.png -"Hochschule für Künste im Sozialen, Ottersberg",University of Applied Sciences,privat,no,1967,342,Große Str. 107,53.10668,9.1631,28870 Ottersberg,https://upload.wikimedia.org/wikipedia/commons/thumb/e/eb/Logo_HKS_Ottersberg.svg/1200px-Logo_HKS_Ottersberg.svg.png -Private Hochschule für Wirtschaft und Technik Vechta,University of Applied Sciences,privat,no,1998,558,Rombergstraße 40,52.72125,8.27891,49377 Vechta,https://www.phwt.de/wp-content/uploads/2020/09/phwt-logo-free.png -Private Hochschule für Wirtschaft und Technik Diepholz,University of Applied Sciences,privat,no,1998,558,Schlesier Str. 13A,52.61171,8.36334,49356 Diepholz,https://www.phwt.de/wp-content/uploads/2020/09/phwt-logo-free.png -Universität Vechta,University,public,yes,1995,4.551,Driverstraße 22,52.72117,8.2938,49377 Vechta,https://upload.wikimedia.org/wikipedia/commons/0/08/Logo_Uni_Vechta-neu.png -Hochschule Weserbergland,University of Applied Sciences,privat,no,2010,485,Am Stockhof 2,52.09875,9.35542,31785 Hameln,https://upload.wikimedia.org/wikipedia/commons/thumb/0/04/Hochschule_Weserbergland_logo.svg/1200px-Hochschule_Weserbergland_logo.svg.png -Jade Hochschule – Wilhelmshaven,University of Applied Sciences,public,no,2009,6789,Friedrich-Paffrath-Straße 101,53.54787,8.08804,26389 Wilhelmshaven,https://www.jade-hs.de/fileadmin/layout2016/assets/jadehs-logo.png -Jade Hochschule – Oldenburg,University of Applied Sciences,public,no,2009,6789,Ofener Str. 16/19,53.14179,8.20213,26121 Oldenburg,https://www.jade-hs.de/fileadmin/layout2016/assets/jadehs-logo.png -Jade Hochschule – Elsfleth,University of Applied Sciences,public,no,2009,6789,Weserstraße 52,53.24244,8.46651,26931 Elsfleth,https://www.jade-hs.de/fileadmin/layout2016/assets/jadehs-logo.png -Steuerakademie Niedersachsen Rinteln,University of Administration,public,no,2006,500,Wilhelm-Busch-Weg 29,52.20696,9.09112,31737 Rinteln,https://www.steuerakademie.niedersachsen.de/assets/image/232/85611 -Steuerakademie Niedersachsen Bad Eilsen,University of Administration,public,no,2006,500,Bahnhofstraße 5,52.23981,9.10423,31707 Bad Eilsen,https://www.steuerakademie.niedersachsen.de/assets/image/232/85611 diff --git a/Material/wise_24_25/lernmaterial/Lösungen_api_datenanalyse.ipynb b/Material/wise_24_25/lernmaterial/Lösungen_api_datenanalyse.ipynb deleted file mode 100644 index ebd02bc..0000000 --- a/Material/wise_24_25/lernmaterial/Lösungen_api_datenanalyse.ipynb +++ /dev/null @@ -1,1468 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 68, - "id": "2759538c-8e99-4c11-b770-7f777480d887", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "from datetime import date, timedelta\n", - "import requests\n", - "plt.style.use('https://github.com/dhaitz/matplotlib-stylesheets/raw/master/pitayasmoothie-dark.mplstyle')" - ] - }, - { - "cell_type": "markdown", - "id": "ff78c6ed-5348-4f1e-89b4-75a4e77298ce", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "slide" - }, - "tags": [] - }, - "source": [ - "# Application Programming Interfaces" - ] - }, - { - "cell_type": "markdown", - "id": "dab62750-7a06-453a-bff6-33704654eb0e", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "## Task 1\n", - "\n", - "wake a response to the Mensa-Api for the timeframe today + 1 Days and today + 7 Days and extract the current Data for meals. Save your data in the Variable meals." - ] - }, - { - "cell_type": "markdown", - "id": "af237c00-26f6-481e-9269-39770f9c6166", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "source": [ - "Get `today`:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "bd6a280c-5acc-4881-a98c-4518375d47e5", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "datetime.date(2023, 12, 22)" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "today = date.today()\n", - "today" - ] - }, - { - "cell_type": "markdown", - "id": "7d01efe7-c776-4299-a936-e29f7ecfcc59", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "source": [ - "Define `URL`:" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "93451e07-90ae-454c-8a8b-f0cbeffebd1b", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'https://sls.api.stw-on.de/v1/location/101/menu/2023-12-23/2023-12-29'" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "API_URL = \"https://sls.api.stw-on.de/v1/location/101/menu/{}/{}\".format(\n", - " today + timedelta(days = 1), today + timedelta(days = 7))\n", - "API_URL" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "a83c65f0-8e9f-4974-a79d-17fc400ad342", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "API_URL = \"https://sls.api.stw-on.de/v1/location/101/menu/{}/{}\".format(\n", - " today - timedelta(days = 5), today)" - ] - }, - { - "cell_type": "markdown", - "id": "7dd1c1b4-09c7-42dc-b840-f1e343ec4dc6", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "Wake a response and convert to json:" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "a00527d4-a92c-436a-9936-287d4db88cbe", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "resp = requests.get(API_URL)\n", - "resp_json = resp.json()" - ] - }, - { - "cell_type": "markdown", - "id": "ba187080-7eaa-46fa-83f5-1ea60e6c675d", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "source": [ - "Extract Meals Data:" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "0a9f352b-8951-40fc-a477-b2d4384aa4aa", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "{'student': '2.05', 'employee': '3.75', 'guest': '4.85'}" - ] - }, - "execution_count": 37, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "meals = resp_json.get(\"meals\")\n", - "meals[0]['price']" - ] - }, - { - "cell_type": "markdown", - "id": "a7691122-e11b-414b-be72-7f50d65967c5", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "Now convert the list of meals into a Pandas DataFrame object and store it in `df_meals`. Make sure that the date column has the datetime `data` type and that the prices are in a numeric (`float`) format.\n", - "\n", - "Hint: You might want to check the `pandas.json_normalize` function." - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "id": "e086f924-1031-4d0c-8f7c-4f5cfd96ba68", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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iddatenamename_entimespecial_tagsprice.studentprice.employeeprice.guestnutritional_values._NOTE...location.address.ziplocation.address.citylocation.opening_hourslane.idlane.namelane.name_entags.categoriestags.allergenstags.additivestags.special
0501812023-12-18PaprikasuppeBell pepper cream soupnoon[Deprecated. Use tags→special instead.]2.053.754.85WARNING: These fields currently contain incorr......38106Braunschweig[{'time': 'noon', 'start_day': 1, 'end_day': 4...10Suppe & Co.Soup & Co.[{'id': 'VEGA', 'name': 'Vegan', 'name_en': 'v...[{'id': 'SO', 'name': 'enthält Soja(bohnen)u d...[{'id': '2', 'name': 'mit Konservierungsstoff'...[]
1501832023-12-18Bulgurpfanne mit Wildkräutern | Kräuterjoghurt...Bulgur with wild herbs and courgettes | Herb y...noon[Deprecated. Use tags→special instead.]2.505.806.90WARNING: These fields currently contain incorr......38106Braunschweig[{'time': 'noon', 'start_day': 1, 'end_day': 4...20Classic 1Classic 1[{'id': 'VEGT', 'name': 'Vegetarisch', 'name_e...[{'id': 'ML', 'name': 'enthält Milch u Milcher...[][]
\n", - "

2 rows × 33 columns

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" - ], - "text/plain": [ - " id date name \\\n", - "0 50181 2023-12-18 Paprikasuppe \n", - "1 50183 2023-12-18 Bulgurpfanne mit Wildkräutern | Kräuterjoghurt... \n", - "\n", - " name_en time \\\n", - "0 Bell pepper cream soup noon \n", - "1 Bulgur with wild herbs and courgettes | Herb y... noon \n", - "\n", - " special_tags price.student price.employee \\\n", - "0 [Deprecated. Use tags→special instead.] 2.05 3.75 \n", - "1 [Deprecated. Use tags→special instead.] 2.50 5.80 \n", - "\n", - " price.guest nutritional_values._NOTE ... \\\n", - "0 4.85 WARNING: These fields currently contain incorr... ... \n", - "1 6.90 WARNING: These fields currently contain incorr... ... \n", - "\n", - " location.address.zip location.address.city \\\n", - "0 38106 Braunschweig \n", - "1 38106 Braunschweig \n", - "\n", - " location.opening_hours lane.id lane.name \\\n", - "0 [{'time': 'noon', 'start_day': 1, 'end_day': 4... 10 Suppe & Co. \n", - "1 [{'time': 'noon', 'start_day': 1, 'end_day': 4... 20 Classic 1 \n", - "\n", - " lane.name_en tags.categories \\\n", - "0 Soup & Co. [{'id': 'VEGA', 'name': 'Vegan', 'name_en': 'v... \n", - "1 Classic 1 [{'id': 'VEGT', 'name': 'Vegetarisch', 'name_e... \n", - "\n", - " tags.allergens \\\n", - "0 [{'id': 'SO', 'name': 'enthält Soja(bohnen)u d... \n", - "1 [{'id': 'ML', 'name': 'enthält Milch u Milcher... \n", - "\n", - " tags.additives tags.special \n", - "0 [{'id': '2', 'name': 'mit Konservierungsstoff'... [] \n", - "1 [] [] \n", - "\n", - "[2 rows x 33 columns]" - ] - }, - "execution_count": 56, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_meals = pd.json_normalize(meals)\n", - "df_meals[\"date\"] = pd.to_datetime(df_meals[\"date\"])\n", - "df_meals[\"price.student\"] = pd.to_numeric(df_meals[\"price.student\"])\n", - "df_meals.head(2)" - ] - }, - { - "cell_type": "markdown", - "id": "19fcfa4a-2dfd-443d-84af-5519d2eb61a1", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "Next, create a simple plot that plots the student prices over time. You can use a scatter plot to do this." - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "id": "039c0393-c015-4f83-8093-5d3a37d11245", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.scatter(df_meals[\"date\"], df_meals[\"price.student\"])\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "01fc72e6-3dc3-4c75-8cd4-1eaa4f3c2dbb", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "## Task 2\n", - "\n", - "Next, make a request to the Mensa API to get all meals in the time frame December 1, 2023 to December 21, 2023.\n", - "\n", - "After requesting the data, Analyze it by their mean price Distribution, and a thing you find interesting to analyze. (Be Creative)\n", - "\n", - "What can you observe?" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "id": "6dcd8328-771a-47a4-accd-d1945118d81e", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "40" - ] - }, - "execution_count": 59, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "API_URL = \"https://sls.api.stw-on.de/v1/location/101/menu/2023-12-01/2023-12-21\"\n", - "\n", - "resp = requests.get(API_URL)\n", - "data = resp.json()\n", - "\n", - "meals=data.get(\"meals\")\n", - "len(meals)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "3b98f3ae-1f53-4330-a62d-3f4926d74456", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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0501812023-12-18PaprikasuppeBell pepper cream soupnoon[Deprecated. Use tags→special instead.]2.053.754.85WARNING: These fields currently contain incorr......Mensa 1 TU Braunschweig{'line1': 'Mensa 1 TU Braunschweig', 'line2': ...[{'time': 'noon', 'start_day': 1, 'end_day': 4...10Suppe & Co.Soup & Co.[{'id': 'VEGA', 'name': 'Vegan', 'name_en': 'v...[{'id': 'SO', 'name': 'enthält Soja(bohnen)u d...[{'id': '2', 'name': 'mit Konservierungsstoff'...[]
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" - ], - "text/plain": [ - " id date name name_en time \\\n", - "0 50181 2023-12-18 Paprikasuppe Bell pepper cream soup noon \n", - "\n", - " special_tags price.student price.employee \\\n", - "0 [Deprecated. Use tags→special instead.] 2.05 3.75 \n", - "\n", - " price.guest nutritional_values._NOTE ... \\\n", - "0 4.85 WARNING: These fields currently contain incorr... ... \n", - "\n", - " location.name location.address \\\n", - "0 Mensa 1 TU Braunschweig {'line1': 'Mensa 1 TU Braunschweig', 'line2': ... \n", - "\n", - " location.opening_hours lane.id lane.name \\\n", - "0 [{'time': 'noon', 'start_day': 1, 'end_day': 4... 10 Suppe & Co. \n", - "\n", - " lane.name_en tags.categories \\\n", - "0 Soup & Co. [{'id': 'VEGA', 'name': 'Vegan', 'name_en': 'v... \n", - "\n", - " tags.allergens \\\n", - "0 [{'id': 'SO', 'name': 'enthält Soja(bohnen)u d... \n", - "\n", - " tags.additives tags.special \n", - "0 [{'id': '2', 'name': 'mit Konservierungsstoff'... [] \n", - "\n", - "[1 rows x 22 columns]" - ] - }, - "execution_count": 60, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_meals=pd.json_normalize(meals, max_level=1)\n", - "df_meals=df_meals.astype({'price.student': 'float',\"price.employee\":\"float\", \"price.guest\":\"float\"})\n", - "df_meals[\"date\"]=df_meals[\"date\"].astype('datetime64[ns]')\n", - "df_meals.head(1)" - ] - }, - { - "cell_type": "markdown", - "id": "3995a8a9-6e02-4228-a288-8708a7fedffd", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "Analyzing Price Distribution:" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "id": "08bcf84c-32c3-4afe-b333-6863acd31dc6", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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dateidprice.studentprice.employeeprice.guestlocation.idlane.id
date
2023-12-182023-12-18501812.0203.1853.70010110
2023-12-192023-12-19501891.9753.2353.71510110
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" - ], - "text/plain": [ - " date id price.student price.employee price.guest \\\n", - "date \n", - "2023-12-18 2023-12-18 50181 2.020 3.185 3.700 \n", - "2023-12-19 2023-12-19 50189 1.975 3.235 3.715 \n", - "2023-12-20 2023-12-20 50397 2.020 3.245 3.760 \n", - "2023-12-21 2023-12-21 50225 2.135 3.300 3.815 \n", - "\n", - " location.id lane.id \n", - "date \n", - "2023-12-18 101 10 \n", - "2023-12-19 101 10 \n", - "2023-12-20 101 10 \n", - "2023-12-21 101 10 " - ] - }, - "execution_count": 54, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "\n", - "aggregation_functions = {'date': 'first',\n", - " 'id': 'first',\n", - " 'price.student': 'mean',\n", - " 'price.employee':\"mean\",\n", - " \"price.guest\":\"mean\",\n", - " \"location.id\":\"first\",\n", - " \"lane.id\":\"first\"}\n", - "df_new = df_meals.groupby(df_meals['date']).aggregate(aggregation_functions)\n", - "df_new" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "id": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#mean_price.plot\n", - "plt.plot(df_new[\"date\"], df_new[\"price.student\"], color=\"yellow\",label=\"student\") \n", - "plt.plot(df_new[\"date\"], df_new[\"price.employee\"],color= \"red\", label=\"employee\")\n", - "plt.plot(df_new[\"date\"], df_new[\"price.guest\"], color= \"purple\", label=\"guest\")\n", - "plt.title('Prices Mensa over time') \n", - "plt.xlabel('Date') \n", - "plt.ylabel('Price') \n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "93879add-8854-4170-8962-13b2fefaa686", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "slide" - }, - "tags": [] - }, - "source": [ - "# Data Analysis" - ] - }, - { - "cell_type": "markdown", - "id": "cde1855d-ddf6-487f-a02f-5e75bafffcc6", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "## Setup" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "id": "23efc8a6-5c1c-45c5-90a7-4c8d70f59fc8", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "markdown", - "id": "15a624b0-53bf-4bc8-a1a6-4bb499d74af4", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "Next read in the dataset `survey.csv`. For testing puposes use the Variable Name `df`." - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "id": "e1064073-6a61-4d49-9984-3f244462d6c2", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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AgeSexScale Python ExpCourseHas Voice Assistent ContactVoice AssistentScale Study SatisfactionUses SmartphoneWhich SmartphoneHas ComputerWhich OSScale Programming Exp
022Männlich4MedienwissenschaftenJaApple Siri4JaAppleJaMac OS2
126Weiblich3MedienwissenschaftenJaAmazon Alexa2JaXiaomiJaWindows 103
221Männlich3MedienwissenschaftenJaGoogle Now4JaSonstigeJaWindows 103
326Weiblich4MedienwissenschaftenJaApple Siri4JaSamsungJaWindows 102
424Weiblich4PsychologieNeinNaN4JaAppleJaWindows 113
\n", - "
" - ], - "text/plain": [ - " Age Sex Scale Python Exp Course \\\n", - "0 22 Männlich 4 Medienwissenschaften \n", - "1 26 Weiblich 3 Medienwissenschaften \n", - "2 21 Männlich 3 Medienwissenschaften \n", - "3 26 Weiblich 4 Medienwissenschaften \n", - "4 24 Weiblich 4 Psychologie \n", - "\n", - " Has Voice Assistent Contact Voice Assistent Scale Study Satisfaction \\\n", - "0 Ja Apple Siri 4 \n", - "1 Ja Amazon Alexa 2 \n", - "2 Ja Google Now 4 \n", - "3 Ja Apple Siri 4 \n", - "4 Nein NaN 4 \n", - "\n", - " Uses Smartphone Which Smartphone Has Computer Which OS \\\n", - "0 Ja Apple Ja Mac OS \n", - "1 Ja Xiaomi Ja Windows 10 \n", - "2 Ja Sonstige Ja Windows 10 \n", - "3 Ja Samsung Ja Windows 10 \n", - "4 Ja Apple Ja Windows 11 \n", - "\n", - " Scale Programming Exp \n", - "0 2 \n", - "1 3 \n", - "2 3 \n", - "3 2 \n", - "4 3 " - ] - }, - "execution_count": 63, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df = pd.read_csv(\"survey.csv\")\n", - "df.head()" - ] - }, - { - "cell_type": "markdown", - "id": "f6703c75-1795-4a02-88bd-001961a3e30e", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "# Hypothesis 1\n", - "\n", - "__The average age in the course is 25.34 years, with a surplus of females.__" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "id": "85f41410-fa96-4d27-963a-2eecc1dbb8ed", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Mean Age: 22.64\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "print(\"Mean Age:\", df[\"Age\"].mean())\n", - "c = df[\"Sex\"].value_counts()\n", - "plt.title(\"Gender Distribution\")\n", - "plt.bar(c.keys(), c, color=[\"black\", \"white\"])\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "84ad4ec5-809e-4d50-9ac4-d0e55998b4f2", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "# Hypothesis 2\n", - "\n", - "__The most used voice assistant is Alexa.__" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "id": "1907f74b-b7bf-48f2-a544-f5acc4dcd2a3", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "c = df[\"Voice Assistent\"].value_counts()\n", - "plt.title(\"Voice Assistent Distribution\")\n", - "plt.bar(c.keys(), c, color=[\"red\", \"green\", \"blue\"])\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "950b588b-6253-428e-a4a3-9efd6f9b9d3f", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "# Hypothesis 3" - ] - }, - { - "cell_type": "markdown", - "id": "6dbaf7e5-a6a3-4dd6-be4d-cf483f6bd240", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "## Hypothesis 3.1\n", - "\n", - "__The least used smartphone operating system is iOS.__" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "id": "68960c84-031a-44de-8904-475a4a2deddf", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "os_dict = {\n", - " \"iOS\": 0,\n", - " \"Android\": 0\n", - "}\n", - "\n", - "for data in df[\"Which Smartphone\"]:\n", - " if data == \"Apple\":\n", - " os_dict[\"iOS\"] += 1\n", - " else:\n", - " os_dict[\"Android\"] += 1\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 78, - "id": "8cbd40a2-64e8-4d3b-99bb-35fbf2a1c471", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.title(\"Mobile OS Distribution\")\n", - "plt.bar(os_dict.keys(), os_dict.values(), color=[\"silver\", \"green\"])\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "db9f1a22-9e5f-4efe-a2f4-096c78d4a353", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "## Hypothesis 3.2\n", - "\n", - "__The most used desktop operating system is Windows 10.__" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "id": "7ed466a2-ec98-49f3-8b74-3e95f3c0b3fd", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "os_dict = df[\"Which OS\"].value_counts()\n", - "plt.title(\"Desktop OS Distribution\")\n", - "plt.bar(os_dict.keys(), os_dict, color=[\"grey\", \"silver\", \"cyan\", \"yellow\"])\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "c98adc74-bfd1-4b3a-9f21-030547052302", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "# Hypothesis 4" - ] - }, - { - "cell_type": "markdown", - "id": "07ba83d7-55d9-4c38-a82b-b6b3751e6354", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "## Hypothesis 4.1 & 4.2\n", - "\n", - "__The youngest people use an iPhone.__\n", - "__Older people use an Android-based smartphone.__" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "id": "312838f3-3191-47ad-88d4-cae46482b7ce", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "age_mean = df[\"Age\"].mean()\n", - "youngest = {\n", - " \"ios\": 0,\n", - " \"Android\": 0,\n", - " \"n\": 0,\n", - " \"ratio iOS\": 0,\n", - " \"ratio Android\": 0\n", - "}\n", - "\n", - "oldest = {\n", - " \"ios\": 0,\n", - " \"Android\": 0,\n", - " \"n\": 0,\n", - " \"ratio iOS\": 0,\n", - " \"ratio Android\": 0\n", - "}" - ] - }, - { - "cell_type": "markdown", - "id": "edb0864e-9890-4c4a-92ca-f275dfbd658b", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "Count appreances:" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "id": "fb13bec6-0536-4268-9fe1-a7ccdc177d76", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "for index, row in df[[\"Age\", \"Which Smartphone\"]].iterrows():\n", - " if age_mean > row[\"Age\"]:\n", - " youngest[\"n\"] += 1\n", - " if row[\"Which Smartphone\"] == \"Apple\":\n", - " youngest[\"ios\"] += 1\n", - " else:\n", - " youngest[\"Android\"] += 1\n", - "\n", - " if age_mean < row[\"Age\"]:\n", - " oldest[\"n\"] += 1\n", - " if row[\"Which Smartphone\"] != \"Apple\":\n", - " oldest[\"Android\"] += 1\n", - " else:\n", - " oldest[\"ios\"] += 1" - ] - }, - { - "cell_type": "markdown", - "id": "d12d9530-4b49-4d9d-ba96-e1e49a2eada2", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "source": [ - "Calc Ratios:" - ] - }, - { - "cell_type": "code", - "execution_count": 91, - "id": "aef9b0fe-064c-4e09-9013-9ee1e53bf27b", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "fragment" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "youngest[\"ratio iOS\"] = youngest[\"ios\"] / youngest[\"n\"] * 100\n", - "youngest[\"ratio Android\"] = youngest[\"Android\"] / youngest[\"n\"] * 100\n", - "\n", - "oldest[\"ratio iOS\"] = oldest[\"ios\"] / oldest[\"n\"] * 100\n", - "oldest[\"ratio Android\"] = oldest[\"Android\"] / oldest[\"n\"] * 100" - ] - }, - { - "cell_type": "code", - "execution_count": 90, - "id": "1f051e34-6a14-4e75-8a4c-4d4bc76db3ca", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "subslide" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.title(\"iOS Ratio between mean Age\")\n", - "plt.bar([\"Y: mean iOS\", \"Y: mean Android\", \"O: mean iOS\", \"O: mean Android\"], \n", - " [youngest[\"ratio iOS\"], youngest[\"ratio Android\"], oldest[\"ratio iOS\"], oldest[\"ratio Android\"]], color=[\"gold\", \"silver\"])\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9e537484-c541-416e-8b25-d7b4a75e1e2c", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "skip" - }, - "tags": [] - }, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/Random Numbers/zufallszahlen.ipynb b/Material/wise_24_25/lernmaterial/Random Numbers/zufallszahlen.ipynb deleted file mode 100644 index 244b4af..0000000 --- a/Material/wise_24_25/lernmaterial/Random Numbers/zufallszahlen.ipynb +++ /dev/null @@ -1,1963 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "7b52245d-145a-434c-8432-4a910ac37628", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-918f356c69a0adbd", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# 3. Programmierübung: Zufallszahlen\n", - "\n", - "
\n", - "
\n", - " Willkommen zur ersten Programmierübung Einführung in Python 3.\n", - "
\n", - " \n", - "
\n", - "\n", - "Wenn Sie Fragen oder Verbesserungsvorschläge zum Inhalt oder Struktur der Notebooks haben, dann können sie eine E-Mail an Phil Keier ([p.keier@hbk-bs.de](mailto:p.keier@hbk-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) oder Martin Le ([martin.le@tu-bs.de](mailto:martin.le@tu-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) schreiben.\n", - "\n", - "Link zu einem Python Spickzettel: [hier](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf)\n", - "\n", - "Der Großteil des Python-Tutorials stammt aus der Veranstaltung _Deep Learning Lab_ und von [www.python-kurs.eu](https://www.python-kurs.eu/python3_kurs.php) und wurde für _Signale und Systeme_, sowie _Einführung in die Programmierung für Nicht Informatiker_ angepasst.\n", - "\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "c0f36367-a7b0-435f-819a-6013b305bc78", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8003a63181c7928b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Vorraussetzung\n", - "\n", - "Da wir einige Bibliotheken brauchen führen sie bitte folgende Zellen vor der Benutzung dieses Notebooks aus, da es sonst zu Fehlern kommt." - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "2e2b133a-e725-4785-90ed-1a44e4bbaa75", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5d81dd4fdb7076e1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Visualisierungs Tools\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline\n", - "\n", - "# Pythons BuiltIn Library & Numpy\n", - "import random \n", - "import numpy as np" - ] - }, - { - "cell_type": "markdown", - "id": "641b1f8a-1c77-43e5-ad86-81ade9932479", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c7e6f6e837a94d41", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Warum Zufall?\n", - "\n", - "Für statistische Analysen jeglicher Art ist es wichtig seine Werkzeuge zu verstehen. Da nicht immer direkt ein Dataset vorliegt oder dieses zurzeit noch im Erstellungsprozess ist, gibt es die Möglichkeit die mathematischen und programmatischen Werzeuge zuvor an nachvollziebaren Zufallsdaten zu testen. Dabei wollen wir in dieser Übung lernen, was Zufall ist, wie Zufallsgeneratoren funktionieren und wie der Zufall auf bestimmte Art manipuliert werden kann.\n", - "\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "1534936a-813f-4045-930c-b7e1e979afa2", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f387eeef09033ea3", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Was ist Zufall?\n", - "\n", - "Für Zufall gibt es viele Definitionen. Aber was genau ist Zufall? Das Würfeln eines Würfels zum Beispiel ist nicht zufällig. Jeder Würfelwurf kann vorhergesagt werden, vorausgesetzt, alle erforderlichen Daten sind vorhanden. Auch das Wetter ist nicht zufällig. Alle Ereignisse lassen sich vorhersagen, wenn genügend Daten vorhanden sind, das Problem ist nur, dass es nie genug Daten gibt. \n", - "\n", - "Jedes andere Beispiel kann mit der gleichen Argumentation als \"zufällig\" widerlegt werden. Daher werden diese Phänomene als pseudo-zufällig bezeichnet. \n", - "\n", - "Aber das nur am Rande. In der Physik gibt es ein Phänomen, das völlig unvorhersehbar ist. Wenn ein einzelnes Photon auf einen halbtransparenten Spiegel geschossen wird, kann __nie__ vorhergesagt werden, auf welchen der beiden Detektoren das Photon treffen wird. Diese Form der wirklich echten Zufalls wird von der Firma [ID Quntique](https://www.idquantique.com/random-number-generation/overview/) genutzt und verkauft Geräte, die das zuvor erklärte Quantenphänomen nutzen.\n", - "\n", - "Aber genug von der echten Koinzidenz und zurück zum Pseudo-Zufall und wie Computer damit umgehen.\n", - "\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "9575afd2-efdd-4ce5-be0a-d2eaf14d979f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-915e9fd37a4dece5", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Pythons BuiltIn Random\n", - "\n", - "Unter dem Abschnitt Vorraussetzung haben wir bereits Pythons BuiltIn Library [random](https://docs.python.org/3.11/library/random.html) importiert. Schauen Sie gerne in die Dokumentation diese beinhält Erklärungen zu allen hier behandelten Funktionen.\n", - "\n", - "Das 'Hello World' Programm der Zufallszahlen ist das Simulieren eines Würfels. Dabei hat jede Seite eines Würfels dieselbe Auftrittswahrscheinlichkeit $\\frac{1}{\\text{Anzahl der Seiten des Würfels}}$. Für einen 6-Seitigen Würfel sind das die Werte `1...6`. Die Funktion [random.randint](https://docs.python.org/3.11/library/random.html#random.randint) gibt uns die Möglichkeit eine ganzzahlige Zufallszahl zwischen zwei ganzzahligen Werten zu ziehen. Simulieren wir im folgenden Beispiel zehn unabhängige Würfe (führen Sie die Zelle gerne mehrmals aus):" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "acdd947d-de8a-4389-8b74-48836acc6602", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2fced744f253cfc2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Wurf: 1 => Ergebnis: 2\n", - "Wurf: 2 => Ergebnis: 4\n", - "Wurf: 3 => Ergebnis: 6\n", - "Wurf: 4 => Ergebnis: 1\n", - "Wurf: 5 => Ergebnis: 2\n", - "Wurf: 6 => Ergebnis: 4\n", - "Wurf: 7 => Ergebnis: 1\n", - "Wurf: 8 => Ergebnis: 4\n", - "Wurf: 9 => Ergebnis: 5\n", - "Wurf: 10 => Ergebnis: 1\n" - ] - } - ], - "source": [ - "for i in range(1, 11):\n", - " wurf = random.randint(1,6)\n", - " print(\"Wurf: {} => Ergebnis: {}\".format(i, wurf))" - ] - }, - { - "cell_type": "markdown", - "id": "fd9d16eb-65da-44a8-8878-882b9bb80d99", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4b4a74f9b1b17afe", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Die Ergebnisse sind doch sehr Zufällig und nahezu nicht Vorrauszusehen.\n", - "\n", - "Möchte man nun die Physik beugen und einen gezinkten Würfel haben bietet 'random' auch hierfür eine Funktion. [random.seed](https://docs.python.org/3.11/library/random.html#random.randint) mit Seed ist dabei der Anfangswert des Zufallsgenerator gemeint. Wie dies technisch aufgebaut ist folgt im nächsten Kapitel. Dabei bewirkt der Aufruf von 'random.seed' das der Startwert gesetzt wird. Die Krux dabei ist das alle folgenden Zahlen nachdem setzen nicht mehr Zufällig sind - Sie sind Pseudo Random. Probieren wir dies mit unserem Würfel aus. Dabei wird der Seed Wert vor jedem Aufruf der 'random.randint' Funktion ausgeführt:" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "cd53f1a3-f777-4e27-8d20-d3cfa1b97a7b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0ead1cf8d3a39192", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Wurf: 1 => Ergebnis: 6\n", - "Wurf: 2 => Ergebnis: 6\n", - "Wurf: 3 => Ergebnis: 6\n", - "Wurf: 4 => Ergebnis: 6\n", - "Wurf: 5 => Ergebnis: 6\n", - "Wurf: 6 => Ergebnis: 6\n", - "Wurf: 7 => Ergebnis: 6\n", - "Wurf: 8 => Ergebnis: 6\n", - "Wurf: 9 => Ergebnis: 6\n", - "Wurf: 10 => Ergebnis: 6\n" - ] - } - ], - "source": [ - "for i in range(1, 11):\n", - " random.seed(42) # Startwert wird vor jedem Aufruf gesetzt\n", - " wurf = random.randint(1,6)\n", - " print(\"Wurf: {} => Ergebnis: {}\".format(i, wurf))" - ] - }, - { - "cell_type": "markdown", - "id": "0d682554-152f-439c-9c57-8d6950704dec", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-303e2d200f7022c2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Und genauso wird die Physik gebeugt!\n", - "\n", - "Probieren wir es im nächsten Schritt selber aus und simulieren einen 10-Seitigen Würfel.\n", - "\n", - "**Aufgabe**: Fühle die gegebene leere Liste `rands` mit 10 Zufälligen Werten zwischen 1 & 10, mittels der Funktion `random.randint`." - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "85e986e4-368b-4a56-b5fe-a4c2f1268ab8", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-cd2a81fd471a6040", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "rands = list()\n", - "# BEGIN SOLUTION\n", - "rands = [random.randint(1,10) for _ in range(10)]\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "120c91d4-6c93-449d-9e12-c812ee97edcd", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-fe7e8399a07b78cd", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[2, 1, 5, 4, 4, 3, 2, 9, 2, 10]\n" - ] - } - ], - "source": [ - "# Hier werden ihre Lösungen getestet\n", - "print(rands)\n", - "assert len(rands) == 10" - ] - }, - { - "cell_type": "markdown", - "id": "384ecb1d-04a4-410d-a0bc-3bb9a066e502", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-94196c05d162e8f2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Die Funktion [random.shuffle](https://docs.python.org/3.11/library/random.html#random.shuffle) kann eine Liste zufällig in-place umsortieren. Wichtig (!!) dabei wird der Zustand der Liste verändert!. Folgendes Beispiel Sortiert ein Array mit geordneten Zahlen `1..10` Zufällig um:" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "51a2973d-b9f2-4a2f-a0bc-8a4837dc388b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3290d35ecac9a91f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Geordnete Zahlen von 1-10: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n", - "Zufällig Umsortierte Zahlen von 1-10: [5, 4, 3, 10, 6, 2, 8, 9, 1, 7]\n" - ] - } - ], - "source": [ - "numbers = [i for i in range(1, 11)]\n", - "print(\"Geordnete Zahlen von 1-10:\", numbers)\n", - "\n", - "# Umsortieren mittels random.shuffle\n", - "random.shuffle(numbers)\n", - "print(\"Zufällig Umsortierte Zahlen von 1-10:\", numbers)" - ] - }, - { - "cell_type": "markdown", - "id": "f5c12549-1986-401f-ba0b-420bbb10a285", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b4fd6773031076b4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Soll die Liste unberührt bleiben und trotzdem eine zufällige Sequenz aus dieser generiert werden wird die Funktion [random.sample](https://docs.python.org/3.11/library/random.html#random.shuffle) verwendet. Dazu wird der Funktion eine Liste gegeben und die länge der Ausgabeliste." - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "id": "7ac3c609-0bbd-4511-81ca-ccf88c70450b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0e2d89c53dc58435", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Liste: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] => 6 Element großes Sample der Liste: [9, 7, 4, 8, 5, 3]\n" - ] - } - ], - "source": [ - "samplesize = 6\n", - "numbers = [i for i in range(1, 11)]\n", - "sample = random.sample(numbers, samplesize)\n", - "print(\"Liste: {} => 6 Element großes Sample der Liste: {}\".format(numbers, sample))" - ] - }, - { - "cell_type": "markdown", - "id": "a4465e36-927c-4deb-8807-5aa854e7649c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e695e92905a78fc4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Absolut Zufällige Floats\n", - "\n", - "Die Funktion [random.random](https://docs.python.org/3.11/library/random.html#random.random) gibt eine Flieskommazahl zwischen 0 & 1 zurück:" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "385c5337-1c5f-42cc-930b-f0007e2a57c0", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1bdf1f5401e3ceff", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "10 Zufällige Zahlen:\n", - "0.8094304566778266\n", - "0.006498759678061017\n", - "0.8058192518328079\n", - "0.6981393949882269\n", - "0.3402505165179919\n", - "0.15547949981178155\n", - "0.9572130722067812\n", - "0.33659454511262676\n", - "0.09274584338014791\n", - "0.09671637683346401\n" - ] - } - ], - "source": [ - "print(\"10 Zufällige Zahlen:\")\n", - "for _ in range(10):\n", - " print(random.random())" - ] - }, - { - "cell_type": "markdown", - "id": "72559deb-f72f-4c14-8da7-ec95fcd74a39", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-dcfeaecec3828dc0", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Visualisieren wir diese Verteilung einmal für 100 Samples:" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "7f3b5b5d-858a-4021-87ec-4dcfb167df41", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-003196d2cdb70499", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "x = [random.random() for _ in range(20)] # Hier werden die Zufallszahlen generiert\n", - "plt.plot(range(20), x)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "04f5de6c-1c10-4401-bd47-ade13028fd17", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-14846e0aed52cf25", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Der Graph lässt sich interpretieren indem man sich die Verteilung ansieht. Diese wechselt rapide zwischen den Werten und folgt keiner smoothen Verteilung." - ] - }, - { - "cell_type": "markdown", - "id": "60ee2157-bb02-42d6-a5a5-d7d9048355ba", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4a2cf0b4ee4947a1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Distribution Functions\n", - "\n", - "Die Funktion [random.uniform](https://docs.python.org/3.11/library/random.html#random.uniform) erzeugt Zufallszahlen in dem Bereich seiner Eingabewerte. Während `random.random` nur Zahlen zwischen `0...1` erzeugt, lässt sich mit `random.uniform` Zufallswerte im Bereich `a...b` erzeugen. Dabei erfolgt die Berechnung, wie in der Dokumentation beschrieben, $\\frac{a}{(b-a) \\cdot \\text{random()}}$. Nutzen wir folgend die Werte eines 6-Seitigen Würfels und Visualisieren wir die Verteilung wieder. Achten Sie auf die Achsen:" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "c5d2d8c0-101d-416c-bb3f-24f0d49b31c8", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2048ce159893a872", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "x = [random.uniform(1,6) for _ in range(20)] # Hier werden die Zufallszahlen generiert\n", - "plt.plot(range(20), x)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "79dff9c5-510c-45a2-92ab-a22a5086c4dd", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-12b409cc047bfe76", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Auch häufig verwendet werden Zufallszahlen die aus einer [Gauss Verteilung](https://de.wikipedia.org/wiki/Normalverteilung) entstehen. Die Funktion [random.gauss](https://docs.python.org/3.11/library/random.html#random.gauss) erzeugt dabei die Werte rund um einen Standardwert $\\mu$. Der Wert $\\mu$ ist in der Funktion `random.gauss` standardmässig auf $\\mu = 0$." - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "id": "1c705bcc-e0c0-44d5-a59a-e49a54dfcb77", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-535ba1d9d8974ead", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "x = [random.gauss() for _ in range(20)] # Hier werden die Zufallszahlen generiert\n", - "plt.plot(range(20), x)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "6cb70992-db57-4e3e-a88a-d4e27adf1307", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2d63ebf3cbf6b805", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Nun die Werte rund um $\\mu = 6$:" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "a6bce87e-b15c-41fd-ba38-ad75fb39f51b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-60aff446b4976944", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "x = [random.gauss(mu=6) for _ in range(20)] # Hier werden die Zufallszahlen generiert\n", - "plt.plot(range(20), x)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "9fcdb0dd-4478-482d-99fb-d846f216badd", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8f5026ab0971e642", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Gegeben sei die Liste `gaussians`; Setzen Sie den Seed des Zufallsgenerator auf den Wert `420` und füllen Sie die Liste `gaussians` mit `20` Elementen mittels der Funktion `random.gauss`. Dabei soll $\\mu = 50$ sein." - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "id": "91bea9ab-d14b-4cea-8fc0-bddb0c746d3f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f5899e4f04d1fb8a", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "gaussians = list()\n", - "# BEGIN SOLUTION\n", - "random.seed(420)\n", - "gaussians = [random.gauss(mu=50) for _ in range(20)]\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "id": "c47bf25f-ca5a-4b55-bd15-dbd0c0b62809", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-bcce24d15f74a12f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Visualisierung ihrer Lösung\n", - "plt.plot(range(len(gaussians)), gaussians)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "5f48c0c9-ecbc-4322-80ad-89cfd9371f5b", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-4614be8448c91fdc", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden ihre Lösungen getestet\n", - "assert len(gaussians) == 20\n", - "### BEGIN HIDDEN TESTS\n", - "random.seed(420)\n", - "assert gaussians == [random.gauss(mu=50) for _ in range(20)]\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "ec32f2e6-3bd4-4dee-8282-825af1d82787", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8e8fed104346eadf", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Pseudo Randomness\n", - "\n", - "Zufallszahlen in Computern werden über Formeln berechnet. Einer dieser Generatoren ist der _Linear Congruent Generator (LCG)_, dessen mathematische Grundlage leicht verdaulich ist.\n", - "\n", - "$$ X_{n+1} = (aX_n + c) \\;mod\\; m; \\quad n \\geq 0 $$\n", - "\n", - "Wenn $ c = 0 $ dann nennt man den Generator auch _Multiplicative Congruent Generator (MCG)_.\n", - "\n", - "Die Werte haben folgenden nutzen in der Funktion:\n", - "\n", - "- $X_n$ ist der Startwert oder seed\n", - "- $X_{n+1}$ ist der folgewert der im nächsten schritt für $X_n$ eingesetzt wird\n", - "- $a$ ist der Vorfaktor vom Startwert dieser wird skaliert, deshalb wird er skalar gennant\n", - "- $c$ ist das hinzuaddierte Offset\n", - "- $m$ ist der Restklassenring oder auch Modulus genannt" - ] - }, - { - "cell_type": "markdown", - "id": "6a7e3d5c-101d-4829-8d15-d463b0a584ff", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e192e7a8c3fd28d5", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe\n", - "\n", - "Schreibe einen _Linear Congruent Generator_ mit dem funktionsnamen lcg. " - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "id": "75b3086c-dec9-46a7-8f46-34ffdadbb6bf", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-94fcba89968e033d", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "def lcg(seed: int, scalar: int, modulus: int, offset: int) -> int:\n", - " ''' \n", - " Linear Congruential Generators\n", - "\n", - " X(n+1) = (a X(n) + c) mod m; n >= 0\n", - "\n", - " m > 0; \n", - " 0 <= a < m;\n", - " c > 0; a > 0\n", - "\n", - " '''\n", - " assert modulus > 0, \"Modulus must be greater than 0\"\n", - " assert 0 <= scalar and scalar < modulus, \"Scalar must be in range 0 <= a < m\"\n", - " assert seed >= 0, \"Seed must be greater than 0\"\n", - " return (scalar*seed+offset) % modulus\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "df92409c-6299-4d1d-bc5b-06a53301ab2b", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-abb6e32ca8dab869", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "3089810780120156248\n" - ] - } - ], - "source": [ - "# Hier werden ihre Lösungen getestet ...\n", - "print(lcg(3935559000370003845, 3203021881815356449, 2**64-1, 11742185885288659963))\n", - "### BEGIN HIDDEN TESTS\n", - "def lcg_test(seed: int, scalar: int, modulus: int, offset: int) -> int:\n", - " ''' \n", - " Linear Congruential Generators\n", - "\n", - " X(n+1) = (a X(n) + c) mod m; n >= 0\n", - "\n", - " m > 0; \n", - " 0 <= a < m;\n", - " c > 0; a > 0\n", - "\n", - " '''\n", - " assert modulus > 0, \"Modulus must be greater than 0\"\n", - " assert 0 <= scalar and scalar < modulus, \"Scalar must be in range 0 <= a < m\"\n", - " assert seed >= 0, \"Seed must be greater than 0\"\n", - " return (scalar*seed+offset) % modulus\n", - "\n", - "s = lcg(3935559000370003845, 3203021881815356449, 2**64-1, 11742185885288659963)\n", - "t = lcg_test(3935559000370003845, 3203021881815356449, 2**64-1, 11742185885288659963)\n", - "\n", - "assert s == t\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "90c4de8f-e3b8-4d23-bf17-9b5aa530edbf", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-6882494a5373136e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe\n", - "\n", - "Nutze die vorher geschriebene `lcg` Funktion, um einen `mcg` korrekt zu implementiert." - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "id": "262922a5-ccb8-41e5-a0b9-440317653ac3", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-09dc983805e666ec", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "def mcg(seed: int, scalar: int, modulus: int) -> int:\n", - " '''\n", - " Multiplicative Congruential Generator\n", - " or Lehmer Generator\n", - "\n", - " Just the same as lcg with the Property c=0 (offset = 0)\n", - " '''\n", - " return lcg(seed, scalar, modulus, 0)\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "d7ffef5c-d97f-410b-857d-4c8d7ad24bfd", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-d8973bd8652557a9", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "9794368968541047900\n" - ] - } - ], - "source": [ - "# Hier werden ihre Lösungen getestet\n", - "print(mcg(3935559000370003845, 3203021881815356449, 2**64-1))\n", - "### BEGIN HIDDEN TESTS\n", - "def lcg_test(seed: int, scalar: int, modulus: int, offset: int) -> int:\n", - " ''' \n", - " Linear Congruential Generators\n", - "\n", - " X(n+1) = (a X(n) + c) mod m; n >= 0\n", - "\n", - " m > 0; \n", - " 0 <= a < m;\n", - " c > 0; a > 0\n", - "\n", - " '''\n", - " assert modulus > 0, \"Modulus must be greater than 0\"\n", - " assert 0 <= scalar and scalar < modulus, \"Scalar must be in range 0 <= a < m\"\n", - " assert seed >= 0, \"Seed must be greater than 0\"\n", - " return (scalar*seed+offset) % modulus\n", - " \n", - "def mcg_test(seed: int, scalar: int, modulus: int) -> int:\n", - " '''\n", - " Multiplicative Congruential Generator\n", - " or Lehmer Generator\n", - "\n", - " Just the same as lcg with the Property c=0 (offset = 0)\n", - " '''\n", - " return lcg_test(seed, scalar, modulus, 0)\n", - "\n", - "s2 = mcg(3935559000370003845, 3203021881815356449, 2**64-1)\n", - "t2 = mcg_test(3935559000370003845, 3203021881815356449, 2**64-1)\n", - "\n", - "assert s2 == t2\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "2c029c46-f4a6-4fa7-93dd-f4585ee0d6e8", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e3049cbe7be08332", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Mittels Pythons Generator Syntax können wir einen einfachen Generator mit der vorangegangenen Aufgabe erstellen:" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "1d037d57-8641-49b3-b3cc-60bd64e12f36", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1cbf76ef6815788d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "def lcg_gen(seed: int, scalar: int, modulus: int, offset: int) -> int:\n", - " ''' \n", - " Linear Congruential Generators\n", - "\n", - " X(n+1) = (a X(n) + c) mod m; n >= 0\n", - "\n", - " m > 0; \n", - " 0 <= a < m;\n", - " c > 0; a > 0\n", - "\n", - " '''\n", - " assert modulus > 0, \"Modulus must be greater than 0\"\n", - " assert 0 <= scalar and scalar < modulus, \"Scalar must be in range 0 <= a < m\"\n", - "\n", - " while seed > 1:\n", - " seed = (scalar*seed+offset) % modulus\n", - " assert seed >= 0\n", - " yield seed" - ] - }, - { - "cell_type": "markdown", - "id": "2801d225-a6c2-409c-aac9-7161d0beec01", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b1c2720d7b6cae5f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Mit den magischen Werten (Woher diese kommen erfahren Sie im nächsten Kapitel) \n", - "\n", - "- seed = $3935559000370003845$\n", - "- scalar = $3203021881815356449$\n", - "- modulus = $2^{64}-1$\n", - "- offset = $11742185885288659963$\n", - "\n", - "lässt sich folgende Zufallsfolge erzeugen (Bitte Keine Angst vor großen Zahlen haben):" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "e1073b6e-9a40-48fd-a11d-03442c3045fb", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c915d2dee5c571e7", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1. LCG Zufallswert => 3089810780120156248\n", - "2. LCG Zufallswert => 8356396685252565260\n", - "3. LCG Zufallswert => 1921117399837525548\n", - "4. LCG Zufallswert => 14806858147081821235\n", - "5. LCG Zufallswert => 2557599628047639428\n", - "6. LCG Zufallswert => 16453652254840064460\n", - "7. LCG Zufallswert => 15995401842808378843\n", - "8. LCG Zufallswert => 681272290641816305\n", - "9. LCG Zufallswert => 10955466795170118648\n", - "10. LCG Zufallswert => 13714992071537968180\n" - ] - } - ], - "source": [ - "gen = lcg_gen(3935559000370003845, 3203021881815356449, 2**64-1, 11742185885288659963) # Generator definieren\n", - "for i in range(1, 11):\n", - " print(\"{}. LCG Zufallswert => {}\".format(i, next(gen))) " - ] - }, - { - "cell_type": "markdown", - "id": "47c6c8e6-4223-4936-a67e-b1242f9f5aed", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-6565f25687e7129b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Wenn wir diese einmal Visualisieren:" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "id": "708b40c4-7878-49af-a8a6-9a6204a5f83a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-75adf84e2d46024f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "gen = lcg_gen(3935559000370003845, 3203021881815356449, 2**64-1, 11742185885288659963) # Generator definieren\n", - "\n", - "n = 10 # Wie viele Zufallszahlen\n", - "lcgs = [next(gen) for _ in range(n)] # LCG Zufallszahlen\n", - "random.seed(42)\n", - "rands = [random.random()*1e19 for _ in range(n)] # Pythons Zufallszahlen + Skalierung\n", - "\n", - "plt.plot(range(len(lcgs)), lcgs, color='r', label='LCG')\n", - "plt.plot(range(len(rands)), rands, color='g', label='random.random')\n", - "plt.title(\"Vergleich Zufallszahlen LCG & Python Random\")\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "51e20ffc-9c08-46e6-b4c1-3cef6804c6d6", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-bc024d97d8babd60", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Wie aus der Grafik zu entnehmen folgen Beide Zufallsgeneratoren einer akkuraten Zufallsverteilung. \n", - "\n", - "Damit haben wir einen eigenständig einen Zufallsgenerator erstellt den wir nach unseren Belieben anpassen können. \n", - "\n", - "Kommen wir im nächsten Kapitel nun auf die (stand 2023) moderneste Familie der Zufallsgeneratoren." - ] - }, - { - "cell_type": "markdown", - "id": "8b778f85-7976-40f7-af83-09fb81e20a8c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-21bc2fd7ce86eaa8", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "---\n", - "\n", - "# A Family of Better Random Number Generators\n", - "\n", - "
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\n", - " Melissa E. O’Neill\n", - "

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Linear Congruent Generators zeichnen sich durch ihre Stabilität und Geschwindigkeit als Hervorragende Zufallsgeneratoren. Doch 2014 gelang Melissa E. O'Neil ein neuer durchbruch in der Konzeption von Pseudozufallsgeneratoren. Das Problem mit existierenden Zufallsgeneratoren ist entweder ihre Stabilität (Wie vorhersehbar die Zufallszahlen sind) oder ihrer Geschwindigkeit (Wie lange der Zufallsgenerator braucht um die nächste Zufallszahl zu errechnen).

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Ihr Durchbruch gelang indem Sie die Vorteile eines Linear Congruent Generators mit dem eines XorShift Generators verband. Dadurch erreichte Sie nicht nur eine Normalverteilung in den generierten Zufallszahlen (und eine damit einhergende Stabilität), Sie hatte auch eine Family von schnellen einfachen Algorithmen entwickeln. Diese nennen sich PCG - Permuted Congruential Generator.

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Die Implementierungsdetails lassen wir im nächsten Schritt aus, da diese sich nicht einfach in Python umzusetzen sind. Auf der Webseite pcg-random.org lassen sich implemtierungen für C & C++ finden. Als weiterführende Literatur ist PCG: A Family of Simple Fast Space-Efficient Statistically Good Algorithms for Random Number Generation - Melissa E. O’Neill als Literatur angegeben.

\n", - "
\n", - "
\n", - "\n", - "Zum Glück hat _Numpy_ eine Implementierung des _PCG_. Diese findet sich unter [Numpy PCG64](https://numpy.org/doc/stable/reference/random/bit_generators/pcg64.html)" - ] - }, - { - "cell_type": "markdown", - "id": "219946a9-88b6-409e-964a-a342932db73b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-41b305bbec0288ce", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Verwendung\n", - "\n", - "Um NumPys PCG implementation zu verwenden muss zuerst das NumPy Modul random importiert werden.\n", - "\n", - "Wir benötigen, wie in der Dokumentation beschrieben, nur die Funktionen `Generator, PCG64 & SeedSequence`." - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "id": "12d2e7bf-161e-42b5-9267-bf1965681fa7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2f9512ef29cb80c4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "from numpy.random import Generator, PCG64, SeedSequence" - ] - }, - { - "cell_type": "markdown", - "id": "7c528b83-9553-4350-9109-884a4706402e", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f8c8e7bc1524f45f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "- __Generator__: eine wrapper Funktion die einen `Bit Generator` (wie PCG64) entgegennimmt und daraus Zufallszahlen konzipiert.\n", - "\n", - "Eine Liste aller Numpy Bit Generatoren finden Sie in der Dokumentation unter [Bit Generatoren](https://numpy.org/doc/stable/reference/random/bit_generators/index.html).\n", - "\n", - "Alle Funktionen die bereits bekannt aus dem Kapitel zu Pythons Random Library sind, können mit dem Generator verwendet werden!\n", - " \n", - "- __PCG64__: der verwendete `Bit Generator`.\n", - "- __SeedSequence__: eine Funktion die verschiedene Zufällige Startwerte Generiert. Dabei wird sichergestellt, dass beim erstellen der `SeedSequence` mit gleichen Startwert immer der gleiche Output geliefert wird." - ] - }, - { - "cell_type": "markdown", - "id": "97a90f84-c40c-4f3b-9757-b0bb51ee77cf", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c5098307e1ba361c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe\n", - "\n", - "Definieren Sie eine Variable `sg`, welche eine `SeedSequence` mit dem Startwert `42` hat. Nutzen Sie die verlinkte Dokumentation [Numpy PCG64](https://numpy.org/doc/stable/reference/random/bit_generators/pcg64.html) als Referenz." - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "id": "5a03977d-40fc-4240-9798-d021dc7a751b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e8a43a6d3693907b", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "sg = SeedSequence(42)\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "id": "b26b54b4-f1ee-4755-844f-8cf146843ec5", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-2e31a0d8fd0aac43", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden ihre Lösungen getestet ...\n", - "assert isinstance(sg, SeedSequence)\n", - "assert sg.entropy == 42" - ] - }, - { - "cell_type": "markdown", - "id": "2803a09b-3e01-4928-862f-f78c2e923f8c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-fee790dabde97467", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Mit der `SeedSequence.spawn` Funktion können Sie im folgenden einen Generator nutzen. Die Funktion nimmt einen Parameter entgegen. Dieser teilt der Funktion mit, wie viele Zufallszahlen erzeugt werden sollen. Der Rückgabewert ist eine Liste über die Iteriert werden kann. Ein Beispiel:" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "id": "386dd1be-3a43-4648-8b14-950d52a11b17", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-134aaab222b656fa", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Sequenz 0: SeedSequence(\n", - " entropy=69,\n", - " spawn_key=(0,),\n", - ")\n", - "\n", - "Sequenz 1: SeedSequence(\n", - " entropy=69,\n", - " spawn_key=(1,),\n", - ")\n", - "\n", - "Sequenz 2: SeedSequence(\n", - " entropy=69,\n", - " spawn_key=(2,),\n", - ")\n", - "\n" - ] - } - ], - "source": [ - "for i, s in enumerate(SeedSequence(69).spawn(3)):\n", - " print(\"Sequenz {}: {}\\n\".format(i, s))" - ] - }, - { - "cell_type": "markdown", - "id": "a77a85af-d45f-469c-9488-59f6ed5a4fc7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0061578957a10bc2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Die einzelnen Sequenzen nutzen wir im folgenden als Input für den PCG64:" - ] - }, - { - "cell_type": "code", - "execution_count": 81, - "id": "67c0773d-8540-4223-9455-617ecc187870", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-9bcea16e80118785", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "seq = SeedSequence(69)\n", - "pcg = PCG64(seq.spawn(1)[0])\n", - "print(pcg)" - ] - }, - { - "cell_type": "markdown", - "id": "6d8904ea-768d-43bb-a2f8-24e7736ba889", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-9530aa102fe716a5", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Um daraus eine Zufallszahl zu erstellen benötigen Sie nur noch die Generator Funktion:" - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "id": "36cb2bb9-5685-430b-aa9c-3572ed5224fe", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-73351514a3bd2599", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "0.28914167495902166" - ] - }, - "execution_count": 86, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "gen = Generator(pcg)\n", - "gen.random()" - ] - }, - { - "cell_type": "markdown", - "id": "fc687570-043f-4e71-bd02-65c4a1031295", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ff6de24546886d7e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe\n", - "\n", - "Nutzen Sie ihre aus letzter Aufgabe erstellte `SeedSequence sg` und erzeugen Sie mittels `Generator` & `PCG64`, 10 Zufallszahlen in der vorgegebenen Liste `pcgs`.\n", - "Als Referenz schauen Sie gerne in das Beispiel der Dokumentation [Numpy PCG64](https://numpy.org/doc/stable/reference/random/bit_generators/pcg64.html)." - ] - }, - { - "cell_type": "code", - "execution_count": 90, - "id": "6a24d0d7-56da-4d9b-b497-2413a8c896ec", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0cac842816238f9b", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "[0.9167441575549085,\n", - " 0.4674907799518424,\n", - " 0.07123920291270869,\n", - " 0.7639328676507445,\n", - " 0.017567502091441867,\n", - " 0.25302055214458075,\n", - " 0.6361856125062569,\n", - " 0.0015791460415535141,\n", - " 0.7096566546463475,\n", - " 0.2983032265878607]" - ] - }, - "execution_count": 90, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pcgs = list()\n", - "# BEGIN SOLUTION\n", - "sg = SeedSequence(42)\n", - "for s in sg.spawn(10):\n", - " pcgs.append(Generator(PCG64(s)).random())\n", - "pcgs\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 91, - "id": "95aca16a-a704-4c1a-8a48-b764854bd63b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-02df0473f204f817", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Visualisierung ihrer Lösung\n", - "plt.plot(range(len(pcgs)), pcgs, color='r', label='PCG')\n", - "plt.title(\"PCG Random Numbers\")\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "id": "fec16481-85a1-4718-8ff5-a5400db85ca5", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-fd3c924c2929b92c", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden ihre Lösungen getestet\n", - "assert len(pcgs) == 10\n", - "### BEGIN HIDDEN TESTS\n", - "assert pcgs == [Generator(PCG64(s)).random() for s in SeedSequence(42).spawn(10)]\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "7d5c7255-9804-40d8-8709-e4c809dd12b7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b9c4e995c23c5967", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Simulation Verkehrsmodell\n", - "\n", - "Mit dem letzten Kapitel wollen wir eine reale Simulation des Verkehrsaufkommen einer Funkantenne Nachbilden. Dabei beziehen wir uns auf das Nachrichtentechnische Modell der Verkehrstheorie. \n", - "\n", - "Eine Erklärung:\n", - "\n", - "Verschiedene Teilnehmer nutzen einen Kanal an einer Funktantenne zu Unterschiedlichen Zeiten. Dabei wird die Belegungdauer oder Verkehrsmenge mit $Y$ beschrieben. Bezieht man diese Größe auf einen (Zeit)Dauer wird dies Angebot genannt und mit $A$ konnotiert. Die Einheit hierfür ist das [__Erlang__](https://de.wikipedia.org/wiki/Erlang_(Einheit)).\n", - "\n", - "Dabei beschreibt ein Erlang in der Praxis die Belegung eines Senders auf einem Kommunikationskanal für eine Stunde.\n", - "\n", - "Das Beispiel von Wikipedia umschreibt dies mit 1000 Gesprächen die jeweils 2 Minuten innerhalb einer Stunde dauern. Oder $$\\frac{1000 \\cdot 2 \\;\\text{min}}{60 \\;\\text{min}} = 33\\frac{1}{3}\\;\\text{Erl}$$\n", - "\n", - "Mittels Zufallszahlen können wir die Teilnehmer an der Antenne modellieren. Dazu nehmen wir als Referenz 1 Stunde. Der Wert der Zufallszahlen soll dann Sinngemäß die Auslastung für jede Minute in Prozent darstellen." - ] - }, - { - "cell_type": "markdown", - "id": "77ced0c5-9364-4ebc-84e4-da9c5d4a5663", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-cee3e9bba1efef06", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe - Zufallswerte generieren\n", - "\n", - "Nutzen Sie ihr Wissen aus vorangegangem Kapitel und füllen Sie die Liste `client` mit 60 zufälligen Werten aus einem PCG64. Nutzen Sie als Startwert `420` für die `SeedSequence`. " - ] - }, - { - "cell_type": "code", - "execution_count": 112, - "id": "2fdefdfc-68fd-4b4a-954b-62a6a8bb92d5", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1f4cc8b24b379755", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "clients = list()\n", - "# BEGIN SOLUTION\n", - "clients = [Generator(PCG64(s)).random() for s in SeedSequence(420).spawn(60)]\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 124, - "id": "db2aff39-dada-42bf-b0ac-b4503dd934dd", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-23031668cfe4f02d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Visualisierung ihrer Lösung\n", - "plt.plot(range(len(clients)), clients, color='r', label='Clients')\n", - "plt.title(\"Verkehrsaufkommen an einer Antenne (in % pro minute)\")\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 119, - "id": "bd6d44ae-7039-408f-ae2c-c1c1fac2670f", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-0b0f9c7e58266631", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden ihre Lösungen getestet\n", - "assert len(clients) == 60\n", - "### BEGIN HIDDEN TESTS\n", - "assert clients == [Generator(PCG64(s)).random() for s in SeedSequence(420).spawn(60)]\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "c6c6db2b-ebf4-4120-8b21-0b365649f03d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b531233e3e53a390", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe - Verkehrswert berechnen\n", - "\n", - "Der Verkehrswert berechnet sich mit $$y = \\frac{Y}{t}$$\n", - "\n", - "Dabei ist:\n", - "- $Y$ die Verkehrsmenge\n", - "- $t$ die Beobachtungsdauer (in minuten)\n", - "\n", - "Der Verkehrswert beschreibt die mittlere Nutzung pro Minute.\n", - "\n", - "Nutzen Sie die gegebene Formel und die Liste `clients` um den Verkehrswert zu berechnen. Speichern Sie das Ergebnis in der Variablen `y`." - ] - }, - { - "cell_type": "code", - "execution_count": 122, - "id": "6e75099e-4323-48a2-a1f7-37bd9ebc0a3b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-6aaff0962b39ecd4", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "0.5221268844976396" - ] - }, - "execution_count": 122, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "y = float()\n", - "# BEGIN SOLUTION\n", - "y = sum(clients)/len(clients)\n", - "# END SOLUTION\n", - "y" - ] - }, - { - "cell_type": "code", - "execution_count": 123, - "id": "8ed49831-157a-479a-8c63-5d641cf72ab8", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-1195f89b67e2abed", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden ihre Lösungen getestet\n", - "### BEGIN HIDDEN TESTS\n", - "assert y == 0.5221268844976396\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "369c0f47-49c9-4ae1-bc0d-e97c88f27288", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4f5da9b1a5c1552e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Plotten wir im folgenden den errechneten Verkehrswert über das simulierte Verkehrsaufkommen:" - ] - }, - { - "cell_type": "code", - "execution_count": 126, - "id": "363ddd24-8438-4d4a-8f06-f250c5822da7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-bf861fec9c51a479", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.plot(range(len(clients)), clients, color='r', label='Clients')\n", - "plt.plot(range(len(clients)), [y for _ in range(len(clients))], color='g', label='Verkehrswert')\n", - "plt.title(\"Verkehrsaufkommen an einer Antenne (in % pro minute)\")\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "b24dc8a1-71ad-415a-a33f-675fcc7c5d10", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-bfe9fce5b3a939dc", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Behalten Sie diese Simulation im Hinterkopf. In der Übung zur Matplotlib bauen wir diese weiter aus." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/api.html b/Material/wise_24_25/lernmaterial/api.html deleted file mode 100644 index 2238166..0000000 --- a/Material/wise_24_25/lernmaterial/api.html +++ /dev/null @@ -1,8661 +0,0 @@ - - - - - - - -Lösungen_api_datenanalyse slides - - - - - - - - - - - - - - - - - -
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z?YBRC|ITaHh=~5)+KD3Bu}8MAaOwq`HPiJW9WL^oqB_WR|iUpOF!pWJ@nQ0x9_g~RUbyLo5(*VO*AtQbCLhz{CwcthXiO@GTQKfkR1 caN3{$48gGum**SHN-+R|r>mdKI;Vst05{BF5dZ)H diff --git a/Material/wise_24_25/lernmaterial/image-and-data-processing/Image and Data Processing Exercise 4.ipynb b/Material/wise_24_25/lernmaterial/image-and-data-processing/Image and Data Processing Exercise 4.ipynb deleted file mode 100644 index 348cbbb..0000000 --- a/Material/wise_24_25/lernmaterial/image-and-data-processing/Image and Data Processing Exercise 4.ipynb +++ /dev/null @@ -1,1518 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "3a58e116-5086-4c94-8108-85679e1a9312", - "metadata": {}, - "source": [ - "# Probleme\n", - "\n", - "- Resourcen für die verwendten Bibliotheken einführen\n", - " - Matplotlib, OpenCV, Pandas\n", - "- Notebook verschönern\n", - "\n", - "- Notebook aufspalten in \"Image Processing\" & \"Data Processing\"pip install jupyterlab-vim\n", - "\n", - "\n", - "Erklären:\n", - "- Array \n", - "- Convolution\n", - "- CSV" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "81f850a1-0650-4ade-a5db-04f49f204dc0", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Collecting jupyterlab-vim\n", - " Downloading jupyterlab_vim-0.16.0-py3-none-any.whl (26 kB)\n", - "Installing collected packages: jupyterlab-vim\n", - "Successfully installed jupyterlab-vim-0.16.0\n", - "Note: you may need to restart the kernel to use updated packages.\n" - ] - } - ], - "source": [ - "pip install jupyterlab-vim" - ] - }, - { - "cell_type": "markdown", - "id": "8e010dba-b4aa-4c67-809b-cdf5b86b57d4", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0803e1c93de27028", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Image and Data Processing with Python\n", - "\n", - "This exercise aims at introducing processing of images and data with python via OpenCV and pandas libraries, respectively." - ] - }, - { - "cell_type": "markdown", - "id": "b54e5077-1cac-4b2d-91fb-961d61185c3f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-765af1c564b972d1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Image Processing - OpenCV\n", - "\n", - "The task of processing images, which can be achieved through different techniques, is referred to as image processing. The output after processing the image can be in the form of an image or a feature (corners, edges etc.) of the image that be used for further analysis or decision making, e.g. detecting a dog or a cat in the image.\n", - "\n", - "An image can be represented as a 2D function F(x,y), where x and y are the spatial coordinates. The amplitude of the function F at a specific value of x and y represents the intensity of the image (also referred to as pixel value) at those coordinates. Therefore, an image can be defined as an array of pixels arranged in columns and rows, where, the pixel provides information about the intensity and color. An image with x,y and z coordinates represents a 3D image, which is commonly referred to as an RGB image containing red, blue and green channels.\n", - "\n", - "OpenCV-Open Source Computer Vision- is a library that consist of 2000+ optimized algorithms for computer vision and machine learning that can be used in several ways for processing images, such as, \n", - "* Converting images from one color space to another, i.e., between RGB and HSV (Hue Saturation Value) or RGB and gray.\n", - "* Smoothing of images, like applying filters to images or blurring og images. \n", - "* Extracting foreground and background information from the images (via GrabCut algorithm)\n", - "* Image segmentation via watershed algorithm\n", - "\n", - "In this exercise, we will cover some basic image processing tasks. " - ] - }, - { - "cell_type": "markdown", - "id": "067e7a56-f944-43c3-98fa-b52d682a2ee7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-148ec1fab164a528", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "Firstly, as you might have come across, required packages should be imported. " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "6b80964d-8159-4646-9247-75144150cef7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5400665f5815eb17", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Defaulting to user installation because normal site-packages is not writeable\n", - "Requirement already satisfied: opencv-python in /home/sid/.local/lib/python3.10/site-packages (4.6.0.66)\n", - "Requirement already satisfied: numpy>=1.17.3 in /home/sid/.local/lib/python3.10/site-packages (from opencv-python) (1.23.5)\n" - ] - } - ], - "source": [ - "!pip install opencv-python" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "a237f0b7-f18c-420a-bcec-0af9bf0166e5", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e1bc4221601b473f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'cv2'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mcv2\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mcv\u001b[39;00m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m pyplot \u001b[38;5;28;01mas\u001b[39;00m plt\n", - "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'cv2'" - ] - } - ], - "source": [ - "import cv2 as cv\n", - "import numpy as np\n", - "from matplotlib import pyplot as plt\n", - "%matplotlib inline" - ] - }, - { - "cell_type": "markdown", - "id": "a072752d-b3b9-4a54-a288-a58134d74fe6", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3f2d4fc147a89f56", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "To process an image, the image must first be read from the local directory. OpenCV provides a function imread() that is used to load the image. If the image cannot be read (because of missing file, improper permissions, unsupported or invalid format) then this method returns an empty matrix.\n", - "\n", - "**Syntax**: cv2.imread(path, flag)\\\n", - "**Parameters:** \\\n", - "**path:** A string representing the path of the image to be read.\\\n", - "**flag:** It specifies the way in which image should be read. It’s default value is cv2.IMREAD_COLOR\\\n", - "**Return Value:** This method returns an image that is loaded from the specified file.\n", - "\n", - "The three types of flags are as follows:\n", - "\n", - "**cv2.IMREAD_COLOR:** It specifies to load a color image. Any transparency of image will be neglected. It is the default flag. Alternatively, we can pass integer value 1 for this flag.\\\n", - "**cv2.IMREAD_GRAYSCALE:** It specifies to load an image in grayscale mode. Alternatively, we can pass integer value 0 for this flag.\\\n", - "**cv2.IMREAD_UNCHANGED:** It specifies to load an image as such including alpha channel. Alternatively, we can pass integer value -1 for this flag." - ] - }, - { - "cell_type": "markdown", - "id": "0c5bde46-472f-4290-9dc8-6c4ce646a40c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8588e60318980b90", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Exercise 1\n", - "\n", - "Use the imread function to read an image in color and grayscale. The image is provided in folder with the name \"Fox.png\", taken from the source below. \\\n", - "[Image source: https://unsplash.com/photos/xUUZcpQlqpM] \\\n", - "Note: This image is used throughout the notebook for image processing tasks. " - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "cca7f730-9c65-4220-a695-6ab14f80a622", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c5ce8a7486a8ae87", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "file_name = 'Fox.png'\n", - "img_color = cv.imread(file_name, 1)\n", - "img_gray = cv.imread(file_name, 0)\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "e7fb3711-c6b3-48c5-81ee-c770fa097364", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-9cf299757db8b1f4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "Similarly, use the imshow function to display the image in color and grayscale. \n", - "\n", - "**Syntax:** cv2.imshow(window_name, image)\\\n", - "**Parameters:** \\\n", - "**window_name:** A string representing the name of the window in which image to be displayed. \\\n", - "**image:** It is the image that is to be displayed. \\\n", - "**Return Value:** It doesn’t returns anything. " - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "5ea56229-4cc6-4ebf-9ee3-61db5f91650b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5619fc21fff3d88b", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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u6HdlFR4m+9uHwqZhmaT6PP1bZX60qsx2pL8AnFMNsYxRnufR3fDeXtTeQRs0OBsOcycsGvowf6kXVt1sE/Jq2ddoi3uDR5ugBBqMr+dVMA2qmYdhAj0Hlp3GozoMLLLJb8Q5VTQPGuuZKm6xxRZbvLrxaBOUiZpmrHaZU9nM243U1DTj6HVxkfYb4/rg7NKGMPvhM6lz8sXCEq5GXdcsZuqZJwqhbl0/Dofl/Q4zqxfm66/Ou2Earvdo4ReXGK9kmPtSm9fNLPliW+WNFsRM8VW3aNN7OdN6Q5FTZoFbvyn3BOf9qr/f5e+lFGJZ3WdJe1B9XZTnvPYh57UnOa/fkLPYd6xzHuvUE9NPH8/GLe5T3XdMCJvZMT0eBGVyTMPxfP4Hj6b7M/HvxpLez4uE62m1Y19FzNc1L2yaL9fkm60pvMo+Y2H91d9T7ovniNSi53dqB9TQiXPd2mWFI1mZvfSNd3CN46am5i/yovoXVvCY4XE/vy1ezXh4VV0zaggaVBNr1DFffr6uzfGIE5TVuFdfm+etd8YQTdQDEbKh/kVSnKWP0KqJfEV4HUnT0muxJOnUq1o9y42vcAPhOjtWkdllceuwo03ZUxONXCfvo4h1+v+on+MW9xvrb/i3RTM2eS9XfepWuRokLZsq5x97gvLQYl7ws+aYHEIgzOxUyCNtkHHKnmaTufxcOKsI5l6Th/NO4I/Cw7AlIFts8fChiYDU45aVm817UVxxS1A2QGg4ijj9BbzpEHzKH8giHxoLPu7HZh+bPRfz6oup7UWdMEztRiAIMe/Re87mpNapJVjUz/pX0MVJv+7BhBhmD6P3y/rFE0ysZap3V4zVN0tWb8R7uLi/F38m4tRg8rCauDTq1B9APzbFWZ/pjf28rLQjuLirddF+R86y58yiuPV9pMS3re61dtaDbpOqgobwbP5pc/Ph2XLz3nqb7Dzm882XaWqj3v6sbUgVNxFT149X27lsah+zLN+6eCwJyirtV9SobDYK+7GpQIOqoTa/T9LOM8bX7Thm6mlQBS3qIywbDDcT24T6lBkCQchTpQOhZri7nKB5Zq/ZxeMsKpyztRJpSKzPBUsIHoRGADpYpJRYoSBIBD6KopfUuTBNzPw5Z68f5fJTzNs73efm7xHmO/goULBHBXVX/OOJfZnqlgVx9bRl9VELLyq3SdqmmJ7T/LsSaulnaW0ZUVxFbl5FRrIRi+wygmgwyIwFztjQhvEXgXU1EXOcY/WX2qpJvIoP44k4TIiXF2LmNZrKV8Sp7T/Wav6e4KwqnNUYf8RMXu8AwgewljIfIZWmLEZol9PZ2UHoNkGZGs1bcYGWdvVeq5Eeipu3Ge6FgOycq+zOjtPS2Nnw/cfjZd/RpMaYj6+HmctPQ75Fx031rZt3k/rXzb/o032ze7uup9n5fFsJSgMWPW73q91N05Zj1aS7SjKyzlWIXHs8mQoxJikVPame6yBOf78KZBV1rwazB8EQlzfpAwTnwJb0j4/46le/wo1XXuGlr3yR11zp8trXfw3PvPnt6O4+vhK5yodsft9iFuuPo+t+7S7KNx+/fTDuHR7ta3ta+nE6vCjPJqPxqjoa/16QW/smPBYEZamPEsHEPmOd/DO+RE4ZZCzOJ+YMV6c3cG4/HNb1pyKrusddEJPw7P46zemn7Qqay9fPcxIvAuBBKAICIQQuBAShtrpIVOfpwQekkAjvkULia/qb5kt4mljN6m0XE635852Pn57vfLk5MrXCi+fi9Hg9fPCxdz6QDwe88sIL/NanP8Vvfea3yEcDnjposeM63E4El598LXvtLlKqmrTpbIjUcbnYedaHy6ZtLX527jcuerA7XV0TcZh/9urv2iKSsbLlSb7mPqyLixP/PzgJUXM/1o2vX4Pma9l0jc4+gV7kHkBL7TPm/k6O59tbUF9oiFsUv0iiMZ93oU1KQ19m6lnSVgiBsMEz/FgQlHUxL6S7PziLquFBs/3xl74keIHzHkLAKEkIbmoQqiSIqNcNQiGEJPhFpG6z6/CgB87FqAzSqhdu0Ovzx3/0RX75o7/AC1/+ElJKlIBuKnjycoduAkZ5BJ5opCPOrmLc4oKwXL150bfn4ty918l7EzzLCUyTiqApbd2+nOV8mqRG60iXYtzstWw+l01UUhd1b9aRcDSl1eOWSSzg4gn7ebCJsXIIgUoTzqZz26uDoIj46o5NpO7P9FC3flk2OZ+FwNxLRPGPFJpgA3iPHQ7oHd1l0DvCFkO00XT39rl05SombeOEJASJF4IgQqMPl8cGAaSUeO+xRcHnfuez/OIv/AJ3b90k0xqpJCIUHOymHOyk7B3ssLe7ixWSc2+jvMUaWDaJP+4XfxWBqY9+85P7aZXt6brn88/IpVeUb6qjqZ5V8Q831iUnm3qT3dRz7SY4T93r5a/u44R1rX9fH1uCMu8FFU6/no/e438f4QMieE7u3ua3PvUJPv87v0neP+LKpRatVoveoKCzf5W3vv1P8dqv/TqynV28kARRKSGabsBjguAco/6AL3zu8/zPX/goN196BSU8OmsTvKVl4Mp+i1YquHRpF2k0FglCVfYnj/tEucUWW6yDTVVGD3oLgYX5FxjE1lXjc1nXQuMil2X42Mc+xl/6S3+Jp556CiEEP/MzP3Oq0z/6oz/Kk08+SavV4t3vfjdf+MIXZvLcuXOH7/me72F3d5f9/X2+7/u+j16vt2lXGGuzQu2YZR+pIhIXXyd0glodzeH6uc1UVjueXXu+ot9zjLUp3BTf3I/FdS4rv+xhFDI+Fv3Du/zSz/1/+crvfZKndku+4XUt3vRUwtdc0TzZcfRe+gIf+9n/D//5//x/80e/8xtIO0KEgCQuvg1+KnIOhImob9l5rouzllsHorqHY33pxGQ4BIJzHB/e5dO//uv87Ef+K7dvvEyiJJlJcNbibc5+N+XapS5vfsPTPPmap3EkURW25pfDqnMLM/+x8DfNezp+E6x7r+bzLfyt+R9Lzq1RVB6Y3reG3/3Gpu3f6/zL6olY//k8HTf7m5+QpvFnrX/5uTalh3E8s89MWJQ/zD1zG4Rp6Ne51UYbPAPrlt+0ztnj+Xs4tasKTO97Y3gct+EItDFB6ff7vO1tb+PDH/5wY/pP/MRP8C/+xb/gp37qp/jEJz5Bp9PhPe95D6PRaJLne77ne/jd3/1dfv7nf56PfOQjfOxjH+P7v//7N+1KPOEx6WD6lzU+3ufLLQoHIRbMK4J4+SRT0Wr9+OHDsheovsmgdZ6yKPjMJ3+N4vYf881fu8//8Y5n+d+/+Rn+5Jsu83Wv6/L2tzzBN73pgDe9xiB6X+b3Pv7f+fVf+h+4Ise7WK8UtQGieljjstzlD+kDtT8ZP1QTxPsZfMAVJbdeucEnP/5rfPQXfp47t29B8CRGYcsSXxYY4egaEOUJe3ttZLaHFS0AZHBx2c85u+drv9lnde5ZbnieHyTm+77yt+TcJudz6pzuPxF5FCGEaHjP6mPa/G+dcU3M/TYpuxibTPRNZGQ+fT7fIuK7SXhVDy9KRXNRY+O6RGV6XI2DIR5Pw9O/ARFXNTaFq0cgjgHrn//GKp7v+I7v4Du+4zsWntBP/uRP8iM/8iP85b/8lwH49//+33Pt2jV+5md+hu/+7u/m93//9/m5n/s5fv3Xf513vOMdAPzLf/kv+Qt/4S/wz/7ZP+Opp57atEuvSoRwsbsrjyECKA9/9IXP8bnf/jW+6WsOePrJHTLjUQKSNKOrFbsdz7UrO9w9OebFA8GN2z0+96mPYa3gnX/2/w5ZG4RABIcIAU+0wdiUQd93iPrB9NPPFiUvfvUFfuF//A++/MUvcXx8jMDRSlOEFAjhkcpz7UqHZ693uXypS9I5oOcNTgrE+Cvk8dV8PXZ4mIwSX6143O7Bgz+fWePjs3RnqTHsinybnv/GEpRl+NKXvsTLL7/Mu9/97knc3t4e73rXu/j4xz8OwMc//nH29/cn5ATg3e9+N1JKPvGJTzTWm+c5x8fHM7/7g4fNgHUW9+ph93nJ53/zUzy5n/Ds9S67bU3WapGkHVzQuCCRUtFpJbz2ySu87U3P8ronWrxmx/Olz/xPfuOXfw436k3YsqBEYmOfhZjdS+ghxFhwG3wA57GjnD/6gy/ws//1I/z+Z3+PYphTjnIkYF1JYQsClkTDlb2UP/Hm67z5za9Hti4zJKuRkgdP0JZ9OS5SnVxU/Vts8WrG/Scn85JgSV2yNSP9COM+1suJWtz6WERMFhGZZbhQI9mXX34ZgGvXrs3EX7t2bZL28ssvc/Xq1dlOaM3BwcEkzzw+9KEP8WM/9mNn6lNd0jB7PF5OuIiETEVa835HFvk/mW8LZpe8LcrbFD7vuZ6jFo5uvcKNr3yRP/X1++xkEiEUeQ4+eLQ2eO8wSuPQSAFZGviaZ6+wv9fmSy/e4uTGb/HFz2R8zTu+DZlkhCCrp9wTgkSscDW71D5mlQ+XBfFN17te5zRdEPXJnmAto+GQ3/3s7/CrH/tVXnrhRYKz5KUF71AiITEJITi08Oxkmid2Dc9c3+X6U0/xim1RVOodEaabPC7q86LrsCzfOvf81PVckl+EdcjEghzL7L8uDFN1wf3Q8W9az73wujpT3/xzPpe3nrqpGH+d9LPaNaysY5o4G6bhmZrPE07T/k3sQVad06yNzvK9ds7T7mw98/WvOp7OW7N9X68v0/dqTCLq8VNiccpeZ8HfRXigEpR7hQ9+8IMcHR1Nfs8//3yVMs8Q5+OW5TnNKGfDD9dX/r20ywgh4L2vjj0vPf95ru55vubJfVqJ5PbdY2ww6KwL2lCGuL9MGQT9wuKlZHcn43VPdvmTbzrgm581uFc+y1d/71NQOiBFYOIVFf5scsV7jMnLFzy+LPF5wSsvvsjH/ucv8ku/8FFeefGrBFcigifYkkQrjFKkxiCDJ5Weq7uGZ652efo11wi6y8BnOGkmxGd2GH24nq8xVtl8jO20Fv22OB8WSZ6apFBNb9GicsukWhch5VraRs2+bVG/5uuphxe1tSzPajTNC6fTZyfqqc1Fc7iprml48gG0sA9NdjvrHi/HOjYwTSSjyTB5HZJyFmlJEy5UgnL9+nUAXnnlFZ588slJ/CuvvMI3fdM3TfLcuHFjppy1ljt37kzKzyNNU9I0bUiZvzmbkJQt5hGJiiMf3OCtb7jMU0+00SbhTu8mX/zqC+zv7WISSWI0ShtUEBidIpWnlRp0yEiN4ondAmMKfvP3fxUZEp79uncgjAHpK+nJvePFTZKTpvh6/hACUsp4/taSDwb88Ze+xKc++Qm+9Ed/xLDfJ4RAno+wpUUriZIa7x3BlWhhuXop4Z1f/wzf8vY3cOngCV7JO+Skk8ctSk8CywczOP9U8bBjfpDeYhXO+jSsU+5+PWnnJxQXgfq4M34X54/n05vSmlCXQMzIsZaEm9LuLTaReCyzIVlld7KI0Gxqh3KhM8XrX/96rl+/zkc/+tFJ3PHxMZ/4xCd47rnnAHjuuec4PDzk05/+9CTPL/7iL+K9513vetdFdmeLDTCeoAeDPsd3X+bKnuHKXgstBUiNUAl56chzh/cCgsR7gRCaEBSFE3iZoFtdTJrypmd2+b+9eZcvfeq/86XPfZKyHFYSikWP3Oyy2fOg/iKseinGqxlCCJRlyY1XbvC/fumX+P/9t4/wxT/4A1yeI7xHSYkUAussQgq8s0igLEYoCi7vKr7hTU/wmutdvEwY2CQuLw4e6autFkVAhvuiB9liiy22mMEyMrEO4VhGTpYRkmV5V2FjCUqv1+MP//APJ+EvfelLfOYzn+Hg4IBnn32WH/qhH+If/+N/zBvf+EZe//rX8w//4T/kqaee4ru+67sAeMtb3sKf//N/nr/9t/82P/VTP0VZlrz//e/nu7/7u8+0gqdJB79ML78oPyy2V9ik/U3a3rTsGKdFhZMUQqirqdcJx3pdiPvo3H3pJTJydtuXOOkN6OUCUAhl2Nk9YLed0soUSsJoOGQ0tBgFJBCCQxtot3dI7YDXHEje/S3P8JFf/wWCMjzztV+PaXWqD43qwaWySQmVikmMlyJX/Yt/GO8/E0L9+0OA8IjqPMY1EgI+CISQEFzcN0fO6YtF9U8IuLJEAi89/zy/9iu/wuc/+1kUAZwnOIcUYMsCW+S02xmtLCVYi9ICESzPXOvw7m/9Bt7wzBVaWYueVfRKhZcqkh+qb6VQ+UIRzYNB871f/RyuV8/i/Kvae1hsmu+1zcnK2hdmqKnvwlx4eYc2a5/Nvng3qqvB9mNRvefp56bxp/MtDs+mzdtTNNstbXLNzmtrs869WzXpr1vPOnWepb1VJGUT9c862JigfOpTn+LP/tk/Owl/4AMfAOB7v/d7+Xf/7t/xd//u36Xf7/P93//9HB4e8qf/9J/m537u58iybFLmP/yH/8D73/9+/tyf+3NIKXnve9/Lv/gX/2LTrryKsUpNsEzFBWNrgYCs5kqHFwrhPXe++kUuJYErB/sMcssf/fFL3Ol7RNLi7p07GHYoRgLnHa1WQpqlaAXO5YyspSMTvFaQdNAMuNYNvGHf8Vu//BGGg5I3vf2bUSZlvG1etO0KiOBACEKQFS2J3mg9oZrk4zmIUDmBE+PNFMfWD5IQPD54sAGUREmBtw4bSrRJYlveI6RGCKJjtbLg5O5dbr78Mp/6vz7BH/zB5xkNh+x22xAcwZdYW1KUFkEgURKjJUIZyrJkLwu85bX7vOW1+7RTA2qX45Fk6BVBVgYbYtxvscB3x6J723T/7oelx6rn53HG4hu0nHRM7Szq4fka6jnWHaYvbi+fxVhW86pW76VAsL6ooRY71/oiw+S6KuXxxSq1yqK0ZeWXlVlFvC6KnMAZCMq3fdu3LW1ECMGP//iP8+M//uML8xwcHPDTP/3Tmza9EerSiEX2Bw8/VpOPTaQ9s3XEwVIQEEIRkNj8hBsvfpE/8WRKmiSUFkyaMbhzl3ww4tqVA6RWcWIPASk1eVGSdFKUThFB4RFYJykFKKlom4J3vvkqzt/idz/1P7h0ZZ9LT72eJE2RIaDUePCRiCBQIUR3+RObDaJ0RUBUD1USiVDdVwHee+R4grCOsixRCcjgcWVOCJ6gDATF2FGct45yOODF55/nU5/4v3jp+ecZDfrY0RARAs5a8JbgS4oyp7IhpixKpJYEZ+kkgtdd7/CGp/Y52OuQtXexMiV3CoRGjCVAMJGabLHFFquxnHA8+jirymNZPYvi1rE3Wda3VWqes0hR1sVjuxcPnHXyvp9Y9KW6XEIS72/z8um1UC1Jm0yf1de9zXsk9HnNteuEELh7eIT1UDpPf5iTl5beYIi3Du8dRZHzxOVLJElKaiTBF+AdUkbJh1Ip0gee2JX8729/hvCZr/DFT/0Pnnzrn+Y1b3gryiSEYFFS4IREBoHAI8R0X9YQ4gojIagkKTElPuQe4R3OOpAegsfZHFuMUDKSHDvqgZRgDEEllarFkQ8H/OHnfp9f//iv8cKXv4wIDqVklAb5QFHkKBn9uIQAZelJEo1JDEoqbDHgcjflW77had759a+j3cpQSYeTUlE4gxemkvLEfowdtZ1fX1IjbgvTt3g0sOpevprx6rg2F0VOVqlcFpVZRhoeNDmBx4SgjCfoTSfqZbYnyyQwTbYjs+nTeWh+XoppUwIyDdfy18+hfkOFONP0M98/ESp7DBFlKILop+T49stc6gj2OglGSYwx9AdHlNZzfDJEq0OG/SFXDnZpZZorV65wsL9LKzNkiaQsBMVoiC0LvHQIY5CyhdGOHV3yf7zz9XzuS0f85m//Ckopnnj2TSitMTpuMmi9Q3qPShQTSQmB4Cv1D0QDVQL4gCQQQol3FoUi2BJhR1AOUToQnCfkA4ROwGd4rwke8v4Jv/s7v83v/MZvcnT7Jt7ltDKDkoJ+v6QYWZwKdLttnBN4X8maQnTfj83ZSTzv+LrrfOvb38DVK12SVgd0RplripDghJoOr2GqHpi/38vu03z89DFYbts+PwZchH+dTXAvVRKL6ozv/6rSq2xDll/38yJWt776rLn9polk3fabM64+z6YVLvV2m1QsiwjGsvj5uhapyaqjNU78PHYjm9iAnNfO4yz92yTfpv1bRk42Uek01rmVoETUB+Z7J0lZVO/8JFIjIbXj+de1eSg4nXfV8bKzjRyoyinAhQDecXznJld2U2QocbYgTVN2dnZIjwqkUNy6fcLd2yd02i2eun6Vne4OaWLwtsDJqPoRUhJQWOcQpSdRitKDkI79juKbvvYKg/wWv/OpX0Rpzc7lJ6HVQiqFd46ABBsQCqRUeO/wZRllSlLiRLR/UUKgRUAKR/AFMkh8MUDZIWrQR4SCIi/BW0SSQZFEj8SHx/zhH3yB3/qNT3N85w6plrQSQzs1BO8wElITDVm1EjgnSZMUKS1agZGOTFm+6Y1P8Nw3Psu1Sy2UMWBa5F6Se0VBihNqaj8zuSGr7szjgXtlK7Gs3jC+yI0koMpDlfbI3oJF9jHLJvQ6ppt3nq43sGhRpxDz135d245FfV1OPF6tWEVkNklvDk+5wVgKPyXNqwnJRUhRxhLxdfFYE5R7B0Hzy7z5yDf/uq47hdXzLTpeVnZq1CeQUmLLIYOTu7xur4MSccmt9x5vS5SENEm4deeQPC94zVOXQUisdfR7ffZ3W2it8c5jnaO0kOgMQcA5i5CeEAKpMrRSzze98TK3736BFz77K7zu659D7l9BaoP3AWMSXClQSUKSJGAtvhhFyYWUBCHwRUGiJUp4slSi/AgZPDIU2PIY5Qe43gBKS54PSVtdrCt48eVb/PGXn+fLX/4yYjRkry1pZynOikg+dIb0Jf1hjrUl+zsteoMCnylGoyHtlqKTCa60DX/uW97C17/xKZJEI00LZMqwgFEpKUI0kJ1ITcaSr1cHP7lvWCRx2mIRlhGch/sarpp8V+V/2HFeac0mKpW65GsqDVtMSJaRkkUEZRlp2eTebAnKqxSROMcBywePtSXHR4e4LCc4RVASKTyEkmLU487tI4ajEp0qXICjo2O0CFze73B8fIKzJUliMElClkqEDzhvKWyJLUfxVXCSLFXsd+DPvfP1fOr3X+bOl38LnnkrrZ19iqJEtNrRW20xglaGBHw+ABEQSsVVusUI6QRaeYwUqFDiyhwTSjJ6DHyf/qiMUpX+CUpbhv27HD7/FdSgx6WkxBtBkrZRSuI84B1ZYmibNsd9gUn3SNI23h4yKhy7Hc1TT16C4pC3f+11XnetSyuVqCRDJRleSILQOJXivcaJgMBDUNPrXa1MesjngkcOE5VrePgn2i3Oj8eNnNRxVinK6noXt3UWcnIeqcqrmqBMBquGY2BiqzI+biofbT1qOu3qC3g8/om5+k6XrT08c8Yo44F0WvVp25n6DVzXb0rTuU76Qq3PQlTeXGftYIp8hB0NkEGQ5wW+DPSGDiE1ly8/Qb8AxyEOzUlvwNHJCU9c3iX4QECSpBlKC4zRZFqAD4SgCUEyGgp86SitRymFSTxXDxK+9U88w6f/4DaHL3+etnkTsnT4MCTolNwGQtHBKPDFKNqeBIkPAVf02OmmZAp06dAi0BsdIUSJUY69lieUQ3q9IW54gjMWbOByq2RHCnbSFOsCKjHkRUkIirIo6bYULaVoJRnolNuHvbhLMSVXD3ZpyyHPPr3LO77+WZ446CC1QiYJQsZVO0GmeJkihIrO2Wo2QxO13lgLsQDrmMDOv+Dn83vS0MZDIpFo/PpblPeC6r9IPKr1XzQBWK2aO3vd65ZZ1s5q1cjmEo1VfWskHxDHh5rGrl68Ob1WNiz5WycI8WC27Xo7YfqblKkqmh5z6ngat77EZRUeO4JyUairQWaWiwaWrsRYZFNyPzj9DEmJEZO+1p7pWRuUKlsxzPHFkHbWxfuS4/6I4xHcuHmCSNooKVDCc3w4otcuufLEFfb3unSzhLgG1yKFQ8uAlhJtFEJqipEnmJSRHYIQWA8ut6hEsJsJ3v61l/jU519CDboomZKFhN5A4EeCfHCCVwGtHCoxDAcFQiiEG6LSFkI4tAKFwLghaQL4klYiCRkMjwbokFP279LKMkLqGfiCtlEUzsfVOiJeFW8UWQKZUGRa0isERV4QguX69X2e2NVcyQr+zNvfwLPXd8haCUKZatBQBGEYlTDIHT4IZOW7JVR2PgIYO5FdZuK6SgbwapYRnHqH5t/DV+uFuY9YNLmsMuy+SKzakPFebNh4EVhGbgJMDbjrNj/j46Y4pu/E5G84/bdR+kJD/JgBzdijzNdxmtTMEpYtQdniQhGi0zJfsLPTot1JUS6vXLtHW5Rbt14idx4hJK993ZO87RvfzO7uHj54nC3IjEZphTEJiVIEH6pVNx6dpJRlSeniUmGlNcGBLR2KwH475etfd5nnb76ASjrs7z4B1uJsybDnCUpihSckBmctWWYglDAaxp2EC4cLAhMcGoX3FhUkqYJupsEbisKifIHyOR0DCMlgZCmFRwiHMZCYlMI6isLjnGDQHyKD41JH88anL9HROU/ut7hy0KHdaqOUQeoEpaMPmMIprBMEop1MHHAaCMWraBJddzLbYovHHavUNXX6vSzvQpITxEpisOhvqDGNJtXMKqIRj/0aeRafwyJsCcqrHvFhkVJgEkOaGpSzJCWUxYCyLBiNhowcIBX9Qc6nf+Nz3Lq5x9PXujz71BX2uxk7JkObBKV0lOSEgLUF1nmCUAQhuXX7NlmastNOEF6SaoF2I65dynCl5fbdYxLb4SCFDvDCyS0y1Y5qpKEjU5AGjVES8gFOR5fzAUUIAiUSlAxoCVp4DvY6GCU4PumhpKeUDqmA4Bj6ESJopC/RHhJhGBY5o5GjKKKn2ZaB173mEpeSnEsdwetfc4mdtkEIWUlHJB6F9ZLCCrzQIE3N2eu9mYjnJXTzr/uDmv6bhp2mvq0/PK3pMn6Le45FqovHiWxOzrB6SOvhRWqX03Gnn9kZKUdN7TLJG+byUDMDOMVhpo1FKQinVThrkJr5vCwgI8vIxibSklk1UWN3GvFIE5SZh2KizVh0fDqtHge1+AcgR1/3ha+rcc7ajhBRnDh+lULwGGPQypCYlE4KeTEk0YKDS/vcPOwTrGcwzDnp51gLo3xIf7CLC/A1z1xDpRmFzQl+SCvVGCXIWhk6SXA+4BAok9AbjGhlmtKDzS2ZkbS1YbedcPvWIcHm7GYJNvX4fYlUjtEgJwTQWpDqgLOebpqhfMFgOMR5cAiEaNHJErRSSAFZluCcJYRWJDnekKWGfu8EJT15EffgyQcDbKniufkUYyRdKbmyt88bn71MGN3ldU89wWuuXUZKCCJ60VU6QemEIA1Cp9HXSiHHruQaplZRDUazKZuKx2fskGKBeguVF94l5Zemnk88H2Zqb7DxmvyzCPNlLu5FvGix/+NY31n7sEm5VXYcm9Q7r7YYH4S5yJlawvwjOFXETwiCCLW8NXX4HMWe4Q8z81GYOx6r2uNxzQpxGjcjvZivqy4hmTuXCcdYfF1XSlc2lJyczlOd3RwRmT1+1UlQ4ldsPJoOjouO6+H5PJwKP9gvg8UkZNkEsF6fAwERfJzIApNdiaU0BC+RCnbaCTudjLv9Pp12i97ohCRJUSNLXkJ/JLC0uHtScPPuCUVRcrC3S6fdwjqLFBLv4wMrtabV7tAfjNDGk+cFigQtoBCOjhTs7GTs7WYoUSJ8oJMkiP0UIQQnIhCcQCmJUoHCOoQvkUEDHu9dNfEl5MUIW6poVOujd9h2K0VKSaeTkiYa50aYoaYcjAheYm1ABotJUtKkQ5a1GOUFVy/vcnlHcjzKuXqwRyvLQMSdn4VSSGUQyuBQeKGwQWAD+BAm9iazd+TeyzvOy60vZop8fL6qXw04i83GJh9J98MmpE7RQ+0tqBOBad65t2Ri0zEnKpkUqOUPoTGtSS2z7HjduEWSq1Wqk1VqovljUTtej5AsJzSL2gmh+dNtER5pgjJHJGcMUpuO6+H5PCwpc/8hWG5KuYqkrHCEE6ASo0Rm6wMnxycURUGeS1pdTV7k7LRT8EdkiaHTbjM8KnAuELzkhZfuIqWjlT6JdYF2q4sUcWdirTWBgPcBa0v6/QFlaXHWIYREInClQyhIjKZ0nna7zWueOqDf74P3eC9otwxKCYJV2NJXnmMdJpOEUCIDdLIEBwxHI5QI4D1SKYK1SCkxRhOCJ0tTWq0U7wo67Q6d3PPCjWNGeUBrScsorhxcIk1btFsGo3e4vNel6B+y89QTdHe6xBVQ440LKxVP0ASpcUFhvSL2kqlxcm0lz5T4LiOWgYuiCYtwvtqb+r/FFo8nLopYLSMMTXHrpK1S58wTh6Yyi+pcl6AsS1907P2rhKBscVYIQhDVHBoZba9/AniEjB5U26nhaFiwt9Pl5lFOmiYkSUBQ4rwnELh7POD23ROG+WWK0rG300EnGikC7SwjBEciU/b3NYd37yKE4PjkhM7lHUxicGWJVCnD3OPDiE67hS+HOAc+WKRUJIlidyfFFR7vwHqL9wWu9ChEJEVIMqPJTPRGO8pHGJOglKIsLVIKWllKYhROGlpZi50OZMkho1GO1obuTou9bkZmJDsdze5Oi0QG8qDo7OyitUKIuJ5LKY0y0UAWafAhGshaT/SpIpiQmPH13mKLLR4t3AupzzoEZFXeZYRl/u8mKp5VEpRlda5bbp4wrcIjT1BCWOwLZNVmeuMLtWn5ermmOiLEzP4gdZuY+XCTjcz8TVy2f8vpvk19ncy2N0aUzoSJpMZj0oyhSpA6JRBX7LSzlL1uYKed0C8FUlqEElWReH69/oBRYSmd4/D4EKE6JErSzjK0jvYew2Gf4WhIlqawu0NRlnQ7baxzOCSldThf0Om0aLXaDPp9jIkrcnCSJDGg407CBg0ehozIUk1/MMLoFB8ciZSoNKW0JZgQSQUBJwNSMHGx3G5nDHPLE/tdvPPs7nW5fGmHbkuTGLiy3yJLNMVoQGI03W4XBPgAxiQIVf2kqQx0JaUL5KXDeUGQanrBw1TMvGoPnum9bsw284wszrfOnjTL8bjYPd6LCWZFi9Xf5ff5rCqPRcaXdWx662Ymv3EFtdMI9VNa0eXm5PXPc9HZhcm/YiZTaOjYquu6iAQsy7dumXXLrSsdacq7DuFYp41Tx2Fsjzh9ylZJTpryjOPHY+0y0rIOHnmC8vBiXhS+TKw/byR5EZPE4r2AZBAEEeIvgHMOrROGeeD2ScFrLrVJMkUrlFy5JDke7nPz5CbOB5RSKOVptTSX9tu0O21u3b7LTqb4ujc+TbuVkUhFnucopeh0unS7bXZ3urzy4ksMesekxjAcjgAYjqJ0RkjBYDhkr9OmGPRQwoJUKAHWebzzSCXjfjylxSQahIcQ7VF8WeDKHKUlzjnKPEfhERISLQl4ytKjpCBLFd1OwpWDDkUx4NoTe2SpQSvIEkEn0wgCI+/odLsYreILJw3IJO7CLBRIMSGazoPzjvhKSTjXPVy+GWDTPb1YPCYM5THDqWF9/jadg49NigpRM7cIs6YXDU0u7Mu43nA6WyNBE/NEY7be03OaqP2pM6n7TUqXE4/541XlNgmvIjGrwo1SjnF9K8jJImKyjjRluxfPFksx/vIQAYL3BB+4c/s2x70B/XwXi6CVKBIPXZnQ3SkJwZGPSo6OCmyAVqcFMkRDVCkJBAb9IfudNqZrkAK0ijYpRWE5Pj5GCEGWtUg0aCUoihxrC4QI7O50ECIQgqfVSimKEVprlASBpHAO5z2JMpQhkCQJg94QJSXelQRfUhZDRCX9kQjKwiEE6FYKCMrRANNqAYEsUaSJ5NJeh27LkCSafNSnne2gJDjrSYwhy1K89wQp0EqBjBY+WkmkknghCM6DkCglIWwn9/uFRQP/g1v6uqzdeYu3Lc6D+y8da0ZTPzaVoiwrt4pgLMq7qvwyacoygrLOr6mdJonKOtgSlFchooQmfrF477FFTpkX9Icjbh5pSvbZbxmQDlEKut2SVqbptg3dtuNur+DkZMST1/a5cmWP7k6LnW6XxBgEAmctMpHRrb0xeOdQSuG8Jy8LtNAoJbG2JE0MZTnC2ejkTYRAlhqKfIAIHlEt2vXekecFcRMChbWOwaBPt9NBS8XQlxRDR5EP4/Jf0cYHR5omeCuRUkZpTJnHZcTtlEs7LYwEY6AsemRG0MkSRIgExJgWompbSoUAlDaYNC6fFlLGl03K6ldJT7bYYgbz0tIFKqAHYRxdFz7cB0wlNQvaXZhBLDiBB4dlapRNj1eVH4dXkZFl+erhsxKUOtHw3p9JghJebRKUEDazQ6kfL66rruuf1eufLtvgS2VFm/Np8/Wuyr9q7575OmfCIkz8ZwgCZV5wdPcOSZIwtIKToePa5R20d2AdSZJy7coBd08ctw5HZKUkSTXHR33clRaCuDpGCSCUhADBa4oipyxGOOcoihwhJUIoesMRe7pNUZQQPMYoCA5rPdYpEhEqYmAx0uA8jIqcwWBErz+g0+lS5EOcD0gpEHiUBB8c+ECRO7SOK3ikkAz6A9rtNmmaEIKrpgjPbreFVpDnOUmmabdb0V2/1jGPlAipEMjJEnStDMqkKG0QUiODwhWB0gYK66OR7AKOsuy5m89Xx7q2K6vyr4tVXzj3uz+b4qK+rjetZsHZn84TzkpFVrOJevIiQjLNO9XbTI5XdGzdfi+6B4vKx+sy0zlOL+ddXPemkox63CIpx6q0ZXGbtLMuEVknvYm4zLe1ipw0EZT5uubJySYkZStBuTAsWoUh1vRTcrFYd4JbiWr1DgASSlty984tQu+EYa65dTTi6r4l1RrnHUVhuXr5Eke9gpNBTn94RKeV8PRTV/i6N7+ZduJ5+tolDvZSui1Dt9uOLDkEitGQ0XBAvz9gNCro9UeARZsCH6JPkTRNoXLmk+c5MlF4EVUqgujPBCRHJ31K6xkMLVoJWlmGUAojod1OGQyGGKOwHoJ3KJnirMU5j7V2ovtWmUFJSWI0UmQYJVBSIGX8G5xDac34PkuhCEqjjEFqg9YJBElRWErnsWWCcwrnBQh1/vuzxVq4d/u/NKtjTtfeYASyRJMTFictqO906qoznKU+F2ik0lRdvea1mcuCyhpI+cXdz4vHpn1bRigWpS+SkiySTCwqsyhtU4Ky6W9RO1sblC1WIzC25aTdbnN5f49RuEOv3+PFG4onD3bZ7wZGRY5AoEVgr5Pw2mee4Ksvn2CM5KWX7vIZPsvVgzZu1EO+9jrt1iVCgCRJcWWBkpJ21kYKya3bd1EqYTDI0UrRybJICpRGCAXBx2W/KkXIGFeUDusgLz2olJOTY+4eDzm4tMvB5QOSTKFllHYURUFiNKlSUcIhAtZalFSkScbR8RFpllFajxQBYwxSBBItyfN8IimTMqqEPAKlNV4YpElIkhRtEkAQPEghUVIhlUQrjZIqfgVuYIfSJP3a4hHHokl4i8cay4jH/PF8nrOSkk0kKPeSoMzbmMyHtwRli7UxcXGPIIg4IRstCUZiFNy8dcKdoyEH+22kyhEi0Gm12GmNGDnFpUvRBiNNdNww0Eusj3vS3DkeUBaWbjullSYkSYJ3HiEURicUZUCbFOujxCRJs4oUKIL3WOerpcOK0nmci+qT0gZsEPGvB520SLIWSSoRwZEYTZHnlGVJqjU+lHF68KBNQlkUFEVBmqYoaRBC4X1AaU2ZjwgBTJISCDjvo8M3qQARVy6ZBG3SSGqMBgzOC0rnCE7ig8N7hw/RYHaLVymWkpN1ZCBbPOpYRETqx8sISVP6w0JQFql2NpGovGoISqgNBuPjWd8jp/flWR4/Do+Xj47bCZNyy+JW97dmRzL5t15+GhYNNmGzceMj0Zi+rFeh/gsCa13cs8Y7EhXpy+3DY559zQF7OzsMho5bd/okWYbo5RzstUEaer0eoVS8lOcUoz6D3hFveP1TtJ6+SllaylGOloLDw2NOTgZ4JGUokdU1L2xgVFiyRDPKS9IkOjwrrSNLFVpLrHPkpYvu7ZEYk5Clgp1uB6UNSivwJVoJ0iwlz0d4Fz3WGqNwzqKUREhBp91BCInShlExika9QmKSDCFVpG0h4ANoIZFKExATiYqQcZdiay3ee5wXeCsQ6MrDbEAGgV8qCt98gpovs85+TZvkP29/Ljr/vcLKXoTZg817fbEqp4u+zmHyTz1ijFX2Lc3pYWFgmj80pldRC9rc5Nyb8i4rv0yqsWmZJsJRT1uHfMRjiHNPaDye5l+Wt15XM3EZx9UlHPPpTQRlU2Iyzt/U9ib39pEmKEwcjc3HzR83+yCJJGWRP5J7aEtSVR+Y9ZUxE25yLFeLDg3ZJumr7n+oDGVDQASJ8w5XbRjYSiGRDpOmlDag8LSzDKGG9Ed9rC24cqmD84FrB9eQKkEKhRQebQz93oAbN2/xxME+wZYUec7dO0fkhaPXH5KXOTvtjIBiVDo6aKwX5L0B+/u71aZ7npNhgZLRbb3z0b28EKC14tqVA9qtjNQkZGnKaNQDEZBKkrUyCAJjEqQyJFkkHkLGzQuFlHjvJ5v9CRkQeCSe4F00jEUgpY4GsjJKmTyeIAEZ1TloTQgSayRFmeBLSUCeaRHPVrVz0Tjb9QxnoCSPFE6d3hKj1FNlF6RPJpsmm5KFTkzOhXtpn7KKvKwTt4i0LCcsYkI+xknLiEpT+uwHe3Pbi0iLGFc4R06aVDVnlayM6/HhVSJBuQjUpRqvBkzPN26ZGETAJIY0zTi5PURf6nL96qW4629/wADHsLAgJL2TE7SES92UwWDA/l4LY1Kk1BgtONjvsNfNMEpy0ushCXgvKJ2gtJCaBIFjlBcEJErBUW/A3m4X7yW3756wt7uDkAppJCcnJ+zt7iGkxJiAc4ErlzPa7RbGaJRWCEl04qZ1dFnf1QyHJUJppDIo6SkKG1VBlYdXrTQhxD2DnCuj63qtEHiKIo9LiqVEiPEqnkqqhUArCVLgQ8DjsQ5GhWdYgBM6OnB7zOe5RxahmYK8mt7/LRZjXSlJU56m8Kq6T0/ey9Kmko9lhGf272KVziIbkUVEY5z/rOkzBGW7F8+9xaMw/4ylKbNC1rrqSkz2lkFA1u7QV3GTv24rJZEiOkZLDNILfChJkmiTkRhNJh2j3iEibSOUItvZodPuopSklWq63Yy8zDk86nM8yLl1+yjalVhPUZZ4oel22pReMswdnXaXQb+HGJa02y12L13ipF8gZMpocIzWGmMM3W6HRGtGwyFFlqBliKt0nK8kHgoKsD4SIgU4P4p2IULEHZZlQMpqF2yhCIDRcSdkqRO0qqQnSsfVPEqjVHSbH7xDOItzjhAEZaEZjQTet6JNz6ov0S222OKhwybkZBPyMpu3WUIyTVugblkR19SnVQTlVB0rpB/rSkzWIyivIgnKvASkSSIyvjjr6O7HeXwIMz5N5u0/JnXNSzaZ68+q8IL+1x+4df2jzIdnyck8YRnrmAJKK6Q2IDVaJyRGIYRnvHNvmmXsesH1q5expaWVavxei+PjPsNRyd3jY27cvMkLL9/gysFlnnnyMi7AYNhj0M8prcejuXnUQ8hAmef4IJEqpd3SoDKcSNi//CR3796m1TVYL0laHcrKSLbVSpHVbsK+2rHYGIOr7GcGgxKTaIzJaHcS8jwHqXDWok0S3bsJiUmiCicQkELigkOp6GslSVuE4FFKgZRIFZcVB1ERGR/7LqQl4PFeElwr9onxc+YnS40XfVEtWx57Fj8pm9S/CvdSmlA7y6U5lqcuy3E2bHJ9Hkc0nf+qa7Iofd1rua70YVXfNk1f3L+6+mT2eFpkHRLS3J8pMZmve5y2Pjmpp9XTZ/uwuI75ck0EZZFqZ1n8IsKy6LzWwSNPUO4FQu1v3eajaexuIkQX1gE4bS27bnhJl+Z9iQmp2Nm7xF2TYtIE5yx5URCCY3d3B60UmZHsd1sAaBWQIaXbSjnuDfF4MJqbd455/sVb/P4faL7uzW/gyuV9pJDkNpAX0e9JmVuMThCVw7O01UUlLZwP2KDYu3SV27dvRNWRMpRlQdbKMCahlaV4ZynLgk67TfCB8caGzpa0dIoPAp2k5NbhfdzrZ2dnB0lUZZVliRDEFTxKoHSGDwGEQGmDdSUoXUlPUqTWCClARB+2zlqEdPFFQxJ8Ql7kDIaaQiisCPhgI8mZ3BIx+dv0rDwuKobzE4g6sb4HEGKmZ692YnK/cHoj1YcV84sg5p3aTCWk83/rZU6Tj7rUZDlxWJegTNtbJElZr50ZY9klhGIR8RgTk02MaF9VEpQHhfGNHks7Ln6SWcCM1gqvrj1EzU40M5aSrN3FJNHbqtGGo6M70PdoLel0WiRKojtJtZrFIwJR0hI81rfxYohjD+t7lE7wqd/+I9JEcWl/l6tPHNDqdggDybW964RgCc6CEEilkTrBW8vtO0cc7O9jTIazAXz0VeLKnDwfkXQ7pGkHVSjKsqAUgTTRZGnGwEcvrtoopE5wfoAUnizLUFKiVXT8FrzHWYuSEikFLlCt1olELdGaICRSJZVjNo2UEuts3LcouMp6B7yHssgpc4nzKT5YglRIraJKqDYwhzBVKz36WO9ZX1eCtMUWDz9Oq28XkZPpYz9v1Lo5GWmKWyZBmf27QV1rkIpV0pJ10zdxdf+4jJhbbAwx+QUEiclIszZl6UDIuMIFgS0LcCWJgnaiMVJgtEFrjZYSJQPtxLDbSTnY2eFStxs9rwpDfwR//MJt/uDLX+X2SQ+UZjAc0W53ePa1r2Vv7xKjYc7h4RFJmuE83Lp9B62j75RWliFEQElBnufYaqmxqKl6BILEJCilSZIM50AgAcHRyQlKKUbDIcPBEELAaEXAE4KnKErardZkybW1Dm1SdOXKPgSJdQHn4+AjpYrGuThCWeCLnOByMiMwwiO8Be8mL6n3Hudc7OdD7hlziy22WA/z7/EiSUZTuF7mXv/micJ4TGrMu6D8fJm6xGTRb1H6q06CMp5Y6mKD075CNomfTYM5m44lkpJ5icr4uKnc+DmdESBWzU5XCS/eq+d0ffPps/WfWps8E4iu3E3WIu3ucfvkBZ468EilyYd9iuEQm0iClqANwYMvPVIKyrIAPGmS4I8GpEnGzs4ORyMHhcWkGXvtfbQKmLQFwgPRBf7h3cPoZbbd4fj4kFu3biEBrRTHx3eRoUP38j7DgaUcDtnZ6URbGSUIhUUIEEqh05ThKCfJ2ug0pZefQGmRQiIFtLIEbypphorkJm21cM7T3dmpJEKgtQEhq3sRUEpjra+WhEuSJI2eacshtswJ3iOFIVEC4y3aFQSn8SiwHhHMxGhWVtKU+JEVUJUkJd5y0eDbhlr6zJ2cuW+cyh0Q43M4I9bjUHPKnIdUInKvCeFF17+qvqb0ZcR30/4ty3/WtLP2Zb7MuuWXXwt5Kl9T9qZ21/k7no/CZASf/jcZ1RdJMM6QVu/jfH/GK2Vi2jjf+Bcm8ZOyc+FJehyuKwJzmuDUCUlst0r34zx+pj7YTILySBOUsRCgruU4z3FT+J5hvhMX0PgMcZmrv05opsRoTGzictqks8fR4Yu8dLvHrnEEL/HO45xlmI+QpUWrDB88hS0pbYHznqzVRYgeeW5BKkyS0mrHZcHDYZ9ESRJ1mdc/8xStVDEa9EnTlMGgj7U5iVGkiaTTbuNsSSfb5+TokOMjQZZmSO8ZjUbs7e9S2Jw0SciHA4TSaJPhgkQqRZDRuLU/HKK1ZqfTrV7YgDIG6xw6SSN50QIXArYsEAKkFFCt6JEyXqEk1XgBJjH4IBmMBoRqU0QfHN55rBe4EUgrkM4ghIZQ4myBlAapNARwNnqYlVJGVVG88NEAF4EQ00Gi/gyE2r8zh9WzL2pJvlqVJebUfGIiKZu9/xeBuaZmsFXlLMdFEJzz1HEv29+k7kUSiYsqNxu/eKXduueyiJz4akVkCHWSUvsAXUIwJvUsICbL0hfVEcPMHc8TlYqk+dnw+OfrRIPTxGT+eEJW/GzaTN+2y4wfPsxIORa8IA8GAe8d1jlMkmG95osv3GQ3cewknjRVXJKm+lJz5PkAIRWj0ZAQHEpFl/Gd7g6HN3r0BhYQGKURwdLJ2ggcg5MTXnzhBZ68eoUsi4Rkd/cywgcGgx7HR3exRtBptzDK88SVy7iigOBpt1sUhSAfjQjek3UyetajrWcwzPHB0213sM7SaXe5NbjDTqdDcJqiKOIKYx+lQkJIkixFCEmRFyitSVV0VkewBBfdthkpEFIgBbjKvqXV6qJoEcoBZZlT5CWu9AhfIMo+FCCUrbbiUWBSglRYQBoTbW3QBDFe4i0nPmnGRKq6JcCyCX5W7BdrEIhQ0ZD6gDqW3DAbt8XDj/NKDR4FnIWcrCqzrrRnGUloim+qZzLpQkVOThMI7338SGwgGPXJfaa+hl9Ter0/i/KtqjeEMCEU879J/zhtDLuQpMxJURbt07MOtgTlXmD8FTx5firFTZP/+gcCMWH4YiKUDJReUHrF4WHOMX2udAXtTNBpKTotQ5IkhCDwtqQo44Z/SmkKG7AOHAJlDMYGdtptkkTRaiVc2ttBioArCvr9E1whsKlBhg6tLOXKwSUSBd469rod+id34w7GlaRm/4kncC6F4CjKgnZ3h6K0GJOSl5Y0y6J7ep1QlmVcraEUzjmUTpASECLaligFUlOUlqyzg3cOpQW+LCDEASNNo88V6yPZCj6QZRlp2sKXOaHywlvkBd7laOFoSUWXEUMbsAhckFEVpDTCpNHxm4wGtkFEJ3BSRhlqnUAIQIgoCRtLR8LMQyMjAWnY10BMq4Ewlb6cVhNtscUsNiU5iybsey01W05G6kuCx+n1v8uJR5NkYhI/VtSMJSEzapzqKJyuYyJBCPGFXEUUFhGYev+W9nMDUnJegrIsPC9BmcnzavEkO39zmmw05o/htJ3I/MsVw9MliRN5xzzpmBqM1PoxSa14ipjmHxOXhj4vOr+FPk7WGBAW558y/ontSzTqwMsEdIbA4YWnKD2jwqGUxPkCpRSFLaNkQiikhNIFBqOCvLCMcofE48s+aEOqFIl2GClJOztAIEskIngGvR6D42P29nZIlOK41+f48JArB/u89OJXkQK0EvT7J+zt7QEBbQyDwSj6LVEaawPSwei4x+5Ol6zVYm93H5OkcSdjbQCPNnHZrw9gCxu9zOoUbaJ6xXlBmRcorQjeMRj0kRWZ0YnGO4e3BSEEXBAok9HuglIjvC+xzlIWI/Jen6IIODQyaSOzNh6BF2NX+IIgA0pVj4Sr9LtR0VOpm8aPy+nnMjB+uePzJyeSE/DBT+xaxMyS2tlnZN3JaN3JZtPJ7WHBRff7vPVdFEm4iDY3jW9KP523biM3HXym2ZrC07KLyMfp8PzqmWltdbJfJxn11mbiwzTeh9n883UuIwBiQ3KyiIzMx83HL8oXpRljsgCztiExjgXEw/uxemexDcp83CKCAlP7mHXwSBOUe4o6mahJRGZIxxzheJDY9MtlPDzEPW4kSZKws7NDd3eP8uQGGofUJbmF/sgjNVE1YUsGoyFFUWItlHaAMG0GuUcQ6GYGJQK7Oy2uXN4nSzRaCUajIQKJ1hpciVKCnXaGtSXBliStlEu7bUbDIScngte+9rUM+iecHB1SlpEQdTpdlNLkowHapBSlBxndy0cHawlaRXVU7J+LG/0JcC6glMRaR1AKqSRSJxWBcVBaVCInEiXvLNZ6dvd3cT4gxuotROXaPyFJE6SQlMUJg36PMCxxJyWukKAy8JYQHCSt6OE2gKVEGINGESyxrSDwodr/R0mCkow1gaeJdtxXqKIhTMhHiCuTApV7/jlnfU3zyrqbDj4utiQPCyFZVq6eto7/kLOmNeevh0RDXFO+ev46IZh81p0q1/RxOK5jeXh5nhkCEqbP/nzazOQ+R1hOk5bZMpsQg5n0OQJwFlKyKLxOXxZJSFb96hKUdaUnIYSJmqdJArRV8dwDTCeIxcePDEKo+FYl1akMpBAglACpKEtP4SWlUPQKjxhalNLIEHDWI0QCWtEfjBgcnzAqymjPkSbsdDMu7XVIlKCTJSSJppXETfvK0iJCiXeQGE2iNYnSKAm7u13uBksIgeFwSLfbJUsNRZ5T2hLrojpEm5TBYER/OGDv0gGl87RbHRCSXn+A1orhcBhVPUJibVmtOioJAdLM0O508CGqb4SQSJ0iZaCVGsp8QL9/RKeziysKTJpQuBFKadK0hfPRwBY/5qgeoy1GDGmJktJ5rB3hXY5wJTI4vCtx0hB0irIJdhiHTCUloSIoXijQGrSqllLLySAeiVZl6Kpk3MV5MolEU3sBkawJOX0uQ5iIplcRjkUejC96Yl+FVe3eq36dt75Nyq+Td34yPG+dq+s4LaU4a38WJTfVMV/XmcKCiWzxVHoTMVnSj/pEvyp+XYISArCBM7NV9TX1a1m5eYJSz7dICjITt6GKZ0xS5gnKeMnxutgSlA3wuJCUiXA1VF/kQkyW2wYRCEIwKnxFJDyjkWSYaWw+opMICmvJbUl/FOgNPEIZfIh+Uva6GVeuXKLTauHKguAsxTBKTEpboKRECcVw0EP4hDQxFG7E/u4e3jkOLl3CBcFoOMC6hADs7O7R7w+4cfMmV69eZzQYYtKUMCro9Ye02i08oLTB2xLrCqwto5M3H3dZBo/3DiUVRsUdjUW16nCU5xijESFQlo7bN++iE4m1BQiBCwVKQ1G4SKzSNlIbhJTIkJJlCTYvyLTDMCALnjJorHNQghcOGzSl0KikDdpgvUMScCI6i/MohDTIJEGY+FpKIRFSTAyRrfdgDNIkCG+QQmK9Q/hIOKWKTuLiAOErC/zxQER1znLyrNY92zaRk1UEIWKc5+Ke//NPtBfTzr3AsjbvN+FqThcr0tc/h03OdZ1w0zM5nfyqcIOdyWy+1emL8tYn1mUkoZEgVL91Ccq43nVsUNYhNYRQW/q7geRkfN5iPYIyye9X1LcmHm2CEmaNTkMlVayZVkxWMUxeu7lwPd9pe5LTX5ybEpNFg37TV+Am6fVw04u7rHwYn3jFip1z2CInH/RxZUkQAkdgVJS0jSIg6Q1ygrXkLcOodORloHQghCH4kp1OxuX9Dpf2o9Qj0RKTtBEiIEUgzRLSUlLmBSF4grUEKUm7HfIi56R/wv7eLs6VBKHYv7RPv3dMt9WmLCydVpckaXHz9i26rYzBoM9wMEJpHzfw8y2uHhzgyiGlt/gQpTCtLCXYgMSRpSnOWawtCEKgRZS0mETjiiG2yOkf91AqSiDyUU6WtrBFjis9QWrStI0QIMYOAoREKYOUklYq6bQEOE9e5hTBEZynHPYxwSCCxg8UDolUktIFfACpE6QyaJMincHnAu8FCInQEus9hXMgDElnDxVA2hGMxa5CI00KSiJDiXAOV1ZfbSFu+jh+ToRS+LGRtJQoqaLKKFTKrSqfFLJ6kabPY3VUe56m6aFBpE9TjJiLDfO5wmQ1RBPmX7f5XGL+HZ6zY5g9nqrBxr2fL0+tH6e6Op91xqcN1Yqq+b6KU32uk7ym3i4+h3lJwen+NLezKL2WJyyofRK/hHzM2W6cHljrf2ppYny5pwN0PRzmrUXCHCFhOdFpIhXr/F0Wty5BmZCEhuNlJGQZeVnWPsytEGogKKvam5WGxKs/9YviGwjP+KMonFLxzNTrHOtiI0+yH/rQh3jnO9/Jzs4OV69e5bu+67v4/Oc/P5NnNBrxvve9j8uXL9Ptdnnve9/LK6+8MpPnK1/5Ct/5nd9Ju93m6tWr/J2/83ew1m7SlQnClJxWETA2SA3jkaeepyEc5uLir5lpn27/9MPSFJ6vZ1X6sraa2l4H0zbFTDgEH/e4yXNsXuKsxRhDmqRxkhQah+JkZHnx5gkv3Rnwwq1jDntDCmdJWymX9ndJ0wTnHKNhTq83oD8cEEIgSZPYjgsIH0i0Ym93B/D0+z3SNEFWS321Vnhr6R0f0c5aDAYjvIfDoxOsD4zygq+++BJKa/r9Hi+9+BLHR8ecHJ8wHPTRCrSSZGlCkY9IpEJ6h/AeV5YIwJYFRkmG/WNskRPKAjsacHjrBoPeMVJJijyn22ph8xF2lKOFJNEG7x1FMcQW0Tg2EIlEu9Vit9uikymyJJDqkpbMyeih87ukxR3M6Aa69yJJ/wXE8VcRJy9h8ttw8hKy/wpq+Aruzh/j7nwFefwiqvcKHL6AP3oRkx+Slj304JBw9Ar+6GVC7yahdweRDxC2xJcFbtSn7B9i+8fYQY+8d0zZP0HYHOEK3LCHG/bw+RDKgmBzfJFjixyb5/iyxFuLdQ7rPG7sEXcirq15h3Ru4sAphEi2PKL61QZIxpPLOE+IvxCY/jd+NcdqBkEIYxIRf2Fcb/0X5n5z6aEqN643Pu/1Z7963yf5a78wG4b5MWLuN1d+fB3qdZ1qo+rjuO+z5afn4MOUAE3S5859Us8kvKCdhenjeuP9mf1vPr6Wt/4jNJQfG4JP6/AN9U6fh2m9TeF6WzNp55jk152ox2U22XtmUs/4vBeRgLDc22tTvmXeWmfzn65/mTfYxvJjcuLH9flIRCa/MD1ecW7rYiMJyi//8i/zvve9j3e+851Ya/kH/+Af8O3f/u383u/9Hp1OB4Af/uEf5r/9t//Gf/pP/4m9vT3e//7381f+yl/hV3/1VwFwzvGd3/mdXL9+nV/7tV/jpZde4m/8jb+BMYZ/+k//6SbdmZz4vERjfAHW8+q6WAIxX/d8nU1tLEur17Oqf0392aT/TVikux8PdkJItDYoKSlKiy2GCCuq0czRThN8iCRUaYOsvr6ddYzyHGslo1whpQUC3VZCCGC9w9sSIxX4wLDXRxvFzu5u1S+Jd2VcjeIFiVQgVEU4Em7euEnW6nDz+RfZ2dvj5uAOO6Ocvf19vvjlz2KB/aLk+vXLtBOPChalJVoKhoMeqVG02lHqkipBZjQiOPonh3Q7e8gg6ff6DE76tDq7nJz06GYJR3duo5VEKYnXAq0MkvhiaqWQUjAcjnCuREowiaKVGWyeU45KbGlBKFIhcKHaQ1lWEisHMghkMGghkSKBUiBDIEuTuJePAxdAoRC+jaOHKO6SJIYgQnRQJ1NU8ARXVKuFAqX1ICuncYDRBlFYSu8R3kcxhNJ4p/FCVmIJGVcsKY33Di8cQQhk7Tdjk0v0WCtE/EWhrUOGqd+VaBMz+SyO5URg/lEVNQNLMbaLmjzfs3nrX/1NT/wKio8Idbohxt8yhDAjMFpQer7+U51r7lON3SyqftOPk3XKNaVt8jFznvaaxqVFH1Tr9HPVx96qvixqf554rPt3UzI0Q4x8ZLRN5GcTacqiPE3xmxrJNjpfo07Oqt8KVU5T2iYqHhE2oTNzuHnzJlevXuWXf/mX+TN/5s9wdHTEE088wU//9E/zV//qXwXgc5/7HG95y1v4+Mc/zrd8y7fw3//7f+cv/sW/yIsvvsi1a9cA+Kmf+in+3t/7e9y8eZMkSVa2e3x8zN7eHj/8//iHZK3W9GRq+vSZk5yLX5S+KG5Z/nV2p13U7rL0TepdlbYofvzglGVJ/+SIOy+/wK2XX+Dk9ldxwyN83sNIj5IibrgnAV+ihWd/b4c01WSpYafTpt1u0261SNOM3mBECJ5WYjAahAh4m0fiERzaREdu7VYLrTVCRJf05WhEORqR6BTnS3xwCAGjUYENkpN+waj0mCwlMYL93T2ef/EGr9y8zaW9Dt/8DW/kUkcyOD4kz0sGw5wQApf2dpEy0O60UcaQpi2UErz08g3arQ5KaXr9PqORxQVJZ7eDtDnC5kgpaLVbaGMwnR2y7g5SBoQyBB/IixxbDAm2xOU5w/6Io7s9jg4PKYooiSiKqHJyrtqTxwcQCuuj7xgpNWODGCUVWguUipOn9YLSSVApUqcYJREiLut2JEjdBp3hkHFzQ5NgvSAIFUmKjCq6wlq8kCilQWpQmiA1QiqUTuLaZqlQMhoAO6FjWGmkYKwUAkLlsTf2WUoxo3bxbqpOUlohxJyQdrICrvo71b1W/45JdGyrSf0zO8ufYjuzKaeSwxzREA11Nte96UB5XjLwIOrZhPCsS2IWEYhFBGZRHctsUFaFm4jIovhNiEn9+LwEZeN6an1b5fDtIglKCB4f/SMsLDf/t55uy5LPfvqTHB0dsVt9pC7CuWxQjo6OADg4OADg05/+NGVZ8u53v3uS5+u+7ut49tlnJwTl4x//ON/4jd84IScA73nPe/iBH/gBfvd3f5e3v/3tp9rJ85w8zyfh4+PjyfH4wa0f1x/AZXYai7CuVKSp3Lgf8+Emack8lrV5ut6pKHz2IzX69Zjv47KVD/Hhibv6KqXj17vWaN1FBsdwOCAvC2RwdFuGnU7Gbifh0v4Oeztd0jSJflGCi7sUB0en3aaVJghvsTYnIBiO4kQeRCBLM7z1EDytVobwFuEt3hYc9wcYo3HlgLIYIqVC6pRRf0ApDDfu3OXJ69fojyz7l69x406fgGIw6JM4jx30sNbRSjNMkkQbFSkJPlAWRXTwNhqRSBic3EXKuPIFKUl0xnA4QpVDtI9u8F2Rk7QyMiAEj9IKpQ2FjYa33llCpRKJP4f1nuFwyGg0BAJKxclfSg2yUmcpgUSiNCDAmAThHUoGpAKEQHswRpAkkiBKgisJ1pMGR+kK8Dm+EKRSkcmMsgBctG9BapRJKZ1HeEh0QonBS4NKMqRJUSZB2LwiNAovQpRSCI0yCUprQvCU1sbVQdKANsQFR3FJNz7Kfq1zuBCXcwuhZp7JMBbA+Fk+EELteSYQxkYgExuE6dfWuHwIkaiI2Qd/Ut/8sy2lnA7kVUWTbBVbmRartTe22Wp4bxe9y7LehzlbmlDr4Hy5h4GkTJIWZDldtKJ7pwRJ8/dFzJz7JC7M563XN7UPiuk11V+trvm26qR05jhMs43LjNNDLc+i9NXHIT6/tUk51jk7wXs/MeJYSgg2ISjLwhNicQ4iNF9fCJWztRDOZni7AdU/M0Hx3vNDP/RDfOu3fivf8A3fAMDLL79MkiTs7+/P5L127Rovv/zyJE+dnIzTx2lN+NCHPsSP/diPnYqfZ5F1rKP2WSc8X+eivDNplUFhffeT08dTeXlNDlL7t6nsODzXr/lwmK2zPo6PfWmM4ces1jmK0lKUFhfAVSN5cB7rA955EulJjOLS/g6JEWgFIThsGR2Y5UVJUTq0qTYa7J+QZQmJlgilSVqSTusSpbUM+316Jz28szhb4MoE6S35aBTtTlyJ9CU77QSdGorcEsohoyJQFCB1Sl56lJGAREtFPhiQe48b9lA6JXiLd4qyLOmo9mTVyqDfj5IdH202MIahDehsr3LGFDg5PkQUkVyYJGWXXZLEUIpADmTtLs7BYDhCKUErS+KXESOUkqRa4xKFURneOqwrowAgQGnjNU2zNgiB0hLvA0p4TKKQQuKchyBJE4NUEqQjBIezJaVzaEAp8Fi0iit9yv4RwQaEVyRSoxMDuSQUNtr/qASlWiATpE0ROqmkKJogJC4IkAqqPY4oDbmzUbojBEIl0acLYKREB0coCsoyx3tBkDJ2qvJCF0I1QFZ6ICFENYGHShsPIKdCFYA5L5P1D5BxOExmhvozPclQk9LEobA++AsBs2RdVn0EKcTk/YhNTL38CnH6vZvohmb6O04K8zb8VI9W7F99Eo1nMV/7TIWNBq1NHxuIpenNZKHWlyVzR1N1zXHNlayTd502FpWZIYMNx/P56vHL89eeO5Ycs1hlMzPRV7+zEpNNiUr8NRm1Ls6/qF8zJGMFOZm1ZYmvtg/g3X0gKO973/v47Gc/y//6X//rrFWsjQ9+8IN84AMfmISPj4955plngNkHa5ktSVP6JuFl9iRN+YIYj5XTAW96PFbpUNXDXDiOZPWy03ZXh2cH71lyMj296gUKniCI4ngpkVKB0NigohFk6XEuYCS0W4bdnRRtFPuXdkmUAiRl6ekPhpQuEITg8n6X1GjKUUnv+BitJe1OCx88t+7cZqfdxpU5zkafJ4eHRwyMopUYfFkipMTIDG8VJ/0Ro+GIVjtjv204OblLPoxqnyRT4HNsaTm626OfFdDLSaUlaysSlZG2WiilMUlCmqaRhA1H6Exi8yG+GJImCuEdo+EQoSXeDhkN+nQTTdbKyFptLu3tUJRDgi/QaZtQFiRJhmy3ECruU+S9I+7k4yCUGC1QQlK4EpyNL6l0CCTtLF5H5wPBl0gERhmkCBWZkRijUBKkcBDinkmBgBAerSRSesa7IxdFjhYCpUAagUkEhRsxGAwQ1pNJgwgp3uU4JwlW4YXEmBQpNXkR9xVyKiVtdRFJgvNxOlM6jUubTQuEQ1KgGVL2S4qyiARGZ6gkXgvpXdx3xI/VOHG5tKhWBnk3Xn0ESmmCG8/bghD83Fqb8cqzamD3/rQEUoiZuMhx6iQ8hkXVhmBKzMfEIC6zl7XJaOyiPKZRrXSKNYXaa1Z72QKTd7tqLEaPJSljo98aiVo0mc/jIvMtJhDLyzalrxu3bt6z5Gn6UG0mHIv/rpu2KG8ks8vJxozb+yWu4C+SqEwkKG5ut+ENCcp8WR9OLyVuIieTMl7U4u8xQXn/+9/PRz7yET72sY/x9NNPT+KvX79OURQcHh7OSFFeeeUVrl+/PsnzyU9+cqa+8SqfcZ55pGlKmqan4pse1E0NZleFz2QkWyMnze0DLOsPc+H1+xtrPt3+3JWDmjiytJY8L6KI3nucl/igca4ELwgetIkGoO3MkCY6Oh0S8evzpNevJiFFaS39fo9sbxeovLc6zys3btJup3TbLZwraLezKOkRkruHdxnlBaPBEIVAm+gTxOg2UhqSBJJEcLnbRRvDV3/ri3zpy1/imde/gYCgKEb48pDDdEQhCvbbGiEUre4eRmlGrkAAZRnP0ztPOSqRPpBqhQqOYjTgsN9HmAFZpum021y7fAlUNAQeDAaUxYid3R0E0a29DwK0RlZKCykruwspkEqijcGL6L1WJ/G+uODRUpIkBuviXj9aGYwxhBBVJMgoVRA6IJRFqTjAOBcXCGeZQUlNJLHgfECpDKVbcSWPzRmNjsnzHEEgqXzceB+3HBAiLmN2AF7gbUBah3ECZIpwPZTRSKB0jiANzmSorINp7SCVwQePLwtSbTCtXRDEpdAhQShNNbdX9jUikhgEpfP4ENUuqjJW9uOPSnH6nZ48sSESDC1CdFhXH/DHEhopJs9+GBP3+M/EpwwBrHVxFYKItlVSSXACb8GFMJUkiOiLJnYg2uaE4GuUJMzJMwWESiIkp6a/oV5nw3mtgy1BWR0+C0FZRlIW5VlYvkHF02jLUSMoiwjBRRKUEMYv2GabE86fywz5CAFqUpn5umaNZUP1gTVOP3WLF2IjghJC4Ad/8Af5z//5P/NLv/RLvP71r59J/+Zv/maMMXz0ox/lve99LwCf//zn+cpXvsJzzz0HwHPPPcc/+Sf/hBs3bnD16lUAfv7nf57d3V3e+ta3btKdmQsNsxNyEHJGYTLdgn5ihjcuFb/2pskQqlzjY1GrZ07UKmqtTOhBVVnsymkVS6iNVs2EhzXCi8v7MO7P5KxqYapdNce6yRA9ovqAd9GQ07n4MDnnUMGRJJK9nZTdjman3WF3t4vRhpPjPsPBAG0MAoGRkkRBmhhC8CTGkKRJtCEaDXG5Y+hHhAREKONeOl5weDxgOMoRIaC15MmrV7FISFoYbRh6i2kprIInDg546+sLfv2zf0zhFHuX9hgOe+hiSL8HOrWMZIHUCYN+H4fCOk/pPOVgiDGarJ0i8iFKJbjREF8U+GJIfnKE7lxBtg54zdPPkKWGkVUcnxxzfOsOiYIgFbs6xeEIoUCLgPNgrSUfjijzAl995SsJSgm8FtWkCgqN856yHCGkJkvbSBXjrHVILTFKoHU0lpVSEPCRKAhPahKSxOA9UQ0kokdeIRTDUY61I0bDAWVZTnyZeBtXVSkkivGKHIkPkdwEITAaghaUYRSNdKViNMoxgPCK4CQ6ZGiXgZAoIcmkQpMShn3KgSIRBpG0CCioiJPzgJATwuIQCKnRSZTcuBDiMyglsiKDvlqyGFl2JfWQcVWWERZn46aRBNCy2ncoBJTWlTQrLoV0FRGRSqKVjnUHj/QxXQiNVFG95aNYhUC0nxFSI8aSEy+jZUqIUhQpPEqMFz2PSYiIdkxCV5KY6CF4vCGBr96/WSXuePwSlagzElBRDVjjaxaCqL3Jy3EvCUpTnk3rWpdsLIpblv8sBGX8t4mgLCUjSyd4pnYslbfqUE3oonreT0/kTH7jRS5jLjP+NcVN00LVXq0P9fOahOvl5gnOrK1M03Wp95cganX56VLvakmyr84l1BxG3tNlxu973/v46Z/+af7Lf/kv7OzsTGxG9vb2aLVa7O3t8X3f93184AMf4ODggN3dXX7wB3+Q5557jm/5lm8B4Nu//dt561vfyl//63+dn/iJn+Dll1/mR37kR3jf+97XKCVZhukLPgcxdjpVk0ZU/5w2KJ1SlZinFlfLX5dqNC7zreWfVjbf3mzvz45mcnIqR+P51xxuVURMSYXRJjrtqiY1QVxIqpWg00pJE00rTUmThDy33L51TPDRPkPI6DW1rQ3dVkKiPcGXWOcY5X1Sk3LlYB8lJMF7BAXlaEh/2OfW4Qmv3D5hVAp6Q0fS3uVLx32sE7xy8yscHg7pdDOuPbHLs1d2ePMzB+xcegJlXuaPvvgSB08McaMBV3daFDZQiAKXaJxzgMCWjiBk5WI/vijtdoZ1HoQCFEooJA4VLMe3b3Htiaf4yot9vvDFL/HZPzjieDDibW9q88ZnDiiB0agkaXVod3cAh9SaRBtkSxJKh5YSoyR5ESUtRT6s/PwIpDbxeRCV0Wz1yR9CiOREaxKjMUZVz2Eki1kW9/3xLnqglapakUOcoEejEfmwh7UlSSJJkhbOukgy0wQpJUURXf1bV2kgpMLouLOyc7EPRglMFhAyYJSONhyBuF2Adyg3QsloTC2CxBd9QilxTkKIhsZi/PQ4Vw1ikRgIWfmSiYojnJD4UKl+VFQvChXtnnwZ1X9qvC8RAicFgkhQvLMoJUnSBKMVwdlIuCZfahDc+GMFvFJIKeP5AsGBECpuMSAl2iSValMQiMQFpavNHccSIB0JjLdo6VEyIES15YCQWKEJKoGgCEFig8CjcNU1CELiZbSZivUFJka5NfWRoHomYEJpwvgTaMXgvmrwX5a+KUFZVdc6q26a4tYlIcvS5o8XEZZ1jtfJu2zy936asFhSESmo94vzLPutqn++X7Hv9d+GEpxT/azq8WFKSOrHDdd0HWxEUP7Nv/k3AHzbt33bTPy//bf/lr/5N/8mAP/8n/9zpJS8973vJc9z3vOe9/Cv//W/nuRVSvGRj3yEH/iBH+C5556j0+nwvd/7vfz4j//4Jl2ZoPFkAwS5zkWID0UdU0Kx2cqfen8WrdK5iPwXh6n9inOOsiyxtqzsKAJSgNKCTCnamcYohZSa/iBHCEGadqov2RFuNOLg4DIhBPJ8SKY0RkUvpSVQFKO4M3E1ISscWaLxCtJkgFJQ5oIX7jqe/8JteqMbXM4Er7vW4tKu5o9eusVnv3iT4AT7HcHbvvYyOmnz1VtHnJSKnUyzv2NI2prL+x2kHeK9wLuAForEmDgIWEcAhoMRwTqMFGTtFrYsyNI2So0oveJnf+l3+O0/vMObvuYp2nuXuDV6iYPrT7Gzp9jpaow0cS+c4CnLgBGCoE1l3GoJ3kXpSTVnBx13fS6KaBAspMYYg1IKKQJI0FJGtYdSKC2rVcdRnWGMAR+lW1rFFcEejwgCa+My5tFoSFmWEDxSS4TwCA1pkoCP6i2Bi2VDAOISYaUUQoTqWQgkqUbJQGFzXOmwPpAkCe0sQQpRSVdAEJ37uRCi1Y31BOtItEZKhQ8B5VwkAD5E+yZh8CWU1uIdMU7Fpc6RqUWbKCVkNOqVAuUliHjuIQSUiL5iVAgYDK2QkkqDxzIajbCjAlc6lFK0kgSEwDuPRCGDQLm4gZKWEik0pfO4AMLGVUzSyUrqo5FaxWupq00cvSAflpTFCKGiikpW54vSKFkt7VYaoRKcMFg0udeUQWFlRWDEeJm2qES7IfIUIfF1Y9xQfVjUVb6PEEFpynMegjL+dza5Fl5AQlb9XUQ+VqVvNqHHFYunicl4Oe6slGFV/TOrguIBsMwrbRNBqacvJyjjtladpw+riNICocICbKziWYUsy/jwhz/Mhz/84YV5Xvva1/KzP/uzmzS9oD8wMUo7lba5hGKZzcpZ6nsYEUJAMF52GR8oIQSJMbSyhDTVFFqAjksmjZZkScLeThuBYzgqMFrh7IiyzGl3MrIsodc7JtWKnU7c00Z46J2c0B/mtNKULDXYskSKQHevTaqjQ7DhKOfppzLCrYKbn3uBV04EWkre8toD/uTrMl64c8RXXwrs7x6ghODw6Ihf+swNLh+0GQwCvXLA5d2U/V2DTvdQmuhFtvQcHp9wJesiQ7QV8MSvaq+g090Fb3Gj6MDMJCmDkeULXx3wWy8Ghuk1+k7yttddofAnuKLED0ucVKQdFd3fex+X4RIwaYaUEm3i7s1eBNJEk6iUUkuKogAfV++4YAlegZc4G0A6lDakSRLVHAJkNWFLASJEn5lJEtUU1lXkwAWGwxFFXmKtRQpBmsZ6xs+s8458lAMOY+IXupESqSJpC0R1lFRjA05LWRTkedycMWu1yRI16Y8SoXLz76vr6qMNifAYJUhSiQ8+2r/4SDbi+WhE8Bil0SpQRhFGlFyJaq8h56IaJ8lAKbTW6Oh8h7LwOBsNjF2Iy7mFh3xYEnwS95HyLkqAKgIplYz2LkZOJDHR6NtG9Y4MaOHjc5B7nA94HyUiJklJk5Ss1UIqR1mOGBUjiv4JbjhEmRTZakeSYjRKmLi3VRHVUy4QJTEiQYvKPijpYEMLLxMCCUFW0qRqHAvBTzTEMx9O47EnTCUqk4hToVnp7mk0Lw1uqG7B+DFVZjePvdO0MGFX9Ql/Nhzj5ttoDk8lSqEWP5YsxeNQPw5hYgM0EanX66v9HferzgFn02FM4jchKFMj0diHKUkYkxFqeWfJx9L65kiDmIRP93XcXj1/U/11gtNEKJrab+ovc/nGxuhTksTaeKT34omuoKdSkJnXZUNCcd9JyGQlz6yNyeQkxNTgb6ynmQ+fGlDq+qoF4anhHox9Fztn6fdPOD4+JB8OIDiMVux0dtltSTqJYjDqMxr06GQZ3nuyVNFqt0kSxWg0pNVq0U4NrZbBKMGw12PQH0VfGcRJ1hiNtzm9Xo+7RcmgP6TX75O02nTTlJ1Wirib09lpc/X6JVrtguFL4NQeQqX8xXe/k49//Ff4zS/d5cs3+mghaBmP0o6Rk3gyhFS0diS+PyIvPcO8ICGuHOm0MlzwlKUntBQOi0eQtDqUZU6QKWhDtyX535770zz/mf+KcDvcuXPCi+2UZ7oH+DLQP+mDTtFpNPa0pZ3YfERTAkuRj3Blgbdx48KiKCiKEhdCXNbrSkJlsJpoQ5KZuJoXHzdUVHGiD8EhtUKr6JU3EFcGldYxGA4ZjXIIlZSj1aKVaqSEsoxtBmdRMqATFe0hVLT1ABF9m/hIhkrrcM6jQlTRGBVVf0qAtyVB2Cjpk/E9kUJVz2FcRSS0REmN1CJKIBIVDXFtZVQqLMEHNJVPOE1lqxMHV+8swnuEUIQyJyDxmCiRIIAvEWPpXgBFiLY1QlASonoyBLSgMob12LygdBajNRgdB0znsdYSvEf7atdofDTWtQ7vLVJpjErIjCQRHu8tvhhCmdPSHp1VJBKLRERD4UTGXat9jnUFIS+ioz4vMdkOqtUFOnjfxquM0rUoZYqVCQ6N87Ja5BMYq4NCpb6L1DEQkEsNUSo52PJhZ8kYF04FGqQdc+n1cF01PpV3zBY8TY4aJCJzBSfhOSPqRcfj8HQSrcdP+xAYf+1X+cfhKuPkbxiTnGlfmyUTi5fmMilfNxY9HT6X47aahKSJ5DSFp/nO7zCuTlDGfZi1sakxzTXxaBOUMJYAxHAINC61XQch1FUtkTREY7XZ45h5nG2N8DLCsLxDzJzYTP1z4aYyS8PT77C8KDg5Oebo8C69k2Py0QDhHVJAWRYclyW9UJJoRWoyrI/GiMNRzqBvSbPoCVaKAi0kNh8xVJUNizHRLbv3ICS9wYCyLChtSb8/wNpAPhyi+wWt7gHf+LVPcDx8mbuDIYP+XfQVg2GEGHl22gVHX/0cB52EN77ljfzO7/8hZemxXiBOCm4fD7lx5y5dmdDqHqBbXbyKKgZtUvrFCYM8j3sMZYbj3hAfSoS17O/sEILHoXj6qcvo8Dwf/9n/k69/wx63e32++NKAp57SDJ2jZR2DkyFCF1x+IkMrTZCSxKQ4W6KkJEkShkpS5q4iGdEXiDEmWjFUS1qlBKOjPxlvS5QJaG3w3mK9RRuDStKKUET1T/AwGuVY6xEI0jQlSxM67XY10Uc1XVkWCBFotVKcrbzUqugZtigttrTIEG1ZrIsO9rRSGB1VLtHgLU6UYuIxVlQGoAHGmwmiIqGC+FdKrLORCAQbCUjloRaqHbMrmww3Xg0gfJWuqz1/CpyvdmquthEItkQBUgaQkiAUzldjgC2iHYmqVgVVfnuivU4sI10gEKVPMgSUFBgdJUMCibWR1BSli2okX+LyAXkJQURS1E0NOk0orSPPSwqbMyzi0nNfJpH8+2q1kVakwaOcJ9EWyRDhLN73cSJDqxZatchlRk6KJMEhsZU9S5DR42/FWarXfQX5WElPVhCUhkl+3bqiZHa59GZdcrEwT2jOvyg8P4HW0xdLERbUMUcAFpVfTB5mJQvzxqhNLuLr6U3hmT4vsV2Z72dzv6tqJhKYqbQjhNXnWZeQTCVFlVR2wT1ZB480QZlhZRdeObMWrvPH4w6sCMdqZhhUrYGGZmtEaZY0rQ6vf26xX7YoGA0HDHo9Bv0TinxI8HHi8tZShBKdSpKsg/C28gCboioDzWBLpPJIAUeHJwx6fXY7GT6VKCXIOl3KPGc4jC7qb98+5uVXbpJlSdwUMEA+sqTKU7pDdpMO73zzAZ/54gnPv3zM11zt8rrX7nCc36HbEexkOb95o8ctH52HWeKGbMcjx807fV686dgxKftX9tnp7lDmPULuKOwJAYezUaTqCXgHWatSDQiFNoajkwG/9Bt/zDv+xFN87esvE0yHX/7k8xiteOOzT7CTlZTFkLxw2KIg6Q3RiSFtZ5RFtP9wpZ2oW0ySoDCURUEII7ystq2TcTIRIlRkIidJ0jhRFtFjctZqY9IUW60sMWlGCCL6SBESk6RoHb3+Gq3AO/JiGF3N+7hFgDHRbiRO/tXg5ywST5ooyjIuuVVCYLK0skeJRMQFSRCiUoXI6fOm4oocH6I0Ji5Zjo5MVLUKR4S4+kjKuHuyVgqlNVJE8uK8Z+JatpIkjndVDi46sotuR6JPFKMU7SQaCduJ47doK1K6SLa0kmSZRqCitMp5jFKYJKHViuo36xxFXhCIfn+UoiIoAlAkXqKkR0pBYsDomC8Ej3MOiUcJBRKs9CgRZbjlsE857EczAKkxicZoNTn3JFVx6XzwlGUf4YcINSRJuyTSkmApKSlIKNB4otowTJceTvYwWkowmGSf3K/FQ8DqcXNTgjJ/vA7xOG94nT7M92fZxL0ofTVBWewHpS5BWUZI5o/XJj8wWfV2VoLSFHf6N0ucZstQ9X98nvX409d1XTzSBIUznPC0rJiVaMwcM72qZ+pWqKpsJhrrlD+Lr5Z1Eb/04goPV1pcWRKcQwYfv/irL8+4QieQ5xYpLCbTBDwmSRj0B3hbkmUKD7TaKVpIvPOMcs/u7g55UXLjlduUNtAfldw56jMsJJn1BJ8jVfyKFVKwqzXtRGD2YO9tB3zl5RG/8psnXDkwiHQHnWZ87o+P+OLNHkMxjC+kCnHJrofDY8vdo4KTS4KTQYFJ434yUmqGwz6dVkbhPO0kxfsiGjLKKDHwCIxOSFLNkbX8yudv8MTBNb742y9x9VLG//YnX8sbLgfaAoZ5CnmAIJHaIKRGCoVzUdyvK6NJKTXGBGTleMxV3nqtLXBlCUKgdPSXEn2aePAOY5K4YaNW1RJZRdpqI3R0MidUwCTEJbUEAh5X+T4RwlXO3eLu0N65yt5i+qxIGSUdzjm8K1FakyQp4yWDqlrtEh0Jq8kmkoSAdT6qppCAQkuN1GPpQ5xMhYAkNSSJjiuogkdWBsBCCHTN5sK5uAzZubjCJ76CFpwDAs7HVTJagpEKZ8tovCpVlAYBwvq4Ck1JUhPrLXIXr4c0hKCwtpw891lSSaKkxLkyblMQAOISd6VTvAuT3XeVUngPZemiVEvFgRoZUCa68C9Li6+Mb5UAvMBVzud88IiiAKVItUY5z3DYx4U+2o3IWpYkdTjhKYQgR1J4SxHiMn8Xxku0A17IuJR5cjbMfrDUxodlY8u62JSgLCILi/LPp61a9bMpIVpGSJqOm8o0EYD59PkJvPFXkZQmMnI/Ccqic1xNUlY5eKu10eDjZdl9WoZHmqBUtnqzXw1iqo6ZsdkYX5QZG7PQLO1Y8nKt4/Bt3E41Ztf6MRXXjvOcClcHIYRaeNzGtH4RmiUtoX5O4/rrHRjrX62lKEaMhj3ywTHlqI8tc4KzSFxcXRI81npUcNEnR+U74/joCIKn20pJElUtHZbs7e5Q5CMGwyF/8EdfRkhFXljuHPa4cziofGBIbIBOK5v4pbDWMywcVy6lXO+2KEvPtZ0uw+IKL9+8w83DE45O+twegDaCzFvGjrOcB4VgMAwc9hz9UXSF3xuWFIWl00lIOzuYNCEfDACND5a8N0AKhTCGrNPC2sDOTptnDiQuNeypHn/xW65yuZvxmuuGTJVxWW+paLW7hMoPRpZqWlmC1DrafIhoYxGCi8QhRHWLtTnOVfsShWjsCZ4govW9SaJ/FikNAQ0qIWu1SbKMICTWx1WvAY/HVytpqkHBAVoiSVACEq3xwVN4h1BRYiSFQOi4/Loooq+WJDEobeJ9cJHsRJWpqVbijOW9UY2qRKB0jrgqWEAo8WNyEgTWWjIdl6KHAFqP1VvjwdNXxCSqp4xWJCLuSzRepYOulk6XFusCQjiCg1FZRgdrQqO0xpjob0SJgEnikl3rcmyQBBlQ42XavqAYlQgiGZSprswZAkrFOGcdUkYpGiIux46/Iq7kkQqdyCgp8tFPUGl9pY4KIKKkRkkZJR/BTc5RCgHe4YscLwUmTWn5QG8wpBydoGSgpSyoAWVISUKLnIRRMIyCBgyOSKiEqra9CIGAwIvK2R4CFcRUxTP9Z2bMCI2q7zCbfT5lyVyysL6ZD72mdkKjLUuYeBgNY5MTJrYiVM/6qfMbB8fthrnhuzZZ1uvZlKSEatxcOEHPG4UyQzioSMoyQrJog721SMqK/i06HodXrRyqLjF1w+gpMYEQ/KxtTXxS8YRIqn2YKbMuHm2CMrk4NSnCeIKeIx8Npdeof7l0Yj59Eq43X73D0+P46olKYjN5lyfpojFcx1gX3UiAJpegVv+Ym1XXxTuHtyWuLHFFQZkPsOUIXFmV9/HL3IZqMnUEKXDWUfpAahIu7XYhOERw9EY9jDH0B32OD48Y5QUn/SFCJfRHln4hyJ2oPIgCLUNhA4mCdqvFTmYIbsSNW3fA7ZBlit1UcGUn4enLu+R2h17hORw4nDC8cvOQuycjbh0W3Dm0nAyj6kYIgRKaXj9nmN/FpAadpAStMV6gk4yj4xOkiD5RbGlJTBodCknNlYNLXO9q2vtdvu5117m6k5ApEEqgtGE4GqGUYq/ToT/o026lGKOrXXvjFjQhVF7RnY2Gt97irSV4i3U53hWAiOqTED2cpmkapRjEbQZ0ktJqd1Amiat+fPShInxAS0VIAsG7OPHZuGQ2CI0kQHD4YHHOETeN9Ggd7UTKsmQs0YiSHhmJhYuSsyg9UZVH18j8ZaUemuxTI81EDeSJzuV8oJIkRZf71pXRYFYpdKKikzrvcC5QFA5rY9+UrNzIh6h6Aqq+KQC0DlB5K/YhSo20NmhtJg7sAlT54zVVQpOlGeOvVluW2KKSoMhoGFyUJUopdNxqO0p2tCZN07jsWUSy5X1cPaVN9IxbFJ7hKG5cWpYWKRXGpOjMkCQJSgnKsmAwGFAUOZK4Os4VHlfkFHlOp7tDp9vFJAnWOYzWSHJ8McQ6SEQLk3TIZIuhNwxCwogEJzJccLjKX0YQ0f4mevuRE/uPcGpcq03kC2aGTeOXpc/EhcV56+FFaVMSU02ic2XqH2WLvs6naZsRlFPHDQTgtISh2bnZ+FlsIijLCMsMwWFZ22FGajHO2+QUbVFdK+tnOtdOj6e/WXISxnxkpszYNmWppfccHnGCEk7dgPn0B+JjJMD8CrzTZKZm0LtG+HQT8aWbbiVYPz5dftx2NCB0jAZDju7c5u7NVxj0DinzAaEsELZEEvd8kSKgCaCjSmAwHLK306HVbjNeTeKcQylDCJKjo2N2d3cJxz0OkhZH/Tw6axuVmKSFVjqSIyfI2h2MdBRliW+ntLIuPh/y8u1jOh1Nt51RFAWZkRzsdHjq8g4IEx247Uhu3D3m5s6Qr7ZG/PFNy92eI2sl+ACjvKQlNUXhyItokxF8AcGhBWgZJVBFYUlTyEtLmig67TZPX7+EyVpc2e9webeFFp5ef0Dv+AStNd1uG51l9PonBMAGgXQerQXel5SjfvQlU0kZoqFpnPBV9QVNqByUqegcDyTOCySKJGuhkwTnHeVoWKkzdFSzyPHGjlNLNqkESihEkITgokSxetZUtVQXoqfbEOKuysYkceVOaSlsdN6mtaryG6yLA4xSajLAjN3LSxVd1oeKgUvvwVc2J0pibYEtHFon0WtuLtByukzZJAZtNEJEIuBdqL6ymJBjiP2RMjo0K0uHUgFjDELrykEdcasAwcRGRgiNSgxSqcoWqIySEiGIZEtSektRFJXjPCpNr0D5aGcSvV96hABdOXWztpxsk5AXeSRzWmNMgjHR14p1Fh+i0XK73cZay2g4ZDgcMRz0KYoSYwxSaVpZRmoMSgi00SgpGZZDytGAQJ9M5rSzLm2VkvmUY5sytJZCpAQMVii80NMdovGTL9b6eLMKy0jCqvzr1HcWR20L+xRCbWw7TSgWlb2XBAXqRqtns0FZJEGpt72ozpm+hOoaNZCN+jVZeo5L2lw3X/ydTheh+T6twmNJUMZxTeqYC2tbROO6UEkugNnwDEOZGilG6cnsjVrXKHYes0uU5/OFU+W99zhrGfV7HN25xeGt2wz7vajb937iAn+8oy/CEWS084hu2w0eyWBYMPAleEu7lYFQnPT7lEUB9AlCkGZt8rs9itLS6XYwJiFNUmxZUJaW0bCAVJGahN6woNcrSVVcJloOLINiQKbE/5+8f4u1bcvS8sCv9csYc8619t7nEudEZEIEmIICZxbIKOsho1SlUpW4CIGEBKhwqQRZEk9p8APwgJAsS7Zkg+AB8cDlhQe/IEsg+cVgIcsyVAlSBYVIC1EF2OISJJlxO7e991pzjtEvrR5a72OMOddca+8dEWAd1zjaZ81xv/XR299b+9vf+JW//MdwIQJCcCYb/fEHz4HKaZr4+MM9/uD5l//6MxOU2x04nmb2h2e8fH2PuoEYTDhuN0bS6Z6bUSzzozpcOBGGZ+SsxDDwv/rGN3h9d0dQ075w0T6REAd7JC5wONzy8ceOuN/hx5EsLKqwOc3kZFoxbhwos3lTvJiE+zRPoEbu9XGHC8E8X40we39/h0wndrs9cRwXvlDOcwMYJlTWCfKiFt6oNbO66lgIr/29iwi+GUPU+A2KLoJxBoIgZ9Pi8G5NIxZxuHb9KaVFO8f50MiwVmiyqhl2AyOVWgslVzIrWHJemmibAAaqOu9Fuz52a9shRCscGU2oTUTMySTWgXsnIOaZK7mC1Cb4Zu3X6v0MENTSrlOioov3SETIjYt1KidLFQ9+OVeMAe+ENCeqVoYhMAzP8N62qa3Tzbmgas9OtXJ7e8vzFy947/33maaJLz7/nJcvXzajUjhNRxOjUwUnOGdFIr0W5nQk1ZlBZw77Z0RfiSivUuFeCyfZQQ0kKriuNmwCby1OctWHomKg/Goo5xGD8S6A5Nrya/3zU/ssBVafMGSPgZA3nX8BKbr93eb70F4eN8JPAQADDHbMa+GZdwUo7/JvDSFtQr56Dp7OnvHFM3sMnP3gAOXCm7I8v67urhub9ebpSw1QHtP1lzZislXntXBWUHD9mN2oa4uXPMUZ6Yh8617toZX+MTw814Jgnjz/dn69p82FPNjWznfpdVnupzfa9jeEyH6/h3ziVCaKWEzb7qk0AqtjDI4xOpwqOU0cj4kSlTxPDEEQX6AqVU1F8342g/Py8y+4P51wQRhiYIie/eiIN7fcHzMpZ7xYp1Rs2M8pnRi8jbJzqUxV+aXvfEJwla9+/DHDoKQ5s9vvyQouRl68N5A58o2veL72wS2DtxHtp1+8pKrDnxIp3TPEwFc/+pAqEeJAzoW744k47gj3EykoqsJ+t0NUjR8x7hjHkVQd4hXvA1PKhGlGQiDu9jx/70Mkemq6J1PY7XZ8cXdPni3NtxtaqKR8pJTUiKsGAFIKcPSkUnBxZr+/YRcPUDKnu4yKWKgkhOZV6PUtaMS4SlUjo+qmwYmz0X8tpb1v0wGh1sb9ca36cWjbSisPYMdwzsg0pawKlanxQFS1pRvXVn+mQvE2wqSTYkPLlmqE02paNOoM8IRgXqGWgd0Ag8f1L0rM46Ei0EJQWuuiqJtL58v4JsWfqRXy69eEECzbrJ3HPEEGWIYhLuCt1gppZppmUpqX78M5QZxvXqd7alF2+z3jbsewGyxVe068vr9nniZUsRTysGuCcAbIhlZBO3jPOI5Mk2VoTdMJUQjeI1RytpBRcB5CJOfEdLzDCcShcCvFPDYlEXQmMjLJSGEka8tma52ctLju4m2AtY7QZcx3sw269itrz3ZtIz1f9GBGL07xyPzFcfs2qq3q9BtG3E8BlaeM8qO/G0i5Ck5swcKReRo0dCzSC1o227MBOD9qkKLar/3hda+/1/Iv7XZWoLBZtl23vZcV3D38t92nbp7RcmyVTXhOHratJ6YvNUBRrDDeFjiceRXEHsdZCfS+SrGO/BKA9CyDJWSim9WbeX3cu3ENZPwo04VV+61IS0V8OA/rMc9BSnfzR2IMTN7IgbU4NGnTsgiIM5CiYh+vD56cTer+8/yK/W4gFSFrMq0TTA9EqcwpM2fl2Yv3UIWSrIpunme0VJM2F2HOVrem1kpwAnjCELk5PDMSba3k6Y79zYEvXh25OTh2+wP3c+WTL4589/N7wqjsx8B7P/4V0jTxWUnc3twYb8NF7j57TYwBdZFPXx0ZvGN6OXETB/J8z8uXr4i7wdJ8XaAUS6GteOZcyXUiZUx51Tl2N6MZze4Rc86E16TVaXGWWlqcM2PrHOrM2O52O5DK8XhcQm15ngErTjfEAU2JU77Dx0gYR4bdjjiOlpVTC7WUi4wCC7/gA/htW2iekwZKuts4xID3Dld08ax0gmvFQJh5RQK1KqlaGYT5NKGqLUxhMKJUAwWldWJOPM4LIQyEECgK3gW0WukEMVncBpQKRU3yvmojzcYBCS2luepyTZ0L47xnno+keSY1rwUiOGnqxXbTeAl4b7yXXJSUTXtn8eK0Nmevxy3/VLV5wlzT6rkj58I4jlZ+QCDXzDAMlmEl4INl2dg3FRpQMcL0/f299RPt3e92u+bkMLDlBE7HI9N0wnvHOOwZ9jtyzpRqHCZxyjAoMY7sIhyqcl8LdzlxnxNFI0qkOr/2C9Lda009edNv2Sj7+gDp0rBf9knXgMJlv3Ttd583DHU5gHq4TwcropfbXAcgb1r22Mj/fJ2ehYAebLsBGNfWr7om17wc2kcUZ+Jlj5FiH9M6eXjcevX6rt/zBrReeT7nfzfgo+93BkquXdMWrLR1G02Vy3f0ttOXGqAsQm0XH6BNF/yMxbPR117xY+i5t+NtgUV/8GfVlH8IkPJY57AlAmvzDC14CTbzurgrLzONepXilBNzIwIu2QjtqeVcQDI1V9wQqU6YSm4dniMT+OLOyLWH/Y4P3n+f3JRLd+NghhgbLdZS8UGa+1uYcgYPw2AF7EpOZjTFodk8C24c0TigOXMsSrk7Ilopfsexznz6xR3f/uzEXCOv7zLRCe7mQNbK6ZhJ5Q7vI3E38Pp+YhgtNDCXI4f9nvv713z9K8+J4phS5ng84bxjFI8Le1yB+1OmamU3DtzePuf+dCLVwuFwSwiBYfAgBrqCc4hJlZmh9p7gA6h5QJbOBLtvy1gBsNF/zZk8nZgUSiyM+wPDeGDYjbjgUS2UVpHYmbsBVW3ZQq5ldDUDUMpZBwJYmGTho+jiKfHevB7H04mKFX50CuqEWjJzNjl9EWEYBmK09OnufcglWzhEAbHaNi4Y+BUxD0utdp1Wndmu27KZSqs2bNuIuBY62XSSFVzooSrLiAk+UEMxUCFdt8VRqknVD6NnGEcrjlhMYyYl438MQwNOpZBzNkG59k5iiDbfPFGutMKNg6V9l1I4Hu+R2ZNSYmyFM8dhJOVMSoVpmqykAS2cWgquPbvD4cB+vycMVvm7Vy6OMeDv17pI4KjVqiELQs2FLCfGnWOIgbEoQ5qQKqQ54usB53YNQAcU022p3csqjrrpGy+N1LXpmtF/0z6PbXMOHN58zDOPRQdc3VL+CAHKw9/1bDD6ABzUSvfwvMu/NQTzEKA8BU4eqyb8AwMUelThTeBEr6975Boe/ddqC117x+8yfakBymON8201Qt4IBN5x/to64AFI2IpXd68NcDavG9fO4h1BW8zZ1lusVlYOTJsXtI0+2nE27aNWpajiY2S325FOEU6WAVGxEvWuaqsr48m5Epx1jrUUnr94wSm10ba+h4jy+mikw/1ux82zWw47T548JSVT8/Q7ptn0SjQ1Fc75Hqjsm2bG4AWpgVoTr+9OnCbTFfHxluFmj6hwKvDdz1/z3c9eom5AvDCd7plqIc8veX57IMShuf4Dr+9nUgZ1lfrqyM3NSNEZ50aOueA87ILl6+Zc2e12SIi4kknJROuCC9RiMv3Pbp5xeHbDdDyBVhNNm464GC3LRZ2NoLCqumWeLYMHUIHpOHOa70Gr8StETbK9mm5H8J54c8Pu5sBuv8eH2OLy9t6duBZaWd7m0jkJjccCS7ZAb3tOVo1PVRoYEHIyoKDQShIIVS0zKOUMOGK0DBkvJr/fO7laTajNl2qhQV1r/6Q0W2hIwHnXhNrs+rQWM85iwMWJM8E356wqsfQMGqsZlXOmZw1py/ARhsahAUTMI1QFVxV8XLwh1t4rMUYOhwMhGtCwLJzUH1rTPwlLeYGcMxrt2p33+HZMA1AG6tM8N6LsSPCB6WRhGmkZUjFGgvfGQfniC+6PR25vn7G/OZhInFiIZ3fYE4dAafL7ORUoGakwjAMueCrCPBeCTgTveBY9jmBGNVcclZnEVLTR243jhDSCNuuA7HIQ9dj0g4CRa8vedZvL3+4M1NQH22znH7MH1wz85fZmxOuT+z2l1vqjBijv+q9f26PXjrsKwN7l+XFl+eP/rux/5R2/afrSA5TFTf3ENpds8jeGU5ZNF8v/1vOmj7GdHhJZLGyyPcL5nCzdydley6++vvs8+qrOP5HFYG3vZb0350xrIjdCnbhWMr5DJWeS5CkVwm6kqOPulHAIdycLmRwOB272O+7v76hV8CGwGyNoZTomgrNqyMMQ2Y8juRTuTomD7Hh1VzlNiZQTxcFwOBBFKacjAHf3M7e3EfxAynB6VSnVRvrH45HDwUitr18euX+d8R7GYcfcwhbHqeJcZb8/oCg3+z3TNHN3TNzcRnyt3J1mxptAGEfSnCi5Elwk7PcMzgq3zfOJ+1Nid5jZ3RyYS+aAMuwjOc1mmEOEOCKihCE2LoWFKZxzuGiudx929uZqZU6WhooIzg+ERpYNw2B6Gt63OLwu74zGiyqtvVtYwurUVC2tKK7p0fSsllJLy7IxojO1Nj5IXUY4zjlGb2m0OZkHAUxLRcRRVFGtJigXLPuof1OiBpI9FvqoTcsk19TIthbuiT5Si4G0UtQKJGIhIWkS+j40ku6cSNNE7c/Pe0Q8Is4gerV6OaVYKrWKZxx35oXDeFSIgRsXdoz7Pb2eTS6FlCs+mJeln7uHdbvXI/hIjXW5T+dcU8IVTrNaNk9K4BzDYO+j5pZWjgB7fBwIMbL3A+KjebiCJ+WZaS54MT7MMAwtDGj3GcU8c1V1ISprVUtb14IbAt4P3A4O5yoxJV7XwF2NHIsyaSHjyPj27ta+xgbZCiqLV6WvOOtTHjEgWwO+LHts27dY/jZApfTr317u2aX3/m9rFHuXuw09WDt+1IizbLjZnsUrobruv93vMg343KvRgEMjorTZlUOmli2n9dyw9+0ehFW4BD+67Ht+r5z9Rs+pCpf3/9j8drlsfl8HbrTyGKs9On+/nXrx0LY9NX2pAcplnYIfRH31GnDpz3ETUWnr32J+fT8LYFjXr4ih0oHT9o50Az/Opy2EeewVL2CMJt99uRPW8G30aeTNGCOT6+qeauJcteDE0lFVPKlauXparZWbmz3Rm6T4s2fP2e1mPvv0E3KaGG93BLGshOfP9tQyk6YTz29HXry44bOXJ169OlooJ4yoE6YsFIFnzz5gjN4Igt6z29/wvU9e8t1PPrHaJGDGalbG8cBc760S8bhDXWQqVqdmzs74ES5zcxhJKVFKNVGr44kXtze8Pt7z/vMdle4ZaC5eZ7Lv2iTUkcjtiw8Yn98ypZlcCzkfoSpxd2P8kBCYT3eU6YQTcB4Eq5pbSzINkNZJ3RxuGEvgNJ2YUjKDJh7nI0ggJ6sErKqLqqyKUFUaP8RbuCRGlErOCdWWGSZYRg3W6TlaJyYshFPpIMU1n1xt7U6EGD1KwHkjrOaSkVLQaunAmWIhvmKhmZ7ZU9q8955xGG2dM35KB0s5r6NfU4g1w28hWoViRN9SLROnk2W1GgBDlaLtWWbLvFFVxBtoc4oJmfVvUhSH3QdYm08pkWslSMBRqcW+pMVD04FXI7n2/qCvKyWbBwhtRGPl/v7O7r+FjI7TzKeffkocdtzc3PLee+/x/PlzxnFgtxtRLczzxDQdOd3fc7y/s3flPDFEhhAYxhFFW+i1Gp9mGX0bgdk7uBkFHx1j8cS5IjWDBtDQuCcOtPeTLCq0qroKWi6di64/eftRrloseT2QPA083nb+bcDLY79Vzz0v6/EeMbBXzrksP7Mx7+jZaIMD3aYNb0BFvfj75D+unL+u+9rTV7ZhqPVeeDCdAZgLcHdtm9pmroGUFZGwnP/a+7Gp8aPecvpSA5RLD8oWeLxp/nLd+TI11PkOx3uXeessnr6Gax3EthO9XH9+X+4cL29mqqp5SGCRQrdO1z4iwUazli1ilX+9wM3zW8ZoqqNelOjNsPeOexwjlJnpdERiRL0pzu6HyGG34/ZmaC7xyM2zF/zS9+/47FVG/MCsdvZXk5IRdvv3APjX3/uCUyrMRE6ThUW0VnKtuOmO+5xw40D1ntf3yXgfjOSaScUzFQfHxBjNOKSizKlSVIgukKtQFLIWgoNaZ5wzbRI3mHdlTon7JIz793j23FHuP8Mny07xcSQOOwuPDCMpBOaSrZ6OWmo2FaooYCGhkksL1XksXdahBWpWarAMFZcS1Vm15ZwLLgTiuGtqp0ZiNeNVULU0XycKuNarAFIRZ2Cpj2pse11IoipmpewqLNxCEyozg54Rcaa2WgrzlOx6W9vL7ftzYiUDVt0UlvtTVU6nE6vwm1++WZG6pPvWakX+EBZ1W/OatHIA3uMQA47ZqkeD4IKReed5srCaVoK3on7et3beQFTKcyMzFkqZKbmQk2U1hRCWEatzjjgMDNFE6VJK5MYn8d4xumEJ5dVSydmhg8fJjkMuvH595Hia+OKzTzjdv2a/P/D8xTOePzP+kqLUXJinE/M0WT0kZ0Jx2rgq5kGzOkTS9IbmcjIvF4VAxrvK3ivRK1E8ohGXBlwxoHLMQq2mJYP0LKs2KFIWo2c9Xl3XbfqiN03rNu2gVwDKtWM9Nv+uy6/97p6Ih6P+hx4QHmyzOd7Z8kvvxblWyaV6LNgggbcgxL5NWKcPoLb3p3r92t8ETq5v9/A5r8vW46znZW1Hev082/3PzvvArf/49KUHKFrZhFUuQyxytg4utkXbiGsDIkRboGN9YT8YCLkeWlLVNd//kdBTX/fwfhsRUlfvzeW6fg1wnX+zIHvFqraiaLH6O7RrrrU0dF4ZomccLbVy3O0I3pPTRNGCW+7dOvj9YeRmDAwxIFLxapVmKRD8iHOwHzyvZyOPih/QcGDc7YneMXjFeeWYrCqwHIRX3/+Uowb8OLR00sR0zJymV/igBBfI6rm/u2M/mAehSuCYM/WY+fGPX3B/vOfjm6/gVbhvRMZh9EynGZ6PKAXnjdRpKcADbojEAnOB6kZuPvgxHBn1kI+OORXi/jnEA9VFxGckDIz7GzSfqHlmmo7mvakzIuAdVDGOQ85p+XJdC1+kdDJ11hLJKRuPYRgZfDBSaa1W4XcbdogOaYRL7enGHWw2ILod0ak0N74IiDNvT2sntVo7qKrNENryUgqpmHJqaBWVl7akrdBf96Y0MKBd96DJ2Hf1WrpybOvZSm4dd1O49c7CTRTFB9aKw+0awxAtDDZN1Fb4MaXJCL3VqmZ7HwhNul61CbpRG+/DGTHVe7IvzCTjnJRELdVCSngoM1UqIUaEgmi24w4BrRjBXDGNnjEu33EpFS9GsJ2mmdPxyN2rl3zx2fcJMTCMO3Y7UyDuVXXMgVQ4nY7kPJPyxG63b3WA7BmXks2z6b2FcCt4VUQSgxPGsVrBxCnxchZepoz3kclHZhWyQq5d0G3jbtdliZnAJ2zHY4DlfLlu/t9/6MXP7fx2+8eVT9/pdwPkytYQryGa7T4PgcDbAZTLf9cACv2bewKMPDUPWykNtTekunx/tV4Xdds81rP7ubRTb/OsL4+pbF7hGTjZVDNepo0dbf9f9n/L6UsOUHqDXB+AtA549YScr2vOkfaotpwPNvObSTZcAOQapWQlq/ad27yc7bYJubTNL4HGJch4CDD6efQKiNkuO//QtoCpH6WqMk0Tr1+9Yjoelw/JuAoF31IvYxwQ51FgmmdeTxO7nWk7THPi9d0rqIVx8Fhhtkya7/FeOOx2iAhzzqSsUAuvT4mie1wM+FEofsQNe+JutCwRlMF5nr94zge14G5/ke9+9xPm00SZE5XCq1MmpYrMGYfiJRHDgEQjzr56dWTOgjrl7nTi/UPEecvCDa2IjThBfGCaCofnO25u91YCrxlRkYGwM0Lq3WnGxT0ln5jmAlXw4w3EPRJ2iPd4CsV7FOOVDMOBmjJzmjlNEynPZphrtnBJ0/JALAU2hJE4jCh7VC18EmMAVdI0k6cZcZ794YCLrSChD6alIYCaQm+lIGoy9DZasdo32oy3iLWxWsvCRxHpvBVZOkRponiqTX6elv1SrDifC1YwsH9/pRRyrYsqrHktLHQxDANhMNJoVaV4t7RX85xUPKZPUtVSfFNKcF+tcnawFN4QAkOTwS/NVV678mzTGunZK6jipaUwq6Wxh92ILKEN8wKG/QCMTTp/8031vqUmhiAMYUCEFgYzjaCUC7lVBSw1N30WBa0cdiM3+wPTYeLu7jX393e8PN4T4olxHNnvd4zDaOGkFlYyIT9Txw2tGCS68oaCE6v3o7TwgVVeRmc8jltfGfYDz/Y7bpPj85PyMlVepdJ0YxqZubnZuyCjZWHpYnDOepynEMsT213b70mD2O712uj62uj+wf4X2/QQz7rcRPT6No95HR4AlSvrrv/r59gce6ns+3ZpxU+eowXt+jdp385Dj9A1gGKTvfvVNshmu+0y3Wy/HufBvV0AnAqLNqmecV56osaqLfYuEOVLDVCq0mpRNG9IBwGXIAIWcGLrLnQBll9ndA2bFtDwpvUP53ULii5eimyAxnJ9y/zjxN5L0PHY+u2y5Xk1BF9zJafMdDqiteBd74wbB8Y5xFkdkf6cc7aS9i/ee4/TNHF3fwIqPgzsdyPBKWW+JwG7IfDixTNqLhznbKm92fHq7p6kgS9OiVdHR5JoVYT3e25fvCB4G9mmVMhu5NmLZ7xfB+5yxL16zXy84zhlUlVSFWq20MRhNzDs9txNRyqF+1RISfBRTX58twNRTscjw7DDOaFWJcQRH3eIH6nEZsyEcRgoKRN2Fk75/ItPefXFS569uEFCgBpxcUfc3VJ9NI/SdI/JxlooQ1wgxh27XUK1wOk1aT618ERpo9gmHS/G10hzptRCHJTgPfM8URXGfbBnEwZiHHHR5OJ7uKe3ftfef2npvaWUNaOnt/9mnKyDa2wlkaWN90J3K7IXwJmnrQGbXArkZuBEMD+cZYzgTJfEOyEEa39xGExTRxWtpYGkbpSlgSMzvLmoVXN2fnGPI6aAXHIhe7d495ysInYiJk5XihU0TPNsXjhnCsT9/k1sbq37YyC81/fZcDRUF26Nqq7hopzaCFKa0KByPN5zf3dPyhUXIsOwY384MIw7SincHHa8fDlwd3+kLuJxpseipZLVeCZrqjFM05GaI+MYGWKw99g5TRgZ2FROInhT8t05ZXSwFyH6SsCjJXEqgi+BQKSKw/xt5rWr/TVXa0OXtuOM8n8pbHFlehNQeRqkbJrdugHbLd7Kw6K6qPz25Y95Qc7XXwCdtwImT4RlWp9qXrC31zx5DABBI9g+uC7O7q09gvOpe0778+3bLf87/70cf1l2QUW4OPzZMbqRlPN1stjQh579x6YvNUApteI73ZkVGFwKrNmyNm3eQg+XbPftffl22i57bP32lS3ZNG/gkqzbcjFvo9ftieQMCSki+uTxHh7z/GEYkdFIr7nWhWkuAloN7Vrc3bPf77i92TNPE3f39+RccS4yRBvZilRqnnj+4n0Gp0RfOR5nTqcjcdjz6lSZ7u6Yi+N+KhyLZRkQHFIq98d7QjBCbogDILy8f833Xp6Y50zYfcAoB1L9FDcmZDi2UXEwwS8cx7kyJSFXIVWrUzLPmRgHcqncnyYO+52FBYqSBKpETrkypErIym6MSPQU4PDsBaoZGYWshc+/921uDl+3EboPDOMNcXdDUbGKxSVR00wpMzkncp6Z5pNlhYSB3W5vJQUQQjS9i5QSNVfEKeoriiMQCV7w3oiQIpbueri5YTwc8HFEnW/G1dq5dX4tQ0Dt/Vn4xrxIgoHyWgslJZxrqbVeNinJ9s8ZHmHREFIjaGatmJemZetgBRRrMSVbO7cZuRibgmqIS8doqqy1yepb1tg0zaa5gzRc16/bmyer2rOp2aT+c8mkvA4+nDj7/mNYDIDzAVELVaVpwkeb74X/VJUQOiCyA9VqZOOtd9KWm16KSd+zDDQs5diKIfpWMLDUO754+ZJcKoebZxZqasJt3BxATI1WnGUu2edsHZBrGjDiO1hTyxIrBe8tE875gHqMg9WUdWtWiiiOiEhEKThmIpUbX/D7HaqOXEAoHKsnYVXAc2szDlkys+rGEF6drgCUxzws7+xBeYvfyEPp9qvbqT5QorV/5WL+OkD5UYGUTpBdl72bcizwdt6VM4DSfz989pc28fz5Pdx+e87u+OiPZLG6yyN65F38kNOXGqD0F3xJfO1/L7d9atljv9+07WPX9cOsRxXLzNgsYoNPmhrn4+Tgs41Xr1oDZLUVmyspk2frCFFFnJXFtj8Vp2LiXc7x6tUrvPfcjAeGXUunrUqtCe+8SbTvI04zZT5SFYbdLaUKL+8njqlyKsJcI6XJqGuppHzieJo4nUoTJ9ub0JeLHO8Tc4aqAXUH3C4TDolhetUqMmcbzZfClCu1CpUATgjOUfKRl69e82z/jDlVbg8R75SMqZ++vLun1si4H7n1gbg3TwvOSMZxHBn2QvTCp7/0C9w+O+CC4vxIloio1bDxmpBhx1216rmqCTRbWm8xzQxxwmF/QBXmTvB0unQcXdQs5Yl6/4qUZsbdLbsDuDA0tVohKPg4UNWjxYCrc80vIg7X9DyW1MW6ai9Uaw4GelwPd5pCrXVe1Y7VO/f2V1vYT1QZQoAAuYVXfPB4HLkqlNrIsSb2V4ols7qWtu6bpoiIcTW6QFvwcRGvK93djCntai4ttbguRj3GYACqGQEDP42bI97UYB1GHFYDGfNsmVFGGLVwFvSCiGv2zlp4cF3fScW1Whr3Qjp1HlxgGB3Pnr2gqvDy9WtO05HPPv+MlK0sg6p5Y2LwrWKyp9dnMcBkBQRdCCgmhV9LIqfE/V2hlsTQFHzNSyx4G2VQcwZxqJjOhUNxUhkcFp69HXAhEu+ET07CKcOcSxuJC6UdT5sH5UnTcpFl/NAQPe3heNf5M6AAIPXxdRfH2IZ4OgB/G2DyIwUoeh2gPAZS4GlA8nDZCiwW4HD1uay8s3MwcT319/KY22fx4D4bVNFr70I5b0/np3mr6UsPULZ/+++nwh9vAg59+7cBKZfTte0fW6+11QhqnpHVN9Lf4vUPb7k3uXCUGSppnhVDIpdpzr2WhIjaKD/NzU3vcM5UUBXzMAhGUKzVSszv93vLMmjVdxUh5cRuP7IbAkNw+EHYjTcM3IAI3/n+F7y8m/l89pxSQP3AqSmPljSjKk1hNJJyperEnAtFbSRdqo3uijrLMCEwHJ4R72443Z+oZTbXP9WUNMW3VNpMGDzD7sBwOHAqwudfvObZiw8Yd548nbgZd4gzrZWsjlQFJBCDs+rHLSYvdWQ3Rnz4hH/97V/kq1//Oj7ucW5HnRJeJlw9Ep3n8PxDNGemnKlMiHcthAOnk4XE4jCgOEquxCbrnkui1IRSyXoClBg93oOoUuaJ7ALZd34MBhyDpSeb7orF2F1JUAsqjazaQh+oQvPGOAfa+CMl5yU01PkbdaOSIc6qLHfbriKUapLw0TlKtbCJYCRgKyAY7Cgd+IgnuNDq+DUPQN22b1mAQmxZPc471AulONCwFPBrPqO1LkpjmpbSAFct5qEASgFKbsePrfOv5gVqACzP7bk4b1L9YZXDd87jQ1d3bfcjq+fFvENGXB52Ay/8C6vdlJKBhpw53d8tRMZhGEm54LTxehqfBiyVOvoICsUJQ4g4sfdymieOp5Pt4z1DHBiGARFv4bySiKa7j8MRxDyjBOX56GDwVKkUCi+PSs0wG4XFPF+Ycq3xeSo9DAhseAV63ittfqw273oI6AcBJdvfbwtQZHNNPcRzDlDOOSjb35cG+PIcj//rQOP6dtAJ4fUCrLzZe/IQhDz0mpwvhxV0nFuQLS55+IoegpMzG6T9nyy/Vdn87u7FHrnYhCb68fqHenG+N01feoCyMKZ5LFzyEHhst38MyGznH25vo46F87P5mPv8Wv5nAz3krClYp9/cvGdtpvUPZ+RcLpc9bGhryOppkJZbKXofLKtgLplci2XztGsK3tzzWStOBlQCx6kwjoHDLrbOVdjvbxiGQC0zU1E0Cbtn73F/mim+kjiRXUSDMGULBZSmiVFK5jTNoCdCPBGH0XQewoDzHQg52uDcXPEpkQqoBKsIHMy9X6pSxbQuBi94v+NwO3Lz7Jb9GHBYBo+6iPMDu/0t3jmqel7dFZwvpHzH7WHHbhxwFXYRiJ794Hn/Kx/weqo42XH74iPGOBAdTPcvKac7jsd76v0RQRh3e1PRzQnJMyKmxzHNiTnNxOipjevRO5fgo+mxiBAGM0DRmzcgeiF6cFSkmNKoFhsxdxDSR4iujaL7O1//NY9CBaos3440QKCqSBWKb82vgWDbxsjFzhkwDdt+K5VWiJDGXak418FyI9rVTE7V1FqDGWaTm7dryEwtZOKaJ0jZDtdLtZBGcJYhpqpNUl42lZC7K9pCWcY1sZDSsBsZw2D1fcrcrtw6zJSSPbf2HKSnYLfvvCa7WecCIQ7kWlvZAXDtGZoWjZUhGGIkhmgqwO34x+PReC/icK1Cs4Gw0PhQmdM0Mc1zA2FYeGgcNt6mZuBqobR/IQZQ1wYu9s6W8h9qCrPBFQ6x8N5OSamS58osMIsnS4MjDbwK3SD2UgzWYV0bHV8bCD7GUXkMgLxpm7NlZ1bxyqCUZdUDYLH+fjqLh0f3e8yDURd+ia17GsxsAdCbuCfrufq1XnpOzq+n8XE3w9v24rZgQN4MFrfLl3PQvarrvzW004FMP+vGRva9uzHk8u+bpy81QKnFRgHQHs9qx+Fifnlk5+9ra/vfYnulB6OXmJydaUOGbSv6PlseiWzXPM5Rsd5mO9uHMdvf18HHm8iyXYEzxIESI9N9S/H0Jr+dVanZlFvVKYMLxg9Rqymy2x0YdoFaC3EcmYsy3U1WzE2EVIVXx3vu7idevT5yd0xMyRQ8ay1M04y01FGj2TjiMBLjgHcBNwTTtuidfynUYumoWdU0W1ygqOfulKjpZGqmMVjl5HE08OQDLgwcjzO7GPjq136M5zcR0cz3v/+K135mN47MFeaXJ37huy+pOvPRRx+yi5EYhOe3ez7+4BlfeX9P9JH3XuzRAjfP3kNLxYmyu3lGkcQ8veRUZsp0pEzJwi1dAVWMp+BDRI6vSdmKw+VcLNrQtExiGM3r4oJ5LaqNjqt6VBO1CGQDAVqtwq3zwTKS2vNn4VtYG3EdvHS1x2boepsQY6wuYlLbNiiLvH1vco2K2z8MVURMn6ZUpagVudNiKqhdVbcWIZVMUYhqJFEremiy9ybznlu4Z0BEKCkbEBCT5E8pm9T8GFsIKS/y8x2ELe1epWmqiHmZGq9DHAQxcGT1iKQV/uuFAz3irUvMOTNNpyVzKQRTfe2FH61UgSz1d0IIjOMOcEyniZpbWnIIDONA0crpdEQR9vv9kpK93+8YhoEspj1jui9Wy6mTf5XmPdJG8i0Z8eY9Cw3sgPWF9l3Ztk6tctbOORiVPMN8yhxPlXs8Wh1Fe0HBiqp7YASbaXzQRV0FLKvVenS7x/Z94+91GH+2bruNewuAsl3+YLsryy+3f7jvFmg8AVBa1tV22ZuKAtrvLUA5B0Hr+u5XXN/ZVRDwxHO+tBvXns3ltZ1t9/Bs6/SOYZ3t9OUGKHV19W7cB3BpxJewCOdPcjt/sf+17XV76B5K6aBGz+c7wukjUduGDeqR8/mLj1au/Fo8NVduU+Tp9evH7WwkWGZ6aCcOIyVP5DlRtHWGDmKwdNZpmhnGHfvDDbUqr++ODEMkFwsKOB+YjtZR12pCaKUaTyHhqAJ0XksM9FRHc6Pb6HuaEyIF7zM+h2Vk3EvSe+/xuXDKJhbmQ0TCQJpOliaNMo4j7733HuN4A96jfo/f7XBx5MOvfJUPX4xEV/nw/cS/+vb3+N7LE6e58vrVa0ARD9/69BeoKZkOB8KLF7f8e7/+V/O/+XXf4Ce/8XXuXt/z6fc/5SsffYWUJpzSjB1E78A7qwA8zyjGsXDOgQScVm5ubzmdhJwT4xiZ54SIYtkzGdEAsdVMypbdo809PdRCVEVqNS9KNKImbeTf20AvbW5hMW0j46bD0J69XHSM3WAuRb42TXn1UADimpJrpmilpyt2zom0dOVcFClNj0UcWj2KI+dKKYlSMr1CcSdsl1LIOuOcb0TjZNcvTT03WBjIOCe6ZLyo9owbu49ULOMntoKUXajN2tTKM7m0nctIHBYyb60Vl6z+zjyf7H16j1PFh4jDsr7Eudb+tQnbmYChD4HD4YY4DByPJ6bTzOtXrxHvuDkcEIHh2Q3jbt8MZHv20nhC1lPgvbNMruiY5zVd3Cg1bdAkFt4R1/9J036xysllp5ymyqtT5uWUKVnINZCXOi32PfcRsG4Gv1cBycUAywzZ2VZX+p83g5bHAIwuI0BdAPi145/tc9bO277L7wuwUvtxuVjfjr75Fh8e++l/1IchnqeBz/n1Xb+XDWA5e27XPBXntuHh73VYfn7uBn4bBOpRHvo5rcH8MBjkyelLDVCuod2nwjhnSHEJl7SeuO+/QSVn+ia0Tfsi7Z1Hu5b+/768HWabuictH7xn4Oj5/868IwY6uuue5ZiXDexaevLletXzekVLBdnmIi+wjCpFepaJaaK4quxvbhBxvL67bzLownR3JISBaZ4o5QTOI1hxu1ILuWSrVSPCnFMT74KUCyKOIeys8FvzMMhmJIgqKc2oKnPKzQAHy3ZwSnGuFTs8kOYTo2pL0/RMUyJExcWRxMip7sj+lnh4wXsfPsPrRBgT99/6Hv/jtz7l9SlTa+H+9Us++eRTFON/iIplaISBn/v5f8FP/9Sv5Q//B/83fuyjH+fVy5dMxyOezHx6xXx/R76/x+XURO4yJc+UNFGr8UtyTojQCuE1AFJqe+52/TkXfIjLR1lrsbBXEeaTcSpqgRoLzieYPa7xJVpcBhpJ2DVg1A2dKJsYfdf8aJk8qkvKbXFWLLI37FpW93FpIMbCCAB+1Q9xfQQtaJUGGHq7NYBT1VJwXFOnHYIBCC8GNkrOiPr24aw6K955go+Nz7PK6/e27Fuqscn6C77GBfQ459ozrwsoCovqrS7XaH1EpaQZpKnJhogET/BCycWqFufEdDpxctK8KiP7/R6A+/sT8zzjnGO/3+ODb4UrhThExnHH3es7yhcW9ik5tWwtMV2UcVy8JlVzI7M3/0at5Pade++W+ylV8I03E7z1LVoz+JXLYzyiys1O+IhIdp4klYLyxYS1rwpoXjuXFgJ7DKD0ZWd9rV7fdp2/XuzvctmjAOWRbc633wKR9a/9e9yDgq6D3cdBQfvX/UrvAlAayjGs8hgw6X/lwbPtGVaLAOLGLrSnz8WIm63t2piZdl+Xvy+f+Qp+bO2FyvBmD+2D7cXXJhe/bU4u9nub6UsNUCpwwbV7qH9yNiObj+g8dNJWn73IBxwUtuv1AWDox+jH386vy1by6uW0nm8Dfs4uoWm9LJvJGSel77Tsslmv3aXTPpT+EVgaZdkAPDOMxllwhNiKuBWLodMNVIV6PDZZ8ohi9Vpqq1WCmGG4P54WA6qqHG6esxtjI+XSOmOabP72QTlUhXEc6UPKqkpKdncpzeSqhLhntztQamYMwQoESkB84G4uEIVhhk/uZr4mA89vbvkX/+wf8//9Z9/mFz858fqY+OKLTyjzkTE4nt3cEAYjy/ogTaTO83f/h3/KX/3r/w/+gz/w7zMMJ1xNDD7jZca7wus08eqLz5lffw7lRM2ThWdSMg5GnoxH4aMVo2ukSyNkrh4EU4PN1Npl52kGdQSJTQOktIYlaM4UkcUzIL4roth7dE7Q0lzAZyn5ZrhkQ2zsGXEWBuogKp23X2lcDWmZL81j470g4sFpAzOFotlUchcU30aQsta+6eBCtVIdmKB9xfuBsVUt7qGinMsCTPrU22+MpjArTaq/NsDdM3y890TfSanSUpd79eFeybkuBc96deEebXWAF0vr9c7AWm78FRHHMAyM4wBiwngheA4HI4ufTqcm1GeVwZ8/e8Zhf2jKrVbPp3uMdvsdseuetKrPAq3ScW6vyoBH/4ZF1YToWjXmWqGUhKtWGNM3fSEn8MwJxUcy1s6cwBcn0Kok7YZv06e0PvEaqOBiubA0rycBR7/uh+u3Rvr6Oa797p6v+sg2W+N/DZwsnp9HgEmfX1Vbe3/6rgDlTZ6Tcy/Pei9dYK97Svonu/V29L/XbUt/uqiua7e/rzzT5Y2cPU8773pEG9LXNvgGQHQdmPdGoash+/8fgNKrtLbp0vDLBYK4Rnp9OP+m7R9f/zbnWJddWb78zz6YM57AZqP+gVw91yP3u1x7a91G7jNhMOMsGBmyKzeZ8XGUqkxTAvEg3hjpjVsx7PZNzVNayqgg3qHVMnymOZtUuHOMu4HgozVmzfTOyDlP6NkSnUtg9AByLhYSqGaAHALqEbdHxOPDwPHulZFOSyHNE+PtLT6M+BghjEDk0y8m/tV3XvONX3ngO7/4mn/wT7/L919VfuEXv0fFtRRejw+Owz5yuBl4dnNg3DnGnYWyShL+zv/rf+D//vv+fWTKvJ6+4H7+jPnld2F6ja8JXybKfI/mmZKNJKtaEJQYvGW8tHowBigita6eMUvHNXIwjeqackKmiWEMFlJwHueCeZ3E42NsBqiFklzz+190oNT+Tlk4GwZGQDVvlrdUVjF+SexifdXmTSRFWrzfiJcpl5bObARNA6QmgDYMw+LdKMXE/nq1Z8ERnDSujUnEp5TMkyKYHLzvHBIBDFR47y0VXaxOzjzPpJSIOTPub4hNDj+q1QEqJRmwFlkydLR7jEo1wUIVu97duIS0arVUdm0ALISRYbQ6SPOcmFNp5/+CYTDvB+0ZT9Np4cnknDhNxkspKRMamOm6JyEYQdhUdQul0J5Jk+h3rvu8VgXhsNZM6t+3OIdHQaxeTy2JkpN5J1s2WfCOZ2Pl41ulztq0OqyfeJ2UVLtxbsb4CQ/K5fLHPCiXy97Vw/KUB2UZWNEd4de3sX+P66D0gdtjnhNgA1DaMrHn9DjgWIGNNGTxpsyda/e2wU9tW7vjdZdzT3v3kF48xNXj8eD5Lr+25mMDhDhDFQ/e7xodOj/eZt5tt32HeNCXG6BsWNnQkPRZiONayOPx411u/+j6/iFyebzHawGt7+9ym7Pd12OfhZPOj/n29/tQK0VV0WQF7azGCZSaEG0MbDGy4JIdUa3kOQ6ct8wDH0xboYmmNiJmBbEMoeNpwoXAuLMCgSJgBWnXei79mhbdCVuwGNPUwNM8z8xzXgzf/nCD8wP7mwF8AOfRWqwh+4GpwGHcEXd7hnHPEG+t846R/88/+5TXL19xzzPuy3dIZWY/7kk5453j/fdvuTkEnt/s2A8DQ4Dnh5H704niAp99/op/9s//Nb/648jrTz8lnL6LnD5levUpdTripBJEmbVSshkHVSOCCljWkCtrobsGMnoHqc0r58RAQC4FqaYt4kJGfKFqNHJx77FytXAAHo+9C9mA1+X9Yzu5TSHJtX20XDORJiLW+Bys4l2deFtVF26Lqs2vIRQlF/PUWDjFkbIyDHUpJGjvuZg3pNUXAiGGYVFzlRiptVh4D/OueW9A1y9eEOgemN1utwAXy+JRoBCcYxgiQl25aqyaJ6raKl13D6LF2E1W3zMMkerc4kVyThjiuDyT1LwwKZmY2zDExnlRTqfJMtSkZxp50Iq2DKA4trBlAyghuAY+TfxNEagG0GvO9l4bkDfKidU7ak0FpGXvOJaMJCeKaEFLpn3ACIUoyvOozLvC8Zh57SpHMME3/PJuae+7P+tr0zWAcrn8TYBlnX+YRnw5/5QHRa7s+9BD8bgHRS62v7bdw/nrgONyH+vXdAEsjx0TWD0dHYgs89sQ0Pmz6RZCt0ih7dePoboc/epz7j8fvK+239lyvVz/4NDnh9iEA56ywZfTlxqgUNl0PMCDGM/lPOfvjisAo7VUecN6dB35Lmu7k2LZp0HfTdxlcYPKivzXNRfgZtm/H/+hh0SvzjejI6sQz5pCaOmk0Q/c50QtqaU62gjMEZEqqJr3xKGIV5PhbhLdFXOhiwjeN3c0hTQnaq3sd6N5CbzV5hGa4JX3ywixA5MuJ74NNYVgRd688xwOB8ahcGrHnueJUidEHCVlvAh+POBc5OaZpXaWMpNSQVwmxkoIJmX/xauZaRbCcEscdjgvxFiZj/c4UT77/me89MJ+CHz0/nPQxPfGPd///BWfv7zncNjxyaef8++8/5zy8tuU178E+YSUGTRZanGtlj0hQsFGbbnM1JKRxhGI0QrJpWJaMFp7DZKK5koBgsNCD97jXAXNpkQrgjjFqRLcQPBWF0e8LffNyImT1dumlerd0kFy1iEKSFiVT8TSgZ0q2dCrET/7h7CR2u5ZWCrO1Emrkop5NUs2hVmfKzFlfDAtmxy8lVBw3oovV7u+Oc1M84QpyYYltKI0gJwmwBxEMQ52j9LHZbrwSqBQU6KgFJp3phUitK/KQkiqdqxxCHhn3joTTzPPRa6FIizeG1XbBjGPRAye3TgsdXJSmnACu3GP84IwkeaJlCvDuOPZsz1D9KY91Lwjvb6KdxCDVavu6qPeWbp5dI45zdC+Ibozqd178OZFc33wobVxi5pX0iuqCS1i/B419eZA5XZU3jtUXk+FOUEqDkphVhYNIm0dlmpBNloWzdyzna4BlLcHJ+uRtyN6W7854zsAlKueiMUIGzePTcZbD+89BkquLbNjdkXnNwGVpiTbPNmGizaj3Rae0X597a/dd7+78z6eDSC5BCfrdV97B+d/3zQpa3+yHnMbUZDN8mv7vxsw6dOXGqB0suc6XXpA3jAviuiV9bo+0PMXuFkvXCkiePmy1v162GRpRAuZ9hwxPeTFnHuAoL9oeXS+f8wPQkTtQxGkVe2VPvxaR/JYTH0Z1aviG/LqRFcfh5atYWnLfSTunMXiTd7disu5NoLsZF1zHa/ERWDJtOj72wjXL9ednYWKqlZKttF9jAMAc6qIj4gbwAWrx1IT4jy1wnGemVImppmb/cE8OHHk2bP3cOI43r9GsMrBpylRVTmdZva7ESeVz159zmevjiimI+KdQpkpxy9w8x2aE9QJNJuaqppBVRq/IpqI2n2aKallSTX9C8toqZv32DwoZKgzOSUoAjoiKAFTjS3F9EKovnm+WJ4/aqEJwbWq2eejt/XfBqAs7au79rcg150p3jpt41yxDBEV2LlAyYVpTlQxb5wLYXmn4sTACMKcCqVCHDy7cccwQq3ZvHe1kooZWAO/7iybJqWE60BeIMbYQIkBXAMK85kbvV8DTV5fpLYQWReHW/k6qjYsMJDHsn8fyYqs6didG7TfmfbJ/f3R+iJnacTjbmTYjdwdj6BWQXkcB4J3LfyTLB27ZszDJow7EImAGPAQQZsns5Ri7aoUskKIYmn5zuOlZyVZ+nnFjifOwnLa+zlVHNYenShjgA9uHLU6ohTC0Uizrw0HM2cltbIGgrWthQfxAJ6sg6+nAcgPM//QY76ddxfbP7bt6jVZ+7i38ZZcHvvBNm8AKfWR5evzazWylmu+/ncbJ3kMYGyXP/b7TdNybYshPAck24Iy65qHQOWpqMSbpv8FAJRz/YanOSBrBo090c38dhs4BwsPjidNHKsvU7YkoMfeh8j2JetbXO9T13DZAB5vEAYg2k2p6VUolpFRiiIScL6ipX+wdemMqEqaFfGVEJsqaTMAIlZdtSKknBnHcZPOaXyCEMJyDYtcuFjNFx883lvnK84v+hidwBlCJMZAra2SbsrczSfSNDNPR8Zhx27ckWohBAgxGkiQaN4eZ5yAWgrzNDGd7tjvbxCtfPD+C77x9R/ju7/4LxhvRrwPnObZROEUvnh5T82JYRd58ezAhx++4GsfvcfHH9yi+TVaZkqeKNMR0bwoxqoar0a9kmuxMgLiCHFERchpIk0mMiaNE7HqeNiz905o2cOUmsm5ebC8Q4jQsjSgUspMUQ9ZFtDoxPQ/xLkl66o3SgOf0Eeqa0cpy/l6hWBkVaHVal448bSUSZqUvWUMESL7EBl22sjMVpHYsmzMQHtv3JWcTLhtqhMxxqV9OufZxWG5pp6F45xjHEcL5cwT9/enJTQTYxczK5SS0JbhszUEPevHOUsRpv228IsQXTCVXFVTn+3gMlhYagsi+2jdt+wYsH7I2rlpihSUcTfywX7gZrphOk6WiRRMADGExrUpqRGGjZdVin0PWkwgsTZQX0rLICqFHjIC8EPzdPYQVdPAsXYYGvDx9LpKIliGF57oFMTAWxBhEKt7JK0qtraQXK1Kk6uhUqmtzAbycKx8jYPyowMnHTw/fY7HwEn/++B3LY+ue3K/B9spysNwz+V2j3llRLfgZPV8P3we/Wnw8AUgDxaeg5O3RSdbz8xDCLIcD+AJUu6PYvpSA5TLF30+bZ1+V/bdbHW5Ymvvz9ZL/wh1MdB2HbbsmmDa+fU+BC+X216bX4zLxbLH5msf8bEBJvQQEYhWcq2kXIlxhzJRs6lY5lKbomwDK83YuQq1OKqzjBHBUYuasJsq4zAaoRAIwYiBC8el5HZ+8L6/l7Vz76Pk3tF672zkVywM4rzxK1Qqz2/2uOc3oGLkTBHGsKNUYZruCXFcQkwlz5RaGIeB/bMdtzc3lFo53k0cxsDXf+zHeW8Pab4jlwp4Pv3slWmEVMhJuX0W+eqPf8Tz25Ff8+/8Mj5+b8f8/X/OdHzJUDIheOZpJpVsRqoRc7p3oqcUg414YwRVG+V3L1CfFqEuZ9kx0QeC960AoFJSYuaIKxmtO8C4HuICLsRWh2f1PF0D8KvHrIOWlQOkYJyhWprmQ287unhRvHe49nzEV+ZknoclnTYa4Bp8YPahcUOccSdajaTDvnnQ8rwouUbvWhG/9bvuJNgOLrSuabfehyXkZ/esqwDcBpj05wprWHHpN8RKJDjc4oGqpXkFMbFCEcEHdzYAqY3Z7L3HuzWdu6qAt4yknGeC94zRwmW1dNJrT3MWcm76MnQ+TFO51cJcyvLd9EynGKz2Ux/R1lpxtZhnsVYjLvcUc+mE6C7eZi9ZRMAFnIPRK96b6ixVyBWO94kv5ozmaJlkqgimYaNVUemegscBSge/57/fDFoeGO2LELYtX4+1BdoCFC1n+1+e4xpg2OoBXV7Lm0DLw+M27Zj+r2+nD9ctd9H6iW2QagXDbdACsKQX9w36fpfT1oPxLuDhbb0cW8/Zv1lwAl96gLJRkl2jGEhH95chnF5fxWbYfkgrKGgNvnUC28d/WSX5zD13hQ9yOZ1xRDZS+UvYp83Xy11FkcsG1LwxstzKZUNpZEDtcKB1LqoNgAhx2KNaSGky/F8y2iql9hEzQM1t5OwLTgs1nShVTUo8BOIwYjVObESm2V7M4D0pZ0RpqaTtQ65m6PonZC/MuBsAaTpRa2EcR8bdSGgyH/txh3OOOWXSnAgOciloSTiJjNFb51kTqBCjI2I6G2k6cpRC8AYSpMDz5+/hdeZf/vPP2O333N7c8vKLO4KYxoT3lo10d/eKjz7Y83/6P/7v2PvMZ1/8IqMrHOeJMQTiuGM63VOSiZWIi1BLC39Vs21dzVQdMQ6klI3b4bwRV9XCN9pCDaVWyEYqHoa98WjUeCQlzaTW04kz0rLXVmV3iAaUXOMPNO9MDwNIGxmv7VFa6vJaadV54y50ifU1U2RNBZcGUr2nqQRbCqw0gCCtbYYGPFOrojzEQGxAaggHQpiXkaxlvdh1CaY90kM31TnzRmFps9C0SmIj1oq27B9ZsnD63x427BWDwUI6RlbuKe6Wntu9T9AAjppBXom19o4QNXDirUYUaoBfvPF/tFbmdCLNMzUbwMq1E1nXLKpt5o8RW+0aqqwA03vPMAxnOjA5F+bTCQ0RF7y1l1oJPiDRPI4VCAjV1QVASlAkWJaVD4FApkZlX+F9VU4pcJyV6WVhroVcW6kB1srUS/u87KZ6z6PX+8jrHoGH4KRPZ+BatXffS1+nNOPff78lyXYBFbryQh7zkFxb9tj2l+u36y6LAG5u6+I6179tWLnZpluL86iAPYvL/1/+XazA+Qm3Id6zX1svynaZeW6Xl9EiEZdH+FFNX2qAUnStO7IAjwXUNTByheOhcI4CZH0Na9YDF+tXtCrLic4Ofbb9A0AqcjbC6G/3vHn08JKeu1ouZtcTnmcVradqjVGbW/4C3iimbOp9pLSMnZqsRP1SULBtabyapouRhdQ67t5ROafUYm5mxFJngVZvpS4CatBTVd2SGdCvyTvHNE2LUXEOvIi5m9NEcY7dOODFyKdhcBQ/oGrK73fHCdXKzeEZRYW5WkG6zqspKOIUI6xmbg6O6ALT3czOv4fTX8Ev/OtvUebEs0Mkp4QDvvLBe4QY+cYv/5if+b/+Tn7D//rrfPoL/4j8xXcZZWI3mBJsDJYOm473OC247gbH0kRryU2Poy5VfEOIaKuJo/TME4fzAhQjWkoDYNNMrRYm8q5rmhRKnhkGR/BWvVdabZCKhcfMa7F6VK51liIY+GzeHlO1ZRmVru2J9u42+6p1la5lpVVVCzmV1jnXtVpwv/88z8QYjD8iFmL13psHyDlSKmtoR8+74urcAoQ6h6lnrMCacdLnlxTentXSw2RtoJBLXkawDlnCcW4DIEq1b8J5j5NAwcBrrSs/JRfLONIGIM3LBJoLeU7knAkhtmPb8V3zGo7juGY4Od+KObbepqVS+042L+t9mgR/JqWZIQ5LOr9l81RoWkalZKgtnOUEaqvjJB6x1DqCq9RQudkVPn5PqDoivjLcVT4/Ka8mtZITat3mYnwvuqR3BSiPb3dlWQMoT+2ny/+WXdbz2pM7BwkLSPlBQjq8cf05ULEnpA+ub/VCLPs9MB7bZ9NpCec1b+xQG1HSzfZng+oHA931Ys7fFGej/i1UWZIvOrVhQY6bQz7BO3kXTsqXGqBs3bh9Wm9+k756tr7/ur7fYw/vqqbIY5NIk8J//BhPzV9m67z5Wh6cni3yFVF7GsshHSIBaWRB1UKtCcRkupesEm1AShWtmZobmZDGExFvWgsC6jwhGAlQRZpbvulqyFavwf65fouC1VzRym4c6R4e552Bz2rKq9kpmh0xemJ0jINV9j2dEjUquVZqukNwDH7Ae8us6Ix5i+1XvIdRlJvdwE3wDO6GX/bxr+Cn/7e/hue3ez755DP+1v/z7/Erv/Fj/B/+9z/N7c2OH/v4fX7svR3z9/5H7r/7P7ErR3I5mtvdOyzlE8QHNGdynheglUvFxNfaNs0ol8a1cY17Ay2jCUVxFLVKwOJcq7ljVfysoJ4VxJNqpEitGSeRIXrCEJEhtmKLsjzw3hqMDGpCM/XMc6KrFHcjn2vL2KkLYjHUYv2SgV/nhSBdk0PJxQBW10SZpml59/0+59kAW3Cu6YsE89zVNdtm5StJj2jQydMpza3dO06nCTgtMvYLDwMWwLud76Eg39o5mMcitEyYkjK5qcmKiOmnNJ0X56t5Hnq2UM04Z5okXbxQVal5ZkrJUqkV1Al4q+jsgyfEsBSGVDVPVYxDE5qz1KZcC/g13b+/u9rSsp0IY1w9Q0YYtuFabZbaNf0TU2q28BrSNWA82qoXiyg+KINmbgf46FkwkFkyJVVmsYFJrrIQwHt3cuY13vRB1z0Y1zwIT4OU7XJZ3QqPHP/6vC5o+9xbYgDlnDfSt/9BAMq1bdbf556Qh16UPqpt216Akutejcu/D6cttHgIKbfbXf+9zHfw02kCS/+9vpM1CeRHN33pAcpjjXppDXK5+C21Tp5YrpdutgfRF324kM2Hton9XzvAtVs6c6joCkJ6x/3wPOecmH6W/ttpr3trhdxoGSTWnmUzgtbl3KoFSqFqU/f0xjErtZpORRiWEQmcx/y76906fV0MD0ChcjjsW2dd8N5CAf38XgTvzFszBIEyEXwhpcphCDw73HA/Z6Y5c3d3R6lCaR998J5UMqqBXJRhHBhDZNCMj6ZzMgbh9hC52UVejO9z85u/ycdfec6PfTiwG2CfPuH4ndf40/fY5c8RtewkSrV03JIbmDD9ipxP7f47MGi1ULQbXdcImD1sUFv/ZEPUEPeIWOgNFasyr5XQOlPLeAEVC61MpyMpW1HFUVwz/H5TbG4FGv1dbIF8N9xVoJbuHVsSjxfgAs3b0kJG4qXlGpsRVlVclQYUQFudGKk9jbcs6coiSt2IpWnLEAthDdF0gOIb2OpcDyNPr3V2DIis38SSUixrmYeuT0LLdCm6hq6cCEWEGEwkz8BWXvqXWlt4oSp417RfGuB0llF201RjVc1rMU0Tx2k2F5+YOF1RhVKxCJX18JZe30bYTohuIPqARCXpvJSfcM41b1UDahutIgvh2XOqYDwcoJey8D6g0tKGMU+Q8wGkUlKltMFaFE/VxLOYqTeCFkcuhakqkyqpGg+ldHXBi+nSUF+GvbfVhK/t86bjOf0BgEn/XRXkmgelE6Cve1L632u/H5vfDprPj/UYp2Y7nXvEz0BNX9a3gx8xHHjDJN0rb+fv3tatp0Uu7OJT7/dtpi81QKkFqu+GdwF3ACz1bq4Ajo4Ez8MeZ96uNUtn8UYo506R1gVccaYo67L11OvZ7J1t6+NsgYvNP7xmNtusxLNrRLK+3QP3Zwv9bK6EguDdSJVsqaBixgKE2lzfzkkjH9I6SY93AUWpNeN9JHghiFLzRFHwPuKFpqVio/gQzEUvooRWA0acM9DReB/BWYryED1STflyHDyezBAFaTySWjJDqBwOAyHAe3Xg7l557T2vjzOv7ieyBlJ2THOyEatW6slRxsB0r3zwfOA+v4RdRHPge790z/3xxP7mhhf7D/mx9wbK/Se40ytcukOnV4yBhZxbFw+Ch5waUKk4aUJtFeONqABmKJyrzPOMOE8c9mbFaaE4mTHZ+4J3gcGPjWNlI3lcE33za9hCnIXqRBzzPJFfVsLxyDyOjLsdYdwRBtMd6cTY3qku5M5qIMRUvoyf5NS2LaVY1LmpvZa8dsgd6ETvCc6RNJvgsLbwq5gAG9oK5U0T2tqTatNLUXuenXCaS0VqaZ6jNcShsIZgQhMoc12YThqYsWe11LOpJnMvau2r6+suILr/a+9yKhkf4qYTMbBRSws9Bgtfipp34TTNrdJxIAxWS2ccRsbo8X5ASRyp1ALio51fC9N0T87GKwneG1HV2THTVHGtIrdWT5ozJc3kzgtrtYScmIBcLsajCDkQ644wjAZgtXs6ejim9wd18Rx5FyGYWnHJCarJ0/ic2IfKhwehJPOKzTMkLZYlRyPdGkpuPUl9Cw/K9rc+WL5UI27/731cfx/16nHefL5+VK2KbtRqRVnOcVmn502/L8/z8G/fYitHv91v29+fg43NcHJz9dCJtNe9FOfHWsAD67NeQjMXz+V8f734betkyS9i9aYsx/w3B5O+3ACltuqrbX71LPDoA9x6QdoC+6Pb+Tb8sw1ZXzCbZfbjcW+MnjWIa5tdvtglxENndXOxvgMNuqPjDBz1xtOv8Wx+c90G3tqHLx4XBpwWVJScjravNA0MZPl4XQc3bYRrHabDO8s4sZozFedDIxq2asfLaE/Ne+I5y9gw/Y5ilVhVGHcR54ToPLvBM3jlZrdjvwsc9pH9OCxgZ04zOSlxGPns88x7u5HbZ1/le5++5Duf3vHZq4l5SoRwwMiMihd4//kNX/v4Ge+/GLjdD2hJTKc9t4dnvP/BV/jah7e4+TOKz6TTESknSp6Za26p0LUZd6uvEoM3Lk7Wpc0oRjgWMb2OKVmFY++D1S0qlRBiI39aurdIhaqLuNg47nHim9cKpCnBOudM4j7EBnyal8Ebj0G0Mk8ncin4POCi6Ws4t46Atu1GG9heKxdvRoYN2PaMwm1n7JxrVZeb4VPwrtfoAR8jQxyapolbKhH39h7CuSdEaHV8UsK5wm434nxkHEdSSpxOJ1QrRQqleWRCI80uarLN2yC0sJlWZBEHdAvxNDSVYy+r16UiaAu/2YsMTHkml8IYY2vbDRBNMzln5pQJTRW3lkKMVpMINQJ3KS3UGeKSrdafQ0999sH+1VKYpiM1xEWTLRcrHGhp/QY0XQOPVa2dZRKuRFwxb1y//l600VRnW10k12oaiXm4YoyU2bw1WiqOyuiBUUgH46C8vC/czcIM5Opa6JRm5HUJ+T3Wtz0GUM7W6cPt39ZD8jbzNN+3gdPzczwGUB5b9thv2xYuvSWPhXQu7dX5tHbwq1JsX97/rP09nDkzuLRB2/XrOc+N2vll9J5CL7Y6BzvrGHzLi/nRgJYvPUDZutPOsmQWJHm+T5/vHNnH1m85Kv241zgjT6HHR7kiCmchnvY+5eyarrDkOyJZAMrDhvAmngtYQkmLZFtxNRfJerKOTBw4XRg83bXdO3A7fV1GAEOM+BjIZcZV6zxD9ITQSsI3PY/gG+wKvnWgPXQTELHRjBePdxjxMwg3u4Fnh4Fnh8jHH75gP3pub/bM6cTNzYHXr17z/e9/gtt7dvsDu1DZ7XZ89eOPyEX4/D7zj/7pv+Sffes73B0rtWlCHPahGVNB1KFFOd3f8dEHL/joww/YRUd6+W18fo0vR1xJ1CZR3nkbThRxJjyXc8aLwztHcZ5aGrGxVhPk0kocD4QQjewoig8OL4BmnLRwBmKep01dlpwnvB/wLpghFjCtlCbj3ioDW6qtb54/C8uFGAnDAN4vhqz20sRmvpd2aDZDKVXP2vry1wmuGfdtu+/f4LKP1hZicATvEYX5dMKhHHYjuUQrY9CK+dWaGYaDHas0Po1zgBnwUmojmQZ2ux3ee+MWte8+xEhwFuqY59K0V4oRQrs7ulVtds3tYoXzWnvsoZMWFlNVqhfzeqjaPYiQ5rwA9xADTvZUhVyVXFbuTCqFlGYT6FNhCBGnLcupCri4pNX3f/bo10KbNVcKYplYLRRVcmmFO+VM58VCZhZ6seKHs6WKuya8WKt909IMjVv7l1JMX8c5b9yXeabmRM0F1BHEsY/Ki1h54Sc+w3NXHZSA9owu7Z1RV0N+W1BxEZ5vXh6ubvvuYOR6v2zfwAKQO7hqgOmpEM9T17R6YTibf/w6zkHFuuyJbR9s89jyzdIrg/On5h9bZofv/cp2fT+vsGTIyo+Wh/JOAOUv/IW/wF/4C3+Bf/Ev/gUAP/mTP8l//B//x/y23/bbADidTvzRP/pH+S//y/+SaZr4rb/1t/Ln//yf56tf/epyjG9961v87M/+LP/9f//fc3t7y8/8zM/wJ/7En1gIdO8yVRrXoCFJWdwKNHcKV5Tvt6iRB8DDRnGWftldxh21tsxg+ovZnu68wbRjbbZ/CExbIZtN29pm+TxMK6Z1uI9f+2P3sxyiLS+lXb2Cx1NxqAtIGHAVlNlqeKhli8A6sq5qRd26QmzwjjTPOOcpoq2Cq91fHyn01EkBxnEkl4QIxBAI3uE0W+opym6M7Hee25sdz29H3n/vhg9eHHh+e2A63nHYj5QaEHGcvBEOQwiEKHzj6z/GOA7E4Jhz5ub5DT/+4/8e3/v+S777vc/55JOXTHPh9d0dabqHfOSX/tX3ePn59/ngvWd8cHvD/cvP8WMhlAktR0o6oXnagEcbxZYyWRZNS20u7TnFOLZaPDR3vGuKsQUvVoyulMQ0z60GUqGTXs1IwZwagPOeUltqq++S7QZQFMssCcG4OsZTAJwVHJRGGC0lN1G82MIXBiBWULEOgxShNuVR1Y1Ks4CKLFWIt53UltRqHgETD6u1UrNxQ5C143feE1jTzrvAWoxjq6UT7Vk6a2O1ViOclgJ3dwRv/J0+zfNMRhZjL5gnJTeelJUMCMQGPsSZAm4IXaHV6ujYt1WhZdAsXBlVxhiJYbAwSbvfGCO3t8bhmqZ5db9r83KpmJH3DidKKUpRXXRfAIZhWKswu+YdAbK0jKe8is7V9j665HmX2D97/lh1ZvNqOrQUCtYGnW/eH+8R762diGu8ICsfoNNEUXsfVa0Y583o+PBGubuvfDHDVCxrKbcioegqKmZkqYf9zuX8YyEeI8H+cEDkqQGj6hriQXu2Wgcnj4V4oIOPnpbfDnDl9/aYsB0oL9fwyO++/QpuHtqT7Xbnf69scRGGOd/3EqRszeY1+2GGtIcO1303Y503CbY9feOPTu+ECn75L//l/Mk/+Sf5Nb/m16Cq/Bf/xX/B7/ydv5N/8A/+AT/5kz/JH/7Df5i/9tf+Gn/lr/wVXrx4wR/6Q3+I3/W7fhd/+2//bcDcrb/9t/92vva1r/F3/s7f4Zd+6Zf4/b//9xNj5D//z//zd7kUoOFh7cit3ff2AXIuxrt1mK0usc2LbICht5EtEu7pvCrbhONtQ9p8gJtrlAcoabvBBeBgTRu+fIcr0Ll+7Wfbynpdj4EVoMlfW8qx+NHilkVRtSqu3a3spBcQWwmWq7habqEBIURL/XXtIdZqfBHRipbE4bDDO/CSGVpBthiM1DlGx4tbq1fy/vMbXry44XCI7EbP7WGH1mpG1zv2+z2vXr4m18rtzTNO88wHH36F/X6HD45XL1/hvOfZ7cg8zfyyj3b8qh//lYAn54ILntevXuLQllpd0DJzswuU+Q43v0JKQsiUmglOKNkq+5qeRMWJJ81mRIKzsIvpibSUUpSUJuNgkFsKrBEuvR847K2OS8o24nd+AwK77Lo4YgiI2Gdaa8K1AnO0goRtkEyolRAHhFUMT5u2jMmjm85NF3Lr59q2YUvyMKJvr4+U87bQ3truFo8a2+uu7XpWTZWyeBdaSKJadkvPXhp3O3IplDThfUCCX7wWPfRjVbfNa2Tk1Lron8zz3EjaniEOaLDMlFJM/M08I25zv3Z9KSU7D4rD+DVJLUTWxbtWDRjzbIUYLWjZevQYAjeHPXEYKMX4NMVYqpZOXjYeXvGmjdJq/nRPiIgQh6FdX21txIopAjgc3kUjIYuRVr33i9eIjRHSauCCuaJqBT29s1Bk12wx8Orae7bwK9pCjWOk5AlfzKvoXc+wEj669bzKwlyVlCs5meJyrbLpl1bgcbXP6e2og4J1I/vzSD/12Py7ghN7UBvPTe3H6V4VafP9r13Vdv6N3hQ7CWz69e29PZzasZfnIZvtZfNLztav+27tz6UN6hlwW1Bh93lu265f2eoV7XZq09b0/Le0Ay0D/EvP/iO/3zSJPvVW32L64IMP+NN/+k/ze37P7+Gjjz7iL//lv8zv+T2/B4B//I//Mf/uv/vv8nM/93P89E//NP/Nf/Pf8Dt+x+/gF3/xFxevyl/8i3+RP/bH/hjf+973GIbhqVMt08uXL3nx4gW/4f/8fyHEa/u02hH0h78+knV+a8TPt2lD0itH3S6Xi/nr0+oqX5ct38oT4Zi3SXf+Qbbty43Pn3F1RsqEyyeknqj5COneyK4tHOG0jTAaL6KTEPsUYi8170FM2yE36XuAGDxjjOwPA47KbhdbxkTl/Re37AZP8JUP33+OF9gNgefPbprBrIzjsMTthxAZYuDl5y+5u7carLkUPv74Y0J0LYNiZhgGdkMgpbQqfjajsD/sSWmm1dOj1mz1deZ7NJ9Irz6j3N9BnkinO6J3lGwqn04rlBnVREpHSqv94jDglkuyUZrCNJ1QLeZWRhrQiIhEG40vXIJs4EOwjJmeSuoCwUcTc3MOpZFJg3FOTDfDfnfuiQ+xVZz25pVYCvMZ12GrQ3MZY187HdeAhoUvarXQT1VLuV1G9VfEp2pdKwSjlsqsKE1sBdW+3rKZYoxnIn5dNXYYR2Jbrqord0VoBrUXBwRqJ/yaUTWvSME3w+y9tArBVsSwm9Ray0o2lp7Z1MTZmncnt+woFyxcJg1wixiYqWqpt/0Z5RZqMTn/REpNXTkOiPNLeKtroBwOB/aHw8I/SbOVCFCU2LRhaCNXU4wteOfauma2+jPqadPBW+grDvg4EIfRSgKECN43b0pEVdo7LNSSqGUmne6ZjxMpK04CwXlSVj5/OfGtT2e+9anyrc+E754cd1mYG79F23u5ZoqXdrUBulvZ+u02P8j8YybswT4oS+hcWZ5bH3z153y5/9uEmjogeDsPCBfrja/VB596dZuzsfdm3epR225w5rBoAOLpZ7YCnIf3rUs7O1++pmg/LBS5Qi66E6HvVTK/8D/9v/niiy94/vw5T00/MAellMJf+St/hbu7O775zW/y9//+3yelxG/6Tb9p2ebX/bpfxze+8Y0FoPzcz/0cv/7X//qzkM9v/a2/lZ/92Z/lH/2jf8Rv/I2/8eq5pmlimqZl/uXLl4B9D7VsXE3LZKNc6EZ6iyC381sS0eYAIo+2r9UurwjyselxN1s7wsaddula+zcPUPq9OLx4cAHUY1VSXeM22OgK7QXc3OKG7sfxjWiYqxKCFfujFva7AWmZSoddYLcbuNlHXjw/8Px2R84JUL760YeUPOMoPL/ZkeYJ52nxePPG5FQal0PJFKTxJEo2vsLzZ7fGCWnvcr/f4xTmydz3IVhH7ZyQTieKOsRF65hbHV/nPLUKYxggBDKK5mweFirBQ80JrRnfxLBiCJaxUizTgtYBmhIvOGd6EtA7CBvdVxQRT60OxCMSCH5AKWhNOGlpsw6U0oy5ZbTUWqmNQBrisOh/9GwWS6PNlLyK4kkroqjeVGK7kmn3FnbjZymkFnKSFgJwIqizDsipmFJqa9e58XK2AEKaGBm0pkMlZyVnE+IbhoH9ft8Azrr9Jc+rtCrYMcalXk9euCtp+R1CaCq5tj41DktonpP+KUu7B8TaliycEwPdrg1G14JuLdPFe7SWpQih6+BcdQ2XLG7XunhkRM0z170WwzgwDCOlrmGeDszmecYV17yOdXkfqRSC0ki0geAs26iDbW0aO6F5M6OaSbCsogjiqSImFOicPafGMaOykmZVETwq3jgywbRyBEvtD17Zj8J7u8rLofJ9D76CVIdUR8W1rJ5Var63i+1vd2bEHgcoP6qwzpMABTYelP6+5fp+bzW/DeNf9rtvCtesA+atbsnlvg/tXI/LbDbYrDmzPRf25eG0cmi232K/N2lhiqse+4uw0Y9yemeA8g//4T/km9/8JqfTidvbW/6r/+q/4id+4if4+Z//eYZh4L333jvb/qtf/Srf/va3Afj2t799Bk76+r7uselP/Ik/wX/yn/wnD5Z3l9slvjjf5kpMbQNAeqfVXVP9Wb+LG+qx6RKAbKeroZelbZrOxbrx4utZOGl9OQhy2ab76s3xLpd7sWisbePbPwMniAli9Q/C0jntKMEHqppKpV9GsYL4wBAjMQSil4Uke3tz4HBjoZ33X9zw4QfPGSO8fpXY7w/sx2Ax91obKTEgTnh9vEeAMQYOuz05tQ4/wsyq47E77Bn3OysU2GrjDOPI6XhsQECYc0a8ZwhDq7Jb8GKje+mZRmrpwloKTjyH/Z4qlUTheP+SwYNzFcU8ObkkK4DnvL0QX6x4YLUUZLSlYleHkhvQKIjrGTvCGHc4N5iCKwXVTGGyQoRlQktu7bFl34iRZLumR8mmqhoRYjSAoub6MABUSgMBlp4rziHBvC2hZ7ucgWjLaKmqLbOoWDto63p0Yxve6W3cwn0W0jBA0UTqciaw8iRyA5Xee3a7gT5qVWUluDaeSSkJqITgmvaJb9+8pWqXpnzcQ6PSrr3kYs88WsG/CkiVBngCqn5JSxbxeCesHBoDOxWw6tKO4IPpzGg1I9z6nUojkzdgXHOiWm65KbZqQTCQn9OMOEcIA7vdbiEJT9PEaZpMmLAReMUJNalxQbwS1LxpAos3sNZqKsO1oF7bN9sysdr7rYZw230Ki1iMrq54Jx5tqsVaoPpCJVFLAooRewHvCs9GeLGD20HZebjL7VlwzufYTmvf1kiwPNzuXTwVj81fTo8eq4V4hPUSLvVZHj/XaojXTc6DGefbrttsLuDKb3242RWQ8/gdy4Nu/hxgPLQ31+zPdrB+PmBQthyTvsy2FS6VZB+fHr7nN03vDFB+7a/9tfz8z/88X3zxBX/1r/5VfuZnfoa/9bf+1rse5p2mP/7H/zh/5I/8kWX+5cuXfP3rX6doRs7SgWkvya0gYwM7z+YbUJHl4VtTk/5XLxvI1iOyTQ/bnnxpKv1s54hY1vXLuz2LG+qyTmUFTNI3fhDXk3Wva+h38ReeN9KWbEdQCztktdH+ICOiiVoigkMxMquoqaI6sVGXayPfniJq6aKB/T6wGyOqleg9NzcHbm9Gdrto5NfDwBAd8+lITgV3YyPYGC3tNrXiaK5YB/zq5Su++tFHTGkmzeb2Hnc75nk2QBM8h5ubRUUzzQXvBwYfqGEga0KCpcHmaWaMkTFESi7QogO+EQVryYQhkk7zQrx2Q0SyZ9zt0DyTptnel3N4bfupoOpxfmwGLKOaW0doYZjevryvIAVIePGLRLx0F7MoPgj4aMdXywDSKoiPeGdKuyH6xsFogmI1o03OHOmZWW4J/dBdz1WpKVNzIcMSLjJyqZgAl5rXqpMyi2bAvDT2qUnz6KwckQ5QOumyTy4XgjchttxAQC4F1CTmHRaWKsW+RRcD01QoKS+j21KVWSYYFe/8kt3kRRjGoaneGq8jBs8Q9+Q0N3L3+t2nlBBR6GRcMf6REZRZPDpaLANqy1kx3RUjLHfBOXtd2mr3GOfIYRykmitSlSCQa0UL5CqWwu9OhDgwDLF57SykJ1UhWHahFyGOQ+vDjPxcm6IyCWZWwyHOiLq56uKtyQqaswnmieCk1SvyARcGC+EhgGX4GLCJROeRohQ3UWuh5NTSoA0Yj9HxwQ38+PPK6ylzKkKqUNU3Mb/GxWqgqI+xRCtCNVIt21G4PjBWP1Do5szAPnY8Xc+3dIuXBvMJL8ryS9b9l9Z1DZydjxofQrfzSbR5tZtF6D3Dg/NfGXBur2OZE13ew3Jvjzwnm296TIu5PAdVXdFepN+rYJ52haptUNaNkP1xm4tWtt61f4MAZRgGfvWv/tUA/NRP/RR/7+/9Pf7sn/2z/N7f+3uZ55nPP//8zIvyne98h6997WsAfO1rX+Pv/t2/e3a873znO8u6x6ZxHBc+w3aqbbByFp3Zolwe4tg+X5tKj6zyTba/9qPUBmCuT1rl3LOxgAJ6G95clK5/Li6o78/l9toBk2zuZv3zdIrYVn9li5T7hvZBlP6oxOEkUilUieAHRDItAcNc1ihDNO+DiGO32y2ZAM7BOEae3d4ChVKUw+2B3Tgwjk2CPZob/YuXrwh9WIcVhAuDx7vYRs+tbk9RXr16xUdf+RCpNjIOIVCqhfyGYeD29pZxHBdNECdGGiy1It7htKMQU/E0QVZt56iUXPDRODVzntkf9uR0xMdI1cg8HU2ZU20fPw7keaZqxodASpMRiL1r8u3W0WsbaVub6FLlEQqNo5LMs6IOF7R5KZpwWc4IVsMohpGeOeBdtFBVC1sgLJ4GMzBuKR8gGPASt4qyiVjGkzirp5NzNv0SbWnTG4NsXU8zME2BsxYDvOIshbyUHkLdtj/72zkqHVQH7wgNXFU1/ZJSCinPRDGJ+dq8F7vdsIRv7JgO40jkBcjVVoqhK9N2LokZfWfttCR71w1AU3QJDRk4amHCWs68nN2b043Zlpuw7fB7WKDWutQMcuJwQK6Zko2oq839aCBDKblSdV5Avf0zL5WleNu36Z1HxdpelTYMaano/Tt37f332kVxGIxzBKgWuFA0tdpJurQXVVn0TNB2/SEShh0uHFs15T4AcWgs3OzhoxeekzomnZlL5lWqFHwb+JkhrOLoLARhqwK7BSBr5sx2emqE/baA5up2Pcuoo6ir216ClhUonG111VOynR4DEU+Bi3WdyMW2+gTtVB4e9RycnG9/zYOyek+24OYipfiy5k7fR8QysPrgmHVosBlC/0DTD62DUmtlmiZ+6qd+ihgj/91/99/xu3/37wbgn/yTf8K3vvUtvvnNbwLwzW9+k//sP/vP+O53v8vHH38MwH/73/63PH/+nJ/4iZ/4gc7dWfKXXI5LF1ffps/XPs95LEVko0/SAYRczLdP7yyt2U5Oz8I5e5NbsHAFVDxAlFdAyGWq2LVveM3eWTuCq3HHzldoTUe7bDkRcTt8BCmTde4qSE3shmgficIQzVhKy46IMfDs2Q2H/cj98Y6bm1vT8tBMLsKgEMOOnDLzceb5h+9xPN3jnGOaZ4IfGQdLA3XOaq3k3MWk1syFGGNTtFWcOGIcUQQfBnMeBCODdkBRW+E2pBfjszuuQGhZDEa89aZR0mToq3jiuEfTiePxzsBNyUTp4RV7x957ckrLKFfEUYoDDWgL2ZgXpDci05zoPIqi4LU2ITtLnfY+sMby3bKvdGE2bx2FGZn1HZsbvxWiAyPaVhv5I1C1MOdqYYRmGGutlFrJmw6rp4PXWtHS25EZRhRKtQrLHTb7YB6iHrJgIVx2tz9nXpb+LalWUsocj/ftvjxD3LVaSyOleUWsunJTOPXNI+BZ5fHp3hvoqdG6ACQjusYYGIeBWpwRXmmVn50zLlTrVC360UXj1g9Ra90Qi9dvti46NzaUqKVQiwm22fUrBeP2OMTUfFu6c0rJ2ukmtCRiALp0oCTSjtu2ERiGuHq9mhdr4SC5VrdJhJR6BePWG9RKzdlAfLAaPYjrQ7Fmsw2Aujjgh529t2Z4nLMinUMtvKiVoo5pdsxzImVlVrvWHi6pXWZAxUoywFktnd4G4N0AylPbP+1BaV9/31Yf2+Ya+DgbIr7FdNnnPgQgjy23z/2a52Q7WH4M6DwxNc2Lx8DJ2aaLxMbF1bbX91j26L+J6Z0Ayh//43+c3/bbfhvf+MY3ePXqFX/5L/9l/ubf/Jv8jb/xN3jx4gV/4A/8Af7IH/kjfPDBBzx//pz/8D/8D/nmN7/JT//0TwPwW37Lb+EnfuIn+H2/7/fxp/7Un+Lb3/42/9F/9B/xB//gH7zqIXnTtI5wzhFjf3ZPeVAePl53ZU0fAcjZ/LXjrdfUr8NxOZ0f6/FlwOJS6zd19kEtTkB5cIMPQPMyKpbNMvtd27W2wTBVPEHGVlHX4tOiwjiYlP3pdMLHwSTIXUAQfIjEcWAYBkqtreBZoGomBqtC/Oz5LafjieAMCNzc3jKnidPxiJbM7WHXRnTKnNNi7PaHG0IMnE7ZYuVqI+JSbBSu0LJZWkE48XhviqlVIQ7GcXAq+NBk4ZukuBF8PSVXstYmO+4Iww5KQlPFhYHd4YZTSUynE0UT0Tfp9VIAj0gh53kh7KIOijetiBbHH4ZhSW01Q2RKo94Jziut3rIZYOeNV9FH584tXqWUJnKWNnJeK/R2AAAmGKft2QT8olTan5E1B/vrHPgYmqaGnv/VVXujoR+QtRaLuFZDpzb1Wmf1k+ZkFadpdZrMYJk3oRRL8UaNy6QK85yYpnu8C8wh47yYEfbmWej33r0dPb3YUcjNE6TqFsDhnUO9UKu09Ggz8D313SgmhpyszEJsHhnzpNTSibLVDL93VCpSN57M5pWpzeNRW1pxb7elhUDFQ82N7CrVigV6t4w6l/sqpXkmDcC6NnrunA1Z1GOhc8W6+mwnvCMtRDfPizfMOQOo3jVvWi2N69V4V95T6c8X0Iqow8fKsDsgqBVOrN0baLouN6PtX4pnngpTVsqxcp+l1e82I9dJ4bRn5x54LZ4O8Tw2vUtY6GxerddcR3dtkLbwKx4/9/U18sjvfopVS+v6vteByLXjPX7eR7Z4MDh/er9r2z4c5G98I1uOij715H646Z0Ayne/+11+/+///fzSL/2Spfn+ht/A3/gbf4Pf/Jt/MwB/5s/8GZxz/O7f/bvPhNr65L3nv/6v/2t+9md/lm9+85vc3NzwMz/zM/yn/+l/+gNdvCprifU2v4zQ2gZn6PABemTdgfrgZWzduX1awjjac8z78uWoFmvtWUSb//f1DwHJBkRsEFS/h37ederbPWwZBmy2D8G217NdlE13i6LM1aTlRcCIoxEVJTolDMJ8umujrDZSEsvosHj6jlSwe66VOR2JwTGOAze3N4C0yq6Zr378MWm2jI7TNJn71xmh9HR8BQ6GaKmzh/2BnCqokTtzrki0tMucKrIXaAUPqzirSeMDUMkpEWNEhE1tlmqkSXVUrF6Qa/dbq1IchDBA3JHyjOLxIXK4uYWSuH91YjpN7PcjQwjk3LNQhKSJUjJDGFEVBh9x2bRQatEWSmk6FerwYY8TK87nxCOUltm0tgkzfhZGC8E3D1ZtRs/ExtgSVr1H64xzAQJIKTSVPIJsigfqeYqwiCC+eV5KbcBCm1FshlTM4Cy6bs3QdQMNlsE17HecxCoWV1eprodQG2+FLmVa2Q0jwQem08w8J0ouVnwyF2KIMI6LgGPOrbxA+8Z9S3fvxNvgnEW5tXt8Ogm2hcHU9FOsn2haM7UJtEl7Bu2bdiImL19p/CZvqq5Y2jUY+NXmyVS1DKJ5tmy2Sm2hQZYvLeVCJbMPkTjENpAxr4kLLcOmvQvvPerMu6EYAAwxtuwdXYCRNk9hJwhr121RbYqxbumXrHoxRn51vgFjFi9Me2wGbLwRzZ0Y2EzziZxm84phGOmwEz4mkIuQyej3Tnw7C/cqFHWL5Il5TWprAWt/dglOfhBg8tjyN88vv5441pWh7GUffHW6WN774gcuCdn8e+JwbRuRy2t9GqQ88IxcVYLtxzm3MfrYtmI26oHHqoHkMzt5cYVduuD6sP7x6Z0Ayl/6S3/pyfW73Y4/9+f+HH/uz/25R7f5Fb/iV/DX//pff5fTPjpVQyjA5v0vHow2CtFt27icbztcQcKXHoxlO11wdytC1s5/RqrdfHjbxnXWxrYgQtYznJ1vc93bddtBwPZom/DSGQh6wLI2l7OKLh/Q+tujEgiu1ShBOE73lCau5VywkTSOOOzwYSAXOJ5ODEMg58IQhybENSAucLw/IuIZouP5i2d88v1vU2tlTolDy8BJKXF3vCcEAxW94wX7XXKTh4+RWpVpmhhTIpSMFBtxS/T44ChpNiKt6mKULeRTMUKrbx+UcW9QqyVTi6VbxmHfvCgTJd0j4ojDyG6/53Sfubt7TR33DENsx/DEGMhl4v74yoBSe84hjKDSFEUHq7NCWcCKyIiLDRhKadfca7ZUcl5TrL0Pm7eqpGRG2DkDaq5WvAeNDqnFCLROTB24qAG2cC7UVnSjVwBN0t5aVHNKYYRpS5DuzDfnrExBWVRpCzkZN+iw3+PcxOl0QlRQ33gg7fszTGVn2Y0jQxyZ55k0W7HFDp66x2mbNdS5KTRhuyFazZrOe+mDhg7uve+1gRzgSSk3oGfAtBtzgwN2HucFj19BWqstpHiUvISV/XJfTRvIeYqeSDnb0ZwzsTiEUs2rl1JqmVT9O2og1/v1PUiXnzfisQ9WfdhS6SvSPGvbauEPjUxTN67t2iU1QiyWHVZaqM5J89ipZR5VK0iJmIfJR0+pHsk0MnILb3vlZu/42gfRuo0qFC187165y46iTY6gvYylV3sElLxrWOdN6572pFxjRbyFB+WiD30waOx/zwzxYx4RWb6Jq+fq22z2vbRjl9M1SsDZgLvbv83gdLE8sh2w9HNsjqUrt+TJEM/yolfgs67QzX2/3fSlrsVzHuK5QHV0VvL2ZV6Sgfry9WUuXhPOPRhn+7Nus8KJi5ehsjSv/q7WLJr1/2x+r4h0vaZl/eIiamDoEqi3a91m6pztfoamMXJcp2VjsXlErMMSjzglEKiaWqqqX2uZhEiIgYqQijIfT4hoAzmOYdyTyww4jkczPM8Oe8bBgZgXA3HMKfHBB+/jRJiqpe/GODDPid1uXFKYve/GbGAcB4Y48PLlS4ZpZn/TRpIh0LOwemaR1b1ZXZHraNOUWNfRScAyljyVlsnhgpWpd4HKjGtclt3uwIRyf/+6VaQdMfM24l1myi9JaWrGywCdSAAVvBvYj5Y+m8pMThMhekR2bXTc5ewdMQ6EIAxxDblIA4y1kUyXyIsYN8U516TuV4JszcUAUZNzD0QLDzQuhDa+RG8fItJG34KUVjpeudqpe98BvxF5jY92NGn5EKjDwDTNNvJybXQu0sIcdjQjuFrKsaUWlyUrBywrxtRz1w5ut9sZYboUqKYD0oGL9mttRrs2aX8R+4a6HL5luPWUUyPE1w5cXE+bLmv/svl/Fw007kxoIVEwL1HFCcwpkYqFCS0Dy/SGnPdLOvHqwbV3J83bZeGtBmDU2qt5WM7TYdd0T3suxnNpGilU8+CoAZpSKq6FBRHjBdE0bxBLW6fMaMlLplSpmV4fiOZNK6oWElYlOOWwc3z8IjBPwjFZ2+Sk1ARZ3fKMW8+1uf6Hfffl9C48h7cJFV2ClPUZ9tlLUHHRp7/By3F+sgaqN/3u2gdf/L3qVLgOXh4e6+Hya7zLHoo58/rT7USzVf1yLlKKu5dkjRq8/Xv5YacvNUDZZvBs03ffSjhGuihO3wvOJHqv7t6O29Ll1tPIw82gpQqzIJRrh9xe6RnHlbO2fXY9V9tzX9cxx4MttgfYnETtxKpKESuo5kRttCiZXMCJx4rl2ige50mpQs1Itn3NSAi7cW/F0zAdjFev7giWn4yRSDPDODK/vuPmcCDGgdM8U6vifCDGAahLh226GsbhKM1gWgZNMtXNnBl2RhDUrrOBEXmnppXR02GHYVhUPJeaeWoG04lDa27PzZFSoSo4H6lNGnwYdkzH1wxxRMhM0z2qFqIpueBkYL+75TS/ptQZ5wo5zQQ/IBLR4hjjiIgn14JSTEAMbcTTgVKNg5NSZhh2DOOwhKfW91cXkAK1ibWZRL04WcjLNFBm7UIpOVFqJQwBYbBUZMHCCa2x9aKF5kmRfro2Sm5Gv64KktZO145LSyWXmSoGUIN3JmbXCK+WxbMqEpvnquu10ICWieZ1ALUdrXbPivfmPaF6Uk6L6FnOyZ6n0Npc//ZsJG/Ppd1UXUeH24KHglvAn3GBtvICdsyUTATQ+YL3xrOZ59nKD9RksvO5WMp6KlaWMYyEYWRwjnHcLe/VwjzGPVEB8fYOUSGnbB6OUA0IuZ5dZFo33YCoqmUL9RARxllRMO9LtNo6LkTEG4dMG7fFRsWKlbhITYk3k3KizLNlRKlaVlFVTA2ge5Uqg6+8ODi+9hymVKniyCrczYXSavU0OLoYxw4Q+zt9tDN72Hst06UxfnCca/vrmfDDxT5yvu3DnZfznu/zuEaJXmy3Pc+6Ss4Wy4PtHx7t4XWsIOsqCXaxLecSFIvTfXP4y/3PbmGzzb8NoPKlBii6tnEbvWPehVUS6KExP2swizE/g5SbDTcNym2RdttAL8BQb2AboGEf/+aCt+fnosldhGIeenoeW3d+h9cb6tnem49Al0ZbtCIqBLHwT8VGczBSNSGU5vmwG/SA9xazdiEYgAnOZO4Hz/E4Exy8/+IWBcIwkjLMGV7fn3h+e9vqsgAqhGiE2zwn44K0F2TGq3kEVPFxRJyFVezyW6osNGKqGW1jASvOm7Et3fWOtAwHIbcsIvF9JGkCW7UaSNBUCURSBgkRFyNzTlaBt8I8H6n1yKJlgjCEA0qk1vbM0OZGF1KxEfo43too3MWGALLJ96hlwpRcmWuhpNlSe31YvD+Cs3BXCFh1VhPW860qrf1n1Y2dOhSrvuy9s0KAOZFqWVRhxXl7Jr3BruNdW+8xDZXeVlRNrbaw9HDOCdGbqmgpFc0m9GYeCsVXZRyi6ZrMydRNW8q3a4TS3lBrWSXoeygjBKtBVDFvTEoTNadW+bm9V+8YogEioQOnNS1X0RbCOB/CiAs4qUsK8hraafoeuSxeAG3ejOg9c5qb8JwZ8HmemaaJlApK08ARhw8DJRemaaY6x1gyYKG87jF1zgpvVjVgk6uVaAjBQm2lppZ9FlYvb+8AW9ilaKGqnTuEgB+GxUvTAb/4YEDFR1oVItBqadc+QjBAkeeE5kJpZQukib7htFXxhqztWYqyH4T3D467k+d+Vu5cJTmYqtUo6t4TVV2yhqzLayyd9u1sbu5hp/egD3ximx/IeD7usbBjbjdp4bXNPtvfrQFeHPFibuOuP9t3MSSXe1/Z5ux43ftxZRL7nle9EqEr1QhrWrHZj63Xp9+cWuV3tPUUal7J9U1u7kU3CPD65bzt9OUGKH1kZDM2ycVsd3hs5juSXHe4Rh5is6NeFEzbpGFdQz9bP9pbTOduxsuDXZ7k2rrr53rK0/LYNVrqqdFkq3iqRJwHqRaCyMW0J3wTiKoqxDCYwZQeXmlpnflIHJu0OUbuS1Mip2zubuc5Hk/sdgOiuqhkHlNiGIyLEodhSRtdpM1DYH84LBooW1dxaXLn4zhaxogYyRDXQEl7Vk6ElK1OQveqaHsu4gwspcnCUKfTHVGEmk02v4aZkmZCtOJqxhWZ6ZkdztlnJdWIl6VWhsET424ZfVp2jolm9Wuv2ci6tYmPFak4Z2quJcQ1TAWQbaTdeQilEVYdIE5BNkJtrrnaW4fUU1O70RVV0wUSq/S7XE8fffXr1bXey9LG2nytvaW5JZRWasFV0/eopZBnrDZMjKtEgCqHwx4Rz2maYEl7xsInG4Bi32hp4StPyTbSt/dfTKyursX4tjyN7k3o1YiXgc1yj7ZtLSvHRLUpyzrQbCnZVddjxxgtlNPS4nsNntNpRp03wT0v+BjZhxGXTZslp8Q0ndpnaJ2+d1b7pocma63sdrtG0pWWlmymvT8L5xxq8ZbGk1nvyWyQWz/ztqxqk0eoBvRQQXvFbBULEYVAHAdKzViYqS7erOUbaf96qZEhBm53mff28Pmx8tmxcp+EBC11WznvcS8n663e1q5d9tVLd3wWRn+4/sk+8cF07tlYj38OTvSJ7a8ZigfhGTn/cTawXA4pb3gofd91yTlRtt35Eq5RNmpHG/sny7ZdD2U58Hls6A3Xsh7rLMz0jtOXG6CoPECMCxAHaOZo0zQ286tRuwZOziRmnnghS3xuc55rRKWH3oxzt/U1N8lTH+t2BHLVxQKPfogCK/1kWdIbYyWXNgpvnZ5rWSmlzjhxTSadFjO3ejIViE0EbAymEIp6bm5vCSFwvH/F89sDp9OEtowOEUvDdM6j3U2/GGg14S1xFDEBs552CxiRNISzApM9Nfd4nNjtDoQwsJBLN0AAWlYDugCc2kbzWjMEjxQbAavSaqdkohg514tjzsVE3Zxlr5zKTMpzC6lkas3Q0npLzpyKFTZ0LuJaXR0RvyF3Ni0TTHpdxAi7W10eA2lpGYku9ZG8SbqrKJlqYYLGR6H5U4wDYgYemnfBdUXR1Wtw2dZ78+oGMbTwWn8XZ6TMUsgbAqdrJFrvTHejlsI8m0qpcXz8EmJxThmix4RoXRsQrECh1mYUofFpOhhzljqu/ThNlK/XtKnGCan9G5WVpLfNaNoSFrcZTgvY8eY52RZLlBYSXSoul7LwheZ5RgKINy9GiBEfA9lSpKg5oz4vtX3MayfEGBmGgWmaGs/FtxCeO6uObPWDHOq16bFpUw9e1Vyptuzs2xcxgHLmKbJ7KErz9BlwCj6QvKemRJozLJLwrX5SU+TNySqaj6Hy4qB8lIT7JEy5kIosVlY3Drprog4/zPRuwOMNB+L6wbbgpHeeD8DJg+0fX3YtVHS5TmCTsPGmi9/amOspwudgQaF5WM/u5MIe/tsK51ybvtwABQMoZ/6EpYNt7qfLINsyr+sO+vDtd62Rh5OdoG6CJNvPQ9r/hPPdLxko23z8p9qdLKj3+tpzb9D2Gq+5ePq5z662PbPughVytQ7KoeACwTlONRGI7MIIYimffaq1Glhpz9KHAKrsdjtePH9Omo94HzgdT5b1Ghw5F+Y5E7zjeDwSvSf4gWlKywjb3Pemu2FpwRYH8N4vqqGukUJpIAMRXr16hXOO29vbxZCvGQ+1pRvb6JzcRuS1Utq22rwuPoSmpol1wq2OTkpW6LDWzDQdGWLbtiZKnVfJeDEjvd8N5ArT6YS4zDC0a9r0Ombwu7ciEBuo6ul5ZkRKAyjVMoXEeAoWLkmE6PFuWACOk1YrpnlDrIPqgKxu+AqNNI0uGR1raGTTqjYgZUtC3oKU2lJdt/otK/HXVE7XOjoZ8ZF5ntdzKC3DzIzlPE/Nc5RBLKPGjHXj3zSAZsRQljbRr0O1k0XXQcM2NXfrgevfxnbbhZviPT4aCExzWQr+dc+ChQQTiuBjQGqmFjWRwVIQ395vVXJN5OCpQyRKWDLMai6k1r4vdaH6M16eOeYpE7fWRlr5KCbMl2Ep+gjgvDZZcuPMWEFLodd9EFEKsqgLF+1ejealK3XxqvWW65xdhwkTzuyC8pUbx5yFlCHlzKukVHWtV9Ll/2sPBItX4oc0hI8Sbh/5vV143lNe9ptrn9rvXy/WPUVc3R7zKnDZnrP/OQMzVw+9Xv7FTT30Wqx6L5feks693AKRTnz/0UHIH2z6kgOUh49v8WBtFizOQ9ls0JGwXn8FZ/G1zde0QIrF3XUN8Cz+mbOLfazBab/wde2Zq/IhPlmBhZ65eDaAYznkuTfn8pyrEVo9SrkJXFGV6pVcIIg3/QYHqrMZNVWis2yQWpREYndjCpR+N7K/Gbg/nqg5E73n/njisN81HY9KzlZYrlfFFcRErbwZqG48VBugsKH8MqIE28a4GK1zUuV0OnF3d8ev+lW/aiFPuibwRuuASymWaQKUnAghUrKNEkPzPgTvuDnc8MkXnyLZJOrRFpfP85LlcDzNTZ+iAiZVX1XJ1WGJwY7gBiMSN5AR40DVjJF0A2AAxHQ/rHOwezSjbJkvLatEAO0eDFN31Vqo2eZ9DQgeh+Kbqyx3r4DUtYMVoVJw3hO9PafqTCG9G/JalZzPq9T2dcCSZrwYydYA5QI4W5jAhNRiXHVpjNDajaqBEmvXDXAu+2vTZDFlVu3gg0wpm5BDA1C9bbABJ9370EN6W5DSyar9SxD6Os+ijloqQRzVORKZ3Lgppt/Sq/+aV2kYPHNZ1WadD/TutpZiYLUZhBgiXXCwP89tG7/0dNRSqM7E8Xq/4lr2TgcXVSs1W7vvKcw1J6p4PGKeVwR1PQtpDVsVqaRqgLB7NNcOhybBbwJsji1AcnjJ7H3io4Mwz8qUQbk8kwABAABJREFUlPw6k5OnqjSaXe+rtob73QzhD+otebuzXB7dnS3Xq+seOdIGnDwNYOT8wFtbcfWaLo+x/j4HGavxWu3FxoNC7/8vwQv8zw1O4MsOUFQ3jd2mtamfU4qU/jHzDshwO3xsx2AdBfRruMZ6vtYYt9s+SmZ67Er04TH7svWc6/LHgMm1a+pTP1bpuEwqKibg5pynCBRpRdvUMiWKNil6tayBVBopshndV69es2tF3WLwTQtitvt3npwNUNzeHDg178ButwPsOqRWYoj44PHeGUjqxerEXOJdPrx/YLVW/tW/+ld8/etfX9JRl7RaVcsqas/J3OZmZEII1DRTU0KLiX95J8QYmKZsnqMu6IeS5rmNRCulJlQyTszLYuDKBL8CnlozwzjgQ1jIlTGOoK5pv5jseq0sQKw2b4ZzXUpfWs2hbsAzXVre6tXQCKOKaMGNVnzO+YAX08WwbAwHlMb1KHiNmzbgscrJq/E2omZXbbXGsTWenU8iIsTgFqO5pDq3r9JpNc5ErfZb1jYrgvFf2rPVqk3ivquiWoZPkKbd0d5nrXltx92j0f7VWpZaPHqx7vK76M/Wbs/CODVvaregVNr7B4bmRUpz92hY/1KrgnPEIZgonYv4OBLjwDAOS0p0aeSNnAtarZCkCwG/qa3TgVZ/D+ZR7ECzD6CsnwuuhV0bGEc2hsdtiMK1GlFYNppQ1VLiu6Fc7qe9mOVZua7bYvMlZyNdYm3WiUek4l1hdIn3d46XO+V1glkVzUKPJnQ22NuawAe92IO+8F2O9Ni21/rK1Tu1Pa8+4jV5PKzzhPdEhLOPYXs9cjHfpqfu9xq14By02B2cW8vHn8q7erW2x7r05LwrF+VLDVCWapkbmLJ8MKyAgmW7C5D66JHPHZBLV6DdL7KiTXi3h/6DkoWeOt5Tx35sGVwDPN19K03/TpDaRm7SYvtq9UWaulXLmhF2PlCdY85K9EYuLTXhxVQ0YzBxt5SU42kGTHF3mhP3p5ndbmfpo46WZpqZpgkdAsNwaK5ou+bUYvOG/k3+vhvCnI0g673neDwyjqOFCpiXDr97ZapWUk6Y0qV1RN47NCun4xHyBCgheO41U/PMfozkbHVXpnmi5IndbiREAx6GgF0rfifEELC6MxMVFm7MNM3M05HD4RYjlppxLHnVZ9EKpWTmWuxY0fRUcqnUMiNScFKoNTVvQuOoVEsXrU3jZBgs64nSGI1Ol7TeRe9YusfmvD3BGjaBXhV4Jef21O1O7DRsJf2QdG6Nyc40g9o8MJYc1K1k31Za1oi09+GX61BV1Bt3xnRjBe/jBpA0blN7j4VNqKpWdPGird6U7pXo578Uhev6Mb3qsJP1e3JYhpivxhMpVU3mvirqrE7RsNsTh11L7bXyCnEcVg6JdmJ6XcLAqro8zxDC0p6tinJtQLOuz0kcRTJOV8+ja6nxBmYsDFrFN2J1eyfNI0IxHRij8RS0GIgRTLSuHy83Qq5W1msFuuCdcVQKuRZyybgKoygjQtCKkwFt93zew/7bHqu/bf97AU7atAyAt8vlIsfmAXC5ft4tH+oMgLzhyh6zIY9xRx7+fpuz/M8/fakBSn+fW4dUf231bA0tzrbudqWpnM2ZsdarWy5n2nSuF46cB6jz3MtyBSxfnuENQOZdgc41UPLYMbqxF7Uk2apdiEuaByWCVOaccWIKl+oiCsy5EL1avLpWqijBWUbJNM2U4MjNRTNNM/N8opZKSjYy9MEkxEUc8zwTQkuZDOZhcI1DMY4jMcYlitAl2UvO7IaBjz78kJISx7u7VtTP4Q8H87CopeYiZgjSPJmnJBgp1gloKUz390RM48U7z6uXdwzhmYmwOcc4jryeTxzvj4yjASbnPMENNrpUxQePqnkT5payGeOOwz6Sc6XWxm/B4SSAbzWGmifBtQJ7pRSmabKMqVZQcJqO1HIECqGHgajkuXFJWjhLSzEvTVOcra2WjrpWd6YCCIRgqahb8iuyZLB1Y7/lnUjzYoHxI2h1hNpKM5RYYmL3CPWpe8EaklkNq1j9nG4Ge3iv9tou2kGmLturGh+DLkrmwjm/RMTCcHSHyMofaY1+Ka63ApUG2HudnVraNbCGUWBp6+KMQF4rS+XsUivkbJUvBFJOJiUfB3bjjhADKuA3gGmV988L5yTGVpZBzPdQOy/LOXBCTvPy7uhZPrKSrL23rCJ8BGdhRPOiyFr7iQ4yDIxJ9xM4exOdv6UbEUrXCNA+eMYxUFCr7jxVVBORys45RidMpaWq0xBrGwz9wHZSn5z9IQ/30DvShw4PprPtNhmeF7/XzS+276vPHfacO9nlQd/9rtN5+Ob6dG39mUeEd3vO14JF77L/lxugPDYtT6CN5BZ35WM79M72fH47dw2ryMXv1WPzZrffgyt4h8b3b4pRvY4MbaotPmlVcGlqmI6MMw5AtU5/jEKupqoQxY4wNyG34Cq7GEjZpLVTUeZiaZNTeoVQefHsltM8sd8PqBamOXE4HEzkzUdSXkmXihr3Q5oRF0uTFAGKud/HMfL8xS3DGHj18jN2hwOqShxDS2UOzGkihpYqOh25v78nhoDTyun+DtHKq88/ZxctXXbcjbzSyssvPuP9995v9ZY847jj7u41SiVEQUoztHEgpwKyw4eIB9RNFC2QTeclhIh30YTZcjIPiWBGpfUEoo6xZSpZnZUWdtkFQhDmCU73XzClZNfvHeIVVU9JE1a8EDSWVlxuVQN20kigmFfMoRAUwTg9NqpW08TpBtwZ2XEr1mZZRE2npBiJuOTcsoSqqeS61mZk9RJYSrbHqVVZppo4nscMbW3VkcWt2TL2WMoCSKSDuF7JWNeqyqtIXTtfq6Pjer+gG+r64oHplY572Kai3goviigl9VRw42HkWpogoIIfACNZI9KKahpHSpxvGi7mXZtzBjcT2nV2snIuGe8du92OIQam6URJsxXac9Jk+J0RU7U2eaaW3VOxd99uyZm6ot1eyYiLpnnjPFbDoAEU10jT2gXgrE3kallZuViGj6jilAZAzROjDfRJdHgZGTFRvhwL86jsUuZ5EU6pkkqiJG/tS3iohv7D9V4/3MHkcuayz5az5Wd8ws36656Sh/v05dKPueDoJ4zMW0yXIORRUPJGG2Lp6EsFY3QRCewh3McP0drcunM74tnqt5r+FwVQrsb3tsj1jU9m63B8+liXe1w6Ld8mNvku0znB9nFX4dssf/Oy9WNUmnpkUbIHb4MsSlZQteq+6vBYxxS9I8TBvAVp4mY3kFKxyrQhMM8z85xNX6RmbvZxyVDxPhC86YZM02TEw5Y2aRyUDflx4dg0l3abN1e748WL5xZKaO7saZooeUZkxHtdQGcMljGT04n7119wsx+Z5gnJE97B65dfWOXcKbHf3/DpJ99BRNntAqdaWmVhS721lFc7l7RQzyyFXdgBRj4NvQ4LJhvuwFJwq1W9FaxSsemU1CV8EkI0DZbGvzEugdWXEbFso5oTzgslFnxVhqEZIgSkoviW/WMF+ar2XDU7l6qa+F4AaiPCSsuQaqEF6SrK/P/Ye5cYWbbtLPcb8xGRWbXWfpw3V9fQNRYgRMunCwg33MNNBAjRQgYBlpCFRIM3iA4djIQQooeQ6AISGCSEBEZYpoNAoonh2ue591pVlZkR8zVuY8yIfFRWrVp772N8Dp5btVdmZLwyMmLOMf/xj/9/jGJ4HxgHCwIfHh7M4VlAugPxkn45TY22qrTFWFO6NumaWhJKMVRMvMf3gb92GXbXTERuHeDVQq2lUz6WD/dzpfNP3DIbXQY1+2xJoVz6/yw8IAkeUSMNt2ZKsrU1UsqkXPHRkATkRKTNB+JgaB/iehpFVxhVLwamXMrqI2WpnWBcMDoa45b0mJWQL9s679d9H/2RrBwfEbRWxBV8LShLmsefXKtuL7BqrThacXgRgvM0qVTX5fz0SFB3znXSLIhTvBcGL4zBkYNwu/FMVdjNjbe54lEq5l91LG5VLvvPd7azwXH5HV8yEXxid2cI8xXi68lE9zwtc7rf6330tfWP3+Gp4IWLr/Pu8eQSJb9OlrUDn45052+uvO4LLukEz7U1XDy9Lkvq4D3Gwh+pAOV92+klvhZ/P38Z35H++WFuZ0hSl7jGnFqlYFohalwTdYHmzCjMqYPgyBWm/UT0liKqLPLlyn4/cbfbE4Mx+m+2r3DOUjWlNMY4MA6RNE+GFHSxLtMp6RUS0USkVsTHmcBW7VwNEbGqnFrZbm8otXb5+Iz3gVp0fUacWGWJ845WJnb3e8Yx8vbu+4TguZsOuFYQLFjabLc8PNyhOiKizGk2QzofqdUqO7abEVWY5kIuM6reuCd+JKdC9ZlhsLQRspQjL+kN16tm/InBoaURRBauha7BiyL4MBBaoZZ6sjwhMgE95y9qKqMqeC8IBcGvKSTUqks0ZYTuRVPyqqMhKniOadJrHdTCjxjHkdYad3d3a7CxlCYvGhzrNov4ly7OvPSg2PgMYOmq0j83HyEHzZ0MxAs5+qjxst7BV7kAx/M9TXOKHNM1a4n0Wq5sQYVg/JamHq15/Q2aQssFdZFxM+DDYGKHnYCNOJxXVtmAfvwmlqpREfCBGAbmNHHoVT5DDCsJXLWepJ/6NYLOO5GVi2V/yz1jVVpgQS21EZylylQdpy65uhhMNgt2aRWHErxADBR3LFFfKr2WoFNxqJa+PgwBxsGxqY2Nr4yuMjjwKNLKESlc76n36Dd/AADy8T65DE6W7/d0IPHcZPT5iekLJrNPBClXUzEvRU9e1K7nz35Q6P1T7Yc7QDkJvOUFCN8Zm/gdu74aepzmCOV0L5drv3+Q8lz1z/+Jpid4kaqYRHltlGa59eAFISAquOZoWhDnKeq5ezhAo3veeHJpzKVCU+4f9taZN9huRlyIOB9IJVlHj3RCXiXGYX3IjCvQTc1sCF3z9TZrLEfehw8rVO/EmWpnbbTazI+mwjhsWJjz3ntStvTU7uGO6h1jDHz6/Ts20fPJd7/L7TZS6kxrmdoKu11miKGniAq1KjGOtFaZc2azueVVvCFnBTwpGwoybkZKqeb148wqwIdg1SbO4V3AuUApmZxLD+xMet+Jp7REa9lQjZLQlrqHkHGmFkTJqkHoyEmztFj2tJYJsaehPBd8ExAarSSCMy5QzWXVuDF849ipSk8RnZYZ12IGdCEENpuReZopfYAPMZ7cU0di69Kcc9RVBbZzejkGLHSUA44pJgFqzr3a51zI7PTfyyqe5dinCNCphsol+rKkrays1hAwJ+Z5g3jiEFbH4taEMUTwAcW+U5mTGe3VAkr/fezeC2qaI85byiuEhW8C4sUE4mpdJ6DL+ddajb/iwvp9vPdstzdAH5zW37ZD9v3JPg3KjkTkRmt55WWVNNNKNQ5SW/yNDGE4JemeVk21zmWx+1BxVIIUNl7ZBuHgrPy+qetJxYUX9LI+8zpD4otqFwHDerDuSvVs4HHOEXkSNbk43CMx/Bf2/88VPjwdROjFu6fW61L21zd7x16/2PZDHaAcwWZWjsjyvl3f5Ml2+nicqcg+cdynt/7N0K6dizzz+eV7t14DsJu/NNbSYrrKacX4DaVmBicMo2euCqWbB6onFfqgGMjzTGl0p1Y1j5kwgDgzAqzNIO3u5DcMkRgjIZi7q/eenNI6OBpXwMoray1dD8QCpVoKIXikEzxjDObVkzJFK9vNjQUJTTtnAcRBwHH3ve8zBCMP5nkmeGX38Ak+gEg1aXORrtHaGMdNr24xRddGpVQrZw5hQMRTaiNXZRgCw8YqXyx9k3HNDBFj98RZ0ARTbK0Mg1V9aFNcg1waJee1U1dVqjYW00ctFXGV5qycd0GVjONQQUpHNCq19KoY192qu3+RecyYEFznMxr3QMw1ehnUliBlqcyprRjyImL3QAg2QNeKUhjiscs5RQOOKRVDjBbxteU6wVGPZe2Em1pgQltLz09VYE877eVYS/CxfLa8PtVF0V5VcwzCjkhNroXajs7XIh4fHKLOfMDEdzfpruSrxvlZtHfqUtbe2ipj7/r1D51j5Xo/1lqFdkzdLKJzrgeLy7m2UnGdjG2XUdZSY7sOIM4jofs1Ld9Tl0lbIwSHdxFpFWqlJumeS/27L8TfRRizX7/T0vPWf+dam3FXst0LrVZoDa8QxRPF0fCmEI1DFjPKd7bLWehln/auofISHXlqX9e2eT74eG7ZU+9Pv/R1ZOb0DF8+vlwPUvTi32XlXoF17fMnAp3j8/XsWVw/3nu2H5kAhbPX7xcsPIpG37EPmxN/9v1/Ees/t8716P78/ZWtTl5rf3uec2wdjnXiqBVmrUack4bfBIo6WskE9QjCXKDVzDhAmHKfjYeOjJhrbmuN6WC6IMKGECIp7YEuD+6dea44Iap1/l6O7r4hGv+j1tIfaAt0BLES2JRxzrEZxw7hF9J8oNzcknOx9FSf4ZdSGWJg2u2YWiE4SNlSSTlN5JQZxsjt7S13b+6ZNTEOQs6NGAMhmFNxVSW4ASRSqgmLOWcE1Zwb4xAteJJyVMvt/BMaBL9Un9j1n6Y9zpmsv/MepwOuinFXADT3NFnuFgYL36LQWqY1C5LAgrAln2yVKKWnADo51VuvqM3M52QlU3bEQZrxHfQ8SFk+X6qsluUhRqSX9i7ls6cpCiNyniAyeq7BYtuZo/BiAGnBltLcsarHLB86CtN5O4si8ek9fKk0e4ngiInJoLWs6anWGtSK9vVLaV012AIGfDSXYIx06oPvPlCeXButFZwPDOMGsMDNBxNWC9EUg1fbADVScceN0FaNxLoERtADM78GhYYUeiOMqyn1SieVL0RZRw9sTp+RpcS6Iy0CiPeEITLkAa25c52W9KCu8gNLcHNKltae+llQJUt9WdqvlIxTIaJE8VSr9+lkc4fgXziUCVcrFi6wiKdQhHN+xnMBhI0u67IVPbq27uNlL0rzXCAo18ahp/rtp6pEX4ak9F094pScBirLOfT78Oqvo1fP44tMA/1QByjPtcvghYv3n+cS/mbCSp5uz6Mk7wqCLD5ZssOKqT4cywKlG8CpNoboqDjm2uhG75YKUjO8i0NkypWWm1WkiKylwybxbVoqVpJrPiaLqqUqnTsilNr5EM6RcyaOYw8eUoeUhdLVM4dgaqqtTQwxrpwC0YbUQpkPHA6TIQlakGoKsJSKtsybN2/su7mK1Ibzgd3DPa1VtjevuX3V2N3fMcYBpDGniRgH011xkVbNdyeoknMi50KIocPx/RqKY1GMtRmzWsfdaleOPZoHpnSwMuNx6PwC0KqglmrAOVozsiutrcRmI0TG7sdjqM/SES2oyoKa6DKV7bN1muDc0kHRy7NNS+WsJPhEodVxFGZaggxVZRgGG9xzughqltTFMSWxojLOlHFPZ6fOn0iiaxd06/estgadtLzM7E9Rk0uF1qWt6ZLWegrHSupP0ZZV64VmaESjew91kz9soF0MGcXZubblvPr9aYhLYLPdMA7xJL1mec9SLCDwHkIX6LMy/o5eaDtBdHqlTgg45+15wcjqy1Nsj/B5WosuNmhaMssE2jRcVu0XWfx+liHU7gk9JUlXPbtGFsyU3rlaAL3sw4lpoQRpeCqi9sybs7RVPslJN/X8IPcuBPjd2zw7wVtGj0cBy/VtPysH5bngxJY9jaA8leJ5eXt6/UtC7QJOPUmS/QHmeH5EA5Qjg+LCqQdZY0E5+f95ezeC8ZJfZFlH+gzl0VFesI+TvT3iqLxfWuklYObl+mtXJLIuUegzKlu+lPqW2jiUwjZ6ijMyZGsNHzwNxzRPeLEZc63m7mt6D8v3suqKw2FvqrNxwDtvFSzRuCSt2v4WfYgYzcflaAxnTsvBm1lhydmIqMPAPE1HJ+BWyfOBaX/PzfaGGDylZEqe8XUmDp67h3vu7u64HT1fejUwDLeEYeYwHxhGS7ukIRop9iZAKZ0wOxIGUwxFrfLDRLMsLWDCYnZhQzAZ9fVH6XWXpXZOiXPUnHtA5ymlMk8J5/zRVLEW0ELTYlVPuqQIemWK1u5KawiNlRkLIjYICqcDV0cyLJyBNfiQdYbdajWlYd+l1lmQEKv2KX1GvgaEJzO7U1TEApgjUnRadbMMstr3uXaOqrSe3rD3FlCc8iBopn68LFuE2ZaLXEsPArv7M4hVErXaS+lhde9dJO472pJzIteCVenE7jkl4MOaJvMLX0FNtC7EYORiEVoXq0t5prSCcsMQY+8i1By9nSAuGH9DMOKqGqcjOEHVKrxqU3PjpiI5Ewdbz4Vwkq7qZpCqXQ+nl5JLwyFdn82t13OR5W/FhP/QNdawZ39BxtaQpXHURrHA2PwKekDiPMEHYmyMsTEmmL0QmiKlARXFr8/D+/Vox9/06tInUPF3hz3yeHx4Yjy4DDDOK0ZP/39l+96lngZll2jJc9dj/R5XAxM9W7wGE+vCa+ke5WIjrMb4AlG5crx3/m4Xh3mfgOZHNEB5vl2iK+8bjjy+4c6DHbn4RR6HQs8/KO9uT90Sl6mcz9cWyPjafpeJVMP6pTlZemTWQGmNSGNwAU+lqaMWZdwOIEqujaFDuymbv00MNnilNBN7NUsTIc+JEDcd7uzuwsW8gIIL1FRW/YbWjLQnwQbHBZkoJdvVEaUJjDe31JJI+x2vxgHNDS9wmHbUlpmTVa988sn3eXCNTfgG4XbLsP0yjTvm3Hj16ha3P9C0AiPDYHyAeZrX9Ac4vI74sCGGjWlfqOJlEeGyeymGsEqgl7KIyAkhesRDrdnk4Z2VYJdiKp+lmieQ0nVHgCjSRX6tw3R4VmXbZZBp0KSZ6qkzafrWKtIMAXPBiKBOgqU5Wi/fRen6r9CgpI5IADWXVQvFTPPaGiScEmpNhO8Y8Hh/dHQ+HSTXUt9Gv8bdkFLdsUNX1n2vT4B2xEKV5o4IzjGltSAjpZegOxrGLVl0H0QaqgW6PYCJtDVKUw5pBhwhggsRHwecN1TQ+86J8gEnhi5FF3Ah0LQr06olSrVl5mmPk21HCo0PJViKLwZPCAI9PdLK0ZBzScs4qgU9zlNrpiVwtZruTq/Osm26O3kvxnfIGpgcCUamWyT9b/E6gp5sUrtXRXtwJ4GjR1QzHZiO0lHtfgGzKBg9fHBjwVITSA2mJuTW01rudECVi3+fapc9+LuGySPB+8n9PzX3WwOI8wDk+HfcUE7O/3wXNmV4NHL0dJWKnq39xBnauKF6Fjgtp6vnKx3/vXx9XImFHO36KktM8tT4dJ7CWcQMeXL/Zxf1Mwjf/MgGKNcG6tNl1z9/vFCvff4IzXi87fUQ5rjPd6ZYTj5/jJ48FZxchl4cYfx3tLPjnZ61nLymh1Ynsx0V0/OwtIOSsNJEonFFcmmU5kA9rTmmuazmcLkUkIb38NGHH9Ga+e6kaUfwrrve2sBnELTxAGou3Gy3tGowvq4kyl56nDMu2Mz0sD9gJnw24w/BQxN2hzsclZpnUq1solXOpP09u90e7xzbzUhJE9//5I5h2LIZt9wETy0zqTjG24+Nm+CgSiMEQbro1TztGYYRFyParCKpNCWnCfoAspBkF8QhRjONm+fUFWcjzntDLVrDOUyptMutO2lkbNDTZiaGuXdGTjA+Cb1OoqMQuixprcuRGzfGVEiPfIsC+HDU6VDtKRAHwbkuq39EXYCOapmonKXljv5H3lk5d13QjpO00Ok+ziptmnakSI/pQt+N9fq9d1pts+jjtKacEojXqpeFI6HVqrkwXynFdTVV+sBcqDUTYpeiRxAfGEZHbo1qimuoGofCBnorKUaadaonSOdK5hYh50TownZ0/pNznmEwF+qec2PxfBLvcNVRab2CTVfExb7zUT4fZ1VDCyqGNEQ9rtsDSHe5XtCho2Fql89vxcTyWul/p+mk2nsGC0gUQ808RyuCJhb8ism1mCZK8JToaVWpW6gqHBrsKySFopZAlNNJ23mne95PLau8d0BzfZ2r/fC1gOTReueaPsdQ4QJZOQteLra+QE7OiML6+Jh6EZgsR1zDs5NYRPTxspOvdj4mXAFU3hVKnE4+lh9j/fa9fz9JDp6eJS/7raz9yAYoP9B2EblyEQR8gSBGP9zjoOPKWl/wUZ9qFw+HLsRGKEv1A4Z29PoM5uLwLZCKDShjNPn8nCtxNO2LECLTYUcUVuXYlBJDsGoO58RmiaWs/iCHaTJDPy/UUtnv9tzcbPFd5EybiV45gaEPnALkdKDmmZvtSMkTORe8RvJ8MCNDrOrnK1/+EqUV9g8Td4fC9vaW6EaQD7h7+wZB2G5v8QJpPuDE46SBqzgPKTecazgKVDOuK6hxSTovxsWBnBLzPLPdbnFOGIZIynP3JuqKnW7hdBwF3Oy6OVoLBLelukAtM6qNUhUvDUJFpNqMVmy2pGpk2FZq9z4yNMo7k7pfzCDpgecpYXcJcpaiYwsQjqTX1oOtWgol53Ub6eiK7wFXOw1E9LyKBmStI1s5KQpaG426dt6naaFjgLMQZxcC33E9S4dJrw4ygjCuUE0ehOCiXV8cc2nMh7wSTb23yrNh2NIwlVjFU9VSJYb4hNWcsFULDDU0WsrEQdbgrVYrHw8xrFcSeuWS5XXwNHynCzVnaKI7SVstCsAL+RkFL9IHOencHbeWKcta1GNGkqZj0n9JsQCLjixpMR2UWux508XfqcHC+Fm4LU6W6ijFuR4sasUphAbRQ3SQqERRxuDZBiH6huRsunAdybogXby4HzrrkN5j9Rcf6Ur/e4qcnAcy77e/UxLucQIsV3f0HAF1mYosgdAlqnKkNvzg2hdNkIUf4QDlMerAMeK7eP3cNku7ntPk6o2kvLvK57ljPdeeD05+o4KUY1seh0pHi/t1TV12XrwjqWf0I1PNRBdpKPsps40g2nh1M/Drv/5ttpvIoRZisGDHlwpemNPMELeILnb25oAcfCBuNpSS2O92iJh5Hdq6L0wjeLf6+eScycUqfoYxQi3sDxPivEmKt0aIAzevXhO8Y4yO3KByzy43HqbGlz++ZbO55X438+kn30c+Gvj4ww9AIt5hnX859BugkHIhIl3wrBKjzUDneTYNDB9W75V5nrsSqYmytZbRalfZSkwV58xTZ5Ect9RARboCqvqANhOta8V8feguy9pM0N78XOxeKtVIwPT30dm51NpQCity1iHops3KRnuQWDv/YOUmqK4DqaUiOkcFAW+8mwpnHVnrpbIhWCl4W6d+0itPOkLTGo1y4sa7aJi49ZwXAqi9r2c6KCbnjom9OYEKrRZLSangBxMWFLFgotaJac6IVIbBWUWSD1aNphjXyHlaM6uH2tNoRpa1YwbnadqYpolxtCq1JRhzYoFP1bqSTVl5NHY9l+obKzNvK6qkqj2l5pFT4m9TcOZF5Hv0uZSZs1Z3GYfM0nBmXyE9lUft90lbqpYMOdNqkvfKUm2kNBPa6cHgwts5okBIT2dp7eJvxoGJLhClIb0KUNSUd+tFeuTpoW5JOR8DmuPQ/GRH1a/B06u8D6r97s91vS+f2v48ZfT50v5XOScYinZMr/C5AohrAchxHON0xm73xGc+0rH9yAYo79fWK/uoXUJqVz594dKXHe/92/tBZvD+QdF5u8SKDPaF7tWCVfHkLtgVQyBjM+rR26xRKUw5Q1NiGNgdElqtNLLlhGwCSyFCrb2MtHfQJWdSSQQf2UTjtEyHA/M8rQM9qjYDrGU1WSulrMJSwzCgDqZ9pqqlLOY5s715RauZyJYxBuZpgDDwdnbk3YTGDc2PDNtXvP74q9w97EgFplQZN1vjiWAOyU2bVc+IUErDh15KLB7vR0BWpEH80dgupckQoNr5KiF0aXVTsq2tANBaoZQZbTOqheCF4CLBmzx8KTZolFIRyTgZeuDTtT9qI/gBCaw6JSZ8ZwOqCP18FzG8ur43UqyVurY+KKm2lf+hHBVYfSe6LqqnR5n5Y4s+rERnQ0P6faatp5/Aqp0MPrbxsXV0Z+k0l1TWERXQdk6SlX7dFoG01hIlT6Q54f1gCN3iah0CIY7kakJzlEIcRzbbLSqzDdY5M24C25stc8ocDgdEDF1xnThrmj9GIl9GkUvxuPW6NUudlJIs7SLmf+X6dym5rIGMguncBEsDinemtIxVDp0Oxoa0LM9un/uvWP/C32osUv/Lb7k+Sz0ItU1av+Z0b6MjllCWsu0FGau1/4anCsjSA8RGcDYANSqqdZW/f9yuDd7y+PVz3ZoI1yTsz2/F80TI8bP3Q6zX4OnZ03mMopyGK5cnp+8c8B9/+niLLx5DWQnqsA4HCt1xVY+33Gc89A91gHJJkPscezrb5+lrvbL8nDh6eTOvaz3a7kVn8sz613Oi5/+eRrlnN/6L0kQvbH22fCR2nQZcvRQSKM2RqvIwZZxW2ERC61C5EyqFKTVqmXl1MzLNjTJnbm831NI4tJkyOF692lJLI6dEnmbw3UgO2O93TIcDKc3c3NxQa1u1U0SsEsICmJlXH7y2Abqah83+kHBhwIWBKIEYhJoTDSX4iB+3qPOMbxOlRW5ef0TcBMJ4w+uP4Ou1kqY9qRaimqCctkqTgYb5koBS62z6JiEyp8Jm49cqFzoKsMz2g/PUktbvtwQFdDGypg5kqSwxnRPRQlUxoyQarYudNe1aYX0WSycuirPqodKqac10LkdtprbrdIGxZQ3qQnBIM4KzuIbURqGLdIk3tVO1fSylvKUUtOuWlFI6umVBinPOpPmbOdyursQ106pppSz6LEsqIXiHqBEctKckbHDtAaxlF1hUhEV8F9A7CtUtxFeHaXTMswW348bhWqFUG0ijjoBV5qg4VBwN4WazJcSBeS6mrFwroZ9HrY1UGsOmB3X9e4cuNtgjN1oPsJbKqUXiH8zzJ8Zg6ZVWUVNINPG4eoK0iJ1/UzP5a62Zhon3BGfl68fH1fhCy/VcOElLcGFeTLWnhXq6hSM3aPkzTtIyIAlUU8DtoR8LDXWtqBJnHko+Ii6jzlGKUnspdXAOj8M1YWG4rAj3I9bEUwjDRT/4jm7t6X7vnB9xGZys6bGTPvX5MuElKHw8gXyK2yJn3+F8m9Nx6GUoSNfnfWLd90VSrh336rlcBiMn7z9LCuiHOkB5qr0kRfOSdZ7ePzwV1Fj7gWf7nvjXDn1KwLKPvyi0Ztm/vTDlzHM0aMlNL+TZuTRyUcbgiM3jikHl6hqpNfJ+Zjt6coGH+3s+/uCWYdhQqqVBxurQBvdv7yg1WclmLWyGkZQS07yjFiOVeu+JIVDyjGplGEYe7u+Z53lVo805EeOGN/f35Ca8/uADam1sbwbyYYcfNzgFQsXpxvgwfuDDj2+4ff0BISgSN9zGgTkZ6lKmHTlPBGfVGriBKR3YvN5aZYyHed4Twsh2uyVnG6yX2f0C+S9EzuV6HmXkPU5CT6kUK7cWDz5QMLXX5Sc2QS1L7Szqn7VURBI4DzXifTSeSVuk3v06g7YKGhPE0z7TtxSIpQJUtVsKgKhxVpa0nhnHSQ9oTIuk1NqF/eoJQmKpm9J5LrmTm62apVGr2RG0ZrLv9jgtQ9h6k/Wgo3fCC1FvQSXEBoaFI6P9unR8AVMvNjJsqRlfE5I9rX/WjOWH72mU2lMctTaCi8gm4GtjToV5mpFOcsZZekd6+m5BkpbSXvFWWt/aIglvv53zVnHmfQ+KfPeXKoVSy5nvkPZHepmg0oOv1pTmdB3Kpava0lMxcoIiGOh0TB2akNqS6jt53E+utbhjVV9bUJROLhaRfh/3qiBMgRjBUk4hUsnMuTIlJZfF6LI7bOtFn3UNIXnU3MVHV0z+Xtye7s/XoOSJ8zvjkZxMFK8e5ang5F199PKD80SwwGkQcwxMLGB8ftfv2y6Pf0qb+KLbD3WActIvWZOLH6r//9GNJY+DPHiceDld5zFnZYGSnzg3HgeTn6WdsaXPP7n495nt3/eYtuFTO+wISoeOL2cHJ5lgVaE0o2PkKuwnq8jJKpAVrzCESFF4e78nOFDxTHMhpR20zEcf3HB3/4CXxs1m4LDfEYZIC5Hd/gHoPjW9E26lUheNlGlm6qZrNze33N/fMwwDcy7MufDxV74KKow3kXmamHJljIHtdmMVJ7Uy3d3j4sDHH31MHCJopopn3Nwg4Y7b21ccvMfPkVISN7evTdbdeR72Mx998AoFQhs4TImbbTAkpTseO7GyaddFyUopRnZU+7O0lYD2MkUx9CP3CqbWLD1gXMMMfYBwsmjWdA8iV3CuIK6hpVoJqxjK4f2CoNiI53wj+NB/YzGVXj0OdEaGrQTncBLQ1hAx1KSdBAhH5MJQkjklq0pRk4KPwZvgnJq2TWu2zyauq4+Wk7vrmGJotXe+HalppsHeB2rpTs3CAuurdvdt1EqwxQZXK/u19VLO5GIB3WZzY6XrgI8DIJSSSHMm+owPncfiA9oypRU2cWCzjavvkLaGiz0Y7wiG0EXg1u+kPSArLIq9hpEvVTaYjk+wc6eY3YRoLzleDHuc9MCooxv15PEVWUueF1XZpse+a/F5aq1SsiF3VimXepqxcxhOztn4HJ0YrLpWj1qJtrMgqQlKpfTAriHgfHdm7mkuNQVcT6Cqv9JfPlaxeiqI0SvLHr+70l6KWPeDLJPTR1s9010+RmfeNVl+His6okun/TC9X+4l26fg9vIbPdr/yXH691qCjJVquwQjl0DJe6Ehn30k/KEOUC7bKUlqCU5Og5HTG1yPSz5HEHEJQy4/nJ3LZcDzWdv14OSpJ+JFi97v+I8WOPTKt7PrK5gofh8EmqKiuKaoempVpqxo8EQZTDQtzwQCwcN+yuSUKWnHRx9syEX55M0dH394w5u7O1rO3HrfnYvt+k/ZBjb6jM6HgZITh2nC9Znsfn9gf9hz8+qG2ho3rz4kjtu1FPZb3/4uwXs2ww3j7WtDHbxSmPj4y1/lZrtBgPlQuAkD6iISt4TNyFYcOVoV0Ob2hqow58K0e2CucHNzgzjl8DAzp8wwRIZhJOeZ0syrpJVC9IFhHHBOyFVNz6Urp5aUUe3GbpjqJzhqExvk23Ewj97UShzLuN1l4uXYQbZWWYtxxeHFDBunmkwUrjWCWnBkBn1+rbYw5KfhiuvKtEJrBenuy9LaWnlVSuscmp6amIzIHGO0waxltBZEC1qh4fGdqFtKIqWC936VuQfWAMmJEn2kqjnzeh8pFHLL0DLiwppeKrUQgyMECxhKMR8Y57eEIVJK4zAdeigljKO3CbpfvKD0qGPSKooRqn1wlNxQ8QTvaDXh1CNqx22l4H1gCNEG5c4vEhF8D1CNQFpRr7QeTGirFiw0S0lBW1EWadaPibj+5/EuYgO6iRo6vzhV9yFsTZ0srfsRdbG7II6CM/Qqz7Q8WdUTXTPFd0G7WtGOljlxBGdBkyKmZ4KYwmzvBbQHyuZMDmMUtk1I6sjZqqXWWtilT1kQmEcd8yWq8tSk7XF73Mdfk087jgaXlTmCrrycY+x3/fhfDO3gMlQ7nUYvI93yBB+XLwj2cjbrp1pP1j3dvx63loul2tN/y2i26pgcQ+zHgcrlb9T3dhIwoy9Hun6oA5RTDooeF67v+zxhXf/y/brs9IZ6wc318lTQy2/Uz8sgf9c6n/ecH8N4zz+MS2paOP5OiumiBBGcaNdmwHxrMA8RqmmTvL4d8GHkbjeRsjO32HliO5oQnHEX4P7+njd3d3z88ccGN3sj7+2niWmeceLY7SerfKDhDjPinLkZixmsfec736WpcnP7mtcfftAJjo0yzdy+/oDU0Q4vag61LlDFMdzcIEPAo5RaTeY/jIShEuItmxsLpMRFhnHDw8Mb6rS3UuthNDXaVEklWaqjFVxhdXE2Ubayim5pO3eiXVCjRcRTjJ5i3Zaj63KYzkRrDRcWDZKCijdvl54CkWBwedOG4s+k4ksxYq4Fc21Npy1pB+MsCHJCdDVy8nlZrPd+1aoRlsG59WN1Mmvfx0LorbVXKNFTUcUQIRVopVH6LN1ABFNjLaX0iierdGmtkXMGNY6PiKPUgqrD+WAcHC2YBIxSB9PrsDDPrnUI3oTYThARF4XNdgu+9iDKUXrKZkESW23UmtCmDDESQ8S7aOiTsw4/Z9P7yUktbRa6No2Y4JkFVGYJ4Hqw5rwzcnUvTT4iJADGZVkNA2WpIhMTvmu66pugevTpccdy5FWHZuWZ9ePgu55MW5EZm4ws1VPHVJsTxXtHiIFQYRzMrqLiSSrsigVIponj11n+mqQ6q4I5nRA9Dk6E8wnq2QfrP+8eGM+Hgkuk4+nPrgc8Z6fweKy5up+n93GObZwEBXot8Hh3W/tyucxE2IKrSaQru7+OppyER7L+bx0PXtp+qAOU36ztBxHA/CDP44vffy9FXGfsbp3116ak0jVOIwwu0hRT8nSBooU4bmjO8f23DwSp6O3Id757T5AK3DBsIdXKdLfne9//pNvHOHJtqGbmOfHmzR2+D3CqXTa+ZIbNlnEYwXvu7h+4e/uW1ipf+epXzbMnDBwOB5vh+8AHH32JN59+YpC7KnFzQ24QxMiycRyYm5DajuA3NAm4uMGFkY2LeEyGPsYNt68+4O2n30PygdZKRxNGQoxMhz1Oxc6xVBAzmwNM3MsZ0rOkhlbuBR2lUnB9hlObLpPQjiphTsBSGUZdK2lyVbSb9xkp1aH16K9TSmUpjMq5rAHKIm0vspBojajqOulgFU9T+uB1NJVbuCkOE83TkxmZecBor1iy1GCplbQEPnFRUaXrknR19aqmj0Ixom5PKVQt5iLUy3LnPOElEmLs4oJmK9AUvI84b9om3o9WgeXD+n10jbh977/tvooxMuCpajwSM4FUmha8GEen1UZKcyf/0jVwXA96rOQ5Z0NUbJhzJ7B6R3mbdl7MqSDj8T5YOEALJG+8FwFnOkLrM9sds1d7iLp4IcFCLm79/lo4UrogHO5I7DbUxJzDF7PD1pqlJx14r7Tm8K6Zlo9g/udi770LlqHSJWXUi6pFoEv0Pw5BWL/3ld7oieVPt6dSK5eD6EncdXW7Jyd1V9+f4fln79/dzoOAS32i8+VPndEl2qFPfPZcM9L+y7d5OdJ12X4rQHlh+6yD/Uu3u84zeXLt0yM8Wn7swN7vHF5C2nrZ8hPBZzEJeJuhO0o7Sp6HEGnOQy2EMICY2JVK5e39PZ7Kq5sRdgVtmdvRc3O7qNE6HvYTuSg3Nzcgjk/f3kNrPNw/sNs98LWvfplGI8SRTz75hC996WNCHFEc3/vep9zf3RNj4OMvfUQcBpx45pQpTYnOM2w3NpMUzzBs8E6ou515o/iB0GfQqlA++RTxQsURxw3jzS2aMk4LJe9RLWy2r8nzTJknFpGz3cNbxs3GgoMeTMzzjPMRH+hBgOluxBCpi85HgVQSJRdKsQDB+yO/orXuySPLb+HQaoFG1ZkwjIBVrCyVLq6rjVp1iVs5Lk4CuZQuZ26tdeRjRcfUPvc+knNeRdkWotiCotRa8eKoIZuOx8ltU2oxIm7NgH2hJbiptaK+K56CpYF6CW4uRu5VbejCy0DItZJKI3ob+HIqzOYGaCXtKNM8I+IYxg3j5oamjqaelCsDAXEdRu+jeG2mdhyWgbQHEWlOpmzcq56cr/h4fKZDCHgnlF7+7pzgZOyS9h6IHcmgBw6FnM1n6pSEvASGFv9pdxA+qsO6VfSsn1vnJ9mg61dkxfgzJunfiiVk6PcLzhCMupQ+9zRS6x5cC19JKRbYOcci4GaXxRG8ompyATU35j5L16aryaAhMBz/TP4Ym+DYdT2OtSeQ7NU0wnMYxnu2K33cZZBiy66td7Fsif7W1MwpngJrANpfP9VOg5Gnlp+mdx5vIyfLl/d2TR+v13MNsuzjFA1Z1u+Vhccd/kDaj0yA8oPECp4f4D/fkT9L6dV5W4KS6+fzeVND77/tMrOz2ZFi3jOtQe03dHCOXJXclNQULw4vnkYDF5jznqKOYRyYUmW3PzAEuL3dkiuoBA5TJuWKc4Fh3PL27QOHaQ+qpHlmMw5YYsAzzbbuzavXVG28fXPPt379W9zc3vDlr36JYdwwTQUw5dDXr18j4hi3N3z66RsOc2azvSHEgOwPVkKKI25ucGEkRCvzrdmcm8cxcPP6NelwoKUDjkhNhhDdvPoSB95S8oFhiIgUDod7YhhPtF/qijYtv21rlVpt8Cm9BNVQKpu5l1op8+LlYjLjIorzgu8/UfSu80IyiicOI7Vmci4rGmAVK3Wtelr4VFay20zXxNlvvKR+Fv2Zpo3Qj7UEPUZQ7U7Ara2ePfQAbehmitqa6YS1Cr2qJDRDVJZgx3mHaC8xl4WPY7dc7fsTAs4FSoMpZUshBWfojjrThXE2sNbamPPi86NGfJbANFu5cdVEaIXbmxucW8TNjubz5ljscWpLpskMMY/VSBVONG6AY8DWGpOarLzpl5wQi/tTtJBtl20X0Tq36Kv0EuhViK2jZ3a9LNhvahyRkosBKl3t1YmpEFMdRQo1547GGCl2IT2XrmWiYkjKgtZZytSW5Vb6BMsctftti3eYPk8wfk5YRABbLw33AeexQAW7t1WE1eiL837t2Es+h6Kctsf96vMVJ0t67nzdJaFyhkRdQ1Hk5CzOdn+annr+jJ9ul0iJnvzZ+2NAcVx2mZJ/GvV46nra/o7pt5PUTyfuH7+drO/O/732TV7WfmQClOtR7+cbnJ+D8i4Rgy9qvy/fx/PL3zfo+LwcmOODf1y2BCkNLEJhKd/sZnOtUarN2iuO6AckOFqaCeMtLjjytKM24SYOIJ7clP0hQ0sIwgcffUiMA59+9y0Pu103Wgu0LkGOwne/+z1DT0Lku598n1/9n/8b1cbXfttvQ3xgtzt0Kf3Cl7/8JYbNFlVlmhO/9uvfQlvhq1/9KjEG/DCauV8c2IwjcYw8PNxb6ifNVHVIGPBDZesdeV9tACiJ0oxjEOJND0IyQ4yUnCgl4fzQr6NHkZUnYMiGN9l+t6QYmnFInHQnXaVWJWelVLqQmhDU413Ft4pzmegDLsQVrVkIz4Z6yFpKK84R+oBYikVOi9jY4ops+ziqtYKAQgyB2o5y/CLS0wqWGkhpRgTGGFdjQKFrtqhQqymzasvEMZpYWUc9fHCrN464YGmh9XPz1amqpFKZcqXkwhA80Qs0tSqi1gc7NxCHGw6HiUOqDNtICAOjBFyxMvdpyjiB25sbq6Cpinq7yVttqDPPpM24YQa0JqBX6yi0bJ5HgiLR42NEvFXWtNaYD4eOogSDwPo1b21Jv+jxoVLt16kbKXpTYHWdgLuUWDcaUrUHJFbC23pKanWMNrtx1qq7ZgJxpl3T9W26Fo2woCl23y0aK9Irz6QtAWkvG2apFDLjwyFagOJdd1NWZRGt8WEgaKBUwciTnfgLhsr0MfIRcHLe+zwx6MmTa13vz44oweWWV6XizvZxyYDRR+ssyrLv0zdfD6SUa+mdz1/me0RPOLtW9lxeBhs9bGYJWxYUaA1ZRDnq8bSL7V7WfiQClJeU0i43xSXA9hvdPksg8IPkknzh+17vbXthswnjgdfu/6GlIdHyzKUqWhs+eNwQqN3O3jmP0vBhYBwCPgouBEqtPOwLUZQPX28ZhoHdbs/9w+4oGtUKt9sN2swsUEQYxw33ux2ffPIJD7sDX//qV6lF2e8ncp7ZbDZstyPjuKGpMs+J73z3e3z65g1f/9rX8CGAODN1CwEXI8NmQ62Fw5yIG6sGCc5R1VPaZEq344i0QnETKSXGGHBhBDkwTwdkEFyvnkDsMXbYgFXbMb0ROjnSBN1sVlrTopVipM1aoeEoFfJs0VkIlTEqQ4DaMrHCsBVCDL0ktutXrCmdth6zlNZTTIszMZQGznIHAN192cq6m0LpJoH0AXMZTH2v8Fk4QTnnXk5tomnmr2SD1NLPFm0EpGuRLLwmT4iOGI3knGvGuYgPvcKodXfiUkhZaU3QVCnSGIJDXCQV0Fa6WuwWl8F8dZxJ4PfUg+/ox8Nuj2AKsbUlQvQralRbwTerUNEYqQKL6i6Y51DTtRgL6AEGtszUW3W99s7iKErNa5m1dm6PP3lWl/SN6+Rc6RwQFvNCLICSLjY3xMjCV6k1U3KmlWzmiM3UXh2g3cCytUbJRl6231NY7Jx0QRrEBiFDZCwwDL5bDyzl1iJ4JxaE+YIXc8V2GIoTvSM3j2vSx0ar/JFe6WGLlsDhsqNZLsbLuqUFIVmv37X15PT1yWhxUqf7vhPfz9rDPiUrv6IaV77ED0KL5KnA5fo658uOqM5naz/0Acpp4HF6GXp9A8db87xdA90+z1D9WRGI51I865k/TiN+7nZ5Pu/HgXlmvyzP8hKc9DmaGhxsfDubhZcGbUqM3vH6ZkMqhbkUc6z14KTiQiP4RuzOuqVWxu0Wp5XaYLc/ME0zznnGYSQnc6HdbLcggvOBcXPDw35PLJn7u906gDZV5inhgxn0ffD6I6oq+92e733yKbvdjg8//JCPPvq4D35LaamVcDaBKaWu2SiEYWMDQSmG8oyOwQ+Im9YKFi9qZbZly353D3PGAbUmasud52Gcl83GzANzyuQ0E3rVRikJqiKi1FpsADM9eGpzTEmZZ0NIfLDgZBxgu2mMFNQlRCIuhl7R0RiG0KtKLCVgQY+VmR7l5LtzNfSqEKsuyTnbexFys3RHCJZemGczPaTP5o0rYumQVvMq5e6b70Rdm4+ZKJ3abLanMhDjazg/EOLGVG19V5l1JinfihFmcxNyNTSqtoSnstlsUInM00wuhWE0WwBxQw+IBRByLqRk3ykOkdaKOW/byXUky3UvHCu31T6gL8GYKtSUSLWbAAZ3Qka1AdLUcfv3dtBaJtWFR2RVTLo6Mx8HJEXXwEb8eeWOIogLq+bJMpgZgda8h1pP5bRmrs5ai0VFvVrKSkrbql67pG8M3XHdL5lO3K2Y4q7rAZHFMk0sQDLRW2EcBjabyjh5NqmSVJgTzEX7MTu6YEycrhb8dEwCa0djk/X37acebXCaQLrQt+rn8TjouOi3FxLz46NdrPYYXbmajmJJLi0BlT4KrM5Sh9eWX4yMzwULTyEx5+8XguxpwHKJuMjZdjbGLRH60+mua+2HOkC5vBVeUl29lmhyvEzXBuZHseCjlM4XFy08Svlc7P38tZxlHq/v57MFS19UO3vslhlLX66qXUtMSKnSaiHcbknqmQ57onO8iqHLbiS8FGL0xCDs9wc+eLWxdEQMvLl/YIwBEceXPv6YnCtjHGgt4YOZ8vkwcrjfk1sjVmVOlc1mNDnxVlGEYRz46KOPSPNEOzTevHnLPCc2my2bm20vvzTeRM2VlioaBB1MGyKljHOB29vX5JIoZMJm5OHhgVdjQDWaW64X9vsdcnvL5uaW/X5Lnu/xUqhaqQlybjQyc+paGTZyEYOj1Uypcw9IlNo1VFJWcoZczUG5LvwAoGTotA7TjXEV7wtZZhtQXKQCcyq0cPSIATofRUFX4WwjYqqitad/FuJrLtzc3NBaYT8diGHohnuNlBJ+8fjxDqoNjoc5MURv/CONxDAQAr1EugdGONribewMLRjGLfhAzuZXJH7ZB8BMoXDIUDSAVvMdGj0SA6kqu5SoVWlSsaAL5nli2G4gV6Y5ISJEbzP/Ng69MmjhUxnKABCiw7segEjuv7MnxtDN9RpCl/RVBdGVuzPG7n6sDWmKU6V0N20LBrQP1IaOaC3mNh0cKr30XC2QdPSUjIRelt7TqZhrs9bW0z1q1s2lIlZXTSvlSMotycwYm/lKKZjcvrcAR2RB2nqaq0lPT4auu2IpJhVoIuRa7J7u1+VmE5l7aX12yoyyqwK6sbQXXbNFjhNMxWwM5FGnfL3/uaZyekR1r7v92KenPe/5PtzFIIwsCPH5AP1Ze9Yl4Lkkup6HAI/TOtf2c7715bc5b88FI08jNJej01Mj0slaIifb/l8SoCztqXIx++z6eteCkzXye8f+7e3LLvL7cFHOPrsahx9nDM/t67n4Y0WczuDiK9H75whizohtl/sW40yUopTuX1oafPrmAa2Z25vRxLqGYDCwCiHANO9tYMMxp8y0PzBERwjCdhwYYkQkM00HSi7kXJBoaRkjgZonyDhu+PKXP6ZWXbknH3z4moeHHdM0kefEw37Hq1ev2dxsVxl6Hzz7/Z794UDsDsTizA14SokPbm8Zx5Fp3lNq5vXr1zyUwpwmAoJKIMQNKc3c3d/xlS99idevP+TTfCDNO0MMqJ3UaBUtbz59S/AeccIQvc1Mm0m+O09PI4gNtl2wbU6NUpfJ3FL5oag0SlNcViY30xRia4QgNDxNjlD/Uk68qJzWphclt5DzRIxxrc7JOTPPmRAcrSpZy6rLsfB5nBNiiEgwxdxcCtM8EX0gYlVduLDAC4hbHF4656XzZyRE1AdLA2hXSfXBHHdTITUhNzHicikEEYZxi6rr6IgRcuPoCT6S55lccjdZtCquMQZDI7wnaKTkmcMhAcp2O3Z9lWpaLFJAHeMwWvk4ret/RAakV8yYLotftUoWtME+b7WaW7f00u21CqrL2PcUkF1Pe7ZW/6J+jbU2VCriFPELrLCgLWZUKR05aWrcmFqK/cbZ0j6rB5Aq2npFGBhi1/dpaatTs0ZDS/xigthM7XfRb5mmiZzbyiHajIExZaZSiVKIkgkSKLpI18sCWSCLC++y/Nlx0AbKq32XPHpx8k7XfZ+OAOfBzeP9HseQp1NGVw75jnZlR88iGufr6fnbkxN44T5e3E6CMjn2N6f7vo6kvN9xfyQClB/G9mxJ7+e9d34TtWuEYGP7243rvWN3SIg2xiCUJqQKRT3ahNFFplJQPJvRqixyzXhnhEMnnqZCyoU5ZytP7mTLVo2LEMKA8zaQx7hBXOS73/4WMUTGcWC3n5kOM4iy3+/54IPXxDiccDIq+/2ew+Fg5xxsllqyeaQ4cQsIv/523ns++OgjvvetX2NOiWHYok5xeWJ6uOeTTz7hq1/5CtNhx33am0fQ4BGv5NKoVSm5J4+aaaFYZY553zjfS0HrovMoa7lxU7qEvOJDY3C97FSgqkmPQ7bfAFNM9V0yXsRm3GDfs7bKNGdiXNIurcvz524K6E3bJhWQma2MWEkqpFRYHGxzsuod75UhROIwMKeJwzQxRKtIiTr2KhELShCP4C1l4U0plhBoztMkoE56+bqAj9RWOFTPoQipWuCFeOLgcT5SmjJXZa6GDokbKE3JtRtbFiVGC2RVfE9vQAwDsytGgs6GnGw3W9xg6F1JidqEYYy44Jln43eE0QbYGDxDDAiLkN1SeWPpEO+syqi0Y9WOVUMfSaOmO3IcJK38V0wspnNY6PwZOCHp9qobi21M9E6bBUcmkteDkpWPYoONdjmAqp0g21Ee1iBkFVi3AGwZy5uRtUsPbI3LVJgmC4obZpoYPUTfiK4wSCLiyRI4JrT6hEyEBTd+LHV/2hZk4XQwvlz5KXyhoyErXPF4QP9i2uk+rwUNV7ZY03rvRjv09PW63Un09ALE6SVNr75+7podUan3nfj+kAcoevHvF9+u3eJf7L4fzwpecozPm6a55Jx81v19lqjY3FgBBFHIteJFqHjmqvjUGFNDc2MbYXSBQMRFT9GGOEMwnPdMeQYxqft5nlf33wbUTsa0mT8rujJ9+3u8eXvPq9tb7h8e2G43JhqmjXEYqBWcNETK6hFj0uwWXPlg+f2Usil8YgNBLgUV808R58i10IC7hz23Y2QMAy5uCMOG+4cDQ3zg9vYjpv09Oc3sDslQoUXPpJojchxMW6StA4sppiKCqvEdTGoc6KJpa6CSFaTignnpiMcIqV5oNEorNvNdTNukMc/JKmWKyaeXWhExIqz2lEipymEy2X5V6QJp2ku/jaUwz/Nyk9i5KBao+EiII02NJI0oLhecT4gMJ/wJ09+wmXcworIzJV+cR51xNWw498wls09wyEqqCirEMDCMZvbXVJlyIxVl3ASaBKZpwoAoK02OLuCC8WIsiLaqIecjwwBJlTQXUqpsNjZYz/PMnBKqWzbbgdDJzKRC6QTmNkaG2O/bRfylz8zXUmK1oVj6M+Kga4MsJa7S7QZO1DR0Yc5Y+kUWHRSOJpTLPSwnz7xD8OLR1kjzbFyUTpBeSbuqFqB012JppmQrPSC3NI/iQvfRWQ0EzeW51qVk2YKdOVVKy5RqaJ9HCECkMJCYdewpHu1pvd5HIJi6/3kfdd7v9EBGLlM8l73POxCUjjpx1jdiSNaqlvt0u8blOyIIZ0svAhI7/+fQkdN9Pfr34ljLMkW7kKU+GmeeOtbp4gWtOw0cT/d/ef6Xn9jmfUtdAsGXjzWfx/6Rv/23/zYiwp/7c39uXTZNEz/7sz/Ll7/8ZV69esXP/MzP8O1vf/tsu1/91V/lp3/6p7m5ueFrX/saf+Ev/IU1L/uboVnXeOSpyMkyeeJvhRcvl+vx77gfeXZf7/r5Lvd7uu+XihWd7sOJvOi8T8/t7LXI2XpPxYvSscCmXa4cm53VZvnqCsy5cUiVt7vEQ1IekjJpYNaASiRXg+5VPCkXcs7mq9JRBUM+hFoa3gemObHb79nt94Cw2098/9M35NJ4e79nmgq73cyv//p3SKmieHb7id1h4tM3d33/lZSSESf7d5ly4mG3Y3fYd+5EIKVibrcx0prB22EYCHHkMCXm1BiGW3zY0HDcPRyY5koYbhk3tzgXyFnNk6ZYkJGKcpgKuShNnZHNxBkqUWB/KOz2hcNUKBUWwqKKUQ1qhVzgMDemuZl3jwpFBZzvJnkmDa8CTU2j5nBIpNzTRThSqVQVxEVybTQVDvNsarTOeCIpG6+ktobzwfQ3mv02DTufOWdSbV2IbiSEDUikNGHOypxKR38ExK8iYT6Ysi9hQMJAk0DB01xE3UBRzyEp+wRTMRSuiSMOGxTPfq7sDpn93CjqET8y50ZuSnMeFyM4z5yLqcKGyJwrc6rUCjGO3N684vb2FarKw/0DaUrQDK2oJZHmCW3NKr1cQNUUU7Up8zRx2B9IKfWgQrpInXFISrZ0y6KUSxfQq8XSoEsptxO3Bh5LCg8wFKVL16vWnuY8pmvA0jB2P+fuZWUVXNoqOaV+j6c1GK5dNbjpStNdK7Fyzmfie5YSOqraLkGWlckLwxDw3rEoFOdUyMmsFoJAQAnacIsw3dKb6TGgetxRXlu2LLe/BV08ejw/0yfK+YvlGl/rkeXk/19MOx3+9dHfc+f+JLmVx13xKbpyvm53qF4CJRYO2JJCXNa8HAUul3G8/mdt2a9bkbeXtM+MoPzyL/8y/+Af/AN+z+/5PWfL//yf//P8i3/xL/hn/+yf8eGHH/Kn//Sf5g//4T/Mf/gP/wGwvPlP//RP841vfIP/+B//I7/+67/OH/tjf4wYI3/zb/7N9z6Pq+nGF0Ron6fqxl5cv2WOpCl3sZwVPnxJIPFs1Q/nj8blvnUJVp/Yl/RgYnnmj7DmE+dy9rmevV8ug56sd+3KXGOsaxeAAsEplK5Uqc3KLL1rKFZF8dHNwFwboYuBOT8aDyVYCqCUyjBsLNVQbHZyd7fjk0/ekHLBx8BBZ968vWPOmeAjUNluBu7u75mmPV/68lf49M0d03RgM0a8h5vf9jVCCOx2e3LKfP2rX+VwmJgOBwSlFhPy0lY5HIzTonrUMPEucHt7w75lI4tGh3OR1oR5TuzEZuvOD8ZF0KWCxgaqkhVZHWDB+aNjqbZFxbWRkoloNbXBPXQeSc5KMS4pIo0QAsMwWIeEUNU0M0pHnsR5kMhhmvCxMAzOgpZSUAohGurhfKB0V+hhGFFxpFbxBURK1+cI1FLABZxfSmkhL8qlLhLHVzRtXXQsMhcF1wjiezn3gIvR7APiSPUDBXPEbmKBETjmYsTYQxYOScnV47xQ1JHnTJoseMwNC7KaI00JURMAbGrpjPkwm+eOM85NLg3XK682mwFxSk4b0jxzf38PKENHR2rN1FLYDBskeHIx08w4eExtppGmGZqy3W6xWXSDzhHR1izNsjwrTakUfD26Akl/lqRrlATn17TL8oy1npLRuvQDyzNraEjOCTqiAia9P0+TafPUE+0d743bu3riHG0LGtonxQ7HEgSdKKX2wb11j6UQPNuNKc6a+aH9Hq12gjDYg0+h1WhaLif6OsdhepkOnnRip0058Q866X9O+qrTZZdLriEoT7X34SLCKZJyfZvFwfp03dNzu1z0FKHV7rTn8wpPa6cc9U4eIyRc4dsYKrLeYLZTzlc++c1O9vWS9pkClIeHB/7IH/kj/MN/+A/563/9r6/L3759yz/6R/+If/JP/gm///f/fgD+8T/+x/zO3/k7+U//6T/xkz/5k/zrf/2v+e///b/zb/7Nv+HrX/86v/f3/l7+2l/7a/z8z/88f/kv/2WGYfgsp/Qb3p67xJ/1s897bLmywvNE3Hfv8/Lzp9KZL/9eHcQWMAEp6wxKr3IQGlkbNQaCA9WMbgI3VUhZ2WxGZHHwxdx/aytQlTzPPNzv2GxHqsL9w46H3Z4QRzzC3f09d/cPIEKL5pHivWc/zQhCSonvfOc7eO9QveFLH3+A95F5nvn0008RdaQPM3naW7DhhOhNNvxu9wCt8er2hloyOU2UnAnekcURfegqqUKMIz5GappJOYFOpnTaS5mjx7gQQThMlVJ0hfpFO0mxmgdP66iJt4IVE99ydp1VnM2gZYFaBYi4cGNBj5qCqoq3VEazqiHxkUYm5YZ4I/iKE1JtqDOCqYjDhWgDuDcjP0uTKakoks0LpmGBgg+OXGsPoIVcFPEbAoG8+sYYilF6asf5CGFA/YDEAfwAwRyu5yZGsXaOnJXd1NjNyn5WDglKFTQbqTjPiZaVxeMliCdlS1HcbEeGzQ2Hww5dUhqpUjbKuNmCGglaVXoqMHBzc8Nm3NBqZbd/oOkGaNSarRooDghGFrb4IRC9DX6mV1PNzsAJztz7zNF6KemFM67Hgi7Lokh7xPN7gNN/W22IGnF6FdbqA4Rzlvb03tOqJ+WZ+bA3aX5l9UhaLAyW8mns9rJj116944TgTIlX6QFRL4d+VKJ7+uSLYvpyVqIdo5I0oNUQz6aFJnaPaZ+Eq5hHj9BOAqU+wbtIZyww7uL/ZMc8HTRlXfNiysbzw/kX296VEn9X9cxzlTaqS3ByDAbeVT787m++XJ/jJPU36pp9phTPz/7sz/LTP/3T/ME/+AfPlv/Kr/wKOeez5T/+4z/Ob//tv51f+qVfAuCXfumX+N2/+3fz9a9/fV3np37qp7i7u+O//bf/9llO5z3aJYz2zJqfm+X8GKY7zX88BbV9Ue0U8bx+Pjzx+trf5bpPrX+y/GSRXNt83Y2AmiPvIu+uPXBpfQbb1AIYCRum4thn4f5QwA3U5pjngvORN2/vmKYEGDqhvX8eNyPzPLPf73m4f1hTNqVabv7+/oGHhz3/63//Gt/97ieUbOkhBXLKfO+7n/Lm03sOU+LN2zseHnaklDjsD8Q4UpsRARHpPIxs6Y9curR8QsRmquI8w7gx/yCn1DZTa6aJEkfz5Fl0KlBlHD1xcCu8rtgAbxkakwavnS+gerzHnK8Mg7LZwjBAiBA3ET/eEMfXxPEW50fEDViKxRAsS+OEnoYSC4IQJEQqjqJQWTyHbsAt2wrqIi6MNAKpWtmz4nF+xMUN4kZc2CBhRPyGcfuKYfuacfO6v35F2L7CDVskbHBhAAmoGPekudCdcD1ZHYXAXD271Lg7ZHZz5TBXptSYcmM3Fe52ibe7wi5BahF1I1Xt/JDA9ua1kaxTV7QVbyWzYo7MrSr7/YHdwdIzwXk2mw03r27ZbDe01jgcDoC5UINVAqWcaDUjomi1Ml4nYurDIaxoScnlLLWSi/Gelr/ls9aRjdarqxYzv1yK8T2WIMFuEAPptcORJ8TYReJ+iAPee+Z55rDfr9wTS7kaYXe53wwPllVSX+BoP7CkbZuitXJ0ST7qvHhvwnet9Yqhmmmt+xH1wLtpQ1tl0X8Rb5wpuvy9OuH0P4OG3Pq3Ll+TL8t6S79zFJeTkxSQvV/QkItOaulArvZ919pJIPDM39onXyy/NiacLVtfn6/3dABy/pmeHrJfJe2nfTzEFzEmvc/U9/n23gjKP/2n/5T/8l/+C7/8y7/86LNvfetbDINpSpy2r3/963zrW99a1zkNTpbPl8+utXmej4Q74O7u7n1P+/9A05Pf5jTyXP79XPSfZ5ssD1Wv+DAk8jLFci0ifqodP3+6pO50diLrkueaomsent6Z9L7EUhLImjLKzfHpXilTYRwGAge+8mGkTjOD80y5sZ9mNkPEiXDYHUDVXG9Rdrt7ci6UXCkpQ8C0UHLmYf9AjJHvf3pH8H6dTb759A0lFz755I2VLfvAm7t7NpuBw37PzXaz8iwOU2KMA3neUetM9JbiwAd8jLRilUc1Z5oa6dK8UGbi4KhFKQ182JBnSxW1WqnNOmPvOum1y84b4GQpHXGuV090xdHu7TJGJXrjoNSOUBQcc4PtuLFy5pTw4ihqgxzeW1ARBxOz60GX8UjM28g5B2HEhQGnyVJD3kMIXf68mJIsVhkhYUBcs3LnWoxH4j3ihQj4VruGiYBbyrodLgjqPbiBZoXIpKImYa+RomYc+fCQeNhXHiZln5V9aqRsZ6sNajHH4FE8EYejEQNsbm6QMLDbvcW88jxNPcErcTCJ/VIqaUoE75jmiZsx0rAB2Q8DURs5JbQJN9sNYRis2qnL/LdSKK2iXqA23CiEbsbnxaEO5pL6IN9VfEW6VkxPi9WEoFa1RsSFQOxE7DUdJEKTE70OXci3rT+v2r+f6ak4lOitGu1wmMyTqRaKKhVDS8Sbb5YTQAsigXaS4jYuTKPoYjToTvCJnoYKAScVrY4sYmmrkqhF7ZpLWPuAXru14DCcqlUdkx+Xfenl8uNrO4t2ZfnzAcb5Xp9at130g48DmSfT+Kpr739WbfNcWkkff4+zap0zNGQJ1E6CmDXNYv8/Vju9m5vzsnYNU9eT14sa9fsd7b0ClP/1v/4Xf/bP/ll+8Rd/kc1m814H+jztb/2tv8Vf+St/5dHyd1WhPM3jeNl6z63zVD7x+nlcLHjmN3on9+Ud652t88Trz3tDXuf9PHUOL0sxdZKEvcQqKEozSezdVAwJCZ55KoypcDs4DtkzF+X1zcju4Z7aImHYcJgSXoxsF7zjcDhwOBxIyWabKc8mdoXjkzdv2O0e+OCDj/je9z/hSx9/iWnOfPLmE16/uuWTN/dMh4kQI+N2S6kPvG63fPrJG27+3/+HhvC977/he9/7lFc3W1qpjIMnvr7BuQhq5b8pF9Q5Sq44dahEkEgIlVZnYoikua2+N60782pTzDDPKp6WstFa6b42i0aG63oo2mexEIMwxkAIjioD6qxyZs6VcTMQxxtSNm8VJ4bKlGYpCfNVEcwXqFdsOBMIq+Kp2GApwQbKMAzmM6OmC1LBTAqdQ73HqXS/oIIGq+LxwWNquBWqnUelD3zR1ESbKEUC1QVac8ydNDw3SK1yd3/g7n7PNGcOc2GfKodk5NYFOdDWiF35t/Z5g/hAk4H7fWL/MHG7ieQucOcXF+V+L1Zgyo0xZYKXVcPl9vaWYdh0n6Hag1i7brXUfvdbSsyJW8mlvps2qmv92XGgldpRE3HmsQPHShzU+Hu6SNrTK2qc7wJpx+BOlX4P1BUZQZWmGa2NWkxBttXSy5khJUNjtGkfWk5TA6DaaFS0686oWrpmNS4ERIz31E6uI2DE145emD9LT2mp76iJ6/egO0/JnEDAS6Hxsb85wYb1OBCezwn1ogc6GTCvDJRX+7WzF++HBrzP2lfB5Suk10UX56l9HEmtl6jKadBy+u9TR393Oxdfe3SmLKjVMSDieB+8sL1XgPIrv/IrfOc73+H3/b7fty6rtfLv//2/5+/9vb/Hv/pX/4qUEm/evDlDUb797W/zjW98A4BvfOMb/Of//J/P9rtU+SzrXLa/+Bf/Ij/3cz+3vr+7u+PHfuzHzoGA5wLqJ9u1jd/vJrxWVvbCLfsT8dTN8fmgsR/GtlxL41hYasGJmsR4hikXSjL4+fbVK+6nwugGNozM9cDNh1+ikkjTAzdjwIkJZj3c77q0uphRnWuMYyQn5Tvf/jYxDOz9gfmQmG8S//vXvsWbt5/wjW98nf1uTwiRL3/lK9w/TLRWuLvbMUSb7+12M//zf/46D/d3hG8Yb6apN9LuGKlaaQhzquzmnWliBN/JnxukNQ77e4II280WtFCp1FrWO8A4KJjEvqumJqqelBqa6ipXbzomdrlihHEc2IwbavOkFska0BAQH3F+wzAEU6FN2ZymxQJD3/kl4uh5f+kBimmEiPOGioRgxnfO4ccRH6KpxTorWaVXiYiY2qqqdI5MwI+m5qsorRTI1YKxVpEY0OCo2qhUBI+rjlYa+6zsJmUqhd3c+OTNjrf3O3Ix/sj9PrGbK7lryBiQ6WjiUKMqEb2nMjAV4X63x6nnVdjQqKav4z1TysaxEI+6yJwbu0NiM0ZyTxGaSeDIMIykeWKaE7n/7kt2JVOIwSMSz5AVEddtDaz6ZXHwtcCm4YMpqi4BgA9LysOQtZwSKkKIi0dRRy3opdenKYO2VPiY1H3JyUixJdu17zN66ZwWEb8GC8ufic5WlGZl4E3MGdl5HCfaK60jHt0YcuG0lOU40h2g3WJoqDhRvMgafC8piNPhcwHYzsKNk0niDzJd/lmafYfPfk5XNU5OgpPzz8+Dk8t9/Ga4MkvgzIqMvay9V4DyB/7AH+C//tf/erbsT/yJP8GP//iP8/M///P82I/9GDFG/u2//bf8zM/8DAD/43/8D371V3+Vb37zmwB885vf5G/8jb/Bd77zHb72ta8B8Iu/+It88MEH/MRP/MTV447jyDiOT56XLIk0OAuD38Wa7mvxGF/4YoODq0HMUht+eixZbmrhEnl47ru85Hu+7Fo83d5fbfY4+7J1X3qcY8jYmpW+pmKCUsF7RB3qhdQcJSvhZssuNULc0lxhPkw48aRSiM6qbNJhb51vq6TpgFBoNyPzdGD/8MDt7Wse7u8R10h5Yv70QEqZ/+//+w61Vr72ta/x8LDnvgc6tzdbvvG1L/H2fsfd/YFf+7Xv8PrVLePmBjSDCLkU3O0GasOHCM7x5u6B7caz3QxIE8SNxEEYy8Tu7lOD8Z1nuHnN/f0dtRS22xtCqNw/TJRa8VHWFJ5zHh+Mt1N7RZTz9ndzO/LRh68Zxw3TDDo7nBup3hNiAD+Cj8QNVA42gDhnM1wC43jTK5IUagfefcSPGyO9xmjfC7tb3TgiPpgiibcByXmH65ox4j1RHKJmBhfGTS/HblSXUao5E2tFhgDODBS1FaQKUkx9dj/DfmrsM3x6P60BSmkgzrOfModUVqND5+yYXXCe0BTnByqBw9yoWdkOkeY8KsIwOmJwzPOB6u1ZbAgpZ2RyfNzMHVhwlJw51MZmHAzxK5V5Nm7TOI5mMVCVVuoaNMS48DfsfreqmkJJmZwz05RorRGjpXKWZ0nV44fBgoyeCio5r6kB7/06EC0omqhpjSyy86Crz08tmTTPtFJprdCaOS77/uytfBORfh9YjtFIsMcUwzIjtkH0JL0h0kmxR8XbxUk5ek+MFlB6lOAxvR8cpR9Te6exoiaia8nx6THW9NUVhLuHay/reB71Qx1JutbvcS340Bf3cafHON3ptRjryD95/E2UrrS8ZPWuHYPT6p+LdNAVvsv7vH6yPeIByMk/P8AUz+vXr/ldv+t3nS27vb3ly1/+8rr8T/7JP8nP/dzP8aUvfYkPPviAP/Nn/gzf/OY3+cmf/EkA/tAf+kP8xE/8BH/0j/5R/s7f+Tt861vf4i/9pb/Ez/7szz4bhFxrJwjg2bJH8crpfXCRGluJVKef/6DbU7mXs3blh1xP/vpGnx3N+aKbXnn98ghlCbR1mVXWZTamBC8ogd2+mtCTFx52M6+3nkAlyJZcJ+b5wKvRkQ4Td2/fMo4j92+/zzztCOEVNWd2+wdKyez3e+NVdJ7ENBdEHLuHiWEc2R1mUqm9rBR8iHz/zR1FFYfrwl83KI5pmrnd2oCVc6blg1UqOUeujbKbEGnUBFoK8fWG29dfoZUKLTGnieYdcQiknEk540PER8ecGqlqn6nWLojVya0N1EEYHJtRGAeHk0rNM15GYvBdkMwjfksjkltAwhY/OKqY4JxxDwMMtzbR0YZWwQWH+IF4s8U5Kxv1Iaw/rx+3JgTnhNAUUsZ7TCBOTWPBBWOAqIIbNrgYEG04GaAmuue16ZJ4R1FPzgeaE6Q5ptR4OCi7qXB/qLx5u+fufjJkS4zXU6r5GZVeobWkKoyA3aheGNQ4TWbe6InjpqdUsqWutVLqgSEGUk5Mh4ncDDnYT1aiO8QBUHJKjMNoaRqzfTR9D3HEEInjgPaqnVIy4ziiquRsXlHajCg7Hw7rOgaNOwZv17eU0l2TGy5EYMCFgKgFP8WV4yOmrGmtVdhvfbT0mPJhEWMrq2y99LSNspgA+o7CWLom9uF+KUFegpCjMnRbT6KuCI6louIwmv5JVULwBG/PGsXUbaP3OAWHnQNL8NFTK2KlRI+6RRsL12+4fluRZ0btF7a1oupyOdeWP4eGX9/3+XsedZGXpcOcpt1YEJPrKMny+buO++LzfeL1k936SZByGh+tfcwL2xeuJPt3/+7fxTnHz/zMzzDPMz/1Uz/F3//7f3/93HvPP//n/5w/9af+FN/85je5vb3lj//xP85f/at/9Ys+ldM05PX3jwGMq+P/Z/XT+eztWnCyLJfTBU+ey2+OQOXzNTOnw9ICvZNS55gTFCpDcKQ3E9E1GsLgHFIEnZSND0SnvH37QC0NGeGweyB4SNOB3b1n/7CjpkorE6qwvY083L2hVo+4SClKzo0Q7vDB8+mbT/nwo4/YzzPiHLvdd7nZbhniwDBumObENM1ELwQ3cHf3gLSMoyJivkCHw8x2HNDmSHNmH4Sb0SPhFqeB1hr7w33X3vDknJjz4qzrmCbTNak9MClV14denJgGhMCcJrTOjHFk3Mae+1d83ODHW5qYXLyLQhxu0ZS75kcfCOLWSKo0XBG0OfwwErY3XRCvz7WbDUoaNl3LRMBDCGbzp9o1NRbTPx9xAuojBekBTCNPQmqV6COqjlyFnBvzLGzsy7FPjvt94u0u83Y/83Z34H4/cZiToTtqaERtnKUajuihElUIqRJ8w4sYqTXEnmHxZnCXCuN2y/ZmQ36bUCpDGBjiQK5WfTOOA9E7C1zEECXrk715E6VMLY3bbVgRhpTSkT/iHDklaqlrNY/xT6RbCLjuaVNX/57WFYSNOFt76XBX46ObQaqsQciCtGhbeE3a0y11vS61Gze2tYLGrX92zLYiIIuCcr+YZ5M55ywlZ+qzrR+jpx9EiONofZLLIJnaHKkkVAutOUvjScNptVLpboi5IG7Lca9xT+Rk1vni8VcWzagvKgFyXlkjV87lffrkx6jFyfdmCU6eWpeLKOCLS/KcOQkAjwdQHsPm6/v3P5XPHaD8u3/3787ebzYbfuEXfoFf+IVfeHKb3/E7fgf/8l/+y8976CfbNVTlqfe/aYfxJyPTK4s+A4H2N2s7fa6W+LsDytb5NWXORu4r1aOa+fDVhiyOadqjqfEqvCYpfHL3KbUqt68+4DDdE2LAJxuA0nQwfYwCtZkjsHNiQmiipDlRslJLYxceKLVwmCduXt0yp9mcV0ul1MZXvvwRKo3vff/7SMvcbAbmOTMdHghOiQ5uxi3iArUIrZjcfCUz5cY8JSiJMYC4SBxG5mlvPi3ekedGbbV7AFnVkJUAN3LpkLwHLzaoZ2euuyoKfaByzjFuRtpwQ3OjgfkSGIdeTTQ0JDfAmQtvGJHRIzTi4KCKlf3GLYjgxogTpWQjVlYZEBdIpfbSUqG2gmoliHniqDiqX3SOBC8OL54qjaSZqQlFPHROzXxQchKmAnNtpKnyZjfz5uHA24eZh33ikLJVP4ma4V0xsq25+Vr5uvmRGCelKvhQGQdlEz1NHFOqeAcuKPe7A9TCh69vQc224NXtK0yhN9CaFbWacqoJjYH50ZRa8U5W0mjOZoYYekWTdw6tjXmaCCGsgUari8S8YQVLgNJaYzoc8MWz2YyE2Pko3pCEJSWmwmpGCG5NJ4naJKx2LZXWGrlkU43NmZRm8px6tU83oZSlutetlWLLoGfIXV9Wy4JV4L2ZLqIepdGykmvtHBsBdXhvJcfDYIkkFU+pwj4lpJi1RHC6oigNXdET5LE4JbyQe/Io3fAb05ZU9Xts8Y4Uz4KiHIOTp3VNvqjKnIv2PID/9GZnKUF5r/Hph9yL5/O3q2kR1eON/dwN/uzNfxFZXq62RptPbHqJ+cllCu8yPLf/yXL+T56HHpfq4+VXt3tq8dn211e/3P+TV+ta9dNJ4L0covVBYXESdk6ZSqPuG2nKxO4p40pg5AbnC+NNYJr3eB/IqfTBxSpHULUaxgqHXSaODudg/1DIBW5eOe7vd2A1DBz2B7bbLTU3M5G7e+Djj15zd3fP977zbb7ypQ9pKjzsDhx2e9DK7WbgdvvKOhXnURdwQWgtIWFDTglphSgBLY3QZd1Nm8OuQWtQ50JTM45L1QZbxcqPu6wXvufzQXv6p7ENJiZ3aIZAFe2eNjIQwtbSN1HwoQMipdF8QEKwNI0PSFEanuoGKhD9hhAd6ERJhaIRRyCrQzGvnKbFnIvFvHgQz1xNW8UD4+DwTUjFc8iBuUCkIxClcZgd8wyewk0Wyly42yfu97MhJ1MiZUXMYAht2gEdZ9VBaqjBQkBtzbpus1ZwVDFZ/znDGB2HXGjzgTE6HnYH6mAl25txICWrxKo18+pmQy2NqZmOTq3ar10FMc6cVQIZt0edEKJnGE3ALedEa2qaKH4gTbOZPqqpq5bqQcySep4nmLuuiQ/m2uyt+skIsJaCayxokXFMWAipzuGdidq12qilkFNinhPzlMhpBjX0RbShBFSMoF3V9RRO55NIXfWKGmYK6Lr3j3pzlBYt3Z7AtgVZAySnlmZzDobgudkMTAlSg5pM7t43Xfi+NswKrAvOUjlrx2HvT8pm1zTPwkF5MpC5PsBfb5dJjmtJlePLq6mhy4Di2aMt32k52kmKZwncTva5fONLbsxLEKLTbU4NT/XRd/5sE9/Pg1L9yAconxlNeCo4OU2jLOtcbtfXew8Q5Pzzk4H/AhtZDsKj21tPvqseIdFrAYX083t0vBec5Om5vXT7z7T/K0210Zaqgqo0UZwK+6niBGoNBCfMJTG6V2zEs3GwzwecH2jFIGPRgtNK8MpmhFIMfUhZyU3BVWqCWmDeZ1wAvPkG5U1CS2NuFUbzU9ntTPp+Oky8fv2a+4eZ73/vu9Q8sRkCr1+9JrdGE0Wd52GufBBGSoV5ToiDNE9EP1DzTHYFgqelbERHb/n4XGBKzcTSuneNc9YJa58tB283TSnQBLxv5HnPsDWzQgSaj2S5obqIsCFIxEWhOqVUIUulOYeTSHTmxmsk3ICGSCmVmj23YQDvKDKTCqCeVsG1JdCwwS14T6mFIIGpwWEqeOBVV704ZOVuglocGxFKhWlSDtlzv3e4BnULLZkQ25yUlExhtzYTrFtSH3Ccoa0C6dpTDViptplJKnOpNIHBR0oJzGlGsz0mpR5oLfDBNtr5e6HmRpoLm7GRAJqhRakTgnPO1o37QPCW0pvTgRgDYYggttz70Mt8zXqgDpGgptrbtCDeLAha7cJmrbLbGY+nlkodCz5GwtD9iVRxhP5dDW3TngIyVWQxxKNWpBn6kaeZeVr0pZQYLZCJzYKYJg2RgDhPaw5dS4INjDJ/HrHr3wSvIKaLj3OBYTBV5FqxCrFa7b6iGmm4VLwoN0OvZlIlFZgVirO0jiWuGqruQr5ezjsK7e97QLUQZ8/6lSfnkk8ELlf5JycDudq5XWvL5E8vFsrx0zXQ6Am/86PoaWggj5brCZpyWup7nHq+f0BwGvo9CnJO9vwb3X6kApQvOtVxbet3pY+uLb8WqrzE1O9d+3hJ+8xB0js/v1zjPMJ+59lemQS95Pj2gLZ1/YaSS8Wx6IFAUYeGiGrBycj9YU+6n5lzZbsdCSImLx6U6GxATF1KwsojpYuXNfJUcV5Qbw9qySYl/3B3v5aM/tq3Erfbkc04stsnfvXwLb77nW/xta98zDg6mhrcXyvMc0YkkLKZJKZcaSVBU97e3TG4hpAZhmBE0dIIDoZNZJBI1pnDrpL64KxA6BUhTe3cS7YUTxgACintcWHE+VeUlEkoeYggG7QNDBpNcl4bGchaITfUB6t6qUJuDh8GApG5FfZ7Q5TGEEgo+1zQKpRiM/WYCiJWTTIODm2wuQlMWXlzv2czWBlzbY37febtvqANkkIpZmx4mBv3h4Zr1aph5pn73cz+MJOypdc639OAsJOZX3dO6J8dFTjFWUDTaqN0YbrS4JAKLRWCyEp+FmfVRDFGSiuoJhAhxAHvFKpZEtTWOExTdzRWgvcQDcEIIayGeiVb+bUTQ1tStcqZ4EDGAWTsAYmV5Ko4c/vOxmeZDgdqM72SYRwJteK8kZVDjDhxnfhazZCzCbUKWjFDyC7mV9eUkmnQpDRTqmccopUAL9fuiVFW3GJ2ekz5LPL4rWueOOdMkdcpVTOmmxJRHKUKTSoihviNg2Orjq02ptYoKFXUdIC69NyxKz9BSuQ40FuQQp+onSApF/3M+0zmH8/tTgfq52ZS15fpBVLd1i7z2HeeE2Mv9rUSh9/1RT5bkHK8fufn8rnHUZHz3+E9tv0hD1BOkIRHo9z/iXjvN1M7eUgftZfkZF6y/8t13w0DXv30ChD1kiPbC+Ni1D4AGcLie0nkgNMNcw6UbN40r263vBpN2A01XkBrjv0CazcoCZqDAqQCreqqql1zJefEfv8AWIWFE/Bf+zKC49O39xz2O7yz6p5clGnOpGnik0/vqFXZ+kipig8jkPn0zR2vt5HbcaRMxltJqRBioLVMrsqUMrhGbY5SK7PFNISgxOiJQRCbwhJDIAbwTlEquWRcntiMpiBaKhyKp/qIU8dGPIHAYS5dth5qhk2FGJwZ4QEtKaMqh0lJc+NQCq9v7No+HGxASUWYpkKMELyjlcJmFLwIh2ZVHG8eMrc3Rkw9zJnvv504zBVBiHPrKR5IWdgnh1NPq4m8Lxx2k9kU5EJtVkGCCA0jjJ4HJ4YkrpwMEYbg2W42oGq2COOGqQDakCa44K0CpevvtKYMMeKKIRzeBcbNhk2AaVdXjQ8RwXtZxxvTMzFO3jRNJsImQquFVo0E6p3Yvz6sQYZqYJ5nC369EDSuhFXnLTivJVG88VpwDl88pWaEXgK9uoGCNrHgqPOlarOAJOds+3RGds45G4IyDF3XxJCXs0mSdFVZ50ycTjtRVo4mgqcoljgbUC3dZftwMRAkEJxHUqZqIdWKJzOIIW9eE1RzL9fuK/V/iEpytV3nl5wHFk/1c0dc7/FKZxU6jwFy9DGk/huHbegTr6+0RxIZV9Z4afvRCVAuB8xr0/JHy9//h73krDwdZR6PccbulmvLrp/H6bHeK5qVk2tydf33jAge7f/0xeXj+Nmv7YvaklaTo7fpYoy2eHQoVt2SxEELRNlCuCUMD4xjxvvMdnRsh4E0myAXG/BOmJMSxAiIpXMyGpimRYM8F3b397RWebi/p6kRWXe7Ga3C3f0OBSPKZisL3h0Kh/0Dd/vKq9sbplwZo2e8ueXuzXeZ5oKncjPeMGwG6jxRmrnrOvEgjVQaKVeqCqU5mjSTavXOcvytsahG1KBIsZSSVaoqkhIhHVCXyHnmIc1MecAFx1iFEIX9AVKp6/f1U2WMwnYbURUOc2YzN6apkJJyPzfmarL69/sGHvazst9bgBKDg1rZJAtyOEyk2rh7KBRspvz2LvP9tzOpmC2BEXKVUpqZAmaPJ1ClUrNjzt0IUBchMWAl3tmgiboVPjFkxQjWQYQQIsMwMk0zc6qIq8RUIUJ0HhcGfFDmvOP+Yc/wamAMAVUzOsylMc+JKN74JyUzTRM+eG62WwTTQ9GOGozjCGpkYi8mtlaLefNoN1estTGweDXZ96qt0EqhloKImfkF71Hp5oEyW//QbQ6sJNa+t1W/KeBoTa28txRybdRazCuoC9GJGDJWWurl6qbAbG7Buu7v+GQvLsX9MTS4pFdqLWiVrI8qCN4HnPO9rNuMM4cQCUOh6YE5HxASXhu+OURHkEgloj4i5xkQHqV4Tha9OIY5SaOsfetpF8MlaVVXxOYIhFzCAksf/VQwJR0Zu4KOHI/CaXLpeO3do/O1fZwSYp/+9i/SOHnn1ZP3uMBnW71g39fbD3WAIpwMg6dACtAtPq9s04e1pVzkOZDhC2mXO782qH/+9sVW7lydIlwekCOR94v/Ps8e+gokuswytX+uQFFQPI2R6Le4OOJco9aJ29c3tDwhLZNpxOAIHqQpRaDEdYxjTgCOpo2SGof9RJmLlfuqMm4G5jnRSmO32zNstwTvedjPaGvMsymPtvCa6kf2844YKq82nrvdjBs2HPKB+/2B2xHEC4KlDubZHJB9iNSU2adCKlB7hQpYysD3jrM2KN01uADeBF1pmvF+j9smnNrM9TAXavL4XHHRc5iN2yFgSrKATIVNLoAw58KmKDmb3HycG1OBMXp2+woum1nfpIRgpbyiyiFXtptAyYUpZeasJBK7pDw8ZB4mQ5q8r/iKiYeVRSHX0TAkqWmgukgTMCIsILoGJwg9rXT0SVFsMK09H5ZS4f5+z2GemEtFciXGhnee4AK4iErlMBXqNPPR1mb7wVkwkWtlmicbSFu/Vt6cmnMuVklVJpwIOS+BQO1lusFKemuF1nAurmmReZ5pqjjvqLWwPINLCa2liSxYWFCbUJbKrkqrHZWwqIGmrRvz2Xc3TZ1CyplSM6W2TjI34rRRVC3dqdTuYCyGGvYUmXlnmbbMmiYSQ8cUugjcEqQcjT8VwTlv4nNgyrmAV0eMnnFwBK84yQQCvs04GREZaFItzePPevtjX3BZyvp4hWegl9MgRE/6E72KkhwFzpY+6OzDI2p1DQI5yTgdaYrnyaI1TFrvXT2Zgvee7REp9uVtXff0kpxdHjkGbk9cs+eEQp9a93JS/1tVPPA8ePCS9X6rvbutU4n/U0HKUwG9PWRNHKoRkQ0h3KJtQ2mJIW4ZopKLebDUkBEn7LTSAlRvcu87MRhe1QZQQYxk24SSbJkCLTTSlHh7eAviaAj7IOR54nA78tGHnto8w3jLLJ552jGnHe2jG1KLRB+YDjO7uRnJtVVL7wAS/Jqs9jFAruRmQlhL5yJYEDJEMJTfqjdQ7QaAgveGHMTBkRTuGzyUxq4204kplZQhJRvQ/NBlx2plyBknVn48V5Py302Kz5W5KkMIzHNDSZQG81xxUrvxouN+SsS98SJKNnO5UDKiMykrqUqvHjLuiyy9eANVh6MS1SMy4Pxo6xpesKi/23yjgWoncvZdLFo6qsYvOqRMfntvqaBmjsu5NEr0VByp2eB7yNVcqqsgzsp8b1JjTg/Mh5mNRLQkYgi8un1FKhas1K5p4r2RRKXUPlhXamn46AEzZjS3ayspLq1R5xnnTG/E+4DDnKpLWVJJxqFZ0JHUEjrNqBrCEoeBGCPDMFiQ0pqha7V1RKpxmBOHydyXW0dgxInxrHDGUdGCOLWUlSjNd2RlEW7rz1jpgeCavvFh7UuXINH2ByKmjmvHrZRqfkaKeS8NQ2DIlSE3hpYZKOSWUWmo6+hoR5+fm49/camgCwRFrn12gaBcIDFnW+hy1hfo+4KonwYmy7PNch+v2M7J/5eA7YVf9uSk9OQ0zr5jR7zeY68/8PajG6D8VvuNaWdBym9EO7MMu/6MqgmW1a4+6fwWbbeobEESwQe0HRhCJAYx51apeBWoSm5wexMIPnGYzOjtYWe8iICVM9esLFxdUTHNi2nGOU/wgd3DAzc3I2PbkJpjLh7Z3pCmhNaBXBqvakTDKx4O9+TicKkRo+CaQDHX5lZz191o5FIR7/CxrRoT0lEDeqojDuZz0rQiDtOeiIEQTN225RnnJkKd0RSobWCqNrDWquQMqaiVAWFdp+/pidaUudigNlernMlN8VLJuaIURDwpK8atgKEJKRWapmM6TgQpBS0FVUejy+GLGDdHxAwVe6Thuq5JdBEXRrxaQs/ReRxoj+EW1HRBR83nRnoE07Snh+hCZgiu1K7Z4Snq2edCaJXarAR5P8/s58g4Ris53yVyOlAjVuLrGg7HELwFNKXrmYjrvkVmgpenAylXNuOAeiXnwv5gAoHjZkOMpg9jCIsFXkuKBDoCRIXWCahC5+rUlU8Sh8Ek9lvDx2gly8V+m5SyEYtLJWVDdRDfB0LFBWETQ0+bOZwqboWhuhpvrSt6ZQOZ9EDP0lSipVeVSReasyG2NbVzF3uWlpRbzoU5l67TI8Tg2A5CUsitkkUR1wmzXNdvPbbjJOkH4s2zTgjOfYEvP794+aLdLqm0M4RELeg+BienG3UM+Qvtcheez4JIP73zy2v7g9Td+pELUF7C2zj63ZyCZ5ftiXzbSwbkF/3QJxjbMzmmy/28L7P6yWvwOW+y6/tdsUuuf6en2uP6/WerltbLf3oNTz+W43pqBMoiA+pvQA7knInA7bjFtwPqrbY0vvJ4CncPCq7gXjt8R1FEhN3eSpvzXGygWGZrKqSUjUzbGvM8oU3YbgZqhbtdZrh9zdQCNMW5LSKBNzslJ89ul6F6as2MwXETAzllYnS4MDAfEjlXcobm7EqZbL3ivIAzQqIpzFdwShjEBNgEVBcxMW9VE66xlcZYHDUr+5RIPRXSVCytUiqI4J0hAdDQpsy5Ia6hzls6DBDNNsN2DpHWnZbBqc2yS7EBaU0BCEhVaNIHntYHL7Vtpf+CrZskqhDEo24AP0C1Gb7rqQgAaSY0Zh23qdMuT/mSzm3L814atSvcWmDWuhS+BUiqQiNQq3K3m/jo9cb4IarEINQCh2nm1SZSqzJNE9L3VXJZ0xtgBGvvlDiYnH7KVqETQqSg5FrwpeJ8sGqhIuSceqrNSMAmbEYXdLPqqBhdD4alByGFUmdDg0ojjiMN4/KU2phL4ZDMOqF25EikoRRKTUgCxhHnPYMPaJNOULXHq6qixa63ExDxeNfLu7HftdSCV296LdJ5YQ5cdzg2ZCl0lCjgQoU5rb8BzarPBg8DlZGMaqapB3UnIo42mLZLxOIafPJcoKK95+loyNoHPbXNSfCA6tmAbuehl6ty8iGnAcg6uernoaf75wIlOQ1+zk5H3/n67AROj70eVDgl71wL7h7t7TRd8+TxTleXZ98/137kApSXt3ZyofVKOPrEEHk6Bp+tfbLKlfjl+UDlhzzHdBYs9NfvFfBc3uDPuV3KceBhfe4f7Um0K2liaErzgRY2HGYTnHrlIkEaNxuruJjnQgiKvxE0K3NtxOBpozkqO29OuKnavwvRrQFpmo86UZ5OYoQ5zcTccCEQ4ytSGxEcMYCK8pAe8LJhag5HhJLIBfzNQGuNlAqbccu4HWkyU9RSLc6bPHkIHheESmHOyhj74BEMpShN0dJoruKZqUPCt4iTCV8naK/IpTAXJeNRCVj1xjEPXauJfK3XXgXXFHFWTlpZ4PwuTc7RtbTWJQ1g/ju1rUBP7y+Xi9aMmKuGRvXsDiKC0/6cirdAjA3iM65jKFahY9U7aLXgtBM2pS0H7O6+cjTaW3xiqq89ddWQXDGukUeaed7MRY04zcQ0H6hlZthEWpopzY5Z5wPDOFBbI6Vk6IFWvA+oCnM1Dx7nYw++Gl4c4zCAmo2hd0bSVm8BUFVz7RYn0JVXVZTarAxZcYTocRLYjB4hkWuxCq25MpcDtVZyzaTSAzCEOWfmZOiYCbJV0NLTZPHs+WutGZelWXrOO49UC5IXtVnXS3ptUBVL59TKwmwV70zVuFjgSjWUywfHMARKGcnJnklaMen/1hCtSMvgErgILYLT9YFffLpOh/PTPuI6O+PKxGkJUvp+FgkDd7KC9v6E/kywrnu6n+fxnWspnqMQ23HZch05CxTcyQTu8WRu+WrXeCWX077T/x8xKTmbVF89/+OG64K1V3jH5PfztP+LA5TfPO3xDyrvN77/VnvUdIX6u5aCDEjYkvaemxhsdlkLBCG4QPMeKGwGz8cfwKf3pet8WGcVo6dW0+VIDVo2J1FzST4+wEsFRW2WVz7Mme3Wg9vQdEA1oGLCZ7VVJE3kGgiuIWFjHBIi4rtWRlbGccD5igsNxOGiIL6SW4UKwTIgVCukWfVQlomRNtPByDkTR0u9uFqp+UBJQm0b1EcQv3b36z15MSld+B2GWCzLtE/IjvC39hh1VTyFRzHscZbYzo4hvYMWuvS6yOqu69wAfkQw0THEdD6MC+Ggy6UfZ9fLfbCsc/SpsbSFp9WeJunGhUGE4AOBDbmZtP4coJXEbv8A25Eo5nckVFI6UJq3CqEx0pqZCKrCMG5Q6IRZRwhCcFYS7rAyd+cXU75mA2NHm8Q7ajOtmKZWEiwu0koiZUNTjK8SCWFEne/6J1bxlUvikCb2U6I2NasCpOsF9ZScqzhRfDAEx3t/PjVTTNK/L/NL6qnVzv+RNYWmImtg0hbjwP67OgfS+vOoUMuC6jlCDMQY8KEixVJJS1CkWtBWaK5gw9XFbPypDuBq04t/n/r8+H4NXJYb6CIgOq0Aen6Av2TNydnJr6md5ZIdOxRWL54ng4i+IzlBeC4vzOeIGd4XD/8i228FKM+2536WdzwaC4iw3CxP7ErObshloV68vxglfiOil3fdkT/wU3jmBN6VQjq98Goz9eYilQ1NR4pO5FapvWzTOUccomk75MLrG08pwv2+MXrBqbKJgFh5r04LOnDsrmR50XXnvZg4m/rK1gVqczQ3UmhkNSfaooqre0s9tUpzI01MaXUYRpBKbg0ypCbs50JuSipC0UWW3jo1CTb79tEw+FwqVv9g5sQLUTPXgq8ZpzOBjKP1QcazeN++Czq2AOb4G5gWibLkb84mm7YGawe7qKmdzQSP81VLa9gS6WRf18c9k2MfcG60L06DbnKnCE6Mf6NNETVnYTsRWVGhBcJevkurxskApcXAEEN36vWEOJJa4e0hUQfHGAK1CXd3D3xwM+KipcBCsBLanLMN8OI7hcfhg/Ercs7sD5XgBO8geoi+oyhYEKIp4fqzbd/bJO1rL2euYmiKcxELNAzCqrUcuSNi1WZNa0f8lP2cSKkgPjEMI955csnUmggRhtgl8cWvASYcr1OrloZr2tAghvQ4u+HNSNAuc8OsAUT86j4urVnFmWq3YBBo2rVZcq9Msua97ds7RcR8hlYfCjlXbT2GnWfhwsnfu9oxAD+Jls8+17N9nSIn+mjNdVfPHu9x1KAcHZof6dIup9UnPte/1hX4+GkI5UXtOiXi6fbo04vh6tE+/29J8ejVm/EIjb2Ti3LBVzn/vD3e8wuIQyIn84/TIOVkb2f70Ss3tl78hpfn9vjXf7zsdK9yus3j73A53h87qdN1Hi+Vx6td3d/7NlnJjk98fvVhP55Tr63BTu8o5DWrR2XDPr9l4+A2eqoowXnKlNkMNtB6KdxuhZwhOCEHhaDghEMyMbKyVPAYk+1IalSTem/NDAdDtEjCunhhboK40TgjEUKbce1AnTOp7ig4DjnxME28utnQmuN+v8d7TyWYum1Tcul8CQR1AtlSBKUJmhuiRj11GAIRBoc4ZzNthW0QbkIjSF2vWWv12Xt8LeftTU/v62U7WVCL681m2ctWXYBMj/ec9D8nZiPgxZlqq7PtRAYIxaTbdfm3n4aYJgvSycNL6kF1/Xdx5qW/r7WS5myBk5iKrYmMQXOBSmTKheBgHCOb7S27txOpVIYQ8T4gOGqbLThSq9ARCYgP62O3Ig0ihtjUBqEb7TVDxmorZ3OTfmtZKKdWzWP7cutTgLhu4mcBwTrIiaM0jERbKnNRqIXaLIhoffCXBq3Z/lBMsRdTSw7Br7+vNiit0lQYokPc0t/11FS/FZyz/VuqzM6pdENFc9Q+olnmHWTigiJGoHWi5mosVgnmqFgs5FZk4OXD5TG4OLtX9eRzPU3vXKy/IhK63pvnwcmxouldYdF5AugkAdW/1BKIrKHX6X3w5F4vgxM52+e1s3j6/LgaWDx76JN1zw+/oEOnk5GjBYU+FrZ5sv1QByhCu3JFT2Z1p4PutUHzc6EA7/olXxbMrGu/JypytvaVu+oadxW6yuTlHi4Dohcc910k1s8F8rxr+2c+t35F1wdExAacJkIhgtvwsFcGBx+oZ8qZzdbUOksp3cCuMni4GWGeFe+gSkOjJzojPXpnpmnCQhqUPqCoTfYq4BWthZonE+ZyFfGR0oXCcSMuviLojEgj7SYOqVClITge5koIgakKLVeGcUspE4eUUOfIuVIm5WYjIIpLdmAvMAbAO3O4dW4tJwUheo84GMhsAvgCqUfKytP34nVidX+w9OSeOJvaHrexTuw8vFz65OW962qlzgnOQejpnX7q1OYQN+Cl0jRT8mwz/N5DOnGosxSO5cvaMTjoiMDyvlYTt6tYYBZLIGfjYwxjNGNHHSjF+CYqjnG7peQbxFnaRXFG+CwQgmOIYpEFDufsvjJBNCyN4ZVWhJaM0KrTTG26IhuW3rG0ByK0kixdJV0xudW1MklEiNF0WKDbNDSbWC3E31ybKRob59m8foq5dg/RgZjkf+2uykUKrikhRnyI+GDXFFFaaZa6Qro6rFVJGWK4DEDGCbJAxeMaiBjhV6uVWoszbx/vPaXYZ85JR3BMA8aCU9PRoep67y73zqOJEkuwY+GCPFJta8d7WNuV5Sf3t14JRvT8/j+ReTvu6R1DwvJYnZH4r04Hl3VkfTYe7fry651MUk+JritieHICx/TtyWQDvQgsTh/i897+JPu7/qsnS75IgP+HO0DRZ+iUl4OYnt4gn2uCfzz41eWc3XjPtceozQ+6PY08/Kg06dde0RNjQ+NkIBEXbphq5O1+z6tBCK3xanD4MFJSZoyem42lB8bBSJ+lKqlZyeNmAD+Z/01tlpNf1GvtWPbPMkMsNZPTRCszMoALwdxnW0UkoOEW53vJKG95mO54vQmoFg6pMI6e8eYDc5+tlUOB3Owbbm6GziUAHx0+1D6I24AUuhx6qY2mpp1SayWGitfENgzd+8cCfXGOk1KJx9dW5CQWvhwiHg8ZxxnhU03X30w6suJE8D1AsQIlXZGHJY/v/GABS0vAAZHcEYGnm7CUZPd3IkiXc1+QlFwqOVUbfLsPT9MKMlKppGbeOtub1wQp0DKpNsYYGDY3BO+Jzs590V+ppXayakOqs0Hbe9R7WKpbSrXych+6boh2uXmO7swOEAukSsvUkg3xqY1xHPoETNCOWORipehNzeKhqTkRO7XB2wMtivF1qlV/DT4jYsZO3kWG4HvwY95U0pSSCtoSMUT7nr3MWzradToIOjVisnPOPIn670szcTdHtDSeeFQdc0nooXRkRWEJ5AUskFBWz52L2/AYWxwxDdEFGTkGLtdwiQUhOd2pPvr8ZMhWfdz/6+N54lVRs8uA5CRYuNQ7eTTSnzxm7zt+nRFvr5JaT8uMz9Gey3aaQbeXej2I+gLaD3WA8lvtt9q1ZpMAe7DML9c6ehEPYUNm4G564PUBbp2wO2ReDREkstvNfDAEhiDMrqFeiT5ANtzjZuPYzCalXyrdT8UEtRZeYOtPa1NFq8HoslSiSEBcF0NSA1rmpqjcIOEVqR7IzbF7ONBq4RURP3jUR5xEXGoojVwrrXfC2hpOIXobMGymrMzJeCg6gEjCuQnvJqL3II4go0HogMPbYIZc65NOru0JbPuIF6XPBzicjC89KDEEavFuMZKvc0roqIlxUkxbAxFk8RwSxfkRHwa0JJOGV0ttnSOnC7nW9cHZuBqqagdT7cGkoQjznHGda1KaEGQgjK9AJg5TxkXHJm652Qa8ZuZpT1EYhy3bzYjTZqhOM+PApoWGGfilpHiJjDHg4ghdPt/7gOu/yXIeTU3KfuqIhaEOriNDXXOlK8IiztAZQJtSS0/3qD0B0u0SWlMrXvSsiq6K3YOLHP4QDc2IMRCC60O6KciGEHHBOD65VIJ3BL8g1UfbgaWpdpSpj4lDDDSvtGIiea5L5AcfcT4yVSEcGsxQSwDMrVnAFGU12NRjnWk+xY5YzvoCLTlB9AxkPX52VJDVk3v8FFVpZ+tdO+K72hrmLKP5WsXD1fTVMVw5opTHT86PuMyJTzP5Z1n9Z07wEnE52+9TOZ+zfb4fcvJbZcYvbNZRnvwwV3gcZ5PAk+hyJUZd47Wchbonoea6tTz6Nc/q6a9F3l8Q2nIaLX/+/Zy3ax5F1z77rMf5LPtf+qSFAyJuoLkNoo7DlHgrlVEa28GDeKqajHwMwhirVYhIIzZBa+N243g1Q+mwecF+4mUCv3RfTQ3JaADeIS4Cvs+SHCIRRamdbOrDLRJuOUyfAoWSBSTw5mGmNEepZh5Yq7CfGzk3tmNPh3RNllxsNAjO0ji0ig8Qgp1jqQWoBA/qlFAb3inOBQRv1UjdnO1qkHKF+3S87NfRuYu55+mmGN9HcIgFKU7woscUT99W5BjEOOc6kqKIG/FxS8kTlMkIs7AOJqfBiXhFqp4tM7j/WJK68CVKNTKxw+O84MYtqo7DdI80IfrIsHnFq41nv3vDdDjgfGTc3OBF2e0Kmu34YYi4CDJnahclQ1xHWIyz0lLG+wBqRpC19BJjMen5Ukv3sqnMXTq/dZQkJaNCq3iCQK1dYr71MvvV8E/X8njff5LlPj32SRYweO86YdV1mXuMv+Qc49D1WNR8m8SZTL13J4P7Ej80XVMnTTGnZBHUdbXgHiyGAEOD25uRVzM85MZDCShWtaT4NUVhVS5HlOR4Xz4OVjq2wxHeOKInK+a5BjC2zlprc5rOWVM+j27si2M93fT01Zl/Tj+bs/5LOJ0KLOs8ceh13SVIsXNeXp+mbp5uT4nbPSttfzKmvTNAe+baPdf+rwxQhOMsbm1XAgB53K8aDMa7r7F7dHtd3mCfP9j4fO0yVr/2eP8QNjm/vuskYumQ3QbiLW4OzHniU63cDo6PKgw+os6xL8r/z96/xNqybPld8G9ERGbOOdfaj3POvbduFdiFLGH8EMiSG3ZJdscCW8iig1sWAhq0kKFhywghIeGHZEt0aJmeBS0LQRdo2KaJbSHR8kOysPn8XYqqe2/VeezHWnNmZkSMrzEiMiNzzrX23udWGU7VF+esPefMR2RkxIgR/xjPuw4Ovak0HsdsC5UqpwHu+8wlwINtTCGZUaGjifWRsHTxIlU4vdio2MIgJcKmQ53H+Z7sDyR3QKeRIBaFVLyg0mFxrDrmnFB/gDxxmRN9J3ReSlAu6L3Qdd7ClKdE1zucL4xXzQ4gq0laqlqkmqZSxPVPDv2qI1nKlvHS6P4bptjseE2KYSzVicM7cIv6xQJ1CVViUr6L2jWFkTt1KA4XBkSPyPSATB7PaoxMVeMs0hlncVGgASiZxcNHS8LFbIn85nGE4HF9QOlxQ0eMmUlnHhM8zomXL0+8CK9xxR5oTgnpbDxzkd0F5wniCCJcyEtgtpwycY6gcbFhAreMRa7rpgQ0wxRzeSdHyjNztGzOClymRGKkK0i0AgPBLV5BmosU0YIr44r2JCMGPIYjw3DEDI2L3YmKpQ8oGyqLmBsgQMzKFCMqmb4Dj7l3GxhJNgoSbD4WA96UTfpRQUvKBTSpGeY65zh0jtMA/Zh5jGb3IwSQUADKVq5Qtx631r+F52pVD2lzgUlXqvrHyH7lgwuUWSQr7bS4MUHqedkfdptrlrm2SJuWScIGlOwwhS7nKzi4bsPOUmRp/yLcbJ52E4y0PPOW5KQCko3tCs+yjLUl7RW/TYxkf7PLP38bkX9eZb/bvbX7/a0IYEwfH4Z75reBt2NCTo53jzPf+Jkfvuq4O92BXkxdIMLh1DHrRLyYZ0kQR98lQqDEE6GocIyfGxBad22aMzlFSwCXE5lMzUyqFBM98STfEbojhCNpfsvpcOLhfMFLILuBS5xJcSTGyPk8WsI5tbD8L0+eTCaLqZdiTBYILBTXIgUpOYViyoxTRIA5eeYciCURImUxfz7k1NN9u5BJXRdgSyZi6hmh2Jogi6Sk5tQRLTFAxNrs9vWXAIuCN7sHPxD6EzqPRZWiSDFDztm8drKaKmwvyvbeFwNbbUCKMs0zYfJo9ngxSUHX9fjhiMuBqcRGeXF34OVp4HT/kvF8NhdjJ3Rdh+pAmmdLIOhs0c9qEWhzNgAwjRNoogvCRRyZs0lSEJO+ZQOyMSWmOZpKxDu8D0sSQkRMojJaxztxpuJRBSdkdUvk2KTFqsNZv9d3Dp3ncDjShR7Ii91JTMnAnkhRF1nwQuc9PmXGychrTgkfrU7ADHlVcIHFpkUxg92lqLOw/o1laQ2N33s4dcJFzYA5G/IxdeXT1NeoY8pHIzXZ26hcL8AFwMh6zZXHzl5q0q4NV8CkOVg3TRsV6i0pSfvjejPwrKji6nWayVil5i3AeWaLbXfuz185Qe9uaMHW9en21P9fxbOUn32RfRKkPDG+8mFp2new3AIw39Ui+O7Eo/aMl0wfPJceLrPl7nl1dyJHSPMDmhTXC90hMM4zOSveZYbO0XmL/lmFCov+XdRCuKt58+Sa9TVn28mVBdp2gyZ+TTi8G8j9C3x/j4tv6Q+B9xO8H2d8ULILTJcLl3FmmjPVgU0Vpt4YSt8Zk5hjRlMiHMVirVAAQQj4LpAUSDDNwmUy41kJhSmJKzFEvnX33vpaioVu96W/nJiXkatSktp/UCQfza526ePKaq3zJRzohjskTSQHMc4YEI2YfMpAj+S8AJRNuHFojmlZcCNTtNgiXVbGORJCKAH9HKLCJV14nDLHg3AYjuYWjXnymIrEEf1sUYVzJsVpsVGKKZGyZSTuvAPXkUscGlkAlMdyCZmxa4wJkYTP3rx8QsecMvM8Y1YpNu59MNfmVHU3UmxXCnm6Yv+UsxbJFCUjcsB5V2xNeijeRzhbIvKSkdkX25NQwvubuidmxZOKPY/Zf2hMuOBYjKt1jUVTVWz1r9ogBYE+wKmHUS2YYpJMKnISo4aneVE1hF1sWPXWwroFLZszN8DJTqPxwdJ64KyPa6U/7SbgGqi0T9qClnLupl3IHiBswcl6+24XUc88A770Cf6/eb3fpPXhOw9QnpZy7GNp7Dv523XoMpnWA2uNVY9gsu7nannWhuIpXeCnSHQ+ZKPxVKyYp67/WctvXv0fU89WvChhQMPAJcLDOHM5WHTY8zQzRzgdTmQH82VmnBTfd3S9BQXzvWdIZsfhS0C22OyULFQ8tluq4R/ElwWneiUo1RUVqpC6s4Bt/T3p0fP+8cIYlYdLIqX33B17VDxTtAUh+I6cEz6Y+sI78zJywdM7T5pnpqj4DmIGktKlbGJ5LgQ5MM+2g/VeSM6yMKPuesvzbYou/yxjLVR3VC2uw9UQtgKS1abFVDvSfC8ghTr/an8qLhwJhxGDmEV6UK5VFHLjaowZxErDqFdXzIwrO/sY48LyHWaP0QUPncf7HtXMZc7MCY6D53g6mEE0Ge87cvW0QUu4+Axe6IeBnCBOE9McEek4+A7f9cX7J5OTSTFCCKgmzHvH2qWaTBpWFvmcDQiAQJ4R9VQVWcrZJBnOlwixuUg5lJQU7yH0gS70ZXcthGDuxfXNwVSUMeYS38SK947B9ZaRWEtU5Vx5bFFTae17ty6ODd8JocO5ErQtJTpnKsreK4OHQ8g8arZcPlrljRWp3gbR61LcSE8qSS7gY7NkUyMh3yTjnVTm5rn6brs2rdigeqC1IGIPKPbzrar72F7fAI7Ns278WiSYWttXj+4261c2Ktv+kKu23igfZBebCj+6fOcBys9WnhYYym8Ek/5tUH5zVGBrnbfrXyfMxz9/BREqHvE9qRjfJVUexsRlFqYEBwn0wwkhMj1eSFHpfE9yF5zLHDqLBBqqV6VQlkIz4queCyqC4nHOQqapmr9MbX9xdDVmjkWa9f0dGg48ns+cRwusdZ4mss54LH5ETJmHhxlRpX8dsIzN5oo6ThHXOUJwdJ3DB4dTi7o6xUR8fOTFnefQdZYjqD/gpSt8L5Ru2kse2/K0aNhKq5RZd6+myil5jWqunCoNkepObHctn9iuWhq876gqg3KN64ABCSdcN+OSxfEwex8LZ2+Gnxa3Y83DY9KcBQSJ2X3kolqZ52i2HNHC0YfOPGecGwje413PeUpMCRBP6By4SIyZvh9wouQUmaaReZ7IOUEBZigMQ09KkZQyc7QkeqIG2GJWyJEQZJE4rCHQrX01U3FMCXLGiQdJTONICB2qWvLwjDhxDF3PGMf13TGp2jAc6LvewuiLxctBXOkbM1ZRLVIfVULMiJSAcS7gnUWNXdxY66KqjaSjiBjNaWodgxA8XReYS3ZlJ7MZbZc8PC5D0B7JM5LDog5VcQZYqW7v2/w06/JbwYWylYzsfy8NLhjgSl9yE7RvN3myWfdXQFLqpL2/lZrcAiwtfNpJWJ7gd+07XxnF1rYviGWtfT2ftzds9vbXc/5JIc6T5dsJB34bA5QPMdr/Z8HJz7rwP3X/Uy5lzz/v27fl27zHPmLpt6n7Oa8eFY/rD+RiVpmBt4+Rt6fAq+jpJ/AdOE9hoLHYZoCQGDrHYYAusKh5lj1b2emr2MLWdR1df8CFjuwCjlAMKN1ml694Mh10J7Q7cn7z61ymRExwd+qIacT5gHM9KWWCV0QtU/AcE15LxE2vBGcL4RTNMrL3JulJU6LvzNYlqSfLwCyBpBU01c9dWPGNlO1DO6nKlE1KVIHIklNHrD5TO9FIUGikHOuCsKpMZVmU6vWIM0lCyc3j84zGydRqKOIyTrVEeNXFrbWNa1EBQP2ds5bAahbkLTMRilojFtuMLhzpu45Z4TwlU884MwAGU934EOj6Hu+8BXJTRxpnNCezQXGBw2FgniamaQKF5D2dDyg1qeEM4kialxw7IEY6BUDUmCE5WGZrpUgInJDmXFIelL5SMVWjN5ufruvou56uABRFzIspJrObEVPDaVam2VRmFjnXnmlB3DzOFVouhrQpmxRIc0acee4Iaz4ly/ps7+OcEkoeoM5NZS4lco6QFK+Bjp5eOmJ2FF88+5QqgaxSEYUCSg1wrKq7W1Lr1i6lQoIn3WpLH673Nqi5YQCrMet+qqwbkyupyG6ztQE37bUf4qXV1kTaQ62E/1pyvl63k6psHn2LH98AcVe3Vb5xdeb2c26U38YA5f/JIs8urjfv+Ggw8eE61vvr72/Xvg9d820ARNuuD13/7fpByOLx/REfegukFoU5KufoefOQkTThTpFOZjovDP2R83kyzxindAiH3hF8Lsx32bvYE7wsEt+MFqNBi5OSRMmiCzCqbVIcSTzZDeBPZILZHDgleEfWmXlKqHY8Pmacg5cvenwP0zxx6jtSnpHekbJ59CCKSmGZwSKzehdIUXg8K2cdOGvPLCbSd8tOVG7ykI/qb1kUJ+UeWLxwql1JAShS1D3XAGX13AHrR8N9xZenxEExO0Jz2RYxjx7ig9l7UMBIdo36aGv7UEXX7XNzLNFlxbLqOmCaJnwBeVktRkjfDWSUxzFxnrOBGBwh9OQ8G5hQR0zKPCfQxOUykuJMjErXHSzbcfCgJSdQTGgAH7zRhELWZPFhvCOnVKLfCsF3MDjGaWaeZ6r3kpb4+JIFnEkbYkrEvOgbDeM4LMx+CEuCQM1qWZRdxHtP5zzVyylXDxxYABRxxgdT1dj4BetLtYjGKVmUWp8ywVtQtqomMq+izFyMf0WkJCucy/mI5EzIF3rtmHGc1ZOlggC/LnxFZKNqkWdvApS9pGS90b59aL/6FLk3IEX1FjBpVTuyzIxWOrJetwIuducX64EPtOWWKn3ZWBSavyn8kBoxqpb9VXuQ8iGAsgVG23f5bePFs8BWK+0ivrvy05ay1WJbdsQGT6PQjyu/GZKBp+KatKDmqeMf9w7fHmw8365vV2dZ/qoo89q8/pnHOhSP7+7w/Yk0PnKZFGbHlDrePk4EVQ4h4ntjrH3XkyJcRo/mCN5ii5iKJ2+eZwzKJABZMzHGsiM3WwBXYq3c4hIqDstkPBC6gSFlplTtJwJv3r1nmh6ZkjI/2qJxf+cJkjn2yuCFh3MmdhDuPIdTh8QJwVQAnXcMw8DQDYzhwBQ7Jnpy8bTY9OONObX24RNdywpOzFZkTQMgrN+39cqmlqryWQBO/RNYPBuk7tgrKHQgPeJPuHBCwozTDC5tHFBF3AagLKxj2ZwaoEu5urzYrneOEXexx2Zg6D2HwYxmzzHzMML9KVjslKz0oSPOU4lH4phL4LQ5ZuZpZpojMQvD4JZF2+GIcyLmhMObpCFbW/qhJ/hgxq5qsVTUC6HrGQ4HSyZI9X6qag8t7xvIcypRZW2AclbUCb7Qtvces7qWBWCCFkAOkmsmZWfZl4sdS84J0YTQ4YtnkHOegLeEhLNl3NZi9LFmpHb4IEuU3Vzdor3HB78AFofi0oTTRySLGZJnsRQEQpGYgFnAZNZIsVtJihZr8mVLsFHztCinpf8KIyoF7qUrsty1fBeaY7CqOxuAUum+eL2s0+z2pqAtz9spPgFA6rEGOe1kJ+v9z9b/dFuW+zf3frtN9L58pwHKqvHcdvyT6o2rA891YiXYLQN9si1X0on9Obf5fRvFfixweFrCsUfRz1333O8PlQ+3z77dovOPUeEsPb9/TplobT6Lm215RsUjCBKO9MM948Ov8eZhgilynjLHAOd54jIlBm8L2mWMFoirH5iiBVdzXghdXS8FpATGohgHbnhlSW+fE/iyby/XrtGtBVFBJeC7I6E/kqYLOkUez2b82R8OXKYzQx9I88z5nIlT5sUdPJ4TOmQ6ga4T5py5TBMdFq2UrHS95+505LPPXvI2nWAMJsrXbLtvAPxmaK5EwXtGbldt/q1GrQJ4qUatVVJSfleDb7G+qwzS7qtqHFmuX4ZUbAfdHrPWdODA9S8JWe2tc1rexRVbihqN1WxO7K2dA/WCUymGwrpIDcAkIKoGSB2Z8yXQnQPIESTwMJrLtlfPNE9434E4i3XjAmOEcZzQ7IlZzOWXBC6a6q0YwWoGvCcBmhLzHM2VGId3JcifuBIkzVRY4jskeFKOBM14Fxaw5cSit57nmTRPxGyxSpyAekdwgc73K88oaqBc4oa4QhVSPNC8OHyNVSNisXmKKgfnsaiG4J3HdZ2p1JIrHkXtOBYpWKGnmGLJ9yN0IdB3nqHvmeaMT+BixOlE0NEMvqVImAq1Oc0oaRm31q5kBaOZGi7/lqdOCzdWl9k1MohRb16O28P3fLyNftXUIRTpiiw12hrQLOqytoLN11qjuzq/BSKV97MtUjU/ejVtRao06mn1DHwYrDx377e5vy3faYBi5TcGqX3Kcz5lcd8vxj87OPn48rHg5NOvkd3nrXubReUjyqp/XZ9xE4ffADf6wfY2tyOIC0g3MJxe8uX/PfN+estdUB7GmbsBLjEzRouJcep6pouS08yhH5hzZJxmYlKLFyF5FeuWuV71uQLmEZJGUhqBiZQDScMizq3v6SrDkYDv7xmOL5ke3+FdLAtSJEXhfM503br2qkBMcL5kuiCc7ixq6vmSkQT3vUVnRaDrHV0fQJR5uhCni4nSxRYnwe8iWm77dt0ZXdN/WRNXYNEYt9bzK+hYj7nmN0s/Vj+UenwHUprnwipIEzyuOzIIJO+YVIkpIbaSltgfqxRlv6kwXJmXGDMqJnXQaFKLXKKrjuPIw0PAiyMA78+ON48zd70HPOc54VSYszAlZUqZ8zgTnBK6AZxJQ1K2KLEimeA8gkdKGPkaM0MVxnHG+1yyA+cCdstvTTZuasa2wQV8ARw1D07Xdbh5Is/2XoSajNHAyDQXlZcziY1lLA4WR4Zkz9CEZRQ2wCRSJSlmU+K9J6W89KvzgSH0+JQX+xW3m+M5mxrIJDo2AE6gD56+c/QdzOrppMNHD2lC8JDjQifkAjyFBYxcq3jKMxuJyZU9CtU1+dbmqcolhGVztFwmN67c8sdqQLz6ft5ScTieZ5br/TeX+4V/7N+tRF3W21J2WcCX7uZ5c83PCDhuqZ4+tnynAUplduXXb+aTnm3D07es+kf7uRPpPVvffhFYK/7QWvxhALWv40N9d+v6LXP/lPa0z6vsY78Teb7uD/XB0+cXLwPx+OFIIjDP5tb4/jzz6tQTndkaiHi87xgGz/l8sXgTvmcqLrxJXRlTXRiEFrGzasl3ookcIzlb6vjFkM0VewHWxR0glwSC4fgS539ii0hyXCbl4XFkzuCivVzXBboA4hJZIKkjJphFCYBmzzRZaNtjpyAWZOvx/MjjY6QLX9DjTHIgjlw8ZNaM17tebcXQVzu10ufagBB23ykB2ag2KPW8rteSF8lKQ2W0DNTWh/XYKkVxqBxwnS8SibLgpkSOkzHjAlBWV2Mr5uVT6EOVJZSrFClBWQWjF6ZxBs6mskM4dMLX72fS0TF4S3rnyMTsuMRMVEG6HnNBVsQlivONSTUEQgg4Z0HaYsx45+n7A3RqsVQWsGedn3Mm1naJN4BbJHV9N4BQ7F0SqrnYmyhCWp7nvWeaY5EUSQEnidx5Dn1H7BPWIl1doHMiZ1/cxB3i1r4WR5H4YBF0vcd7R1DzoPKFQGroeNPUFSCRTEolYmHzg5gbtHmheUgCmlCNqCRUhJqxvlXhtEBkI03RrfTELtvKO3RZ5XWl94XcV2rUhd6rMnMzEZpjLdhZJShtPJQV4yyDe7vo+rE8/9Zleg00nuaj2hjHLpOIfc0NxPtAfWsb9uXbbsC/0wBlLbcR3lMdoeuFHyEpuIWo+Yj613u3UpOnF88WnHwb6cfTQOQWQPgQiNmc/LTjdYexed7+fDl2Q1/5YWJ+3sjq2T6igAixUOm+PzI9Oo53RzKOyxTxx4B3yvFwh/cB73pSdsxxwnceZCTlmSkmshTX4s2Oqu7SADVbAjNe9ODM8yHXd67iZKlC5EDyB0J/jxuOyPjANM08jDMPo8Xm8F1Ydsx1FxuCM/fjcyZ3cOodMSsBRT2o2O5+jpkwCKfTie7S4bLg8iKvKH33dNTIhY5lT0VShnX1sllBSqONr9c00hVXpSSAyGIay2LGKmufrg+U7bOxd1Q8IgHpBK9KVwBKRJFo4dVbOmkZuvOWsVekLCIq4Ax8mmssjFPJ2RPVAKyI2aScLcZI7iHPGdGIZmEmMGVwLtB1DqcJ1RGRNeWBqpJxeLGAaqhlBpZqi6G28FtbTfpR36PahoAjp4iqGVA774ma0SkyTROazVtG8DifkeItNE6TSWvUc5knSyToTGIXY1w8cLxzVl+uiRsqmBBrJwY0VSHljKRYvHscwVkkWicmEfIiIM5C82egxolRW8a9s2zhrvRhzl2JZCtXgIQi9VqWbt2rcFYblAqGVkJetovXUglpv0h5dMurbgVXk93NDf9fDGgryL6xtlyB/vb70+sQ+8uA6mS0YIXNGlRhzmoU754VcFzz6Oesip8EOLo58FHlOw9QburdfgPqLN+4DRa2kpu9dKHVL34YLd66/0Ptqm2rBHkLgLAQpawXsrn6CRR+E2DcvPCZ482JVk1wdeUTE+/2e+3vewKMfqDLzf7B47sB1w8olszvMk08nCP5VW9i9iKK9z4gPhNnkzIkdcwllX3KFkfFsIiNnfOy5B4JYoG9unAEGXDSk5SV4d7oqygd3t/RH18yn9+il5HHy8ysIAqXNBsDx6LRZhTxFsPEBU8iMmfLIDicAscA4oWYqgutp+sHZPKLbnxr1/F0B26SFTfzTsqOsgUiNe7J8qaNVGSVnqzX23WlDVVftNB5rVkbUi6eB7pWYInzHBYbRQlDJMcZNDGTkRIRtY3HUdvvRBZX5KQ1Vogje9AcLUEfZeeOeeX0feDhHAjB4+QA6oiTRYDtgifS8f5xIrhM39/hRfDB3GuVTBZhmhKZkaFTgvcEH5hzJl4uxcMGy2acC4CTEpHY2fXivcVvQUtG5pHQdYs0q0Z79V3xtsHUOI+jpUxwEsjqiTnTOUdKyjzPTHMw6UgJGkZNQthSrGiRipWFztWMzLEY1fp1pSyxbkRWbx7pAkJinJRZTXVl7vmB0GVkMrDntMMVOwzDHXXZK5IRSgLCAjxMetIYxS4gpeEZLSHLag+2qpsb/q9Gm8u0vdrkyY7HrmuAxUcqm4D23gZ371tkp9sWrvWvAH5b2neroOIThBWbt9lKl25UIh+vtllntG6OfEz5TgOU1eDoWUD3LcutXfo1Sr6lTnkWW964/rnft49fA6etOPLq5s1PXQhXWt7elO27/yy2LLevu+7bj37GDoUvk2f/Ik81TRXBMvuJ7+mHO3Adj+eZ87szLsG7zzvuO+HhktEcefUiMAyex8uMC4Hj8Y709lK8HxI5lnfKZWKXFdh5CyN+PN0Tup5pEx1yuyupGzp1SsQxdPcMp8+ZH78ivX3LlJRYEhE+TpkXR8/dsSf4RN8pfX9gupw5XzJ9sIic4r0ZjgZjJilZgj4nJmXImNGmxcl4Wmq3GY+2bwuDlcJMF1sUaY81MKw+o1XpLBh3NZBdR7a4Ejf91AKVzUCXxbiCcpUOvOK6E364kNNITjPBp0UNYfYceQEldYGti2wN5ubAJGVYwDLnbKxHRsbO816UOM8mqUkDOSbSPHMcBNWOSG95lLLZfdRouopJVlRmxhipciznHDkZgAohGAgR1wCoOn8V82DxJb+O5V7K2RIR5hIrxbtATJmsBsJUYJ6VeTpjuXcCqjXarENzZpxmLsHUXi6Yp5eIJyfISZEgDagr4+sEsPD3KWZUZ+go9WqRvrBITZ0Tcq71qAHAZB5JOCF0gT5kumQB4ryDIEISiruxNvW1OZWqSm4rQWkXieuNzV5KcGvj5HaH9tfb52qDUo1mK7iQ6/s3Vez59MeXfUuftxup77amf2iFlLfuv1XXkxqE38DF+LsNUFzN8/BpSPHZOnc7+ttql6fByXL2prTj48HJhyUOz1/7/LPW+78t+Pg0neKH29eWFmvcEr3KDuBUcea2hqeaYu+uCr4/cv/yM775cc95vHBwwiXBT96MHJzns3OkCz2XGDkOJ4bhwJQi9/f3DF+/hcnE5jCjScnJopFq8VhwzuG7gA8WEE4KcKkRR6xfVmPZarBmMVEODP29qaBiJipkjNFHMuOceXQTQ1A0KQ9ciFOkC6Y+GUV58JHBOfrChGaXGS+Rzs+8y2feP4zMCuoCVY2imzbV/t72v2452RXYWN+zABVhY6QnNbBJfW9pKt88r7Rpue+a5lZtfz2XS8RRh5MAvsd3B5I341QpAKSVolTgZHTXRJ0tLrDOeZw39UVMkTkmVDJK5PGspu6begumxgu8KPMUeXee6Z1AOOKK5C1ly15c6TRpyYWkyhRnc8V2AioLgML7QtOuhK1XgmayziaFydHUOl1A1ILKIbLYloBjjjM5mS1K33nQ4sFkxkolN48sAikLpjab7YpXXAjWt9kCuXWd2YhYDqVmDEo6B83Z3quZmLnJJg0VM+hiLJtyKv1rmaVzUVd1InSS8ZIIZKJY+oAFzmqhSc0NSKnqnjWTsXC9668qvmtNc/OjMiSRzSXbYGpbnppZDb0X0CLb9aRWfSU9qVdsDm29eKqCZvcyDePcKaBu8ttVxSlX7/800LhV13Oeoy2g+VTw8t0GKGUnWInzZ6+vZYDQouIrVYQ0ezhZia25mSvme/M58uz5bQPrP5Vj31bR1LZu32GLoD/FUOm6Tft+uj6+p/Z9H+3x/O7iKqC8NW/XczfbcKvC7SmRsu/0Pce7lzjfQTxzuDsgQfj1Nw+cAnzxEn7hB3eWSt4Ld3d3xLdvUFWOxxPy8LgwiZQgJWtZ1sK0S7yIeZ6I04jrI6KWhl7A7FIaJKZlZ40KESX4IxIG5jkVt2STzqjCOZqHyhDAY8HEXhwCd4ce78zrQwSmOTF5IQSP+KqiMc8LcYpXW2TUSTExvDGGO17d9r5Fgq3gpLQfls+aL8cEH6vge7mnBfWsa8H1MMomZcgSAqc5v9gYCEC2kOh+QPwR/IFMQLUadxZphbT2NwacVpACmq1XTMoguGxePrMIKo7zZTYVSkoEl7n0jqEbSEl4mEY0ZwKOF8MBdWIJ8bxAnulQZFKmmKxNIkwKpGwQNmckG+CykPIF14nDuY4QWDIAOzHbFHLGezF345iYU0KheBMlQrAQgdkrvS9SFxTVWBZ0B3RYSHnr7Zo3KRfJzpwyvWZ8yShNGbMa5bUCVdWa5NDerUa9XfhPWbBM4mEGuCmbmioniyFkuRbNxsXlGdRjbkiFv9XFT23eaU1lgIG+KkWhHFvpuGl4+7nw1/W30Vob06Tev+NiSx2OLWeu77veL7WODQ9/jicb0FzLfq7qdkLsRSJXtdtYG7+xeze17cDlzyQVWTY/pRWfsPZ8twGKszwkK+O+0YmtWG97924BX7/vF+MPgZMNk5T9fbs2y/4Za91bO4rbg6jLdSsXX4HzHlBtnnzVhqfa1l5/+9JnAM4T12/6fo+wr2tfn//spG2rfBocbUudjALqCWEoInNlGAaUzJsH+PoEP/n6zO/+BTgeOnxwIJ6h63l7eaDvDjg3cj6fiRFikrILbUZBK2Ch2EWUyXm1i2olCnY8SUC7I4fTa0QDQYRZteQ9sTIqTLMBFCdw8GY4298HuoMgPpLIpCyMc+SYI+KMUXcOTgF6nelIRLWooyy0taP53V5vtTnJy+vU6LA0dysW3v6KkOT2j7KJX3qmQJnlqg1I2fShfXetga+KReT1J/AnEoGYSlAwBFdUGpWP4ATJZWcuHucsXptSg4uBqidOZrCaskUg1jzjVJlcZAyZ7nRPFzpm3/EwT0xZGIKz2CxuAKdonszFu7Tb4nsoXoVEMaxO2aIDi0lNoLjqqoFbh0dJBrhzQnO0UPqidN7Re8cYE4pYMszZorqmHLk7mJGq4CykPhkvQJ6B0h/iccG8cbRIWbIqc1ZSEUyUHmRJ3SB5IXFVis1TLupQKQkPbaCrWs3GveRocrZoilrslZSUnCNePMFlXEwmKcFck7UGmMst/1dzkdrZnKhU2jDqbBfMlh9rBastbTZStnUB2PKcNXRAmUdXJL9Tbe/WlecBwba+K0PU0p7NNKuGwTfXRlnGiCpBWW/c1LMHK7fa91zbBVORWs26tWP7QPlOAxTvzc3NULgsusfWcHbvwLqWJ4DBcq695pqIdHNfu5g/Veft59w0Er117ObztiDi455Zn7v93T7aVGZPU9GHAI7uJtP10z8c6vh5Cc+2vc+dv3XOdliFi7oOF3pIHh86Ht69I87CFB0//vULv/LTr3jxO77HESGEHhd6hAspRYb+SIwj01hcPrGswlUnb0u6x4UB6Y5kf0BrYr5S9jETgEXE7/yAH+7xoeNwGNA5MsYIrH42lVLmDLMq5ynRRYeeZ2YXYbBJ7ntbBKc58uIEQRVJF3omApGsAUXIQkOTe4DSWIgUyYPtjlcY0Uo/9tJDEYr3zpZu92O5kTDux7UVsVwVLYuElv+LXYkfCP0dobvnol8TJ1vIXQkFj3NF0LOKoqEGd6uuzII4RwieHNd8PqrYoh1nxtEx94L2jsNwous6SD0PjxfOMXHMjq5IRdJlIkWLfzKEYBGDUVKcmVIy7xgjBlQzKZb8N85TbX0Ee3bX9QiByxjNVXi2HEwm9dFitGrRZFFIriS0BAuTr4kQpHisBUwy7Yq0yWL2xJhLdmTjtblIlqpUR5XiAeTx3o47BE0mEVnsj2C5146t9j8iZpTsnUWx7YLD+2zETSrHFYkJsscMok2KZAtsY4fCFpxUmmDh0dc6jfXIjuo20l9Z2lppcnu8jIy01+8BhTTtoDl/G6xsn/PxZX1mXROva1iOS71+2Xo/KzV5FpBcbUBXedOnSu6/0wDF+YB4b/7/aky9MsAayrqWqv/8UFk78DoWRwsmtpISuCauW6Blex1SfeMb9i+1ztuL+IdASAvOrp9tpXptNM1o3uPWu7ETczwFQFrg9DwhfozdyqeAjys123O3qCwgqRuO3L/8nPNXb3nz9oF3by/cD47LqLz3yq+/feBfvNwTjkcOpxNdCTue8wVwHA4BfTuREiadUMzbwoNIwIWebrjHhxMzPVnXnBe3bCvslOU4TgSQju74ArlcYI5U5tqw3QWgTAlCzJwvEe0z/cGZV48mcJ6swnmeeLycmXFo7OndTCAxLxFfn6Kva6btqGqaFaDYuZXZPY39ZSGjJjrQ7trGc+fmQG7LGq2z9o/t7TOC+BPh+Jpwfst4OROnSAjOFnEpbS3Ggqp18ZSy86/FPLr6wXLn2O7TRqCqKHKc8XrhZd/THw4cQ8dPUmSMI4+juX2nnCGCVyE44dB1IJaQErXIqqKOvgv0IdB3waQR0eLoVPsmpEhOtKp4bOceo6kEg1D4SC6qoMpehKzCNCecJrxX+t7C07sCgOqoKOb9Nae8hKrfbABLe1OGQDC7FOcsOm8ZZgvgtib3Ay1Zow1wVMNfM+AuXjzeM3TKYcg8TBlSRCTiJeAll3w/btHsawtOlKKuWtu4SE5XV50NPdXe0c0MkJVH3wLtsuOjixFtpW1ZKt/Poao+W/+9Pffa9u3n0tbuY288XttU+cWNuUgjHdH1jqs6PkJ68rwKaLuIfApI+e4DFOfJknHaJAETkEbkZ1ES106qBHxrh7cQYfneor4l0E7DUK+lJrLWKVs33/b7WraixqfKTRWGCM3jSxtr/cvqd0UQT6HZK/VRPbZ7xtVEvbr/+XLL7mZpNutytIrzP1znZn61le2v03Yhtsij3eGe9+p4PI/ErMRZefcuMryEMTsexpn+fKY/3jMcBpy3aJcpXfDe0fXCnI0B4qTsqi3eQwgdXeiMbnImFxsHFZrIldtOqPQVNYA7cf/qc37y019lTok982jfX8UxzpkwJoKngCHPMHiUzON5QnPm2B8YjieCzAw+0gMjrnh9rFYi1pxmrBpRr5O6GVhZa9vlqx1U9dipxnh6c/zXI82IL8S3170/UVo+23hMZQT8QDi85nB/5vz4QL48mLGni4Ymc13Qquh7lZxAw5TFEzqzx7CFN5maodBqcHDXOz47eV6+9LxOHc4lfvxlZBwjZ1GSQkgGaoJXghcLvlfD72pJJqkWrdh7b32/oRctHjRCmmcSxXBUFSmuv8E7svN03ldzKBRzIx4niyHiRRmcgbtcQv3HVA1fa+h7BXE4b55EfsnFY/YxWgCMiuCCubE7a/KiQqigr0qlUo6kZNJA5xx935sdDA50LhnEKUHlwEULve9IeEm4xdakSipbumh+LQun0W9d6C3SbgMJWnuwhQJ3fzuQsjGS3fDc1ji20qUBsNrePYC55gP7n7I51trDbttbekO30MlUPddA40olu1gLXwd8W1/1GpB8SMWztuLT5EDfbYDivIUt13VQqu97SepJjVpYkbV13pp5pJa9/Yc2xyuAWL63DLYFNU+BDNkTcq2vvXcHDhrwdF1l85ybC3HD5pt6djVsrlzKwqSfAwVbEefV2Q/gicWifXfv4lK6B1w3nr9rzXMPu7625KVQ5xDfczi9YDicmM8zykRMcLko7xx89S5zjo776JjGTBc6joeerh85HnvgkdAJIUFMJu9eYq85i4qZ80SKF3AnHM6eu+Tq3fqhrAuhI0uHdHf0xxfmkbEwMl0isS42oU7ABbxL6y4SR1azFxjjhO8DL1+84O54JJM59o67LvDNLDj1FWZAo3/fAuzVxmY1cl1/L30slMV9Ha31t1uuuQ3Yr8e3HcYVQN0e7DaYVhX126EA4UQ4fc5w/57p/J44voE4E7yaVK0AtHrv1XcBUbcsDmLpjdGcTB3ihD547o8DL0+Bz+4cnwXP4fCCIMKv/No3pOzwwx3eCzq+JaXJVDBxJtU8SDmZXREmfUjJ8in54p2j2cR0WgKnpWwGrolE9VoxYGif3luSP0SZkzDHTExKztAHC8wWswEnp1Lc0VOJ76Pl2ULwfgmRrwoxRkIIReWjJpEJiS54qupvWe6KRNuJWzaMOWUgAhbVth8sXggixJx5HNOyoImAqOJFCQ6CFmPfQqOrW3H5UJbfe7qqoGklmz2fbHlrNXC1YHja1nWDbm/ZEVofNCuOCBtDjLoOfHBz157X3e8KHDaPbuBsBS/b62tVJkSsNF+lgtcSj+eO7eu9FUvluhXPl+84QAkmoqWK1vNC0Cux6o0/Z4nbaKQsbDt9yzhvMNAduNgw8/J7q3pZ69mqgNq66w52rehjDFqvrqkh1D9aIvP8uadsdD5WVHdLJ9mCwPaaRZr0VF2bPn/ygbumXqEUAyk41Ae6w4mcLQJmRogKEoV3D8r//dML/+L3HnHiUTfw6sWRw9ATgqfve0LozM3TO1wxWFwIQcw24Xx5YDic8V1amHYFaLqZupWB10RqHnUHXHco0ULrdZXG7XdGmaLy9v3Iy6Pj2Af6viN0Unb4ineBYRjofMCp2VOcho53FLBUGLAshrKwIq01wFYJ2dXAq2YG1N3YhtnfGptlH3nFlFvvnFssrV1bbhvFt/NQF8iCljQC/Qv6Fz8gPFqE3ml6QL2alEuq+uK63pWZN7RbwXxpY1YDp34IHO8OvLw/cDgMvHrdcRh6lMSvffOI6470fcdlvpBmi0oc08iUzTDVY5FgVc1GRLDQ9F3n8M6AYk4lJ48mwFxyzV03AYmcIWdfElcaWJlnZYp5BQ7lMwQhJixOS7a3ydXbSaRIZCy4mveFR+VITIkYI+I6k77ESJwD3mWc94saagmKl1Y3Y5MKVbW70YMrz6lzaxgy/mIbympnIqp4l+lFTFWWi8SSjDQ8Hr2GsbpbgFeCq1S8qnKqtLzayVACAG7qbOjgSs3erBH7mXK1CWs3ph9ZPs5GT7dHngIVT6CGpyQlH6vi2R5v19IP2yDW8vFXAn/hL/yFZRLXv9/ze37Pcv5yufBn/syf4YsvvuD+/p4/9af+FD/5yU82dfzoRz/iT/7JP8npdOIHP/gB/8l/8p9YrolvUbz3+NDjfY/3Bla8D+V4eObPL+ohKeGYkcJ6pflj+65gnW5nqivZuvNaxdqV4bff3e54CyC2u7d1B7ol+vWv1MFaX/t31d4bf8+du752Xz/P1mG7+fWvmActf/v2b35/4G8/Jjeff9XkZkydbCU14vBdz2UcuYwzGWEmkxCyOh5Gs0P5yTdvePvwUGjVwtWnmOlCD2pic3H1+dY3qexWIRD6E+L7Eo59QZ8suzNZ77U4HQ4VT8JzON6bW3PzUqtoGwSzG5gzTLMlphvnyDhHLtPEZZyZSxK6aZzNQwQLOjbOM3NS5lw8Vjbgzvqo9mv1snBtf7fjQcOCZflWqWb5t47F1W5zQ2tt2Q1oKydvOkKXYxYbCWzxUkx1kdUxS4cOrzi8/AWOL36A96cSgyOSS5yPlq5rsZgkyjp023kEkLIylfgfoes4Hu94cbrji5cHfte/+JJ/+V/6Pi9e3BkYoMN1J9TZBst5JWs0Q1QpHkbeE0tsEFWT1NSs2DknlLSAxxWMFalKimQteXe8AxWmSRnnEl1eHFEt0WRWRyyeXlNMpp6sfNJhnlrFW6sGshOEGCPTbK7BWfMi7UkpbTaLlXaMri2lgAGusNj4qGZiTqXdpjLzwXh0pQFNisYIOSKSLAkmNSjbbjO6QtNSv+4+W7q6JreVp6/ed9LMURaedc1PF/pv1gW5RdvLNdvrvu3fzTa0U6h9xc0cXtec/cX7+q/ufWIduL72ups/pnyyBOX3//7fz9/+2397rSCsVfzZP/tn+Z/+p/+J/+F/+B949eoV/9F/9B/xb//b/zb/6//6vwIW/OdP/sk/yQ9/+EP+zt/5O/zqr/4q/96/9+/RdR1/5a/8lU9uvLgCMtR2w85VP3tdCZEt8S56WtKK7HW9r9TcdOhuoCnI8Or4HnBsB2lh3fX4pspa39WJzb2l5uVbecGr9hnftiu3xljbstHBXh1/gqIEWi+fJ1UwTxHksuusV163ffu+u9Zf1bu9Qp95dG1ANWYz5uJxvkPFMrUKJXwJSnaOOcE5Ot4+nHlxfOD1/YngBcGMHeesSAgQ52Y3Vgz4VPCu53R6ST8cGJ3lwxHqDkuKamHb4iXwoEKWnu7uC168+h7fvPl6lQw23ZmLj2AGHmaj+dDNDH1HL8JlivTOshXjOyQMZAlEGXiMjjELOdi4u6Vd6+i0YyXayHw2w7LS9XJ9c8FmXBoxyEZaWI+U599yR7zOGn/t3VB7KCtknHmsqAGwqB51J9zpexyKOmR8/xNiGlEmRIIZg5YXVEylkpMthuLrhsbAiuURMtF/zInLFHkYZy4xk8Xhu45+CByOyu/6F16SYuaf/erXvHuY6Pt7fJ5I0SLcehe5zNFoK3hCifdhi6PRVG2XFCAmxaXVueJ0nGrfOzM69Z6uM1CQNC2qP1Wh2Jmauiblcm7GDRbZ1TtZ6kKzeT5JV/oFc41OGfVmi2I/SwZotUB3bWC8GhMHxerW6h5dkvyVMPqaUskonfFO6ZzHuwq/zIM4Fan5EutEManJourRHW1Ic2zLJOxoC6VXd+HF5bjl4QvdbnnxavS+Daq2XLNzfKjryM9WmjeUrVpGGkOVxbvtxn3rfL+2D9sHYLuWlGz1BvWYXbt9Us1LeHvNuF0+GaCEEPjhD394dfzNmzf89b/+1/kbf+Nv8Mf+2B8D4L/5b/4bfu/v/b38vb/39/jDf/gP8zf/5t/kH/2jf8Tf/tt/m5/7uZ/jD/yBP8Bf/st/mf/0P/1P+Qt/4S/Q9/0ntUW8t5T3eTWOXexQykLXsEi7pgISMd9+KdEac87UjJdWCjEtgKJZCJuFvUXGt4AMy13N+QpZr15oD2qsHdeL+G5B27WpBuPSph5dW7+por2mrbANIqSsixI36r5VngM4V4f27yPt8S1Au1ll22/PXgm1JzLgVPFYfp0aFlwKk5vF4lC8fVC+epO4P3guc+ThceT1qwN9HxAsyFaqoCELKkZn5lXh6fvBFoeUUF9jRLiSLFAWZr9//wUiygDhBcf7z22xKknV1jex56Xy7lGFKSoPD5mXx8T94PGdEjpPysplikuOofOYmJJFW3XeAeZqXOtfd1cr9bhCEbeBttGVNGOygPlV7HETiK9hnOrDbwyoruxw6bNK38uB4v6KAb2MLaS5LJyoR72D4QVOoMfUMun862g6V8pApLpyF2lM3eA4C1wmzuGl0KqJJMjAOCnvHiLvzhNjikQygwjBC9+78/DDAaf3/NNfecv5khhOX5i6Jil9NxPzTIqRydccTh1u3cQXOivzq6gcTGoJSaPlshGhC54uBFzoGDJ0XQ8ys3RWI4XKWoFFwseZvhOymjQjJQsqaCkBzIsoq5rkBc+UlDxHfAiouIU8s4IkRXJCnS4eRoLFQhFKmHwRolb+bUkJs7PsP04yfXD0XaabFZ9BohSbFzPeFWweGyZZVUb1FSsNrgRaN23WFq07/gI0l44Wt2ZMlt0AVLIUWZN+Ns/RwrN3q8FWOgnc5O2fVPKmTdfxSqSZGPWdy7Ulh9Fmmi0AZPtOz4OUdTbK1f2NBIsyx+uc+cjySSoegP/j//g/+IVf+AV+1+/6Xfw7/86/w49+9CMA/vf//X9nnmf+9X/9X1+u/T2/5/fwO3/n7+Tv/t2/C8Df/bt/l3/1X/1X+bmf+7nlmj/xJ/4Eb9++5R/+w3/45DPHceTt27ebP7AFwDkThdaw9yZOtLTyzrvmz461qp5VJWSiRksd7qkidzbEy9V3KUS9Vc/sRV83zt9SX9xQ28iOgBeRo4hZtrV/UiaA24oMoU5Ft/lc679WES1ix82OQsqxXd3N+94S8d2+pgRkKn9VxVb/9mLKjxFtfnxZmZMth4K4jtAfMd9gT8Iieo4KjxF+7euJpD3H4wnI5DnRh2BmLNn046pFDZBojLETOU+Ml/ekOOGl7LhlfT5tnzQ0pyKoKwzUdxzuXuJc9yQ7c0AQRxDbdUiGPGVEHSEMZBxjymRVLpcHpssZNNF5WVxCbVFfmc2tsbMmt7RcQcxtmrDfNHPp1u5yHRdu0eMGpLYu1kWFo3VRLFITNRuKpEIs7qxVimJgw0HokeEF3csfcPjsF+juvgB3JJd0wvZuZRWXsnPXtX+cM56y8A3nQAIpe87nxMNjZIxmoJxFEB84nnq+//rAv/TDe37n9070zvLl+MM90h05DEdenI4ch95iiKjFdRHfgetQEeailkuaC68TU+vUaKx1g1bkDd47hq6nc50FYhMKwLBAczGrGcguIM4SSk6z5QeKVWVT6o1xJsa4gIyclXlOJZGh9VhKRR2GxUCJKZptTCPJrvmQKp1UUB+CIwSHd1juHWeZjYM30GV5iTAwojVoW7NL3yye2hwri2OzJF/t5Bcy29GgSFkS1rm651W3ePb2+mse2IKL34jy/IZxO+tWLiibIG236nhKbfPU79/I8kkSlD/0h/4Q/+1/+9/yr/wr/wq/+qu/yl/8i3+RP/pH/yj/4B/8A3784x/T9z2vX7/e3PNzP/dz/PjHPwbgxz/+8Qac1PP13FPlr/7Vv8pf/It/8ep41dWDGk014r1bcURaPWQu2UBzyohLSHI4lxeVT40KClwNxvb7SvDbXeVy83p+IfjmfHO2/WWTqRwv1y+iSLkWkz1FWAtpbojQPXvf2pTyrBaEb973+taPObc/ea3iqO6AbRCkp6//9LJuxdUJ3XDkeHrF49e/gi8qhlzoKAEPl8zDw4yIIwRhHCdyygwh4IteHWduxEu2VwFNM9P4wDSdOZAtUZsr4vUyBgtNLO+2MtFlb+J7htNLuv7IPI9Xb1NgsrFGNY+Lu1NPP7ii5rCIp94rKUU0R/r+iIzVtsDGZDUMvMWEtoBkPV7zCtVhvT1XaksXE1aBPRUvEqHN++/nSb1W1k+t7qa2u647eAONBlaqP4rWhV8c6nuQl/i7RJ8TkmF+/HWLyCq5hE0v9F/GeAv8AedxqoiKqZidMqtjjBCzQ503r63Q4SXQHxOfz5Hf+YMT4zjx4zcjGgaOp5cwv6cT6DDgoEWyEdWyYturxgLRHM4biI2THfE+mG2URqY44Rz0/ZG+O3DoA8E7c88FUmaJjRI68/QxOxhlmmceHqHzns4HtFO8c6SczR5mAZIsICVn6DpfhlUtMWBR71TwKJrLOxXPJCn2TM4Z0FctxrUZEYsgm7OplihqT9FcNgXZwuKrmPpiFSzeNNjc0tE1+K2u9cuGrdrG3YquLGsdG+pseX3zvfZTQ7y7uj5O7dE+Sxf1zfbO5yQem/nYCirL8f11z8c2+edTPgmg/Jv/5r+5fP/X/rV/jT/0h/4Qv/iLv8h//9//9xyPx9/wxtXyn/1n/xl/7s/9ueX327dv+R2/43csKNayMroGoMB+UYOVfswGxReRWCoZNYuaR8rkIjX33VggN4t4S4zruavjzzLv5pisYsgrVUpBJ8vUWD62v9dje6C0b+YtgLJ93r6pW2D2RHkOzT/z7jU+wVrHdqLDx4Gzp4tWHQpCBnH4/shwfIHp5uflyoxlTZ0TfPXmwpdfv+XV8RWkzDjPQELE3B1r7AnbiVLCcJegW1Kjkpb3WBb66gWwvm+NV1BjeAigviMMd4TugDRePlabFO2yWkA2YEwwpcwUYZxhmIUuGJg4Hg7cne5AOvy8Ssrqp+WmaQCK7gM8yTo0bSuaISvmGeyuWPu/DgPSJM6DCk7qtdpcvj57e07LQ7WqFig5WdSCN2atcpBqe+AREqLZMuK6Dhle4jXbTlJn5vMbchyheECZrYcsRtBVlL4aO3uQjIqCy6h4okJCzAjWd4jv0ODx4jilxA9i4jzec4nKm0cBuUe84gWCN3XJXMK8z3Oi8wOhSIZtYWcx6SgkhZOOrrPcTSmZvZ0TZQhwd+w5DoHzPAGm9qr2PH40zxjnLJ/UpRi5dl1H1/dkVfoQcMHhsnnaqNR+sXrMuDgsG5r6Vz15oEi4ijo9JbNa8b5GxpUiWVnDQaSYSDGaNCYJWhIepiikomKyRA9qE47G9nBBlavnzgpC6vyv36vU2ZeOXIFJbRtSpc2LQmMzH1bSvMW72ks/gnfeKjumt12DaN55t+5cqX2a+3cA5EPqnOd/b+RYzze+TUfxgfIzuRm/fv2a3/27fzf/5J/8E/6Nf+PfYJomvvnmm40U5Sc/+clis/LDH/6Q/+1/+982dVQvn1t2LbUMw8AwDNcniqqgxDte9kgfLoIpkBXJmB2C2CIjrhhoNcR+W8rQuH1uzm/3mNsd8ir9uGW8ui7M9dq6GJSbKtEX4PyUZKcFT+u5W5PlmujWdsrV+Sefd1VuuxAv73n1rIa0Ze29jwJCn1wqQKjtzEjoLVqrD2gam3krJFXGCL/+TeSXf/qel/cHXh+DeS1kCxNedzKCGf+ZhH2Nliku2AJVwoYvwLNhZpWdru1awUrKFhNF8QieamdRX6c1RhOEiyoP88xd7gndgEhCROlC4Hg8kVW4XCYy3kLv49YdagNQ6hhsSWtDscs16+c1OtmQdRNJV5oL9k76t4s2bHCVtFSgkrWqYmRRJSxPUpq7DMo4pYS675H+Ff4+0+fJvFrOX6O52qTYnaKr5FFVF28WdSxGtFlMpRMTpCxQxp7QI8HUySEnSJnvXSJvHi7MKfEuBbIcGI6OQcwGY44T5/O5rPaRmE2N54MrVJRLtuXVXsb5DokOSMXtNuFInAbHy/sDb8+zqXe0GItr5jKaGqUPQhJT9aSc8Y8TXTdTVcFuShbp1QtZzZ7Ke48DcpyJ3pktSlbU6+L1VOnDXKNzkzTQHCe890W1pOQ0L6o41SLlKV5Cmov6KInZe1FUoTSu+VcqntYuovLqFaRUEGJenFUVv35CkXYWgLJuf9sNkzTLwDU0v/p+CzDsfu9Zslxbh1/XcYOXP8WnpbFa/xAIWdt0Hbxtvf4WONkeq+kIPmqJLuWTbVDa8v79e/7pP/2n/PzP/zx/8A/+Qbqu43/5X/6X5fw//sf/mB/96Ef80i/9EgC/9Eu/xN//+3+fn/70p8s1f+tv/S1evnzJ7/t9v+/TGyAgjShu1QXv9X3bv2rkZnYpHeKDxVQpNi3VLsXCPm/dha9diBvwsXGFve0WW8+V1eDKjkQaGxJoFmlZhPj2n+zrZfOMWr80u4H275YrdGsvUwMm1R3q9s8m8/K3syHZ/37+r+5sq053e27/3Otjstz3sX/buhwqgeF4j/M9gqMLHRWAZiyM/DeP8KtfTfzk6wuPcyRLib+QFc3GXFNiGR/jiZ6uP9If7nDdgewCmfpcyp9b+nr5W8kbwPrYdQZ0dlNAtUQdpUp8ZFmkY8qczyOakqmiUC7jxMPjhcfLTJKOJKHsRB2O1ehyT3/LsR0db49ds2MDJeuRqn9v1Up2iTR33P5bFq1mAcu7v5TLLr383rZIQSLqGgaspg6WcIDDa7qXP0//8of4w2eoWFZiU/eu77iAn8zCcxTzEsrqiEm4TMr5kiypnjgQ4y2u6/GnlwwvXvHyxZEv7hwve3Mhfj9mRo70d684HA+cDj13h8AQhM4ZiEvVzkQKmHfmuOC9Z4Fjzi82dqYOiRyHwMsXR/rO4quQhZws2eQ4WRaFlKXYpTguk8XVefdw4TIlppiZ5sQ4zYzTzBzTkmPHe5Nip5RK1FkKQDdVTM4tMKHw4OvQDDGZ0XnMZvzpS2C4YuxFThFyKmHuN4S1jMlmfJ7dyBcAUgEJq4SMhuYXvszKn7a8ZLsmLHR+FR6htWvZl2tav+bvN9ayGzVta30CnLBhMxvavvX7Zy5ahrAYi8knAJRPkqD8+T//5/m3/q1/i1/8xV/kV37lV/gv/ov/Au89f/pP/2levXrFf/Af/Af8uT/35/j88895+fIl//F//B/zS7/0S/zhP/yHAfjjf/yP8/t+3+/j3/13/13+y//yv+THP/4x//l//p/zZ/7Mn7ktIflAESlEpZV5raGM0efESFUwjumNmwVZsqBievnq4bNFiOX+BQxXGOq2vzffZft7RyHPSSb2LmsrAGH9XGE9C1k2aH5bZ3vD9fMAVtH17tzufbb3tJft3uETiV1kFd0vz2tFBlfX7/vs6bLu01cgJy4QwoCIEDrPIQTmR9P1O7Col1l58z7x6988cupmXr+8Q7G8JzHZvtwV18m6a3SuYxju6Yd7cH2RWNQxsUV232Cn67tLXXKcI3SDJXLbCSiuhKeqBECTEueMhSqHlCPO92XxdrhwwPd3aOrIem3k3fZrS+tVtrP2fSXnFU7JfqxktQC4tQNdZSJX3XH1jtWGxL7rAkJMglIWp5sUUOdwXnbervg9qirqBDiQh88YXgpelMkrl3dfktLIEsSOAgozqLMUG1SAnZWcHfMsPD5G3j2MnC8zL9IaIBIJcDzgxXM6n3l9dLwdEm8H5XHqmTAXcB+UTjKBxEVGnPdk8YxTLG7JwtCZkW4mFS8bcF5xmRLYT4oqJRJcz/3pxN3pPecxkrMsGYktSCFM0WKwmHoFUsz0DxeG3vJPSVn0vU+msgzKMPQWL6XmQar8aemnTJWPpeLiU2msqnRaaXXdFCmK7zwuOMRZMDqHSWtEzHOnTrdFOnbTZmIvmZPmZwMY2o2g1E3kCk5uS3NlebeG3dqXnavKwtM2x57hp3tJyI03q3U8JfGgnav6jEPzJwCGf97lkwDKL//yL/On//Sf5ssvv+T73/8+f+SP/BH+3t/7e3z/+98H4L/6r/4rnHP8qT/1pxjHkT/xJ/4E//V//V8v93vv+R//x/+R//A//A/5pV/6Je7u7vj3//1/n7/0l/7St2t9XejLmmsozX+Ecc8q4q8LhS676rQwbIs9YJbiJmG7JgRpgMJqN7DWv4LqRqy/rEuu+b4jVmnqKPfI7vzSjivKu+FivACpLRHrpu5t/3xboHFrMjePv3XHdgGT5a2X88+hjqt2PTP+UsZJ1C9V45wFh8IM+VKK1L19EOi80HdCEuXX31/ow0QXAmTT2RecY+0oInfbKmrxxPEoFqBNSphwY2xu5Yvl5Vv7G8USmjhx4Dqc80bkdWF94h0VmGblckmcR7gcAqfeE7NDJIA4sutssdSEJ+I0mTFnVV02O7QNgN4cq94u7THZvE97V908XO+gtuO3qma270Tz1raImbSIAkxylaxs7qoL327+wBqwjyKWQUAGZHhFJ4L4QHYd0/tfR+IFIZtqoTwvqZYkd9jiDUSFMSqPU+b948TDZWSaZ/rY0XUg3iRhrle60wtOdydeHt/wc6cZNPB2FKZZ8H1HFyKd8zjpiWkEcSQnXMYZTZYTx7tqE2MB2VQ9KTpQk3CMTLgsuL7jfuh5fT/w9v2ZKZWot6VH5ihMo/WoCsQIs8LDOHO8XBi6DiGQ8oz3nhAsn1TSzOCEIJ6kZkNj0W6BKtWoA5IyGS1RcnOJRJstOzE150+70SwSb1GCmPG3d4pPCSHiCGgJ6W+G0g3EtaosUWRLaQtQrCNfQAlVKtGCk7o5rLxiB3TK5/W3/bX18o/jn7DOr00FLRpr35O6lalIjfpmm/paV/8qyVr4VAVbT4K8+tlKprZSqn0wvFvHWknXx5RPAij/3X/33z17/nA48Nf+2l/jr/21v/bkNb/4i7/I//w//8+f8thny3axLXRRgMpzC1VTw3q/A7BYGOYOakaUmvNiZb7o3iojbgFKg5orsaqwTDZro2se2yzD7W+Rtd4b7/mh39rUc/N1bx5/ahHaX1Ynwy1gs3nI5shzI3FrAXzq/O2r9szguafV8Vt3404cvvMmKZkKE5WiMlCIqhxOR04nxyWOfPVu5vP7EWQgdB3iMot/cVmBq+2GOMH7zlSI4sgCUPXd20W7gidrnxki1sBo6hyhC4gUVvTEKyrmeVRMrEjZMyfHecyceqNRHywmis4PHHngzt+jdMQCpDbg92owKgkt7P1KQrfMwSfoYx8HYcdyr85tY4KyvH/bD7mRoLZ3ttPLeHHL+FeGbosc4ITMAekt1PvRdXjnSeev0flMSlMZkwKKUjSAW3ZISTNTUs4x8e488vb9mc/PJ4a+p+szLpnhqkhHONxzePma0zdf8fLxTYkY6zlHxyV0yCAEEoMbCNGbfUaMTJKIKTNNFCNTM+w36ZozIJsTuURnDc5A6F3f89n9wK8dAg/TZMoHLWrMoqIk2/hYVHrz/rpME+Mc8d6RsuKr94xYKH7tAq4rweI8JVdPpVPFKYu0o6aTQAyMp2yeZWb8XSRidbOopprsnacPSpfM7dhJRoptTaqcditKwQzeWbI1XNOWrDFQ1h2GASRxJpkvqplF4tPy6N38e4pXttT4KZLk26Hj17dojYDbxiyX7DaiXGkB1hvaR7USma10pr1/Pxtvt/cWOPnU8p3OxbMVNT8/+E93jiy73z3yWwjT3QIpVRfIoh7yLIDUMO0yMaRp7cLhd22Xpc6n3unjf6+z8kMT57ljtW/quttAl2bxaRn+et+H637u/PO/PzzRnztf/Tmsj8xrJZuKx3UmwnaO4GGMmQiMSZmSktTj1LwrHi+RYRjo+yPBm2GluVGWnVlO+NDT90e87xCpLpe+CEB2XHPH85bDrnIQQZzfxOJ48tXVbFEou+3LmDkG0/EnlK7vyNNMH7/hzp94lJdc3J1FXa2M+mZ/tz42thi28oqrDeaNZur+uv3J5msrLYGVkVZWWSUZH2saf7tdeuObQ/xgdHEHPnji+Z75/DVy/oYcJ5hnckpoMoPSXHf7mJptnGYeziOXi4WDjzESY8SHVOzePL4/cLh/wd2LFzy++4bD9MhdfyZe4DIOJeqvIxzhSIdOZ7woOQ3mRSYUtaIl18s5Wqwd59DMkocn5YzLidApn7048erFI2/PM1MUCx+fLdFltWtZVFjAFJVxikwx0kW3RIAFR3SReZqY+44+FDdmMYlS0trdlY86fBDilMkp4XzAScASNefivaOWsVtqHiALie9DwrlcwuXrYrJnbuAZxbGdEtJQT+Xl9VQB0OUZFDCyAJQaubdR66x2VqyI5xZ2/wQA8htTdNmMGUirHFlvtu83rRXPSEx+1vKdBii13FxweX7XvhnAJsGYiR9t6+wqwaJmFClSItGyQdUtMNAM1ahrecyGqFfi/hhgcguEVJJUO7B93+X3xwOd/bGFtpad9O73vj1Xuwm3+/0xs+XjwebVnbvrn58c1Uan7pDMmyH0R8JwYnpvV3jvIFoI71nh63dn4jTy6s5xP3imDMyRnDLeeZyYsaqJpC14V9cPdF23jLvUnZkNFKunzrYP1uV23R2qOPDdhx30iiAgAT50dL3gfImPGnrCcEKdA73g9YykCxLUvHkkrG14CrBW6pMbO9flRXT7c6FG3Zx+ovmlB4otyWJvUkFJWXwKOMkrsX4cSCndrU27pdRnx21hs/k+IEHwriN097jhHj2ciJd3xPN74uWBnOcyjq4Y2Nv8nhNcpsxlzsQktuCXHEiF0SChoz/ccf/yFe/ffMXh8T138wNzcJwvnjdv4Twk0kl4PQSGrkdTz90p0U2eudgTxawk8WRNoGkxTNVsySlzTqjMDCFyN5z4/qt7vnp3Jj7MFq6ewuakummvIeunCJcp8XC50AXP0NVAlqb+MElOpPMRBIIIronIXaPFmq2pM5uZaPFNnA90XYdz5nYcYy5B4zJJI6glz7TcaREtbvRODAjZ+GdySQOwLNW1k2V1CbdTld+6gkd2Rq7L73pN9d5pQPuTvOk2aGnOfjyI/oiy58mrZP9aUvJx3PRp6cjHtvxjVDzlx0fVB78FAMp+MV8Jss0HUOFH/c46wmVLJ81VIlLCYiteiyuqyApSNmuKlLlQbAsa8aY09a/X7hfiFdys9ikrseuubSsI2S3KN/ri1vfajq2+tP5zSwT4PJi5/fvaOeyTQIfsfuzn/lWs5P3zn5sAyygvi5WIoxvuGA4vOeNIKTeY0nTjY4RA5u7gyOLAB4vmqTNOC7/OdfGmhCj3xDgzjWfCYSRLiVZbvAek2j61YLb9V9ROicP5nm442r1NjJ6n3nDOyuN5xOM4HjoynjFmzpeZy+BIcUTdkewOJPeCKAfyTiKy7dOGnq76XtiAqo1oue31p9n0HlTupSUVeC3H1KDlU/c/WffCyLd8sgKoAn+K0MqhDGTvwQ2IH3DdEde/xYVfQ0SJ4/sSP8kWYu+8aScQzlPm/ePMGNUAibdYTVp5TugIhzuOL15zd/+Sh2++ZDy/5eQ9753n7aPyOJqKZCh0opmSXyeTZ1vYx6iMWU2SkpKpGzOkCEIi6Iz4QJpnQlBe3R94eRp4+zCRKbYdXrDgaLpGQ8YMaC8zvH8cOfQdXTha2wu/iykxxZkwuwWEIELNvt2OkYgSvHkLVelOjfIdcskZFALTNDHPkZQjoIQgdMEhzCUQorcsOYVvrS7lK6DdSnxh8dhZeJ9rOIE0vLnaodg1xgTKu+xZZsO7Nz+fKBUAf3x5DtZspSSyUcW0x7dbmqeevxjkt98/ACpuAZGbLf3tquK5VVZbDyNWU1HY5Nts9pYb1mPLvaprEKSaghcTp+a6sDUEUUneLq+cdbU1aUHFbeBgz1ieL/X6+oT9Ai9cr/fNsRaAyB4I7Z+974yPARO3nr+74tkLdu15uim3L/iI9j1dmpVOpIyj4MKR/vgSFc+cphJfxxYrxLBHTKDqmWPi4Tzy4thz6D3ezZCgGqKpWvC/GGcul0eOaaQXsz2oAfiWnX+h0aqDX4zXahOLCN+HgcPxhQGcJpjcE29IwtyjUwljPmUlqTM35+JZkf2J2b/iko/gQhEW6g0Q3bRpJxzZDEXh+O12oJ1fTVSSbXuvwMmq3NHm/B6YrOqd9f6rkVe9kWBwqe36kCHCzWqUtRo43+H7A84f6VwA8ebSPT6Y3Rq62nAgnMfMN+8uXC6WAds2Pub2S7a0Gq7r6e5ecHr9Oac3X3N+fKBLDxxFOLhXnHPPnITzlJjTiMRI57BcO5qZ4sw0TUzZkdJMnieCKEEcSjIbk1xCzs8R6WYO3vHydODQnZliXKajxSKhhPvHwsq7TEyZccqM08xx6Ekpl4zWFv/Fwtkn5mhRZl3OhNBZkLayuTMVp3lNihSZU1n7FRDvEIp7tDOwN8+Y2spbBOc+OLyLJtnMCbQGaWvH7xYlrGk7aMFINYJdpKnbUAvrxu1GucFTP7VspdZ649wNV2m7+oka95KTlsafbmt51HJFuxmuoGrp4k+wK7mKSbPsCn4bSVBq2asojLZ2Xd4yX9Hl2nr/NiCZNndWYik7B/LS0QsCZ7UCX7wLrLb6gBttbYHEdiHQ3bXXwOaa4LaizKfv/3DgtW39H0K+H7IhuVLBfGBi/2bqcquUKguLqsUAyoG7l58hPhDjbInJ1gYDFaQo06ycx5mXp4H7U8fpbDvYOUWcuNU2ImU0JYJ3dJ0ZUqay2xaqEa23MOPOkVNmTnlRY1TKygjiOo53L3EuFAPGp98QzFA2qS0205x4eJx554Vv3j/y8njP/eEVcvwhuB8Q8gt6PJfpDM78Om7RRlXrNFuAhte0c+0GSNlcW37ekppIA0AaNqllIVpxnZY51qhNtJ2PtyUnNxuyXHvNPK3u8mxxRHU4f487CMF5VAL57U/IVZJCIiPE6BjnzMPjzONlsmzB2TL8pjgDUuIwBcLxntPr7/Hi/QOPD+94nH5Kp285uJ7sBpz0ZGYi3mw1cqLrhM4LQ+c4dIHpMnMeJ2JM9B6OwRF8R+edSRuKdw4ofef5/MWJX7+78Dg9FFfkqjYrQ+bA+9L3GeaoTHNknGa8uDpryMEvKqE5JgMopa8CZrwMxpLaqME5l+jLSJF4Zpw4uuCA3qRRJXlQzDNdELrOE3xG0AJQrhf1TVA2BEvXzAJCnLgl1lRNBriJabIAmDa2iSy4pnnas3zqSUlFs858u1Jo9EMbxCvo/rOXWxuJj7622XJ8Sqt+ywCUtlyL9/ZFF+bXApk98Sy/K8KsGMf2nyzEoi0KZxFztnEuVtWT/VUXx3bvJw1zhm2I4o0ulduL+ObYHhRcieOUxUK9uV/adj/1LNmy8euW+Ou21WffvP7D5RpA/WxFpVnMxKEucLp7hQsdKZ6pFiJVs13jL8xTRHNgniM5Je7u7jg+ZB4TxIsxW3FqMRvE4VwAVeIcUa/gikmnbHdruqiHat+tCz1iVoHD4YTzgRQ/4v0oiiOx5WnOmcsceXsZeXPuCeEVs7xk9nfMOTPPj8VzzTWxWm6D6vVzGwZ/z3ieGusW06xkWSWcUubOuoGocpeqOF08RNo6W53Q7qFXO7l9expwYlF1N/IbLHaKLqBSCah/Ab2nuw8Iwvzwa8TzWwNOyRbzqQucx5l37x+5jBM5W6qCNE/mdRMCIVgY/P7uJfdf/IDz+S3ny3vend/S8Z4gd6AdSEd3uDOwER8QyQRxuKEH15EQHsbIlCxPVOccfR/o+4CjGPY7gEzn4MXpwOevX/D2EjlfzvgAPpjkIqdMEEzqvMTRgTkmxmnCI0hWhEDoHCl7YkoLXTsSNXlrLdUdO5ekhCmagatILlLCTGQE6bBgiR6hI+VMmGNJHiiE4uLsZ0HjksBg4aWbDVkrtZaVv20DNgqrxKQBLEVyufDsqz3hp2+ybm0MP740FH91+3Y2lBXmWzzjI1vyCQDrY9VAT5XvPkDRNRiNtP80i6iw2qYsHjj19l11C4GjJZ23XoEWKQyraUTBKSUn0IaZ1SvqhGnsM/YgosUXC/fWhmGW9rmKmMriRr1U13rb7dC6XK11inmFLPYQixj0du6GpVXyVGAiSj2bE+u7Nbr/p8uzy9lVO75NqePm90zHefzhHt/fo+M7vFNyqv2Slwl/HjPni/LD792hRJxYVm0h0gVhjiVqq9pYhS6UTLQB8cE8hcSYn1LE6tHGaoVCtnNzrXTAAf0RP5yYxzc3+qVKGwxQ+/L1Mia8h/u7QMyBRAnS9uIX+Fpe881ZyTIbpJSe1byxHckFJbDKCG8A5PWG26UFMwut1t8UMtL1cbpT8aiSFva7gpXq9lufr20qgBvg5DZYb3Z2AjTRSlupTd2gJBy4A65/TffC4qEIwvz4Bs0WCG2aM+/PM1+9vfBwnomqeCekkt3XV1VKEPxw5PTqC16eH3l8eODdQ+Y8R1J+5DwLD9OBrus5HE4wJZBM6IVeMz7MqCrjHBmnkWlKPM4JHxy9Whwf1JFzZppmet8TOs/dMfDiGMjJEbpM13kcQqqU6Eu2Y8v8wZwsC/IYI0kz6jBD1yDMYs4DuGxzi2iRiZ2QJRMjOPwKUHImEy1gXpHaoRmVaBsD5/BeCD4Q3IzDYr70wXHsPJfkGLOpnyoNybLxbFyCxexhlijjbjXyvR0VtoCUJcrsCnC+7ZJ/2233+vzu4EKK2y/1fP3ndqt0OV8P5NvX7657TkoiT7S1qsHrXGrh/QLzvyVQ+U4DFIF1x1TVNwomu69uYevCvpdC7NTtTVEoC9P1BQoqi69/C4bWTeYqXhPZJomrq2LrDbHWrAuDLmb/qFZRZklmJg5166TL4pp6Wewq7YnrDnD53gAUxfTgtkP3yy6xBu7Z9nVZqja7gGaFd09Bk939zTXXZFqYyxUB721efhYJivWEK3RSl1rnPcfTS+5efMG797+Kc0JM1toKKaOabOjhnHChp+vFdsJLcLOmaWKLVtcN+G6wfCzOW8RSLZlpkbWfN8S8GmLXSS4I/eEFpxdfML77cVm8ZXMP5Vp0hTk5w+WS6LwnnwJOerrDKxhecbkIpxC57zKP0XFOmVnrnQ04aT4X++MrQ+SV+bW2XLfKs6JiLfOgBQWw2J7Up1RmqS04YWGHO8b7HENcQd3mnspTllIWPVEscKOgzpPdAZFXuJzpU0LTRBzfg2amGd49zvz0ywd++uV7vvjiBX3fU203UJY5LWGgOyn3r7/Hq8dHzg+RmN7AFJnmC2/fRXLs+eIodNKRnZKdx8tMlzPH3vH6rmecer7KkSllzpPZq4hYLBfFQFNiInqPF+Xu0JHSQC7AQMmELuCdNw8ZjYudSMrCnIGUiTkjzuF9x5AUXAnDT6IPAlkILlkEWrGcVlO08crZ+FzKiThjsVOkqF8K58zFEMYVwODF4Z3SeeiD4+CF3sOsFllKFVI7Heo8ciVfW+Vz1fakSFOcW+1Q7HMHTJrx/5Q90ccCkdtz5NYWQdtTu7m5p/BbwMWOXa9m67UtqNH9/Nng/Ftgo4CTjfSxaXdz7p9bssD/t5UFgDQgBViYz55xPs1IpfzvildOXiYMOBM6oEv0yOURSzXrbsySWK2iwr2ofI8sFUWyomp5J1TTClK02C+IgROcLxNsjUhrwcesBa4iNGmAyYLYCtdxakEFckacN/XOMkmbvqXay0jDzF3zTi0ozGvfL/25unKu/QtVktAuMR9W59zYvbc78WeKyNJLi8FqDdLVDQeOpxe8xVmfl3EUJ0v8kYTjYc5cJuXw2YlpLKnrpUZ99cv7uNARuoEQehBbIChRLDcRpG6914Z0BRHP8fiKz7/4IV//6j8GiqFsY6/S3uoA77wtUDkxXhLvH0ay9IThjjR+w2fMfBZGLu41k96R6dFWwncTSuruHDfAyrcrVZ2zlVjoCq+1YXtaGW7DINsdyRVIuXpa87c7XL/ssYrU6/OapA6Hcwdc/wp/SvR5AhI6XZimyIMov/blA7/8K2/54fc/4/504tAHqlSuuqXjHL6D490LXn3+fcbHR2KM8G7m8hB58zDya+dH0n3P64PjroMuQB96JGS6nLk7Ki/HnvM0cpkiihlKd8XzR/HMKXNJE9kHsgqH4QDiGKdHxmki5czxcCCEwBwjzkHwRW4ljlxUPeqEcYp0ITLFtDiXZbXrDOAnfA4QbNMRi26yevAo5gINYpGSvfETG3eTyKQl1Ug7LjbW3oklTixSmUXq0QCRqtapgGSr5imZlDf52wq0afh0lRr/RpXnJQjrJLgGHbVFK/3vy5O2J3Lz8tKe7TNuG8JexwnT5rvx9/X6ayPa2+39UPktBVCgASlNqYaRt87fun5DQEX94RwF/Vt0WWqmzmW3tzK8dfDqDtltWH1dJOt9qmZAZwNrybAkRzQni7OgEZOmFJAkFrLc+4DWhIayeQIIS/CoK6Yt1EhHFvK9hH1fMlxWgKGwWSnrrqQCoipBWoCLNDTY9GG7UNQO0LoHWH2gqlhWNotkW8o97XBpCwfXbrilgii9fQMWFLWV73HhYKHpNZZorCWXSHnXWRVN8OXXD/zCq8A82c4QCUBaxMNOBOcDvhvw3RF1PSKhhNRsVYzXO7N12TVjbBEHGnD+yP3L71k9Gq8ZN+t41BSC4jy99yCZt+9H/q9f+THff9Xzw1cHXgwnpvg9HkJgTPckZ2Hw9yCx9eBZ+ndDbzT08XRR3V7zNJ9eT1jiw4bZVZccrSHOobqVrxuGp8BJyyT3wKQB8eVeaU5B8QZaRFvF8FQdCY+6I254TcDm65y/Il4eOI/K1+8u/Oj//orvf3HHi/uB739+T9f5staanYd3Hjz44cDx/hWvPv+cND6g+jVjVr55UN6+i3wNBAIeRwgUo1KPE88xOO4GzyEI42SUPmd4nBIxR5x3jDFxmWZGdcx45uzo+w6RnnGaDDSoFODVmYF3KFzMW0A6LckT5wyP40zoJlSGIlXO9J2uUZhTwkVXwEdTiqFtTpbm0jkbZ0fls5ZfqAa5S5otG3KydAM1kNyi8abSZKH/HRih2qQ0oEV20pT2mlIjVJW2XFPTtykfkqJsJSN7etUGN28BS/2931Z+fKv3gGLftvZ8WefsQL1woeer9abl/bu2f6j8lgAoNyUixQ5jv1A9BU5uGceuRrKrt41zxR207KZWD58VnNhAFfWQOlSK/k+c/V6WVGOKNaiSVhCSkwEUjWj5zDmuPu0FoGiygGBSLdORuv6xcaGT6jxZRfelb0pbpTUGaxeRhbjW+6yXHCzpuqtVQuuy1/YLy2cFc6orI6Hp4xXssPb5gvxXoLT8VLZRWet9z+xQqhRIJC8xbawdiviBw/3nODcgaWLoPHG2jK2x3J2xMN9ffjPx1ZsJJ8I4g00lX7Cf6bOd93TDER8Gku+wGCjtjmylqy3DWaGGvW8Bui7gh3ucH0j50l61uV8xD5eYlSnGxbBQScQ5cX4cufSJTjKX/jPObkDdgCxcf11M9sKsK+B3A5N8SMe8P71X5yzftSYDbOosQELq90V6szLoK/H0FShdmW31t6v0aWevgc0yJlolbivzVyCLB38kDJ8xaISYiNPMlEben0d+/OUb/s8fdXzx2ZG7U8/rl6eyQEdSNFoR53DdQH+84/7Va+L5DXF8z+N45r5XvvSOqJ5IRxRHQojZAsmJSwQfOfYdnUWJZy7xcrKDmCZCEOYsvJ9G3p4Tcw64EHhxf2Toeo6HA+dxLBFajY67GnwORXVmTrZZWmzXovL+PKLOMYSO5BJ9zPSdFK+3jJNEt0gswHKcYVJbqRLqWM6bStyyg1uG5JRysQdk8YQSNaamRbLtiw1JNQzfABFaiUo57mSZp0bYNbx9+U8q0CkkIIWjPUPbz4OP9lwzVzcLeZ3RO2CicK0WKXS9A+ILBeue7ivN79vSXn/7PW5JVKrzyDJX1ol6+3OZMzce/0z5TgOUSki3jYxYFrPGrNPuuyExeconfXXddSXRVJGiuJrrpzI5WcZAG7GkXeGASFXFaAUw9rAiKbGkhAZQImgsoKV+WpRIW+AcTiJZfLGWtzwyXppQ5UtkRFnDN0vZjcu6NNrlldGvQe62IkRDAuuvkoJrASnOmI4uy3/budRJti4ysgCSOul1MdI1QCf1mhrrYG1xWZxWGmjruhJH3KKLcmcFC9WsGd9zvP8MHw7o/H6JbSHUXZoNXgbeXZSvHhKnY8dlNhdQLc8XEdsxekdGGOdkM62ZbS2skEb60CoNtRroKqaOcp4wnPD9iTS/uXq1FuwoRfogwjwnsoILWE6Y4wntPLMGkhhw8iI41cUtdAWpFfyvx1aVXh2Ea5B/1e3NfNgMQ/2uqzFdq9pZ3q1uGhqGJw042eCoCl5ppCybxgCl9ra3l+9lc7Oea9tZQXQ9a/Pa1stA9neEIdKdJqZ5JD7OTCnz5vHML//ka773yy/4/PNXvLg/0XeOlCPzdEFE8KFHxBP6jv50x+nlK8aHt9y9n7jrZ+4HzyiB5Do0BAgODWabgShZMl0fLfuwTCTN1HSAKSsaLXfNGBNv3488ThN9b7l8Xt8deHV/j3eOyzSTUiph5h2dtxkScybFREqKaCKEHhXHZUxkvZBPjuDA+5G+D4QukHLmMs5kFbo+4EuUZaeV71bPnlxSQawdnlXX6LuqILnZ/DSSE6UBI3V83AI2VglJYwTbSEz297WEtCH1Z1hLyy+30+DDC3+9bqNIqkh7w4drfRWM3z6+fe4WXDzVjg3QWT500WrmHYjZvGi7OWftixYMfWDP8mT5TgOU58pq/qjUuBJPeX48JUXZVVg4X7bU59nE77qoQ1aGrqpoimUHWP0NZM2YXECMRYY06UnWuBDkotKpwAQteV5q5IeEEs1mJBeQkm2yueKSuhiGOVPhOGkWF7G4G1IN0xoxZ93R3J4UpY7aTwImEcLyKtZdB81cLn1UF59lQ7CoeJYOL1Fzrf1VIrOAv9p/Cmuk2qqOcGy4x37o2nm/SGqqvVJZmkRQ8RxOr+hPLzmfvyTnTNcVI+eUy4JoMUYuCX7yzcT3XGDOFbTZw7fgVHChR11g3YcvTdjhqVZ/XGyLChNXFHVCdzjRH05MD+3YrFXWnsuli7vQ4bHEakPnUac8TiP380BQT+4DOdriljhAw6rbhm4lJy044YPlFnN86tje7uRW2e8wN+CkHLsFTpb7alyT5d71GMv9zasV+ym3Xl3slypjL2pAHEk6nD/hDp8zxJGcLhDPzBm+eUj88k/e88OffMOrlyc+f3lCcOQcifME4su+whGGI8PdK053b7g7PHDXjZyCBUWbYrbAbHjmkpLD4Yl4sgQOhwP3p5EpKa7rEHzZ4Yol3wsdSOTxnJhT5NCPcDry4nRHFwJv3r03UI1JUXywyK0alSSJqNHsrgg46cgameZMPyfUw+NFOR56+i6QgRQtjP1BB/re7Eaq7Y1zZt9X/5yrBudl81OBBJYk0HvFe8Ul01K7XDeqNsKtwXoFI9V9vlXlyGKQu6qAWhpf9lAtYnqSItfyPAh5+rfQKqrrfrFZ+JtdmSx0x3r+Vtt0W+eH2rJOKb392dy3nYH13/XIU4CotU/5mPJbFqBAQYbPcNAnpS91t7Y7ZouFTYCqbzUzgbqINIRc7EpyBRqV5ZVF1mxOUpG2JIsuaeIXsmaocTqkEKQ0YFpL0KWsFldDPWtyq/L4Ej13MZpSa3Orf60gxSaoX97NJnFh4re6Z7O3VCAVEFhlEdei+pYwF1sBLaqnhXGALQO+MIwKUlrD0jVOxxL1s07c5v2bj2uhypMrn+dwesnx/hWPX5nnwakf8J3n/OZx0xkR+Pr9hO8cMZs7pIMSskTKUFuys+A9c1n1N6BZ9v143dPUfWCxfRgOB/rDqYjC89W9HghOiGo70PM4EXpP3wWGztvOPXimMSPhJXP3Q97Iayb6knG2UnFrG9NKMlq0t+/U5xnPx4CTtFkQtrXfKltwsmObt8BJc+NWDbnSiWr7XddzZaGosLluPOopELIKSTp8uKM7vGR+/Io4j8QMjxP89MsH/tmPfsJnL3p6/wNOh54gHnJJolfaKt7THe443r/m1atHXr8f+fJx5PEcGaeJNw+Ky8IgkWPvGTqH5kKLoeN0OiBjJKlYUDSEznvEB04Hz+kAXXhY3OS9D/Rd4HgYAPjym7fFgDUYEEBKsj6zdxGxaMjiPMGZUXlMinPOosrOJTmi8+V7SQLoPM6XTYwzqbRJUWoi1sLzXH2e4p3DO4fzSggQshAyuGSGspaRWdaZsPC4NirsPu5JI0VZ6KixRbmCvZ8OTj6l7G3jbP1pFnNtIkfeACdP27Fs2/YcQKKh8QUcLf/e3vUtnP4D9bO4/iu/bbx4aucttp3tOS02JFSmKmXRl81AL7t+bZivarN4NBW3xFzsF7JiUe1zuUcUxFRAqhFNeTH4qmJl1OKo5JzQVDx1SmTEZSMnWO6O4h5XJ95ifiuVWdaLpa6OVNfhNQFW1amu77E1clz/muVp7deNmB/WxFzlnmI0V8Wvhe3bPdrUXxC9SY8U1AJDlUEqWUXteK3FPmuuGpMqbIyFFymDZzGubTN8Nt90+UdQcXa1rOdFBN8PhMM9GUfKZujX+Q6ApEoHdAKTwiUpD4/mupAD9MeuqAE7UEFTJl7eEx+/hIOn616Q/QHFkcWTcajWWDaFRrXQiJRdUpEs1eXQ+YF+uFs3dgsDsGs80Imj945xnsnAOSaSQuiFaTI7FD2dGMNrHuXELIdCmXMBqQY0a8C+lnQ2wP0GP97PwavvN8HJdudaRqhB5PUVtcktsrajgo9COkAJO7/pH6jebPv2W/eWPezutkqfjf9QqUqXXftSPRkkk9Uj/oDvXxCOL0jze0gz02XmqzcP/LNfhhennuPQ8/Pff83QBzQLyIwrYNyJx3cHhvvX3H8+8/ll4suHL3lzmbjMwlkdPiYObiQfA3BEcMzZMmYH39N3nimZ+tg5j+86xAcG5zgd4XScmOJM1kzME1kTx37gcBgMgGQzmM1ZTTtdQEPwFpxOFbJmgpOymNZs3iWBYWYJZz/HmTw5wjAQtG4MM95ZjrNMJqdoRv+LPZ2n85BCtkiyTghO6RwEyUUyWCXjBXSohU9oJS/L92bTo8jm+JoksI5lS3qrnVJbnpMSrAS2bsY2wKEBGU2NVGC9rxNa27qnpCYrV75ubOWhurvt+p5lQ1m/L8/ctbPeo+3jqgS+md/N9av95ceV7zRAQda+Lrzcvut+0FcGv1LeukibtMEqNGCzEtGGRKQlMXNrE2d4RKt4tkptKlBccEBagEl1Hc45F4Bin0twKLEw2Ku3R/m32r1o2cO1diaNFGQxnF2AiDTfrw2n1u+6MOdbJNSCvpVgq8Hi+rLaXN/czErJ7WcBUNroQaUyujpesiwgIsms/qQqMvyy8IBfgBIo67pnDKwirkX9d71RJzlnKplSy2Uci2GgLf6h6KUtbD08jBFJELxCEPquTlAhx5Hp/A3d468xhB7xnixCkgGKO/JVYsMl0B+LVG4FL4pIIIT+5p5uUXSZUp+AYyYTC2aOCd4/nHnzjefQHeiZufMzzo1cVEjOMec1Q3AL6DZM6cnycTvNW1dVCcRNF8kKOGjAkq7jvOx3pYIVlrFV9lTZ1lqBbLvDafnF2qL1s8bnYBG9182N/bT7svO4cCQcX5LHb8iXREqJx3Pm176C/8//9evcnzqChy9e3+FdwGsCPMHbBsOHQHe64y7PfD5d+OLdyE/ffsPbcUZzx5wUyRk/TtTop/McMUfDQOgs8P5lSswTzHrG+Y5ER/DC8dARHyPny8ibd46hD3jnzGsmQ1IL1DbPkeAduBpAzS8MN2mmc94iJ1eTtxJbJGeFAKHzpGxRaB/HiS4EAzUF9HjniqQ5E+cR7zu893gn4D1dSHTBUgs4KcrfnIvBcmLZwBQAoptAbJU31uBrdUNg17Y2bLWODeEsa8pKQ/v1ZTm3+Sxllwhq3Rbq5vcenKwr/o7GF9Bzfb/S1r8eb6WHT9qRLD+3tiS6u+eKp2/OrU9+3mD448t3G6DA02oamgW1+az3bOtQbGder5NVgtCO+u65Uj6dM/1zRhF1OByabZeuYhNbszRrc0Go1Zi22HzUHD9SdtblJTaNWIy9kGUSOle8eUpcFIsQu77nlVFwAQjVGBDNZW4Uxry3QdF1AbDDNRNoAzRYPK/Xm3SdiHU86jutY1HqWOxKCrJbwKCjleKoUvqjeBLUf4Vi0NpKJNpGt7YsO5uV5to6pgC+2J+Ml2jBpACXDCCWsA+cZ5M9OM2EydH5DnXRurUE7UrTO+L8ntDfAwdqID+LheHQpedlacNTRTEV4C0hqXeCV6XvO+Y5LuOmZbGIUem6A0nFkhjGd7zqz7zoE+8TvEvmoaQVqNsAPdOan71s+N2O6a57iRt2JpvhW5n4ckEFz3s0ZH6sdX3d0G8FOMu50qr1WKH6RgpTr13VQsY3VAV8X6Qor4hxJqYLc1LeP8789Mv3/JN/9hOCB03f4+X9QD/05NyhfU2YByF48mHg7v6OL16/5PMvzzxcZiYpGxbXkTQxz4mUE3OcLOjwMOCTSRvfZeWbxwsqBgZEehKeu5MFjXs8X3j3buTQP+JdYJojMSpJldklJGdydnhvtLoEN4OiqsbikTghOId3stjMCYoPHrRjPk/Ml5Gp73B9h1OzmTMPa0/KphbKWYGeqnL23tP1HaFLeG9jKljyTRHFqeLMUtYi0xYpoIiAq8EoiwSlqnicK7ikNZJ9llILqenud/le59rCAwuQUD5Yc633tnSjguAtr71Wpdj1K75ZfP9u3vOh76vkhI+8Z93EPGeQ+6nlOw5QbGfd8JLluOV5eII0boKOFsyURaNct3ZylUashOKcBS+iSk+ceZ04p6hT1FmcArxacCc1CYAW+5FcB7dhqlqMZ0XMxdUMYFkmE8Bq2GqTzTm/ABW3ZOWS3cK/vquSl8VBcxGdNzEebnUZWgBhcV9c+iVvQ/8vwOfJUo0K23aVSS6wiCOlqm8aYEPdpcp6TjJO/XL9siy3K1lZeG+iznZ4ybgQUDH3Sk0RyHTe0YeAVxjPEwET/89qvZEVxinRl2BTTiBLZrqcOT+8h8MFf1yfW804bQHcLHfP9Jvp6tNir1QbXfvH+i9rzW9igC0XI+VxtGBtd0fPZY68f/8G/9Wv0L2+K8H6jngJxuhVDLcuIPNnYzRPl0Z0vIxDAdD19Rr41pbFWVsaRtyI/1bAcu0hsZnSm9aUT11/bdkvtJueFezIOgwlc7rZotwThs/Q6UKKkRRnLrPy9buJ8OO3DJ1j8IL/+ddojkQfiHNn+WYEnM4I0Pc9L+4Gvv9q4HHMfHmOzNkj3YCEzJxnC6KWnIECZ1KK4BOK4+GSmSJ4SfRd5ng8cH8InA4n3njl8XxmniPzHC0hoQgpZeYYocRoSjkZCPHFHZiaKTmTvSeIlKiwtRPNfdjlYC73XUeKiXEaS16dsIAE5xzZGc0lTUhOxkPVJKHOO0LncT5hHoOZ4DydWuZoU6DTABG3+aRsJBdHgDpm8tSMu0EgWlXwW551+17dTM2PKS2YqXNuMYi9qdJp27k9t7e5+pCh+v643rjvuftvqZxWvvHtecd3GqCsjL2wp6bDWs+cDUOBuilbd2yNPcYa2EwWcLKeb4MN1dV0BSlFcEFGcb4afSlL5mQxSUoVMS7tTkV6gtFh1oxzpr5Y9LoixTOHZhL6BZys9iZVurFOxKXFWneUhqi0JkGri7fk27Qka3+3E7ui+oUQy+KgtY3b25fFRjbELFSbByhgyRcJkWphRnVnW0Z8Y6ehSLH/sX5yLDYNLWAt4GQBKU3/ryDGjAGHw4nh9AonI1kuSEocD4OJpVMmOqzPxIxSRywM/hgTclHuxeFFCd4h0nE43HF39woXDkQJ1AikVe20EQbUpixqFt30pb1UWhfuLe5EvEULra7wKRk4CSLEDJfLhW/eZuZ5At9xeHUhjY+MYSbK0UZSMymt4/MxQpRl7u3avy/LXOQZUqted8v71jPbYzaClSqa9rIDJDeeIsvGY325alS/Skha4LjWbbhwy1MWEUpRPakoSR3On/CHV3TpkTSfyWkmKVzmzJuHma++fuCbz9/zvZcHBi9kScRpwgdvCfJIuGwSuaEPfO/VgfMYOc8zX10gywEcpJjKwhIY5wnNifvebFG8D2SEh7NR3f0xczwkTj30Q8+hE778xpZ5zTXYoEVxJRqR55xwHg5Dh7gmY7cYOM9J0WARa723jULOyjSbW3IIgS4ERBJxjlxkpO8xIF03fsUQ1qR9sYCJNfHoorIBvBd8Fgskh8kiY27WBGmurxu5zQavPPO5DcHC26RZZ/fSM202Rc2ZfbUtz2vA73r5nl63EpU9AHjKc6c1epXm9/78R/3+BFADe++cCtK27/mp5TsNUJ4vzzHWSnbNIirNuXazJS3hNWPW7JiqR4yWWCHVG2KpIxWwkM3SXtVUP5IjOQlJMXWPONt9Fe8fUkQ1FOTvDFhoG4CtenhsJ99mduwWN2v/ymhFdfWKydCaye66c2XTzhX6W2bPutfUAhT2zxaWhWfbtxWcSXk3TDwMVIO2tgp7XKZKQiwrcUbxFjtlY/hjd9W9iH2RsrgUBrZcW1RJKN1wx+nl57/psXIAAItrSURBVLj0QNATObxlGAJC4nJ5T3/oCM5zfryUaLP21DlDHjNeJlO3dMHE/MMLJNyRpLeAXuIK+/ErSL56y/qyi7yo9JmS43zTEF4B8Y6u6zifz8wpkcqbJVWLkVPqEudJqpwvFw73Cd/3SJQlovFG+vSRZeG7HwNonjjebCE2V7XMugIT21CwYfCyUwctT7vik8qKLbataTHHVRsKcK4XblRh5THSxJLJztyO6e6RcAD3SMZy2cwRxikTZ1vga4qLOSVc8PTBoy7jiwo2eMf9seOzu8BX7zNfj8p5nHEEXHFXnlPiPM7MPhB8oPcdh8PA3fHMNJnks+uKJMUpLwbHqT/iUR7OF4IDdRY5O+VMiaaACAxSUmEgZviPmudQyngRfMzETFHxwDQnJJqkcRig63v6riuSmYyq2c6EkqTQOUsmaF6BRT0ittFLKRsIwviGefUIQQ2cJBVCGfklWopUw/tt9NjKuhfWLrdhil592y7Ai2uwVGLZLcib+7eAYeVlN0BG5cFL1ddA4TlwslD4DjBswcT+veRJoffTEpOn3kGbv5+t/BYGKNdla4PS7syurtyoh1ovg9UYjuWfupOq91h4bmNUzpdJkQR1iZwFskclIdn0o4uWO8pCOJqzAZcmZ4srbnmLUWhpyCoZaSZLw2WvyWSVylxPwjUo4PrOuz7K6+q4KGqaRaIlzcUgbYMZyrPrhUtyQqWqFxYws3l0M1EWvbGSa4SKEgvmam0tfVhxjS6CouqxUqRTGOg53r3k/tX3iOdAh+UZSfMjcZqYYqLvHF0X0EMgpcQcFUlmkyLAOEVCcBxfvODw4nO64+eovyfLQKZKUMoS26gJmg7afF2ZGeRkO+xCEbTql4zyOM3InEz0TsExDmIGp8qcM+OcOCSFrEzTSH58tIUzhEJWW1D+G1k23jw3gcFTOy4bmwWIrEdZvPTYZhLa3LufBbp+SHtZOVhYdnP7emSjwpTVtm3JoKvW1zWis7oeCSdcd8L5d+Q0UaWA5nNTwqmp0WacZzTOuEOP7yzZnorDhY5+CNwfPKcBvFPeni/k6AkuI5qY58y7SyxgBV4eLRbS/TGAZlIWOi8MndCROToI/UDAEUTp+kB2pmJSzcUbx2KteG/eOS5li/KaM0JCfbGdcx4/WWbl3tsmxrI8ZxQxV+Y+AI45JaYYcTEaQHGuSO0qAFp5Ws55iSZrLEEWVVNIjrn0ncWDkWUsqvqIXXiFbWqQdq5V2lrV4isfo4x/mW8Lr72mnWtC+/iF2uwDq8fNFnRsvi+AZ1/Basi9HtoChj3guCVJfLaNT0hT2rf4jSq/pQDKYgj7Ad66iGY/kgdvA7lVG5TdcynE5YztLC6sVa3jBE0lgFpWC7BWxKlUolSKO7J59phtRybLluAEAaeLJEFLKnXnxMBD296dmseOQ91B3jIyNiO1DxPZKi61NtUAb8rKAG4Z6u69i1BWFxRVct57WG3QRpnEjRGxUxaPHgpwKVIYA3CyLLwWuqZOSJNaCWI5iQq4GY53nF68ZnaKxDMpXXBE5mkkZWEcZ8TB8dAR1DM+zkhajXbBpFKuO3C4/4z+9AV0L0yF4twSEaC2XzekuGUW26KMlzPz5dwoxVZYmMvtqrlI8ax7UonG6RTGCJcI3Xni3dt3JHfg/j5ahlqNSFcy32qlgxXQb22xfvbyHIXZerACj/W4bFx8152mlpH/ENMsbd9JP64MX29ds1TTSF/Kdy0Lp+HtKmDPZm0lHud7xA8411sUVo+5znaC9xnVSEoRxObylCIi4L0ZkYoPdMNAHDv6IPRe6LxDc+LxPKJpwpFIWXl/jlymxOMlMd53HDvLZj10jsts9hsOR+dhqJ5nSZgOHb7vyNLRh4ATIZJN+gbEEnBNgJgic5wBIYdQ5rTxjThHJu84Dh1D1xtfmjPTNOF9sZPzjpQyMUVy7nHB5k7OkFJe+UIBFM55MsmCOToxj6FsNKKFX7lmHi0GoouKZ/tXxScrODU6kw0FtJIV2xiKNlKT9lxhNlunnXr9x5RVVV63B9cSj5U+YcVIy7NugKGNca1cg4qt1OVph5MnW/3U9Tf2BN+mfOcBylbS0Uo+dNtBN3jqKsresq92g7T2dN3119X0WsZelmJL/FXFisXtLYsju4RLycBFzpatWIyt1dDPTrOFHI+25FiOiox5Cdley/bfvq6xZcJ4Y4fV1bj162+A2zr16iZ2RcNb/WMBG5W4m9D89qKNi57YrmNRC0gCrXr+6hF1bROzmXglJoqIlCSHFHG91M1rGYNrxE+RjJjdTgEAZSHR8g5VZLzcUPav1XZHs4WmFEyU3h9eQI5I9HjJ5NFzyBYVExTfDxAC3jtOPjG7kXgerX+D53D3ksPpHh+64p4ZcHiyVkYuu51OS4h5d9T+zapMlzNzHFlslpp+sDcCb8IGBm+2AnPOZtbsIEVK7iWl63uGQ09warlgusGikaoRykrvHxdYaWXute/Lt0JDtgGuUsJKhXmRSm6LXn1KkTYgdekoDF3WnpCGVtaq6pzVMt+2vKK1U2vr09oHpQ7jDboAv0JBJdjg+g7qMILEl/ocKj2EHucFMvRBOA6BF8eOQ+dKvSXsQJqJ48iIEpzgBjN4db4j9EdcP3DoLtyFxNcivBkz0xQhz+SUebxEphQ5T5HLHHl5dBy8I6aSW8qDEkGi0ZEo4jN97/HBMxc1Dc4jCWrmZQO/Fgxuiso8VS9ELGM3oDkzuoQXGGPm7gjHoUNdYpohdIm+d3hMhRSjEJMBOe99maeeeV7nrRNzORaZbRzKxsosuaqthjZBH80xYQNGluPViL3yxsrPVtXwrYW+0tFCXtoA2RoCgevtxXPbjQp6lno3gKSNvVLrXrck+/kizfNvl20rVh7a3rXylErzLRhimbss7btdGmeFTUPL708ALt9pgLJYZG9UN/sF7BoxXhvN7ndP+117vZfN8zZtKf/KMga2CFQnGidi3jviiyFaEzdEbRegOeJywkkye5Rim64pk9Vtg55RPVh82cWpRZR1Sk0l7pxQ44xQdyQ3yi2QUt0ETUpT2qFVGSXLuy42OtKkL29UONXaf5VayeaZm1IDKUgdW2WJbttM/72BWF2PavwR3cyq1Vh5va9MRHGgvrRrTeTnnKc7nNA8QSxu4kWykJ2pdZx3RBQnDj84DvSMCVKcidnch4PvisHfRK8zTjqEkjF42Zk3TS2/F1ps1Aq1dH1Pdzwwvqs3bRmAQzkGT0y20+27jilFxpTMBjoa2EwZLjEij2fc/ZmTGM2mXF3ObylL6hhcA6tlgd4FyWuE5OVAA6hat91mdyfbO1jofdcbixSlSjYNVTX3NABPVrmZsp3HW35Q58Ja/1rbahvQSiYr2N92VWX+FkEVFxDXgXd0KtwdA6/uB17eDfTBbDrmeSqLbYIcSROMApIDnReCZMxmo+PQO069BS57HGfO44STRE6ZeU5MKZGwc5dReH3ydM6RcnFsVzPGT9mkLkiJyiomCRWB4L3xncKTzEVZSEntGXNCRHFRmOIMGrDAg2ZDN1a1jCjHzjOJ0s3RwI9UWhNTm+ZsIfVLnJWclTGOpJjxvkPEF++hGofG4qL4Ynvilt3XuumoAd+WjRRtAsE6hh8wlF1IcKWnOtYrnFk98WTH3/a/b1S8qVSurm0B+tqUWy1+Ujpyc128rn8BH5XPbq6T6+t2z7taf/fPu+JXHy7faYDyceU2UAGeYFBP17G9rmGfNweqME2RxeodigamxEQXcUgugbk0Q+7JKSM+4XLN01NC3+eM87a4UHW+YIBEDfggilNBxNz3TLWUi2TAjHSrSmnfG3uQsgEoRYJiIbPXQF61H9xiiJaXBX4bNn8dgesJuGtDBT1Sso2yjsvWEHi1owHWaLaymxDL7v2GNIhiZCsWUptski6c0A8DonekyZEq7ztYqnuXYtnFGPhxznPwB6J6pssZTeeSd8kb81cT9qvkArq2bawGfUv/r4RkPbbwGUc3nLh/+X3e/dr/F3RuqW5ZeJ1z5Gg5nMZ5QhV6cThVLN5Wje8yo25C3j/Ciwfy6QUqTRC4ho5but4O3zVguB7fW3Pwmlmt82Y9V4GpNN5OVcKxQChZv2xhQ8FLkgtTl8XmZ31eA54bALwxOF/RSkPETWO0aURd/HTTc+ahEnp8GOj9xP3J8/q+4+4geInEaWSWTN95vJgUbJ7OkGZ09qTg6L2AJpwIfd8x9EoIEVDGMaJY/q84J+aYSZhHjEZlCEp36ptQ9Mo0Zy5zJDMRFTQpIShdEIa+Y+gTSkKyhZvvQkCcI8eZGC3QpEiR7MUS+0csmGRMMzKD5mwhEIq7u7gZLfYjWa3vY0zEaC76zjlCsOPjCPM8k5Kpw8w12eFdJnjBZ8Wr4BUL4NYsyCol/5irUpQ1SNtWzdPwqZY6dQUEe8r9f2OpoOWm0W1z7HkVzkcAtW9ddNm8fMpjvtMAJWPCR/ZSjaI22exEb4HHD5St+ghssbzeLd0i7nrcvHvs+YuFgkVyKsgeVHuLe+ITzne4FFGXkNzYtmg22xXxxTagSDDUU7MRi3O243EsC6Hp7J3FYxEtIKL1XtmCk7W/tot69e6wxIZFklLAh+IRSuyXJUjSmkqdsvNqO+7WzqLtN5FqKOcWsbwxnmKZb3es91LXkZ3osZm4i7qilRSJLvFoXA3+pg7fdageSt8WZYw4vHRIKjYemshxNo8dlDvp6LoDOR44vfyMz77/A1589jnueECdLEaT9V2o0rxCrYt0b/duC0BxQtff8frzf4Gf/ugfkcY3tTfLXy6B+ixBmjjbWU7RxmwQMXfpzpPzxOP5Av7AIU6keIE0gQ8sQa52QHwFSrfp/XZ5atJtaWFdEDZyiXUeF++cGqjcpo698/b6LfhbjNqbft2rlCrgaZDhsotc3ncnzVrxSvO8DXApd2sF7x2uOyLdkZAvDAPcHTynwREkm/txAtd5fHCkIIzniXEayZOgXSAHhxNFNeGdmrFr33E83fHlmwfevTuDOlLMpJhRB11wZAfTnJljWrrebD2UOSZSHsnqCQ76zqLCHvpE8BPeZZwLhGCq6zovk9pfKN6LKVloBCWgKDFmkpqLMYUnnIbSNc4x9I6skHIizMkCtHXBVGDFazGEADIRczR3Z5SuC/QxEdWCJrqUEOxvFRgX2hXL6yWVchpwIrIe+61QWri/3T+slPzkTGwAtjb3WPmN6J/tpuNTyncaoCANONkT2pO7uOuyV/sshm+wMLy2epGNI8umnuZXc30hD3ElyWBx53RSPH2UnDsLQuQTzgc0RzR7wPL1WJV5zRpc3PxMjVQmo1qwNntoMdTEtZs7U1com1172/anEPiywBeQolWyIcUwTKoOuJgGLowAJCt5l+viOenVFrTkZrFcu7YNxKeqhalt67VLtVzfkES7ENUTmpeEY4JFr8QH6AZUpBi2Wo4VVIvKLpLSjJSImc73dN1AHHsul5mvv3nLcP8Fp3uHhg6SuzlNDUC1fdEstU08HgDXHfn8B7+T4/1nPMxvi4GgvWsGppTxc7Ske8lsmjIwl366zDOHKXE4CKfDgc7BdH6Lxkc8cxk767fV4LxF9+0qzLavd2N6u9xmVK3ev32SW2jX6MxtWOfNnmwEKisILA1cYUxNhtneW/NASW3lNVuv47JIuhrEsrly4SVlProArkf9gWmGcZyBjqHzhOAgJ9Is5D7bMQHJkWkcUe+QFNDgCV5MFSyKd0rwnr4bUA1czmagWjIdgEDqlM4JKSvTPDOIluR/Fjtlmia6PiASCM68j5wrrsJCkX5okZJ6kuaSnwcDVM7Ae0yK99YPrgDcnGDMCR4umOHLAe89U1SzFxNPVot5EpNFwkVsQ2eJCB1d3zGOMzElizvkPN4pXiCISU7qVtUV+6DVFqWm/ljV3K2Bfju2t2wZP9Vg9GcpiwRPr+fPRpLzlBqnXLm3RFlgv+bVOH8DQLbP2N69i/v1iWV9j1VgoEpja/Ph8t0GKKVcqWYW3ZfuzuvmozL+p1U8K/DZSxye0y0aIG12yFolARXVOHDFAyeLuef5AKEvaccjWaMtfNGyHdN41tSEaZozJr724HTND6Ja7DlK+H1Zd50l5O3Ve9TfK1CpkoaiaioqHlQX7yJz5XPkYmtTreoRKQJ4G4OaWXkBlM3OfDMRnwAwm34vwyvtvZvFQdbJzoYK1kGXdTyrVc06/wysiFjQqSB92QEKXgw4GhMWapJHUfuL3UjsLsxAjGcu5wvnxwuHV2YE7RaXcmHLdaSMXdvOLRNZ1Fw+cHzxOa8//wUevv5lROIGi1s8lowrhpqLB0Y5N87JFpeo6DzTHU+cH9/w9stf5fXx+zAcIYRiBr5p5CLxuwL7lWYKrV+z1naMNz/XVss6rvURxQGcNbN3ZbfCGqxvV1VNcFgBTzNPXZWiVP5Qialt777J7cZF67SuX2SZS02Ww42hrs09U3uo65m14+Ex0sV3/NxLx5zvbcHXTI7mGRNKcB3NiTTPkC3wn0PxEnDiLVcXZjTqXMB3R3IOxGkmqZAodiZZGTolnzwOGAahl0TnKHYvM95F+r6z5KdpNvqsrq5FmqGYu29MiZhSsV8BX8Lg42RR/XpvdiQhG9UkFc4XkzR2nScEj5NE6KrKGbQEZ7PglBQ+mBeblDjb83IJrV/HxIzCLdS9r2rUshmUsiGUynMqQKlUJiz0sZLylh/dAt0fAi/ruZvE/uQ90nzfnOOazK9LS7g32tc05apFyxq30nbto9vvD2v+uuv2XqtOaWID7aScHyi/JQDKrbLuhW94SjxBNE8bzbWfu+c8Qax1rRFtFpc6okIDTooKyDnEe0LoyLm3TMc5ozmanYqsqolcsgGLE7Sqd9STnZrlfVbMq8YMaJ3DAI6TJiWNW965vsNGipK3RrIrQMklyEsJJlL8qRf3uyo/FrVnSCHo8mBd8gzdNkRu+7X25IpD9q6eq2pAl36u42RL7LrmV4lEE7V2fdoyYCZdKszPB3AOXxULziM5l3eq6RCy2eukCfHBVHpxJAyBF6++4HT3Od6fyBKwXaQzcLO0C2MINZsubELALF4nS284usMdX3zvX+BX/s/OwGsjfTCAogxdh/eO8TKWxARWUoY5KQexOBfeZY6dIDqSxzOEGVxnibE3IvBqbLgdp8rQlnFYgLlbwMDVjnAz7tWwuaok7ZGFOktPrTuwKjXZzCVoAEub2mHhoDeZ5lN2Z21b6mZjkWxp/d3S2ip1sV+53FvoqYCULB0zHQ+jkh4e+fnPjzxcMveDt11lypz/f+39e8ytV3Efjn9mrfU8e7/vOfYxhtjGgIlD+Imk0JbihAKRqipWSULUJI1SEbkVTStQEmggVLmQlkal5dLLHwlRBSJSaauSokZt0iQK9IegQUUi5tKShpAA/UIFItgEjH18zvvu/Txrrfn+MTPr8uz9Hh/n22Ifs5e9z7v3c12XWTOfNTNrZjNJ8D/zXTK/r+zKuy2rMClwdn7EsDqPzAFznjGBEbUupsBYbxjXrYHV4HBucHAW1iDNiPMGYwgI4yjxT3Q8pA4ygTNLsLQYk+y60ekvZhrR5KaYEWPEsBoxeK/1NQ0GEGPCdopYDeLAT84hOMlCzsxIMZU+TRoNmUh296So8VDE1qr8qOHZdSREo+xcMRWJJqXJx9MEgGRcGXxcDUg5SwYUemmuOev5ohW/OjDTv+Ps5y21Kwau99G88MbqFtDOSTnVfpfFwvKatvTHm4WF/r7a8hgFKKT/iwS98pao3bI7MLu47yFVgC1x6r8SKZEBTgXNA5CJlB2cd+AsIEW0JklW7DnKal1XDtBVajHfGFcn9fkoL7c4KeZbYSDBtAS1jTsARTUnZRdMriYe2Wmg6MuWvW3TmXVBaVvl2r5r47Sc0XWL8z39G7hgdOpQY+ZkIm13BVHXNb4CgPJU24VSx0te7OCC+b4YtDA/GBXGSEizh2cRTsB1WI0rXHj8LRiPn4CEc0g8IjnJZuwauujZq0HqXug3SxXAOziscN31N2IYjrDdbNFOeB11bOYZtDApeRDAhGnKSEcOq/UKOc+IE3BdcAiOELOGO4cDnFH9Agx0Y2UMy0jB6FDHoGXkjfauHZgy31qQUrQf1dBS9ls0NFdghCGEVj2Ktv8qvcgjrsxYTTVd20ldO/cVxcFSp7JCkfczWMw8foWZPbaXI+5/cMLFkwmPO/bwlJBTRIoROc4YXZ2PmXVNoDvNzPHaOeEZLgzw4xGyI0QCJgbm2jPwkXE6SXwhRxnBZwmklh1iYqQ0IacJjgbVDIrja2ZG1Ai3zlveHVbliu74AYkjPxEiErbbGaN3mqVYZsugviWeSAIbzqIlmhjwIwHwZU7IGOhiSMfDkTjPIrXgVMBSSoTMGjeKhFc7Is1obOBR04AUk4VqVVA3PNjiZp92/GpBym7ZbyrqzM/Nc6iQ8i6NEnZpdsecvXeBXeuynMBLcFc0KRa9elGPvm/ozPbt1onKxCEqr7mqck0DFFUe9KtRO4GGbe9Bk2Cu2lluOk2ZX2Fz3eqwkWBnMKnynsJDuXu+DJBDzppmPIupBBY93gHOZ/gckcMgeThyKteRTiIGkLh3ItTlv7wzq9mFUcAEl3cZ+q3iHgp+GMoNmbXuWYWu7s0vQlP6RnIBUekrIl0Tl0bbGxoMzSoAW0plVyaFHSV7RwPmCvO3bdraeTWhIoOp5qppX2G+LNynXa6SpVZG/zcPf5b8IpYlujxL70qzgMkwwPGAQOdw/vrH4dzjbgGN1yPRCkmCTxQfiuqGSfWd2l+2z8pMLMxqMNN6OhcwnDuPMK4wbc62J+e83OSr/koa52Q8WuHGx1/ApdMZOZ0ix8tw68cBlEGuYV4l0m/LlCuILPhJx7nOvgo6yoCakOBcQab1ApHsxmha5Mhp12Sdr+1k0lpZ5Nu9jM/GUpiF5eB6KHBCRLXNNh20faTzkFST0uycLhqlZvGodXUAeZAbkBFwuk34ysXL+OMvX8TKZ1xYA45n5BQxbwPOrQe9jcTniwMyMsASpiAliYo0uAFwK9DAiH7EKU4g+3qqN0LKkGzqGRA/WcLgtUogpAykHJHmGdEP2OaEkyljMyecblPZwQPSnDcsPMw5UVTAyYIkccY0R0xxxDh6MBIyR3gXsApj2Z1kmbVBEtl4DbmfDfCUmEs67w1flP4k3RCQsU0JUZYXAk40N1lW3uF0nsJxkZNlurNraOZsqXm2JqGnIwfTgTZVZahJm7vnoTvSyqp6oGqMzwYipR7QUBZFHuo7C48v6Ke+cw/YsXpUk3MVkmVml0UG9c/h3RaVI9zwCwuyeRXl2gYoVzgnwk6/tz/0wI4drAMpUN7aIFIU97grvrkFNOXd3XlBn7K7R3wFCiEzI3vJzOvzgBw0mBsnYejZqT9IKg9mm3X6ssyowswEckFcDCB3Vi8jQsEjMsFYfU2qpgUNOFFGT9CU5SIcDBkX1Xi3ugBQXFCdpkNX8az3WzsMRAgo6bcF7gDRZjQYKGYSlYtFoNu4SHt57/DRziSz0W7qWWKyNCsBlp1VEi00IKcgZh/yIB9APqgQruCun95OzXR2pLIT2Kod5oOh/UiMMAzww9DcUu9VfVnpn/Zs5owhDJg2EV/96kWsj1ZYrc8hHB9jHAOSJ2RnanlXbMcEalwuqDy7V/u2L1yAk2bAbIxIzQcFtpABODPpmMmHUX2nXAUmBdjUh+/Y75VAZKhI7z0bnHSFqLanHqz92dLYPpoq3WCVcAACMhM2c8RXHriMz93jEDCBH7/GuYGQ5i3ivIXDEVajmEKyjkHO5j8UxV9DtQsZHhxGZCc7YwjAoFXy2uc5ZcTkMEcJ1sdenFqH4BHgMQRfFj/bOePBky0unU6Y5oRxqElJTZ9F5DEMTkP6SO6crGERNtMEciuJsRInzMFjPY4YnARzzFnio+iyR7U1Zo5V3ugYyBaJFxpyIJV3lcVlFmAkLqDKuzw05L1OUmfPbXmBmeWqrlVogAvdyNhyQ9ct+OAyqbiZs1SWHvZd5z7aqWEyghr5UPkS84IfLYDEPnDt7AUNKe7XCDfPae7vU25wQXLctK/ljO20qBivfWLu5yI3vbc3X9H+ck0DlD91WQgj4zGtsDPmuldttlf9e7a666wqyPWuDH+Gh2cGuwgOAT4ncBgROCOBwEkiReYsa6Sq6iZdDTiDIBLhklVZgqp1kXf3UQqZjYnaVmIx7chqM9eJ2vSdrU7I1ai1NXqtrTKXwtiYdhFJCjza+7EDTCRPTjv5W8KnMm7Gk/5vlcoYtHEm7CgDTgAKvJjnMgMpJQS2vkyFyRWwS2IPb80otorUxgHlOhPUMrbDMGAYxobB1d42GmjZSGXCwBQT1qsBp5sJp5sZiWacP+8xjGu4YYXsA9h5cFnpUNfsjv6pMk2rQWVqjX7Iplx/VARJ2z51qHYNG5SzvS/Z7jDvN+O2Y7Y025S+KUxfx8a0eahAW7QoFZixsQEAHavfq5mRq5jFudV5yce02Sbcf3GD+9YON573OB4GcBY/jnkIGLw4VpNXoR4jEmXMswCUzA6ZqDqAQgCJAzAoGDNwM0fGZmZMkbCdGedGARzBDXBuwDAEBOUfMUuMlGmS0PYwXxAnif4AaLwSCcPPmZCi7BybU8bJdoLzDsSSFPB0s8V6vcYqaD4gy7adLXOxbIvGSniAIwI8wzR9gDjeEgGZE5L6okjIIlKa0UUPSzwUNpcTGH6nQmtQ3luFJumYVsCwZ73SOD/3x89m+Uvut1uq7KiuCFXG1PPWknJuocUh3kd6vKhbww/2gRV7V3uu+Zxl0tov85Zg3/7y1QamBnCNAxQTqlLaDuk7Z98qznwh+qGo/1ZC7QmhEMtiUK7GaYpbqm5Xyo7g1QTAnuF4lO+BC/HIbhkPoigRaXUlUVvcCDmI+cexghiduFzaUR1LrV7FvMOMnTD3VhxEoDbJt5xFbKQWqNR62GSqgAMw5z4AkgtnEZrfqWbGdhCQ010QDFRX0gZRXkU520mznidaUsOVivS39JCYf4g9nB/ALInUpmkLhAnsRMASRIMhKxSNcqlgrVAGq0OfZWZWhl3T0shurdW4xnp9HkTDHrrqaRlorO8kocWd93AEXL58ikwj1roq55RktxlVpmW7X/p1VM/8pQ/N/o9KT4sOJV3qOTWNKJzVd8luDAFC1d+Eytv2lXzF852avFPxaLX0uMFGA1hUwAhVbSDbylx2pjFR97ROJd72Eun1XmJ7hGEE+YA5MU62GaeTAFoXPBAdkoLblAKG4DV0T8acIsCkW3JVW6pBzxzNGIPDKsgGwcDi2DpDklhOEdhMjM1EmAah2SEMWA1rhDBKFFcibNlhThlzIph4mOYtMmeEQXzaHBFckDkb1BnV0lSk7YR5TohzUodbh2lK2Gwj1mHAIB7Aom1R/iRtzbplXoZJUgK4csx7j3EcsJ0SLFeZRK0V4BGc15QiUJDJyj902DVPkNEKgVAjMBg4dYVPFg11AxaKADe6uiK/b3+fzaR6vtPWpj9fuDujxoWy+oGxXyuhSzpF1L204/oSqlz17LrZpft9anbbvwQounGC9/Pfs8o1DVAA6ICdyZ7OvsmMmsWBtlmBNtsH9zs4PQzJeNb7ywq0mhIksJY3ya7qWfHIF0HhJZ9PFlt1tiize8SpaUWy7joxzYOsBrlMuuoYi/IcKtFjgZJaj4TAZdueV8c1ibvivOX/UXHTrJYNhnW+JKRrvXKs1Zi4Akycfi9chrUdOfeqx26MzvY+r31zBfhB1HVnYVAiQVH/NXantEQeoAA4ye6a2CHGhCHP2k4x9TjOYtJRhiE7GEyDoHTHWVd8FmUYMO2FrKAygg943ONuwlf+5I8lyVyJ8ivO1dLODPNFGLxEAE0ar2YbE4JnnJxO8KsI772YG521GeK8DaDknylAghphXhl6s+AtwKUwwgJaqxBqmZVB1jq/Gl8nGYii0ahUxaiZZ63sLs+4eX891gsXY965jDmVYWc9Jm1VYNqRUAVw+2I8sC5omB1CkG22DMIcGSlKrpkQAsZhQOaMSIDzARbHwwcnoQdywpwyogZYy+wkCWBwOPKS8yauR0EjUevFjATCzMA2kpzSOCnOEcZxxHq1lsiuAGIiTGmL7ZzFdOkkL9g0J4ASHAXL1CDj5hy8l3Y59ambpogpJQFjYcQ8z9hsJmxXA0IYNZKxaIKdk8VYjAnzHLFajSWCNJhBGtfFAretViOmOIEoA5zASeYLs/jcBUeIjUbJeJLRXAtYbHFgdFXA6kJDsdRWXJ3z7C4dFh2jyiybF1yO7cqUWnu7vpc8hSNR5bal3uUK07x0RLlXhD0cK8Detumzi0OELVZMzj3MZ1/zAGUvbnwohNbo79QSaCf2PnXXfCMMZ997luaes+vSCj2qmgmQ+mIOepkQeiKnDCMByQOkjpkpiVBim6iQ3RfEuquFUZk214ljwKT5XmtmjrEGNqR+jpyonNWc4byT6JLOwkqrmOnysbjS52bWAEk+mgpoKjix4+Lsptc4U+GaQKy7juRTNT7lHXvH7ezSjVP7vVV5Ul1/Vc5BJUIsyIOdB3hABmNOEcM8IZCHYg3pV91NJayxapNEVS3BqsDWl6qpUo7mtE+dc7juwg247sKNiEnGn8zuq2BFhEBSQOOQphmDzxh9BAaHmGcgHGEYj7E+Oof10THyuEJyYoKwoFkGFkoALO0WBoszYmHsDeAtXdhz1NYHSJQlrX+N9G0FKUZ5DeNtOGtl+O34LoJLLRhxaz4rdzWRZYnQJJt0Sl9mAqjXMZbPxZlMH9pfuZt6BO8J4+ixHoOEeQfAzsGHAS6McGFUsG4aT8IcZ0xTwhSzPo8wBIfVIABnGD3AGTFlzdwNJDASi4Ns1NgkXDq96VsiZHaIWXbvpJyRU0ZKADxJlnEn9TCtJxQiOttibxqROQErQggDUkrYTBNONgGrwWM9BE27JXzUuYCUBXQxa5BEiKm5mN4YJV5UCAkhJHiXJNVH4hIbSuEjRBtnY2rzyHzHqoM+UaUzLmlAWiBR+6gsZffxFK7tAbiA/HK/0oYp4Hd8VSjDtluXOuvFVF+wn7i62lkxQN08q4i9K8mlRbOKBkf7A9xXQwnfQD2aHmwXewZO2r1UV1OueYDy/6lQVem2TNDKvpV4dS7aBSD7wMl+4dha6I2rVSeuDGheCQUXBIkA65wAFIuBkCIYs/i95iSZcsFi20XqVg8mwGFrX651aevf9o0z84KCBu+9rLR9gPNewIkXLUo187StBEq4LQM6ROpUWsGJvK6CEwMo5phnQtrGAQq+ioZIjzOnuoLnfjweqpx13XJ8YW0qag0DK1506xghiRohmYwJyFnAJNl42lbwEiOixoUxnxQyLQWjxtJhAY9gB0LC0bljHJ2/TkKYG71UPiSAVZ2sHQBeJTjH8DQDlBAI4mjrj5AxgEsGWGswl3Gr/xqzKT0BsKsQWJnYHmwg5/UJNc5Jw4BR303lvM0TDbxBLXtTEM0PPb5SN5tTAjpqjRRcARp9mTUkRRUY3MSpsXaWadROm2a6G/hnPUH6O6UEIuBoPeC6cyOOVx4+JaQ5Ao4QhhEhrBD8IKGLOIoPGssnZsJmyjiZZmxzQs4EkFefkoDsxAySm/rmLH4oKWk/q19XTDO2WwKPK7hhRGbCnFlASkyI04ycGT4MogVUmrcFBEA6ByWo2moYkIYB8zxjnmc4t0IIA2KMmKYZc0o4Xo3iUwIgpoTVagTgkKK8k0dvYUw08jbrxkLV3noBKj4wQpBt+0kXVSKQURc9jlQL2xzrEHGlameAnND/VTDhGh60w1u4EnxVuDYuAbRfnpTvyh1aGdNqPR4yVMZyDtACSJ2h7eluwO75TsNomMle2WqWednGtn9sbjuN63N18xW45gGKMZym5xadf1VIsQG53aMLgTaXUuOUiV3B9tDgpHlFO4BKjCacOWiqc8tBQoRECUQR5BxS8f0gxFifZ3ZdAV5tTBQufxnQwGrWfDO9SP+R2pSd8/AKEohElesMkHj5eB/U1FNXVD39EWSnSn2PfS9aFQBoMiGLTbsBKKjjmG115EgSKypGELMPlWb2SpDdcWjFUztu7Th217faE3uCTk6ro6yCADiJKeK9MPQY1blZtRykJpxqxpJ2ipnFlee2jaiwOAGQtgfvMa7XIFZnUy6jqSCiBtnjFFHXhwmUJ3CWLMcnW3GePEeyCoYTx+Vi6lHUw6AS44ZUyJNKBNNCZhhzanu3draB8gp5uNKffjcOT8a2RS1Y6LMW1zkuQmvQvbKpQmvrb7WhMg9rP7MCJfMzkefoitR4RXlx+/IlE6m0x8yq2ZRKBSKsVx7H6wFHK/EH4pzhw4AhiAO0HwaAk+wThuS3YiZMc8JmijidCFsAMzlEqPbOtBKqMXCwBRgKfwkhyLZhADFGEDsMQUACQ8LYSwwUSeLnHGEIg/jOsPqwabZ0IoltMk1TAS3DMCClKPFOQijHU86Yp4i0TghKIylJCIVxNYAImOYZ40wS/h+oIIihOxgBixAbvIT+dwldkDOD+bLIMr7WmpEB2xlm41sXSpV/9D5+KDRdaQBlfrT4QHhJQwR6M1GvIen5kgSWtPobZVUuXQNM7i0NmOkPX73JRgB0XViYI7iwo4d4PxaAzZYYewDL15EPirGT+uvhltJ52vlF7baDVvQbFwXgVXX0Pg1M9+QFSCGCbr+UvfwWnEhMCEn2+KcMUASRhoYGAZEkXLSq9GWVqMy6xDWpwcstLLW8UFfwCjI8aWIw5wSAeDPrqNnFBQUvoQjW4tAKS+DYCHOq8QaqD4rr+qZkd1aAVMw65At6L+PiBGgRMlwWdJYBONOmwIDKGRRB1VBAyvyqJWp3hbP82xftY+clrxJJBthMhE0GaI7gbOpyWTnLzgPZ2eOIxIbvPYYQNAdKZWJVLa0C3NIMMBBzxLg+lnRoRbNgwA+K39WZOhtwzXD27jTBkyRpO90mnN9uMI6TJhuU7NhsD2oBH9CsmIyNClN2zTbNcm3t9m48KpSqx6nQTbP4OEPjV27onrnYYL2Hpxp2qo+sRl7WujPQ7epgANn6lQAuOqD+7XKs9kFpHTMoJzgkcNqC8wyfxbQTgocfAsKwwhAChmGADwEIHgSP4B1cFN+KOM2YImPOHhHHmLAGU0DiLYCMEDxmR3ABGIiEf5Ao90YSX6QxeHjymlOHQZRl7jvxQ0nsJCibJpkM5BUMBOGUWRInOI04nDKJzwonDIPHMAQMq5Xk2IkRwzBIr7DT3URJArl5wugIU4xYr0Wr4sD6bgHYzBAeE4BhBOYsmmHnV3BuAvOkkbPFOZ1gMYNIgb9FlBXYUvhSmdPVLFy1lEJ37dZb5qXAVhrXH602YcfhXtWgZfceuDyn3MYE4oC6S7EHMtXUpcd3CJt25sJZwGSv8yua9mibHQyIl9pc4Xl1BrWa+pKYU3k+kHsl6EOUhw1QvvCFL+BnfuZn8K53vQsnJyf45m/+Zrz97W/HHXfcUSr78z//8/jlX/5l3H///XjBC16At7zlLXj6059ennHffffh7/7dv4vf/M3fhHMOP/iDP4hf/MVfxPnz5x9WXcoAtML2YZReQJYllJ5cspvmfUrk+0CHIcQzzUNkpNWDnq76tnokBQO2MiaHnJwQAzmkhhnL3MpwnCRkNMcamr5oVWqGHMBkjD7DyXNd0Z44OB/gg4AQdqY9cZJx2YWy4jcNi01yZ2zZGkQGWOq72vPSN9UXxUxAZTdPt/IF2j32JRkbS0JCRSYKwKojp91PbdQtA4YMcBYfoM4GvCh1BbA4oSAXFlRMH59No2NshwQYJuV4Emgww6WM6BLiPJfVHZHk5wkeosVSoEA6ngKDGOPqWALI6UqzAC9jtjb21l85SZyWnEBpAmFGWA0Yj89jtT6CDx7sdaun+WAQoeVNrYBnpvJeKNCEaRp2GBp35piSngn9+FTIQt29KAz+CqVjyruLgXZlt+8W83HKepxdbZ9r79HatHVsz8qrKgw21MMpIsYJBEbw4uQ6jgNW6zVWawEoPviqrSQCQcZXXu8h5hwHPxzD8RrIhDhtJdme9StneJgphsAxYfDAGEgAipcQ8+QcQljB+QHkA1KOmOdYMh/X7Ng6F2HNaQ1Iskyco9Dvaj1iPawxTVOZC6SLlMyMeZbMw8Pg4Ygxx4gYE9ZD0N1EQnfzLAH7/SCLpGFwGBJjmhnBQfxRfIQjgMzvCgpSLKps8WNzDTBRftRM5LIIWPDzVgMmsVaoIZj2WlcOL+8vC9DFhgy2hTELGBY+mHvQgwpS2u8mm2rZBScPR1OxvI9sEaWPNtB+ZY2MAi8iFD+Ustiwvw9PTD8sgPLVr34VL3jBC/CX//Jfxrve9S58wzd8Az796U/jcY97XLnmn/2zf4Y3v/nN+Df/5t/g9ttvx2tf+1q88IUvxCc+8Qms12sAwF133YUvfvGLeM973oN5nvEjP/IjeNnLXoZf+ZVfeTjVAdAIfxjj/NMNzJVfop1bJHsLW6ScZRK4kk/KEthUdEwltLqg2AGUPSiL/wlSbgZZV9TI8Dkgpwh2kkm0+iDo5OCMBF3Bg4ryxBQc4ggLmcy6+hANyQBoAjByHs4Nyri8rE6KD0r1naAioHR1Io2U93YBk4DWbYpKpVqA0sIqw1vdmhfMkrm3AhIuK7AeDKq4UVBU3gsGZ6vfrirW6r/PdturNcU/pRN61gcaKp+zMDom2U6RmJGjRMQkMuYqACWqLV5MKkm3XYoATRkI47r4AVm/SX8bU+QCVDpAnxKQJnDawq8CwtF1cKsj8Zsp5jqzyVdgbtqGOt/sLykf0ggs5VW9ycX8rOxx7V8A6gysD+6CqhmDO4s5Lp/a0kgVDHVcFHgUAVSfkNlArOpnCR2twGphq+sdMIUdOmFm5CTmkDjPGAePo6MV1qsRR6s11utjDOOA4J1oTLwBfsArw3dzjbY8eI+BHUJicJ4xb06Q5gnzHJFTAieAE5tXBhwB4wgcr+W9q2GUhQh5DOMKLozip5IiYhKNig9BzU66Sw9KXk6WGjmZY6e0P6WMmSIyM1ZhlD5JWcfcqR+50FRMlda9Y8xzRl6J2TAbjWfNauwzQgga0dZjCIzZM8ZBck6dzhluBoiyzoysCxxorBTlVR0oUXpt6dHwS6ET81VSc2aJgtxy/zrXLebMXh7PudFy9sCnB86VLnsZgv74w0zf0pYrgYx6zuRVOaHKlb5eS7kmWCwXeGLPzMXhGWUBezXlYQGUf/pP/yme8pSn4O1vf3s5dvvtt5fvzIxf+IVfwD/4B/8A3/d93wcA+Lf/9t/i5ptvxq//+q/jxS9+Mf7wD/8Q7373u/HhD3+4aF1+6Zd+Cd/zPd+Df/Ev/gVuvfXWh1OlvrSakKZOfzrA0iO/ooqzVSrV55c7qB+UK4GTJZ/tBCK4+mDqzh72DkgEJAem1DTTBHGGzwN4yCAkZGREVr8HVfOXDMW2IiaxOUuYeNuurEGyyMO5IJ8Q1MRjDrEBpkIlkhggUGADKhbg2kkmMAswasfE7Y6PCVmSeuyOXwNwyKLySq6Rvo9t1bIQFlKL8izhQa6C28ylruD6niq0+qq2PgxkwoxaJoQK3pg13DzLO10S/xmlAbKVqTrVzrLs1kBdM3KSPE5wArD8MKoJLqjjowC8Qr1UoEqVwgyJd5ImII8IQ0BYnQOc7K6S1bKagwgwYiTtq7JDQWm0/NXx5HJyV7C7DnRUQE7N93ac+6GnnXAP3ULBwBK41FkOuPYS2KDYG6W6VM6Lk2w1WzEIsK21lREUYWJ1U1hcxrvlH1lNbDlFcI5YrwacO15jfbTCOI4IfoD5gJi5U+LkkSilkjjCx3mLlGeI5jCCeUaKjO3mEuZpi7idwTFL/h4AkQEXGasADAFYjYT1KD4oOUlQNtt2HEl9PJxDCIPEIqEkOcJsdQ9WvzTbJShdklnD4MeMeU4YA8uWZJ/hPcEiIHvvCp3OMQMc4eCwnRJiFq1Jzgnei99ajBmYEyzxg7AZgnOqgRoChiHDZ6/a0QyirOAHJZhk8e1qCEpItC6ehC0ab7R5zALKyeihypgCLAzr2MK1kn+/nfgMbF2BQPVTaYFCC37rzNmVaQ/b9/KM0mo02/e2NeHmmP02HoaW5wDqt1TWSpbC9arKwwIov/Ebv4EXvvCF+KEf+iG8//3vx5Oe9CT8+I//OF760pcCAD772c/innvuwZ133lnuuXDhAp773Ofigx/8IF784hfjgx/8IG644YYCTgDgzjvvhHMOd999N37gB35g573b7Rbb7bb8vnjx4hXruc8GeLUDZsKIcmF1EEZp3Xq2mvmhUGmpQ7P0rGajwvWE4Ml4rMEilHgjnKksWH1li83frETmkGkS5oasAtwyFIuAZBDYacyNBiSR14ntfQNWDKRIXo4aSM20COrLYloFaoRk2ZYIVB+LeqzpLd3uV/u0NfPs+IboOafZoAGAcwJK+G0Bc9T1c/U5svrC0rRrr8JWNu242Eg0Jiq5JOuA1X6ot/Y0YTFFoCs9ASkoAaksWJQMsNj1OWWkpCtjzack2q2g2h6jEQI5zZpMaqozMGpXMGT8QwZyQI6S42UbZe0Jzb0kMDMp/zXHQqF+BoqTaOGhtgIseZuwv+hxZ8KgGff6b714B6Ash8PGrAUnKmGq9qd9yBI40c69nKmOE9dA5SJsrJ2Vvit7pjp+do0CHeccIjI4zwBHhEAIoToB5yx9lhjiU+EJ3gUET6CckThjjjNimhHnCXH2SC5KPXPCZnOK6WSLeTuDo9TdgrQFAGtP8IHhvPAHSUwKpHnCNM0YwoREXkCHmgxJQbAInoycGUNQZ3knYCClVGiCnEPKSQK1jYB3XHysjDZyZqSMkodsRgbNEVOMmOYZIUiesqS+dykxUp6RWXKXJc1LlnMsUW29Uwf7AuYTPGc4uOJLV3hUMxcWM7PyrYa0zLekcNgzNODlugJGjM6M/Cr/WmohyoWWqsNo15kJiPfcX83ZckvzfqNXJU0qdNoAjoV8bHulOscvZJcubls/THtX/WhftryTIDvNtG3/15xkP/OZz+Atb3kLXv3qV+Pnfu7n8OEPfxg/8RM/gXEc8ZKXvAT33HMPAODmm2/u7rv55pvLuXvuuQc33XRTX4kQcOONN5ZrluWNb3wj/tE/+kdn1mtHyDfHloSwr3OWx4rdHUYbIuxbxrt8yj5tyVkDYYi9u9feW569+GbCzwEiAEUgE0vE2FB2bAi7kBwWEzI5ZJqVZYvoyXmGCRdbBTBXYWP+A6QrDirmHDUj+EUoehXKZEuPViD2rW6ub+9tx8LV2KDdORs/Ey7av84pQjeAAP0IqDQBINoJqErXPs1AcgWFbLts7K2ttCUqjoflGiKI1qI6qlLTBz1IqROVFdSIEKhjbct1ZhGW5uMsrbF6qRkQ+u7yqf5ANnZd/zoCsZmadIdEnLDZTthO2+L6Gbzu1CADiK7QdaFSM2UZj21WiWeC9QaIiKltcb4DHksx0jC9BmKiOdIMpzVY7+NuGMqOr2ZI5LuslqkZE9nxVreg1mdA6+NKbdprRBvRrJw5IcUtcopCRjGV7bg5J5AL6pROcOqbMgSHPM+YN0BOCSlKbBLmAGTx14pJtBbyyRLzBAJObHgSV3MUA2pGEfMsILtn2AlQElPKAOcluivBfLq4hrgnRooZc0owEyxrm5M6hZvgDJ7ggyYlTBkzYqEny5/FLFugcxZ8nWMEEYm/VgaIIuBD6cucBbBNc0ZMA4gGkMZpymVlpCYk09rs0Z4ABXMqyFlCZB1HNlBqMsAAaUt9+reRHx2dUgUYtR4tQEGZX0WBuwA8O5UrzbC5UYFRg4uwBAa7z+Nyu2m77ZqSE53QzP++fyQkD6kWyV7ZABZq3rMzc88uDwug5Jxxxx134A1veAMA4NnPfjY+/vGP461vfSte8pKXPJxHPazymte8Bq9+9avL74sXL+IpT3nKbkcBwENoT65Om9KsrixrbjleuM3OXVcCKcvfV1LHVYRqUtPMSgZSHByCMFlfFMPyLOeQnEN2ovnILiBHj9hRq5p7yDUTUhitmVzIdnCYsHdVU2FhrU17Iu1imJd8BVfcvVM++0P1GGhBwySI2nuljhWLmgCj4mAGrZNEtFSHQYImP9SoqpqzCOaUW4ABN9XNKrB6VaWMjQFGKCCxfmGAJPpmDUK3f3yl1L4qTEjfKFt8LRaHMQd1jnYm2A1yVu2U1KOCCeuTDh5R40NCHuQJyIzNNONkcwqv+NITQIEL3iT4wlgKICVj7gZrCroViuRdGFEgXMuw+go23/ufcrm+60wVDfrzZf4uhZPUtX1MXSW7Ms4GqbJeTzAm3fMUuxaN/1J7PmdGzhHbzSlinADPkk8nDZpfJgJYlTnmvfhbjENA5Cy7o7I4uXvv4SE7fMCEac44nSI2MRUgIpFQquksZyBlh8weiR2mGOER4IKHD7JDJ5GDc1lNKKJ9yxpNGDmDgvh1DJYXJyUkjbNTQDQzUmbEOYLJgSljGB1WPgAEzGnCPInGcRgGkNdxdiYUpR8zANbt1QzGbH53zummQyr9yhBfmuADnBuRwlBy9zidE84RbPtIPzrLxYqZfFDotyzclrS153vrW7JDHw8DoFSgsfu3+BQCZYIYODrLv4R4MQcaxtZZYZv7BUDm/j40/dD0pGngLaq7aVj7uEDLtIkPXR4WQHniE5+Ib/3Wb+2Ofcu3fAv+43/8jwCAW265BQBw77334olPfGK55t5778Wf//N/vlzzpS99qXtGjBH33XdfuX9ZVqsVVqvV3nO96UQZ91KjskfDYvcuS7XZ278WlKt515WYY6vaWtSvEA+VabBTD9OASNAhFWJsgr0R3M6putY3BMbqJ0lIukXXJY/sBPkn64NEYFYB3mhGiGSHQLdMBOrEbUCBo2b7XiuMbWarYKDygApadh3ARIsgfQuQq6uRsv+/nVGwSd5MpAJQKlovwoQtOBpASN11pep7QcSuqaIwCFtpQ7QUMo+p4rzSX7vPNf8EaS4poDK1LWk+LQJxlLExSU1Okg4iw5KqEVEDGNvcSPK7ZS/GKE1DJj7BsopOOWI7zViHAA8IQIU4bEK1UQ4WEZeEVlQwdE00Rshn7eRRrVYRBj0ILVo4zZW1vJ9yy5ANcFVw2UB7VPpZFnN+1KnF5gRJpX+K3ADqOUKNmgtzVVoIBN3JVahd57v4rCfM8ynSPIFHdTIljfWjod85e3WbqrlqbOYTGD44jOOAeRKay5mxnbY4OT3FaYrIgMQY0b4McAjIyImx2WRsZyCzA+Al2zALBPAkfCJpAj9oZuLWv0r8p6AgWCydOUuiP/PPYJZjMSZxypAtiOLkCiDNESnL9uMaLTqUEAZivpHWZtZ4LiAFeLmYlxkoZigiDbPJ+jwvmij5eHhH4nTcgJHexbQwgX4xQXX8ytyxq3nPd25NOwuZUWiWG+pkHdX+eMvpzvRhLHFxSs2VVs9agC80qWjM3KUhWFzTn3goq0AjxSq/tj9d/f8vAZQXvOAF+OQnP9kd+9SnPoWnPvWpAMRh9pZbbsF73/veAkguXryIu+++Gz/2Yz8GAHje856H+++/Hx/96EfxnOc8BwDwvve9DzlnPPe5z3041dkpVSmrnWlwzlZ7ZwzE3mcR73RjNzhnghSuBLtnMO1Yu0kPRODcepFYDpUK2wmm9VD7ngo451wBKEwOnIT5OI0smaNHJtvh4QGaQD6ANWEXwLCwjc6JnVeEj2k66kqYta42z3tg0uy0MR+SghSoH5eW4RXCbVYE3KtjS79qv5dp3SJ9YhW4te/VoAVvqdiL+kM1Pk247rpsso+OBi/AkH3VY+xI1d/it0Hs68RuQJPtbOogGxmaoRIx0+riyMCcgAPOJNuo2cEi0WYFLYCDt1D7DVvZT+qsfZi1LeJbleGxmTNW8wxWB+shS94Yr/UJzsGx7RiSHDJU6gDYPKv6ZWPwtc2mPpaaGEOugKXu4tnj2AoG+8rErXR6rrK7YXd+FiCjDzDNlZkEBHSYlqQ+xVb1IgTrc31Tg2qiU+0Ka38AQoecQDkCcUYg1pgoGT4A5AmZCSkmeNoANJRxLgHT5og5RtnxlYGUB0QeMWXg4uVLuHy6KaH0k/KGQIwjdhgVOGwm4GQjGYrzqGaVOGNmgvOEiDUe3GRc2iRMk0QndqT8hcV3ZI4ZacWyVRke7pQw5QSLCyOxTARQJB3XlMUzKZBscT6dI2LO8MwILDubwGbmSSBiBCfxj+pqHogc4RMhJ537GbqocmWbPVDNOoOv2aOdCygxOepolnq3VNJRVjMPK/1Qs16iLlaImZ/Nn6T+rvQm5nTdFm1pDPQBtLMQ07xjvDBfGk+BtIkak2UPA6zBe+SVvYoasNL2gJ4zrcrZYKkBL2Q8Cxo8T2iAWHg0GPBXK4TxMAHKT/7kT+L5z38+3vCGN+Cv//W/jg996EN429vehre97W3SXiK86lWvwj/5J/8ET3/608s241tvvRXf//3fD0A0Lt/1Xd+Fl770pXjrW9+KeZ7xile8Ai9+8Yv/1Dt4Ov8S+y5nmhXawyjU/em+1SO2730RubK5et9gmoq9Gj7RMfQiYbkSWPuMSr6q3nesOTLE0ZUhdljWRH5i7nEqB2W1n5MBFAnqZmYCcbrUJGXduq3ZGkYoRGvtsYaXtrVd1oCU7vpFH5We49qHpf39DVUUGEiw7be5maEFVHB1ONZ6kIIri37L1Gx8KwyEAU6lvmVFtJz+TEDWXS8G3rI9B0WzI0zAoaXJ0hcEEPuqCobVl3VLssakkC00qI2UcbM6AxJynhb01nWf/ctckkZad81zwqWTDbbBIfgtfPAYgsPgvG7vDBh8QAgZIdRn26Yk2T1Buktp8daKaxvh0BQDsXv4aHkKowFDy9LQkPWNvnS/2r2+q+WlNZw5ddc2I9N8lvXTZUUjvMwsRABymhGnSaeQXJeyOI7GlDFPkwT7c8CQJYeNI5Jke9sNNtst4hyRskemATGPOJ0ZFy9dxul22wFTxxKobXSEkAkRjGkGpikLyGAgOAcaA1ZDQBhXuDwR7ru0wcWTiDnbDhjhBKzOr44Y85gwDAESXVqcUMEO3ov2L3gBrpkZOWZstxFxnRFWXnmMhM+PMcO7LDmCoji/svOIc0YmVgd97dec4cgjEYpZB+pvIsHlgEyVTxFB4zR5+MaRv9KAcZF9SU526Y4UQFdaog6EmyyvPn3cACzlBdzKKvNpzB1YLosUQDW/DfxeTCsqB1hBUiM4Sv4mOX+G4qNpQ21f5Uu9ueehzKr1gdqGKo4LOCRc/YYV4GEClG/7tm/Dr/3ar+E1r3kNXve61+H222/HL/zCL+Cuu+4q1/z0T/80Ll++jJe97GW4//778R3f8R1497vfXWKgAMA73vEOvOIVr8B3fud3lkBtb37zmx9OVQBgp8Ouzr/k/1RRPw126EHK7koLwI6gM3OG3rIosnrq1YSu+d6qIs3voDG3ZCA7C7JEauKRSeF8QI4zOIu3uwl5C9pkiQBJQ1RrIAGdgJUxX7GvC32fNRZchXfzrKpdyUXE6FxDsQVDJ27pS3Hk42yhy3JRy9YVkAO7XH6XLMzavtK3pJMeTnP9SF2pUV1Lu+rwFu+LgjGbaLaqDepWFyCNhyIT2d5pf6svp8SuYMpgR+CsfjU51TQFLag15sJ8JsM1DZIF2TITgp2b54iUGMFVu33wDkMIGIeA1ThgFTKGwWPMwBBYtW5eXKSdk62paMxsC2BKZa7scFtpjqs0VppWAMJDze0lMIIAMBswIt2ebYRU1waOGVkXHSyIvJnCyzltwg3dbznWwGo20EWYIU6d8zwVWp5jksy/04w4ekQSc11IQf2mWLcWT5imCfM8I2Ug04jsj8HuHOJpwsnphBRzVxsHFPcbq3ZOwDwlySy8dnDjgHFYYVytwAjYzBGbmREzyU465+CcxGHJMSMl0ebMMSJniXMiEaUteJyA4+qQqrFRYsZ2llgmUP6SsyQzTDkjJQnfH3PGQANijqDEGJ3TxIGEmHOlDRJwwiTAJGZCKtBX6Q+kDr2iRZF5biTREklxAT2z7JMzJUZQM+7cXLv71+it9UFRn5t9IFpjicjc7wGCrIMYJQIymfN6eWpZ1lXSv/LcOctHsn+vfeeirdvzJAVGBtqoNh65+Xt15WFHkv3e7/1efO/3fu+Z54kIr3vd6/C6173uzGtuvPHGP1VQtn2lE/h4KJBS0W17z/J5DwlyikrMuGfBuGc+b+mLUs+3dSsvqM8u15mABSxp2LKeFtiMHUBZhLI4zXpZvZPEy8gUKkBBLszbHExdCPC6hdUEfLsC3qsZsn5dCqSmjmdrT5pnQpm8gXBWmzjqWBfTlEkYiCrcJj/pSoqLpmeROdkpSCDxvylATFtidcm61RfcgyMqsVVUbamrAhPBtooRjKTb0037QZXh9LZpvZeqYyOKmpuQKSlgEcc168kl89nPTPvvdZu5xrLQc5nF7JOYgES6FTgheMkeO24jxmHGGHzz10vQMB8w+BpxFAaYm16Rf9tomupcR4D4elH9lKsqsMOit3aKodmu/XVFVzRuZABS6Vbj3hBLOHswl/Po6Jyav3vU3M01BlAqWJYYJtN0WjQtMTE22xmb7Yz5aABT6NoOiCPqPE9ISXa1kB8BOkbmc0jpCNt8GSdbAT3mj8MQjVAEYzYNKST6as4Jl083OLeS5J/D6AAXME2MaU6AhiMXbZJoRTzJPKDskFn8S+Y5qiOtE15hO/s46zZkLzl9ckZUR95hYPjCZ6SrOMvuns02YjtFjMMIZtl1RCkhDINEtLZdQQasyeYQZA5TEN8am1fajb74uZimhJsdNkBdYuyjJ73DaKLj420iyUYWGIXs8EcUgd2BlD05bsxIK9TqwK5qWkxRUhZvBm4aTUtR7iiwb+fhlcpex1luvhcQRnBUfXKqt6GZwlCOlpnLXLTCD6dc07l4lsx3H0gRBq4dV+n2T1U6dNmsyozBX6meS/td77+BBWOqGoYqdKkct8vr9x4EEHmZTCqM0eTayUl29nBOAlIsVws0ABJJzp02kqwakwoeaFWV9s6CTdgm1xUcqs5Q05cVvWps0ACTTriq854wegULGuyM2LZEar+QBzTBXhGaFhpeGZcFnpOeVz9QZjh2om3IqQLJdnvqog/K2JXJWme3rXTQTGRSZk2LsS+ijmQFRUxwWZwYxR+ljTWizqikDrENEzgTrDCjjURZY7CIYM1ZGL+F5I85wScRYGE7y+6SMGG9GrAKDutxAI8DgACXHLyrQIOhZhP9nmzOGH0rSHCcQPAANREnXRtTREEf1V6S2u4xGHH9Rc1vKqBBThRjoeJQCSpq4KMfi+KwXvqyCki5tgGJ2te2xZgzY54nnJ5cwmZzWTKPwyMmxhRFI8EQzYPTMPTeORBnxHlGmmeAJWoqYcDMK+S0QkLAdo7YbDdoI/YmEoovOyYIOHIB45BBjjHnjE3MWEcxs0wxgSGRWkeN1Oq2EmPFKehJQNFgpCRbjKGOpyE0kVqZEAbxgUspI2dxAJ7njGmKCI4VwJAmCpTdalNM2M4RR4kRfEBOW8wxYswZfiA4Fq1mTBGcgeAJQ3Agl+EdwbMDw8OHAD8MJQ2HTo1uAdG7o7YAelEW/F4st7Qz3hUY9uCjAyNkfBPdOeUGmp+LYLF/2zfYvCz+TXqUOqCDgoIKr7agiIX+u3/6pgIofjb2Uj1RFgllivU1VGMVzO/G9FhMufBoRpK5zeYld3XlmgYowJWASQ9SbEz+j5qBGqFGJU7K/s7fB1LkESrcgYZuzK9A8Ck1dW+eCKBnkG2ziEh2gHATNlu1Ka4FKDlVdE66CwQCVuDUP6N9MHMRFl3bWqLvFxN7+/ss7ZWhoOKDgQpQBBwZwTdmChPYZSo3r1cQINHNVHCq9oScBaGrq34GA1mBALNqL1h3jxBKHERWgblnFU3NNuXO4CLSWiewOSFn1AB3DeBuBDKLSki0YjCGmJdPVzrvx6b2KwpDrMkk+wup9J4xNW0NA6zq/eRULZ+l/3NyRSPDGgzQLejQlQjDpI6TAjxk9W1+AgTvBcx4WGZrlDkhDBwL5qYr266xZNUvo2Hf7HQbNZZNv+B1IdDwZz4LSNcLasfZcZu3xhtIfCZymrDZXMbp5gQhR8wR2EyM7ewwzZKLJqaElM0MKQ7r2UjWS3TXjAGUA5g9cnTYbLfYTts9FRSQMkFodMgM5wHvZTxPtxGjn8WvaAUgOIRhQAgZ3kkGYyi9ZKDhV0KrKWUE5xCcA9QcTLq7JzjZyZSLaUL6ZI4RLhBW44jBO2ynCVGDrWUGttuI7ToihDWGcSXao5hBJBumc6p81IPhHBDI0qUyvCY09MMgu4a85jRqTE7QtlSM0ae12Blr49eoc52UhnrfQAUjBnyL9qX5TRXyNiIJxama6rP6oTSiVLcC5ZGNYCjfC++jWif5Xss+fxIzxVhcmqVVwPhxRuXFdZHIyFovx5UPqy4P1bSjx3UH6dWUax6gAA8FUoA6bP9ngMkOIROVbLFErX/E/noutQ9LkMKotIcFKtcQbDBP6StpVMys4byZNGSlwz6Dk4SUdqxhpFtAoc8r9ywmN/a1DVk9taml6z19duUxEIxixFwngQECCUFevf5tK2TRfTZai9oPvggP6wPzQaGyLdeVVY74HxhIySB4WY0Ys4VuJW0BVan2AiwVoKL1ySz+MGQMz3xULJqNTWLos9GRL8GJB6R6/tqOrh0bdunPxXEFva1mjrRvTODbb3MyNY0ZMyOZ9iNlbOcoKX1SRJxnbKYACY5Xac8AivxUe7/+473H4ALCMIhfSwgYgxPh433Rshjr3Wcu3DFhLcB8Oy8MdHADLljwaGXmrcZLBRm3SKml02Zoqj+A/FPV/kAmRowzNpsTnJ6eYOAtVm5AYMLlE8bJ6YjNtMU0iVaAM1tgUI0GDATvwN4D2SOzQ8qEaY548NIlTNsZZ5UEiSg7cRKM7h1SZgEoYca5uIKY9xhzhmRKjhnMVEIvWu8xUPJozTFqHh3CoMn8iGRnk3eS04eI4TyVgIApZwAS2+XoaEQIDptpLsJ+miM204TVaoX1uEKmGSlnzPMsDv8JZcESdduxdLov27/JewTLCF2SmarpG40/mI0b7cataUvLr6sDdT2+z4+ObWUBdL9NHhUn/IJbqPne0Fjzr9RF2Iv5rMlBLjt4jCLLfWy0y/W8zqfezKV3UeVcKH/b+pD2884JiVZDDDjhE1l9qMh8ApkhCaIMsFxdubYByoI5XY1mpBOT5f66EpLjuzd1x01QtENpA6/CqwKV/oFF26CE008OXSVySx5LkjVFnxFitT0aO+GGtYhiwNXvmcQcosHMOJsyuPHhsDfTwvm2acNuaQJi2bKv3gBuBdXiGbuIvhe4LUCx73K8qhDtfAe0GqBGgJhLINlSLV6II1FH27K/Vf4yW/9K/iNoFNYOCNkKpYCqxmm6WU1048i1vwr+aJHmsn9a4ACCOPyZE7V9Gnqj/o2dEAdqP9q5AlLa/tN+aHazEFDCi3OW3WPRATECp5DcJ2ba885yrlTfKNMd2ZgOXkHJOGC1GrEeB2B0cDSCMcDDddoX6QlSmta+4jrH2ki2LQ306nQq7kCmbXGoQsf6UOa7nLcIOqVfCuOv/WLTlTWwWF0YAUSynXfabhCnGd4lzBNwmjNO14zNdoVpO2E+GiQOiIYAqLSvVGixitSZd54mnFy+jJiiUVHfdshqOEPMPnBACF5BBsG7QXPueERmnEwJlzYRm1ny9pomzJVFCYvJlzQKLjLcOGIVgmQcVsDiwOBJYq8wHLJqgcXxWgLQHY0DQpCxjSnDkwQnnOeEOSasBnkXMyOxaOYkVQeQOGOaEzabiBg9GAPEBCF8wFI8GDhxlWB6rQcJPe7TKCwL4azYKX+aYmAG6Dl3BWAmH+QglbE0bU69eql57SBK9x0QWmzf15fCYZYcq9Rrv4ytK4DWM4XKZgejQujxqy/XNkABqoDY261WbLtWw+RRhXZ9li2AKnEsgYlcZ4ilgzslXgAcN/ZGu7klIt5Ty+Z9CioKEoWHrHozwP1WVbmc6l9SoW7nSgPMOY0AkqzIlJ3YiJFkZV80NX1dJIaKIeyG6FVI1z4zo0MN+9561XPmYjLqnESXzKGAtAYosLXLAErjh2JSmcrtWp/eaU4YlSsOshIrpkplEyo7ZhlW26muNC0qbQ9Q5QFUpJ+dtlWEDYN5ByqYK4igxlhkmLAUxrordMvooKgI2twc2qc1K2/50wAQM0mWitrTm7pLDqfO54glL0wGEAnwjrAFq0DNQBYm5harV/sUZ2YiEM0YncPxesC5OCPGEcgDcmaMQ8I4DuJf4H3Z8spl7mqwwEYzR0zIijZc8Sak0j02NtU4xsgl2JUYCnpbuzy3dWPsWLtqTfromHa/Bu8DgziD84R5OsXogNE55EnyH51OAggSK+1kydeTWbYTc7aU97qbjh0y1EzLM7bTRtrSbSZswbbBMkA2s7ji/BoGwrgaEYYVTjcRlzaMS5skW36ZkXQHDyHDefHz8CrUMzIoE46cR3AOg1O/kCGUt8fE8GB4AoIjjIEwBK9kS1gNI7BmzFMEs8RQAZPsJlsDwXnZFVY0W6yB3IB5JkyRMCcBLKAEjwRwBMcIjDrfXTWL7orlhgfRfqBytomnkl4PbuszWv8QuV/mj9FJfYfSSTulc6NP1ajeouVreCJ4gZoWWo82LH+pq9B4b5Inw917Sw/oenON1dv4u+SUyoVpizmHQdTz7Kst1z5AKcKaC3BYqt6ABnMUna/6dnDLfux87n/b18Vbu+PUIl8h+BYunaV675+9O3C9aaQXHh1wYgM+VI8pszQH27KdFl6udQbTJCS17VjpMgAvBJo9vGr6dFJY2xmyuif9TaQJ7Spyr0KmtrH2RxWq9rdZS+j7KgNoVentJGtNDB0gMpDS+tbQAqjCpp7QiZmSrG/aCVjprwFIC6DXdSSL+hx2p9angB0l4+JEa/1UtEG1faXfCk1LT+1o5Zr3y7j1AErGs6Hnph3W47Vy2ZRVAMTJsrtWNRWUWUO2e8W44tuU2bxn5D3JM9KpBOiSgGQT1uNctjWPQ8AQPIJ3siPDE3yQ2BbMQetbg+150wZpfwh4tPMylo4lXgwraKl8gHBWrlXTpnUONtp9xEDN3aW8hwnsld5zwmZzgs3JJQyeMPoBaTshZmCapA9jYnEqTQk5JjHBJi/ZjzWY3pwJm0jYJoeIERlZzTHA3kprcSAEzYkDyO407wN8GEE+IDLh8ibhZDNjmqP4F7Hk5JFFj2wh9sxw3umiSRc8Xj7eEcbBYzUOAIkztN9GpUCH4IFhcBo/BUgpYSBgDAMcSSTlou0AyTtcdXQFO4m0CwkYZ4aCxLJTKCv/Et86dSRnjYuioMzmUt4JWqY7fGjJi+pv0u8F8DdMyRamxjMqBTX8SxlmhR2VE+4MXutrUp5g3wx2CqOwkPL2TCI09W/fZbTZQO2W6TmtB5vMkN/1Wbmpb1dZtIyXHMv2drQ8UBZ3lBmOgZ3uv0K5pgFKj1SpQMt9O2V457gNhDkp9ted9ftKpRMYMNWbwud+ibPblsXgLyeJAZTWb2CJ1Nv31+f1be5W3/CSdIXVOcp2rbTBwCr4rlCwYhG0T+t8bOwiDV9d+1AdSMtuDdKdAkCd8Q0c2UHctLykK/uAiXP1mHKaDsi19ZeqK/LPynAs7HeW7MIWD6Uo/8s7e4fiFuD0x5pfzTZYG6saQp00cbICle49etwCIOmsl7ot4vIswIOi6abubd/uAdJcO7zEFCktQOlTAKCC3biYKYgIpH3GVPWYYv/PyDEhxYQpJmwGj9WQMASP1RgwBo/VIIHiQggYR49hGDCGgCAx+eGJiz8RIOHqiCSuiRgcKsgni0XDuqUY2rYibAgG9gFSp8Hdwg2q7WLPsIBL1kzAyIyUZpyeXMbly5eQUgaTk2y9DMwT6xbbGVNMiLOT3S0pIaco/j0xYo4J2+xxEh1OecSEEafzBiebabFwqv/q6MMDWI9A8AIMJmSsxgCmgG1kbE5nXNpqRusMMc1wBntpu5lMvKOS4RjIutOPRBsTJOZIGMTBeYhJzD3q7Dt4xjh4rMcBwUPaRih+SMwk0ZChpsKUQQMXUw1pPOgpRvVDk5EWLTODFXwxFjxDQYfsUFS2xDX6djemZDysp/9KJnXMu8Uot7qq+te2JdsiseOPsF04xncrmKkguQcm7SAXQAzSxaU2wK7f0Qb12/sLeDJ5QLvn6vW88HNle3M5JP1n88h8qFqQkmWBUFJYXl25pgEKsAQQFS3unjvrfqDs5N7RuixWRYv3ttdYMSAAFbqF0QGoavUeWABl7btTv71OtbXiO+CkquH0fQ3zbKtKZIDDlevbOnbCyjRK7Qb7ri/k2D5gWOrZ34EC/NsYF4W+e4CyuBVUJlTtz1YbYpobkAjz9hhp43v3P3lnp/nQNrW+LgJUJDlaracKYFLnVVDTh/va0fTrTncKsFOxAFlJVhqT1aXTcCraRq5CFywrGOQl6NgdDztHu5XY3+92h/Zl1VwJ8C7X6w4OY9DlzWxXG/OVYIQJkqIgJfE9OPWEIcwITswBq8FhpdqUIQQcrTxW44jVMGIcAoL3unujaljYVmyQVXhtv/gg2dq0U05qYKy60Gm+W7dRE0KQa5/1PormhAtI/ivGPG1x+fJFnJxelkBnnAvPnqaMk9MJJ9sJc0xIOagik2EagZiSbsN12CaHmQO2zLh0coqTkw1ET9AbmtriCFiPDuePRqxXHpySxmCZMAwBHICTOWMzRcyJJSgaZPdRapLF2S6dMt6k6n0DAI7ETAPVzjoGyGH0EvBvNQas1yOCY3BOEk+IHYKXOCpOwbQD12Sfzom5kDw857owIjkn5g8z5bZuvdLBBPF9MQ1ei6+X3hBl2FssoL8LEO96ueXL9tyyBLAh7p+PFmwsAAg3WpNKej0I6O7kdu2gvLSes75ibYD8rt/7OnB5UDFyN78zGW+smhQRB/IGMydX7XKunx0V39cRQAEMQAAlB8DOuV1w0YMaoMe/V3pPVbJduVLC4CT8N+o4lXf12hQT01cGPi237AFUd61RrYaSdM2KubYFqG23ANEKk9V+X2RQcfy1exo7fUfs9uwGrGAfOXJ3Xd+VSx+A+symM5plChqVIRUBWnePVCHcOs1KvXswa68wDVDRnLCYeHKOxbG43Spn79L9J2hjefTmniU4qH4jBuPEiRSoYfYVrBDA7IqmpAwNQcCRMjdqVnm1T2RVXjUofTHQ1o7N/qsYlk24CAAykGJjJH1dGFxLt0CJuQLU/ivsLGfMibCNEZ5kxWt+C2MYsBo8jlcDVqsZq3HC0TjiaDVgGAZw8GBPGJBU20IIPmBcBd0BIhFUY/ay7ZcYlhizrIxboGEgr8V2AJy1n+qISlubNlK9MaeMaXuCB+6/D5vTU93FVceOWfL/xKSaM/WZgKZuYJYdK9uZcTplRASwG8EccOnkEk5PT2CC6kplHDzOH68wBsIMguWwcV7iIsWcMSdWE5xQZ8pQjQ90Z7gItxijzg0WXwkHdZ414CpGvOAdMsvW5nHwWA0B63GA96xeuyauJRGlgUzhAbJ7h0izHpNoW0IY4FICEpc5yNoe7wf4ECqQIgEnofGDKmNUFnh2RHkDd0NZeEenBWU0NA4FvKpdbgKYGeW3SlLTthT+2/AGy8tT3osqF2z+MdBp+YquvAklXzmEPas1Fu1fsArPtPpR4UmtdrBM5QYVWTOoMX2zugiYWYeRuoXewynXNEAx5t+bVs4W8vt8U+p1vBfg7HvnQ15USEqECyPDVu9ye6/2656953tfz6spRdL2SHkHpMhvV2qrk7ggeRMdxrx1Gtrs44ZAqe/3DgQutCiEXJk4A32tCHv1r1cqC9UQFSddAye6+6MAlRZg9v4vbIHYWK3JCk4kYJs4gcp+R4nFYpqMAkTI6aodi/7e/V5BTusIa0xLtkXaypg0eqPdS+VjtKZrmeUwk4CCwqDLGNXzPWppAYj11eJ5gNar1dCZfbsnCmFy9R0NhWt/W1/IBQkMyuLISo4Ro/hCeB8xBIfTrfg5rMaA49WI49UIR4AjxuAzrjti3HjhOlx3dA4XLpzDueMjDKOYhGLK2GwZp9sZ9z9wGZdOZzCPYJjKv6FTt5x/VM/p34IfG1BWI2kKTaQ44eTyg3jg/vswzxMCAB9Iorom8elgBQOzBhsUvx0JZJZSQspAzB4RKyQ6xrC+gJACNttTpDQ3Y7B/OUAErEbZ3kuQ4GiWQ0civSbMicWfQ2lATJuMFBnZMTzUYW2xhT+zgpQy1Y0GhFd4gqZLEIAyDg6eGORlxxLIIQp7FCA6DnDOIaZJA7llzWIsZk1xvGZd+KmJiT1AEvl6GEb4YQB5M1cL8bmF71AB9S3rEAlfxxcVSIi1rra9mD4LrufS/baIrfxuz6LWJmlDQ4XClBbLorWlMwMltihfjLmJp/J4qjKnebm8r6H5erz/GCciW7wueZppThbPIOWPIAWyZSwMwFxduaYBihVejMrSNLMEJvuBi3035v0whWT7PP1bXULVCdWOtKBqedNVlM5B8qHqUhB6lURMlfgt+p+UxiGz1FF38BShqcTdqlCKgD27PtRcXeeUjVtXYxT1+v4WPURXNf4nRYT3u4b6x/HOCglczT3lYytGlsB2XQReEmFqzKVs6wYKE9gdqkol7YQtWhzIqqQ60Db93WmTrL8a8NKuFDt/b0K3PUrr13fLso8WQo9Mi1N3ARlNM7PWmbFDDjavNBcOaaA3lerCjg3NsKrfWfQsiTMoM+bocDoljNuEITisxwnr4CU6qSMcjQ6eBgzhBJwjMktyO0druGGF644GrEKCQ4S/YYV5njBNEXBjDahVwKONR4vkFv4JZXVtvwyoyHxgACnOuHz5QVy8eL8IZA/44DASYZ4iAEbKEs11TknNd6JFkS3HDNYdRjOvEYcLcOvHIV3e4HSz6QTjWcU7wjCK8N9OGds5wYeoz69KewlNr/XPssMpQQS3CHjZouya7ePMrCAqI7DTtBRVgFpCwSForp6cAac5nIYgwRKT8MgQxHznvcMcCdM0AdoPRIScRavolDZs0eE0b5A4/gb44NV3xQCFzckeuXsbKx3wfRoWkwXcgheuwKH4kxD1i04bFmr5Kwq4qPSm85LTQtBXjUy79b+41TqrR0OvBpKbVu5qe1AU0PVN1cVkt/RHSVFbAXDaHxYtlpQHtKlHlp89zPDMck0DlKVQqcyiYdKKOCoIaQimubaeN01KvY4aAq0aBO6ftVOWjK1B0eQkc1fz7oYGy/V9O+tEIG1X75CpbTWhsZQzncRQwuamvQA0CpB1SkNIjWADoXqP8yJmixI/886uhta8cEUt1L7u7NCNthHcjz9Q+6aZ+DvApFvE9PdL9zXxRTrG0DACm2QWwbbYvrlfeS/6sBNuzXjsA5sV3DR1UJs9KdjlYkbc357dQnsyDe8y42WdqhnO+rLR+Dguc4xYpZ2BqLbbjR7sP2L19kcJNc9gdaZV5bWOXc4GbiCBypLDnCEaEYqaD4iwnRO22y2++sApzh0FnP/qJXzl/ku4cP05rAeP4/UIj4TEjMQBOU5gHiSmr5lWignHxtvApTnbVodu4ws9xqaCGTMzpmmD09MTnJ6elnEVXw1RxJHjEuGYiEogtKz5lmTt6jAzYcMjkr8O8MfYTCe4fPm0MZlhQW+15MzYbmdcPt0ipogMgh9XWB+fw3q9wqWZJFBclC28zPL+zGIKc8wAPMw526mG0ABKjJKfZwy+E0BEsivHwSIBM1KKMk3Iq/9QKI7gQ/Dw3pJUeiTvJay+midzEwrBwFXd0m/npV7DEBCCRJK15Q5R4/1BOqb9gY7ml/PJo+GghJLDqbAEKlzCrip1awX7PuZMMOfxVvQ3Pwv1GMow4NLs5GkX6rS4t64k+ud3j65ypsoboMrGZlobqREDyBorR1NZMKN4y+98dl99pXJNAxSgCsDFQZTRsZUisDP2y9VifVYNMdNe3g9rBmFJaLT42z6cSn2qKrGx11GrhdjnRtU8CiigSx5NJZJiry2qy+cWkBQY3Txxh2Z2Jmq/m6FMjkU9mc3ltr9/CVLKPc08XLSwXrSHoKtpoBGier11dXUm1RPNRO+2CTagQ/5L0iOk3WQgx1xGjE+QjSkVRGEgyT7SYrfDk/b9ln6qQEg0EgyQCnRigMX+LpJCQIqEZLf4KkvGY9tnudTGTIy1/3paaEGK/ZVvrvw2GFHuyQq/nbbaxqdwJCrVkGd5wAuNyopSt8tan8LAAZcVu2w9TZodwGHKQCKHeZK+cQSMlBFOMoaLMwZ/gtU9D+Jo9FiNHuvRY3AR584dY7VaI04Jw7BCToz1eoXVuMI4BhytVxJ9mRgpM1IkxJixnYDkVjs4wECxaVRyZjgmZI6YplM88MBXcXp6UvozMUvQwIERBsJq9Di3WuN4XGP0ErU46WIh5oyZCSccsKFz8OEcnBuw2VzGxQcvigG2yK3czJeK6mMGHngwYwwThiFjCB7H6xVWqxUQBpyeTLi8TZgiIzEV9snIiCkhAHCoMUkIDMmeQRqKPsIPAT6k4h8Rk4yXCxp7CYycGDMzODi4LFoaPxCCF94QTMtCLDuDvJdszlHisBAkjg4sIjY04y8Sco5w6i/myEk02RA0X48AQdelLmAYEO7WIrUz6/dmlHsQsH/etL/bJ/Tip84MNkCPukg2Ib/0XynzmGEW1mZO6ZyxN1L93fKXArrL4k2MyR00IeUWzP1x7SPmrLFwLKpQ2fiNGqlatCps/ilQHkZVLj1UuaYBSiukqu8EmpXEfpABoADvoh1BK0w19Lt6h5FRgAZ7U5pG8cmoNSrv7o9T868JUJKdV7YqMyFuz6lP3HlO992Qb2kz7b2zCGFUILPTn4vbdhzDunebtAZ6gEOKnpurFyClVHunBvqu5Tzfd01Xtw46VYBwhuzlpkEtDVUGUB5cn0ito538diXAGzWpBHYD0fXasCs0asHOWtDKmZE5AQpUhN6tXgzjWFW8o7y7ZS5nxSCodTRlbw+2hZ8xSHdMOFIQzwzOZvYxsyFryOse1sorWuZkK9hcZWq3bcL6zEB3P1YpZ+RcQR0RMMHMOoAnxuCBgWR3yRgIq5GxGmcM/kGAGYN3GILD0XqN1RBwvBKAMo4e40pCpq9XR2Avyfs2eUZmBqmDbR++XxpheWzinHByehlfvf+rSGae8A7ej3COMHjgaHQ4t17heD1iDATnPObIGMIg3eEIc8qYZwcajjAenQcDeOCB+3H58mWAJMNwMWEskBMDiAzcf5oQwhbnjwecO3ZIGZjmGTEBl08mnG5mxKKhEIGSOIEQlQ5zl0Xc5nJm1rxCE7xjNQdVzYTt7gE0KzkD2SnwSzJ+wyAmGe8lKF/r3zLHBBO5BI3+7FmBj8wHzhJQ0CLeGjfyusOLNOkpFnyi/S417LUS7SKMqPK4XqNQv5ssMf+6wmcaLfkSrJgmZNftzmSXtafyTTvbYyRbMizfAnV0NZCixzu8RWjBT6197ctWu2pgo65y9EHMqLG06nfTdndmnqss1zRAAfY1ttrp9t7RjKqAfaGOvUKUANt+WGBOCwQKKqX2BcAV3g87SyTa5GzmgVyIfb8Qa0mTut91hdv3gwGf+lv7h9FSdu2XRjCdSUOLSb6AJuX5htjtFtrXV2e94qHOL8BJD3wqCKv1rWMnDEQEeq+Fac04Ziu15hbIAyIHdr4I0tL3Tp1jyT4NgNzpo0Vp69pp1LQtbL4vBkKoZqm2qLgaaImbHqwLvZ75LMHjGb2MSgutw3OtryPSFPeVCszfp2XcxVyCZrlAEm/Hnusc1FzRgttmri38kmzssvqncDFPZtNlgFiimHpy8E7BiGcEv4X3EjwsOInPMW4iAgFr72THySpgvR6wWgVcd915rNdHcGGAjxFpSmDIOJMbQBSELggAJZgPx7Td4uIDl3B6eYsxHCGsGKvAGIK8I4IxDAHrozX86MDDgNkd49y5x+E0MQIRJmzw4HSKkzmAxwGZGZcvX8K9996LzGpuYdLE3+3M4TKECYTTzLi0YQwjYc0Oc8yIIt8xR0JKTnenscoXBidZERMIMSbMc5QtuzoeYqVmAAnzTJi97JgZgtxfsqGbBkyFN0UDqREhBNmZY1mcvWpqdKznmJDSjJSTbif2SvZUNCMSPrhujWqopOZz2qcNQcPOAYmPUgR0a+Lve3bf5oZeBjQ37ZleBjrUkNlJrKX2g8p84+4/2L2sf2n3dVWOLGWAVa/lf/tkRVu4+1SwobGh9G8LcM0Ux7lP3ZC/bpxkC0LbX/ba9huKbMmVuSfEHqgwxAJZibGosLvrdhno8ri9kVTTwBq/rc+GfAWXpeJJXp+lZxbvrwJ0RxPSOL12z1CCbgHePk2FPhn9TNzTn2SOY4zqbHj16Lm+eM8Bbt5qTMh+UwUZO8BTK2dq1V0Nila+gBTrK2Mcoi2R13AjYGvCwWW1u0XtHkDQ+xK1wMouQFMfdaTUfEcEYdhcdP17uq9ZuTw0POzubCogz8kkTnCmSWpXVnKpJma0VVar2WxBizlkO2lLZgvkRBXw2HgRgZucPC2Al9mi45VzG2UFBNEeEDIcEYJjOMrwJGYF74AhEIJPWI0SafUSdNUPIASJ5XHddQ/i/LljnD8+wtHRGuTENyImyUfk/aCfUIRxmhMuX/wKXN7iWc94Gp580/XgvMVTb7sVn/6jP8Jz7/gLePd/eR8282WwPw8eHoetvx6X6Hpcf/7JWK2PwGCMKcLnr+DcekA49w34kwfux6XLJ3j8Dedw6zc8AV/+8lfgHHC62WIznxEFF0AE4WRKWG8SjtYZMTMSCMgSLj5nja5baAUFoCdkzHPUbb5BQYo5r9YpkrLEUHGpmoWd0zQFxLqFWmPfJDEJzDEj5ISge6/JVUBh75tcQpoTMpGmO5DtyykLn2MmwImzrKVX8GbOUQ2Fo31ygiqNWU/ZgqKwR67TYLFIrCBcxT2j+90NAPXApAh76+ii2mycYvX97fXtMxhVVpSkoeA6H+yjz63zhsrjq0moDRXAC55Vf3O3WKqmG/Pd64FL+0nNua+XbMbKsEtwJFQAsm+idsLaiKlVHRvwaIRaT4yLFaUKqd0w1z2W3ac5aFfmREZoUsdsgZqgcGEJ4dEChz0nrR86VNxcV2ZSBRgPBz50JF6cZ/edb9vamizqm3YEHNA7/p1Vh1b7sZS6zUpgqWER2ljm8dF7CmnYd0X7zf79uqJxZSKK06Arzcqcd8b7LGCyu7tMtkdam4yJmCgm1C6Xw1lNDloPNTlAq5lz7YvaN03fWXO6rmv7v3fuLcDc4nc1q9beGVnyR9nTjNp26dGpRkuPNe83/6GyJrZhIQBMJddNYc2F2TbvYmPshMSS+M4RIWTd6sseMTnMMWqkVNOXCoDxjvHA5Yvw/hIGD6xGh6OjNdYr2b4cvIcnr61xcG6E94QpbvGVL38O33jbjUA6wvHqKXjizTdhc3KKP/v0J+O66y/g8Tf+ADanE04uXcbRGDCeP8b6wnmk4RzScAwmj6OjI9x24ckY1ucRVudBFLS9CZcuXsaf/MmX8LkvfA6f/NSn8Tsf+BAevHyCaZ7r+HLto8jAdo6YYxCAkiWa7mZOSLlxQm3+piSLqOSz+II4oTPWMah0LJCQQZhiQs4JQfMxgUSsioO2xfSRrMnTHLFKA1LOSDEhqyaFoIkFhwEhJExzQkyahR0BEm9IhLGEdnOFErw5yZITemUGsu1EagqrRodV9GscEmPfPRyR1mUIEAYU9DS8ppkkFfioLCKtKRnIIA1uVkyjjfa8vFi1K/aXbMef8oIlvS9mVttOqZbVxbQYrQHWtBqVZuqzWjCVy/USsNK0JzUfl827nKv/ydeliYcXHQ/qtRlLLcZS02Eryg6wVr14J9wke6zbfVaLwqmuHLDnXbXUlWd5v/q6sEZLLFRaKrcLBGo/tITUl+X7dwFBnRHd3NjTb2eX/WH8z7qvKrH2w6K9Wq+mvrtaD1p8kqjcGdhN/oYafE0nUm/qafosc5cgEMZQuG+HrSQLKFxoFlpflFazc1apWyJtsgtIoizvN/5RxryGJNEjthpa9pfeuEhYxld0+pGHc9Nm+WGArM6eClpLS3YBYttxqGNYGKxrQGy1ERXs0sawMSAp4ETvU0BW2W8uj8hNHRIDxA4kuzuRii9LBLhmwJWILLloTcllBL9B8BfhPWEIhPVqhSF4SFRmiVSb0oxxXOO+rz6AQDPyHHD/6kHxHgVhHAOe/OSbsVof4+TyKbwL8E7MSjfecITP/O/P4ej4AqYp4fh4jfXRiHEtgcpEoAU8/rpjPOnmG/D/+6Yn4tue/Sw45/HRj30cf/zFe7CNsaP7ZhmG4r/kBoAGxAxE1Jgm7Y0l6G3mBsTUJ1pCPkcOTA6cSQO5xWbcZV5k5ZEOojHjLD4m2zkWq2iIASFIHSXz8YDVmDHFjOl0RkxCKynpDh/dFg2S/D0py5bnlDKGQbMay2m0eWgsvELtF9MGtVo+EwV1npTrO6bSg5RiHGrBCzMIGoFa8wY5Pc4N76TuWTbfRWsJGxsDnrUyZVflzqfwLGEYrRjp5eMeOdK20RY2yovKoq0EFKxafwMtFsMm5whLomjHrrZc0wClChcDFHsAxB6hsBQQpilhY7w6WrvCOXdagP48FZTbwuCzhFF1o63aGFNhy7MrAZWFUCM89ikNikzkXbBiArPmfulrs3zivj7s7bjLx9iLjcT3aY32v3d5+KHua1F4O7adcyoD7FiTwfUcZwlQqHlHEWnW1BLefqmmbFWdcoM5kNrtbVssqm0FMIv6Lru01KcypRJGWjUscoXTdkKOu2EvUK2aInWm6+bE7vX9vQmyE4mEIRGEcTYAgsz8Uui/EXLlt9xrQnB3VVXprStkfWnvauaEkq5pTxZUXMBaAVAkcy9DkuYlAzVcdzjITgQFWoXxWgh/hqMEInHGFcfhUwwhiF+LC4D6XTBnDA5YhREnc8BXL13CaiCs1oT0wAZHRwPgZ3z14v244foLGMYAcoyUE8ZhEC2ARmEVc5STKKyUwSnDMWFcDVivr8N1F67Dy1/6Enzhi3+C//gbv4l3/f/fh9Nt7EaWAAQvAdu8D4gZ2MSIbeSSdI81CKHlr5LxE4ASU4RL4pxKCjRsvFPO8NlhTpJXiXNCCEGEUSv0y44zIGXxa5nmiDA4eEqah4hrrBTvMY4rDHMGbZLkJcoZU/SYIiEmp/spzVlZVu4pR6XbgF0fvUZot2dabGA0t3c2tXTdfm/9p0ygN9+V8uT1Gs24gJcemJj5xrKoCxZYzBWuAGs5l8SpeVdjITxvt1WGe4Q3LNu3NNnUtB85pwaI9KBEzmnUYa5yOF+FhtzKNQ1QOiZbgEoP/KwsnV/lPtcNnhy37cMLAFPgpQrVlrBJXarKoyrTL85WHaeg+iioicfqRyTOYNwz205I7wEgBXvXfx6yLNvePqslfrQrDW7btyTyXjjXx1chvu/3Tm33DeCy3jYR912QsvhKZNoVdmABHUXt2INBAzaAxrPgLHlB9G919qpmnwqQ2i290r4lQBEQU4G0rRTtN5f2V0Bi5ousv0npSbo7q5JDIoSSxSVfFItXkwtAkffUfDmm+Wihs14DoEQ/tvF36gxbBL+AAd6JwFoBCusDmLLK/aqitma3Y7GrfVxEBLX7y9hVkFwiFVekqJ9GVLD4QkRIhDJSoVUpu6HxQrqqqm9IWMYwwTsWtT8lsJOtsN4BgTICJayC7CQaB8JXLmecW3sEPABOEQ9eAo6PT/G4G44lAJsf8eDJKbzfIoKxjkCEhvAPhBwjPEX45ACKYHJYBcbTnnoLXvDc5+B9v/N+ST6YTNoygiOJwrtaYzWu4F3APM/ILGOX1KGRFvQstAfEmOBchCfx02HnQBmISYwfwja8arFIUgrkZjqz+Wkpj6OMmDOmaQvvAQ/CHBN8jBo9eIDzsk3Ye48wrMCbhGmO2M4ZMQbkLJsNCtC38e0Eoc6XnZVQrZstq0pcp4696f3N9tnCDBUpt+YWO0cNmDAfkTKfm/NloQrj6wzZmqQm0i5EvNE7N/PKrumdUa0PqhYLzfP2SwnjiWUGFNCyC4C6xYWCW+YkzkFJ61/ShdACYF1duaYBChYNJjLm1Aavog6I7PODaB6o5w2g2IeBku/EhLkOpAoVYl9Wch04sdtBqGpx2xlUmiF/ywEC4NUz25ygqBBvqxJsAUltVrVpdq1r8MGuVqLxe2CdLgZSOnB0FnEt4Uy9nJr1gTy/N4Es1711OlW/HJskzurDrLZgbkdJ8VO/1bftF4BV5WiMo3mrMSxiUOM0VlYMXFcLYDP9NDKwNlCFrXozEMmqmjRcOBGIvOYM8ZVJ9Z0EY1Q1k7K0ubSomCFYAv8RC0BgX9vEKGPIDImAC9OcqKZJdwbB0U7gPZDVLRdASATJpaJgq26rZCDv8Uex+2zMbBVmDLqZwz0fNl+eXM7lastCSUtQ1ElevHRacEIG2NTEoH48ibMElSo7hzQwGtu7ChqrbegEAwowbcOvQ00doACSLoVzQHCE0SeMnjAEh0tbRnhwRiCWGB24hMEB4x9/FcNAWA3icDsOA7y/H6vVgHPHa6zXg2R09oTj9VoyPQ/iGJozcP6663F6+UGsHGHyJHH0MuDgJJsvZTifMa4IwyBOwkRQrT0hZsZg23K17yweDKuZJ2YgEMBpBrJDgISnT0nzR5Ps8JnmjO0UsVoprSODku2sAsgLr51nBigBSGCakeGwGgd4jnCZNDaLB1MCXEAmYMqMOWv0DRZtEjlJKuio5vSx6LPiv94D95ZXt3ijnYisvNJAS7s4kpNm+m2eWY7Ls8p8tWuhAl1njTE80vuqprRdCDXPLfWrvMmut/xNmbkcMpBpJeXdhV1L06hPVyDDmktun6YkI3OEREWJstvKdoNlRk7yTHPA/roy8exLPkRkaLbTP+i5XWfXxROb8675LjPYhF1nthFJhEx7Arf1i2nIKNPOqbaai6jlUMpt6lweVoWs3WIgDKirgLad3EyyZfuLytPeXUOZ17+1L7FsK/rzHaaxvzsg0aboWaCnrecSwat5pXAWu4OLOmivqaiYanIFBqU1+r6yekRhRpnV6StXJ7AWHC/VofJM2fHjyMtuBnUYhHPijKnxQ8hAxqJviw9FWRnlytgMGHd9l8GJwU0iPsE5tY5WT/MHgGrwGA6U9GkNWmqdxosa21qnQLBkvzPgRT0ANfoRMGIh7iswKZrQQv/cdEXu6IMaGpLRNnBis2Ax9uRqPcGNhYrK9sfqBF2/c0NvMCat3bKkV8sJYyHXnQtwGnU1O4JjRmbZeTJnRogsAcnAIJZw99SNdyoxdixkOznG6AnrIWAcPY5WA86fO8LxeoVzRyscHx/h+HjE8emMTB63PulWXN7M2GxmTNsZeU7gtAWck+SEmZCyRKl1LgBIAvjgQN7DhYA8A+QCcp6BMvSu1jQzmCO8D7rgz4g6AjklxJwRgsO49iDyAFswYCf5eYagfiSym4c2k+zOYcl7E4L0E7OTXEHZBB1KUkOj4QzRiDvdqux1N08hA+zy+/18cI+QlovK5gWhj1wdcA0MlCBoudJ3AyYMtNj9PZPstRIGZKq2ogLn5ce0Ji1oMFi01FgwizlvWZZ9QaRuvXZ/rs9fvsv8TZL6ACHnLo9S5iyb/5v6Xm25tgGK2sFalbaBB2YTVJVptdcAwBKo1IBPtHO+aFYaodc+nWxbg91jjLYAmfIPevCzbBQ0jbX95G4ht3P5vkkGi+7XXFOYft4h2FrBdjI12WYbcFIB0pJJ057r9zOF3ILEs5vW1SerIxYVcFKFy/I9tPhSQZYJwupL0r6j+F82grbUObcq1NwBlLLrAcZMLI2BxSjxZQsqqeqfKOlf6uuMSjLEymaIm/daFdW80qi3C4Bumi/31fY3b9H7ZSypycDcDgo1XnWV+UJJ3fwJUqOpSlXdbvVsmWQj4FsmWxh3iX9fr+9AX3mumdN2aa/zDevGGIDawqHjZjRkjLdEwbQ8OHsYd9su+Z7FnOgYLmv8D58094zEKPGcJGZMsp43U139SHj5BHAEWLZGE0jjgoiJZqAoGhnvMIQHJQFf8Dg+WuG6cwOOj1dI0eGbnv6tON1sMU0zpu2EOG3BKcK7hOvWAWE9YMqSMoApIPOmCHjnLay9OP2Ko2ZWNivjPM9Jsjo4MeWklAXImnZRTWabyWO9jbKjRqkzqOnF+QBV6yDlhM00Y86sgZIdxjQKQCGvW7pN8DrtMgeJQeMrbdowoy/FAbgpZwGW9ncH6hcAgqGLYZZFQ27OyU4Zq5O02wBLT5u6ROtAcdWIdDtjgEKnDwVSJE8Qde0o7TpDg7Kkdcs1VHhczh0fFFBiviaNCdySXBpIaQDK15kGpRE4++zu9q/5lVBrWEHRAgPKNEuETp2Gujhs3og2qBsWAEfMQFS0OAZYanAqeSlZhmCcIaD5jONW7Y4B9wy/HGyPcbkQO4KKy921Nrz/7csJ3NSoIe6mVXuBkFXjytCkuVIJOxXzgJhospp48s4EpD3P7gWOCft+N0sFNqIdcOTL/Vl9UPptc1lXFtwdY3OEI41i6QeAWYNWecCJKcDpX+3BWg8SUwuhBT1mzqIaspuqOaUFKJnNLLNfy9Ob10RTVrUMfd+3lFgYp8BmoeMFYDDtzY7zr9bD6Qo8N8+XR3Kpb6VR/TDKTr0E84+oDutVkyNm7yXwF0tYD2IqaCe0OAFQ3wkG+uBwyg+Kr0NjDqNW/0EKfrK52squFQeYY3F5ql5nH1mxRnCegQaMMlgjrTqN5+JKtNzBE7wjjMMJVsGyFo84Ovc4HJ0HMsfiH5DTDHDCoH4xKWYcuxk3YEKkAatxwDRtIX5NLNtufYAjj3H0YtKBw3ajW3YZGIME6yMmOCY1H2junJSBzVZ3OKHk6knODNczfAjF1EkQ14XtFOHcDKzkHJwT7Qmr/5aFSyeUyM07WbwbflQBxkPzteX35fzpNBpGlwouMoA+emoLtoXii8xC9Xep6YQa8GG8zrS9ubZlB5ywBUNrAIAqFitd1zZlnUvL48vvuQVUZjrKxgdZAUnVlKQkmpOlBoWRxc/JgNRjHaBYB87zFoYDWsfD9q8AArc41nynlgHVQRLHRWEv5hC4c689f9/yt5yrPjBlpwMMKJEyvWULa5079G0TBf3e8joZDRhkkAoKAXANKuZUWW4DstDsSDGF864GqQrQM0sDUNqVwpI17DZ5AfZQBZYxhcwZxAk5Td1KwkJwO+yfaLx4DpAqOCHontNaDxH6roxVERONKYDRaE4aIWPvcE5Xoi4AnDFzgteU8KyOgiZYC6hTruEK2KhginMSQYvGZLEIrW/9xjt9x0XYwYRr8wwUAd7T8s7Ki3W7o/YJ2463bhjdzlzZB2yXwqKlyW41zDpXjFkunt3Oc2n2QvtJqNqwouVhiT6bJW8IGqa7bPdSA2TgbtlGc9AEgIQkmgGdwyWVpM5119Q7J9mRI2OUkHlSG34qYyaPpjJ2orfS6B8keXEklL8XR9whYD2O4pti0V0HDwwDmEXzQcRYrz3W13n49QnG4+uw2ZwgxYjt9hTnz53DPEVsTk/x5CfdggsXrsf/86lPIfGE22+7DRcvXhShhYin3f5UfPnLf4KvfvVP8MUv/rEeJ8TEiEnNNjnjaJCdTt6Lr8scGSEk9eEJ8F76LE4ZU9pimoHgA1wYAHLYRsYUxbE2JmA7zcjOyY4f75BSxHa7RQgbACQ7i3yoiSDdflrsabw/tgsIGo1GXjoSmGa11VLnshTgVnvNphlnCT7HVQtiSLuAj4VDqlwrczyjaqxE+EsbqnlmCURQ/EHKvFn0Qdvu3MzDFqCYr0lmTeaYM1Ke5XvKyApW5BlJN8rZM9Led+4rxFdz1aOsfOYzn8HTnva0R7oah3Ioh3Ioh3Ioh/KnKJ///Ofx5Cc/+YrXXJMalBtvvBEA8LnPfQ4XLlx4hGtzKBcvXsRTnvIUfP7zn8f111//SFfn67ocxuLRUw5j8egph7F49BRmxoMPPohbb731Ia+9JgGKxY24cOHCgdgeReX6668/jMejpBzG4tFTDmPx6CmHsXh0lKtVLOx6lh7KoRzKoRzKoRzKoTzC5QBQDuVQDuVQDuVQDuVRV65JgLJarfDzP//zWK1Wj3RVDgWH8Xg0lcNYPHrKYSwePeUwFtdmuSZ38RzKoRzKoRzKoRzKY7tckxqUQzmUQzmUQzmUQ3lslwNAOZRDOZRDOZRDOZRHXTkAlEM5lEM5lEM5lEN51JUDQDmUQzmUQzmUQzmUR125JgHKv/yX/xLf+I3fiPV6jec+97n40Ic+9EhX6TFV3vjGN+Lbvu3bcN111+Gmm27C93//9+OTn/xkd81ms8HLX/5yPP7xj8f58+fxgz/4g7j33nu7az73uc/hRS96EY6Pj3HTTTfhp37qpxBj/Fo25TFX3vSmN4GI8KpXvaocO4zF17Z84QtfwN/4G38Dj3/843F0dIRnPetZ+MhHPlLOMzP+4T/8h3jiE5+Io6Mj3Hnnnfj0pz/dPeO+++7DXXfdheuvvx433HAD/s7f+Tu4dOnS17op13RJKeG1r30tbr/9dhwdHeFpT3sa/vE//sc7+aMOY3ENF77Gyjvf+U4ex5H/1b/6V/wHf/AH/NKXvpRvuOEGvvfeex/pqj1mygtf+EJ++9vfzh//+Mf5Yx/7GH/P93wP33bbbXzp0qVyzY/+6I/yU57yFH7ve9/LH/nIR/gv/sW/yM9//vPL+RgjP/OZz+Q777yT/8f/+B/827/92/yEJzyBX/Oa1zwSTXpMlA996EP8jd/4jfxn/+yf5Ve+8pXl+GEsvnblvvvu46c+9an8t/7W3+K7776bP/OZz/B/+S//hf/X//pf5Zo3velNfOHCBf71X/91/r3f+z3+q3/1r/Ltt9/Op6en5Zrv+q7v4j/35/4c/+7v/i7/t//23/ibv/mb+Yd/+IcfiSZds+X1r389P/7xj+ff+q3f4s9+9rP8q7/6q3z+/Hn+xV/8xXLNYSyu7XLNAZRv//Zv55e//OXld0qJb731Vn7jG9/4CNbqsV2+9KUvMQB+//vfz8zM999/Pw/DwL/6q79arvnDP/xDBsAf/OAHmZn5t3/7t9k5x/fcc0+55i1veQtff/31vN1uv7YNeAyUBx98kJ/+9Kfze97zHv5Lf+kvFYByGIuvbfmZn/kZ/o7v+I4zz+ec+ZZbbuF//s//eTl2//3382q14n//7/89MzN/4hOfYAD84Q9/uFzzrne9i4mIv/CFL/zfq/xjrLzoRS/iv/23/3Z37K/9tb/Gd911FzMfxuKxUK4pE880TfjoRz+KO++8sxxzzuHOO+/EBz/4wUewZo/t8sADDwCoSRo/+tGPYp7nbhye8Yxn4Lbbbivj8MEPfhDPetazcPPNN5drXvjCF+LixYv4gz/4g69h7R8b5eUvfzle9KIXdX0OHMbia11+4zd+A3fccQd+6Id+CDfddBOe/exn45d/+ZfL+c9+9rO45557uvG4cOECnvvc53bjccMNN+COO+4o19x5551wzuHuu+/+2jXmGi/Pf/7z8d73vhef+tSnAAC/93u/hw984AP47u/+bgCHsXgslGsqWeCXv/xlpJQ6RgsAN998M/7oj/7oEarVY7vknPGqV70KL3jBC/DMZz4TAHDPPfdgHEfccMMN3bU333wz7rnnnnLNvnGyc4dy9eWd73wn/vt//+/48Ic/vHPuMBZf2/KZz3wGb3nLW/DqV78aP/dzP4cPf/jD+Imf+AmM44iXvOQlpT/39Xc7HjfddFN3PoSAG2+88TAeD6P87M/+LC5evIhnPOMZ8N4jpYTXv/71uOuuuwDgMBaPgXJNAZRD+dqXl7/85fj4xz+OD3zgA490Vb4uy+c//3m88pWvxHve8x6s1+tHujpf9yXnjDvuuANveMMbAADPfvaz8fGPfxxvfetb8ZKXvOQRrt3XV/kP/+E/4B3veAd+5Vd+BX/mz/wZfOxjH8OrXvUq3HrrrYexeIyUa8rE84QnPAHe+50dCvfeey9uueWWR6hWj93yile8Ar/1W7+F//pf/yue/OQnl+O33HILpmnC/fff313fjsMtt9yyd5zs3KFcXfnoRz+KL33pS/gLf+EvIISAEALe//73481vfjNCCLj55psPY/E1LE984hPxrd/6rd2xb/mWb8HnPvc5ALU/r8SjbrnlFnzpS1/qzscYcd999x3G42GUn/qpn8LP/uzP4sUvfjGe9axn4W/+zb+Jn/zJn8Qb3/hGAIexeCyUawqgjOOI5zznOXjve99bjuWc8d73vhfPe97zHsGaPbYKM+MVr3gFfu3Xfg3ve9/7cPvtt3fnn/Oc52AYhm4cPvnJT+Jzn/tcGYfnPe95+P3f//1u8r/nPe/B9ddfv8PgD+Xs8p3f+Z34/d//fXzsYx8rnzvuuAN33XVX+X4Yi69decELXrCz5f5Tn/oUnvrUpwIAbr/9dtxyyy3deFy8eBF33313Nx73338/PvrRj5Zr3ve+9yHnjOc+97lfg1Y8NsrJyQmc60WY9x45ZwCHsXhMlEfaS/fhlne+8528Wq34X//rf82f+MQn+GUvexnfcMMN3Q6FQ/n/Vn7sx36ML1y4wL/zO7/DX/ziF8vn5OSkXPOjP/qjfNttt/H73vc+/shHPsLPe97z+HnPe145b1tb/8pf+Sv8sY99jN/97nfzN3zDNxy2tv4fKO0uHubDWHwty4c+9CEOIfDrX/96/vSnP83veMc7+Pj4mP/dv/t35Zo3velNfMMNN/B//s//mf/n//yf/H3f9317t7Y++9nP5rvvvps/8IEP8NOf/vTD1taHWV7ykpfwk570pLLN+D/9p//ET3jCE/inf/qnyzWHsbi2yzUHUJiZf+mXfolvu+02HseRv/3bv51/93d/95Gu0mOqANj7efvb316uOT095R//8R/nxz3ucXx8fMw/8AM/wF/84he75/zv//2/+bu/+7v56OiIn/CEJ/Df+3t/j+d5/hq35rFXlgDlMBZf2/Kbv/mb/MxnPpNXqxU/4xnP4Le97W3d+Zwzv/a1r+Wbb76ZV6sVf+d3fid/8pOf7K75yle+wj/8wz/M58+f5+uvv55/5Ed+hB988MGvZTOu+XLx4kV+5Stfybfddhuv12v+pm/6Jv77f//vd1vnD2NxbRdibsLuHcqhHMqhHMqhHMqhPArKNeWDciiHciiHciiHcihfH+UAUA7lUA7lUA7lUA7lUVcOAOVQDuVQDuVQDuVQHnXlAFAO5VAO5VAO5VAO5VFXDgDlUA7lUA7lUA7lUB515QBQDuVQDuVQDuVQDuVRVw4A5VAO5VAO5VAO5VAedeUAUA7lUA7lUA7lUA7lUVcOAOVQDuVQDuVQDuVQHnXlAFAO5VAO5VAO5VAO5VFXDgDlUA7lUA7lUA7lUB515QBQDuVQDuVQDuVQDuVRV/5f2vojQup/W18AAAAASUVORK5CYII=\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "plt.imshow(cv.cvtColor(img_color, cv.COLOR_BGR2RGB))\n", - "plt.show()\n", - "\n", - "plt.imshow(cv.cvtColor(img_gray, cv.COLOR_BGR2RGB))\n", - "plt.show()\n", - "\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "4c68b2a4-db47-41e6-9c69-f6632decc517", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-fe00931e2364ad4d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "Next, we aim at learning the following:\n", - "\n", - "* Access pixel values and modify them - pixel values can be accessed via the rows and column coordinates. For RGB image, an array of Red, Blue and Gree are returned, whereas, for grayscale image only the corresponding intensity is returned\n", - "* Access image properties - shape, size, and data type \n", - "* Set a Region of Interest (ROI)" - ] - }, - { - "cell_type": "markdown", - "id": "227cbd20-2598-46ce-9fa0-1962cf8acc9e", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3965c065698f1c03", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Exercise 2\n", - "\n", - "Perform the following tasks:\n", - "* Access only the blue pixels\n", - "* Access only the red pixels\n", - "* Access olny the green pixels\n", - "* Modify the above selected pixel colors \n" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "3252309c-8e95-49b2-8442-0b3b3d84771d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f0a051e9b4f746a6", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[ 71 123 160]\n", - "71\n", - "123\n", - "160\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "# Accessing pixels in image\n", - "img_color = cv.imread(file_name, 1)\n", - "px = img_color[200, 200]\n", - "print(px)\n", - "\n", - "blue = img_color[200, 200, 0]\n", - "print(blue)\n", - "\n", - "green = img_color[200, 200, 1]\n", - "print(green)\n", - "\n", - "red = img_color[200, 200, 2]\n", - "print(red)\n", - "\n", - "img_color[0:100, 0:100] = [0, 0, 0]\n", - "\n", - "plt.imshow(cv.cvtColor(img_color, cv.COLOR_BGR2RGB))\n", - "plt.show()\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "6e5ea468-2ca4-4c2d-a81b-ed8fb686555f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f5ada7ce3c854693", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Exercise 3\n", - "\n", - "Accessing image properties:\n", - "* Print the shape, size, and data type of the image " - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "6ab1b9a5-46c0-4af9-a497-3c334c4869a3", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-92bdb9c1098eb969", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(666, 1000, 3)\n", - "(666, 1000)\n", - "1998000\n", - "666000\n", - "uint8\n", - "uint8\n" - ] - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "# image shape\n", - "print(img_color.shape)\n", - "print(img_gray.shape)\n", - "\n", - "# total number of pixels\n", - "print(img_color.size)\n", - "print(img_gray.size)\n", - "\n", - "# data type\n", - "print(img_color.dtype)\n", - "print(img_gray.dtype)\n", - "\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "587f2993-b5d6-4177-8337-78e18e86e08f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-54e3c13c8ffcd289", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Exercise 4\n", - "\n", - "It might be required in some task to select and modify a specific region of the image. For example, in eye detection tasks, first face detection is performed over the entire image and then eyes are searched for in this specific region, instead of the entire image. Thefore, the task here is to select only the face of the Fox and display it. " - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "43cdabd6-a75c-4918-9fcd-8f7a5773c10b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-48fe936535ea0e96", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "# ROI can be accessed using numpy indexing\n", - "fox_face = img_color[90:300, 170:340]\n", - "plt.imshow(cv.cvtColor(fox_face, cv.COLOR_BGR2RGB))\n", - "plt.show()\n", - "\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "376e3c0f-3478-4022-99ee-6c05601a9b03", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b94f847d591245f4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Image Transformation\n", - "## Image Rescaling\n", - "\n", - "Next we learn how to resize an image, which refers to the scaling of images. Scaling images is useful in many image processing as well as machine learning applications. It helps in reducing the number of pixels from an image and that has several advantages: \n", - "\n", - "* It can reduce the time of training of a neural network that reduces the number of pixels, thus, reducing the size and complexity of the image. \n", - "* It also helps in zooming in on images. \n", - "\n", - "Many times we need to resize the image i.e. either shrink it or scale it up to meet the size requirements. OpenCV provides us several interpolation methods for resizing an image.\n", - "\n", - "**Syntax:** cv2.resize(src, dsize[, dst[, fx[, fy[, interpolation]]]]))\\\n", - "**Parameters:** \\\n", - "**src:** [required] source/input image. \\\n", - "**dsize:** [required] desired size for the output image. \\\n", - "**fx:** [optional] scale factor along the horizontal axis. \\\n", - "**fy:** [optional] scale factor along the vertical axis. \\\n", - "**interpolation:** could be one of the following values \n", - "1. INTER_NEAREST - a nearest-neighbor interpolation \n", - "2. INTER_LINEAR - a bilinear interpolation (used by default) \n", - "3. INTER_AREA - resampling using pixel area relation. It may be a preferred method for image decimation, as it gives more-free results. But when the image is zoomed, it is similar to the INTER_NEAREST method.\n", - "4. INTER_CUBIC - a bicubic interpolation over 4×4 pixel neighborhood \n", - "5. INTER_LANCZOS4 - a Lanczos interpolation over 8×8 pixel neighborhood" - ] - }, - { - "cell_type": "markdown", - "id": "c1e470ab-8ee3-4724-8a5f-69f393986e0c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-51b9173689788391", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Exercise 5\n", - "\n", - "* Define a variable scale_percent that will hold the percentage by which the image should be down scaled. \n", - "* Use this variable to change the width and height of the image to downscale the image. You are free to use any interpolation technique. It is recommened to try all to understand their effects. \n", - "* Print the original and downscaled dimensions of the image and display the images using imshow method. " - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "44402f44-af93-4ece-883e-850d8310dbef", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-cb3c972bc4970a07", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Original image dimensions: (666, 1000, 3); Scaled Down image dimensions: (133, 200, 3)\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "scale_percent = 0.2\n", - "scaled_down_img = cv.resize(img_color, None, fx= scale_percent, fy= scale_percent, interpolation= cv.INTER_AREA)\n", - "print(f'Original image dimensions: {img_color.shape}; Scaled Down image dimensions: {scaled_down_img.shape}')\n", - "\n", - "plt.imshow(cv.cvtColor(img_color, cv.COLOR_BGR2RGB))\n", - "plt.show()\n", - " \n", - "plt.imshow(cv.cvtColor(scaled_down_img, cv.COLOR_BGR2RGB))\n", - "plt.show()\n", - "\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "f8f19a89-4862-4a6e-8e43-ef19b7ec74eb", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-eebd0c890bf179a2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Exercise 6\n", - "\n", - "Similarly, \n", - "* Define a variable \"scale_percent\" that will hold the percentage by which the image should be upscaled. \n", - "* Use this variable to change the width and height of the image to upscale the image. You are free to use any interpolation technique. It is recommened to try all to understand their effects. \n", - "* Print the original and upscaled dimensions of the image and display the images using imshow method. " - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "410c49df-1034-411d-8617-6fb990c97fec", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-710777ab9179613f", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Original image dimensions: (133, 200, 3); Scaled Down image dimensions: (266, 400, 3)\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "scale_percent = 2.0\n", - "scaled_up_img = cv.resize(scaled_down_img, None, fx= scale_percent, fy= scale_percent, interpolation= cv.INTER_LINEAR)\n", - "print(f'Original image dimensions: {scaled_down_img.shape}; Scaled Down image dimensions: {scaled_up_img.shape}')\n", - "\n", - "plt.imshow(cv.cvtColor(scaled_up_img, cv.COLOR_BGR2RGB))\n", - "plt.show()\n", - "\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "606901ca-5f3d-4b19-a99f-95aab2424b75", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d76f038a390ce80b", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Image Translation and Rotation\n", - "\n", - "In addition to rescaling, the location of an object can be shifted or the image can be rotated. The documentation for the translation or rotation of the image can be found at: \n", - "https://docs.opencv.org/4.x/da/d6e/tutorial_py_geometric_transformations.html " - ] - }, - { - "cell_type": "markdown", - "id": "c28e95b1-1d4b-4962-98b9-cfef4fbb36b1", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-78e5903549ae7f5a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Exercise 7\n", - "\n", - "Following the documentation provided above, translate and roate the image and use the imgshow function to diplay these effects. " - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "03f84aca-56df-44c0-af2a-eb6a708c0dd2", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-f046a6dd0d760f54", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "rows, cols, colors = img_color.shape\n", - "\n", - "# The warpAffine() function applies an affine transformation to the image. \n", - "# After applying affine transformation, all the parallel lines in the original image will remain parallel in the output image as well.\n", - "translation_m = np.float32([[1,0,250],[0,1,50]])\n", - "translated_img = cv.warpAffine(img_color,translation_m,(cols,rows))\n", - "plt.imshow(cv.cvtColor(translated_img, cv.COLOR_BGR2RGB))\n", - "plt.show()\n", - "\n", - "# You need the center of the image to roate it\n", - "rotation_m = cv.getRotationMatrix2D(((cols-1)/2.0,(rows-1)/2.0),45,1)\n", - "rotated_img = cv.warpAffine(img_color,rotation_m,(cols,rows))\n", - "plt.imshow(cv.cvtColor(rotated_img, cv.COLOR_BGR2RGB))\n", - "plt.show()\n", - "\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "fd0e2f9d-1461-48d5-a8ca-611826588e01", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a11ec638f35fe058", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Image Filtering\n", - "\n", - "Changing the appearance of an image by altering the color of the pixels is known as image filtering. This enables to emphasize certain features or remove other features. For example, a low pass filter (LPF) helps in removing noise from the image, blurring the image, etc, whereas, a high pass filter (HPF) helps in finding edges in the image. OpenCV provides a function cv.filter2D to convolve a kernel with an image, where a kernel is a 2D matrix. \n", - "\n", - "If you're not familiar what convolution is, you can watch the video under the following link: \\\n", - "https://www.youtube.com/watch?v=KuXjwB4LzSA&ab_channel=3Blue1Brown\n", - "\n", - "**Syntax:** filter2D (src, dst, ddepth, kernel) \\\n", - "**Parameters:** \\\n", - "**Src** – The source image to apply the filter on \\\n", - "**Dst** – Name of the output image after applying the filter \\\n", - "**Ddepth** – Depth of the output image [ -1 will give the output image depth as same as the input image] \\\n", - "**Kernel** – The 2d matrix we want the image to convolve with " - ] - }, - { - "cell_type": "markdown", - "id": "0d796561-1bf8-483a-8400-ee8816fb440b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-bc806435dbd4c922", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Exercise 8\n", - "\n", - "To apply a filter to an image, the kernel should be first defined. Perform the following:\n", - "1. Define multiple kernel - identity, edge detection, box blur and Gaussian blur\n", - "2. Apply these kernels to the image and display the images\n", - "\n", - "**Idendity Kernel -** \n", - "$$\\begin{bmatrix} 0 & 0 & 0 \\\\ 0 & 1 & 0 \\\\ 0 & 0 & 0 \\end{bmatrix}$$\n", - "\n", - "**Edge detection Kernel -** \n", - "$$\\begin{bmatrix} -1 & -1 & -1 \\\\ -1 & 8 & -1 \\\\ -1 & -1 & -1 \\end{bmatrix}$$\n", - "\n", - "**Box Blur Kernel -** \n", - "$$\\frac{1}{9}\\begin{bmatrix} 1 & 1 & 1 \\\\ 1 & 1 & 1 \\\\ 1 & 1 & 1 \\end{bmatrix}$$\n", - "\n", - "**Gaussian Blur Kernel -** \n", - "$$\\frac{1}{256}\\begin{bmatrix} 1 & 4 & 6 & 4 & 1 \\\\ 4 & 16 & 24 & 16 & 4 \\\\ 6 & 24 & 36 & 24 & 6 \\\\ 4 & 16 & 24 & 16 & 4 \\\\ 1 & 4 & 6 & 4 & 1 \\end{bmatrix}$$" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "50d6574f-f75c-42d5-9700-80e231b0569e", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-61a1634d1981db99", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - 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\n", 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\n", 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "\n", - "# will have no effect on the image\n", - "idendity_kernel = np.array([[0, 0, 0],\n", - " [0, 1, 0],\n", - " [0, 0, 0]])\n", - "\n", - "# detects the edges in the image\n", - "edge_dect_kernel = np.array([[-1, -1, -1],\n", - " [-1, 8, -1],\n", - " [-1, -1, -1]])\n", - "\n", - "box_blur_kernel = np.ones((3, 3), np.float32)/9\n", - "\n", - "gaussian_blur_kernel = (1/256) * np.array([\n", - " [1, 4, 6, 4, 1],\n", - " [4, 16, 24, 16, 4],\n", - " [6, 24, 36, 24, 6], \n", - " [4, 16, 24, 16, 4], \n", - " [1, 4, 6, 4, 1]])\n", - "\n", - "img_1 = cv.filter2D(src=img_color, ddepth=-1, kernel=idendity_kernel)\n", - "img_2 = cv.filter2D(src=img_color, ddepth=-1, kernel=edge_dect_kernel)\n", - "\n", - "# Box blur and Gaussian Blur have similar effects\n", - "img_3 = cv.filter2D(src=img_color, ddepth=-1, kernel=box_blur_kernel)\n", - "img_4 = cv.filter2D(src=img_color, ddepth=-1, kernel=gaussian_blur_kernel)\n", - "\n", - "plt.imshow(cv.cvtColor(img_color, cv.COLOR_BGR2RGB)),plt.title('Original')\n", - "plt.show()\n", - "\n", - "plt.imshow(cv.cvtColor(img_1, cv.COLOR_BGR2RGB)),plt.title('Idendity Kernel')\n", - "plt.show()\n", - "\n", - "plt.imshow(cv.cvtColor(img_2, cv.COLOR_BGR2RGB)),plt.title('Edge Detection Kernel')\n", - "plt.show()\n", - "\n", - "plt.imshow(cv.cvtColor(img_3, cv.COLOR_BGR2RGB)),plt.title('Box Blur Kernel')\n", - "plt.show()\n", - "\n", - "plt.imshow(cv.cvtColor(img_4, cv.COLOR_BGR2RGB)),plt.title('Gaussian Blur Kernel')\n", - "plt.show()\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "88629f82-dd58-4c18-81e4-2629e12ff5b8", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1f5e6ff25f2d107f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Exercise 9\n", - "\n", - "In addition to the filter2D function, where a kernel needs to be explicitly defined, OpenCV also provides functions to filter the images. Read the documentation provided by OpenCV on the following functions:\n", - "* blur\n", - "* GaussianBlur, \n", - "\n", - "apply these filters to the image and display the images. " - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "0037c3b9-36f1-499d-aa32-adc0d52b9b32", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a5251d944ce8d9c1", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "blur = cv.blur(img_color,(5,5))\n", - "plt.imshow(cv.cvtColor(blur, cv.COLOR_BGR2RGB)),plt.title('Blur')\n", - "plt.show()\n", - "\n", - "gaussian_blur = cv.GaussianBlur(img_color,(5,5),0)\n", - "plt.imshow(cv.cvtColor(gaussian_blur, cv.COLOR_BGR2RGB)),plt.title('Gaussian Blur')\n", - "plt.show()\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "1731eddd-9ffc-48af-8429-e869fef5d705", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-de15c985fedd5592", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Data Processing - pandas\n", - "\n", - "Pandas is a python library commonly used for processing large data sets. It provides functions for analyzing, cleaning, exploring, and manipulating data and derive conclusions based on statistical theories. Furthermore, it enables cleaning up of messy data sets, making them more readable and relevant. Through the next few exercises, we will learn the basic functionalities of pandas. " - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "c87ada25-0a9c-4758-88c4-3872adde9d3a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2e3eb8ad4b829277", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Defaulting to user installation because normal site-packages is not writeable\n", - "Requirement already satisfied: pandas in /home/sid/.local/lib/python3.10/site-packages (1.5.2)\n", - "Requirement already satisfied: numpy>=1.21.0 in /home/sid/.local/lib/python3.10/site-packages (from pandas) (1.23.5)\n", - "Requirement already satisfied: pytz>=2020.1 in /usr/lib/python3/dist-packages (from pandas) (2022.1)\n", - "Requirement already satisfied: python-dateutil>=2.8.1 in /home/sid/.local/lib/python3.10/site-packages (from pandas) (2.8.2)\n", - "Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)\n" - ] - } - ], - "source": [ - "!pip install pandas" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "f1b1513b-3857-4989-ab04-b4ebdab10c13", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a2f64dd9099eb95c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "import pandas as pd" - ] - }, - { - "cell_type": "markdown", - "id": "0a581b23-b1c1-4cac-851b-53700353f218", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d72bf798024e6eab", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Exercise 10\n", - "\n", - "The first step is to learn to load the data. Here we focus on reading data in CSV format. Therefore, the first task is to read the provided CSV file (taken from the following link: https://web.stanford.edu/class/archive/cs/cs109/cs109.1166/problem12.html) via read_csv function. \n", - "\n", - "**Syntax:** pd.read_csv(filepath_or_buffer, sep=’ ,’ , header=’infer’, index_col=None, usecols=None, engine=None, skiprows=None, nrows=None) \\\n", - "**Parameters:** \\\n", - "**filepath_or_buffer:** It is the location of the file which is to be retrieved using this function. It accepts any string path or URL of the file. \\\n", - "**sep:** It stands for separator, default is ‘, ‘ as in CSV(comma separated values). \\\n", - "**header:** It accepts int, a list of int, row numbers to use as the column names, and the start of the data. If no names are passed, i.e., header=None, then, it will display the first column as 0, the second as 1, and so on. \\\n", - "**usecols:** It is used to retrieve only selected columns from the CSV file. \\\n", - "**nrows:** It means a number of rows to be displayed from the dataset. \\\n", - "**index_col:** If None, there are no index numbers displayed along with records. \\ \n", - "**skiprows:** Skips passed rows in the new data frame." - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "22e3b329-e0ac-45ab-b2fc-4f6759cb1ea7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ae9adc24b8a42cca", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "data = pd.read_csv('titanic.csv')\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "b8a54185-c6f8-4489-868e-1e12888d31ce", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-44333c9f0b61e36f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Exercise 11\n", - "\n", - "In the next task we want to explore the read data. Perform the following tasks:\n", - "* Use the head() function to display the first 5 rows of the data\n", - "* Use the tail() function to display the last 5 rows of the data\n", - "* Use the columns property to display the columns in the data\n", - "* Create a list with any six column names and create a new data frame (from the original) with only these columns\n", - "* Print the data type of each column\n", - "* Create a dictionary with new column names (simply capitalize all names) and change the name of the columns via rename() function \n", - "* Use the describe() function and print the count, mean, standard deviation, minimum, maximum, and quantile values. " - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "723046de-01e1-4fee-bcec-44be8c689725", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4d863ed6b2d93169", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Survived Pclass Name \\\n", - "0 0 3 Mr. Owen Harris Braund \n", - "1 1 1 Mrs. John Bradley (Florence Briggs Thayer) Cum... \n", - "2 1 3 Miss. Laina Heikkinen \n", - "3 1 1 Mrs. Jacques Heath (Lily May Peel) Futrelle \n", - "4 0 3 Mr. William Henry Allen \n", - "\n", - " Sex Age Siblings/Spouses Aboard Parents/Children Aboard Fare \n", - "0 male 22.0 1 0 7.2500 \n", - "1 female 38.0 1 0 71.2833 \n", - "2 female 26.0 0 0 7.9250 \n", - "3 female 35.0 1 0 53.1000 \n", - "4 male 35.0 0 0 8.0500 \n", - " Survived Pclass Name Sex Age \\\n", - "882 0 2 Rev. Juozas Montvila male 27.0 \n", - "883 1 1 Miss. Margaret Edith Graham female 19.0 \n", - "884 0 3 Miss. Catherine Helen Johnston female 7.0 \n", - "885 1 1 Mr. Karl Howell Behr male 26.0 \n", - "886 0 3 Mr. Patrick Dooley male 32.0 \n", - "\n", - " Siblings/Spouses Aboard Parents/Children Aboard Fare \n", - "882 0 0 13.00 \n", - "883 0 0 30.00 \n", - "884 1 2 23.45 \n", - "885 0 0 30.00 \n", - "886 0 0 7.75 \n", - "Index(['Survived', 'Pclass', 'Name', 'Sex', 'Age', 'Siblings/Spouses Aboard',\n", - " 'Parents/Children Aboard', 'Fare'],\n", - " dtype='object')\n", - " Survived Pclass Name \\\n", - "0 0 3 Mr. Owen Harris Braund \n", - "1 1 1 Mrs. John Bradley (Florence Briggs Thayer) Cum... \n", - "2 1 3 Miss. Laina Heikkinen \n", - "3 1 1 Mrs. Jacques Heath (Lily May Peel) Futrelle \n", - "4 0 3 Mr. William Henry Allen \n", - ".. ... ... ... \n", - "882 0 2 Rev. Juozas Montvila \n", - "883 1 1 Miss. Margaret Edith Graham \n", - "884 0 3 Miss. Catherine Helen Johnston \n", - "885 1 1 Mr. Karl Howell Behr \n", - "886 0 3 Mr. Patrick Dooley \n", - "\n", - " Sex Age Fare \n", - "0 male 22.0 7.2500 \n", - "1 female 38.0 71.2833 \n", - "2 female 26.0 7.9250 \n", - "3 female 35.0 53.1000 \n", - "4 male 35.0 8.0500 \n", - ".. ... ... ... \n", - "882 male 27.0 13.0000 \n", - "883 female 19.0 30.0000 \n", - "884 female 7.0 23.4500 \n", - "885 male 26.0 30.0000 \n", - "886 male 32.0 7.7500 \n", - "\n", - "[887 rows x 6 columns]\n", - "Survived int64\n", - "Pclass int64\n", - "Name object\n", - "Sex object\n", - "Age float64\n", - "Fare float64\n", - "dtype: object\n" - ] - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "print(data.head(5))\n", - "\n", - "print(data.tail(5))\n", - "\n", - "print(data.columns)\n", - "\n", - "cols = ['Survived', 'Pclass', 'Name', 'Sex', 'Age', 'Fare' ]\n", - "data_with_cols = data[cols]\n", - "print(data_with_cols)\n", - "\n", - "print(data_with_cols.dtypes)\n", - "\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "ee5ed60b-534b-43d6-a8f9-1d5f1c6cc47d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-08260af69b8d0603", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Index(['SURVIVED', 'PCLASS', 'NAME', 'SEX', 'AGE', 'SIBLINGS/SPOUSES ABROAD',\n", - " 'PARENTS/CHILDREN ABROAD', 'FARE'],\n", - " dtype='object')\n", - " SURVIVED PCLASS AGE SIBLINGS/SPOUSES ABROAD \\\n", - "count 887.000000 887.000000 887.000000 887.000000 \n", - "mean 0.385569 2.305524 29.471443 0.525366 \n", - "std 0.487004 0.836662 14.121908 1.104669 \n", - "min 0.000000 1.000000 0.420000 0.000000 \n", - "25% 0.000000 2.000000 20.250000 0.000000 \n", - "50% 0.000000 3.000000 28.000000 0.000000 \n", - "75% 1.000000 3.000000 38.000000 1.000000 \n", - "max 1.000000 3.000000 80.000000 8.000000 \n", - "\n", - " PARENTS/CHILDREN ABROAD FARE \n", - "count 887.000000 887.00000 \n", - "mean 0.383315 32.30542 \n", - "std 0.807466 49.78204 \n", - "min 0.000000 0.00000 \n", - "25% 0.000000 7.92500 \n", - "50% 0.000000 14.45420 \n", - "75% 0.000000 31.13750 \n", - "max 6.000000 512.32920 \n" - ] - } - ], - "source": [ - "### BEGIN SOLUTON\n", - "new_col_names = {'Survived': 'SURVIVED', 'Pclass': 'PCLASS', 'Name': 'NAME', 'Sex': 'SEX', 'Age': 'AGE', \n", - " 'Siblings/Spouses Aboard': 'SIBLINGS/SPOUSES ABROAD', 'Parents/Children Aboard': 'PARENTS/CHILDREN ABROAD', 'Fare': 'FARE' }\n", - "data = data.rename(columns=new_col_names)\n", - "print(data.columns)\n", - "# print(new_data.columns)\n", - "\n", - "print(data.describe())\n", - "\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "0ce1edb1-c5c1-44d2-9e0d-eee07cc1cbdd", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-62091a587f819a86", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Exercise 12\n", - "\n", - "Pandas provide a groupby() function to split the data into groups based on criteria, which provides a mapping of labels to group names. \n", - "* Group the data according to PCLASS and display the mean value\n", - "* Plot a bar graph of the returned dataframe" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "974c2a5f-d08e-4691-aefd-a9f96d0bf017", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5cc6c7dd8afe3d16", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " SURVIVED AGE SIBLINGS/SPOUSES ABROAD PARENTS/CHILDREN ABROAD \\\n", - "PCLASS \n", - "1 0.629630 38.788981 0.416667 0.356481 \n", - "2 0.472826 29.868641 0.402174 0.380435 \n", - "3 0.244353 25.188747 0.620123 0.396304 \n", - "\n", - " FARE \n", - "PCLASS \n", - "1 84.154687 \n", - "2 20.662183 \n", - "3 13.707707 \n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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nHVSrVg1mZmZo0qQJFi9ejIKCArHN33//DYVCgaSkJJ2aOnbsiIkTJ4qvT58+jV69eqFmzZowMzNDnTp1MHDgQNy+fVvSV1HT8ePH9X5PiuLu7g5TU1OdJxc/qffZ96V///64ceOGzv4+mezs7NChQwccOXJEp7979+5h4sSJqF27NkxMTODk5IQRI0bg5s2bRdYWHh4OQ0NDfPXVVzrLoqOjJZ/ZatWqwcvLC2FhYdBoNCXa95eB4YOIqiR/f3/8+eefWLNmDS5duoSYmBh07NgRd+/efe56YWFhSEtLw82bN7Fu3TocPnwYEyZMKFMtZmZmUKvVuHz58nPbTZs2DQMHDkTz5s0RExOD5ORkrF+/Hm+++SZCQ0PFdp9//jmWLFmCuXPn4vz58zh06BBGjRqlE4gKCgqwe/du9OrVC+fPn0e3bt3w9ttv4/Dhwzhz5gy+/fZbmJiYSEIDACQnJyM1NRVbtmzBuXPn0LNnT7HN9u3b0aFDB9SqVQuHDh3CxYsX8fHHH+OLL77AoEGDoO+zTO/cuYPOnTvDzs4O+/fvx4ULFxAVFQUnJydkZWVJ2h44cABpaWmSqWXLlnq9J0U5evQosrOz0a9fP6xZs6bINiNHjkRaWhpSU1Oxc+dOpKSkIDAwUKfdkxoPHz4MJycn9OjRAxkZGeLye/fuoXXr1jhw4AAiIiJw5coVbNy4EVeuXIGnp6dO0AOAyMhITJ06FZGRkUXWZmNjg7S0NPzzzz9ISEjAqFGjsHbtWjRv3hypqakv3P+XgaddiKjKyczMxJEjRxAXF4cOHToAAGrXro1WrVq9cF1ra2uoVCoAwBtvvIGhQ4diw4YNZaqnQYMGqFmzJj799FNs3ry5yDbHjx/HwoUL8c0330jCjouLC1q2bCn5Uo+JicHYsWPRv39/cV6zZs10+kxISICxsTE8PT3xzTffQKVSYeHCheLyunXrolu3bjrr1axZE7a2tnB0dMSsWbMwePBgXLlyBbVq1cLIkSPRq1cvrF69Wmz/4YcfwsHBAb169cLmzZsxcODAEr83v/32GzQaDX744QcYGT3+ynJ1dUWnTp102trb24v/N88q6XtSFLVajffffx8dOnTAxx9/jGnTpum0sbCwELft6OiIcePGYfTo0cXWqFKpMGPGDGzcuBEnTpxAr169AACffvopUlNTceXKFbE/FxcX7N+/H/Xq1UNwcDD27t0r9hcfH4/s7GyEhYVh7dq1SEhIQJs2bSTbVCgUkto8PDzQs2dPNGrUCFOnTsVPP/1UovehPPHIBxFVOVZWVrCyssKOHTuQm5tb6n5u3bqFXbt2wcvLq8w1LViwANu2bcOpU6eKXL5hwwZYWVlh7NixRS5XKBTiv1UqFQ4ePIg7d+48d5sxMTHo2bOn+OX05C9yfZibmwMA8vLy8Ouvv+Lu3bv45JNPdNr17NkT9evX1zuoqVQqPHr0CNu3b9f7qMmz/ZTkPXnW/fv3sWXLFgQGBqJLly7QaDRFnip52r1797B58+bnfi6ys7Oxdu1aAICJiQkAoLCwEBs3bsTgwYN1QpS5uTnGjh2L/fv34969e+J8tVqNgIAAGBsbIyAgAGq1ukT7VbNmTQwePBgxMTE6R7bkwPBBRFWOkZERoqOjsWbNGtja2qJt27aYMWMG/vrrrxeuO23aNFhZWcHc3By1atWCQqHA4sWLy1xTixYtMGDAgCL/qgaAS5cu4c033xT/+geAxYsXi0HKyspKPIe/ePFi3LlzByqVCk2bNsVHH30k+Wv5iZ07d4p/cffv3x8BAQHo0KEDHB0d0bdvXyxfvhxarbbYmtPS0rBo0SK88cYbaNCgAS5dugQA8PDwKLK9u7u72KakWrdujRkzZuD9999H9erV0b17d3z11VeSUxVPtGnTRvJ+WFlZictK+p48a+PGjahXrx4aNWoEQ0NDDBo0qMgv+JUrV8LKygqWlpawt7dHcnJykadBntRoaWmJRYsWoWXLlujcuTOAx6eYMjMzi33/PDw8IAgCrly5AgDQarXYunWreHonMDAQmzdvxoMHD164X8Dj/4/79++/8FTjy8DwQURVkr+/P1JTUxETE4Nu3bohLi4OLVq0QHR09HPXmzJlCpKSkvDXX38hNjYWAPDuu++Wy1+PX3zxBY4cOYJff/21RO1HjBiBpKQkfPfdd8jKyhKPDDRs2BBnz57F8ePHMWLECNy+fRs9e/bEhx9+KK574cIFpKamil98hoaGiIqKwj///IOFCxfijTfewPz589GoUSOkpaVJtlurVi1YWlqK4y62bdsm/vUOoExHKIoyb948pKenIyIiAo0aNUJERATc3d1x5oz0CqdNmzYhKSlJMj1RkvekKJGRkZKxG4GBgdiyZQvu378vaTd48GAkJSXh9OnTOHr0KNzc3NC1a1eddps2bcKff/6Jbdu2wc3NDdHR0TA2Npa0Ken7t2HDBtStW1c8fdS8eXPUrl0bmzZtKtH6T7bz9FEzuTB8EFGVZWZmhi5duuCzzz5DQkIChg0bhtmzZz93nerVq8PNzQ316tWDj48Pli5dioSEBBw6dKjM9dStWxcjR47E9OnTdb6A6tWrh2vXriE/P1+cZ2trCzc3N7zxxhs6fRkYGMDT0xMTJ07Ezz//jOjoaKjValy/fh3A41MuXbp0gZmZmWS9N954Ax988AGWL1+Oc+fOIScnBxEREZI2R44cwV9//QWtVoukpCTx9EL9+vUBPA42Rblw4YLYxsbGBgCKvOIiMzMTSqVSMs/e3h79+/fHokWLcOHCBTg5OWHRokWSNs7OznBzc5NM+rwnzzp//jyOHz+OqVOnwsjICEZGRmjdujUePnyIjRs3StoqlUpxm23bthUHED8bBJydnVGvXj307dsX8+fPR9++fcVTfzVq1ICtre1z3z+FQiHul1qtxrlz58TajIyMcP78+WIHnhbVn42NDezt7UvUvjwxfBAR/X8NGzbUuYLiRQwNDQE8PodfHmbNmoVLly7pfLkFBATgwYMHWLlyZan6bdiwIQCI+7dz50707t37uetUq1YNjo6OOu+Jq6sr6tatC2tra8n8rl27ws7ODl9//bVOXzExMbh8+TICAgIAAHZ2dqhevToSExMl7bRaLa5cuSKGlKKYmJigbt26ev9fPevZ9+RZarUa7du3x+nTpyVHU0JCQl44tqIkn4t+/frByMhI/D81MDDAgAEDsH79ep1LerOzs7Fy5Ur4+fnBzs4OZ86cwalTpxAXFyepLS4uDseOHcPFixefW9/t27exfv169OnTBwYG8kcBXu1CRFXO3bt30b9/f4wYMQJNmzaFtbU1Tp06hYULF77wC/n+/ftIT0+HIAhISUnB1KlTUaNGDZ0rDM6cOSP5clYoFCW6usLBwQEhISE692zw9vbG5MmTMXnyZNy4cQPvvfcenJ2dkZaWBrVaDYVCIX6J9OvXD23btkWbNm2gUqlw/fp1hIaGon79+nB3d8ft27dx6tQpxMTEiP1/9913SEpKQt++fVG3bl3k5ORg7dq1OHfuHL799tsX1g0AlpaW+O677zBo0CCMGjUK48aNg42NDWJjYzFlyhT069cPAwYMENuHhIRg/vz5cHBwQOvWrXH37l3MnTsXNWrUwHvvvQcA2L17NzZu3IhBgwahfv36EAQBu3btwi+//IKoqCjJ9u/evavzpW1rawszM7MXvifPys/Px48//oiwsDA0btxYsuzDDz/E4sWLce7cOTRq1AgA8PDhQ3HbGRkZmDt3LszMzNC1a9di3y+FQoEJEyZgzpw5GD16NCwsLDB//nzExsaiS5cuWLhwIRo3bozr169j5syZyM/Px4oVKwA8DkatWrVC+/btdfr19PSEWq0WP0OCIIif2czMTBw7dgzz58+HUqnEggULiq3vpRJeMRqNRgAgaDSaii6FSmj56NgyTVR5ZWdnC+fPnxeys7MruhS95OTkCNOnTxdatGghKJVKwcLCQmjQoIEwc+ZM4eHDh2K72rVrC0uWLJG8BiBONWrUEN555x3hzz//FNscOnRI0ubJZGhoKAiCIMyePVto1qyZ2P7Z14Lw+Pdg9erVBQDC9evXJcs2bdokdOzYUVAqlYKxsbFQq1Yt4f333xeOHz8utlm9erXQqVMnoUaNGoKJiYng4uIiDBs2TPj7778FQRCEH374QWjbtq2k3z/++EMIDAwUXF1dBVNTU8He3l5o3769EBMTo7Nv//7773Pf38OHDwt+fn6CjY2NYGJiIjRq1EhYtGiR8OjRI0m7R48eCcuWLROaNGkiWFhYCLVq1RIGDhwo2eerV68KI0eOFOrXry+Ym5sLtra2gqenpxAVFSW2uX79epHvOQBhw4YNJXpPnrV161bBwMBASE9PL3K5h4eHMGnSJEEQBKFDhw6SbVarVk3o0KGDcPDgQZ0an/6sCIIgZGVlCdWqVRO+/PJLcd6dO3eE8ePHC87OzoKxsbHg4OAgDBs2TLhx44YgCIKQm5sr2NvbCwsXLiyyti+//FKoWbOmkJeXJ0RFRYl1KRQKQalUCq1atRLCwsJK9T37vJ95fb6/FYJQziODykir1UKpVEKj0YjnBOnVtuKjg2VaPzjCp5wqIbnl5OTg+vXrcHV11Rk7QK+uXr16oV27dpg6dWpFl0KVzPN+5vX5/uaYDyKiKqZdu3bi2AuiisAxH0REVQyPeFBF45EPIiIikhXDBxEREcmK4YOIiIhkpVf4qFOnDhQKhc4UHBwM4PEo2ODgYNjb28PKygr+/v5F3n+fiIiIqi69wsfvv/+OtLQ0cfrvf/8LAOIjiidNmoRdu3Zhy5YtiI+PR2pqqnijGCIiIiJAz6tdatSoIXm9YMEC1K1bFx06dIBGo4Farcb69evh4/P4vg1RUVHw8PDA8ePH0bp16/KrmoiIiCqtUo/5yMvLw08//YQRI0ZAoVAgMTER+fn58PX1Fdu4u7vDxcUFx44dK7af3NxcaLVayURERESvr1Lf52PHjh3IzMzEsGHDAADp6ekwMTGBra2tpJ2Dg4POvfafFh4ejs8//7y0ZRDRK+qCu4es2/O4WPSTQIno1VPqIx9qtRrdu3eHk5NTmQoIDQ2FRqMRp5SUlDL1R0RUEsOGDRMHzZuYmMDNzQ1hYWF49OiRpJ2fnx8MDQ3x+++/P7cPY2NjuLq6YurUqcjJyZG0K2qgvkKhEJ9cGxcXB4VCgUaNGqGgoECyrq2tLaKjo8U2z5vi4uJQUFCABQsWwN3dHebm5rCzs4OXlxd++OEHnfqHDx+OmTNniq8PHTqEd955B/b29rCwsEDDhg0xefJk3Lp1S1JnZmamTl916tTB0qVLS/z6aX///bdkP6ytrdGoUSMEBwfj8uXLkrbR0dFiOwMDAzg6OmLgwIG4efOmpF3Hjh2LfI8++ugjyf+LmZkZbty4IVm3T58+4h/WL+Lu7g5TU9Mi/8h+tgYHBwf0799fsr1n993Ozg4dOnTAkSNHdPq7d+8eJk6ciNq1a8PExAROTk4YMWKEzr4/ER4eDkNDQ52HFALS99HQ0BDVqlWDl5cXwsLCoNFoSrTvZVGq8HHjxg0cOHAAH374oThPpVIhLy9P50OZkZEBlUpVbF+mpqawsbGRTEREcujWrRvS0tJw+fJlTJ48GXPmzJH8or558yYSEhIwbtw4REZGPrePa9euYcmSJfjuu+8we/ZsnXZRUVGSAftpaWno06ePpM21a9ewdu3aIrfTpk0byboDBgwQt/1katOmDT7//HMsWbIEc+fOxfnz53Ho0CGMGjVK53dzQUEBdu/ejV69egF4/FRbX19fqFQqbNu2DefPn0dERAQ0Gg2+/vprPd7V0jtw4ADS0tJw+vRpzJ8/HxcuXECzZs0QGxsraWdjY4O0tDTcunUL27ZtQ3Jysnjhw9NGjhyp854vXLhQ0kahUGDWrFmlqvfo0aPIzs5Gv379sGbNmiLbPKkhNTUVO3fuREpKCgIDA4vd98OHD8PJyQk9evSQXC167949tG7dGgcOHEBERASuXLmCjRs34sqVK/D09MS1a9d0+oyMjMTUqVOL/ew+eR//+ecfJCQkYNSoUVi7di2aN2+O1NTUUr0nJVWq8BEVFYWaNWvi3XffFee1bNkSxsbGkg9JcnIybt68CW9v77JXSkRUzkxNTaFSqVC7dm2MGTMGvr6+ksfMR0VFoUePHhgzZgw2bNiA7OzsYvtwdnZGnz594OvrK14J+DRbW1uoVCrJ9OyDucaPH4/Zs2cjNzdXZ30TExPJuubm5uK2n0wmJiaIiYnB2LFj0b9/f7i6uqJZs2YICgrCJ598IukvISEBxsbG8PT0xD///IMJEyZgwoQJiIyMRMeOHVGnTh20b98eP/zwQ6m/nPVlb28PlUqFN998E71798aBAwfg5eWFoKAgyREhhUIBlUoFR0dHtGnTBkFBQTh58qTOmEELCwud9/zZP3DHjRuHn376CWfPntW7XrVajffffx8ffPBBsV/wT2pwdHRE69atMW7cOPzxxx/F7nvjxo0xY8YMaLVanDhxQlz+6aefIjU1FQcOHED37t3h4uKC9u3bY//+/TA2NhZvefFEfHw8srOzERYWBq1Wi4SEBJ1tPv0+enh4ICgoCAkJCXjw4MFLvwW/3uGjsLAQUVFRGDp0KIyM/m/IiFKpRFBQEEJCQnDo0CEkJiZi+PDh8Pb25pUuRFQpmJubIy8vDwAgCAKioqIQGBgId3d3uLm5YevWrc9d/+zZs0hISICJiUmptj9x4kQ8evQI3377banWBx4fhT548CDu3Lnz3HYxMTHo2bMnFAoFtmzZgry8vGK/cJ4dyycXAwMDfPzxx7hx4wYSExOLbHP79m1s374dhoaGMDQ01Hsbbdu2RY8ePTB9+nS91rt//z62bNmCwMBAdOnSBRqNpshTJU+7d+8eNm/eDC8vr2LbZGdni0e/nnyOCgsLsXHjRgwePFjnTIK5uTnGjh2L/fv34969e+J8tVqNgIAAGBsbIyAgAGq1ukT7VbNmTQwePBgxMTE6pwDLk97h48CBA7h58yZGjBihs2zJkiXo0aMH/P390b59e6hUKvz888/lUigR0csiCAIOHDiA/fv3i7cKOHDgAB4+fAg/Pz8AQGBgYJG/wHfv3g0rKyuYmZmhSZMmuH37NqZMmaLTLiAgAFZWVpLp2XP1FhYWmD17NsLDw0t93n3x4sW4c+cOVCoVmjZtio8++gh79+7Vabdz507xlMvly5dhY2MDR0fHEm2jVq1aL9yX8uLu7g7g8diIJzQaDaysrGBpaQkHBwccOnQIwcHBsLS0lKy7cuVKnTrXrVuns43w8HDs27fvheHhaRs3bkS9evXQqFEjGBoaYtCgQUV+Pp7UYGlpCXt7eyQnJxd5lKRNmzZiu0WLFqFly5bo3LkzAODOnTvIzMyEh0fRg7g9PDwgCAKuXLkC4PGj7bdu3Sqe3gkMDMTmzZvx4MGDEu2bu7s77t+/j7t375aofWnoHT66du0KQRBQv359nWVmZmZYsWIF7t27h6ysLPz888/PHe9BRFSRng4O3bt3x8CBAzFnzhwAj8+XDxw4UDzCGxAQgN9++w1Xr16V9NGpUyckJSXhxIkTGDp0KIYPHw5/f3+dbS1ZsgRJSUmSqagB+0FBQbC3t8eXX35Zqn1q2LAhzp49i+PHj2PEiBG4ffs2evbsKRmjd+HCBaSmpopfboIgQKFQlHgbR44cKdG+lAdBEABAUp+1tTWSkpJw6tQpfP3112jRogXmzZuns+7gwYN16nwSuJ7WsGFDDBkyRK+jH5GRkZKxG4GBgdiyZQvu379fZA2nT5/G0aNH4ebmhq5du+q027RpE/78809s27YNbm5uiI6OhrGxcZHvxYts2LABdevWRbNmzQAAzZs3R+3atbFp06YSrV/Ue17eSn2pLRFRZdepUyesWrVKvHLgSdC4d+8etm/fjvz8fKxatUpsX1BQgMjISMkXnaWlJdzc3AA8/kJq1qwZ1Go1goKCJNtSqVRiu+cxMjLCvHnzMGzYMIwbN65U+2VgYABPT094enpi4sSJ+Omnn/DBBx/g008/haurK2JiYtClSxdxzEn9+vWh0WiQlpZWoqMfrq6uOqdinj4NX54uXLggbvMJAwMD8b308PDA1atXMWbMGPz444+SdZVKZYnecwD4/PPPUb9+fezYseOFbc+fP4/jx4/j5MmTmDZtmji/oKAAGzduxMiRI4uswc3NDWq1Go6Ojti0aZMkEDo7O6NevXqoV68eHj16hL59++Ls2bMwNTVFjRo1YGtrK74Xz7pw4QIUCoW4HbVajXPnzkn+TwoLCxEZGanzuSyuPxsbG9jb27+wbWnxwXJEVGU9CQ4uLi6SX9Tr1q1DrVq1cPr0aclfzV9//TWio6OLPRduYGCAGTNmYObMmUUOTi2p/v37o1GjRuV2D6SGDRsCALKysgA8PuXSu3dvcXm/fv1gYmKicyXIE0VdWiuHwsJCLFu2DK6urnjrrbeKbTd9+nRs2rSpyIGcJeXs7Ixx48ZhxowZLxzroFar0b59e53PR0hIyAvHVjwZl/K8z0e/fv1gZGSElStXAnj8uRowYADWr1+vc0lvdnY2Vq5cCT8/P9jZ2eHMmTM4deoU4uLiJLXFxcXh2LFjuHjx4nPru337NtavX48+ffrAwODlRQSGDyKiZ6jVavTr1w+NGzeWTEFBQfjf//6Hffv2Fbtu//79YWhoiBUrVkjmZ2ZmIj09XTI9CQNFWbBgASIjI5/bpij9+vXDkiVLcOLECdy4cQNxcXEIDg5G/fr14e7ujtu3b+PUqVPo0aOHuI6zszOWLFmCb775BkFBQYiPj8eNGzfw22+/YfTo0Zg7d65eNRTn1q1bOqdB/v33X3H53bt3kZ6ejmvXriEmJga+vr44efIk1Gr1cweTOjs7o2/fvjpX5Tx8+FDnPX96e88KDQ0VrygpTn5+Pn788UcEBATofD4+/PBDnDhxAufOnSuyhtOnT2PMmDEwMzND165di92GQqHAhAkTsGDBAjx8+BAAMH/+fKhUKnTp0gV79+5FSkoKDh8+DD8/P+Tn54ufN7VajVatWqF9+/aS2tq3bw9PT09JOBIEAenp6UhLS8OFCxcQGRmJNm3aQKlUYsGCBcXWVx542oWIXorKesfRxMREnD59Gt9//73OMqVSic6dO0OtVktuNfA0IyMjjBs3DgsXLsSYMWPEQZDDhw/XaRseHl7sOAMfHx/4+Pjg119/1at+Pz8/bNiwQRy0qlKp4OPjgzlz5sDIyAi7du1Cq1atUL16dcl6Y8eORf369bFo0SL07dsX2dnZqFOnDnr06IGQkBC9aijOokWLsGjRIsm8H3/8Ee3atQMA8fEcFhYWqF27Njp16oTVq1eX6NTJpEmT4O3tjZMnT6JVq1YAgO+//17n/9HPz6/Y8GhnZ4dp06ZhxowZxW4nJiYGd+/eRd++fXWWeXh4wMPDA2q1GosXL9apoVq1amjatCl++eUXNGjQ4Ln7M3ToUHz66adYvnw5pk6dCnt7exw/fhxhYWEYPXo00tPTYWdnh+7du+Onn36Ci4uL+NiTp08FPc3f3x9ff/015s+fD+DxwFRHR0coFArY2NigQYMGGDp0KD7++OOXfs8thVDSESwy0Wq1UCqV0Gg0vOFYJbHio4NlWj84wqecKiG55eTk4Pr163B1ddW5ZwW9mnr16oV27dq99Ps40OvpeT/z+nx/87QLEVEV0q5dOwQEBFR0GVTF8bQLEVEVwiMe9CrgkQ8iIiKSFcMHERERyYrhg4iIiGTF8EFERESyYvggIiIiWTF8EBERkawYPoiIiEhWvM8HEb0UZb3zrb70vVPusGHDsGbNGp35ly9fhpubG8LDwzFz5kwsWLAAU6ZMkbSJjo4Wb5euUCjg4OCA9u3b46uvvoKLi4vYrmPHjoiPj9fZxujRoxEREaFXvUSvEx75IKIqq1u3bkhLS5NMTx7dHhkZialTpyIyMrLIdW1sbJCWloZbt25h27ZtSE5ORv/+/XXajRw5UmcbxT09lqiq4JEPIqqyTE1NoVKpdObHx8cjOzsbYWFhWLt2LRISEtCmTRtJG4VCIa7r6OiIoKAgTJgwAVqtVvJcCwsLiyK3QVSV8cgHEdEz1Go1AgICYGxsjICAAMljyIty+/ZtbN++HYaGhs999DsRPcbwQURV1u7du2FlZSVO/fv3h1arxdatWxEYGAgACAwMxObNm/HgwQPJuhqNBlZWVrC0tISDgwMOHTqE4OBgWFpaStqtXLlSsg0rKyusW7dOtn0kehXxtAsRVVmdOnXCqlWrxNeWlpbYsGED6tati2bNmgEAmjdvjtq1a2PTpk0ICgoS21pbW+OPP/5Afn4+9u7di3Xr1mHevHk62xg8eDA+/fRTyTwHB4eXtEdElQPDBxFVWZaWlnBzc5PMU6vVOHfuHIyM/u/XY2FhISIjIyXhw8DAQFzXw8MDV69exZgxY/Djjz9K+lMqlTrbIKrqGD6IiP6/M2fO4NSpU4iLi4OdnZ04/969e+jYsSMuXrwId3f3ItedPn066tati0mTJqFFixZylUxUKTF8EBH9f2q1Gq1atUL79u11lnl6ekKtVuOrr74qcl1nZ2f07dsXs2bNwu7du8X5Dx8+RHp6uqStqakpqlWrVr7FE1UiHHBKRAQgLy8PP/30E/z9/Ytc7u/vj7Vr1yI/P7/YPiZNmoQ9e/bg5MmT4rzvv/8ejo6OkikgIKDc6yeqTBSCIAgVXcTTtFotlEolNBqN5Fp5enWV9U6W+t6Zkl4dOTk5uH79OlxdXWFmZlbR5RDRS/a8n3l9vr955IOIiIhkxfBBREREsmL4ICIiIlkxfBAREZGsGD6IqMxesXHrRPSSlNfPOsMHEZWasbExgMf3siCi119eXh4AlPkBinrfZOzWrVuYNm0a9u7di4cPH8LNzQ1RUVF4++23ATxORbNnz8b333+PzMxMtG3bFqtWrUK9evXKVCgRvXoMDQ1ha2uL27dvA3j8+HiFQlHBVRHRy1BYWIg7d+7AwsJC8viB0tBr7X///Rdt27ZFp06dsHfvXtSoUQOXL1+W3Klv4cKFWLZsGdasWQNXV1d89tln8PPzw/nz53kfAKLXkEqlAgAxgBDR68vAwAAuLi5l/iNDr/Dx5ZdfwtnZGVFRUeI8V1dX8d+CIGDp0qWYOXMmevfuDQBYu3YtHBwcsGPHDgwaNKhMxRLRq0ehUMDR0RE1a9Z87t0/iajyMzExgYFB2Uds6BU+YmJi4Ofnh/79+yM+Ph5vvPEGxo4di5EjRwIArl+/jvT0dPj6+orrKJVKeHl54dixY0WGj9zcXOTm5oqvtVptafeFiCqQoaFhmc8DE1HVoFd8uXbtmjh+Y//+/RgzZgwmTJiANWvWAID48CQHBwfJeg4ODjoPVnoiPDwcSqVSnJydnUuzH0RERFRJ6BU+CgsL0aJFC8yfPx9vvfUWRo0ahZEjRyIiIqLUBYSGhkKj0YhTSkpKqfsiIiKiV59e4cPR0RENGzaUzPPw8MDNmzcB/N/As4yMDEmbjIwMcdmzTE1NYWNjI5mIiIjo9aVX+Gjbti2Sk5Ml8y5duoTatWsDeDz4VKVSITY2Vlyu1Wpx4sQJeHt7l0O5REREVNnpNeB00qRJaNOmDebPn48BAwbg5MmTWL16NVavXg3g8aj3iRMn4osvvkC9evXES22dnJzQp0+fl1E/ERERVTJ6hQ9PT09s374doaGhCAsLg6urK5YuXYrBgweLbaZOnYqsrCyMGjUKmZmZaNeuHfbt28d7fBAREREAQCG8Yg9l0Gq1UCqV0Gg0HP9RSaz46GCZ1g+O8CmnSoiIqKLo8/3NZ7sQERGRrBg+iIiISFYMH0RERCQrhg8iIiKSFcMHERERyYrhg4iIiGTF8EFERESyYvggIiIiWTF8EBERkawYPoiIiEhWDB9EREQkK4YPIiIikhXDBxEREcmK4YOIiIhkxfBBREREsmL4ICIiIlkxfBAREZGsGD6IiIhIVgwfREREJCuGDyIiIpIVwwcRERHJiuGDiIiIZMXwQURERLJi+CAiIiJZMXwQERGRrBg+iIiISFYMH0RERCQrhg8iIiKSFcMHERERyYrhg4iIiGTF8EFERESy0it8zJkzBwqFQjK5u7uLy3NychAcHAx7e3tYWVnB398fGRkZ5V40ERERVV56H/lo1KgR0tLSxOno0aPiskmTJmHXrl3YsmUL4uPjkZqaivfee69cCyYiIqLKzUjvFYyMoFKpdOZrNBqo1WqsX78ePj4+AICoqCh4eHjg+PHjaN26ddmrJSIiokpP7yMfly9fhpOTE958800MHjwYN2/eBAAkJiYiPz8fvr6+Ylt3d3e4uLjg2LFjxfaXm5sLrVYrmYiIiOj1pVf48PLyQnR0NPbt24dVq1bh+vXr+M9//oP79+8jPT0dJiYmsLW1lazj4OCA9PT0YvsMDw+HUqkUJ2dn51LtCBEREVUOep126d69u/jvpk2bwsvLC7Vr18bmzZthbm5eqgJCQ0MREhIivtZqtQwgREREr7EyXWpra2uL+vXr48qVK1CpVMjLy0NmZqakTUZGRpFjRJ4wNTWFjY2NZCIiIqLXV5nCx4MHD3D16lU4OjqiZcuWMDY2RmxsrLg8OTkZN2/ehLe3d5kLJSIioteDXqddPvnkE/Ts2RO1a9dGamoqZs+eDUNDQwQEBECpVCIoKAghISGws7ODjY0Nxo8fD29vb17pQkRERCK9wsc///yDgIAA3L17FzVq1EC7du1w/Phx1KhRAwCwZMkSGBgYwN/fH7m5ufDz88PKlStfSuFERERUOSkEQRAquoinabVaKJVKaDQajv+oJFZ8dLBM6wdH+JRTJUREVFH0+f7ms12IiIhIVgwfREREJCuGDyIiIpIVwwcRERHJiuGDiIiIZMXwQURERLJi+CAiIiJZMXwQERGRrBg+iIiISFYMH0RERCQrhg8iIiKSFcMHERERyYrhg4iIiGTF8EFERESyYvggIiIiWTF8EBERkawYPoiIiEhWDB9EREQkK4YPIiIikhXDBxEREcmK4YOIiIhkxfBBREREsmL4ICIiIlkxfBAREZGsGD6IiIhIVgwfREREJCuGDyIiIpIVwwcRERHJiuGDiIiIZMXwQURERLJi+CAiIiJZlSl8LFiwAAqFAhMnThTn5eTkIDg4GPb29rCysoK/vz8yMjLKWicRERG9JkodPn7//Xd89913aNq0qWT+pEmTsGvXLmzZsgXx8fFITU3Fe++9V+ZCiYiI6PVQqvDx4MEDDB48GN9//z2qVasmztdoNFCr1Vi8eDF8fHzQsmVLREVFISEhAcePHy+3oomIiKjyKlX4CA4OxrvvvgtfX1/J/MTEROTn50vmu7u7w8XFBceOHSuyr9zcXGi1WslEREREry8jfVfYuHEj/vjjD/z+++86y9LT02FiYgJbW1vJfAcHB6SnpxfZX3h4OD7//HN9yyAiIqJKSq8jHykpKfj444+xbt06mJmZlUsBoaGh0Gg04pSSklIu/RIREdGrSa/wkZiYiNu3b6NFixYwMjKCkZER4uPjsWzZMhgZGcHBwQF5eXnIzMyUrJeRkQGVSlVkn6amprCxsZFMRERE9PrS67RL586dcebMGcm84cOHw93dHdOmTYOzszOMjY0RGxsLf39/AEBycjJu3rwJb2/v8quaiIiIKi29woe1tTUaN24smWdpaQl7e3txflBQEEJCQmBnZwcbGxuMHz8e3t7eaN26dflVTURERJWW3gNOX2TJkiUwMDCAv78/cnNz4efnh5UrV5b3Zl4Pc5Tl0Iem7H0QERHJqMzhIy4uTvLazMwMK1aswIoVK8raNREREb2G+GwXIiIikhXDBxEREcmK4YOIiIhkxfBBREREsmL4ICIiIlkxfBAREZGsGD6IiIhIVgwfREREJCuGDyIiIpIVwwcRERHJiuGDiIiIZMXwQURERLJi+CAiIiJZMXwQERGRrBg+iIiISFYMH0RERCQrhg8iIiKSFcMHERERyYrhg4iIiGTF8EFERESyYvggIiIiWTF8EBERkawYPoiIiEhWDB9EREQkK4YPIiIikhXDBxEREcmK4YOIiIhkxfBBREREsmL4ICIiIlkxfBAREZGsGD6IiIhIVnqFj1WrVqFp06awsbGBjY0NvL29sXfvXnF5Tk4OgoODYW9vDysrK/j7+yMjI6PciyYiIqLKS6/wUatWLSxYsACJiYk4deoUfHx80Lt3b5w7dw4AMGnSJOzatQtbtmxBfHw8UlNT8d57772UwomIiKhyMtKncc+ePSWv582bh1WrVuH48eOoVasW1Go11q9fDx8fHwBAVFQUPDw8cPz4cbRu3brIPnNzc5Gbmyu+1mq1+u4DERERVSKlHvNRUFCAjRs3IisrC97e3khMTER+fj58fX3FNu7u7nBxccGxY8eK7Sc8PBxKpVKcnJ2dS1sSERERVQJ6HfkAgDNnzsDb2xs5OTmwsrLC9u3b0bBhQyQlJcHExAS2traS9g4ODkhPTy+2v9DQUISEhIivtVotAwhRRZqjLOP6mvKpg4heW3qHjwYNGiApKQkajQZbt27F0KFDER8fX+oCTE1NYWpqWur1iYiIqHLRO3yYmJjAzc0NANCyZUv8/vvv+OabbzBw4EDk5eUhMzNTcvQjIyMDKpWq3AomIiKiyq3M9/koLCxEbm4uWrZsCWNjY8TGxorLkpOTcfPmTXh7e5d1M0RERPSa0OvIR2hoKLp37w4XFxfcv38f69evR1xcHPbv3w+lUomgoCCEhITAzs4ONjY2GD9+PLy9vYu90oWIiIiqHr3Cx+3btzFkyBCkpaVBqVSiadOm2L9/P7p06QIAWLJkCQwMDODv74/c3Fz4+flh5cqVL6VwIiIiqpz0Ch9qtfq5y83MzLBixQqsWLGiTEURERHR64vPdiEiIiJZMXwQERGRrBg+iIiISFYMH0RERCQrhg8iIiKSFcMHERERyYrhg4iIiGTF8EFERESyYvggIiIiWTF8EBERkawYPoiIiEhWDB9EREQkK70eLEdERCS7Ocoyrq8pnzqo3PDIBxEREcmK4YOIiIhkxfBBREREsmL4ICIiIlkxfBAREZGsGD6IiIhIVgwfREREJCuGDyIiIpIVwwcRERHJiuGDiIiIZMXwQURERLJi+CAiIiJZMXwQERGRrBg+iIiISFYMH0RERCQrhg8iIiKSFcMHERERyUqv8BEeHg5PT09YW1ujZs2a6NOnD5KTkyVtcnJyEBwcDHt7e1hZWcHf3x8ZGRnlWjQRERFVXkb6NI6Pj0dwcDA8PT3x6NEjzJgxA127dsX58+dhaWkJAJg0aRL27NmDLVu2QKlUYty4cXjvvffw22+/vZQdICJ61oqPDpa5j+AIn3KohIiKolf42Ldvn+R1dHQ0atasicTERLRv3x4ajQZqtRrr16+Hj8/jH9yoqCh4eHjg+PHjaN26dflVTkRERJVSmcZ8aDQaAICdnR0AIDExEfn5+fD19RXbuLu7w8XFBceOHSuyj9zcXGi1WslEREREr69Sh4/CwkJMnDgRbdu2RePGjQEA6enpMDExga2traStg4MD0tPTi+wnPDwcSqVSnJydnUtbEhEREVUCpQ4fwcHBOHv2LDZu3FimAkJDQ6HRaMQpJSWlTP0RERHRq02vMR9PjBs3Drt378bhw4dRq1Ytcb5KpUJeXh4yMzMlRz8yMjKgUqmK7MvU1BSmpqalKYOIiIgqIb2OfAiCgHHjxmH79u04ePAgXF1dJctbtmwJY2NjxMbGivOSk5Nx8+ZNeHt7l0/FREREVKnpdeQjODgY69evx86dO2FtbS2O41AqlTA3N4dSqURQUBBCQkJgZ2cHGxsbjB8/Ht7e3rzShYiIiADoGT5WrVoFAOjYsaNkflRUFIYNGwYAWLJkCQwMDODv74/c3Fz4+flh5cqV5VIsERERVX56hQ9BEF7YxszMDCtWrMCKFStKXRQRERG9vvhsFyIiIpIVwwcRERHJiuGDiIiIZMXwQURERLJi+CAiIiJZMXwQERGRrBg+iIiISFYMH0RERCQrhg8iIiKSFcMHERERyYrhg4iIiGTF8EFERESyYvggIiIiWTF8EBERkawYPoiIiEhWDB9EREQkK4YPIiIikhXDBxEREcmK4YOIiIhkxfBBREREsjKq6AKIiIhedys+OljmPoIjfMqhklcDj3wQERGRrBg+iIiISFYMH0RERCQrhg8iIiKSFcMHERERyYrhg4iIiGTF8EFERESyYvggIiIiWTF8EBERkawYPoiIiEhWeoePw4cPo2fPnnBycoJCocCOHTskywVBwKxZs+Do6Ahzc3P4+vri8uXL5VUvERERVXJ6h4+srCw0a9YMK1asKHL5woULsWzZMkRERODEiROwtLSEn58fcnJyylwsERERVX56P1iue/fu6N69e5HLBEHA0qVLMXPmTPTu3RsAsHbtWjg4OGDHjh0YNGhQ2aolIiKiSq9cx3xcv34d6enp8PX1FecplUp4eXnh2LFjRa6Tm5sLrVYrmYiIiOj1Va7hIz09HQDg4OAgme/g4CAue1Z4eDiUSqU4OTs7l2dJRERE9Iqp8KtdQkNDodFoxCklJaWiSyIiIqKXqFzDh0qlAgBkZGRI5mdkZIjLnmVqagobGxvJRERERK+vcg0frq6uUKlUiI2NFedptVqcOHEC3t7e5bkpIiIiqqT0vtrlwYMHuHLlivj6+vXrSEpKgp2dHVxcXDBx4kR88cUXqFevHlxdXfHZZ5/ByckJffr0Kc+6iYiIqJLSO3ycOnUKnTp1El+HhIQAAIYOHYro6GhMnToVWVlZGDVqFDIzM9GuXTvs27cPZmZm5Vc1ERERVVp6h4+OHTtCEIRilysUCoSFhSEsLKxMhREREdHrqcKvdiEiIqKqheGDiIiIZMXwQURERLJi+CAiIiJZMXwQERGRrBg+iIiISFYMH0RERCQrhg8iIiKSFcMHERERyYrhg4iIiGTF8EFERESyYvggIiIiWTF8EBERkawYPoiIiEhWDB9EREQkK4YPIiIikhXDBxEREcmK4YOIiIhkxfBBREREsmL4ICIiIlkxfBAREZGsGD6IiIhIVgwfREREJCuGDyIiIpIVwwcRERHJiuGDiIiIZMXwQURERLJi+CAiIiJZMXwQERGRrBg+iIiISFYMH0RERCSrlxY+VqxYgTp16sDMzAxeXl44efLky9oUERERVSJGL6PTTZs2ISQkBBEREfDy8sLSpUvh5+eH5ORk1KxZ82VsskLUmb6nTOv/bVZOhRARUbGarGlS5j7ODD1TDpXQEy8lfCxevBgjR47E8OHDAQARERHYs2cPIiMjMX369JexySqrrD9Um8Mflb2IjivK3geVi7IGYqDsobg8ftGX+XPJzySVswvuHmXrgJ9JiXIPH3l5eUhMTERoaKg4z8DAAL6+vjh27JhO+9zcXOTm5oqvNRoNAECr1ZZ3aeWuMPdhmdbXKoQy11CQXVCm9R8UlG19AMjOyyrT+pXh/7qyKOtnEij757Ksn0mg7J/Lsn4mAX4uy0vj2fvL3MdZM34mgVf/M/mkPkEowf+XUM5u3bolABASEhIk86dMmSK0atVKp/3s2bMFAJw4ceLEiROn12BKSUl5YVZ4Kadd9BEaGoqQkBDxdWFhIe7duwd7e3soFIoKrKzy02q1cHZ2RkpKCmxsbCq6HCJ+JumVxM9l+RAEAffv34eTk9ML25Z7+KhevToMDQ2RkZEhmZ+RkQGVSqXT3tTUFKamppJ5tra25V1WlWZjY8MfKHql8DNJryJ+LstOqVSWqF25X2prYmKCli1bIjY2VpxXWFiI2NhYeHt7l/fmiIiIqJJ5KaddQkJCMHToULz99tto1aoVli5diqysLPHqFyIiIqq6Xkr4GDhwIO7cuYNZs2YhPT0dzZs3x759++Dg4PAyNkfFMDU1xezZs3VOaxFVFH4m6VXEz6X8FIJQkmtiiIiIiMoHn+1CREREsmL4ICIiIlkxfBAREZGsGD6IiIhIVgwfREREJCuGDyIiIpIVw0cVkpKSghEjRlR0GVSFZGdn4+jRozh//rzOspycHKxdu7YCqqKq7sKFC4iKisLFixcBABcvXsSYMWMwYsQIHDx4sIKrqxp4n48q5PTp02jRogUKyvhoaKKSuHTpErp27YqbN29CoVCgXbt22LhxIxwdHQE8ft6Tk5MTP48kq3379qF3796wsrLCw4cPsX37dgwZMgTNmjVDYWEh4uPj8euvv8LHx6eiS32tMXy8RmJiYp67/Nq1a5g8eTJ/2ZMs+vbti/z8fERHRyMzMxMTJ07E+fPnERcXBxcXF4YPqhBt2rSBj48PvvjiC2zcuBFjx47FmDFjMG/ePACPn7SemJiIX3/9tYIrfb0xfLxGDAwMoFAo8Lz/UoVCwV/2JAsHBwccOHAATZo0AfD4cdtjx47FL7/8gkOHDsHS0pLhg2SnVCqRmJgINzc3FBYWwtTUFCdPnsRbb70FADh79ix8fX2Rnp5ewZW+3jjm4zXi6OiIn3/+GYWFhUVOf/zxR0WXSFVIdnY2jIz+7/FRCoUCq1atQs+ePdGhQwdcunSpAqujqkyhUAB4/AebmZmZ5DHw1tbW0Gg0FVValcHw8Rpp2bIlEhMTi13+oqMiROXJ3d0dp06d0pm/fPly9O7dG7169aqAqqiqq1OnDi5fviy+PnbsGFxcXMTXN2/eFMcl0cvD8PEamTJlCtq0aVPscjc3Nxw6dEjGiqgq69u3LzZs2FDksuXLlyMgIIBhmGQ3ZswYyam+xo0bS47Q7d27l4NNZcAxH0RERCQrHvkgIiIiWTF8EBERkawYPoiIiEhWDB9EREQkK4YPIiIikhXDBxGJhg0bBoVCAYVCARMTE7i5uSEsLAyPHj0C8PgupatXr4aXlxesrKxga2uLt99+G0uXLsXDhw8BAHPmzEHz5s1fuK3s7GzY2dmhevXqyM3N1Vl++vRp9OrVCzVr1oSZmRnq1KmDgQMH4vbt22Kb7du3o3Xr1lAqlbC2tkajRo0wceLEcnkviOjlYfggIolu3bohLS0Nly9fxuTJkzFnzhx89dVXAIAPPvgAEydORO/evXHo0CEkJSXhs88+w86dO/V+Fsa2bdvQqFEjuLu7Y8eOHZJld+7cQefOnWFnZ4f9+/eLTyF1cnJCVlYWACA2NhYDBw6Ev78/Tp48icTERMybNw/5+fnl8j4Q0cvD+3wQkWjYsGHIzMyUhIGuXbvi/v37mDRpEgYOHIgdO3agd+/ekvUEQYBWq4VSqcScOXOwY8cOJCUlPXdbnTp1wqBBgyAIAn7++WdJeNmxYwf69++vc4v2p02cOBGnT5/mjfOIKiEe+SCi5zI3N0deXh7WrVuHBg0a6AQP4PGt+59+PsaLXL16FceOHcOAAQMwYMAAHDlyBDdu3BCXq1QqPHr0CNu3by/2LqgqlQrnzp3D2bNn9d8pIqpQDB9EVCRBEHDgwAHs378fPj4+uHz5Mho0aFAufUdGRqJ79+6oVq0a7Ozs4Ofnh6ioKHF569atMWPGDLz//vuoXr06unfvjq+++goZGRlim/Hjx8PT0xNNmjRBnTp1MGjQIERGRhY5foSIXi0MH0QksXv3blhZWcHMzAzdu3fHwIEDMWfOnHJ7DktBQQHWrFmDwMBAcV5gYCCio6NRWFgozps3bx7S09MRERGBRo0aISIiAu7u7jhz5gwAwNLSEnv27MGVK1cwc+ZMWFlZYfLkyWjVqpU4+JWIXk0c80FEomHDhuHWrVtYtWoVTExM4OTkJI656N27Ny5evIjk5OTn9vGiMR+//PIL3n33XRgaGkrmFxQU4Ndff0WXLl2KXC8vLw9vvfUW3n77baxZs6bINtevX0f9+vWxevVqDB8+/AV7S0QVhUc+iEjC0tISbm5ucHFxkQz2fP/993Hp0iXs3LlTZx1BEKDRaErUv1qtxqBBg5CUlCSZBg0aBLVaXex6JiYmqFu3rni1S1Hq1KkDCwuL57YhoopX9DByIqJnDBgwANu3b0dAQABmzpyJrl27okaNGjhz5gyWLFmC8ePHo0+fPgAe38Pj2SMf1tbWsLGxwa5duxATE4PGjRtLlg8ZMgR9+/bFvXv3kJCQgI0bN2LQoEGoX78+BEHArl278Msvv4hjQ+bMmYOHDx/inXfeQe3atZGZmYlly5YhPz+/2KMnRPRqYPggohJRKBRYv349Vq9ejcjISMybNw9GRkaoV68ehgwZAj8/P7HtpUuX8NZbb0nW79y5M7p37w5LS0t07txZp//OnTvD3NwcP/30E3r06AELCwtMnjwZKSkpMDU1Rb169fDDDz/ggw8+AAB06NABK1aswJAhQ5CRkYFq1arhrbfewq+//lpuA2OJ6OXgmA8iIiKSFcd8EBERkawYPoiIiEhWDB9EREQkK4YPIiIikhXDBxEREcmK4YOIiIhkxfBBREREsmL4ICIiIlkxfBAREZGsGD6IiIhIVgwfREREJKv/B1frMRFJkQooAAAAAElFTkSuQmCC\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "\n", - "print(data.groupby('PCLASS').mean(numeric_only=True))\n", - "data.groupby('PCLASS').mean(numeric_only=True).plot(kind='bar')\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "adee91c8-743e-4315-b324-283d6a22e165", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.16" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/image-and-data-processing/titanic.csv b/Material/wise_24_25/lernmaterial/image-and-data-processing/titanic.csv deleted file mode 100644 index 853188c..0000000 --- a/Material/wise_24_25/lernmaterial/image-and-data-processing/titanic.csv +++ /dev/null @@ -1,888 +0,0 @@ -Survived,Pclass,Name,Sex,Age,Siblings/Spouses Aboard,Parents/Children Aboard,Fare -0,3,Mr. Owen Harris Braund,male,22,1,0,7.25 -1,1,Mrs. John Bradley (Florence Briggs Thayer) Cumings,female,38,1,0,71.2833 -1,3,Miss. Laina Heikkinen,female,26,0,0,7.925 -1,1,Mrs. Jacques Heath (Lily May Peel) Futrelle,female,35,1,0,53.1 -0,3,Mr. William Henry Allen,male,35,0,0,8.05 -0,3,Mr. James Moran,male,27,0,0,8.4583 -0,1,Mr. Timothy J McCarthy,male,54,0,0,51.8625 -0,3,Master. Gosta Leonard Palsson,male,2,3,1,21.075 -1,3,Mrs. Oscar W (Elisabeth Vilhelmina Berg) Johnson,female,27,0,2,11.1333 -1,2,Mrs. Nicholas (Adele Achem) Nasser,female,14,1,0,30.0708 -1,3,Miss. Marguerite Rut Sandstrom,female,4,1,1,16.7 -1,1,Miss. Elizabeth Bonnell,female,58,0,0,26.55 -0,3,Mr. William Henry Saundercock,male,20,0,0,8.05 -0,3,Mr. Anders Johan Andersson,male,39,1,5,31.275 -0,3,Miss. Hulda Amanda Adolfina Vestrom,female,14,0,0,7.8542 -1,2,Mrs. (Mary D Kingcome) Hewlett,female,55,0,0,16 -0,3,Master. Eugene Rice,male,2,4,1,29.125 -1,2,Mr. Charles Eugene Williams,male,23,0,0,13 -0,3,Mrs. Julius (Emelia Maria Vandemoortele) Vander Planke,female,31,1,0,18 -1,3,Mrs. Fatima Masselmani,female,22,0,0,7.225 -0,2,Mr. Joseph J Fynney,male,35,0,0,26 -1,2,Mr. Lawrence Beesley,male,34,0,0,13 -1,3,Miss. Anna McGowan,female,15,0,0,8.0292 -1,1,Mr. William Thompson Sloper,male,28,0,0,35.5 -0,3,Miss. Torborg Danira Palsson,female,8,3,1,21.075 -1,3,Mrs. Carl Oscar (Selma Augusta Emilia Johansson) Asplund,female,38,1,5,31.3875 -0,3,Mr. Farred Chehab Emir,male,26,0,0,7.225 -0,1,Mr. Charles Alexander Fortune,male,19,3,2,263 -1,3,Miss. Ellen O'Dwyer,female,24,0,0,7.8792 -0,3,Mr. Lalio Todoroff,male,23,0,0,7.8958 -0,1,Don. Manuel E Uruchurtu,male,40,0,0,27.7208 -1,1,Mrs. William Augustus (Marie Eugenie) Spencer,female,48,1,0,146.5208 -1,3,Miss. Mary Agatha Glynn,female,18,0,0,7.75 -0,2,Mr. Edward H Wheadon,male,66,0,0,10.5 -0,1,Mr. Edgar Joseph Meyer,male,28,1,0,82.1708 -0,1,Mr. Alexander Oskar Holverson,male,42,1,0,52 -1,3,Mr. Hanna Mamee,male,18,0,0,7.2292 -0,3,Mr. Ernest Charles Cann,male,21,0,0,8.05 -0,3,Miss. Augusta Maria Vander Planke,female,18,2,0,18 -1,3,Miss. Jamila Nicola-Yarred,female,14,1,0,11.2417 -0,3,Mrs. Johan (Johanna Persdotter Larsson) Ahlin,female,40,1,0,9.475 -0,2,Mrs. William John Robert (Dorothy Ann Wonnacott) Turpin,female,27,1,0,21 -1,2,Miss. Simonne Marie Anne Andree Laroche,female,3,1,2,41.5792 -1,3,Miss. Margaret Delia Devaney,female,19,0,0,7.8792 -0,3,Mr. William John Rogers,male,30,0,0,8.05 -0,3,Mr. Denis Lennon,male,20,1,0,15.5 -1,3,Miss. Bridget O'Driscoll,female,27,0,0,7.75 -0,3,Mr. Youssef Samaan,male,16,2,0,21.6792 -0,3,Mrs. Josef (Josefine Franchi) Arnold-Franchi,female,18,1,0,17.8 -0,3,Master. Juha Niilo Panula,male,7,4,1,39.6875 -0,3,Mr. Richard Cater Nosworthy,male,21,0,0,7.8 -1,1,Mrs. Henry Sleeper (Myna Haxtun) Harper,female,49,1,0,76.7292 -1,2,Mrs. Lizzie (Elizabeth Anne Wilkinson) Faunthorpe,female,29,1,0,26 -0,1,Mr. Engelhart Cornelius Ostby,male,65,0,1,61.9792 -1,1,Mr. Hugh Woolner,male,46,0,0,35.5 -1,2,Miss. Emily Rugg,female,21,0,0,10.5 -0,3,Mr. Mansouer Novel,male,28.5,0,0,7.2292 -1,2,Miss. Constance Mirium West,female,5,1,2,27.75 -0,3,Master. William Frederick Goodwin,male,11,5,2,46.9 -0,3,Mr. Orsen Sirayanian,male,22,0,0,7.2292 -1,1,Miss. Amelie Icard,female,38,0,0,80 -0,1,Mr. Henry Birkhardt Harris,male,45,1,0,83.475 -0,3,Master. Harald Skoog,male,4,3,2,27.9 -0,1,Mr. Albert A Stewart,male,64,0,0,27.7208 -1,3,Master. Gerios Moubarek,male,7,1,1,15.2458 -1,2,Mrs. (Elizabeth Ramell) Nye,female,29,0,0,10.5 -0,3,Mr. Ernest James Crease,male,19,0,0,8.1583 -1,3,Miss. Erna Alexandra Andersson,female,17,4,2,7.925 -0,3,Mr. Vincenz Kink,male,26,2,0,8.6625 -0,2,Mr. Stephen Curnow Jenkin,male,32,0,0,10.5 -0,3,Miss. Lillian Amy Goodwin,female,16,5,2,46.9 -0,2,Mr. Ambrose Jr Hood,male,21,0,0,73.5 -0,3,Mr. Apostolos Chronopoulos,male,26,1,0,14.4542 -1,3,Mr. Lee Bing,male,32,0,0,56.4958 -0,3,Mr. Sigurd Hansen Moen,male,25,0,0,7.65 -0,3,Mr. Ivan Staneff,male,23,0,0,7.8958 -0,3,Mr. Rahamin Haim Moutal,male,28,0,0,8.05 -1,2,Master. Alden Gates Caldwell,male,0.83,0,2,29 -1,3,Miss. Elizabeth Dowdell,female,30,0,0,12.475 -0,3,Mr. Achille Waelens,male,22,0,0,9 -1,3,Mr. Jan Baptist Sheerlinck,male,29,0,0,9.5 -1,3,Miss. Brigdet Delia McDermott,female,31,0,0,7.7875 -0,1,Mr. Francisco M Carrau,male,28,0,0,47.1 -1,2,Miss. Bertha Ilett,female,17,0,0,10.5 -1,3,Mrs. Karl Alfred (Maria Mathilda Gustafsson) Backstrom,female,33,3,0,15.85 -0,3,Mr. William Neal Ford,male,16,1,3,34.375 -0,3,Mr. Selman Francis Slocovski,male,20,0,0,8.05 -1,1,Miss. Mabel Helen Fortune,female,23,3,2,263 -0,3,Mr. Francesco Celotti,male,24,0,0,8.05 -0,3,Mr. Emil Christmann,male,29,0,0,8.05 -0,3,Mr. Paul Edvin Andreasson,male,20,0,0,7.8542 -0,1,Mr. Herbert Fuller Chaffee,male,46,1,0,61.175 -0,3,Mr. Bertram Frank Dean,male,26,1,2,20.575 -0,3,Mr. Daniel Coxon,male,59,0,0,7.25 -0,3,Mr. Charles Joseph Shorney,male,22,0,0,8.05 -0,1,Mr. George B Goldschmidt,male,71,0,0,34.6542 -1,1,Mr. William Bertram Greenfield,male,23,0,1,63.3583 -1,2,Mrs. John T (Ada Julia Bone) Doling,female,34,0,1,23 -0,2,Mr. Sinai Kantor,male,34,1,0,26 -0,3,Miss. Matilda Petranec,female,28,0,0,7.8958 -0,3,Mr. Pastcho Petroff,male,29,0,0,7.8958 -0,1,Mr. Richard Frasar White,male,21,0,1,77.2875 -0,3,Mr. Gustaf Joel Johansson,male,33,0,0,8.6542 -0,3,Mr. Anders Vilhelm Gustafsson,male,37,2,0,7.925 -0,3,Mr. Stoytcho Mionoff,male,28,0,0,7.8958 -1,3,Miss. Anna Kristine Salkjelsvik,female,21,0,0,7.65 -1,3,Mr. Albert Johan Moss,male,29,0,0,7.775 -0,3,Mr. Tido Rekic,male,38,0,0,7.8958 -1,3,Miss. Bertha Moran,female,28,1,0,24.15 -0,1,Mr. Walter Chamberlain Porter,male,47,0,0,52 -0,3,Miss. Hileni Zabour,female,14.5,1,0,14.4542 -0,3,Mr. David John Barton,male,22,0,0,8.05 -0,3,Miss. Katriina Jussila,female,20,1,0,9.825 -0,3,Miss. Malake Attalah,female,17,0,0,14.4583 -0,3,Mr. Edvard Pekoniemi,male,21,0,0,7.925 -0,3,Mr. Patrick Connors,male,70.5,0,0,7.75 -0,2,Mr. William John Robert Turpin,male,29,1,0,21 -0,1,Mr. Quigg Edmond Baxter,male,24,0,1,247.5208 -0,3,Miss. Ellis Anna Maria Andersson,female,2,4,2,31.275 -0,2,Mr. Stanley George Hickman,male,21,2,0,73.5 -0,3,Mr. Leonard Charles Moore,male,19,0,0,8.05 -0,2,Mr. Nicholas Nasser,male,32.5,1,0,30.0708 -1,2,Miss. Susan Webber,female,32.5,0,0,13 -0,1,Mr. Percival Wayland White,male,54,0,1,77.2875 -1,3,Master. Elias Nicola-Yarred,male,12,1,0,11.2417 -0,3,Mr. Martin McMahon,male,19,0,0,7.75 -1,3,Mr. Fridtjof Arne Madsen,male,24,0,0,7.1417 -1,3,Miss. Anna Peter,female,2,1,1,22.3583 -0,3,Mr. Johan Ekstrom,male,45,0,0,6.975 -0,3,Mr. Jozef Drazenoic,male,33,0,0,7.8958 -0,3,Mr. Domingos Fernandeo Coelho,male,20,0,0,7.05 -0,3,Mrs. Alexander A (Grace Charity Laury) Robins,female,47,1,0,14.5 -1,2,Mrs. Leopold (Mathilde Francoise Pede) Weisz,female,29,1,0,26 -0,2,Mr. Samuel James Hayden Sobey,male,25,0,0,13 -0,2,Mr. Emile Richard,male,23,0,0,15.0458 -1,1,Miss. Helen Monypeny Newsom,female,19,0,2,26.2833 -0,1,Mr. Jacques Heath Futrelle,male,37,1,0,53.1 -0,3,Mr. Olaf Elon Osen,male,16,0,0,9.2167 -0,1,Mr. Victor Giglio,male,24,0,0,79.2 -0,3,Mrs. Joseph (Sultana) Boulos,female,40,0,2,15.2458 -1,3,Miss. Anna Sofia Nysten,female,22,0,0,7.75 -1,3,Mrs. Pekka Pietari (Elin Matilda Dolck) Hakkarainen,female,24,1,0,15.85 -0,3,Mr. Jeremiah Burke,male,19,0,0,6.75 -0,2,Mr. Edgardo Samuel Andrew,male,18,0,0,11.5 -0,2,Mr. Joseph Charles Nicholls,male,19,1,1,36.75 -1,3,Mr. August Edvard Andersson,male,27,0,0,7.7958 -0,3,Miss. Robina Maggie Ford,female,9,2,2,34.375 -0,2,Mr. Michel Navratil,male,36.5,0,2,26 -0,2,Rev. Thomas Roussel Davids Byles,male,42,0,0,13 -0,2,Rev. Robert James Bateman,male,51,0,0,12.525 -1,1,Mrs. Thomas (Edith Wearne) Pears,female,22,1,0,66.6 -0,3,Mr. Alfonzo Meo,male,55.5,0,0,8.05 -0,3,Mr. Austin Blyler van Billiard,male,40.5,0,2,14.5 -0,3,Mr. Ole Martin Olsen,male,27,0,0,7.3125 -0,1,Mr. Charles Duane Williams,male,51,0,1,61.3792 -1,3,Miss. Katherine Gilnagh,female,16,0,0,7.7333 -0,3,Mr. Harry Corn,male,30,0,0,8.05 -0,3,Mr. Mile Smiljanic,male,37,0,0,8.6625 -0,3,Master. Thomas Henry Sage,male,5,8,2,69.55 -0,3,Mr. John Hatfield Cribb,male,44,0,1,16.1 -1,2,Mrs. James (Elizabeth Inglis Milne) Watt,female,40,0,0,15.75 -0,3,Mr. John Viktor Bengtsson,male,26,0,0,7.775 -0,3,Mr. Jovo Calic,male,17,0,0,8.6625 -0,3,Master. Eino Viljami Panula,male,1,4,1,39.6875 -1,3,Master. Frank John William Goldsmith,male,9,0,2,20.525 -1,1,Mrs. (Edith Martha Bowerman) Chibnall,female,48,0,1,55 -0,3,Mrs. William (Anna Bernhardina Karlsson) Skoog,female,45,1,4,27.9 -0,1,Mr. John D Baumann,male,60,0,0,25.925 -0,3,Mr. Lee Ling,male,28,0,0,56.4958 -0,1,Mr. Wyckoff Van der hoef,male,61,0,0,33.5 -0,3,Master. Arthur Rice,male,4,4,1,29.125 -1,3,Miss. Eleanor Ileen Johnson,female,1,1,1,11.1333 -0,3,Mr. Antti Wilhelm Sivola,male,21,0,0,7.925 -0,1,Mr. James Clinch Smith,male,56,0,0,30.6958 -0,3,Mr. Klas Albin Klasen,male,18,1,1,7.8542 -0,3,Master. Henry Forbes Lefebre,male,5,3,1,25.4667 -0,1,Miss. Ann Elizabeth Isham,female,50,0,0,28.7125 -0,2,Mr. Reginald Hale,male,30,0,0,13 -0,3,Mr. Lionel Leonard,male,36,0,0,0 -0,3,Miss. Constance Gladys Sage,female,8,8,2,69.55 -0,2,Mr. Rene Pernot,male,39,0,0,15.05 -0,3,Master. Clarence Gustaf Hugo Asplund,male,9,4,2,31.3875 -1,2,Master. Richard F Becker,male,1,2,1,39 -1,3,Miss. Luise Gretchen Kink-Heilmann,female,4,0,2,22.025 -0,1,Mr. Hugh Roscoe Rood,male,39,0,0,50 -1,3,Mrs. Thomas (Johanna Godfrey) O'Brien,female,26,1,0,15.5 -1,1,Mr. Charles Hallace Romaine,male,45,0,0,26.55 -0,3,Mr. John Bourke,male,40,1,1,15.5 -0,3,Mr. Stjepan Turcin,male,36,0,0,7.8958 -1,2,Mrs. (Rosa) Pinsky,female,32,0,0,13 -0,2,Mr. William Carbines,male,19,0,0,13 -1,3,Miss. Carla Christine Nielsine Andersen-Jensen,female,19,1,0,7.8542 -1,2,Master. Michel M Navratil,male,3,1,1,26 -1,1,Mrs. James Joseph (Margaret Tobin) Brown,female,44,0,0,27.7208 -1,1,Miss. Elise Lurette,female,58,0,0,146.5208 -0,3,Mr. Robert Mernagh,male,28,0,0,7.75 -0,3,Mr. Karl Siegwart Andreas Olsen,male,42,0,1,8.4042 -1,3,Miss. Margaret Madigan,female,21,0,0,7.75 -0,2,Miss. Henriette Yrois,female,24,0,0,13 -0,3,Mr. Nestor Cyriel Vande Walle,male,28,0,0,9.5 -0,3,Mr. Frederick Sage,male,17,8,2,69.55 -0,3,Mr. Jakob Alfred Johanson,male,34,0,0,6.4958 -0,3,Mr. Gerious Youseff,male,45.5,0,0,7.225 -1,3,Mr. Gurshon Cohen,male,18,0,0,8.05 -0,3,Miss. Telma Matilda Strom,female,2,0,1,10.4625 -0,3,Mr. Karl Alfred Backstrom,male,32,1,0,15.85 -1,3,Mr. Nassef Cassem Albimona,male,26,0,0,18.7875 -1,3,Miss. Helen Carr,female,16,0,0,7.75 -1,1,Mr. Henry Blank,male,40,0,0,31 -0,3,Mr. Ahmed Ali,male,24,0,0,7.05 -1,2,Miss. Clear Annie Cameron,female,35,0,0,21 -0,3,Mr. John Henry Perkin,male,22,0,0,7.25 -0,2,Mr. Hans Kristensen Givard,male,30,0,0,13 -0,3,Mr. Philip Kiernan,male,22,1,0,7.75 -1,1,Miss. Madeleine Newell,female,31,1,0,113.275 -1,3,Miss. Eliina Honkanen,female,27,0,0,7.925 -0,2,Mr. Sidney Samuel Jacobsohn,male,42,1,0,27 -1,1,Miss. Albina Bazzani,female,32,0,0,76.2917 -0,2,Mr. Walter Harris,male,30,0,0,10.5 -1,3,Mr. Victor Francis Sunderland,male,16,0,0,8.05 -0,2,Mr. James H Bracken,male,27,0,0,13 -0,3,Mr. George Henry Green,male,51,0,0,8.05 -0,3,Mr. Christo Nenkoff,male,22,0,0,7.8958 -1,1,Mr. Frederick Maxfield Hoyt,male,38,1,0,90 -0,3,Mr. Karl Ivar Sven Berglund,male,22,0,0,9.35 -1,2,Mr. William John Mellors,male,19,0,0,10.5 -0,3,Mr. John Hall Lovell,male,20.5,0,0,7.25 -0,2,Mr. Arne Jonas Fahlstrom,male,18,0,0,13 -0,3,Miss. Mathilde Lefebre,female,12,3,1,25.4667 -1,1,Mrs. Henry Birkhardt (Irene Wallach) Harris,female,35,1,0,83.475 -0,3,Mr. Bengt Edvin Larsson,male,29,0,0,7.775 -0,2,Mr. Ernst Adolf Sjostedt,male,59,0,0,13.5 -1,3,Miss. Lillian Gertrud Asplund,female,5,4,2,31.3875 -0,2,Mr. Robert William Norman Leyson,male,24,0,0,10.5 -0,3,Miss. Alice Phoebe Harknett,female,21,0,0,7.55 -0,2,Mr. Stephen Hold,male,44,1,0,26 -1,2,Miss. Marjorie Collyer,female,8,0,2,26.25 -0,2,Mr. Frederick William Pengelly,male,19,0,0,10.5 -0,2,Mr. George Henry Hunt,male,33,0,0,12.275 -0,3,Miss. Thamine Zabour,female,19,1,0,14.4542 -1,3,Miss. Katherine Murphy,female,18,1,0,15.5 -0,2,Mr. Reginald Charles Coleridge,male,29,0,0,10.5 -0,3,Mr. Matti Alexanteri Maenpaa,male,22,0,0,7.125 -0,3,Mr. Sleiman Attalah,male,30,0,0,7.225 -0,1,Dr. William Edward Minahan,male,44,2,0,90 -0,3,Miss. Agda Thorilda Viktoria Lindahl,female,25,0,0,7.775 -1,2,Mrs. William (Anna) Hamalainen,female,24,0,2,14.5 -1,1,Mr. Richard Leonard Beckwith,male,37,1,1,52.5542 -0,2,Rev. Ernest Courtenay Carter,male,54,1,0,26 -0,3,Mr. James George Reed,male,18,0,0,7.25 -0,3,Mrs. Wilhelm (Elna Matilda Persson) Strom,female,29,1,1,10.4625 -0,1,Mr. William Thomas Stead,male,62,0,0,26.55 -0,3,Mr. William Arthur Lobb,male,30,1,0,16.1 -0,3,Mrs. Viktor (Helena Wilhelmina) Rosblom,female,41,0,2,20.2125 -1,3,Mrs. Darwis (Hanne Youssef Razi) Touma,female,29,0,2,15.2458 -1,1,Mrs. Gertrude Maybelle Thorne,female,38,0,0,79.2 -1,1,Miss. Gladys Cherry,female,30,0,0,86.5 -1,1,Miss. Anna Ward,female,35,0,0,512.3292 -1,2,Mrs. (Lutie Davis) Parrish,female,50,0,1,26 -1,3,Master. Edvin Rojj Felix Asplund,male,3,4,2,31.3875 -0,1,Mr. Emil Taussig,male,52,1,1,79.65 -0,1,Mr. William Harrison,male,40,0,0,0 -0,3,Miss. Delia Henry,female,21,0,0,7.75 -0,2,Mr. David Reeves,male,36,0,0,10.5 -0,3,Mr. Ernesti Arvid Panula,male,16,4,1,39.6875 -1,3,Mr. Ernst Ulrik Persson,male,25,1,0,7.775 -1,1,Mrs. William Thompson (Edith Junkins) Graham,female,58,0,1,153.4625 -1,1,Miss. Amelia Bissette,female,35,0,0,135.6333 -0,1,Mr. Alexander Cairns,male,28,0,0,31 -1,3,Mr. William Henry Tornquist,male,25,0,0,0 -1,2,Mrs. (Elizabeth Anne Maidment) Mellinger,female,41,0,1,19.5 -0,1,Mr. Charles H Natsch,male,37,0,1,29.7 -1,3,Miss. Hanora Healy,female,33,0,0,7.75 -1,1,Miss. Kornelia Theodosia Andrews,female,63,1,0,77.9583 -0,3,Miss. Augusta Charlotta Lindblom,female,45,0,0,7.75 -0,2,Mr. Francis Parkes,male,21,0,0,0 -0,3,Master. Eric Rice,male,7,4,1,29.125 -1,3,Mrs. Stanton (Rosa Hunt) Abbott,female,35,1,1,20.25 -0,3,Mr. Frank Duane,male,65,0,0,7.75 -0,3,Mr. Nils Johan Goransson Olsson,male,28,0,0,7.8542 -0,3,Mr. Alfons de Pelsmaeker,male,16,0,0,9.5 -1,3,Mr. Edward Arthur Dorking,male,19,0,0,8.05 -0,1,Mr. Richard William Smith,male,57,0,0,26 -0,3,Mr. Ivan Stankovic,male,33,0,0,8.6625 -1,3,Mr. Theodore de Mulder,male,30,0,0,9.5 -0,3,Mr. Penko Naidenoff,male,22,0,0,7.8958 -1,2,Mr. Masabumi Hosono,male,42,0,0,13 -1,3,Miss. Kate Connolly,female,22,0,0,7.75 -1,1,Miss. Ellen Barber,female,26,0,0,78.85 -1,1,Mrs. Dickinson H (Helen Walton) Bishop,female,19,1,0,91.0792 -0,2,Mr. Rene Jacques Levy,male,36,0,0,12.875 -0,3,Miss. Aloisia Haas,female,24,0,0,8.85 -0,3,Mr. Ivan Mineff,male,24,0,0,7.8958 -0,1,Mr. Ervin G Lewy,male,30,0,0,27.7208 -0,3,Mr. Mansour Hanna,male,23.5,0,0,7.2292 -0,1,Miss. Helen Loraine Allison,female,2,1,2,151.55 -1,1,Mr. Adolphe Saalfeld,male,47,0,0,30.5 -1,1,Mrs. James (Helene DeLaudeniere Chaput) Baxter,female,50,0,1,247.5208 -1,3,Miss. Anna Katherine Kelly,female,20,0,0,7.75 -1,3,Mr. Bernard McCoy,male,24,2,0,23.25 -0,3,Mr. William Cahoone Jr Johnson,male,19,0,0,0 -1,2,Miss. Nora A Keane,female,46,0,0,12.35 -0,3,Mr. Howard Hugh Williams,male,28,0,0,8.05 -1,1,Master. Hudson Trevor Allison,male,0.92,1,2,151.55 -1,1,Miss. Margaret Fleming,female,42,0,0,110.8833 -1,1,Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo) Penasco y Castellana,female,17,1,0,108.9 -0,2,Mr. Samuel Abelson,male,30,1,0,24 -1,1,Miss. Laura Mabel Francatelli,female,30,0,0,56.9292 -1,1,Miss. Margaret Bechstein Hays,female,24,0,0,83.1583 -1,1,Miss. Emily Borie Ryerson,female,18,2,2,262.375 -0,2,Mrs. William (Anna Sylfven) Lahtinen,female,26,1,1,26 -0,3,Mr. Ignjac Hendekovic,male,28,0,0,7.8958 -0,2,Mr. Benjamin Hart,male,43,1,1,26.25 -1,3,Miss. Helmina Josefina Nilsson,female,26,0,0,7.8542 -1,2,Mrs. Sinai (Miriam Sternin) Kantor,female,24,1,0,26 -0,2,Dr. Ernest Moraweck,male,54,0,0,14 -1,1,Miss. Mary Natalie Wick,female,31,0,2,164.8667 -1,1,Mrs. Frederic Oakley (Margaretta Corning Stone) Spedden,female,40,1,1,134.5 -0,3,Mr. Samuel Dennis,male,22,0,0,7.25 -0,3,Mr. Yoto Danoff,male,27,0,0,7.8958 -1,2,Miss. Hilda Mary Slayter,female,30,0,0,12.35 -1,2,Mrs. Albert Francis (Sylvia Mae Harbaugh) Caldwell,female,22,1,1,29 -0,3,Mr. George John Jr Sage,male,20,8,2,69.55 -1,1,Miss. Marie Grice Young,female,36,0,0,135.6333 -0,3,Mr. Johan Hansen Nysveen,male,61,0,0,6.2375 -1,2,Mrs. (Ada E Hall) Ball,female,36,0,0,13 -1,3,Mrs. Frank John (Emily Alice Brown) Goldsmith,female,31,1,1,20.525 -1,1,Miss. Jean Gertrude Hippach,female,16,0,1,57.9792 -1,3,Miss. Agnes McCoy,female,28,2,0,23.25 -0,1,Mr. Austen Partner,male,45.5,0,0,28.5 -0,1,Mr. George Edward Graham,male,38,0,1,153.4625 -0,3,Mr. Leo Edmondus Vander Planke,male,16,2,0,18 -1,1,Mrs. Henry William (Clara Heinsheimer) Frauenthal,female,42,1,0,133.65 -0,3,Mr. Mitto Denkoff,male,30,0,0,7.8958 -0,1,Mr. Thomas Clinton Pears,male,29,1,0,66.6 -1,1,Miss. Elizabeth Margaret Burns,female,41,0,0,134.5 -1,3,Mr. Karl Edwart Dahl,male,45,0,0,8.05 -0,1,Mr. Stephen Weart Blackwell,male,45,0,0,35.5 -1,2,Master. Edmond Roger Navratil,male,2,1,1,26 -1,1,Miss. Alice Elizabeth Fortune,female,24,3,2,263 -0,2,Mr. Erik Gustaf Collander,male,28,0,0,13 -0,2,Mr. Charles Frederick Waddington Sedgwick,male,25,0,0,13 -0,2,Mr. Stanley Hubert Fox,male,36,0,0,13 -1,2,Miss. Amelia Brown,female,24,0,0,13 -1,2,Miss. Marion Elsie Smith,female,40,0,0,13 -1,3,Mrs. Thomas Henry (Mary E Finck) Davison,female,34,1,0,16.1 -1,3,Master. William Loch Coutts,male,3,1,1,15.9 -0,3,Mr. Jovan Dimic,male,42,0,0,8.6625 -0,3,Mr. Nils Martin Odahl,male,23,0,0,9.225 -0,1,Mr. Fletcher Fellows Williams-Lambert,male,43,0,0,35 -0,3,Mr. Tannous Elias,male,15,1,1,7.2292 -0,3,Mr. Josef Arnold-Franchi,male,25,1,0,17.8 -0,3,Mr. Wazli Yousif,male,23,0,0,7.225 -0,3,Mr. Leo Peter Vanden Steen,male,28,0,0,9.5 -1,1,Miss. Elsie Edith Bowerman,female,22,0,1,55 -0,2,Miss. Annie Clemmer Funk,female,38,0,0,13 -1,3,Miss. Mary McGovern,female,22,0,0,7.8792 -1,3,Miss. Helen Mary Mockler,female,23,0,0,7.8792 -0,3,Mr. Wilhelm Skoog,male,40,1,4,27.9 -0,2,Mr. Sebastiano del Carlo,male,29,1,0,27.7208 -0,3,Mrs. (Catherine David) Barbara,female,45,0,1,14.4542 -0,3,Mr. Adola Asim,male,35,0,0,7.05 -0,3,Mr. Thomas O'Brien,male,27,1,0,15.5 -0,3,Mr. Mauritz Nils Martin Adahl,male,30,0,0,7.25 -1,1,Mrs. Frank Manley (Anna Sophia Atkinson) Warren,female,60,1,0,75.25 -1,3,Mrs. (Mantoura Boulos) Moussa,female,35,0,0,7.2292 -1,3,Miss. Annie Jermyn,female,22,0,0,7.75 -1,1,Mme. Leontine Pauline Aubart,female,24,0,0,69.3 -1,1,Mr. George Achilles Harder,male,25,1,0,55.4417 -0,3,Mr. Jakob Alfred Wiklund,male,18,1,0,6.4958 -0,3,Mr. William Thomas Beavan,male,19,0,0,8.05 -0,1,Mr. Sante Ringhini,male,22,0,0,135.6333 -0,3,Miss. Stina Viola Palsson,female,3,3,1,21.075 -1,1,Mrs. Edgar Joseph (Leila Saks) Meyer,female,25,1,0,82.1708 -1,3,Miss. Aurora Adelia Landergren,female,22,0,0,7.25 -0,1,Mr. Harry Elkins Widener,male,27,0,2,211.5 -0,3,Mr. Tannous Betros,male,20,0,0,4.0125 -0,3,Mr. Karl Gideon Gustafsson,male,19,0,0,7.775 -1,1,Miss. Rosalie Bidois,female,42,0,0,227.525 -1,3,Miss. Maria Nakid,female,1,0,2,15.7417 -0,3,Mr. Juho Tikkanen,male,32,0,0,7.925 -1,1,Mrs. Alexander Oskar (Mary Aline Towner) Holverson,female,35,1,0,52 -0,3,Mr. Vasil Plotcharsky,male,27,0,0,7.8958 -0,2,Mr. Charles Henry Davies,male,18,0,0,73.5 -0,3,Master. Sidney Leonard Goodwin,male,1,5,2,46.9 -1,2,Miss. Kate Buss,female,36,0,0,13 -0,3,Mr. Matthew Sadlier,male,19,0,0,7.7292 -1,2,Miss. Bertha Lehmann,female,17,0,0,12 -1,1,Mr. William Ernest Carter,male,36,1,2,120 -1,3,Mr. Carl Olof Jansson,male,21,0,0,7.7958 -0,3,Mr. Johan Birger Gustafsson,male,28,2,0,7.925 -1,1,Miss. Marjorie Newell,female,23,1,0,113.275 -1,3,Mrs. Hjalmar (Agnes Charlotta Bengtsson) Sandstrom,female,24,0,2,16.7 -0,3,Mr. Erik Johansson,male,22,0,0,7.7958 -0,3,Miss. Elina Olsson,female,31,0,0,7.8542 -0,2,Mr. Peter David McKane,male,46,0,0,26 -0,2,Dr. Alfred Pain,male,23,0,0,10.5 -1,2,Mrs. William H (Jessie L) Trout,female,28,0,0,12.65 -1,3,Mr. Juha Niskanen,male,39,0,0,7.925 -0,3,Mr. John Adams,male,26,0,0,8.05 -0,3,Miss. Mari Aina Jussila,female,21,1,0,9.825 -0,3,Mr. Pekka Pietari Hakkarainen,male,28,1,0,15.85 -0,3,Miss. Marija Oreskovic,female,20,0,0,8.6625 -0,2,Mr. Shadrach Gale,male,34,1,0,21 -0,3,Mr. Carl/Charles Peter Widegren,male,51,0,0,7.75 -1,2,Master. William Rowe Richards,male,3,1,1,18.75 -0,3,Mr. Hans Martin Monsen Birkeland,male,21,0,0,7.775 -0,3,Miss. Ida Lefebre,female,3,3,1,25.4667 -0,3,Mr. Todor Sdycoff,male,42,0,0,7.8958 -0,3,Mr. Henry Hart,male,27,0,0,6.8583 -1,1,Miss. Daisy E Minahan,female,33,1,0,90 -0,2,Mr. Alfred Fleming Cunningham,male,22,0,0,0 -1,3,Mr. Johan Julian Sundman,male,44,0,0,7.925 -0,3,Mrs. Thomas (Annie Louise Rowley) Meek,female,32,0,0,8.05 -1,2,Mrs. James Vivian (Lulu Thorne Christian) Drew,female,34,1,1,32.5 -1,2,Miss. Lyyli Karoliina Silven,female,18,0,2,13 -0,2,Mr. William John Matthews,male,30,0,0,13 -0,3,Miss. Catharina Van Impe,female,10,0,2,24.15 -0,3,Mr. David Charters,male,21,0,0,7.7333 -0,3,Mr. Leo Zimmerman,male,29,0,0,7.875 -0,3,Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren) Danbom,female,28,1,1,14.4 -0,3,Mr. Viktor Richard Rosblom,male,18,1,1,20.2125 -0,3,Mr. Phillippe Wiseman,male,54,0,0,7.25 -1,2,Mrs. Charles V (Ada Maria Winfield) Clarke,female,28,1,0,26 -1,2,Miss. Kate Florence Phillips,female,19,0,0,26 -0,3,Mr. James Flynn,male,28,0,0,7.75 -1,3,Mr. Berk (Berk Trembisky) Pickard,male,32,0,0,8.05 -1,1,Mr. Mauritz Hakan Bjornstrom-Steffansson,male,28,0,0,26.55 -1,3,Mrs. Percival (Florence Kate White) Thorneycroft,female,33,1,0,16.1 -1,2,Mrs. Charles Alexander (Alice Adelaide Slow) Louch,female,42,1,0,26 -0,3,Mr. Nikolai Erland Kallio,male,17,0,0,7.125 -0,1,Mr. William Baird Silvey,male,50,1,0,55.9 -1,1,Miss. Lucile Polk Carter,female,14,1,2,120 -0,3,Miss. Doolina Margaret Ford,female,21,2,2,34.375 -1,2,Mrs. Sidney (Emily Hocking) Richards,female,24,2,3,18.75 -0,1,Mr. Mark Fortune,male,64,1,4,263 -0,2,Mr. Johan Henrik Johannesson Kvillner,male,31,0,0,10.5 -1,2,Mrs. Benjamin (Esther Ada Bloomfield) Hart,female,45,1,1,26.25 -0,3,Mr. Leon Hampe,male,20,0,0,9.5 -0,3,Mr. Johan Emil Petterson,male,25,1,0,7.775 -1,2,Ms. Encarnacion Reynaldo,female,28,0,0,13 -1,3,Mr. Bernt Johannesen-Bratthammer,male,29,0,0,8.1125 -1,1,Master. Washington Dodge,male,4,0,2,81.8583 -1,2,Miss. Madeleine Violet Mellinger,female,13,0,1,19.5 -1,1,Mr. Frederic Kimber Seward,male,34,0,0,26.55 -1,3,Miss. Marie Catherine Baclini,female,5,2,1,19.2583 -1,1,Major. Arthur Godfrey Peuchen,male,52,0,0,30.5 -0,2,Mr. Edwy Arthur West,male,36,1,2,27.75 -0,3,Mr. Ingvald Olai Olsen Hagland,male,28,1,0,19.9667 -0,1,Mr. Benjamin Laventall Foreman,male,30,0,0,27.75 -1,1,Mr. Samuel L Goldenberg,male,49,1,0,89.1042 -0,3,Mr. Joseph Peduzzi,male,24,0,0,8.05 -1,3,Mr. Ivan Jalsevac,male,29,0,0,7.8958 -0,1,Mr. Francis Davis Millet,male,65,0,0,26.55 -1,1,Mrs. Frederick R (Marion) Kenyon,female,41,1,0,51.8625 -1,2,Miss. Ellen Toomey,female,50,0,0,10.5 -0,3,Mr. Maurice O'Connor,male,17,0,0,7.75 -1,1,Mr. Harry Anderson,male,48,0,0,26.55 -0,3,Mr. William Morley,male,34,0,0,8.05 -0,1,Mr. Arthur H Gee,male,47,0,0,38.5 -0,2,Mr. Jacob Christian Milling,male,48,0,0,13 -0,3,Mr. Simon Maisner,male,34,0,0,8.05 -0,3,Mr. Manuel Estanslas Goncalves,male,38,0,0,7.05 -0,2,Mr. William Campbell,male,21,0,0,0 -0,1,Mr. John Montgomery Smart,male,56,0,0,26.55 -0,3,Mr. James Scanlan,male,22,0,0,7.725 -1,3,Miss. Helene Barbara Baclini,female,0.75,2,1,19.2583 -0,3,Mr. Arthur Keefe,male,39,0,0,7.25 -0,3,Mr. Luka Cacic,male,38,0,0,8.6625 -1,2,Mrs. Edwy Arthur (Ada Mary Worth) West,female,33,1,2,27.75 -1,2,Mrs. Amin S (Marie Marthe Thuillard) Jerwan,female,23,0,0,13.7917 -0,3,Miss. Ida Sofia Strandberg,female,22,0,0,9.8375 -0,1,Mr. George Quincy Clifford,male,40,0,0,52 -0,2,Mr. Peter Henry Renouf,male,34,1,0,21 -0,3,Mr. Lewis Richard Braund,male,29,1,0,7.0458 -0,3,Mr. Nils August Karlsson,male,22,0,0,7.5208 -1,3,Miss. Hildur E Hirvonen,female,2,0,1,12.2875 -0,3,Master. Harold Victor Goodwin,male,9,5,2,46.9 -0,2,Mr. Anthony Wood Frost,male,37,0,0,0 -0,3,Mr. Richard Henry Rouse,male,50,0,0,8.05 -1,3,Mrs. (Hedwig) Turkula,female,63,0,0,9.5875 -1,1,Mr. Dickinson H Bishop,male,25,1,0,91.0792 -0,3,Miss. Jeannie Lefebre,female,8,3,1,25.4667 -1,1,Mrs. Frederick Maxfield (Jane Anne Forby) Hoyt,female,35,1,0,90 -0,1,Mr. Edward Austin Kent,male,58,0,0,29.7 -0,3,Mr. Francis William Somerton,male,30,0,0,8.05 -1,3,Master. Eden Leslie Coutts,male,9,1,1,15.9 -0,3,Mr. Konrad Mathias Reiersen Hagland,male,19,1,0,19.9667 -0,3,Mr. Einar Windelov,male,21,0,0,7.25 -0,1,Mr. Harry Markland Molson,male,55,0,0,30.5 -0,1,Mr. Ramon Artagaveytia,male,71,0,0,49.5042 -0,3,Mr. Edward Roland Stanley,male,21,0,0,8.05 -0,3,Mr. Gerious Yousseff,male,26,0,0,14.4583 -1,1,Miss. Elizabeth Mussey Eustis,female,54,1,0,78.2667 -0,3,Mr. Frederick William Shellard,male,55,0,0,15.1 -0,1,Mrs. Hudson J C (Bessie Waldo Daniels) Allison,female,25,1,2,151.55 -0,3,Mr. Olof Svensson,male,24,0,0,7.7958 -0,3,Mr. Petar Calic,male,17,0,0,8.6625 -0,3,Miss. Mary Canavan,female,21,0,0,7.75 -0,3,Miss. Bridget Mary O'Sullivan,female,21,0,0,7.6292 -0,3,Miss. Kristina Sofia Laitinen,female,37,0,0,9.5875 -1,1,Miss. Roberta Maioni,female,16,0,0,86.5 -0,1,Mr. Victor de Satode Penasco y Castellana,male,18,1,0,108.9 -1,2,Mrs. Frederick Charles (Jane Richards) Quick,female,33,0,2,26 -1,1,Mr. George Bradley,male,37,0,0,26.55 -0,3,Mr. Henry Margido Olsen,male,28,0,0,22.525 -1,3,Mr. Fang Lang,male,26,0,0,56.4958 -1,3,Mr. Eugene Patrick Daly,male,29,0,0,7.75 -0,3,Mr. James Webber,male,66,0,0,8.05 -1,1,Mr. James Robert McGough,male,36,0,0,26.2875 -1,1,Mrs. Martin (Elizabeth L. Barrett) Rothschild,female,54,1,0,59.4 -0,3,Mr. Satio Coleff,male,24,0,0,7.4958 -0,1,Mr. William Anderson Walker,male,47,0,0,34.0208 -1,2,Mrs. (Amelia Milley) Lemore,female,34,0,0,10.5 -0,3,Mr. Patrick Ryan,male,30,0,0,24.15 -1,2,Mrs. William A (Florence Agnes Hughes) Angle,female,36,1,0,26 -0,3,Mr. Stefo Pavlovic,male,32,0,0,7.8958 -1,1,Miss. Anne Perreault,female,30,0,0,93.5 -0,3,Mr. Janko Vovk,male,22,0,0,7.8958 -0,3,Mr. Sarkis Lahoud,male,35,0,0,7.225 -1,1,Mrs. Louis Albert (Ida Sophia Fischer) Hippach,female,44,0,1,57.9792 -0,3,Mr. Fared Kassem,male,18,0,0,7.2292 -0,3,Mr. James Farrell,male,40.5,0,0,7.75 -1,2,Miss. Lucy Ridsdale,female,50,0,0,10.5 -0,1,Mr. John Farthing,male,49,0,0,221.7792 -0,3,Mr. Johan Werner Salonen,male,39,0,0,7.925 -0,2,Mr. Richard George Hocking,male,23,2,1,11.5 -1,2,Miss. Phyllis May Quick,female,2,1,1,26 -0,3,Mr. Nakli Toufik,male,17,0,0,7.2292 -0,3,Mr. Joseph Jr Elias,male,17,1,1,7.2292 -1,3,Mrs. Catherine (Catherine Rizk) Peter,female,24,0,2,22.3583 -0,3,Miss. Marija Cacic,female,30,0,0,8.6625 -1,2,Miss. Eva Miriam Hart,female,7,0,2,26.25 -0,1,Major. Archibald Willingham Butt,male,45,0,0,26.55 -1,1,Miss. Bertha LeRoy,female,30,0,0,106.425 -0,3,Mr. Samuel Beard Risien,male,69,0,0,14.5 -1,1,Miss. Hedwig Margaritha Frolicher,female,22,0,2,49.5 -1,1,Miss. Harriet R Crosby,female,36,0,2,71 -0,3,Miss. Ingeborg Constanzia Andersson,female,9,4,2,31.275 -0,3,Miss. Sigrid Elisabeth Andersson,female,11,4,2,31.275 -1,2,Mr. Edward Beane,male,32,1,0,26 -0,1,Mr. Walter Donald Douglas,male,50,1,0,106.425 -0,1,Mr. Arthur Ernest Nicholson,male,64,0,0,26 -1,2,Mrs. Edward (Ethel Clarke) Beane,female,19,1,0,26 -1,2,Mr. Julian Padro y Manent,male,27,0,0,13.8625 -0,3,Mr. Frank John Goldsmith,male,33,1,1,20.525 -1,2,Master. John Morgan Jr Davies,male,8,1,1,36.75 -1,1,Mr. John Borland Jr Thayer,male,17,0,2,110.8833 -0,2,Mr. Percival James R Sharp,male,27,0,0,26 -0,3,Mr. Timothy O'Brien,male,21,0,0,7.8292 -1,3,Mr. Fahim Leeni,male,22,0,0,7.225 -1,3,Miss. Velin Ohman,female,22,0,0,7.775 -0,1,Mr. George Wright,male,62,0,0,26.55 -1,1,Lady. (Lucille Christiana Sutherland)Duff Gordon,female,48,1,0,39.6 -0,1,Mr. Victor Robbins,male,45,0,0,227.525 -1,1,Mrs. Emil (Tillie Mandelbaum) Taussig,female,39,1,1,79.65 -1,3,Mrs. Guillaume Joseph (Emma) de Messemaeker,female,36,1,0,17.4 -0,3,Mr. Thomas Rowan Morrow,male,30,0,0,7.75 -0,3,Mr. Husein Sivic,male,40,0,0,7.8958 -0,2,Mr. Robert Douglas Norman,male,28,0,0,13.5 -0,3,Mr. John Simmons,male,40,0,0,8.05 -0,3,Miss. (Marion Ogden) Meanwell,female,62,0,0,8.05 -0,3,Mr. Alfred J Davies,male,24,2,0,24.15 -0,3,Mr. Ilia Stoytcheff,male,19,0,0,7.8958 -0,3,Mrs. Nils (Alma Cornelia Berglund) Palsson,female,29,0,4,21.075 -0,3,Mr. Tannous Doharr,male,28,0,0,7.2292 -1,3,Mr. Carl Jonsson,male,32,0,0,7.8542 -1,2,Mr. George Harris,male,62,0,0,10.5 -1,1,Mrs. Edward Dale (Charlotte Lamson) Appleton,female,53,2,0,51.4792 -1,1,Mr. John Irwin Flynn,male,36,0,0,26.3875 -1,3,Miss. Mary Kelly,female,22,0,0,7.75 -0,3,Mr. Alfred George John Rush,male,16,0,0,8.05 -0,3,Mr. George Patchett,male,19,0,0,14.5 -1,2,Miss. Ethel Garside,female,34,0,0,13 -1,1,Mrs. William Baird (Alice Munger) Silvey,female,39,1,0,55.9 -0,3,Mrs. Joseph (Maria Elias) Caram,female,18,1,0,14.4583 -1,3,Mr. Eiriik Jussila,male,32,0,0,7.925 -1,2,Miss. Julie Rachel Christy,female,25,1,1,30 -1,1,Mrs. John Borland (Marian Longstreth Morris) Thayer,female,39,1,1,110.8833 -0,2,Mr. William James Downton,male,54,0,0,26 -0,1,Mr. John Hugo Ross,male,36,0,0,40.125 -0,3,Mr. Uscher Paulner,male,16,0,0,8.7125 -1,1,Miss. Ruth Taussig,female,18,0,2,79.65 -0,2,Mr. John Denzil Jarvis,male,47,0,0,15 -1,1,Mr. Maxmillian Frolicher-Stehli,male,60,1,1,79.2 -0,3,Mr. Eliezer Gilinski,male,22,0,0,8.05 -0,3,Mr. Joseph Murdlin,male,22,0,0,8.05 -0,3,Mr. Matti Rintamaki,male,35,0,0,7.125 -1,1,Mrs. Walter Bertram (Martha Eustis) Stephenson,female,52,1,0,78.2667 -0,3,Mr. William James Elsbury,male,47,0,0,7.25 -0,3,Miss. Mary Bourke,female,40,0,2,7.75 -0,2,Mr. John Henry Chapman,male,37,1,0,26 -0,3,Mr. Jean Baptiste Van Impe,male,36,1,1,24.15 -1,2,Miss. Jessie Wills Leitch,female,31,0,0,33 -0,3,Mr. Alfred Johnson,male,49,0,0,0 -0,3,Mr. Hanna Boulos,male,18,0,0,7.225 -1,1,Sir. Cosmo Edmund Duff Gordon,male,49,1,0,56.9292 -1,2,Mrs. Sidney Samuel (Amy Frances Christy) Jacobsohn,female,24,2,1,27 -0,3,Mr. Petco Slabenoff,male,42,0,0,7.8958 -0,1,Mr. Charles H Harrington,male,37,0,0,42.4 -0,3,Mr. Ernst William Torber,male,44,0,0,8.05 -1,1,Mr. Harry Homer,male,35,0,0,26.55 -0,3,Mr. Edvard Bengtsson Lindell,male,36,1,0,15.55 -0,3,Mr. Milan Karaic,male,30,0,0,7.8958 -1,1,Mr. Robert Williams Daniel,male,27,0,0,30.5 -1,2,Mrs. Joseph (Juliette Marie Louise Lafargue) Laroche,female,22,1,2,41.5792 -1,1,Miss. Elizabeth W Shutes,female,40,0,0,153.4625 -0,3,Mrs. Anders Johan (Alfrida Konstantia Brogren) Andersson,female,39,1,5,31.275 -0,3,Mr. Jose Neto Jardin,male,21,0,0,7.05 -1,3,Miss. Margaret Jane Murphy,female,18,1,0,15.5 -0,3,Mr. John Horgan,male,22,0,0,7.75 -0,3,Mr. William Alfred Brocklebank,male,35,0,0,8.05 -1,2,Miss. Alice Herman,female,24,1,2,65 -0,3,Mr. Ernst Gilbert Danbom,male,34,1,1,14.4 -0,3,Mrs. William Arthur (Cordelia K Stanlick) Lobb,female,26,1,0,16.1 -1,2,Miss. Marion Louise Becker,female,4,2,1,39 -0,2,Mr. Lawrence Gavey,male,26,0,0,10.5 -0,3,Mr. Antoni Yasbeck,male,27,1,0,14.4542 -1,1,Mr. Edwin Nelson Jr Kimball,male,42,1,0,52.5542 -1,3,Mr. Sahid Nakid,male,20,1,1,15.7417 -0,3,Mr. Henry Damsgaard Hansen,male,21,0,0,7.8542 -0,3,Mr. David John Bowen,male,21,0,0,16.1 -0,1,Mr. Frederick Sutton,male,61,0,0,32.3208 -0,2,Rev. Charles Leonard Kirkland,male,57,0,0,12.35 -1,1,Miss. Gretchen Fiske Longley,female,21,0,0,77.9583 -0,3,Mr. Guentcho Bostandyeff,male,26,0,0,7.8958 -0,3,Mr. Patrick D O'Connell,male,18,0,0,7.7333 -1,1,Mr. Algernon Henry Wilson Barkworth,male,80,0,0,30 -0,3,Mr. Johan Svensson Lundahl,male,51,0,0,7.0542 -1,1,Dr. Max Stahelin-Maeglin,male,32,0,0,30.5 -0,1,Mr. William Henry Marsh Parr,male,30,0,0,0 -0,3,Miss. Mabel Skoog,female,9,3,2,27.9 -1,2,Miss. Mary Davis,female,28,0,0,13 -0,3,Mr. Antti Gustaf Leinonen,male,32,0,0,7.925 -0,2,Mr. Harvey Collyer,male,31,1,1,26.25 -0,3,Mrs. Juha (Maria Emilia Ojala) Panula,female,41,0,5,39.6875 -0,3,Mr. Percival Thorneycroft,male,37,1,0,16.1 -0,3,Mr. Hans Peder Jensen,male,20,0,0,7.8542 -1,1,Mlle. Emma Sagesser,female,24,0,0,69.3 -0,3,Miss. Margit Elizabeth Skoog,female,2,3,2,27.9 -1,3,Mr. Choong Foo,male,32,0,0,56.4958 -1,3,Miss. Eugenie Baclini,female,0.75,2,1,19.2583 -1,1,Mr. Henry Sleeper Harper,male,48,1,0,76.7292 -0,3,Mr. Liudevit Cor,male,19,0,0,7.8958 -1,1,Col. Oberst Alfons Simonius-Blumer,male,56,0,0,35.5 -0,3,Mr. Edward Willey,male,21,0,0,7.55 -1,3,Miss. Amy Zillah Elsie Stanley,female,23,0,0,7.55 -0,3,Mr. Mito Mitkoff,male,23,0,0,7.8958 -1,2,Miss. Elsie Doling,female,18,0,1,23 -0,3,Mr. Johannes Halvorsen Kalvik,male,21,0,0,8.4333 -1,3,Miss. Hanora O'Leary,female,16,0,0,7.8292 -0,3,Miss. Hanora Hegarty,female,18,0,0,6.75 -0,2,Mr. Leonard Mark Hickman,male,24,2,0,73.5 -0,3,Mr. Alexander Radeff,male,27,0,0,7.8958 -0,3,Mrs. John (Catherine) Bourke,female,32,1,1,15.5 -0,2,Mr. George Floyd Eitemiller,male,23,0,0,13 -0,1,Mr. Arthur Webster Newell,male,58,0,2,113.275 -1,1,Dr. Henry William Frauenthal,male,50,2,0,133.65 -0,3,Mr. Mohamed Badt,male,40,0,0,7.225 -0,1,Mr. Edward Pomeroy Colley,male,47,0,0,25.5875 -0,3,Mr. Peju Coleff,male,36,0,0,7.4958 -1,3,Mr. Eino William Lindqvist,male,20,1,0,7.925 -0,2,Mr. Lewis Hickman,male,32,2,0,73.5 -0,2,Mr. Reginald Fenton Butler,male,25,0,0,13 -0,3,Mr. Knud Paust Rommetvedt,male,49,0,0,7.775 -0,3,Mr. Jacob Cook,male,43,0,0,8.05 -1,1,Mrs. Elmer Zebley (Juliet Cummins Wright) Taylor,female,48,1,0,52 -1,2,Mrs. Thomas William Solomon (Elizabeth Catherine Ford) Brown,female,40,1,1,39 -0,1,Mr. Thornton Davidson,male,31,1,0,52 -0,2,Mr. Henry Michael Mitchell,male,70,0,0,10.5 -1,2,Mr. Charles Wilhelms,male,31,0,0,13 -0,2,Mr. Ennis Hastings Watson,male,19,0,0,0 -0,3,Mr. Gustaf Hjalmar Edvardsson,male,18,0,0,7.775 -0,3,Mr. Frederick Charles Sawyer,male,24.5,0,0,8.05 -1,3,Miss. Anna Sofia Turja,female,18,0,0,9.8417 -0,3,Mrs. Frederick (Augusta Tyler) Goodwin,female,43,1,6,46.9 -1,1,Mr. Thomas Drake Martinez Cardeza,male,36,0,1,512.3292 -0,3,Miss. Katie Peters,female,28,0,0,8.1375 -1,1,Mr. Hammad Hassab,male,27,0,0,76.7292 -0,3,Mr. Thor Anderson Olsvigen,male,20,0,0,9.225 -0,3,Mr. Charles Edward Goodwin,male,14,5,2,46.9 -0,2,Mr. Thomas William Solomon Brown,male,60,1,1,39 -0,2,Mr. Joseph Philippe Lemercier Laroche,male,25,1,2,41.5792 -0,3,Mr. Jaako Arnold Panula,male,14,4,1,39.6875 -0,3,Mr. Branko Dakic,male,19,0,0,10.1708 -0,3,Mr. Eberhard Thelander Fischer,male,18,0,0,7.7958 -1,1,Miss. Georgette Alexandra Madill,female,15,0,1,211.3375 -1,1,Mr. Albert Adrian Dick,male,31,1,0,57 -1,3,Miss. Manca Karun,female,4,0,1,13.4167 -1,3,Mr. Ali Lam,male,37,0,0,56.4958 -0,3,Mr. Khalil Saad,male,25,0,0,7.225 -0,1,Col. John Weir,male,60,0,0,26.55 -0,2,Mr. Charles Henry Chapman,male,52,0,0,13.5 -0,3,Mr. James Kelly,male,44,0,0,8.05 -1,3,Miss. Katherine Mullens,female,19,0,0,7.7333 -0,1,Mr. John Borland Thayer,male,49,1,1,110.8833 -0,3,Mr. Adolf Mathias Nicolai Olsen Humblen,male,42,0,0,7.65 -1,1,Mrs. John Jacob (Madeleine Talmadge Force) Astor,female,18,1,0,227.525 -1,1,Mr. Spencer Victor Silverthorne,male,35,0,0,26.2875 -0,3,Miss. Saiide Barbara,female,18,0,1,14.4542 -0,3,Mr. Martin Gallagher,male,25,0,0,7.7417 -0,3,Mr. Henrik Juul Hansen,male,26,1,0,7.8542 -0,2,Mr. Henry Samuel Morley,male,39,0,0,26 -1,2,Mrs. Florence Kelly,female,45,0,0,13.5 -1,1,Mr. Edward Pennington Calderhead,male,42,0,0,26.2875 -1,1,Miss. Alice Cleaver,female,22,0,0,151.55 -1,3,Master. Halim Gonios Moubarek,male,4,1,1,15.2458 -1,1,Mlle. Berthe Antonine Mayne,female,24,0,0,49.5042 -0,1,Mr. Herman Klaber,male,41,0,0,26.55 -1,1,Mr. Elmer Zebley Taylor,male,48,1,0,52 -0,3,Mr. August Viktor Larsson,male,29,0,0,9.4833 -0,2,Mr. Samuel Greenberg,male,52,0,0,13 -0,3,Mr. Peter Andreas Lauritz Andersen Soholt,male,19,0,0,7.65 -1,1,Miss. Caroline Louise Endres,female,38,0,0,227.525 -1,2,Miss. Edwina Celia Troutt,female,27,0,0,10.5 -0,3,Mr. Malkolm Joackim Johnson,male,33,0,0,7.775 -1,2,Miss. Annie Jessie Harper,female,6,0,1,33 -0,3,Mr. Svend Lauritz Jensen,male,17,1,0,7.0542 -0,2,Mr. William Henry Gillespie,male,34,0,0,13 -0,2,Mr. Henry Price Hodges,male,50,0,0,13 -1,1,Mr. Norman Campbell Chambers,male,27,1,0,53.1 -0,3,Mr. Luka Oreskovic,male,20,0,0,8.6625 -1,2,Mrs. Peter Henry (Lillian Jefferys) Renouf,female,30,3,0,21 -1,3,Miss. Margareth Mannion,female,28,0,0,7.7375 -0,2,Mr. Kurt Arnold Gottfrid Bryhl,male,25,1,0,26 -0,3,Miss. Pieta Sofia Ilmakangas,female,25,1,0,7.925 -1,1,Miss. Elisabeth Walton Allen,female,29,0,0,211.3375 -0,3,Mr. Houssein G N Hassan,male,11,0,0,18.7875 -0,2,Mr. Robert J Knight,male,41,0,0,0 -0,2,Mr. William John Berriman,male,23,0,0,13 -0,2,Mr. Moses Aaron Troupiansky,male,23,0,0,13 -0,3,Mr. Leslie Williams,male,28.5,0,0,16.1 -0,3,Mrs. Edward (Margaret Ann Watson) Ford,female,48,1,3,34.375 -1,1,Mr. Gustave J Lesurer,male,35,0,0,512.3292 -0,3,Mr. Kanio Ivanoff,male,20,0,0,7.8958 -0,3,Mr. Minko Nankoff,male,32,0,0,7.8958 -1,1,Mr. Walter James Hawksford,male,45,0,0,30 -0,1,Mr. Tyrell William Cavendish,male,36,1,0,78.85 -1,1,Miss. Susan Parker Ryerson,female,21,2,2,262.375 -0,3,Mr. Neal McNamee,male,24,1,0,16.1 -1,3,Mr. Juho Stranden,male,31,0,0,7.925 -0,1,Capt. Edward Gifford Crosby,male,70,1,1,71 -0,3,Mr. Rossmore Edward Abbott,male,16,1,1,20.25 -1,2,Miss. Anna Sinkkonen,female,30,0,0,13 -0,1,Mr. Daniel Warner Marvin,male,19,1,0,53.1 -0,3,Mr. Michael Connaghton,male,31,0,0,7.75 -1,2,Miss. Joan Wells,female,4,1,1,23 -1,3,Master. Meier Moor,male,6,0,1,12.475 -0,3,Mr. Johannes Joseph Vande Velde,male,33,0,0,9.5 -0,3,Mr. Lalio Jonkoff,male,23,0,0,7.8958 -1,2,Mrs. Samuel (Jane Laver) Herman,female,48,1,2,65 -1,2,Master. Viljo Hamalainen,male,0.67,1,1,14.5 -0,3,Mr. August Sigfrid Carlsson,male,28,0,0,7.7958 -0,2,Mr. Percy Andrew Bailey,male,18,0,0,11.5 -0,3,Mr. Thomas Leonard Theobald,male,34,0,0,8.05 -1,1,the Countess. of (Lucy Noel Martha Dyer-Edwards) Rothes,female,33,0,0,86.5 -0,3,Mr. John Garfirth,male,23,0,0,14.5 -0,3,Mr. Iisakki Antino Aijo Nirva,male,41,0,0,7.125 -1,3,Mr. Hanna Assi Barah,male,20,0,0,7.2292 -1,1,Mrs. William Ernest (Lucile Polk) Carter,female,36,1,2,120 -0,3,Mr. Hans Linus Eklund,male,16,0,0,7.775 -1,1,Mrs. John C (Anna Andrews) Hogeboom,female,51,1,0,77.9583 -0,1,Dr. Arthur Jackson Brewe,male,46,0,0,39.6 -0,3,Miss. Mary Mangan,female,30.5,0,0,7.75 -0,3,Mr. Daniel J Moran,male,28,1,0,24.15 -0,3,Mr. Daniel Danielsen Gronnestad,male,32,0,0,8.3625 -0,3,Mr. Rene Aime Lievens,male,24,0,0,9.5 -0,3,Mr. Niels Peder Jensen,male,48,0,0,7.8542 -0,2,Mrs. (Mary) Mack,female,57,0,0,10.5 -0,3,Mr. Dibo Elias,male,29,0,0,7.225 -1,2,Mrs. Elizabeth (Eliza Needs) Hocking,female,54,1,3,23 -0,3,Mr. Pehr Fabian Oliver Malkolm Myhrman,male,18,0,0,7.75 -0,3,Mr. Roger Tobin,male,20,0,0,7.75 -1,3,Miss. Virginia Ethel Emanuel,female,5,0,0,12.475 -0,3,Mr. Thomas J Kilgannon,male,22,0,0,7.7375 -1,1,Mrs. Edward Scott (Elisabeth Walton McMillan) Robert,female,43,0,1,211.3375 -1,3,Miss. Banoura Ayoub,female,13,0,0,7.2292 -1,1,Mrs. Albert Adrian (Vera Gillespie) Dick,female,17,1,0,57 -0,1,Mr. Milton Clyde Long,male,29,0,0,30 -0,3,Mr. Andrew G Johnston,male,35,1,2,23.45 -0,3,Mr. William Ali,male,25,0,0,7.05 -0,3,Mr. Abraham (David Lishin) Harmer,male,25,0,0,7.25 -1,3,Miss. Anna Sofia Sjoblom,female,18,0,0,7.4958 -0,3,Master. George Hugh Rice,male,8,4,1,29.125 -1,3,Master. Bertram Vere Dean,male,1,1,2,20.575 -0,1,Mr. Benjamin Guggenheim,male,46,0,0,79.2 -0,3,Mr. Andrew Keane,male,20,0,0,7.75 -0,2,Mr. Alfred Gaskell,male,16,0,0,26 -0,3,Miss. Stella Anna Sage,female,21,8,2,69.55 -0,1,Mr. William Fisher Hoyt,male,43,0,0,30.6958 -0,3,Mr. Ristiu Dantcheff,male,25,0,0,7.8958 -0,2,Mr. Richard Otter,male,39,0,0,13 -1,1,Dr. Alice (Farnham) Leader,female,49,0,0,25.9292 -1,3,Mrs. Mara Osman,female,31,0,0,8.6833 -0,3,Mr. Yousseff Ibrahim Shawah,male,30,0,0,7.2292 -0,3,Mrs. Jean Baptiste (Rosalie Paula Govaert) Van Impe,female,30,1,1,24.15 -0,2,Mr. Martin Ponesell,male,34,0,0,13 -1,2,Mrs. Harvey (Charlotte Annie Tate) Collyer,female,31,1,1,26.25 -1,1,Master. William Thornton II Carter,male,11,1,2,120 -1,3,Master. Assad Alexander Thomas,male,0.42,0,1,8.5167 -1,3,Mr. Oskar Arvid Hedman,male,27,0,0,6.975 -0,3,Mr. Karl Johan Johansson,male,31,0,0,7.775 -0,1,Mr. Thomas Jr Andrews,male,39,0,0,0 -0,3,Miss. Ellen Natalia Pettersson,female,18,0,0,7.775 -0,2,Mr. August Meyer,male,39,0,0,13 -1,1,Mrs. Norman Campbell (Bertha Griggs) Chambers,female,33,1,0,53.1 -0,3,Mr. William Alexander,male,26,0,0,7.8875 -0,3,Mr. James Lester,male,39,0,0,24.15 -0,2,Mr. Richard James Slemen,male,35,0,0,10.5 -0,3,Miss. Ebba Iris Alfrida Andersson,female,6,4,2,31.275 -0,3,Mr. Ernest Portage Tomlin,male,30.5,0,0,8.05 -0,1,Mr. Richard Fry,male,39,0,0,0 -0,3,Miss. Wendla Maria Heininen,female,23,0,0,7.925 -0,2,Mr. Albert Mallet,male,31,1,1,37.0042 -0,3,Mr. John Fredrik Alexander Holm,male,43,0,0,6.45 -0,3,Master. Karl Thorsten Skoog,male,10,3,2,27.9 -1,1,Mrs. Charles Melville (Clara Jennings Gregg) Hays,female,52,1,1,93.5 -1,3,Mr. Nikola Lulic,male,27,0,0,8.6625 -0,1,Jonkheer. John George Reuchlin,male,38,0,0,0 -1,3,Mrs. (Beila) Moor,female,27,0,1,12.475 -0,3,Master. Urho Abraham Panula,male,2,4,1,39.6875 -0,3,Mr. John Flynn,male,36,0,0,6.95 -0,3,Mr. Len Lam,male,23,0,0,56.4958 -1,2,Master. Andre Mallet,male,1,0,2,37.0042 -1,3,Mr. Thomas Joseph McCormack,male,19,0,0,7.75 -1,1,Mrs. George Nelson (Martha Evelyn) Stone,female,62,0,0,80 -1,3,Mrs. Antoni (Selini Alexander) Yasbeck,female,15,1,0,14.4542 -1,2,Master. George Sibley Richards,male,0.83,1,1,18.75 -0,3,Mr. Amin Saad,male,30,0,0,7.2292 -0,3,Mr. Albert Augustsson,male,23,0,0,7.8542 -0,3,Mr. Owen George Allum,male,18,0,0,8.3 -1,1,Miss. Sara Rebecca Compton,female,39,1,1,83.1583 -0,3,Mr. Jakob Pasic,male,21,0,0,8.6625 -0,3,Mr. Maurice Sirota,male,20,0,0,8.05 -1,3,Mr. Chang Chip,male,32,0,0,56.4958 -1,1,Mr. Pierre Marechal,male,29,0,0,29.7 -0,3,Mr. Ilmari Rudolf Alhomaki,male,20,0,0,7.925 -0,2,Mr. Thomas Charles Mudd,male,16,0,0,10.5 -1,1,Miss. Augusta Serepeca,female,30,0,0,31 -0,3,Mr. Peter L Lemberopolous,male,34.5,0,0,6.4375 -0,3,Mr. Jeso Culumovic,male,17,0,0,8.6625 -0,3,Mr. Anthony Abbing,male,42,0,0,7.55 -0,3,Mr. Douglas Bullen Sage,male,18,8,2,69.55 -0,3,Mr. Marin Markoff,male,35,0,0,7.8958 -0,2,Rev. John Harper,male,28,0,1,33 -1,1,Mrs. Samuel L (Edwiga Grabowska) Goldenberg,female,40,1,0,89.1042 -0,3,Master. Sigvard Harald Elias Andersson,male,4,4,2,31.275 -0,3,Mr. Johan Svensson,male,74,0,0,7.775 -0,3,Miss. Nourelain Boulos,female,9,1,1,15.2458 -1,1,Miss. Mary Conover Lines,female,16,0,1,39.4 -0,2,Mrs. Ernest Courtenay (Lilian Hughes) Carter,female,44,1,0,26 -1,3,Mrs. Sam (Leah Rosen) Aks,female,18,0,1,9.35 -1,1,Mrs. George Dennick (Mary Hitchcock) Wick,female,45,1,1,164.8667 -1,1,Mr. Peter Denis Daly,male,51,0,0,26.55 -1,3,Mrs. Solomon (Latifa Qurban) Baclini,female,24,0,3,19.2583 -0,3,Mr. Raihed Razi,male,30,0,0,7.2292 -0,3,Mr. Claus Peter Hansen,male,41,2,0,14.1083 -0,2,Mr. Frederick Edward Giles,male,21,1,0,11.5 -1,1,Mrs. Frederick Joel (Margaret Welles Barron) Swift,female,48,0,0,25.9292 -0,3,Miss. Dorothy Edith Sage,female,14,8,2,69.55 -0,2,Mr. John William Gill,male,24,0,0,13 -1,2,Mrs. (Karolina) Bystrom,female,42,0,0,13 -1,2,Miss. Asuncion Duran y More,female,27,1,0,13.8583 -0,1,Mr. Washington Augustus II Roebling,male,31,0,0,50.4958 -0,3,Mr. Philemon van Melkebeke,male,23,0,0,9.5 -1,3,Master. Harold Theodor Johnson,male,4,1,1,11.1333 -0,3,Mr. Cerin Balkic,male,26,0,0,7.8958 -1,1,Mrs. Richard Leonard (Sallie Monypeny) Beckwith,female,47,1,1,52.5542 -0,1,Mr. Frans Olof Carlsson,male,33,0,0,5 -0,3,Mr. Victor Vander Cruyssen,male,47,0,0,9 -1,2,Mrs. Samuel (Hannah Wizosky) Abelson,female,28,1,0,24 -1,3,Miss. Adele Kiamie Najib,female,15,0,0,7.225 -0,3,Mr. Alfred Ossian Gustafsson,male,20,0,0,9.8458 -0,3,Mr. Nedelio Petroff,male,19,0,0,7.8958 -0,3,Mr. Kristo Laleff,male,23,0,0,7.8958 -1,1,Mrs. Thomas Jr (Lily Alexenia Wilson) Potter,female,56,0,1,83.1583 -1,2,Mrs. William (Imanita Parrish Hall) Shelley,female,25,0,1,26 -0,3,Mr. Johann Markun,male,33,0,0,7.8958 -0,3,Miss. Gerda Ulrika Dahlberg,female,22,0,0,10.5167 -0,2,Mr. Frederick James Banfield,male,28,0,0,10.5 -0,3,Mr. Henry Jr Sutehall,male,25,0,0,7.05 -0,3,Mrs. William (Margaret Norton) Rice,female,39,0,5,29.125 -0,2,Rev. Juozas Montvila,male,27,0,0,13 -1,1,Miss. Margaret Edith Graham,female,19,0,0,30 -0,3,Miss. Catherine Helen Johnston,female,7,1,2,23.45 -1,1,Mr. Karl Howell Behr,male,26,0,0,30 -0,3,Mr. Patrick Dooley,male,32,0,0,7.75 \ No newline at end of file diff --git a/Material/wise_24_25/lernmaterial/numpy & matplotlib/matplotlib.ipynb b/Material/wise_24_25/lernmaterial/matplotlib.ipynb similarity index 99% rename from Material/wise_24_25/lernmaterial/numpy & matplotlib/matplotlib.ipynb rename to Material/wise_24_25/lernmaterial/matplotlib.ipynb index 3dca8b3..1d410bd 100644 --- a/Material/wise_24_25/lernmaterial/numpy & matplotlib/matplotlib.ipynb +++ b/Material/wise_24_25/lernmaterial/matplotlib.ipynb @@ -175,6 +175,7 @@ "cell_type": "markdown", "id": "e7b78221-3568-45c5-964f-422b2668f4e5", "metadata": { + "jp-MarkdownHeadingCollapsed": true, "nbgrader": { "grade": false, "grade_id": "cell-30de8243b097dfdc", @@ -212,7 +213,8 @@ "schema_version": 3, "solution": false, "task": false - } + }, + "scrolled": true }, "outputs": [ { @@ -640,7 +642,8 @@ "schema_version": 3, "solution": true, "task": false - } + }, + "scrolled": true }, "outputs": [ { @@ -1087,6 +1090,7 @@ "cell_type": "markdown", "id": "147244b1-7bdc-40bc-9f87-93997f9742ed", "metadata": { + "jp-MarkdownHeadingCollapsed": true, "nbgrader": { "grade": false, "grade_id": "cell-230328a26793cddb", @@ -1239,6 +1243,7 @@ "cell_type": "markdown", "id": "d5275062-b7f5-4193-9b5a-70f4e861c819", "metadata": { + "jp-MarkdownHeadingCollapsed": true, "nbgrader": { "grade": false, "grade_id": "cell-3adde3f53176bcb0", @@ -1450,7 +1455,8 @@ "schema_version": 3, "solution": false, "task": false - } + }, + "scrolled": true }, "outputs": [ { @@ -1603,7 +1609,8 @@ "schema_version": 3, "solution": true, "task": false - } + }, + "scrolled": true }, "outputs": [ { @@ -1714,7 +1721,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.0" + "version": "3.12.7" } }, "nbformat": 4, diff --git a/Material/wise_24_25/lernmaterial/meme.png b/Material/wise_24_25/lernmaterial/meme.png index 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\n", - " \n", - "\n", - " \n", - "Python ist eine universelle Programmiersprache, die aufgrund ihrer Einfachheit sehr leicht zu lernen und zu bedienen ist. Die Funktionalität kann durch den Import von Bibliotheken erweitert werden. Im Folgenden werden wir Ihnen zeigen, wie man hier im Jupyter Notebook Python Code ausführen kann. Die grundlegenden Konzepte und Strukturen in Python werden mit Hilfe von externen Quellen gezeigt. Die Übungsaufgaben dienen zum Testen und der Hands-on-Praxis des gelernten Wissens. Im zweiten Teil werden die Bibliotheken `numpy`, `sympy` und `matplotlib` kurz vorgestellt und Übungsaufgaben dazu gestellt.\n", - "\n", - "In diesem Jupyter Notebook werden die grundlegende Funktionen und Konzepte in Python vorgestellt. Dazu wird es kleine Programmierübungen um das gelernte Wissen in Beispielen anzuwenden.\n", - "\n", - "Das Jupyter Notebook ist in Zellen unterteilt, die durch Boxen gekennzeichnet sind, die einzeln ausgeführt werden können (entweder über `Shift + Enter` oder den `Run`-Knopf). Sie können auch alle Zellen im Notebook ausführen über `Kernel > Restart & Run All` oder dem \"Vorspulen\"-Zeichen.\n", - "\n", - "Bitte beachten Sie, dass alle Zellen im Notebook ein gemeinsamen Workspace nutzen. Das bedeutet, dass Bibliotheken nur einmal importiert werden müssen und dann innerhalb des Notebooks genutzt werden können. Es können jedoch auch Variablen überschrieben werden, wenn diese nicht richtig gekapselt werden (z.B. über Funktionen).\n", - "\n", - "Viel Spaß und Erfolg!\n", - "\n", - "Es gibt _sehr_ viele weitere Python-Tutorials online, z.B. auf [Youtube](https://youtu.be/kqtD5dpn9C8), mit denen Sie die benötigten Grundlagen für Python lernen können.\n", - "\n", - "Wenn Sie Fragen oder Verbesserungsvorschläge zum Inhalt oder Struktur der Notebooks haben, dann können Sie eine E-Mail an Paul Nowitzki ([p.nowitzki@tu-bs.de](mailto:p.nowitzki@tu-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&cc=besser@ifn.ing.tu-bs.de,%20le@ifn.ing.tu-bs.de)), Karl Besser ([besser@ifn.ing.tu-bs.de](mailto:besser@ifn.ing.tu-bs.de)) oder Martin Le ([le@ifn.ing.tu-bs.de](mailto:le@ifn.ing.tu-bs.de)) schreiben.\n", - "\n", - "Link zu einem Python Spickzettel: [hier](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf)\n", - "\n", - "Der Großteil des Python-Tutorials stammt aus der Veranstaltung _Deep Learning Lab_ und von [www.python-kurs.eu](https://www.python-kurs.eu/python3_kurs.php) und wurden für _Signale und Systeme_ angepasst. " - ] - }, - { - "cell_type": "markdown", - "id": "2de11f87", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-d1b6225195341484", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "## Aufgabe 1-1: Datentypen und Variablen" - ] - }, - { - "cell_type": "markdown", - "id": "6ab82d94", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-095d0c8663473ea9", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Eine Definition und Zuweisung eines Wertes zu einer Variablen erfolgt über den `=` Operator." - ] - }, - { - "cell_type": "markdown", - "id": "bed3548e", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-e703bd590336dbb9", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe**: Definieren Sie zunächst die zwei Variablen `a` und `b` und initialisieren diese mit einem Integerwert ungleich 0:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "12ad52cc", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-38558c816fdeb383", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "a = 1\n", - "b = -2\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "fceefd81", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-9aec33e8d27e8106", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "assert isinstance(a, int)\n", - "assert isinstance(b, int)\n", - "\n", - "assert a != 0\n", - "assert b != 0" - ] - }, - { - "cell_type": "markdown", - "id": "473eaf9a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b503ba72573ea20e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Ein String-Objekt (Text) können sie mit Hilfe von `'Some Text'` oder `\"Some Text2\"` definieren. Definieren sie die Variable `text` mit einem beliebigen Text." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "eef86caa", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1188bd957b9e1c98", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "text = \"Hi Mom, I am on TV!\"\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "3624a893", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-b6c5a77a33bde905", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "assert isinstance(text, str)" - ] - }, - { - "cell_type": "markdown", - "id": "e82998a1", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1763af54eb134b32", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Geben Sie die Werte der Variablen auf dem Bildschirm mit Hilfe der [print-Funktion](https://www.w3schools.com/python/ref_func_print.asp) aus. Der Output soll wie folgt aussehen: `\"a = 12 und b = 12\"` (Die Werte sollen dann den Werten aus ihrer Definition entsprechen. 12 ist hier nur ein Beispiel).\n", - "\n", - "Hinweis: Für die Ausgabe der Variablen in einem String-Objekt wird die [format-Funktion](https://www.w3schools.com/python/ref_string_format.asp) verwendet." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "abf16ea3", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8149b06e15a5d0a0", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "a = 1 und b = -2\n" - ] - } - ], - "source": [ - "# BEGIN SOLUTION\n", - "print(\"a = {} und b = {}\".format(a, b))\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "8142c51f", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-97c2cafe4fbb33c1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe:** Addieren Sie die Werte der Variablen `a` und `b` und speichern Sie das Ergebnis in der Variable `c`:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "5df47a7f", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-75b4095bcaa5ab4a", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "c = a + b\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "d9a5ff84", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-e897c81ec0545569", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "assert isinstance(c, int)\n", - "### BEGIN HIDDEN TESTS\n", - "assert a + b == c\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "22192796", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-83d9dfcbd73a6c79", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Geben Sie das Ergebnis der Addition im folgenden Format aus: `\"a + b = (datatype = )\"`. (Die Ausdrücke `<...>` sind durch den jeweiligen Inhalt zu ersetzen.) \n", - "Der Datentyp einer Variablen kann mit Hilfe der Funktion [type](https://www.w3schools.com/python/ref_func_type.asp) abgerufen werden." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "41ad3920", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-89b0a52e9998c4cb", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "a + b = -1 (datatype = )\n" - ] - } - ], - "source": [ - "# BEGIN SOLUTION\n", - "print(\"a + b = {} (datatype = {})\".format(c, type(c)))\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "ad5aa173", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-6d1a6b863f5c42d1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Speichern Sie auch die Ergebnisse für die Multiplikation, Division, Ganzzahldivision, Exponentiation und den Modulo-Operator in den unten angegebenen Variablen:\n", - "\n", - "\\begin{align}\n", - "m &= a\\cdot b\\\\\n", - "d &= \\frac{a}{b}\\\\\n", - "i &= \\lfloor\\frac{a}{b}\\rfloor\\\\\n", - "e &= a^b\\\\\n", - "r &= a\\; \\textrm{mod}\\; b\n", - "\\end{align}\n", - "\n", - "\n", - "Die Ausführung der anderen arithmetischen Operationen in Python erfolgt analog. Eine Übersicht können Sie [hier](https://www.python-kurs.eu/operatoren.php) entnehmen." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "728b83fa", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-e4a5884ac413cd47", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "m = a*b\n", - "d = a/b\n", - "i = a//b\n", - "e = a**b\n", - "r = a%b\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2f5ebf9a", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-93235c2c6510fc3b", - "locked": true, - "points": 3, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "assert m == a*b\n", - "assert d == a/b\n", - "assert i == a//b\n", - "assert e == a**b\n", - "assert r == a%b\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "93aed1ec", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-e8d0da8229c50b55", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "## Aufgabe 1-2: Sequentielle Datentypen: Listen und Strings" - ] - }, - { - "cell_type": "markdown", - "id": "06f60e75", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-e829b042c10534b2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "Sequentielle Datentypen sind ein wichtiger Bestandteil in der Programmierung. Dazu gehören Listen, Tupel und auch die in Aufgabe 1-1 genutzten String-Objekte.\n", - "\n", - "Wichtige Eigenschaften dieser Datentypen sind:\n", - "- Die Elemente von Listen, Strings oder Tupeln sind in einer bestimmten Reihenfolge angeordnet.\n", - "- Der Zugriff (Lesen und Schreiben) dieser Objekte erfolgt über Indizes.\n", - "\n", - "Beispiel für eine Liste:\n", - "`some_list = [\"a\", \"b\", \"c\"]`\n", - "\n", - "Beispiel für ein Tupel:\n", - "`some_tuple = (1, 2, 3)`\n", - "\n", - "Beispiel für ein String:\n", - "`some_string = \"Python ist cool!\"`" - ] - }, - { - "cell_type": "markdown", - "id": "2f8cecd9", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-12a0b9c3b6e5441a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "**Aufgabe**: Definieren Sie die Variable `l` und weisen Sie dieser Variable eine Liste mit aufsteigenden Integerwerten von `0` bis `4` zu." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9d18ab2e", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-a47c28c0674be0de", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "l = list(range(5))\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f06c66b2", - "metadata": { - "editable": true, - "nbgrader": { - "grade": true, - "grade_id": "cell-2116010bb09add7a", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "assert isinstance(l, list)\n", - "### BEGIN HIDDEN TESTS\n", - "assert l == [0, 1, 2, 3, 4]\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "56058b07", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b8f643167979c5e1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Hängen Sie der Liste `l` noch den Wert `42` an.\n", - "\n", - "Hinweis: Nutzen Sie dafür die Methode [.append](https://www.w3schools.com/python/ref_list_append.asp)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fd5d9064", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5ba438d830677790", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "l.append(42)\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8cf3e111", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-4e49a95d8f8e1bca", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "assert l == [0, 1, 2, 3, 4, 42]\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "65bf74ce", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-01ba15275a765efc", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe** Geben Sie den Inhalt der Liste mit Hilfe der `print()` Funktion aus." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f3a78a8a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5b392a24d0ed100a", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "print(l)\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "3b4e7159", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-595ed0febab392a3", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "## Aufgabe 1-3: Dictionaries" - ] - }, - { - "cell_type": "markdown", - "id": "d17fb780", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d21e87c25280c85e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Initialisieren Sie die Dictionary Variable `my_dict` mit folgendem Mapping:\n", - "\n", - "| Key | Value |\n", - "|:----|:------|\n", - "| `\"apple\"` | `\"Apfel\"` |\n", - "| `\"banana\"` | `\"Banane\"` |\n", - "| `\"cherry\"` | `\"Kirsche\"` |" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2585e308", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b462428ed9c9617c", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "my_dict = {\"apple\": \"Apfel\", \"banana\": \"Banane\", \"cherry\": \"Kirsche\"}\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ed73673b", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-ceecad3d50b9f3ba", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "assert isinstance(my_dict, dict)\n", - "### BEGIN HIDDEN TESTS\n", - "assert my_dict == {\"apple\": \"Apfel\", \"banana\": \"Banane\", \"cherry\": \"Kirsche\"}\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "82eb700a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b2e8643ce6771d13", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe:** Fügen Sie nun das Key-Value Paar `\"pear\": \"Birne\"` zu `my_dict` hinzu." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8c76bec2", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e88317079248bf45", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "my_dict[\"pear\"] = \"Birne\"\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1840fbf7", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-5e68ca12bc0c13dc", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "assert my_dict == {\"apple\": \"Apfel\", \"banana\": \"Banane\", \"cherry\": \"Kirsche\", \"pear\": \"Birne\"}\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "50347f8d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-94ec5997d98e07ac", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe:** Drucken Sie jedes Key-Value-Paar aus `my_dict` in einer eigenen Zeile im Format `Zu gehoert .` aus. Verwenden Sie dazu den `print()` Befehl." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "43992f58", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4c9804ba462612f4", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "for key, value in my_dict.items():\n", - " print(\"Zu {} gehoert {}\".format(key, value))\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "3af58d44", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c6b2adacb2ca42b8", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe 1-4: Funktionen" - ] - }, - { - "cell_type": "markdown", - "id": "ca2ba62a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c9188bbb0560e9a3", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Funktionen können wie folgt in Python definiert werden:\n", - "```python\n", - "def some_function_name(param1, param2):\n", - " a = do_something1(param1)\n", - " b = do_something2(a, param2)\n", - " return b\n", - "```\n", - "\n", - "Das `def`-Schlüsselwort leitet die Definition einer Funktion ein, gefolgt von dem Funktionsnamen, den Eingabeparametern der Funktion in runden Klammern und einem Doppelpunkt. Wichtig ist, dass die Anweisungen innerhalb der Funktion eingerückt sein müssen. Das Ergebnis (oder die Ergebnisse) werden mit Hilfe des `return`-Schlüsselworts gekennzeichnet." - ] - }, - { - "cell_type": "markdown", - "id": "1103172b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1fe9a24d046f3b13", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Schreiben Sie Ihre eigene Funktion `fibonacci(n)`, die die `n`-te Zahl der Fibonacci-Folge berechnet.\n", - "\n", - "Die Fibonacci-Folge ist wie folgt definiert:\n", - "\n", - "$ \\mathrm{fibonacci}(n)=\n", - "\\begin{cases}\n", - "0 & \\text{if}~n = 0\\\\\n", - "1 & \\text{if}~n = 1\\\\\n", - "\\mathrm{fibonacci}(n-1) + \\mathrm{fibonacci}(n-2) & \\text{if}~n > 1\\\\\n", - "\\end{cases} $\n", - "\n", - "Es existiert zwar eine Fortsetzung der Fibonacci-Folge für negative $n$, diese soll hier allerdings nicht betrachtet werden.\n", - "\n", - "Hinweis: Diese Aufgabe kann auf mehrere Arten gelöst werden, beispielsweise [rekursiv](https://www.w3schools.com/python/gloss_python_function_recursion.asp)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5fe64db2", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-273f9551a614d75f", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "def fibonacci(n):\n", - " # BEGIN SOLUTION\n", - " if n < 2:\n", - " number = n\n", - " else:\n", - " number = fibonacci(n - 1) + fibonacci(n - 2)\n", - " # END SOLUTION\n", - " return number" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1ea4932c", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-bd84fc94aca517aa", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "assert fibonacci(0) == 0\n", - "assert fibonacci(1) == 1\n", - "assert fibonacci(2) == 1\n", - "assert fibonacci(3) == 2\n", - "assert fibonacci(10) == 55\n", - "### BEGIN HIDDEN TESTS\n", - "assert list(map(fibonacci, range(26))) == [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765, 10946, 17711, 28657, 46368, 75025]\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "b3c4472b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1b4c87ec9a37f6ff", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Nutzen Sie Ihre selbstdefinierte Funktion `fibonacci()` und geben Sie die Fibonacci-Zahlen der ersten vier Elemente der Liste `l` mit Hilfe der `print()` Funktion aus. Der Output soll für jede Fibonacci-Zahl eine Zeile nach folgendem Format enthalten:\n", - "`\"Die Fibonacci-Zahl von ist \"`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "311b18a3", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c34ee038f199afe2", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "for n in l[0:4]:\n", - " print(\"Die Fibonacci-Zahl von {} ist {}\".format(n, fibonacci(n)))\n", - "# END SOLUTION" - ] - } - ], - "metadata": { - "celltoolbar": "Create Assignment", - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.7" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/prog_tut_2.ipynb b/Material/wise_24_25/lernmaterial/prog_tut_2.ipynb deleted file mode 100644 index ae27089..0000000 --- a/Material/wise_24_25/lernmaterial/prog_tut_2.ipynb +++ /dev/null @@ -1,1010 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "480f9a0e", - "metadata": { - "editable": true, - "nbgrader": { - "grade": false, - "grade_id": "cell-b5ef3c2f2dca81de", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "# 1. Programmierungübung: Python Tutorial Teil 2\n", - "Willkommen zum zweiten Teil der ersten Programmierübung Einführung in Python 3.\n", - "\n", - "Wenn Sie Fragen oder Verbesserungsvorschläge zum Inhalt oder Struktur der Notebooks haben, dann können sie eine E-Mail an Paul Nowitzki ([p.nowitzki@tu-bs.de](mailto:p.nowitzki@tu-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&cc=besser@ifn.ing.tu-bs.de,%20le@ifn.ing.tu-bs.de)), Karl Besser ([besser@ifn.ing.tu-bs.de](mailto:besser@ifn.ing.tu-bs.de)) oder Martin Le ([le@ifn.ing.tu-bs.de](mailto:le@ifn.ing.tu-bs.de)) schreiben.\n", - "\n", - "Link zu einem Python Spickzettel: [hier](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf)\n", - "\n", - "Link zu den Dokumentationen der hier verwendeten Pakete finden Sie hier: [numpy](https://numpy.org/doc/1.20/), [sympy](https://docs.sympy.org/latest/index.html) und [matplotlib](https://matplotlib.org/)\n", - "\n", - "Der Großteil des Python-Tutorials stammt aus der Veranstaltung _Deep Learning Lab_ und von [www.python-kurs.eu](https://www.python-kurs.eu/python3_kurs.php) und wurde für _Signale und Systeme_ angepasst." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a960ea6a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3e540637ce0cf04e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "import numpy as np\n", - "import sympy as sp\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "markdown", - "id": "2f7db248", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d1b6225195341484", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe 2-1: Numpy Arrays" - ] - }, - { - "cell_type": "markdown", - "id": "089a51bc", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-095d0c8663473ea9", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "*Hinweis:* Viele der Befehle in `numpy` haben eine sehr große Ähnlichkeit zu den Befehlen in Matlab. Wenn Sie bereits Erfahrung mit Matlab haben, können Sie Teile Ihres Wissens schnell und einfach übertragen." - ] - }, - { - "cell_type": "markdown", - "id": "e4ad5db2", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e703bd590336dbb9", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Definieren Sie zwei Numpy-Arrays `a` und `b` mit fünf beliebigen Zahlen." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bd93bfef", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-38558c816fdeb383", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "a = np.random.randn(5)\n", - "b = np.random.randn(5)\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8b623711", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-9aec33e8d27e8106", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "assert len(a) == 5\n", - "assert len(b) == 5\n", - "assert isinstance(a, np.ndarray)\n", - "assert isinstance(b, np.ndarray)" - ] - }, - { - "cell_type": "markdown", - "id": "c134b1d8", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b503ba72573ea20e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Addieren Sie die Arrays `a` und `b` element-weise und speichern Sie das Ergebnis in der Variable `c`. Führen Sie die Rechnung analog für die Multiplikation aus und speichern Sie das Ergebnis in `m`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2823ae03", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1188bd957b9e1c98", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "c = a + b\n", - "m = a * b\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a6b6b68b", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-b6c5a77a33bde905", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "assert isinstance(c, np.ndarray)\n", - "assert isinstance(m, np.ndarray)\n", - "### BEGIN HIDDEN TESTS\n", - "assert np.allclose(c, a+b)\n", - "assert np.allclose(m, a*b)\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "3bd6887d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-7922eb482763dc29", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe 2-2: Mehrdimensionale Arrays" - ] - }, - { - "cell_type": "markdown", - "id": "2a428a87", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1763af54eb134b32", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe**: Erzeugen Sie die Matrizen $$A = \\begin{pmatrix}7 & 2\\\\-4 & 42\\end{pmatrix} \\quad \\text{und} \\quad B = \\begin{pmatrix}-5 & 4\\\\3 & -10\\end{pmatrix}$$ als zwei-dimensionales Numpy Array und speichern Sie diese in Variablen `A` und `B`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "70187580", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8149b06e15a5d0a0", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "A = np.array([[7, 2], [-4, 42]])\n", - "B = np.array([[-5, 4], [3, -10]])\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "758568f0", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-204f2d8dca887710", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "assert np.shape(A) == (2, 2)\n", - "assert np.shape(B) == (2, 2)\n", - "assert isinstance(A, np.ndarray)\n", - "assert isinstance(B, np.ndarray)\n", - "### BEGIN HIDDEN TESTS\n", - "assert np.allclose(A, np.array([[7, 2], [-4, 42]]))\n", - "assert np.allclose(B, np.array([[-5, 4], [3, -10]]))\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "77221d98", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-97c2cafe4fbb33c1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe:** Addieren Sie die Matrizen `A` und `B` und speichern Sie das Ergebnis in der Variable `C`. Führen Sie die Rechnung analog für die Matrix-Multiplikation ($A\\cdot B$) aus und speichern Sie das Ergebnis in `M`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9ec28862", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-75b4095bcaa5ab4a", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "# BEGIN SOLUTION\n", - "C = A + B\n", - "M = A @ B\n", - "# END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1807fc05", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-e897c81ec0545569", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "assert isinstance(C, np.ndarray)\n", - "assert isinstance(M, np.ndarray)\n", - "assert np.shape(C) == (2, 2)\n", - "assert np.shape(M) == (2, 2)\n", - "### BEGIN HIDDEN TESTS\n", - "assert np.allclose(C, A+B)\n", - "assert np.allclose(M, A@B)\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "60ca6b51", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-019cd9f4d679a343", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe 2-3: Eigenwertzerlegung" - ] - }, - { - "cell_type": "markdown", - "id": "e60997af", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0e95a972c78dd588", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe:** Führen Sie die Eigenwertzerlegung der Matrizen `A` und `C` durch. Speichern Sie die Eigenwerte in den Variablen `l_A` und `l_C`, sowie die dazugehörigen Eigenvektoren in den Variablen `v_A` und `v_C`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0e6e2de9", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-da0326102531dd25", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "l_A, v_A = np.linalg.eig(A)\n", - "l_C, v_C = np.linalg.eig(C)\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cd158192", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-7119f54a5fe54554", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "assert len(l_A) == 2\n", - "assert np.shape(v_C) == (2, 2)\n", - "### BEGIN HIDDEN TESTS\n", - "assert np.allclose(np.sort(l_A), [7.230083961, 41.76991604], atol=0.001)\n", - "assert np.allclose(np.sort(l_C), [2.201351413, 31.79864859], atol=0.001)\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "e83039c3", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3f4a2620cf6d4006", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe 2-4: Sympy" - ] - }, - { - "cell_type": "markdown", - "id": "0cd374e0", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3769021537c05f9a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Mit Sympy können Sie symbolische Rechnungen in Python ausführen.\n", - "\n", - "**Aufgabe:** Definieren Sie die Funktionen\n", - "\n", - "$\n", - "\\begin{align}\n", - "f(x) &= \\sin(3x)\\\\\n", - "g(x) &= \\exp\\left(\\frac{x}{2}\\right) - 7x^3\\\\\n", - "\\end{align}\n", - "$\n", - "\n", - "in den Variablen `f` und `g`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "56b77c4f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c1bc77e56c226d65", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "x = sp.Symbol('x')\n", - "### BEGIN SOLUTION\n", - "f = sp.sin(3*x)\n", - "g = sp.exp(x/2) - 7*(x**3)\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7286cac1", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-529c99fe459dccce", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "samples_x = np.random.randn(10)\n", - "samples_f = sp.lambdify(x, f, \"numpy\")(samples_x)\n", - "samples_g = sp.lambdify(x, g, \"numpy\")(samples_x)\n", - "assert np.allclose(samples_f, np.sin(3*samples_x), atol=0.001)\n", - "assert np.allclose(samples_g, np.exp(samples_x/2)-7*(samples_x**3), atol=0.001)\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "6c2dd86f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ce06db1fa873d0a8", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe:** Berechnen Sie die Stammfunktionen von `f` mittels [Integration von Sympy](https://docs.sympy.org/latest/modules/integrals/integrals.html) und speichern Sie diese als Sympy-Funktion in `F`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "717d274b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-63502fc38661e8f8", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "F = sp.integrate(f, x)\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9d33c865", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-4bc1f83a8304d373", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "### BEGIN HIDDEN TESTS\n", - "samples_x = np.random.randn(10)\n", - "samples_F = sp.lambdify(x, F, \"numpy\")(samples_x)\n", - "assert np.allclose(samples_F, -np.cos(3*samples_x)/3., atol=0.001)\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "3e1758f8", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-389527b1733be1e8", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe:** Berechnen Sie das bestimmte Integral $$G=\\int_{20}^{25} g(x)\\mathrm{d}x$$ und speichern Sie die Lösung als float in der Variablen `G`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8565c8e6", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b867f76246767778", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "G = float(sp.integrate(g, (x, 20, 25)))\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b7ae55b7", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-a107f3748f1d838e", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "assert isinstance(G, float)\n", - "### BEGIN HIDDEN TESTS\n", - "assert np.isclose(G, -7*25**4/4 + 7*20**4/4 - 2*np.exp(20/2) + 2*np.exp(25/2), atol=0.001)\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "b8c28bc1", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-15cba5457c117498", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe 2-5: Matplotlib" - ] - }, - { - "cell_type": "markdown", - "id": "f0abbc39", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-aaff0f486439460f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe:** Plotten Sie die Punkte $(a_i, b_i)$, wobei $a_i$ und $b_i$ die Elemente aus den Arrays `a` und `b` sind. \n", - "Es sollen zum einen die Punkte selbst markiert werden und zum anderen sollen sie zusätzlich miteinander verbunden werden.\n", - "\n", - "Geben Sie der x-Achse die Beschriftung `\"Werte aus a\"` und der y-Achse die Beschriftung `\"Werte aus b\"`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "732be88f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-7d1fc64a2ceac3a3", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "plt.plot(a, b, 'o-')\n", - "plt.xlabel(\"Werte aus a\")\n", - "plt.ylabel(\"Werte aus b\")\n", - "### END SOLUTION\n", - "axis = plt.gca()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a43077fa", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-1a8cb5ce1d117f15", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "from plotchecker import LinePlotChecker\n", - "pc = LinePlotChecker(axis)\n", - "### BEGIN HIDDEN TESTS\n", - "pc.assert_xlabel_equal(\"Werte aus a\")\n", - "pc.assert_ylabel_equal(\"Werte aus b\")\n", - "pc.assert_x_data_equal([a])\n", - "pc.assert_y_data_equal([b])\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "5cf8d195", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-235092fd5dc92284", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Aufgabe 2-6: Effizienter Fibonacci-Algorithmus" - ] - }, - { - "cell_type": "markdown", - "id": "91624223", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-da5d467c21a05339", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "Die im ersten Teil implementierte Fibonacci-Funktion löst zwar das Problem, besitzt aber eine Laufzeit von $O(2^n)$ mit Rekursion und $O(n)$ mit einem iterativen Ansatz, weshalb sich diese Ansätze nicht besonders gut zur Berechnung von großen Fibonacci-Zahlen eignen.\n", - "\n", - "Um den Fibonacci-Algorithmus in logarithmischer Laufzeit $O(\\log n)$ zu implementieren gibt es den folgenden Ansatz:\n", - "\n", - "Die ersten beiden Fibonacci-Zahlen $f_0$ und $f_1$ werden zum Vektor\n", - "$\\vec{F_1} =\n", - "\\left(\\begin{align}\n", - "& f_1\\\\\n", - "& f_0\n", - "\\end{align}\\right)\n", - "$\n", - "zusammengefasst.\n", - "\n", - "Durch Multiplikation der Matrix $\\mathbf{A} = \\begin{pmatrix}1 & 1\\\\1 & 0\\end{pmatrix}$ mit $F_1$ lässt sich der Vektor $\\vec{F_2} = \\mathbf{A} \\cdot \\vec{F_1} =\n", - "\\left(\\begin{align}\n", - "& f_2\\\\\n", - "& f_1\n", - "\\end{align}\\right)\n", - "$ berechnen. Diese Multiplikation kann beliebig oft vorgenommen werden, bis der gewünschte Vektor $\\vec{F_n} = \\mathbf{A}^n \\cdot \\vec{F_1}$ erreicht ist.\n", - "\n", - "Die logarithmische Laufzeit kann durch geschicktes Berechnen von $\\mathbf{A}^n$ erzielt werden, indem die folgende Rekursions-Vorschrift angewandt wird:\n", - "\n", - "$\n", - "\\mathbf{A}^n =\n", - "\\begin{cases}\n", - "\\mathbf{A} & \\mathrm{wenn}\\; n = 1\\\\\n", - "\\mathbf{A}^{\\frac{n}{2}} \\cdot \\mathbf{A}^{\\frac{n}{2}} & \\mathrm{wenn}\\; n > 1\\;\\mathrm{und}\\; n\\; \\mathrm{gerade}\\\\\n", - "\\mathbf{A} \\cdot \\mathbf{A}^{\\frac{n-1}{2}} \\cdot \\mathbf{A}^{\\frac{n-1}{2}} & \\mathrm{wenn}\\; n > 1\\;\\mathrm{und}\\; n\\; \\mathrm{ungerade}\n", - "\\end{cases}\n", - "$\n", - "\n", - "Der Laufzeitvorteil entsteht dabei dadurch, dass jedes der beiden $\\mathbf{A}^{\\frac{n}{2}}$ bzw. $\\mathbf{A}^{\\frac{n-1}{2}}$ in jedem Rekursionsschritt nur einmal berechnet werden muss.\n" - ] - }, - { - "cell_type": "markdown", - "id": "8408ffda", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ae233ff5332b301e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "**Aufgabe:** Deklarieren sie zunächst die Matrix `A` und den Spaltenvektor `F_1` wie oben beschrieben. Da im Folgenden mit großen Zahlen gerechnet werden soll, muss die Deklaration mit dem Parameter `dtype=np.int64` durchgeführt werden, um spätere Overflows zu vermeiden." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c9ec3ac3", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-abb29dd054d75a76", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "A = np.array([[1, 1], [1, 0]], dtype=np.int64)\n", - "F_1 = np.array([[1], [0]], dtype=np.int64)\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "29e2481a", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-b9a2651d938be45c", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - }, - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "assert A.dtype == np.int64\n", - "assert F_1.dtype == np.int64\n", - "### BEGIN HIDDEN TESTS\n", - "assert np.allclose(A, np.array([[1, 1], [1, 0]]))\n", - "assert np.allclose(F_1, np.array([[1], [0]]))\n", - "### END HIDDEN TESTS" - ] - }, - { - "cell_type": "markdown", - "id": "f07282f7", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5d2f31ad0277ca35", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "**Aufgabe:** Implementieren Sie nun erneut die Methode `fibonacci(n)`, die die $n$-te Fibonacci-Zahl mit der oben beschriebenen Methode auch für große $n$ berechnet.\n", - "\n", - "Hinweis: Für die \"Exponentiation\" einer quadratischen Matrix bietet Numpy die Methode [np.linalg.matrix_power()](https://numpy.org/doc/stable/reference/generated/numpy.linalg.matrix_power.html)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "84d172ed", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-00ec909bed8ed5ec", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [], - "source": [ - "def fibonacci(n):\n", - "### BEGIN SOLUTION\n", - " if n < 2:\n", - " return n\n", - " else:\n", - " return (np.linalg.matrix_power(A, n-1) @ F_1)[0]\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a262cb49", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-118913143e3418fd", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - }, - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [], - "source": [ - "# Hier werden die Loesungen getestet...\n", - "assert isinstance(fibonacci(0), int)\n", - "assert fibonacci(0) == 0\n", - "assert fibonacci(1) == 1\n", - "assert fibonacci(2) == 1\n", - "assert fibonacci(3) == 2\n", - "assert fibonacci(10) == 55\n", - "\n", - "### BEGIN HIDDEN TESTS\n", - "assert list(map(fibonacci, range(26))) == [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765, 10946, 17711, 28657, 46368, 75025]\n", - "\n", - "#import signal\n", - "#if hasattr(signal, \"SIGALRM\"):\n", - "#\n", - "# def timeout_handler(signal, frame):\n", - "# raise Exception(\"Timeout\")\n", - "#\n", - "# signal.signal(signal.Signals.SIGALRM, timeout_handler)\n", - "# signal.alarm(20)\n", - "\n", - "assert fibonacci(40) == 102334155\n", - "assert fibonacci(50) == 12586269025\n", - "assert fibonacci(90) == 2880067194370816120\n", - "### END HIDDEN TESTS" - ] - } - ], - "metadata": { - "celltoolbar": "Create Assignment", - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/python-plotting/Graphical representation.ipynb b/Material/wise_24_25/lernmaterial/python-plotting/Graphical representation.ipynb deleted file mode 100644 index b0af46a..0000000 --- a/Material/wise_24_25/lernmaterial/python-plotting/Graphical representation.ipynb +++ /dev/null @@ -1,923 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-fae4670da2ba00e2", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Graphical representations, Matplotlib, Contour Plots\n", - "\n", - "A Python plotting library called Matplotlib creates publication-quality graphics in a range of physical formats and in cross-platform interactive settings.\n", - "Four graphical user interface toolkits, the Python and IPython shells, the Jupyter notebook, web application servers, and Python scripts can all make use of Matplotlib. The open source documentation can be found under: https://matplotlib.org/stable/index.html#\n", - "\n", - "__Creating Plots__\n", - "\n", - "Figure\n", - "\n", - "|Operator |\tDescription |\n", - "|---------|-------------|\n", - "|fig = plt.figures() | a container that contains all plot elements |\n", - "\n", - "Axes\n", - "\n", - "|Operator |\tDescription |\n", - "|---------|-------------|\n", - "|fig.add_axes()
a = fig.add_subplot(222) | Initializes subplot
A subplot is an axes on a grid system row-col-num. |\n", - "|fig, b = plt.subplots(nrows=3, nclos=2) | Adds subplot |\n", - "|ax = plt.subplots(2, 2) |\tCreates subplot |\n", - "\n", - "__Plotting__\n", - "\n", - "1D Data\n", - "\n", - "|Operator |\tDescription|\n", - "|---------|------------|\n", - "|lines = plt.plot(x,y) | Plot data connected by lines|\n", - "|plt.scatter(x,y) | Creates a scatterplot, unconnected data points|\n", - "|plt.bar(xvalue, data , width, color...) | simple vertical bar chart|\n", - "|plt.barh(yvalue, data, width, color...) | simple horizontal bar|\n", - "|plt.hist(x, y) | Plots a histogram|\n", - "|plt.boxplot(x,y) | Box and Whisker plot|\n", - "|plt.violinplot(x, y) |\tCreates violin plot|\n", - "|ax.fill(x, y, color='lightblue')
ax.fill_between(x,y,color='lightblue') | Fill area under/between plots|\n", - "\n", - "2D Data\n", - "\n", - "|Operator |\tDescription|\n", - "|---------|------------|\n", - "|fig,ax = plt.subplots()
im = ax.imshow(img,cmap,vmin...) | Colormap or RGB arrays | \n", - "\n", - "Saving plots\n", - "\n", - "|Operator |\tDescription|\n", - "|---------|------------|\n", - "|plt.savefig('fig.png') | Saves plot/figure to image |\n", - "\n", - "__Customization__\n", - "\n", - "Color\n", - "\n", - "|Operator | Description|\n", - "|---------|------------|\n", - "|plt.plot(x,y,color='lightblue')
plt.plot(x,y,alpha = 0.4) | Colors plot to light bluw color |\n", - "|plt.colorbar(mappable,orientation='horizontal') | mappable:the image,contourset to which colorbar applies. |\n", - "\n", - "Markers\n", - "\n", - "|Operator | Description|\n", - "|---------|------------|\n", - "|plt.plot(x,y,marker='*') | adds * for every data point |\n", - "|plt.plot(x,y,marker='.') | adds . for every data point |\n", - "\n", - "Lines\n", - "\n", - "|Operator | Description|\n", - "|---------|------------|\n", - "|plt.plot(x, y, linewidth=2) | Sets line width|\n", - "|plt.plot(x, y, ls='solid') | Sets linestyle, ls can be ommitted, see 2 below|\n", - "|plt.plot(x, y, ls='--') | Sets linestyle, ls can be ommitted, see below|\n", - "|plt.plot(x,y,'--', x\\*\\*2, y\\*\\*2, '-.') | Lines are '--' and '-.' |\n", - "|plt.setp(lines,color='red',linewidth=2) | Sets properties of plot lines|\n", - "\n", - "Text\n", - "\n", - "|Operator | Description|\n", - "|---------|------------|\n", - "|plt.text(1,1,'Text',style='italic') | Places text at coordinates (1,1)|\n", - "|ax.annotate('point A',xy=(10,10)) | Annotate the point with coordinates xy|\n", - "|pt.title(r'\\$delta\\_i=20\\$',fontsize=10)| Math text|\n", - "\n", - "Limits\n", - "\n", - "|Operators | Description|\n", - "|----------|------------|\n", - "|plt.xlim(0, 7) | Sets x-axis to display 0 - 7|\n", - "|other = array.copy() | Creates deep copy of array|\n", - "|plt.ylim(-0.5, 9) | Sets y-axis to display -0.5 - 9|\n", - "|ax.set(xlim=[0, 7], ylim=[-0.5, 9])
ax.set_xlim(0, 7) | Sets limits|\n", - "|plt.margins(x=1.0, y=1.0) | Set margins: add padding to a plot, values 0 - 1|\n", - "|plt.axis('equal') | Set the aspect ratio of the plot to 1|\n", - "\n", - "Legends/Labels\n", - "\n", - "|Operator | Description|\n", - "|---------|------------|\n", - "|plt.title('Title') | Sets title of plot|\n", - "|plt.xlabel('x-axis') | Sets label next to x-axis|\n", - "|plt.ylabel('y-axis') | Sets label next to y-axis|\n", - "|ax.set(title='axis', ylabel='Y-Axis', xlabel='X-Axis') | Set title and axis labels|\n", - "|ax.legend(loc='best') | No overlapping plot elements|\n", - "\n", - "Ticks\n", - "\n", - "|Operator | Description|\n", - "|---------|------------|\n", - "|plt.xticks(x, labels, rotation='vertical') | Set ticks|\n", - "|ax.xaxis.set(ticks=range(1,5), ticklabels=[3,100,-12,\"foo\"]) | Set x-ticks|\n", - "|ax.tick_params(axis='y', direction='inout', length=10) | Make y-ticks longer and go in and out|" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-a1f4d01637d085cc", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "Load the necessary packages and define the arrays __x__, __y__ and __z__ by running the cell below." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline\n", - "import numpy as np\n", - "x = np.arange(0,100)\n", - "y = x*2\n", - "z = x**2" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c92f9e3b1186aa0a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "\n", - "## Exercise 1\n", - "\n", - "Follow along with these steps:\n", - "\n", - "- Create a figure object called __fig__ using plt.figure()\n", - "- Use add_axes to add an axis to the figure canvas at [0,0,1,1]. Call this new axis __ax__.\n", - "- Plot (x,y) on that axes and set the labels and titles to match the plot below:\n", - "\n", - "![Plot XY](exercise1.png)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "fig = plt.figure()\n", - "ax = fig.add_axes([0,0,1,1])\n", - "ax.plot(x,y)\n", - "ax.set_xlabel('x')\n", - "ax.set_ylabel('y')\n", - "ax.set_title('plot xy')\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-f487f69f6d693b81", - "locked": true, - "points": 0, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN HIDDEN TEST\n", - "assert isinstance(fig,plt.Figure), f\"{fig} is not an instance of plt.Figure\"\n", - "assert isinstance(ax,matplotlib.axes._axes.Axes), f\"{ax} is not an axis \"\n", - "assert ax.get_title().lower() == 'plot xy', f\"{ax.get_title()} is not the same as plot xy\"\n", - "assert ax.get_xlabel().lower() == 'x'\n", - "assert ax.get_ylabel().lower() == 'y'\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-009335e6db4359f4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "\n", - "## Exercise 2\n", - "\n", - "Create a figure object and put two axes on it, ax1 and ax2. Located at [0,0,1,1] and [0.5,0.5,0.3,0.3] respectively." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "fig = plt.figure()\n", - "\n", - "ax1 = fig.add_axes([0,0,1,1])\n", - "ax2 = fig.add_axes([0.5,0.5,0.3,0.3])\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN HIDDEN TEST\n", - "assert isinstance(ax1,matplotlib.axes._axes.Axes), f\"{ax1} is not an axis \"\n", - "assert isinstance(ax2,matplotlib.axes._axes.Axes), f\"{ax2} is not an axis \"\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ad87f38d4c194c66", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "Now plot (x,y) on axes __ax1__ and on axes __ax2__ plot (x,z) as shown in \n", - "\n", - "![Alt text](exercise2.png). \n", - "\n", - "And call your figure object to show it." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "ax1.plot(x,y)\n", - "ax1.set_title('plot xy')\n", - "ax1.set_xlabel('x')\n", - "ax1.set_ylabel('y')\n", - "\n", - "ax2.plot(x,z)\n", - "ax2.set_title('plot xz')\n", - "ax2.set_xlabel('x')\n", - "ax2.set_ylabel('z')\n", - "\n", - "fig # Show figure object\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-52e7d1a8a36277f7", - "locked": true, - "points": 0, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN HIDDEN TEST\n", - "assert ax1.get_title().lower() == 'plot xy', f\"{ax.get_title()} is not the same as plot xy\"\n", - "assert ax1.get_xlabel().lower() == 'x'\n", - "assert ax1.get_ylabel().lower() == 'y'\n", - "\n", - "assert ax2.get_title().lower() == 'plot xz', f\"{ax.get_title()} is not the same as plot xz\"\n", - "assert ax2.get_xlabel().lower() == 'x'\n", - "assert ax2.get_ylabel().lower() == 'z'\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-383cddeb2332477d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "\n", - "## Exercise 3\n", - "\n", - "Create the plot below by adding two axes to a figure object at [0,0,1,1] and name it __Plot A__ and at [0.2,0.5,0.4,0.4] and name it as __Plot B__.\n", - "![Exercise 3](exercise3.png)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "fig = plt.figure()\n", - "\n", - "ax = fig.add_axes([0,0,1,1])\n", - "ax.set_title('Plot A')\n", - "\n", - "ax2 = fig.add_axes([0.2,0.5,0.4,0.4])\n", - "ax2.set_title('Plot B')\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-f1b47006770bcca0", - "locked": true, - "points": 0, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN HIDDEN TEST\n", - "assert isinstance(ax,matplotlib.axes._axes.Axes), f\"{ax} is not an axis \"\n", - "assert isinstance(ax2,matplotlib.axes._axes.Axes), f\"{ax2} is not an axis \"\n", - "assert ax.get_title().lower() == 'plot a', f\"{ax.get_title()} is not the same as plot A\"\n", - "assert ax2.get_title().lower() == 'plot b', f\"{ax2.get_title()} is not the same as plot B\"\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-91b7c64bab74fa07", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "Now use x and z arrays to create a zoomed version as shown in the plot below. Notice the x limits and y limits on the inserted plot:![Exercise 3.b](exercise3_b.png)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "ax.plot(x,z)\n", - "ax.set_xlabel('X')\n", - "ax.set_ylabel('Z')\n", - "ax.set_title('full')\n", - "\n", - "ax2.plot(x,z)\n", - "ax2.set_xlabel('X')\n", - "ax2.set_ylabel('Z')\n", - "ax2.set_title('zoom')\n", - "ax2.set_xlim(20,40)\n", - "ax2.set_ylim(0,2000)\n", - "\n", - "fig\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-725ebaa6bc9455b8", - "locked": true, - "points": 0, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN HIDDEN TEST\n", - "assert isinstance(ax,matplotlib.axes._axes.Axes), f\"{ax1} is not an axis \"\n", - "assert isinstance(ax2,matplotlib.axes._axes.Axes), f\"{ax2} is not an axis \"\n", - "assert ax.get_title().lower() == 'full', f\"{ax.get_title()} is not the same as full\"\n", - "assert ax2.get_title().lower() == 'zoom', f\"{ax.get_title()} is not the same as zoom\"\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-29c04b7329cfa60e", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Exercise 4\n", - "\n", - "Use plt.subplots(nrows=1, ncols=2) to create empty plot below. Name the first subplot as __xy__ and second subplot as __xz__.\n", - "\n", - "![Exercise 4_a](exercise4_a.png)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "fig, axes = plt.subplots(nrows=1, ncols=2)\n", - "axes[0].set_title('xy')\n", - "axes[1].set_title('xz')\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-046fc90eb41678c4", - "locked": true, - "points": 0, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN HIDDEN TEST\n", - "assert isinstance(axes,np.ndarray)\n", - "assert isinstance(axes[0],matplotlib.axes._axes.Axes) and isinstance(axes[1],matplotlib.axes._axes.Axes)\n", - "assert axes[0].get_title().lower() == 'xy', f\"{axes[0].get_title()} is not the same as xy\"\n", - "assert axes[1].get_title().lower() == 'xz', f\"{axes[1].get_title()} is not the same as xz\"\n", - "### END HIDDEN TEST" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3e6118aac1523838", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - " Now plot (x,y) and (x,z) on the respective axes. Set the linewidth to 3pt, marker to '__*__' and color of __xy__ plot to red and for the __xz__ plot, set color to blue and linestyle to dashed. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "axes[0].plot(x,y,color=\"blue\", lw=3, marker='*')\n", - "axes[0].set_xlabel('x')\n", - "axes[0].set_ylabel('y')\n", - "\n", - "axes[1].plot(x,z,color=\"red\", lw=3, ls='--')\n", - "axes[1].set_xlabel('x')\n", - "axes[1].set_ylabel('z')\n", - "\n", - "fig\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8690f8c5e6e59a90", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "Plot the same figure with a size of (10,2) by adding the __figsize__ argument in plt.subplots()." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(10,2))\n", - "\n", - "axes[0].plot(x,y,color=\"blue\", lw=3, marker='*')\n", - "axes[0].set_xlabel('x')\n", - "axes[0].set_ylabel('y')\n", - "\n", - "axes[1].plot(x,z,color=\"red\", lw=3, ls='--')\n", - "axes[1].set_xlabel('x')\n", - "axes[1].set_ylabel('z')\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-becf64c4bbc48d1f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Bar plots\n", - "\n", - "Bar plot enables us to visualize the distribution of categorical data variables. They represent distribution of discrete values. Thus, it represents the comparison of categorical values. The x axis represents the discrete values while the y axis represents the numeric values of comparison and vice versa.The open source documentation can be found under https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.bar.html\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d509dfb9ce8c8417", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Exercise 5\n", - "\n", - "Initialize the variables with the following data and plot a bar graph to vizualize the popularity of various Programming languages.\n", - "\n", - "|Programming Languages|Java|Python|PHP|JavaScript|C\\#|C++|\n", - "|--|--|--|--|--|--|--|\n", - "|Popularity|22.2|17.6|8.8|8|7.7|6.7|\n", - "\n", - "- The plot should have grids on (both major and minor). \n", - "- Name the title of the figure as __Popularity of Programming Language Worldwide__.\n", - "- Label both x and y axes with respective labels.\n", - "\n", - "The final plot should look like this:\n", - "\n", - "![Exercise 5a](exercise5_a.png)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "x = ['Java', 'Python', 'PHP', 'JavaScript', 'C#', 'C++']\n", - "p = [22.2, 17.6, 8.8, 8, 7.7, 6.7]\n", - "x_pos = [i for i,val in enumerate(x)]\n", - "\n", - "fig = plt.figure()\n", - "ax = fig.add_axes([0,0,1,1])\n", - "\n", - "ax.set_title('Popularity of Programming Language Worldwide')\n", - "ax.set_xlabel('Languages')\n", - "ax.set_ylabel('Popularity')\n", - "\n", - "ax.minorticks_on()\n", - "ax.grid(which='minor',linestyle=':')\n", - "ax.grid(which='major',linestyle='-')\n", - "\n", - "bar = ax.bar(x_pos,p)\n", - "ax.set_xticks(x_pos,x)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-5e9ee62323d8fb2d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "Change the color of the bars to ['red', 'black', 'green', 'blue', 'yellow', 'cyan'] :\n", - "\n", - "![Exercise 5c](exercise5_c.png)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "colors = ['red', 'black', 'green', 'blue', 'yellow', 'cyan']\n", - "for i,color in enumerate(colors):\n", - " bar[i].set_color(color)\n", - "fig\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-345c3a5c2f31b1c4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "Plot the same data as horizontal bar graph in a new figure as shown below:\n", - "\n", - "![Exercise 5b](exercise5_b.png)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "fig = plt.figure()\n", - "ax = fig.add_axes([0,0,1,1])\n", - "ax.set_title('Popularity of Programming Language Worldwide')\n", - "ax.set_xlabel('Popularity')\n", - "ax.set_ylabel('Languages')\n", - "\n", - "ax.minorticks_on()\n", - "ax.grid(which='minor',linestyle=':')\n", - "ax.grid(which='major',linestyle='-')\n", - "\n", - "ax.barh(x_pos,p)\n", - "ax.set_yticks(x_pos,x)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4356eca51fa89384", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Pie Charts\n", - "\n", - "A pie chart is a circular statistical graphic, which is divided into slices to illustrate numerical proportions. In a pie chart, the arc length of each slice is proportional to the quantity it represents. Pie charts are a popular way to represent the results of polls. The open source documentation can be found under https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.pie.html#matplotlib.pyplot.pie" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-6c1fcc8a4ad86fac", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Exercise 6\n", - "\n", - "Initialize the following data and plot a pie chart to visualize the prefered sports among people:\n", - "|Sports|Cricket|Football|Hockey|F1|\n", - "|--|--|--|--|--|\n", - "|People|15|30|45|10|\n", - "\n", - "The sports title should be the labels of the pie chart as shown below:\n", - "\n", - "![Exercise 6a](exercise6_a.png)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "\n", - "s = ['Cricket', 'Football', 'Hockey', 'F1']\n", - "p = [15, 30, 45, 10]\n", - "\n", - "fig,ax = plt.subplots()\n", - "ax.pie(p,labels=s)\n", - "# ax.axis('equal')\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-d16322e4cb78e72c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "# Contour plots\n", - "\n", - "Contour plots also called level plots are a tool for doing multivariate analysis and visualizing 3-D plots in 2-D space. If we consider X and Y as our variables we want to plot then the response Z will be plotted as slices on the X-Y plane due to which contours are sometimes referred as Z-slices or iso-response.\n", - "\n", - "Contour plots are widely used to visualize density, altitudes or heights of the mountain as well as in the meteorological department. Due to such wide usage matplotlib.pyplot provides a method contour to make it easy for us to draw contour plots." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-75ecdb619bbc13d3", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "source": [ - "## Exercise 7\n", - "\n", - "Make a contour plot of the equation $Z=X^2+Y^2$ by first creating a mesh grid between $x$ and $y$. The plot should look as follows:\n", - "\n", - "![Exercise 7a](exercise7_a.png)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "x = np.arange(0,100)\n", - "y = x*2\n", - "\n", - "\n", - "[X, Y] = np.meshgrid(x, y)\n", - "fig, ax = plt.subplots(1, 1)\n", - " \n", - "Z = X**2 + Y**2 \n", - "ax.contour(X, Y, Z)\n", - "\n", - "ax.set_title('Contour Plot')\n", - "ax.set_xlabel('X')\n", - "ax.set_ylabel('Y')\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.16" - }, - "vscode": { - "interpreter": { - "hash": "23df9ff646ca1c5e2dfe7a3d7568c302b6a7972f96b6a2ba92f9d9e3e979b69c" - } - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/Material/wise_24_25/lernmaterial/python-plotting/exercise1.png b/Material/wise_24_25/lernmaterial/python-plotting/exercise1.png deleted file mode 100644 index 97871b7adcc17525aa6e2b2c2a03bc9eb8f0c58c..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 15259 zcmb_@cRZKx+xMkX8bp1Ij7ZWjQdYv=tY)aP`Kb06>XeY}t3y04;ik#ZOPE)2sceZoS-lJ+GW?4p0) zsr#!kF+*ZnNZ@F6OkR4^FJt z)ryq(4^}LMJBjS6;MoQpi+!SGstmta_Nnr-@I$@L=n(u++{xYpKied=(M;T7;oJ&8 zlGGt&7)D~DfH}e>sJ%_#hlK)O)2{8zvl_g0&h1fH7~TA6)5ZL5;&ZXhHHY4}Od`Zj zeYec39x`QY1cNBj=)gDEG}P+Qf5=D_?9q;(5*LM&P+$B8y4l>vE-QgQxRuPhY1z zd|rF8+bKpikUmjlsz_~fsY-mUQf#)Cx3k2(P%}gK*rTeZpHmptCjs-|e_2_%?N?s~ zKXF1^bnRD#%XhCG>gwtVTvy+CyK}p*F0@oXQFD5G&W}WC7icvaV7rZBg^-9$Rp00Jb0-TMZd7TRpKg52w54s&t7Kk z(VFkh0$1~GTKs5^HfLNF{P^*s#kaS1D>a52KSWAzeBRgXxw#&ckekbA*d6~)xN4#! z=UI4o%JS^+_|kNLgosmS$6^`(pRX_q%)NhMwDwJ<~F{^60Q==h7ru86)hi z?Btadmnb0z+0C_K@jQoNrFB>xO+CHH%)*}q>{Wt%d?OpHQ(CgJK5uSz!3379#rW=L zS7^9LYmmHy*-d40R(vyF%zY)E0kORFIw6pxnTCslSHeo zH#aX|zHDi~)>q-Hp{JLA)wZ~W_UWl!D)4^Lst6CMiW(wnZvMpHD#(G1igQt#A7*>;2R`E+%$?=6Q+fXAq$tsa3B{@}V zYwJQWTC7$I?c9QqIDbCtb{>8E&&L$Ef0rVnhPeI_6Zm8ddp_Deb|7U0jAG-vkAY9=#AWHyg95=eb;C zm}}cBrlFxh?mh*(JuNp^yG>_6+I|Z=W1M@dPpWvPngdcuz$`&@uUe>D$eDR$76Fcx8R5m}VH%u3k-Zo*g=Q=FFAu zLZ>#zHvJ^9E6zwma_9`rr{?S;Fk*ndi?*ffZ)Rp@2t&1p0-41P0JG-;bzWV+rT3-79utv?lG7oSdA?#H%X8aFkQ( z>({Dq95wGgT@?G=wnQfgEzi@Ze-&@6j2Enor9EHQ%WC5Ytx2q|zWlMO%6Co#+A4G7 z`r;Wf#;K*Lc{vEqBsMu28JSaDTrB{Q?#7WyNwSX)XF#o&f_ClNrLLtlELhn;eL_^U zTaaDl=FJRPvR-tKQrrm7wx;uWos+|F*?b}~DM>!)vb_8;=$)L0ad1$O+c5ljfPo=x zwq9I(Buqj`NXY)3Udcs3oQs}JP=Pd7<30G!VR#IHtPPGnhA4+~j2`ur73KuahK@>3 zFtTUQo|RO=4(bxKLoaa3dk@0eSd6!3RM*#Q#fZ7PRdw6sv+);5>1k>X6?RS#3msSH zES`mi?qJ&gX_RmZcG?u|Cv4kUeoh9T7toqz(@Vt_Fv4^=bV_F}EG+B`y8(!1nMB-I za*02`r93%$@p6z46;mp=e!)`U$&)7=0d?Jtp^|Hgj`NhdC6gD5S3F*Is9C56gfoko z)iHvxD|s$eFaxp<7v7n$e}^^{Scr*9^JLJ2cK6&yYEwiAyHVd{rDd$9Ha--<@?z}1UcRwP}&^sH&?JKB? 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zfWqoJZ1(8Ke(D4iJZQnmgHSoa$X1i63t^}!J<pcYPc);$h_yix;(Ng2t7BNOxHiC=ST;M3Ux+^K3${ y$aZ85{&b-WMNH-YTPNWEpKASoX(4 < scheme > : < scheme-specific-part >\n", - "\n", - "_scheme_ legt fest welche Methode zum abrufen der Resource verwendet wird. (Bsp. HTTP)\n", - "\n", - "_scheme-specific-part_ beschreibt spezifischen Parameter die für das angewandte Protokoll verwendet werden\n", - "\n", - "Beispiel HTTP:\n", - "\n", - "Für das _scheme_ benötingt wird _http://_ oder _https://_ verwendet. _://_ trennt das _scheme_ vom Spezifischen Part.\n", - "\n", - "Optional, für einige APIs notwendig kann jetzt ein Nutzername und Passwort angegeben werden getrennt durch ein _:_ und mit _@_ an die Domain angehängt:\n", - "\n", - "```\n", - "< user >_< password >@< domain >\n", - "```\n", - "\n", - "Notwendig ist der nächste für die meisten Bekannte teil der Host oder Domain.\n", - "Dieser kann als _IPv4_ (Bsp. 178.160.4.2), _IPv6_ (Bsp. 2065::8800) oder _Domainname_ (Bsp. www.tu-braunschweig.de) angegeben werden.\n", - "\n", - "Damit erhält man im Normalfall bereits eine funktionierende Adresse:\n", - "\n", - "> https://www.tu-braunschweig.de/\n", - "\n", - "Die Standardkommunikationskanäle für _HTTP_ & _HTTPS_ sind _80 (HTTP)_ und _443 (HTTPS)_. URL erlaubt aber die Spezifizierung eines abiträren Ports bei eingabe der URL. Dies kann nützlich sein wenn API zugriffe auf anderen Ports passieren sollen oder Dienste auch Sicherheitsgründen bewusst von den Standardports getrennt werden. Gültige Portnummer liegen in dem Bereich von 0 bis 65.535 (=2^16-1). Für das Beispiel wird Port 9090 verwendet. \n", - "\n", - "> e.g.: http://example.com:9090/\n", - "\n", - "Damit auch bestimmte Dateien angesprochen werden können unterstützt HTTP die möglichkeit Pfade anzugeben. Der Standardpfad von Webseiten ist meist eine _/index.html_. Der Pfad kann aber auch auf Unterordner des Webservers bzw. der Resource zugreifen.\n", - "\n", - "> e.g.: http://example.com/directory1/directory2/file.txt\n", - "\n", - "HTTP unterstützt (ähnlich wie Datenbanken) eine _Query_ anfrage. Dazu wird mittels _?_ ein oder mehrere Parameter übergeben. Dazu spezifiziert man erst das abzufragende Attribut (im beispiel _user_) und übergibt diesem einen Wert (im beispiel _=peter_). Mehrere Parameter werden durch _&_ getrennt.\n", - "\n", - "> e.g.: http://example.com/api?user=peter&age=30\n", - "\n", - "HTML Seiten unterstützen _Fragmente_ oder _Kapitel_, diese Werden angegeben mit _#_.\n", - "\n", - "> e.g.: http://example.com/document.html#site3\n", - "\n", - "Daraus ergibt sich nach Spezifizierung folgendes abstraktes Modell für HTTP:\n", - "\n", - "```\n", - "http(s)://:@://?=#\n", - "```\n", - "\n", - "> e.g.: http://peter:1234@example.com:9090/files/users.html?user=peter&age=30#livestory" - ] - }, - { - "cell_type": "markdown", - "id": "40ec9940-0991-4a5a-983c-2dafb6d711e9", - "metadata": {}, - "source": [ - "## JavaScript Object Notation\n", - "\n", - "![](https://upload.wikimedia.org/wikipedia/commons/c/c9/JSON_vector_logo.svg)\n", - "\n", - "(kurz: JSON) 1997 von Douglas Crockford unter [RFC 8529](https://datatracker.ietf.org/doc/html/rfc4627#section-2) spezifiert, ist ein einfach lesbares Textformat zum austauschen von Daten. Es unterstüzt verschiedene Datentypen zum Austausch wie folgende Tabelle Zeigt:\n", - "\n", - "| Type | Value | Explanation |\n", - "|-----------|-----------------------------|----------------------------------------------------------------------------|\n", - "| Nullvalue | _null_ | Describes a Key without any Value |\n", - "| Boolean | _true_ or _false_ | These aren't Strings! |\n", - "| Number | _42_ or _-12.5_ or _3.4e12_ | Describes a Number |\n", - "| String | _\"This is a String\"_ | Just a normal String. Behold _true_ is a Boolean and _\"true\"_ is a String. |\n", - "| Array | _[42, \"best Number\", true]_ | A collection of data can hold mixed Types |\n", - "\n", - "Um ein JSON Objekt zu beschreiben wird es in _{ }_ eingekapselt und folgt einem _< Key >:< Value >_ Konzept, bei dem jedem Wert ein Schlüssel zugeordnet wird. Der Schlüssel muss innerhalb eines Objektes immer eindeutig sein und wird als String, also in Anführungszeichen _\" \"_ angegeben. Schlüssel-Werte-Paare werden mit _,_ getrennt. Bsp.:\n", - "\n", - "```json\n", - "{\n", - " \"Number\": 42,\n", - " \"Question\": \"What is the answer to everything?\",\n", - " \"ComputeTime\": 3.4e6,\n", - " \"finished\": true,\n", - " \"Interns\": [\"Arthur\", \"Ford\", \"Zhapod\", \"Trillian\"]\n", - " \"UnnecessaryNestedObject\": \n", - " {\n", - " \"UnnecessaryNestedObject\": \n", - " {\n", - " \"UnnecessaryNestedObject\": \n", - " {\n", - " \"UnnecessaryNestedObject\": \n", - " {\n", - " \"kEy\": null\n", - " } \n", - " } \n", - " } \n", - " }\n", - "}\n", - "\n", - "```" - ] - }, - { - "cell_type": "markdown", - "id": "0e63b343-032c-40d5-ab7e-3ba89a4e1bf9", - "metadata": {}, - "source": [ - "## Python Datetime" - ] - }, - { - "cell_type": "markdown", - "id": "46189b02-922c-49f3-8afc-e8d52975261d", - "metadata": {}, - "source": [ - "## Stundentenwerk Mensa API\n", - "\n", - "Die Dokumentation zur Mensa API befindet sich unter https://api.stw-on.de/#einfuhrung" - ] - }, - { - "cell_type": "markdown", - "id": "96308adb", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-e23c74ac6f2b9827", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Basic Example\n", - "\n", - "For making the calls to the API, we will use the very popular [requests](https://requests.readthedocs.io/en/latest/) library.\n", - "It allows to perform HTTP requests, which we need to get the latest menu." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "6538d76c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-685a30ab750c3f6c", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "import requests" - ] - }, - { - "cell_type": "markdown", - "id": "d7459fea", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4d486b0abefc44d3", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "An example of an API endpoint that can be used to request the menu for a particular Mensa and week is given in the `API_URL_EXAMPLE`.\n", - "(Try opening that website in your browser and see what happens.)\n", - "\n", - "You will need to adapt this in the following to request the menu for multiple Mensas and varying weeks." - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "dd43eaee", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4a82b88787cce066", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'https://sls.api.stw-on.de/v1/location/101/menu/2023-07-17/2023-07-27'" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from datetime import date, timedelta\n", - "today = date.today()\n", - "\n", - "API_URL_EXAMPLE = \"https://sls.api.stw-on.de/v1/location/101/menu/{}/{}\".format(today - timedelta(days=10), today)\n", - "\n", - "API_URL_EXAMPLE\n", - "\n", - "# Hint Mensa-Codes:\n", - "# Mensa 1: 101\n", - "# Mensa 2: 105\n", - "# 360: 111" - ] - }, - { - "cell_type": "markdown", - "id": "1eb40e52", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b7ec4ca409f5ac01", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "The actual request is done using the `requests.get` command.\n", - "This basically returns the content that you can also see when opening the link in your browser.\n", - "\n", - "Since the returned value is in the [JSON](https://en.wikipedia.org/wiki/JSON) format, we need to use the `.json()` function to grab it.\n", - "\n", - "As you might have noticed already, the JSON format looks very similar to the dictionary structure in Python. Therefore, the output of the `.json()` function is a dictionary, from which we only need the `meals` key." - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "827cc9c2", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-dd3e78d210747035", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[{'date': '2023-07-24',\n", - " 'id': 35099,\n", - " 'lane': {'id': 10, 'name': 'Suppe & Co.', 'name_en': 'Soup & Co.'},\n", - " 'location': {'address': {'city': 'Braunschweig',\n", - " 'line1': 'Mensa 1 TU Braunschweig',\n", - " 'line2': None,\n", - " 'street': 'Katharinenstraße 1',\n", - " 'zip': '38106'},\n", - " 'id': 101,\n", - " 'name': 'Mensa 1 TU Braunschweig',\n", - " 'opening_hours': [{'end_day': 4,\n", - " 'end_time': '14:30:00',\n", - " 'start_day': 1,\n", - " 'start_time': '11:30:00',\n", - " 'time': 'noon'},\n", - " {'end_day': 5,\n", - " 'end_time': '14:00:00',\n", - " 'start_day': 5,\n", - " 'start_time': '11:30:00',\n", - " 'time': 'noon'},\n", - " {'end_day': 0,\n", - " 'end_time': '00:00:14',\n", - " 'start_day': 0,\n", - " 'start_time': '00:00:11',\n", - " 'time': 'noon'}]},\n", - " 'name': 'Die Mensa 1 ist vom 24.07.2023 bis 11.08.2023 geschlossen. Ab dem '\n", - " '14.08.2023 sind wir wieder für Euch da.',\n", - " 'name_en': 'Die Mensa 1 ist vom 24.07.2023 bis 11.08.2023 geschlossen. Ab '\n", - " 'dem 14.08.2023 sind wir wieder für Euch da.',\n", - " 'nutritional_values': {'_NOTE': 'WARNING: These fields currently contain '\n", - " 'incorrect values. Do not use them yet!',\n", - " 'per_100_grams': {'caloric_value': None,\n", - " 'carbohydrates': None,\n", - " 'fat': None,\n", - " 'protein': None,\n", - " 'roughage': None,\n", - " 'salt': None,\n", - " 'saturated_fatty_acids': None,\n", - " 'sugar': None}},\n", - " 'price': {'employee': '0.00', 'guest': '0.00', 'student': '0.00'},\n", - " 'special_tags': ['Deprecated. Use tags→special instead.'],\n", - " 'tags': {'additives': [], 'allergens': [], 'categories': [], 'special': []},\n", - " 'time': 'noon'},\n", - " {'date': '2023-07-25',\n", - " 'id': 35100,\n", - " 'lane': {'id': 10, 'name': 'Suppe & Co.', 'name_en': 'Soup & Co.'},\n", - " 'location': {'address': {'city': 'Braunschweig',\n", - " 'line1': 'Mensa 1 TU Braunschweig',\n", - " 'line2': None,\n", - " 'street': 'Katharinenstraße 1',\n", - " 'zip': '38106'},\n", - " 'id': 101,\n", - " 'name': 'Mensa 1 TU Braunschweig',\n", - " 'opening_hours': [{'end_day': 4,\n", - " 'end_time': '14:30:00',\n", - " 'start_day': 1,\n", - " 'start_time': '11:30:00',\n", - " 'time': 'noon'},\n", - " {'end_day': 5,\n", - " 'end_time': '14:00:00',\n", - " 'start_day': 5,\n", - " 'start_time': '11:30:00',\n", - " 'time': 'noon'},\n", - " {'end_day': 0,\n", - " 'end_time': '00:00:14',\n", - " 'start_day': 0,\n", - " 'start_time': '00:00:11',\n", - " 'time': 'noon'}]},\n", - " 'name': 'Die Mensa 1 ist vom 24.07.2023 bis 11.08.2023 geschlossen. Ab dem '\n", - " '14.08.2023 sind wir wieder für Euch da.',\n", - " 'name_en': 'Die Mensa 1 ist vom 24.07.2023 bis 11.08.2023 geschlossen. Ab '\n", - " 'dem 14.08.2023 sind wir wieder für Euch da.',\n", - " 'nutritional_values': {'_NOTE': 'WARNING: These fields currently contain '\n", - " 'incorrect values. Do not use them yet!',\n", - " 'per_100_grams': {'caloric_value': None,\n", - " 'carbohydrates': None,\n", - " 'fat': None,\n", - " 'protein': None,\n", - " 'roughage': None,\n", - " 'salt': None,\n", - " 'saturated_fatty_acids': None,\n", - " 'sugar': None}},\n", - " 'price': {'employee': '0.00', 'guest': '0.00', 'student': '0.00'},\n", - " 'special_tags': ['Deprecated. Use tags→special instead.'],\n", - " 'tags': {'additives': [], 'allergens': [], 'categories': [], 'special': []},\n", - " 'time': 'noon'},\n", - " {'date': '2023-07-26',\n", - " 'id': 35101,\n", - " 'lane': {'id': 10, 'name': 'Suppe & Co.', 'name_en': 'Soup & Co.'},\n", - " 'location': {'address': {'city': 'Braunschweig',\n", - " 'line1': 'Mensa 1 TU Braunschweig',\n", - " 'line2': None,\n", - " 'street': 'Katharinenstraße 1',\n", - " 'zip': '38106'},\n", - " 'id': 101,\n", - " 'name': 'Mensa 1 TU Braunschweig',\n", - " 'opening_hours': [{'end_day': 4,\n", - " 'end_time': '14:30:00',\n", - " 'start_day': 1,\n", - " 'start_time': '11:30:00',\n", - " 'time': 'noon'},\n", - " {'end_day': 5,\n", - " 'end_time': '14:00:00',\n", - " 'start_day': 5,\n", - " 'start_time': '11:30:00',\n", - " 'time': 'noon'},\n", - " {'end_day': 0,\n", - " 'end_time': '00:00:14',\n", - " 'start_day': 0,\n", - " 'start_time': '00:00:11',\n", - " 'time': 'noon'}]},\n", - " 'name': 'Die Mensa 1 ist vom 24.07.2023 bis 11.08.2023 geschlossen. Ab dem '\n", - " '14.08.2023 sind wir wieder für Euch da.',\n", - " 'name_en': 'Die Mensa 1 ist vom 24.07.2023 bis 11.08.2023 geschlossen. Ab '\n", - " 'dem 14.08.2023 sind wir wieder für Euch da.',\n", - " 'nutritional_values': {'_NOTE': 'WARNING: These fields currently contain '\n", - " 'incorrect values. Do not use them yet!',\n", - " 'per_100_grams': {'caloric_value': None,\n", - " 'carbohydrates': None,\n", - " 'fat': None,\n", - " 'protein': None,\n", - " 'roughage': None,\n", - " 'salt': None,\n", - " 'saturated_fatty_acids': None,\n", - " 'sugar': None}},\n", - " 'price': {'employee': '0.00', 'guest': '0.00', 'student': '0.00'},\n", - " 'special_tags': ['Deprecated. Use tags→special instead.'],\n", - " 'tags': {'additives': [], 'allergens': [], 'categories': [], 'special': []},\n", - " 'time': 'noon'},\n", - " {'date': '2023-07-27',\n", - " 'id': 35102,\n", - " 'lane': {'id': 10, 'name': 'Suppe & Co.', 'name_en': 'Soup & Co.'},\n", - " 'location': {'address': {'city': 'Braunschweig',\n", - " 'line1': 'Mensa 1 TU Braunschweig',\n", - " 'line2': None,\n", - " 'street': 'Katharinenstraße 1',\n", - " 'zip': '38106'},\n", - " 'id': 101,\n", - " 'name': 'Mensa 1 TU Braunschweig',\n", - " 'opening_hours': [{'end_day': 4,\n", - " 'end_time': '14:30:00',\n", - " 'start_day': 1,\n", - " 'start_time': '11:30:00',\n", - " 'time': 'noon'},\n", - " {'end_day': 5,\n", - " 'end_time': '14:00:00',\n", - " 'start_day': 5,\n", - " 'start_time': '11:30:00',\n", - " 'time': 'noon'},\n", - " {'end_day': 0,\n", - " 'end_time': '00:00:14',\n", - " 'start_day': 0,\n", - " 'start_time': '00:00:11',\n", - " 'time': 'noon'}]},\n", - " 'name': 'Die Mensa 1 ist vom 24.07.2023 bis 11.08.2023 geschlossen. Ab dem '\n", - " '14.08.2023 sind wir wieder für Euch da.',\n", - " 'name_en': 'Die Mensa 1 ist vom 24.07.2023 bis 11.08.2023 geschlossen. Ab '\n", - " 'dem 14.08.2023 sind wir wieder für Euch da.',\n", - " 'nutritional_values': {'_NOTE': 'WARNING: These fields currently contain '\n", - " 'incorrect values. Do not use them yet!',\n", - " 'per_100_grams': {'caloric_value': None,\n", - " 'carbohydrates': None,\n", - " 'fat': None,\n", - " 'protein': None,\n", - " 'roughage': None,\n", - " 'salt': None,\n", - " 'saturated_fatty_acids': None,\n", - " 'sugar': None}},\n", - " 'price': {'employee': '0.00', 'guest': '0.00', 'student': '0.00'},\n", - " 'special_tags': ['Deprecated. Use tags→special instead.'],\n", - " 'tags': {'additives': [], 'allergens': [], 'categories': [], 'special': []},\n", - " 'time': 'noon'}]\n" - ] - } - ], - "source": [ - "resp = requests.get(API_URL_EXAMPLE)\n", - "data = resp.json()\n", - "\n", - "from pprint import pprint\n", - "pprint(data.get(\"meals\"))" - ] - }, - { - "cell_type": "markdown", - "id": "ba34c8a8", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-bd8670a16c01faaf", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "The response object `resp` contains all information about the returned response, e.g., the [status code](https://en.wikipedia.org/wiki/List_of_HTTP_status_codes). This can be accessed using `resp.status_code`." - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "30c25792", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-8c31ebd06d496e82", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Response Status Code: 200\n", - "The response is OK\n" - ] - } - ], - "source": [ - "print(f\"Response Status Code: {resp.status_code:d}\")\n", - "if resp.status_code == 200:\n", - " print(\"The response is OK\")\n", - "elif resp.status_code == 400:\n", - " print(\"Bad request\")\n", - "elif resp.status_code == 404:\n", - " print(\"Page not found\")" - ] - }, - { - "cell_type": "markdown", - "id": "7f29b034", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3a85de1510d22a61", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "# Exercise\n", - "\n", - "## Task 1\n", - "\n", - "wake a response to the Mensa-Api for the timeframe _today - 7 Days_ and _today - 1 Day_." - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "id": "87f6c752", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0b6b462a6367f7f4", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "from datetime import date, timedelta" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "id": "8930b71f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-08a14df39976e5fd", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "today = date.today()\n", - "API_URL = \"https://sls.api.stw-on.de/v1/location/101/menu/{}/{}\".format(today - timedelta(days = 7), today - timedelta(days = 1))\n", - "resp = requests.get(API_URL)\n", - "resp_json = resp.json()\n", - "meals = resp_json.get(\"meals\")\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "id": "9f9e52ec", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-547c77541bc7e8d7", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "ename": "AssertionError", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[76], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(meals, \u001b[38;5;28mlist\u001b[39m)\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(meals) \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m meals[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdate\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mstr\u001b[39m(today \u001b[38;5;241m-\u001b[39m timedelta(days \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m7\u001b[39m))\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m meals[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m][\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdate\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mstr\u001b[39m(today \u001b[38;5;241m-\u001b[39m timedelta(days \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m))\n", - "\u001b[0;31mAssertionError\u001b[0m: " - ] - } - ], - "source": [ - "assert isinstance(meals, list)\n", - "assert len(meals) >= 1\n", - "assert meals[0]['date'] == str(today - timedelta(days = 7))\n", - "assert meals[-1]['date'] == str(today - timedelta(days = 1))" - ] - }, - { - "cell_type": "markdown", - "id": "f174a34e", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-ed3079a3df502335", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Now convert the list of meals into a Pandas DataFrame object and store it in `df_meals`.\n", - "Make sure that the `date` column has the `datetime` data type and that the prices are in a numeric (`float`) format.\n", - "\n", - "_Hint:_ You might want to check the [`pandas.json_normalize`](https://pandas.pydata.org/docs/reference/api/pandas.json_normalize.html) function." - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "id": "cefd8da9", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-9259345eb48b5c8b", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION ###\n", - "df_meals = pd.json_normalize(meals)\n", - "df_meals[\"date\"] = pd.to_datetime(df_meals[\"date\"])\n", - "df_meals[\"price.student\"] = pd.to_numeric(df_meals[\"price.student\"])\n", - "### END SOLUTION ###" - ] - }, - { - "cell_type": "code", - "execution_count": 78, - "id": "349bfe40", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-7757b771151de7c4", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "assert isinstance(df_meals, pd.DataFrame)\n", - "assert df_meals['price.student'].dtype == float" - ] - }, - { - "cell_type": "markdown", - "id": "f564dc6c", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-6ac65fd244814f1d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "Next, create a simple plot that plots the student prices over time. You can use a scatter plot to do this." - ] - }, - { - "cell_type": "code", - "execution_count": 79, - "id": "c0d9ebed", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-b407c97934dfeca2", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 79, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "plt.scatter(df_meals[\"date\"], df_meals[\"price.student\"])\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "markdown", - "id": "b2f985cc", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-47eead3031d0c7f0", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Task 2\n", - "\n", - "Next, make a request to the Mensa API to get all meals in the time frame August 1, 2022 to December 1, 2022.\n", - "\n", - "What can you observe?" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "id": "dadfc688", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-357c6cd2a43ed307", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "400\n", - "{\"error\":{\"code\":400,\"message\":\"Cannot query more than 21 days at once\"}}\n" - ] - } - ], - "source": [ - "### BEGIN SOLUTION\n", - "API_URL_2 = \"https://sls.api.stw-on.de/v1/location/101/menu/2022-08-01/2022-12-01\"\n", - "resp2 = requests.get(API_URL_2)\n", - "print(resp2.status_code)\n", - "print(resp2.text)\n", - "### END SOLUTION" - ] - } - ], - "metadata": { - "celltoolbar": "Create Assignment", - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/regex/Regular Expressions.ipynb b/Material/wise_24_25/lernmaterial/regex/Regular Expressions.ipynb deleted file mode 100644 index 6417859..0000000 --- a/Material/wise_24_25/lernmaterial/regex/Regular Expressions.ipynb +++ /dev/null @@ -1,850 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "c850ea25-9bde-4feb-a1d0-056c5870d59e", - "metadata": {}, - "source": [ - "# Regular Expressions (Regex)\n", - "\n", - "Wir schreiben das Jahr 1950 der Mathematiker __Stephen Cole Kleene__ erfand das Konzept der _Regulären Sprache_. Ein Konzept der theoretischen Informatik zum Beschreiben von syntaktischen Ausdrücken. Damit einhergehend lassen sich durch spezifische ausdrücke, den _Regular Expressions_, verschiedene Formen des _pattern matching_ durchführen. Eine der mit abstand wichtigensten Anwendungsfälle für _regual expressions_ ist das Kompilieren von Quellcode in Maschinensprache. Dabei werden ausdrücke wie _while_, _for_, _if_ etc. formalisiert und können einfacher in Übersetzt (Kompiliert) werden. \n", - "\n", - "Ein weiterer Nutzen von _regual expressions_ ist das _just-in-time compiling_ von dem auch Python als interpretierte Sprache gebrauch macht. Dabei wird der Quellcode zur Laufzeit für die Maschine übersetzt (meist nicht direkt der Quellcode, sondern eine zwischenstufe die als _Bytecode_ bezeichnet wird). Es wäre sonst nicht möglich so einfach Jupyter Notebooks zu verwenden.\n", - "\n", - "\n", - "Ein paar Fakten zu _regular expressions_:\n", - "\n", - "- _Regex_ findet sich in vielen Dialekten wieder. (vgl. [Regular Expression Engine Comparison](https://gist.github.com/CMCDragonkai/6c933f4a7d713ef712145c5eb94a1816))\n", - "- Die Programmiersprache _Perl_ entstand aus einer Bibliothek von Henry Spencer zum nutzen von _Regex_ \n", - "- Eine frei Nutzbare Seite (Achtung mit Werbung) zum testen und prüfen von Regulären Ausdrücken in verschiedenen Dialekten ist [Regex101](https://regex101.com/)\n", - "- Jedes Unix(-ähnliche) System (Linux, MacOS, BSD, etc.) hat das Programm _grep (**G**lobal/**R**egular **E**xpression/**P**rint)_ zum analysieren von Datenströmen/Textdateien vorinstalliert.\n", - "\n", - "\n", - "

\"Kleene.jpg\"
By Konrad Jacobs, Erlangen, Copyright is MFO - Mathematisches Forschungsinstitut Oberwolfach,<a rel=\"nofollow\" class=\"external free\" href=\"https://opc.mfo.de/detail?photo_id=2122\">https://opc.mfo.de/detail?photo_id=2122</a>, CC BY-SA 2.0 de, Link

" - ] - }, - { - "cell_type": "markdown", - "id": "b689ee80", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-27269d9f8e03f3e9", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Introduction\n", - "\n", - "You can find _a lot_ of material on regular expressions (regex) online.\n", - "Therefore, we will not repeat the background but focus on some practical exercises in this notebook. Some tutorials/useful links can be found below.\n", - "\n", - "The way that we need and use regular expressions is to describe patterns of characters to match in a given string.\n", - "\n", - "You can think of them as a string of characters, which describe a certain pattern, e.g., \"four numbers followed by a word of at least 5 characters\". \n", - "This can then be used to test given strings/texts and match the pattern specified in the regex.\n", - "This is done using the [Python Standard Library `re`](https://docs.python.org/3/library/re.html).\n", - "\n", - "\n", - "**Material on Regular Expressions:**\n", - "\n", - "- [RegEx Howto in Python](https://docs.python.org/3/howto/regex.html)\n", - "- [RegEx Tutorial](https://www.regular-expressions.info/tutorial.html)\n", - "- [Interactive RegEx Tutorial](https://regexone.com/)\n", - "- [WikiBook on RegEx](https://en.wikibooks.org/wiki/Regular_Expressions)\n", - "- [RegExr: Testing & Visualizing RegEx](https://regexr.com/)\n", - "- [Debuggex: Visualization of individual regex as finite state machine](https://www.debuggex.com/)\n", - "\n", - "**Testing with Regular Expressions:**\n", - "- [Regex101](https://regex101.com/)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "8a5d3654", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-168430a9112ab605", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "import re" - ] - }, - { - "cell_type": "markdown", - "id": "b6ccac77", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4c79f2d5a1e62a04", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Example 1\n", - "The regular expression `Hello [A-Z][a-z]+` specifies a pattern that begins with the literal string `Hello ` and is followed by a capital letter (specified by `[A-Z]`) and at least one small letter. (`[a-z]` describes the lowercase letters and `+` specifies that there is at least one of them)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "7e25056b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-98f2d91954c191a3", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Testing the string: 'Hello World'\n", - "Found pattern at characters: 0 to 11\n", - "---------------------------------------------\n", - "Testing the string: 'Hello You!'\n", - "Found pattern at characters: 0 to 9\n", - "---------------------------------------------\n", - "Testing the string: 'This does not match the pattern...'\n", - "Pattern not found in string.\n", - "---------------------------------------------\n", - "Testing the string: 'We can also have the Hello World pattern somewhere within the string.'\n", - "Found pattern at characters: 21 to 32\n", - "---------------------------------------------\n", - "Testing the string: 'Hello world does not match'\n", - "Pattern not found in string.\n", - "---------------------------------------------\n", - "Testing the string: 'Hello W does not match either'\n", - "Pattern not found in string.\n", - "---------------------------------------------\n" - ] - } - ], - "source": [ - "example_re = r'Hello [A-Z][a-z]+'\n", - "test_strings = ['Hello World',\n", - " 'Hello You!',\n", - " 'This does not match the pattern...',\n", - " 'We can also have the Hello World pattern somewhere within the string.',\n", - " 'Hello world does not match',\n", - " 'Hello W does not match either']\n", - "\n", - "\n", - "for test_word in test_strings:\n", - " print(f\"Testing the string: '{test_word}'\")\n", - " match_object = re.search(example_re, test_word)\n", - " if match_object:\n", - " print(f\"Found pattern at characters: {match_object.span()[0]:d} to {match_object.span()[1]:d}\")\n", - " else:\n", - " print(\"Pattern not found in string.\")\n", - " print(\"-\"*45)" - ] - }, - { - "cell_type": "markdown", - "id": "5ec979b2", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-aca8488169bc0df9", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "_Note:_ Since regex often use special characters like backslash `\\`, it is helpful to define them in Python as raw strings, i.e., using a preceding `r` (see `example_re` above)." - ] - }, - { - "cell_type": "markdown", - "id": "820c31ae", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-4d3281e8922cd534", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Task 1\n", - "\n", - "Write a regular expression `r1` which matches the following words:\n", - "- hello\n", - "- yellow\n", - "- jello" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "e7e426b0", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c48986402655ab08", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION ###\n", - "r1 = r'.*ello.*'\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "223fa54c", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-0a761cfdabd44f1b", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "\n", - "\n" - ] - } - ], - "source": [ - "# Test Cell\n", - "\n", - "test_words = ['hello', 'yellow', 'jello']\n", - "for _word in test_words:\n", - " match = re.match(r1, _word)\n", - " print(match)\n", - " if match is None: assert False\n", - " assert match[0] == _word" - ] - }, - { - "cell_type": "markdown", - "id": "c3086449", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-bea454dd22c7499a", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Example 2\n", - "\n", - "In the first example, we have use the `[A-Z]` and `[a-z]` patterns to specify capital and lowercase letters, respectively.\n", - "There are a lot more of such predefined patterns, e.g., `[0-9]` or `\\d` for matching a (single-digit) number.\n", - "\n", - "A list of these special characters can be found in the [`re` documentation](https://docs.python.org/3/library/re.html#regular-expression-syntax).\n", - "\n", - "\n", - "The following regex can be used to match a word with at least 3 letters (both capital and lowercase are accepted), followed by a two-digit number, a comma, and a four-digit number where the first number is either a one or a two." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "5a02b00a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-1a01734fc48cc488", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Testing the string: 'November 21, 2022'\n", - "Found pattern at characters: 0 to 17\n", - "---------------------------------------------\n", - "Testing the string: 'Jan 01, 1970'\n", - "Found pattern at characters: 0 to 12\n", - "---------------------------------------------\n", - "Testing the string: 'JuNE 45, 4521'\n", - "Pattern not found in string.\n", - "---------------------------------------------\n", - "Testing the string: 'Abc 1, 2020'\n", - "Pattern not found in string.\n", - "---------------------------------------------\n", - "Testing the string: 'July 02, 90'\n", - "Pattern not found in string.\n", - "---------------------------------------------\n" - ] - } - ], - "source": [ - "example_re2 = r'[A-Za-z]{3,} \\d{2}, [12]\\d{3}'\n", - "\n", - "test_strings = ['November 21, 2022',\n", - " 'Jan 01, 1970',\n", - " 'JuNE 45, 4521',\n", - " 'Abc 1, 2020',\n", - " 'July 02, 90']\n", - "\n", - "\n", - "for test_word in test_strings:\n", - " print(f\"Testing the string: '{test_word}'\")\n", - " match_object = re.search(example_re2, test_word)\n", - " if match_object:\n", - " print(f\"Found pattern at characters: {match_object.span()[0]:d} to {match_object.span()[1]:d}\")\n", - " else:\n", - " print(\"Pattern not found in string.\")\n", - " print(\"-\"*45)" - ] - }, - { - "cell_type": "markdown", - "id": "b565244d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-0abe35e63e18f0d9", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Task 2\n", - "\n", - "Write a regular expression `r2` that only matches dates in the ISO format `YYYY-MM-DD`.\n", - "It should _only_ match a string, if the whole string is a date. If the date is only part of the string, it should *not* match it.\n", - "\n", - "_Hint:_ You can use `(a[0-9]|b[01])` to specify the pattern that matches either an `a` followed by a single digit **or** a `b` followed by either `0` or `1`." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "1e2bb2bd", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c264d2e9cac73db0", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "r2 = r'^(\\d{4})-(0[1-9]|1[012])-(0[1-9]|[12][0-9]|3[01])$'\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "5bbd62f5", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-c80282e7adcccb6a", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "\n", - "\n", - "\n", - "\n" - ] - } - ], - "source": [ - "# Test Cell\n", - "\n", - "# The following strings should be matched\n", - "dates = [\"1970-01-01\", \"1999-12-31\", \"2000-02-28\", \"2022-12-09\", \"4250-09-10\"]\n", - "for _date in dates:\n", - " match = re.match(r2, _date)\n", - " print(match)\n", - " if match is None: assert False\n", - " assert match[0] == _date" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "0d8e4b98", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-e46e8f78178eb2b7", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "None\n", - "None\n", - "None\n", - "None\n", - "None\n", - "None\n", - "None\n" - ] - } - ], - "source": [ - "# Test Cell\n", - "\n", - "# The following strings should not be matched\n", - "no_dates = [\"1970-01-32\", \"abcd-12-31\", \"2000/02/28\", \"2022-14-20\", \"2002.12.02\", \"1234-2-1\", \"77-09-02\"]\n", - "for _date in no_dates:\n", - " match = re.match(r2, _date)\n", - " print(match)\n", - " if match is not None: assert False" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "b72e49ac", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-48f63facb72e517a", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "None\n", - "None\n" - ] - } - ], - "source": [ - "# Test Cell\n", - "\n", - "# The following strings should not be matched\n", - "no_match = [\"This text contains the date 1999-12-31 but it should not be matched.\",\n", - " \"2020-02-20 is a date in the beginning of the string\"]\n", - "for _text in no_match:\n", - " match = re.match(r2, _text)\n", - " print(match)\n", - " if match is not None: assert False" - ] - }, - { - "cell_type": "markdown", - "id": "ce239065", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-31d99fd79761847d", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Example 3\n", - "\n", - "You can save parts of the found pattern in a group to have access to it later.\n", - "\n", - "In the following example, we modify the regex from [Example 2](#Example-2) to capture the individual parts into groups." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "89ba4f51", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-7d320972e47ae922", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "('November', '21', '2022')\n" - ] - } - ], - "source": [ - "example_re3 = r'([A-Za-z]{3,}) (\\d{2}), ([12]\\d{3})'\n", - "\n", - "test_string = 'November 21, 2022'\n", - "match = re.search(example_re3, test_string)\n", - "print(match.groups())" - ] - }, - { - "cell_type": "markdown", - "id": "393ff9c6", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-68cbff25c972809f", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Task 3\n", - "\n", - "Write a regular expression `r3` which matches text between `
  • ...
  • ` tags and adds the found text to a group. This should be the only capturing group!\n", - "\n", - "_Hint:_ You might want to check how to define non-capturing groups and non-greedy matching." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "c93ee04d", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-420f01248c7eddeb", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "### BEGIN SOLUTION\n", - "r3 = r'
  • ((?:.|\\n)*?)
  • '\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "37681e3d", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-488cd60d5bed2019", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['Item 1', '\\nItem 2', '\\n Item 3\\n ']\n" - ] - } - ], - "source": [ - "# Test Cell\n", - "\n", - "test_html = \"\"\"\n", - "\n", - " \n", - " Test HTML\n", - " \n", - " \n", - "

    Heading 1

    \n", - "
      \n", - "
    1. Item 1
    2. \n", - "
    3. \n", - "Item 2
    4. \n", - "
    5. \n", - " Item 3\n", - "
    6. \n", - "
    \n", - " \n", - "\n", - "\"\"\"\n", - "\n", - "matches = re.findall(r3, test_html)\n", - "print(matches)\n", - "assert len(matches) == 3\n", - "assert matches == ['Item 1', '\\nItem 2', '\\n Item 3\\n ']" - ] - }, - { - "cell_type": "markdown", - "id": "4370f245", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-53152b78922af0b1", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Task 4\n", - "\n", - "Write a regular expression `r4` to find all words in a string that are acronmyms, i.e., written in all capital letters, and all words that have a capital letter in them which is not at the first position.\n", - "\n", - "Next, write a function `shield_acronyms` that uses this regular expression and adds curly brackets `{...}` around the found words and returns a new string.\n", - "\n", - "_Hint:_ You can use the [`re.sub` function](https://docs.python.org/3/library/re.html#re.sub) for this task." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "ed6b99f1", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-545bc5786ee8e947", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Define r4 here\n", - "### BEGIN SOLUTION\n", - "r4 = r'([0-9A-Z]+\\b|[a-zA-Z]+[A-Z0-9]+[a-zA-Z\\b]*)'\n", - "### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "504cd6d3", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-900922b2243d5a55", - "locked": true, - "points": 1, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['MIMO']\n", - "['M2M']\n", - "['IN', 'mmWave']\n", - "['5G', 'SHIELded']\n", - "[]\n" - ] - } - ], - "source": [ - "# Test Cell\n", - "\n", - "test_words = [(\"MIMO\", [\"MIMO\"]),\n", - " (\"M2M\", [\"M2M\"]),\n", - " (r\"Acro IN mmWave Title\", [\"IN\", \"mmWave\"]),\n", - " (r\"5G should be SHIELded\", [\"5G\", \"SHIELded\"]),\n", - " (r\"Regular title with Names\", []),\n", - " ]\n", - "for text, matches in test_words:\n", - " result = re.findall(r4, text)\n", - " print(result)\n", - " assert result == matches" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "f955d228", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-2c36d0ef19bac550", - "locked": false, - "schema_version": 3, - "solution": true, - "task": false - }, - "tags": [] - }, - "outputs": [], - "source": [ - "def shield_acronyms(text: str) -> str:\n", - " ### BEGIN SOLUTION\n", - " r4 = r4 = r'([0-9A-Z]+\\b|[a-zA-Z]+[A-Z0-9]+[a-zA-Z\\b]*)'\n", - " new_text = re.sub(r4, r'{\\g<0>}', text)\n", - " return new_text\n", - " ### END SOLUTION" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "3b71b683", - "metadata": { - "nbgrader": { - "grade": true, - "grade_id": "cell-550110e95fccc717", - "locked": true, - "points": 2, - "schema_version": 3, - "solution": false, - "task": false - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{MIMO}\n", - "{M2M}\n", - "Acro {IN} {mmWave} Title\n", - "{5G} should be {SHIELded}\n", - "Regular title with Names\n" - ] - } - ], - "source": [ - "# Test Cell\n", - "\n", - "test_words = [(\"MIMO\", r\"{MIMO}\"),\n", - " (\"M2M\", r\"{M2M}\"),\n", - " (r\"Acro IN mmWave Title\", r\"Acro {IN} {mmWave} Title\"),\n", - " (r\"5G should be SHIELded\", r\"{5G} should be {SHIELded}\"),\n", - " (r\"Regular title with Names\", r'Regular title with Names'),\n", - " ]\n", - "for text, expected in test_words:\n", - " result = shield_acronyms(text)\n", - " print(result)\n", - " assert result == expected" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "41222440-923d-44a4-8dc7-d7a6309d4e0a", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "celltoolbar": "Create Assignment", - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.16" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/regex/Web Parsing.ipynb b/Material/wise_24_25/lernmaterial/regex/Web Parsing.ipynb deleted file mode 100644 index 5d7d470..0000000 --- a/Material/wise_24_25/lernmaterial/regex/Web Parsing.ipynb +++ /dev/null @@ -1,171 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "8f7ee9ed", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-fd19a00f47ad1a34", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "- [Beautiful Soup Documentation](https://beautiful-soup-4.readthedocs.io/en/latest/)" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "ebaad76f", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-9138585fc343d8a7", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "from bs4 import BeautifulSoup" - ] - }, - { - "cell_type": "markdown", - "id": "1336423a", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-235041934d89cb33", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "source": [ - "## Example of Parsing a Website" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "8bf54e3b", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-c6761d82e17018f0", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "with open(\"example.html\") as html_file:\n", - " soup = BeautifulSoup(html_file)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "14566e25", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-93b2d5726c5469a8", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Test HTML\n", - "Test HTML\n", - "------------------------------\n", - "Print all list elements on the website:\n", - "Item 1\n", - "\n", - "Item 2\n", - "\n", - " Item 3\n", - " \n" - ] - } - ], - "source": [ - "print(soup.title)\n", - "print(soup.title.get_text())\n", - "\n", - "\n", - "print(\"-\"*30)\n", - "print(\"Print all list elements on the website:\")\n", - "\n", - "li = soup.find_all(\"li\")\n", - "for element in li:\n", - " print(element.get_text()) # you can use .strip() to get rid of trailing whitespace" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "d64b13b5", - "metadata": { - "nbgrader": { - "grade": false, - "grade_id": "cell-3a99db5db1577717", - "locked": true, - "schema_version": 3, - "solution": false, - "task": false - } - }, - "outputs": [], - "source": [ - "import requests" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4bdf24a4", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "celltoolbar": "Create Assignment", - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.8" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Material/wise_24_25/lernmaterial/regex/example.html b/Material/wise_24_25/lernmaterial/regex/example.html deleted file mode 100644 index 6578ac4..0000000 --- a/Material/wise_24_25/lernmaterial/regex/example.html +++ /dev/null @@ -1,16 +0,0 @@ - - - Test HTML - - -

    Heading 1

    -
      -
    1. Item 1
    2. -
    3. -Item 2
    4. -
    5. - Item 3 -
    6. -
    - - \ No newline at end of file diff --git a/Material/wise_24_25/lernmaterial/survey.csv b/Material/wise_24_25/lernmaterial/survey.csv deleted file mode 100644 index d1e8039..0000000 --- a/Material/wise_24_25/lernmaterial/survey.csv +++ /dev/null @@ -1,26 +0,0 @@ -Age,Sex,Scale Python Exp,Course,Has Voice Assistent Contact,Voice Assistent,Scale Study Satisfaction,Uses Smartphone,Which Smartphone,Has Computer,Which OS,Scale Programming Exp -22,Männlich,4,Medienwissenschaften,Ja,Apple Siri,4,Ja,Apple,Ja,Mac OS,2 -26,Weiblich,3,Medienwissenschaften,Ja,Amazon Alexa,2,Ja,Xiaomi,Ja,Windows 10,3 -21,Männlich,3,Medienwissenschaften,Ja,Google Now,4,Ja,Sonstige,Ja,Windows 10,3 -26,Weiblich,4,Medienwissenschaften,Ja,Apple Siri,4,Ja,Samsung,Ja,Windows 10,2 -24,Weiblich,4,Psychologie,Nein,,4,Ja,Apple,Ja,Windows 11,3 -23,Männlich,3,Medienwissenschaften,Ja,Amazon Alexa,4,Ja,Samsung,Ja,Windows 10,3 -21,Männlich,3,Medienwissenschaften,Ja,Amazon Alexa,4,Ja,Samsung,Ja,Windows 10,2 -22,Weiblich,4,Medienwissenschaften,Nein,,3,Ja,Samsung,Ja,Windows 10,2 -19,Weiblich,4,Medienwissenschaften,Ja,Apple Siri,3,Ja,Apple,Ja,Windows 11,2 -21,Weiblich,4,Medienwissenschaften,Ja,Google Now,3,Ja,Samsung,Ja,Windows 10,2 -20,Weiblich,4,Medienwissenschaften,Ja,Apple Siri,4,Ja,Apple,Ja,Mac OS,2 -21,Weiblich,4,Medienwissenschaften,Nein,Apple Siri,4,Ja,Apple,Ja,Mac OS,2 -21,Weiblich,4,Medienwissenschaften,Ja,Amazon Alexa,3,Ja,Samsung,Ja,Windows 11,4 -20,Männlich,4,Medienwissenschaften,Nein,,3,Ja,Samsung,Ja,Windows 10,3 -22,Weiblich,4,Medienwissenschaften,Ja,Apple Siri,2,Ja,Apple,Ja,Windows 11,2 -22,Weiblich,4,Medienwissenschaften,Ja,Amazon Alexa,3,Ja,Apple,Ja,Mac OS,1 -21,Weiblich,4,Medienwissenschaften,Nein,,3,Ja,Apple,Ja,Mac OS,4 -19,Männlich,3,Medienwissenschaften,Ja,Apple Siri,4,Ja,Apple,Ja,Windows 10,2 -30,Weiblich,3,Medienwissenschaften,Ja,Apple Siri,3,Ja,Apple,Ja,Mac OS,2 -27,Weiblich,4,Medienwissenschaften,Ja,Apple Siri,3,Ja,Apple,Ja,Windows 11,2 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