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bnaul/bokeh_test.ipynb

Last active November 28, 2016 02:42
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bokeh_test.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"from bokeh.plotting import figure\n",
"from bokeh.charts import Histogram\n",
"from bokeh.embed import notebook_div\n",
"from bokeh.mpl import to_bokeh\n",
"from bokeh.layouts import gridplot\n",
"from bokeh.models import Legend\n",
"from bokeh.palettes import PuBu3 as palette\n",
"from bokeh.io import output_notebook, show\n",
"\n",
"\n",
"N = 100\n",
"features = ['amplitude', 'median', 'maximum', 'minimum']\n",
"labels = ['A', 'B', 'C']\n",
"X = pd.DataFrame(np.random.normal(size=(N, len(features))), columns=features)\n",
"y = np.random.choice(labels, size=X.shape[0])\n",
"colors = [palette[i] for i in range(len(labels))]\n",
"\n",
"plots = [[figure(width=300, height=200) for j in range(X.shape[1])] for i in range(X.shape[1])]\n",
"for i in range(X.shape[1]):\n",
" for j in range(X.shape[1]):\n",
" for l, c in zip(labels, colors):\n",
" inds = np.where(y == l)[0]\n",
" plots[i][j].circle(X.values[inds, i], X.values[inds, j], color=c, legend=l if i == j else None)\n",
" plots[i][j].legend.location = 'bottom_right'\n",
" plots[i][j].xaxis.axis_label = features[i]\n",
" plots[i][j].yaxis.axis_label = features[j]\n",
"\n",
"plot = gridplot(plots, ncol=X.shape[1], mergetools=True)\n",
"div = notebook_div(plot)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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"\n",
"\n",
" <div class=\"bk-root\">\n",
" <div class=\"plotdiv\" id=\"050a046b-fa1c-4f30-8e88-c651a0e7a06d\"></div>\n",
" </div>\n",
"<script type=\"text/javascript\">\n",
" \n",
" (function(global) {\n",
" function now() {\n",
" return new Date();\n",
" }\n",
" \n",
" var force = \"\";\n",
" \n",
" if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force !== \"\") {\n",
" window._bokeh_onload_callbacks = [];\n",
" window._bokeh_is_loading = undefined;\n",
" }\n",
" \n",
" \n",
" \n",
" if (typeof (window._bokeh_timeout) === \"undefined\" || force !== \"\") {\n",
" window._bokeh_timeout = Date.now() + 0;\n",
" window._bokeh_failed_load = false;\n",
" }\n",
" \n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
" \"</ul>\\n\"+\n",
" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"</code>\\n\"+\n",
" \"</div>\"}};\n",
" \n",
" function display_loaded() {\n",
" if (window.Bokeh !== undefined) {\n",
" Bokeh.$(\"#050a046b-fa1c-4f30-8e88-c651a0e7a06d\").text(\"BokehJS successfully loaded.\");\n",
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" }\n",
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" \n",
" function run_callbacks() {\n",
" window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
" delete window._bokeh_onload_callbacks\n",
" console.info(\"Bokeh: all callbacks have finished\");\n",
" }\n",
" \n",
" function load_libs(js_urls, callback) {\n",
" window._bokeh_onload_callbacks.push(callback);\n",
" if (window._bokeh_is_loading > 0) {\n",
" console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
" return null;\n",
" }\n",
" if (js_urls == null || js_urls.length === 0) {\n",
" run_callbacks();\n",
" return null;\n",
" }\n",
" console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" window._bokeh_is_loading = js_urls.length;\n",
" for (var i = 0; i < js_urls.length; i++) {\n",
" var url = js_urls[i];\n",
" var s = document.createElement('script');\n",
" s.src = url;\n",
" s.async = false;\n",
" s.onreadystatechange = s.onload = function() {\n",
" window._bokeh_is_loading--;\n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
" run_callbacks()\n",
" }\n",
" };\n",
" s.onerror = function() {\n",
" console.warn(\"failed to load library \" + url);\n",
" };\n",
" console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
" }\n",
" };var element = document.getElementById(\"050a046b-fa1c-4f30-8e88-c651a0e7a06d\");\n",
" if (element == null) {\n",
" console.log(\"Bokeh: ERROR: autoload.js configured with elementid '050a046b-fa1c-4f30-8e88-c651a0e7a06d' but no matching script tag was found. \")\n",
" return false;\n",
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" var render_items = [{\"docid\":\"f60af008-a11a-4908-9eff-853f8e023384\",\"elementid\":\"050a046b-fa1c-4f30-8e88-c651a0e7a06d\",\"modelid\":\"b8129541-88d3-49ec-9dcd-2d7a47e1d086\"}];\n",
" \n",
" Bokeh.embed.embed_items(docs_json, render_items);\n",
" });\n",
" },\n",
" function(Bokeh) {\n",
" }\n",
" ];\n",
" \n",
" function run_inline_js() {\n",
" \n",
" if ((window.Bokeh !== undefined) || (force === \"1\")) {\n",
" for (var i = 0; i < inline_js.length; i++) {\n",
" inline_js[i](window.Bokeh);\n",
" }if (force === \"1\") {\n",
" display_loaded();\n",
" }} else if (Date.now() < window._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!window._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" window._bokeh_failed_load = true;\n",
" } else if (!force) {\n",
" var cell = $(\"#050a046b-fa1c-4f30-8e88-c651a0e7a06d\").parents('.cell').data().cell;\n",
" cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
" }\n",
" \n",
" }\n",
" \n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
" run_inline_js();\n",
" } else {\n",
" load_libs(js_urls, function() {\n",
" console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
" }(this));\n",
"</script>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from IPython.display import HTML, display\n",
"display(HTML(div))\n",
"#output_notebook()\n",
"#show(plot)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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