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.readme.md

Bokeh in Jupyter notebooks

The output_notebook uses the INLINE method to load the Javascript and CSS libraries for Bokeh. The INLINE resource allows a Bokeh plot to be rendered without an internet connection.

Alternatively, the CDN resource can be used if an internet connection is available.

The INLINE resource is too large to render on Github Gists thereby limiting the online editting abilities of the gist.

Comparision of resources

Notebook Version File Size
INLINE 1713034
CDN 210484

Importing with INLINE

from bokeh.io import output_notebook
output_notebook()

Importing with CDN

from bokeh.io import output_notebook
from bokeh.resources import CDN
output_notebook(resources=CDN)

Grapefruit

GrapeFruit is a pure Python module that let you easily manipulate and convert color information. Its Primary goal is to be natural and flexible.

The original version is Python 2.

Display the source blob
Display the rendered blob
Raw
ColorStudyGrapefruit.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" <link rel=\"stylesheet\" href=\"http://cdn.pydata.org/bokeh/release/bokeh-0.9.1.min.css\" type=\"text/css\" />\n",
" <script type=\"text/javascript\" src=\"http://cdn.pydata.org/bokeh/release/bokeh-0.9.1.min.js\"></script>\n",
" <script type=\"text/javascript\">\n",
" Bokeh.set_log_level(\"info\");\n",
" </script>\n",
" <div>\n",
" <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
" <span>BokehJS successfully loaded.</span>\n",
" </div>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from bokeh.io import output_notebook\n",
"from bokeh.resources import CDN\n",
"from bokeh.plotting import figure, show\n",
"output_notebook(resources=CDN)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import grapefruit\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"colorHsv = grapefruit.Color.NewFromHtml('#B3DE69').hsv"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
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"<script type=\"text/javascript\">\n",
" Bokeh.$(function() {\n",
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" Bokeh.load_models(all_models);\n",
" var plots = [{'modelid': '094db858-bc88-4c99-93e7-5a8e604ad189', 'elementid': '#9a66054c-4cd2-4b30-be04-2cac792c23dc', 'modeltype': 'Plot'}];\n",
" for (idx in plots) {\n",
" \tvar plot = plots[idx];\n",
" \tvar model = Bokeh.Collections(plot.modeltype).get(plot.modelid);\n",
" \tBokeh.logger.info('Realizing plot:')\n",
" \tBokeh.logger.info(' - modeltype: ' + plot.modeltype);\n",
" \tBokeh.logger.info(' - modelid: ' + plot.modelid);\n",
" \tBokeh.logger.info(' - elementid: ' + plot.elementid);\n",
" \tvar view = new model.default_view({\n",
" \t\tmodel: model,\n",
" \t\tel: plot.elementid\n",
" \t});\n",
" \tBokeh.index[plot.modelid] = view;\n",
" }\n",
" });\n",
" </script>\n",
"<div class=\"plotdiv\" id=\"9a66054c-4cd2-4b30-be04-2cac792c23dc\"></div>\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"p = figure(width=400, height=400,\n",
" x_axis_label = \"Saturation\",\n",
" y_axis_label = \"Value\",\n",
" title='HSV Study'\n",
" )\n",
"inc = 10\n",
"Steps = np.linspace(0,1,inc)\n",
"dSteps = np.diff(Steps).mean()\n",
"for (xindex,saturation) in enumerate(Steps):\n",
" for (yindex,value) in enumerate(Steps):\n",
" colorPlot = grapefruit.Color.HsvToRgb(\n",
" colorHsv[0],\n",
" saturation,\n",
" value\n",
" )\n",
" p.rect(\n",
" x=[saturation], \n",
" y=[value], \n",
" width=dSteps, \n",
" height=dSteps, \n",
" color=grapefruit.Color.RgbToHtml(colorPlot[0],colorPlot[1],colorPlot[2],) )\n",
"\n",
"show(p)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"colorHsl = grapefruit.Color.NewFromHtml('#B3DE69').hsl"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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"<script type=\"text/javascript\">\n",
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" Bokeh.load_models(all_models);\n",
" var plots = [{'modelid': '36cca86d-2ab7-4d19-9122-1edc19282a63', 'elementid': '#5fd2fc0b-c6db-4f10-8725-5635241e6799', 'modeltype': 'Plot'}];\n",
" for (idx in plots) {\n",
" \tvar plot = plots[idx];\n",
" \tvar model = Bokeh.Collections(plot.modeltype).get(plot.modelid);\n",
" \tBokeh.logger.info('Realizing plot:')\n",
" \tBokeh.logger.info(' - modeltype: ' + plot.modeltype);\n",
" \tBokeh.logger.info(' - modelid: ' + plot.modelid);\n",
" \tBokeh.logger.info(' - elementid: ' + plot.elementid);\n",
" \tvar view = new model.default_view({\n",
" \t\tmodel: model,\n",
" \t\tel: plot.elementid\n",
" \t});\n",
" \tBokeh.index[plot.modelid] = view;\n",
" }\n",
" });\n",
" </script>\n",
"<div class=\"plotdiv\" id=\"5fd2fc0b-c6db-4f10-8725-5635241e6799\"></div>\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"p = figure(width=400, height=400,\n",
" x_axis_label = \"Saturation\",\n",
" y_axis_label = \"Lightness\",\n",
" title='HSL Study'\n",
" )\n",
"inc = 10\n",
"Steps = np.linspace(0,1,inc)\n",
"dSteps = np.diff(Steps).mean()\n",
"for (xindex,saturation) in enumerate(Steps):\n",
" for (yindex,lightness) in enumerate(Steps):\n",
" colorPlot = grapefruit.Color.HslToRgb(\n",
" colorHsv[0],\n",
" saturation,\n",
" lightness\n",
" )\n",
" p.rect(\n",
" x=[saturation], \n",
" y=[lightness], \n",
" width=dSteps, \n",
" height=dSteps, \n",
" color=grapefruit.Color.RgbToHtml(colorPlot[0],colorPlot[1],colorPlot[2],) )\n",
"\n",
"show(p)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
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