Simple DataShader interactive demo with no external datasets

DataShaderDemo.ipynb

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 "cells": [
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   "source": [
    "*Installation*\n",
    "\n",
    "```\n",
    "conda install -c bokeh datashader\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datashader as ds\n",
    "import datashader.transfer_functions as tf\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.random.randn(10000000)\n",
    "y = np.sin(5 * x) + np.cos(6 * x) + 0.1 * np.random.randn(len(x))\n",
    "z = x ** 2 + y ** 2\n",
    "df = pd.DataFrame({'x': x, 'y': y, 'z':z})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cvs = ds.Canvas(plot_width=400, plot_height=400)\n",
    "agg = cvs.points(df, 'x', 'y')#, ds.mean('z'))\n",
    "tf.shade(agg, cmap=['lightblue', 'darkblue'], how='log')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.models import BoxZoomTool\n",
    "from bokeh.plotting import figure, output_notebook, show\n",
    "\n",
    "output_notebook()\n",
    "\n",
    "x_range = (-5, 5)\n",
    "y_range = (-5, 5)\n",
    "\n",
    "plot_width  = int(750)\n",
    "plot_height = int(plot_width//1.2)\n",
    "\n",
    "def base_plot(tools='pan,wheel_zoom,reset',plot_width=plot_width, plot_height=plot_height, **plot_args):\n",
    "    p = figure(tools=tools, plot_width=plot_width, plot_height=plot_height,\n",
    "        x_range=x_range, y_range=y_range, outline_line_color=None,\n",
    "        min_border=0, min_border_left=0, min_border_right=0,\n",
    "        min_border_top=0, min_border_bottom=0, **plot_args)\n",
    "    \n",
    "    p.axis.visible = False\n",
    "    p.xgrid.grid_line_color = None\n",
    "    p.ygrid.grid_line_color = None\n",
    "    \n",
    "    p.add_tools(BoxZoomTool(match_aspect=True))\n",
    "    \n",
    "    return p\n",
    "    \n",
    "options = dict(line_color=None, fill_color='blue', size=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "samples = df.sample(n=1000)\n",
    "p = base_plot()\n",
    "p.circle(x=samples['x'], y=samples['y'], **options)\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import datashader as ds\n",
    "from datashader import transfer_functions as tf\n",
    "from datashader.colors import Greys9\n",
    "Greys9_r = list(reversed(Greys9))[:-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cvs = ds.Canvas(plot_width=plot_width, plot_height=plot_height, x_range=x_range, y_range=y_range)\n",
    "agg = cvs.points(df, 'x', 'y',  ds.count('z'))\n",
    "tf.shade(agg, cmap=[\"white\", 'darkblue'], how='linear')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datashader as ds\n",
    "from datashader.bokeh_ext import InteractiveImage\n",
    "from functools import partial\n",
    "from datashader.utils import export_image\n",
    "from datashader.colors import colormap_select, Greys9, Hot, viridis, inferno\n",
    "from IPython.core.display import HTML, display\n",
    "\n",
    "background = \"black\"\n",
    "export = partial(export_image, export_path=\"export\", background=background)\n",
    "cm = partial(colormap_select, reverse=(background==\"black\"))\n",
    "\n",
    "def create_image(x_range, y_range, w=plot_width, h=plot_height):\n",
    "    cvs = ds.Canvas(plot_width=w, plot_height=h, x_range=x_range, y_range=y_range)\n",
    "    agg = cvs.points(df, 'x', 'y',  ds.count('z'))\n",
    "    img = tf.shade(agg, cmap=Hot, how='eq_hist')\n",
    "    return tf.dynspread(img, threshold=0.5, max_px=4)\n",
    "\n",
    "p = base_plot(background_fill_color=background)\n",
    "export(create_image(x_range, y_range),\"NYCT_hot\")\n",
    "InteractiveImage(p, create_image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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