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- {
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "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": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3.6 + datashader",
- "language": "python",
- "name": "datashader"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.6.1"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
- }
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