{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Title**: HeatMap Tap stream example\n", "\n", "**Description**: A linked streams example demonstrating how use Tap stream on a HeatMap. The data contains the incidence of measles across US states by year and week (obtained from [Project Tycho](http://www.tycho.pitt.edu)). The HeatMap represents the mean measles incidence per year. On tap the Histogram on the right will generate a Histogram of the incidences for each week in the selected year and state.\n", " \n", "**Dependencies**: Bokeh\n", "\n", "**Backends**: [Bokeh](./Tap.ipynb)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import panel as pn\n", "import numpy as np\n", "import holoviews as hv\n", "from holoviews import opts\n", "\n", "hv.extension('bokeh', width=90)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, let's look at an extremely simple example. \n", "\n", "We will create an empty `hv.Points` element and set it as the source for the `Tap` stream. " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Create an empty Points element\n", "points = hv.Points([])\n", "# Create the Tap stream with the points element as the source\n", "# We set the x and y here with starting values\n", "stream = hv.streams.Tap(source=points, x=np.nan, y=np.nan)\n", "\n", "# Create a callback for a dynamic map\n", "def location(x, y):\n", " \"\"\"Create an empty plot with a changing label\"\"\"\n", " return hv.Points([], label='x: %0.3f, y: %0.3f' % (x, y))\n", "\n", "\n", "# Connect the Tap stream to the tap_histogram callback\n", "tap_dmap = hv.DynamicMap(location, streams=[stream])\n", "\n", "# Overlay the Points element (which is linked to the tap stream) with the location plot\n", "points * tap_dmap" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's see what it looks like if we used Panel to give us more control over layout and event triggering" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# create an empty Points element\n", "points = hv.Points([])\n", "# Create the Tap stream with the points element as the source\n", "# We set the x and y here with starting values\n", "stream = hv.streams.Tap(source=points, x=np.nan, y=np.nan)\n", "\n", "# make a function that displays the location when called.\n", "def location(x, y):\n", " \"\"\"Display pane showing the x and y values\"\"\"\n", " return pn.pane.Str('Click at %0.3f, %0.3f' % (x, y), width=200)\n", "\n", "# Display the points and the function output, updated\n", "# whenever the stream values change\n", "layout = pn.Row(points, pn.bind(location, x=stream.param.x, y=stream.param.y))\n", "# display the container\n", "layout" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, we will now look at a more complex example." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Declare dataset\n", "df = pd.read_csv('http://assets.holoviews.org/data/diseases.csv.gz', compression='gzip')\n", "dataset = hv.Dataset(df, vdims=('measles','Measles Incidence'))\n", "\n", "# Declare HeatMap\n", "heatmap = hv.HeatMap(dataset.aggregate(['Year', 'State'], np.mean),\n", " label='Average Weekly Measles Incidence').select(Year=(1928, 2002))\n", "\n", "# Declare Tap stream with heatmap as source and initial values\n", "posxy = hv.streams.Tap(source=heatmap, x=1951, y='New York')\n", "\n", "# Define function to compute histogram based on tap location\n", "def tap_histogram(x, y):\n", " return hv.Curve(dataset.select(State=y, Year=int(x)), kdims='Week',\n", " label=f'Year: {x}, State: {y}')\n", "\n", "# Connect the Tap stream to the tap_histogram callback\n", "tap_dmap = hv.DynamicMap(tap_histogram, streams=[posxy])\n", "\n", "# Get the range of the aggregated data we're using for plotting\n", "cmin, cmax = dataset.aggregate(['Year', 'State'], np.mean).range(dim='measles')\n", "# Adjust the min value since log color mapper lower bound must be >0.0\n", "cmin += 0.0000001\n", "\n", "# Display the Heatmap and Curve side by side\n", "(heatmap + tap_dmap).opts(\n", " opts.Curve(framewise=True, height=500, line_color='black', width=375, yaxis='right'),\n", " opts.HeatMap(clim=(cmin, cmax), cmap='RdBu_r', \n", " fontsize={'xticks': '6pt'}, height=500, logz=True,\n", " tools=['hover'], width=700, xrotation=90,\n", " )\n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
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