{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Themes\n", "\n", "Themes can be used to customize the appearance of Sankey diagrams. `sankee` contains a few built-in themes, but you can also create your own themes for additional control. Let's get started by setting up and initializing our packages." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import sankee\n", "import ee\n", "\n", "ee.Initialize()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## The Default Theme" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`sankee` includes a default theme it will use unless you specify one. To demonstrate, we'll look at urban expansion around Houston, Texas between 1986 and 2020." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d0994cf3e9e64dfd8e5b46bb96e85453", "version_major": 2, "version_minor": 0 }, "text/plain": [ "SankeyPlot()" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "aoi = ee.Geometry.Point([-95.78867372638199, 29.773539101705214]).buffer(30_000)\n", "sankee.datasets.LCMS_LU.sankify(\n", " years=[1986, 2020],\n", " region=aoi,\n", " n=100,\n", " title=\"Urban Expansion in Houston, TX\",\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Built-in Themes\n", "\n", "You can override the default theme using the `theme` argument to `sankify.` Using `theme=\"d3\"` will give us a similar appearance to a Sankey diagram from the [d3-sankey](https://github.com/d3/d3-sankey) library." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "df7523a6ed674f3684b43cc481992bc1", "version_major": 2, "version_minor": 0 }, "text/plain": [ "SankeyPlot()" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sankee.datasets.LCMS_LU.sankify(\n", " years=[1986, 2020],\n", " region=aoi,\n", " n=100,\n", " title=\"Urban Expansion in Houston, TX\",\n", " theme=\"d3\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Or we can use `theme=\"simple\"` to get a slightly more minimalist theme." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "28013a243b824fdcb529b3da6055b613", "version_major": 2, "version_minor": 0 }, "text/plain": [ "SankeyPlot()" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sankee.datasets.LCMS_LU.sankify(\n", " years=[1986, 2020],\n", " region=aoi,\n", " n=100,\n", " title=\"Urban Expansion in Houston, TX\",\n", " theme=\"simple\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Building a Custom Theme\n", "\n", "The `theme` argument accepts either the name of a built-in theme *or* a custom `sankee.themes.Theme` object. You can create your own `Theme` object to define a custom style. Let's try that." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Link and Node Arguments\n", "\n", "The first way we can modify a figure is by passing in keyword arguments for the link and node styles. We'll experiment by changing the `thickness` and `pad` between our nodes and the `link` colors. Check out the [Plotly documentation](https://plotly.com/python/sankey-diagram/) for more information." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "custom_theme = sankee.Theme(\n", " # We can set a custom link color to override the default. We'll choose a transparent bluish color.\n", " link_kwargs=dict(color=\"rgba(0, 180, 255, 0.1)\"),\n", " # Thickness sets the size of the node rectangles and pad sets the spacing between them. We can \n", " # also customize the border around nodes using the line argument.\n", " node_kwargs=dict(thickness=100, pad=100, line=dict(width=4, color=\"#628eb3\")),\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we'll apply our custom theme to our Sankey diagram." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "769b17bfa31f46e7b42b6742deaf6add", "version_major": 2, "version_minor": 0 }, "text/plain": [ "SankeyPlot()" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sankee.datasets.LCMS_LU.sankify(\n", " years=[1986, 2020],\n", " region=aoi,\n", " n=100,\n", " title=\"Urban Expansion in Houston, TX\",\n", " theme=custom_theme\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Title and Label Styles\n", "\n", "The other way to customize a theme is by specifying CSS properties to apply to the node labels and figure title. We'll add those to the theme parameters we defined above to finish our custom theme." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "label_style = \"\"\"\n", " font-style: italic;\n", " font-size: 18px;\n", " color: #4e6980;\n", " letter-spacing: 2px;\n", "\"\"\"\n", "\n", "title_style = \"\"\"\n", " font-size: 24px;\n", " font-weight: 900;\n", " font-variant: small-caps;\n", " color: #4e6980;\n", "\"\"\"\n", "\n", "custom_theme = sankee.Theme(\n", " link_kwargs=dict(color=\"rgba(0, 180, 255, 0.1)\"),\n", " node_kwargs=dict(thickness=100, pad=100, line=dict(width=4, color=\"#628eb3\")),\n", " label_style=label_style,\n", " title_style=title_style,\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The final product with our custom node, link, label, and title styles:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": 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