Another notebook for generating a legend figure from labels and colors

make_legend2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_colortable(name_to_color: dict, title: str, sort_colors: bool = False, emptycols: int = 0) -> plt.Figure:\n",
    "    \"\"\"\n",
    "    function taken from https://matplotlib.org/3.1.0/gallery/color/named_colors.html\n",
    "    \"\"\"\n",
    "\n",
    "    cell_width = 212\n",
    "    cell_height = 22\n",
    "    swatch_width = 70\n",
    "    margin = 12\n",
    "    topmargin = 40\n",
    "\n",
    "    # Sort name_to_color by hue, saturation, value and name.\n",
    "    if sort_colors is True:\n",
    "        by_hsv = sorted((tuple(mcolors.rgb_to_hsv(mcolors.to_rgb(color))),\n",
    "                         name)\n",
    "                        for name, color in name_to_color.items())\n",
    "        names = [name for hsv, name in by_hsv]\n",
    "    else:\n",
    "        names = list(name_to_color)\n",
    "\n",
    "    n = len(names)\n",
    "    ncols = 4 - emptycols\n",
    "    nrows = n // ncols + int(n % ncols > 0)\n",
    "\n",
    "    width = cell_width * 4 + 2 * margin\n",
    "    height = cell_height * nrows + margin + topmargin\n",
    "    dpi = 80  # other numbers don't seem to work well\n",
    "\n",
    "    fig, ax = plt.subplots(figsize=(width / dpi, height / dpi), dpi=dpi, facecolor=\"white\")\n",
    "    fig.subplots_adjust(margin / width, margin / height,\n",
    "                        (width - margin) / width, (height - topmargin) / height)\n",
    "    ax.set_xlim(0, cell_width * 4)\n",
    "    ax.set_ylim(cell_height * (nrows - 0.5), -cell_height / 2.)\n",
    "    ax.yaxis.set_visible(False)\n",
    "    ax.xaxis.set_visible(False)\n",
    "    ax.set_axis_off()\n",
    "    ax.set_title(title, fontsize=24, loc='left', pad=10)\n",
    "\n",
    "    for i, name in enumerate(names):\n",
    "        row = i % nrows\n",
    "        col = i // nrows\n",
    "        y = row * cell_height\n",
    "\n",
    "        swatch_start_x = cell_width * col\n",
    "        swatch_end_x = cell_width * col + swatch_width\n",
    "        text_pos_x = cell_width * col + swatch_width + 7\n",
    "\n",
    "        ax.text(text_pos_x, y, name, fontsize=14,\n",
    "                horizontalalignment='left',\n",
    "                verticalalignment='center')\n",
    "\n",
    "        ax.hlines(y, swatch_start_x, swatch_end_x,\n",
    "                  color=name_to_color[name], linewidth=18)\n",
    "\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 872x74 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plot_colortable(\n",
    "    {\"Poultry House\": \"red\"},\n",
    "    \"Legend\"\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "cafo",
   "language": "python",
   "name": "conda-env-cafo-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}