{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0",
   "metadata": {},
   "source": [
    "# Tutorial 13 – Advanced Matplotlib Plotting\n",
    "\n",
    "# Advanced Matplotlib plotting\n",
    "\n",
    "This tutorial covers horizontal bars, histograms, filled regions,\n",
    "reference spans, arrows, infinitely extending lines, and secondary\n",
    "y-axes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from maxplotlib import Canvas\n",
    "\n",
    "x = np.linspace(0, 2 * np.pi, 200)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2",
   "metadata": {},
   "source": [
    "## Common plotting primitives"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3",
   "metadata": {},
   "outputs": [],
   "source": [
    "canvas = Canvas(width=\"12cm\", ratio=0.65)\n",
    "canvas.barh([0, 1, 2], [2, 4, 3], color=\"steelblue\", alpha=0.8)\n",
    "canvas.set_yticks([0, 1, 2], labels=[\"A\", \"B\", \"C\"])\n",
    "canvas.set_xlabel(\"Amount\")\n",
    "canvas.set_title(\"Horizontal bars\")\n",
    "canvas.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4",
   "metadata": {},
   "outputs": [],
   "source": [
    "samples = np.random.default_rng(4).normal(size=1000)\n",
    "canvas = Canvas()\n",
    "canvas.hist(samples, bins=30, color=\"slateblue\", alpha=0.75)\n",
    "canvas.set_xlabel(\"Value\")\n",
    "canvas.set_ylabel(\"Count\")\n",
    "canvas.set_title(\"Distribution\")\n",
    "canvas.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5",
   "metadata": {},
   "source": [
    "## Steps, stairs, broken bars, and pie charts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6",
   "metadata": {},
   "outputs": [],
   "source": [
    "canvas = Canvas()\n",
    "canvas.step([0, 1, 2, 3], [1, 3, 2, 4], where=\"mid\", label=\"step\")\n",
    "canvas.stairs([1, 2, 1], edges=[0, 1, 2, 3], color=\"purple\", label=\"stairs\")\n",
    "canvas.set_title(\"Discrete data\")\n",
    "canvas.set_legend(True)\n",
    "canvas.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7",
   "metadata": {},
   "outputs": [],
   "source": [
    "canvas = Canvas()\n",
    "canvas.broken_barh([(0, 1), (1.5, 0.75), (2.75, 1.0)], (0, 0.6), color=\"orange\")\n",
    "canvas.set_xlabel(\"Intervals\")\n",
    "canvas.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8",
   "metadata": {},
   "outputs": [],
   "source": [
    "canvas = Canvas()\n",
    "canvas.pie([30, 45, 25], labels=[\"A\", \"B\", \"C\"], autopct=\"%1.0f%%\")\n",
    "canvas.set_title(\"Shares\")\n",
    "canvas.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9",
   "metadata": {},
   "source": [
    "## Regions, arrows, and reference lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10",
   "metadata": {},
   "outputs": [],
   "source": [
    "canvas = Canvas()\n",
    "canvas.plot(x, np.sin(x), color=\"black\")\n",
    "canvas.fill_betweenx([-1, 0, 1], 0.5, [1.0, 1.5, 2.0], alpha=0.2)\n",
    "canvas.axvspan(1.0, 2.0, color=\"orange\", alpha=0.2)\n",
    "canvas.axhspan(-0.25, 0.25, color=\"steelblue\", alpha=0.15)\n",
    "canvas.arrow(2.0, np.sin(2.0), 0.5, 0.3, length_includes_head=True)\n",
    "canvas.axline((0, 0), slope=0.2, linestyle=\"--\", color=\"crimson\")\n",
    "canvas.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11",
   "metadata": {},
   "source": [
    "## Secondary y-axis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12",
   "metadata": {},
   "outputs": [],
   "source": [
    "twin_canvas, primary = Canvas.subplots()\n",
    "secondary = twin_canvas.twinx()\n",
    "\n",
    "primary.plot(x, np.sin(x), color=\"tab:blue\")\n",
    "secondary.plot(x, 100 * np.cos(x), color=\"tab:red\")\n",
    "primary.set_xlabel(\"Time\")\n",
    "primary.set_ylabel(\"sin(x)\", color=\"tab:blue\")\n",
    "secondary.set_ylabel(\"100 cos(x)\", color=\"tab:red\")\n",
    "twin_canvas.set_title(\"Two scales sharing one x-axis\")\n",
    "twin_canvas.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13",
   "metadata": {},
   "source": [
    "Secondary y-axes are supported by the Matplotlib and Plotly backends.\n",
    "The plotext and TikZ backends currently reject a canvas containing\n",
    "`twinx()` plots instead of silently producing an incorrect figure.\n",
    "\n",
    "## Scientific field plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(-1, 1, 40)\n",
    "y = np.linspace(-1, 1, 40)\n",
    "xx, yy = np.meshgrid(x, y)\n",
    "z = xx**2 + yy**2\n",
    "\n",
    "canvas = Canvas()\n",
    "canvas.contour(x, y, z, colors=\"black\")\n",
    "canvas.contourf(x, y, z, alpha=0.5)\n",
    "canvas.pcolormesh(x, y, z, alpha=0.25)\n",
    "canvas.set_title(\"Scalar field\")\n",
    "canvas.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15",
   "metadata": {},
   "source": [
    "For point-density data and matrix-oriented displays:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "16",
   "metadata": {},
   "outputs": [],
   "source": [
    "canvas = Canvas()\n",
    "canvas.hexbin(xx.ravel(), yy.ravel(), gridsize=12)\n",
    "canvas.matshow(z)\n",
    "canvas.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17",
   "metadata": {},
   "source": [
    "Unstructured triangular data and vector fields are also supported:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18",
   "metadata": {},
   "outputs": [],
   "source": [
    "points_x = np.array([0.0, 1.0, 0.0, 1.0])\n",
    "points_y = np.array([0.0, 0.0, 1.0, 1.0])\n",
    "triangles = [[0, 1, 2], [1, 3, 2]]\n",
    "values = points_x + points_y\n",
    "\n",
    "canvas = Canvas()\n",
    "canvas.quiver(points_x, points_y, np.ones(4), np.ones(4))\n",
    "canvas.triplot(points_x, points_y, triangles=triangles)\n",
    "canvas.tripcolor(points_x, points_y, values, triangles=triangles, alpha=0.3)\n",
    "canvas.tricontour(points_x, points_y, values, triangles=triangles)\n",
    "canvas.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19",
   "metadata": {},
   "source": [
    "## Statistical and event plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20",
   "metadata": {},
   "outputs": [],
   "source": [
    "canvas = Canvas()\n",
    "canvas.stem([0, 1, 2], [1, 3, 2])\n",
    "canvas.stackplot([0, 1, 2], [1, 2, 1], [2, 1, 2], alpha=0.4)\n",
    "canvas.set_title(\"Discrete and stacked data\")\n",
    "canvas.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21",
   "metadata": {},
   "outputs": [],
   "source": [
    "canvas = Canvas()\n",
    "canvas.boxplot([[1, 2, 3], [2, 4, 5]])\n",
    "canvas.violinplot([[1, 2, 3], [2, 4, 5]])\n",
    "canvas.eventplot([[0.2, 0.5], [1.0, 1.5]])\n",
    "canvas.show()"
   ]
  }
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