{
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   "source": [
    "# Tutorial 08 – Plotly Backend\n",
    "\n",
    "The **Plotly backend** renders your maxplotlib canvas as an interactive `plotly.graph_objects.Figure`. Unlike the default matplotlib output, Plotly figures:\n",
    "\n",
    "- Are **interactive** in Jupyter: zoom, pan, hover for values, toggle traces.\n",
    "- Can be **exported as standalone HTML** files that work in any browser—no Python or server required.\n",
    "- Support multi-subplot layouts.\n",
    "\n",
    "### When to use Plotly vs matplotlib\n",
    "\n",
    "| Use case | Backend |\n",
    "|---|---|\n",
    "| Quick static plot / publication PDF | `matplotlib` (default) |\n",
    "| Interactive exploration in Jupyter | `plotly` |\n",
    "| Share a self-contained interactive report | `plotly` → `fig.write_html(...)` |\n",
    "| LaTeX document figure | `tikzfigure` |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%matplotlib inline\n",
    "\n",
    "from maxplotlib import Canvas\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2",
   "metadata": {},
   "source": [
    "## Plotly in Jupyter\n",
    "\n",
    "In notebooks, you can either:\n",
    "\n",
    "- call `canvas.show(backend=\"plotly\")` (displays and returns a Plotly figure), or\n",
    "- call `fig = canvas.plot(backend=\"plotly\")` and put `fig` as the last line of a cell.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 2 * np.pi, 200)\n",
    "\n",
    "canvas = Canvas(width=\"10cm\", ratio=0.45)\n",
    "canvas.add_line(x, np.sin(x), color=\"steelblue\", label=\"sin(x)\")\n",
    "canvas.set_title(\"Displayed inline\")\n",
    "canvas.set_legend(True)\n",
    "\n",
    "fig = canvas.show(backend=\"plotly\")\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4",
   "metadata": {},
   "source": [
    "## 1 · Basic line plot\n",
    "\n",
    "Switch to the Plotly backend by passing `backend='plotly'` to `canvas.plot()`. The returned object is a genuine `plotly.graph_objects.Figure`, so every Plotly method is available on it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 2 * np.pi, 200)\n",
    "\n",
    "canvas = Canvas(width=\"10cm\", ratio=0.55)\n",
    "canvas.add_line(x, np.sin(x), color=\"steelblue\", label=\"sin(x)\")\n",
    "canvas.set_xlabel(\"x\")\n",
    "canvas.set_ylabel(\"y\")\n",
    "canvas.set_title(\"Basic line plot\")\n",
    "\n",
    "fig = canvas.show(backend=\"plotly\")\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6",
   "metadata": {},
   "source": [
    "## 2 · Multiple lines\n",
    "\n",
    "Each `ax.plot()` call becomes a separate Plotly trace. Enable the legend with `ax.set_legend(True)` so trace labels appear."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 2 * np.pi, 200)\n",
    "\n",
    "canvas = Canvas(width=\"10cm\", ratio=0.55)\n",
    "canvas.add_line(x, np.sin(x), color=\"steelblue\", label=\"sin(x)\", linewidth=2)\n",
    "canvas.add_line(x, np.cos(x), color=\"tomato\", label=\"cos(x)\", linewidth=2)\n",
    "canvas.add_line(\n",
    "    x,\n",
    "    np.sin(2 * x),\n",
    "    color=\"seagreen\",\n",
    "    label=\"sin(2x)\",\n",
    "    linewidth=2,\n",
    "    linestyle=\"dashed\",\n",
    ")\n",
    "\n",
    "canvas.set_xlabel(\"x\")\n",
    "canvas.set_ylabel(\"y\")\n",
    "canvas.set_title(\"Multiple lines\")\n",
    "canvas.set_legend(True)\n",
    "\n",
    "fig = canvas.show(backend=\"plotly\")\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8",
   "metadata": {},
   "source": [
    "## 3 · Scatter plot\n",
    "\n",
    "`ax.scatter()` maps to a Plotly scatter trace with markers only."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9",
   "metadata": {},
   "outputs": [],
   "source": [
    "rng = np.random.default_rng(42)\n",
    "n = 120\n",
    "x_data = rng.uniform(0, 10, n)\n",
    "y_data = 0.5 * x_data + rng.normal(0, 1, n)\n",
    "\n",
    "canvas = Canvas(width=\"10cm\", ratio=0.6)\n",
    "canvas.scatter(\n",
    "    x_data, y_data, color=\"steelblue\", marker=\"o\", s=20, label=\"observations\"\n",
    ")\n",
    "canvas.add_line(\n",
    "    [0, 10],\n",
    "    [0, 5],\n",
    "    color=\"tomato\",\n",
    "    linestyle=\"dashed\",\n",
    "    linewidth=2,\n",
    "    label=\"y = 0.5x\",\n",
    ")\n",
    "\n",
    "canvas.set_xlabel(\"x\")\n",
    "canvas.set_ylabel(\"y\")\n",
    "canvas.set_title(\"Scatter plot with trend line\")\n",
    "canvas.set_legend(True)\n",
    "\n",
    "fig = canvas.show(backend=\"plotly\")\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10",
   "metadata": {},
   "source": [
    "## 4 · Bar chart\n",
    "\n",
    "`ax.bar()` maps to a Plotly bar trace."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11",
   "metadata": {},
   "outputs": [],
   "source": [
    "categories = [\"Alpha\", \"Beta\", \"Gamma\", \"Delta\", \"Epsilon\"]\n",
    "values = [4.2, 7.1, 3.8, 5.9, 6.4]\n",
    "x_pos = np.arange(len(categories))\n",
    "\n",
    "canvas = Canvas(width=\"10cm\", ratio=0.6)\n",
    "canvas.bar(x_pos, values, color=\"steelblue\", label=\"metric\")\n",
    "canvas.set_xticks(x_pos, categories)\n",
    "\n",
    "canvas.set_xlabel(\"Category\")\n",
    "canvas.set_ylabel(\"Value\")\n",
    "canvas.set_title(\"Bar chart\")\n",
    "canvas.set_legend(True)\n",
    "\n",
    "fig = canvas.show(backend=\"plotly\")\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12",
   "metadata": {},
   "source": [
    "## 5 · Mixing lines and bars\n",
    "\n",
    "You can place multiple trace types on the same axes — Plotly handles the overlay automatically."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13",
   "metadata": {},
   "outputs": [],
   "source": [
    "months = np.arange(1, 13)\n",
    "rainfall = np.array([55, 48, 62, 70, 85, 40, 30, 35, 60, 90, 75, 65])\n",
    "cumulative = np.cumsum(rainfall)\n",
    "\n",
    "canvas = Canvas(width=\"10cm\", ratio=0.6)\n",
    "canvas.bar(\n",
    "    months, rainfall, color=\"steelblue\", alpha=0.7, label=\"monthly rainfall (mm)\"\n",
    ")\n",
    "canvas.add_line(\n",
    "    months,\n",
    "    cumulative / 10,\n",
    "    color=\"tomato\",\n",
    "    linewidth=2.5,\n",
    "    marker=\"o\",\n",
    "    label=\"cumulative / 10\",\n",
    ")\n",
    "\n",
    "canvas.set_xlabel(\"Month\")\n",
    "canvas.set_ylabel(\"Rainfall (mm)\")\n",
    "canvas.set_title(\"Monthly rainfall + cumulative trend\")\n",
    "canvas.set_legend(True)\n",
    "\n",
    "fig = canvas.show(backend=\"plotly\")\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14",
   "metadata": {},
   "source": [
    "## 6 · Multiple subplots\n",
    "\n",
    "Multi-subplot canvases are fully supported. Each panel gets its own axis labels and title; `canvas.suptitle(...)` sets the figure-level title."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 2 * np.pi, 200)\n",
    "rng = np.random.default_rng(0)\n",
    "\n",
    "canvas = Canvas(ncols=1)  # , width=\"14cm\", ratio=0.35)\n",
    "\n",
    "# Left panel — line plot\n",
    "canvas.add_line(x, np.sin(x), color=\"steelblue\", label=\"sin(x)\", linewidth=2, col=0)\n",
    "canvas.add_line(x, np.cos(x), color=\"tomato\", label=\"cos(x)\", linewidth=2, col=0)\n",
    "canvas.set_xlabel(\"x\", col=0)\n",
    "canvas.set_ylabel(\"y\", col=0)\n",
    "canvas.set_title(\"Trigonometric functions\", col=0)\n",
    "canvas.set_legend(True, col=0)\n",
    "\n",
    "# Right panel — scatter\n",
    "x_s = rng.uniform(0, 6, 80)\n",
    "y_s = np.sin(x_s) + rng.normal(0, 0.15, 80)\n",
    "canvas.scatter(x_s, y_s, color=\"seagreen\", marker=\"o\", s=18, label=\"noisy sin\", col=1)\n",
    "canvas.add_line(\n",
    "    x,\n",
    "    np.sin(x),\n",
    "    color=\"black\",\n",
    "    linestyle=\"dashed\",\n",
    "    linewidth=1.5,\n",
    "    label=\"true sin\",\n",
    "    col=1,\n",
    ")\n",
    "canvas.set_xlabel(\"x\", col=1)\n",
    "canvas.set_ylabel(\"y\", col=1)\n",
    "canvas.set_title(\"Noisy observations\", col=1)\n",
    "canvas.set_legend(True, col=1)\n",
    "\n",
    "canvas.suptitle(\"Multi-panel Plotly figure\")\n",
    "\n",
    "fig = canvas.show(backend=\"plotly\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16",
   "metadata": {},
   "source": [
    "## 7 · Log scale\n",
    "\n",
    "`ax.set_yscale('log')` is passed through to Plotly's axis type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "17",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0.1, 5, 200)\n",
    "\n",
    "canvas = Canvas(width=\"10cm\", ratio=0.55)\n",
    "canvas.add_line(x, np.exp(x), color=\"steelblue\", label=\"exp(x)\", linewidth=2)\n",
    "canvas.add_line(x, np.exp(1.5 * x), color=\"tomato\", label=\"exp(1.5x)\", linewidth=2)\n",
    "canvas.add_line(x, x**2, color=\"seagreen\", label=\"x²\", linewidth=2)\n",
    "\n",
    "canvas.set_xlabel(\"x\")\n",
    "canvas.set_ylabel(\"y  (log scale)\")\n",
    "canvas.set_title(\"Log-scale y axis\")\n",
    "canvas.set_yscale(\"log\")\n",
    "canvas.set_legend(True)\n",
    "\n",
    "fig = canvas.show(backend=\"plotly\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18",
   "metadata": {},
   "source": [
    "## 8 · Saving to HTML\n",
    "\n",
    "`fig.write_html()` saves a fully self-contained HTML file. The file works in any browser without Python, Plotly, or a running server — ideal for sharing interactive figures with colleagues."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "19",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 2 * np.pi, 200)\n",
    "\n",
    "canvas = Canvas(width=\"10cm\", ratio=0.55)\n",
    "canvas.add_line(x, np.sin(x), color=\"steelblue\", label=\"sin(x)\", linewidth=2)\n",
    "canvas.add_line(x, np.cos(x), color=\"tomato\", label=\"cos(x)\", linewidth=2)\n",
    "canvas.set_xlabel(\"x\")\n",
    "canvas.set_ylabel(\"y\")\n",
    "canvas.set_title(\"Saved interactive figure\")\n",
    "canvas.set_legend(True)\n",
    "\n",
    "# Writes a standalone HTML file — open it in any browser\n",
    "canvas.savefig(\"output.html\", backend=\"plotly\")\n",
    "print(\"Saved to output.html\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "### Plotly backend feature table\n",
    "\n",
    "| Feature | Supported | Notes |\n",
    "|---|---|---|\n",
    "| `ax.plot()` — line trace | ✅ | `color`, `linestyle`, `linewidth`, `marker` all passed through |\n",
    "| `ax.scatter()` — markers | ✅ | `color`, `marker`, `s`, `alpha` |\n",
    "| `ax.bar()` — bar chart | ✅ | `color`, `alpha` |\n",
    "| `ax.fill_between()` | ❌ | Not supported by this backend |\n",
    "| `ax.errorbar()` | ❌ | Not supported by this backend |\n",
    "| `ax.axhline/axvline` | ❌ | Not supported by this backend |\n",
    "| Multi-subplot canvas | ✅ | `Canvas.subplots(ncols=...)` etc. |\n",
    "| `canvas.suptitle()` | ✅ | Maps to figure title |\n",
    "| `ax.set_yscale('log')` | ✅ | |\n",
    "| `ax.set_legend(True)` | ✅ | |\n",
    "| `fig.show()` | ✅ | Interactive in Jupyter |\n",
    "| `fig.write_html(path)` | ✅ | Standalone interactive HTML |\n",
    "\n",
    "### Typical workflow\n",
    "\n",
    "```python\n",
    "from maxplotlib import Canvas\n",
    "import numpy as np\n",
    "\n",
    "canvas, ax = Canvas.subplots()\n",
    "ax.plot(x, y, label='data')\n",
    "ax.set_legend(True)\n",
    "\n",
    "fig = canvas.plot(backend='plotly')   # → plotly.graph_objects.Figure\n",
    "fig.show()                            # interactive in Jupyter\n",
    "fig.write_html('report.html')         # share with anyone\n",
    "```"
   ]
  }
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