{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3e0ec8fe",
   "metadata": {
    "id": "3e0ec8fe"
   },
   "source": [
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MeiraDavidson/math_module2/blob/main/notebooks/ch11_fundamental_theorem.ipynb)\n\n",
    "# Chapter 11 — Companion Notebook\n",
    "## The Fundamental Theorem of Calculus\n",
    "*why finding an area is the same as undoing a derivative — the summit of the book*\n",
    "\n",
    "Four live pictures of the chapter's one idea and its payoff: slide the right edge of an area and watch its growth rate land exactly on the curve (Part 1); turn a definite integral into a single subtraction $F(b)-F(a)$ (Part 2); run the product rule backward with integration by parts; and, as the book's final act, watch $\\ln x$ appear as the area under $1/t$ and find $e$ as the place that area first hits $1$.\n",
    "\n",
    "> **How to use this notebook.** Run every cell from the top (Shift+Enter). Each widget below is live — drag the sliders and watch the picture respond. Requires `ipywidgets` and `matplotlib`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "05309897",
   "metadata": {
    "id": "05309897",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1782336287054,
     "user_tz": 240,
     "elapsed": 26,
     "user": {
      "displayName": "Meira Davidson",
      "userId": "09448014842742744623"
     }
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import animation\n",
    "from ipywidgets import (interact, interactive, fixed, Dropdown, Checkbox,\n",
    "                        Button, Output, VBox, HBox,\n",
    "                        FloatSlider, IntSlider, FloatLogSlider)\n",
    "from IPython.display import HTML, display, Markdown\n",
    "\n",
    "# Book 2 palette — matches the printed figures in figures/png/\n",
    "BLUE=\"#1f4e79\"; RED=\"#c0392b\"; GREEN=\"#2e8b57\"; ORANGE=\"#e08e0b\"\n",
    "PURPLE=\"#6c3483\"; TEAL=\"#1b9e9e\"; GRAY=\"#7f8c8d\"; DARK=\"#2c3e50\"\n",
    "SHADE=\"#9fc5e8\"; SHADE2=\"#f4b6ad\"; SHADEG=\"#a9dfbf\"; LIGHT=\"#d6dbdf\"\n",
    "\n",
    "plt.rcParams.update({\n",
    "    \"figure.figsize\": (7.2, 4.5), \"figure.dpi\": 96,\n",
    "    \"font.family\": \"serif\", \"mathtext.fontset\": \"cm\", \"font.size\": 12,\n",
    "    \"axes.spines.top\": False, \"axes.spines.right\": False,\n",
    "    \"axes.grid\": True, \"grid.color\": LIGHT, \"grid.linewidth\": 0.7,\n",
    "    \"lines.linewidth\": 2.2, \"lines.solid_capstyle\": \"round\",\n",
    "})\n",
    "\n",
    "def axes(ax=None, title=None):\n",
    "    '''A clean axes with a light grid; returns the axes.'''\n",
    "    if ax is None:\n",
    "        _, ax = plt.subplots()\n",
    "    if title:\n",
    "        ax.set_title(title, color=DARK)\n",
    "    return ax\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd7d10b7",
   "metadata": {
    "id": "cd7d10b7"
   },
   "source": [
    "## 1. The moving edge — FTC Part 1\n",
    "\n",
    "Fix the left edge at $a$ and let the **right edge** $x$ slide. Define the *area-so-far function*\n",
    "\n",
    "$$A(x) = \\int_a^x f(t)\\,dt,$$\n",
    "\n",
    "the signed area under $f$ from $a$ out to $x$. The whole theorem is the answer to one question: *how fast does this area grow as $x$ moves right?* Push the edge out by a sliver $h$ and the area gains a thin strip of width $h$ and height about $f(x)$ — so the growth rate is the height of the curve. In symbols, **Part 1**:\n",
    "\n",
    "$$A'(x) = f(x).$$\n",
    "\n",
    "Pick a curve and drag $x$. The **top** panel shades $A(x)$ in green and shows the strip being added at the right edge. The **bottom** panel plots the accumulated area $A(x)$ in red, and overlays its *numerical* derivative $A'(x)$ as a green dashed line — watch it land exactly on the blue dot $f(x)$. The Fundamental Theorem, seen live — *(Figure 11.1)*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "17fa7c4d",
   "metadata": {
    "id": "17fa7c4d",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1782336295286,
     "user_tz": 240,
     "elapsed": 832,
     "user": {
      "displayName": "Meira Davidson",
      "userId": "09448014842742744623"
     }
    },
    "outputId": "2c554df4-5878-4036-c49b-f762c863352e",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 752,
     "referenced_widgets": [
      "280e8400d2414dc2a82ca16136e17d90",
      "e5e5c7eb437e41a0bed1613b68244d4e",
      "9f7ebc24f1ea49fc80602b79d8c6a450",
      "ee2d96c8e74f49f4a0cbb27d3b92d3eb",
      "6d2e349d43844b2294815b32d9db7d9c",
      "7c1e4feafa1a42aebe4ce5c546e411ad",
      "b6e55544a05a46528199542264c6c06c",
      "2da8737122ec41bfb517186893465551",
      "d46fe7db2995467b97001d5770bb41e6",
      "84691fe959d44ccda74bf22f5141a0e1"
     ]
    }
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "interactive(children=(Dropdown(description='curve', options=('f(t) = sin(t) + 1.5', 'f(t) = t^2', 'f(t) = 0.5 …"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "280e8400d2414dc2a82ca16136e17d90"
      }
     },
     "metadata": {}
    }
   ],
   "source": [
    "_CURVES1 = {\n",
    "    'f(t) = sin(t) + 1.5':   (lambda t: np.sin(t) + 1.5,  0.0, 6.2),\n",
    "    'f(t) = t^2':            (lambda t: t**2,             0.0, 2.4),\n",
    "    'f(t) = 0.5 t + 0.5':    (lambda t: 0.5*t + 0.5,      0.0, 4.0),\n",
    "    'f(t) = e^{t/3}':        (lambda t: np.exp(t/3),      0.0, 4.0),\n",
    "    'f(t) = 4 - (t-2)^2':    (lambda t: 4 - (t-2)**2,     0.0, 4.0),\n",
    "}\n",
    "\n",
    "def _area_to(f, a, x, n=600):\n",
    "    '''Numerical signed area A(x) = int_a^x f, via the trapezoid rule.'''\n",
    "    if x <= a:\n",
    "        return 0.0\n",
    "    ts = np.linspace(a, x, n)\n",
    "    return float(np.trapz(f(ts), ts))\n",
    "\n",
    "def _moving_edge(curve='f(t) = sin(t) + 1.5', x=3.0):\n",
    "    f, a, b = _CURVES1[curve]\n",
    "    x = min(max(x, a + 0.05), b)            # keep x inside [a, b]\n",
    "\n",
    "    fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(7.2, 6.8),\n",
    "                                   sharex=True)\n",
    "    ts = np.linspace(a, b, 600)\n",
    "    ys = f(ts)\n",
    "\n",
    "    # --- Top: the curve and the shaded area A(x). ---\n",
    "    ax1.plot(ts, ys, color=BLUE, lw=2.4, label='$f(t)$', zorder=3)\n",
    "    mask = ts <= x\n",
    "    ax1.fill_between(ts[mask], 0, ys[mask], color=SHADEG,\n",
    "                     alpha=0.95, zorder=1,\n",
    "                     label='area $A(x)=\\\\int_a^x f$')\n",
    "    # The thin strip added at the right edge.\n",
    "    h = 0.10 * (b - a)\n",
    "    xs = np.linspace(x, min(x + h, b), 30)\n",
    "    ax1.fill_between(xs, 0, f(xs), color=RED, alpha=0.45, zorder=2,\n",
    "                     label='new strip ($\\\\approx f(x)\\\\,h$)')\n",
    "    ax1.axvline(x, color=RED, lw=1.2, ls=':')\n",
    "    ax1.scatter([x], [f(x)], s=70, color=BLUE, zorder=6)\n",
    "    ax1.axhline(0, color=GRAY, lw=0.8)\n",
    "    ax1.set_ylabel('$f(t)$')\n",
    "    ax1.set_title(f'Area so far:  $A(x) \\\\approx$ {_area_to(f, a, x):.3f}',\n",
    "                  color=DARK)\n",
    "    ax1.legend(loc='upper left', framealpha=0.9, fontsize=9)\n",
    "\n",
    "    # --- Bottom: A(x) and its numerical derivative vs f. ---\n",
    "    xx = np.linspace(a, b, 200)\n",
    "    Avals = np.array([_area_to(f, a, t) for t in xx])\n",
    "    dA = np.gradient(Avals, xx)            # numerical A'(x)\n",
    "    ax2.plot(xx, Avals, color=RED, lw=2.4, label='$A(x)$', zorder=3)\n",
    "    ax2.plot(xx, dA, color=GREEN, lw=2.2, ls='--',\n",
    "             label=\"$A'(x)$ (numerical)\", zorder=4)\n",
    "    ax2.plot(ts, ys, color=BLUE, lw=1.4, alpha=0.55,\n",
    "             label='$f(t)$', zorder=2)\n",
    "    ax2.scatter([x], [f(x)], s=70, color=BLUE, zorder=6)\n",
    "    ax2.scatter([x], [_area_to(f, a, x)], s=70, color=RED, zorder=6)\n",
    "    ax2.axvline(x, color=RED, lw=1.2, ls=':')\n",
    "    ax2.axhline(0, color=GRAY, lw=0.8)\n",
    "    ax2.set_xlabel('$x$')\n",
    "    ax2.set_title(\"$A'(x)$ (green dashed) lands on $f(x)$ (blue) \"\n",
    "                  \"\\u2014 Part 1\", color=DARK)\n",
    "    ax2.legend(loc='upper left', framealpha=0.9, fontsize=9)\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "interact(_moving_edge,\n",
    "         curve=Dropdown(options=list(_CURVES1), description='curve'),\n",
    "         x=FloatSlider(value=3.0, min=0.1, max=6.2, step=0.1,\n",
    "                       description='right edge x'));\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "771ad09f",
   "metadata": {
    "id": "771ad09f"
   },
   "source": [
    "## 2. Area becomes a subtraction — FTC Part 2\n",
    "\n",
    "Since $A(x)=\\int_a^x f$ is *an* antiderivative of $f$ (Part 1), and any other antiderivative $F$ differs from it only by a constant, the laborious definite integral collapses into arithmetic. **Part 2:**\n",
    "\n",
    "$$\\int_a^b f(x)\\,dx = F(b) - F(a) = \\big[F(x)\\big]_a^b.$$\n",
    "\n",
    "Find an antiderivative, plug in the endpoints, subtract. Pick a pair $(f, F)$ and drag the endpoints $a$ and $b$. The shaded green area under $f$ (top) equals the **rise** of $F$ between the two marked endpoint values $F(a)$ and $F(b)$ (bottom). Read the title: the trapezoid-rule area and $F(b)-F(a)$ agree to the decimal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "886dd7a3",
   "metadata": {
    "id": "886dd7a3",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1782336314333,
     "user_tz": 240,
     "elapsed": 529,
     "user": {
      "displayName": "Meira Davidson",
      "userId": "09448014842742744623"
     }
    },
    "outputId": "474b2b5f-833d-4238-ff7e-70f265182a07",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 784,
     "referenced_widgets": [
      "b6ec8a3187904d3f88aace4b0f68a504",
      "033899679a5d469e8a0eb89d909e41ef",
      "c8b349fddc37415393777b2df330d68d",
      "6eecef9ad947406dab6368001c2a7fbe",
      "70b9de467fc94d1eabdd30006ad0ac82",
      "77f0cfa4398d44baa5f47a60eb34a63d",
      "1096c3d772604ba5801734983040b550",
      "d107b2606d734ceeb61cc26845edbb07",
      "2ee4751d36cf456aa54977fd4cf2c316",
      "8398b3e4479742528b9ec7e1b58808af",
      "e3a1d5744c734f8a828aeb486af93fbc",
      "d4554b2845824c7c97dfa99ec7b218c8",
      "f54b949c7d6348e48861bfc8a81a904d"
     ]
    }
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "interactive(children=(Dropdown(description='(f, F)', options=('f=x^2,  F=x^3/3', 'f=sin x,  F=-cos x', 'f=cos …"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "b6ec8a3187904d3f88aace4b0f68a504"
      }
     },
     "metadata": {}
    }
   ],
   "source": [
    "# Each preset: (f, F) with F' = f, plus a default [a, b] window.\n",
    "_PAIRS = {\n",
    "    'f=x^2,  F=x^3/3':\n",
    "        (lambda x: x**2, lambda x: x**3/3, -1.5, 2.0),\n",
    "    'f=sin x,  F=-cos x':\n",
    "        (lambda x: np.sin(x), lambda x: -np.cos(x), 0.0, np.pi),\n",
    "    'f=cos x,  F=sin x':\n",
    "        (lambda x: np.cos(x), lambda x: np.sin(x), 0.0, np.pi/2),\n",
    "    'f=e^x,  F=e^x':\n",
    "        (lambda x: np.exp(x), lambda x: np.exp(x), 0.0, 1.5),\n",
    "    'f=1/x,  F=ln x':\n",
    "        (lambda x: 1.0/x, lambda x: np.log(x), 1.0, 3.0),\n",
    "    'f=2x+1,  F=x^2+x':\n",
    "        (lambda x: 2*x + 1, lambda x: x**2 + x, -1.0, 2.0),\n",
    "}\n",
    "\n",
    "def _trap_area(f, a, b, n=800):\n",
    "    ts = np.linspace(a, b, n)\n",
    "    return float(np.trapz(f(ts), ts))\n",
    "\n",
    "def _ftc2(pair='f=x^2,  F=x^3/3', a=0.0, b=1.0):\n",
    "    f, F, _, _ = _PAIRS[pair]\n",
    "    if b - a < 0.2:\n",
    "        b = a + 0.2\n",
    "    lo, hi = min(a, b), max(a, b)\n",
    "    pad = 0.35 * (hi - lo) + 0.2\n",
    "    xs = np.linspace(lo - pad, hi + pad, 600)\n",
    "    # 1/x and ln need a positive window; clip safely.\n",
    "    if 'ln x' in pair or '1/x' in pair:\n",
    "        xs = xs[xs > 1e-3]\n",
    "\n",
    "    area = _trap_area(f, a, b)\n",
    "    exact = F(b) - F(a)\n",
    "\n",
    "    fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(7.2, 6.8),\n",
    "                                   sharex=True)\n",
    "    # --- Top: f with the area from a to b shaded. ---\n",
    "    ax1.plot(xs, f(xs), color=BLUE, lw=2.4, label='$f(x)$', zorder=3)\n",
    "    fillx = np.linspace(a, b, 400)\n",
    "    ax1.fill_between(fillx, 0, f(fillx), color=SHADEG, alpha=0.95,\n",
    "                     zorder=1, label='$\\\\int_a^b f$')\n",
    "    ax1.axhline(0, color=GRAY, lw=0.8)\n",
    "    ax1.axvline(a, color=RED, lw=1.0, ls=':')\n",
    "    ax1.axvline(b, color=RED, lw=1.0, ls=':')\n",
    "    ax1.set_ylabel('$f(x)$')\n",
    "    ax1.set_title(f'Area $\\\\int_a^b f$ = {area:.4f}', color=DARK)\n",
    "    ax1.legend(loc='best', framealpha=0.9, fontsize=10)\n",
    "\n",
    "    # --- Bottom: F with the endpoint values and their rise. ---\n",
    "    ax2.plot(xs, F(xs), color=ORANGE, lw=2.4, label='$F(x)$',\n",
    "             zorder=3)\n",
    "    Fa, Fb = F(a), F(b)\n",
    "    ax2.scatter([a, b], [Fa, Fb], s=80, color=RED, zorder=6)\n",
    "    ax2.annotate(f'$F(a)$ = {Fa:.3f}', xy=(a, Fa),\n",
    "                 xytext=(6, -14), textcoords='offset points',\n",
    "                 color=RED, fontsize=10)\n",
    "    ax2.annotate(f'$F(b)$ = {Fb:.3f}', xy=(b, Fb),\n",
    "                 xytext=(6, 8), textcoords='offset points',\n",
    "                 color=RED, fontsize=10)\n",
    "    # The rise F(b) - F(a), drawn as a vertical gap at x = b.\n",
    "    ax2.plot([b, b], [Fa, Fb], color=GREEN, lw=3.0, alpha=0.8,\n",
    "             zorder=4, label='rise $F(b)-F(a)$')\n",
    "    ax2.plot([a, b], [Fa, Fa], color=GREEN, lw=1.0, ls=':',\n",
    "             zorder=2)\n",
    "    ax2.axvline(a, color=RED, lw=1.0, ls=':')\n",
    "    ax2.axvline(b, color=RED, lw=1.0, ls=':')\n",
    "    ax2.set_xlabel('$x$')\n",
    "    ax2.set_title(f'$F(b)-F(a)$ = {exact:.4f}   '\n",
    "                  f'(matches the area)', color=DARK)\n",
    "    ax2.legend(loc='best', framealpha=0.9, fontsize=10)\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "interact(_ftc2,\n",
    "         pair=Dropdown(options=list(_PAIRS), description='(f, F)'),\n",
    "         a=FloatSlider(value=0.0, min=-1.5, max=2.0, step=0.1,\n",
    "                       description='a'),\n",
    "         b=FloatSlider(value=1.0, min=-1.0, max=3.0, step=0.1,\n",
    "                       description='b'));\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20bc189c",
   "metadata": {
    "id": "20bc189c"
   },
   "source": [
    "## 3. Integration by parts — the product rule, backward\n",
    "\n",
    "The product rule integrated and rearranged is\n",
    "\n",
    "$$\\int u\\,dv = uv - \\int v\\,du.$$\n",
    "\n",
    "Use it when the integrand is a product and differentiating one factor makes the leftover integral *simpler*. Choose that factor to be $u$ (it gets differentiated) and the rest to be $dv$ (it gets integrated). Pick an example: the widget prints the $u,\\,dv,\\,v,\\,du$ bookkeeping and the resulting $uv-\\int v\\,du$, then plots the integrand (blue) and its antiderivative (orange). Check visually that the orange curve's slope *is* the blue curve."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bab69bc8",
   "metadata": {
    "id": "bab69bc8"
   },
   "outputs": [],
   "source": [
    "# Each example: integrand, its antiderivative, and the parts table.\n",
    "_PARTS = {\n",
    "    'int x e^x dx': dict(\n",
    "        integrand=lambda x: x*np.exp(x),\n",
    "        antideriv=lambda x: (x - 1)*np.exp(x),\n",
    "        u='x', dv='e^x dx', v='e^x', du='1 dx',\n",
    "        result=r'x e^x - \\int e^x\\,dx = (x-1)e^x + C',\n",
    "        xlim=(-3.0, 2.0)),\n",
    "    'int x sin x dx': dict(\n",
    "        integrand=lambda x: x*np.sin(x),\n",
    "        antideriv=lambda x: np.sin(x) - x*np.cos(x),\n",
    "        u='x', dv='sin x dx', v='-cos x', du='1 dx',\n",
    "        result=r'-x\\cos x - \\int(-\\cos x)\\,dx = \\sin x - x\\cos x + C',\n",
    "        xlim=(-2*np.pi, 2*np.pi)),\n",
    "    'int x cos x dx': dict(\n",
    "        integrand=lambda x: x*np.cos(x),\n",
    "        antideriv=lambda x: np.cos(x) + x*np.sin(x),\n",
    "        u='x', dv='cos x dx', v='sin x', du='1 dx',\n",
    "        result=r'x\\sin x - \\int \\sin x\\,dx = \\cos x + x\\sin x + C',\n",
    "        xlim=(-2*np.pi, 2*np.pi)),\n",
    "    'int ln x dx': dict(\n",
    "        integrand=lambda x: np.log(x),\n",
    "        antideriv=lambda x: x*np.log(x) - x,\n",
    "        u='ln x', dv='dx', v='x', du='(1/x) dx',\n",
    "        result=r'x\\ln x - \\int x\\cdot\\tfrac1x\\,dx = x\\ln x - x + C',\n",
    "        xlim=(0.05, 4.0)),\n",
    "}\n",
    "\n",
    "def _byparts(example='int x e^x dx'):\n",
    "    d = _PARTS[example]\n",
    "    # Render the bookkeeping table and the result as LaTeX/Markdown.\n",
    "    table = (\n",
    "        '| choose | differentiate | integrate |\\n'\n",
    "        '|---|---|---|\\n'\n",
    "        f'| $u = {d[\"u\"]}$ | $du = {d[\"du\"]}$ |  |\\n'\n",
    "        f'| $dv = {d[\"dv\"]}$ |  | $v = {d[\"v\"]}$ |\\n'\n",
    "    )\n",
    "    display(Markdown(\n",
    "        f'**Bookkeeping for $\\\\displaystyle\\\\int u\\\\,dv$:**\\n\\n'\n",
    "        + table +\n",
    "        f'\\n$$\\\\int u\\\\,dv = uv - \\\\int v\\\\,du = {d[\"result\"]}$$'\n",
    "    ))\n",
    "\n",
    "    lo, hi = d['xlim']\n",
    "    xs = np.linspace(lo, hi, 600)\n",
    "    fig, ax = plt.subplots()\n",
    "    ax.plot(xs, d['integrand'](xs), color=BLUE, lw=2.4,\n",
    "            label='integrand', zorder=3)\n",
    "    ax.plot(xs, d['antideriv'](xs), color=ORANGE, lw=2.4,\n",
    "            label='antiderivative (its slope = integrand)', zorder=3)\n",
    "    ax.axhline(0, color=GRAY, lw=0.8)\n",
    "    ax.set_xlim(lo, hi)\n",
    "    ax.set_xlabel('$x$'); ax.set_ylabel('$y$')\n",
    "    ax.set_title('Integration by parts: integrand vs antiderivative',\n",
    "                 color=DARK)\n",
    "    ax.legend(loc='best', framealpha=0.9, fontsize=10)\n",
    "    plt.show()\n",
    "\n",
    "interact(_byparts,\n",
    "         example=Dropdown(options=list(_PARTS), description='example'));\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5803ad7f",
   "metadata": {
    "id": "5803ad7f"
   },
   "source": [
    "## 4. The logarithm as an area, and finding $e$\n",
    "\n",
    "The book's final act. We *define* the natural logarithm as the area under $1/t$:\n",
    "\n",
    "$$\\ln x \\;:=\\; \\int_1^x \\frac{1}{t}\\,dt \\quad (x > 0).$$\n",
    "\n",
    "Drag $x$ and watch the green area accumulate; the title reports both the shaded area and $\\ln x$ — they are the same number. The vertical green marker shows where the area first reaches exactly $1$: that place is the number **$e$**. (For $x<1$ the integral runs backward, so the area is *negative* — exactly $\\ln x < 0$.) Every loan the book took on $e$, $\\ln$, and $e^x$ is repaid right here — *(Figure 11.2)*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5ecbd6c3",
   "metadata": {
    "id": "5ecbd6c3"
   },
   "outputs": [],
   "source": [
    "def _log_area(x=2.0):\n",
    "    lo_t, hi_t = 0.25, 6.0\n",
    "    ts = np.linspace(lo_t, hi_t, 800)\n",
    "    fig, ax = plt.subplots()\n",
    "    ax.plot(ts, 1.0/ts, color=BLUE, lw=2.4, label='$y = 1/t$',\n",
    "            zorder=3)\n",
    "\n",
    "    # Shade the signed area from 1 to x (green); area = ln x.\n",
    "    if x >= 1:\n",
    "        fx = np.linspace(1, x, 400)\n",
    "    else:\n",
    "        fx = np.linspace(x, 1, 400)\n",
    "    ax.fill_between(fx, 0, 1.0/fx, color=SHADEG, alpha=0.95,\n",
    "                    zorder=1, label='area $= \\\\ln x$')\n",
    "    area = float(np.log(x))            # = int_1^x dt/t, exactly\n",
    "\n",
    "    # Mark t = e, where the area from 1 first reaches exactly 1.\n",
    "    e = np.e\n",
    "    ax.axvline(e, color=GREEN, lw=2.0, ls='--', zorder=4)\n",
    "    ax.annotate('$t = e$  (area here $= 1$)', xy=(e, 1.0/e),\n",
    "                xytext=(e + 0.15, 0.62), color=GREEN, fontsize=11,\n",
    "                arrowprops=dict(arrowstyle='->', color=GREEN))\n",
    "    ax.scatter([e], [1.0/e], s=70, color=GREEN, zorder=6)\n",
    "    # Mark the movable right edge x.\n",
    "    ax.axvline(x, color=RED, lw=1.2, ls=':', zorder=4)\n",
    "    ax.scatter([x], [1.0/x], s=70, color=RED, zorder=6)\n",
    "    ax.axvline(1, color=GRAY, lw=1.0)\n",
    "    ax.axhline(0, color=GRAY, lw=0.8)\n",
    "\n",
    "    ax.set_xlim(lo_t, hi_t)\n",
    "    ax.set_ylim(0, 4.2)\n",
    "    ax.set_xlabel('$t$'); ax.set_ylabel('$1/t$')\n",
    "    ax.set_title(f'x = {x:.3f}:   area = {area:+.4f}   '\n",
    "                 f'=   ln x = {area:+.4f}', color=DARK)\n",
    "    ax.legend(loc='upper right', framealpha=0.9, fontsize=10)\n",
    "    plt.show()\n",
    "\n",
    "interact(_log_area,\n",
    "         x=FloatSlider(value=2.0, min=0.3, max=6.0, step=0.05,\n",
    "                       description='right edge x'));\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57c323a9",
   "metadata": {
    "id": "57c323a9"
   },
   "source": [
    "---\n",
    "\n",
    "*Four windows onto one theorem. Widgets 1 and 2 are the two halves of the Fundamental Theorem — the area function's slope *is* the curve, so a definite integral is just $F(b)-F(a)$. Widget 3 is the product rule run backward. Widget 4 is the summit: $\\ln$ defined as an area, $e$ located as the place that area hits $1$, and every promissory note the book ever wrote paid in full. From here, Chapter 12 lets the sums run forever.*"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "name": "python",
   "pygments_lexer": "ipython3"
  },
  "colab": {
   "provenance": []
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "280e8400d2414dc2a82ca16136e17d90": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "VBoxModel",
     "model_module_version": "1.5.0",
     "state": {
      "_dom_classes": [
       "widget-interact"
      ],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "VBoxModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "VBoxView",
      "box_style": "",
      "children": [
       "IPY_MODEL_e5e5c7eb437e41a0bed1613b68244d4e",
       "IPY_MODEL_9f7ebc24f1ea49fc80602b79d8c6a450",
       "IPY_MODEL_ee2d96c8e74f49f4a0cbb27d3b92d3eb"
      ],
      "layout": "IPY_MODEL_6d2e349d43844b2294815b32d9db7d9c"
     }
    },
    "e5e5c7eb437e41a0bed1613b68244d4e": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "DropdownModel",
     "model_module_version": "1.5.0",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "DropdownModel",
      "_options_labels": [
       "f(t) = sin(t) + 1.5",
       "f(t) = t^2",
       "f(t) = 0.5 t + 0.5",
       "f(t) = e^{t/3}",
       "f(t) = 4 - (t-2)^2"
      ],
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "DropdownView",
      "description": "curve",
      "description_tooltip": null,
      "disabled": false,
      "index": 0,
      "layout": "IPY_MODEL_7c1e4feafa1a42aebe4ce5c546e411ad",
      "style": "IPY_MODEL_b6e55544a05a46528199542264c6c06c"
     }
    },
    "9f7ebc24f1ea49fc80602b79d8c6a450": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "FloatSliderModel",
     "model_module_version": "1.5.0",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "FloatSliderModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "FloatSliderView",
      "continuous_update": true,
      "description": "right edge x",
      "description_tooltip": null,
      "disabled": false,
      "layout": "IPY_MODEL_2da8737122ec41bfb517186893465551",
      "max": 6.2,
      "min": 0.1,
      "orientation": "horizontal",
      "readout": true,
      "readout_format": ".2f",
      "step": 0.1,
      "style": "IPY_MODEL_d46fe7db2995467b97001d5770bb41e6",
      "value": 3
     }
    },
    "ee2d96c8e74f49f4a0cbb27d3b92d3eb": {
     "model_module": "@jupyter-widgets/output",
     "model_name": "OutputModel",
     "model_module_version": "1.0.0",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/output",
      "_model_module_version": "1.0.0",
      "_model_name": "OutputModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/output",
      "_view_module_version": "1.0.0",
      "_view_name": "OutputView",
      "layout": "IPY_MODEL_84691fe959d44ccda74bf22f5141a0e1",
      "msg_id": "",
      "outputs": [
       {
        "output_type": "stream",
        "name": "stderr",
        "text": [
         "/tmp/ipykernel_3694/650901362.py:14: DeprecationWarning: `trapz` is deprecated. Use `trapezoid` instead, or one of the numerical integration functions in `scipy.integrate`.\n",
         "  return float(np.trapz(f(ts), ts))\n"
        ]
       },
       {
        "output_type": "display_data",
        "data": {
         "text/plain": "<Figure size 691.2x652.8 with 2 Axes>",
         "image/png": "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\n"
        },
        "metadata": {}
       }
      ]
     }
    },
    "6d2e349d43844b2294815b32d9db7d9c": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "model_module_version": "1.2.0",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "7c1e4feafa1a42aebe4ce5c546e411ad": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "model_module_version": "1.2.0",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "b6e55544a05a46528199542264c6c06c": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "DescriptionStyleModel",
     "model_module_version": "1.5.0",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "DescriptionStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "description_width": ""
     }
    },
    "2da8737122ec41bfb517186893465551": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "model_module_version": "1.2.0",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "d46fe7db2995467b97001d5770bb41e6": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "SliderStyleModel",
     "model_module_version": "1.5.0",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "SliderStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "description_width": "",
      "handle_color": null
     }
    },
    "84691fe959d44ccda74bf22f5141a0e1": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "model_module_version": "1.2.0",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "b6ec8a3187904d3f88aace4b0f68a504": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "VBoxModel",
     "model_module_version": "1.5.0",
     "state": {
      "_dom_classes": [
       "widget-interact"
      ],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "VBoxModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "VBoxView",
      "box_style": "",
      "children": [
       "IPY_MODEL_033899679a5d469e8a0eb89d909e41ef",
       "IPY_MODEL_c8b349fddc37415393777b2df330d68d",
       "IPY_MODEL_6eecef9ad947406dab6368001c2a7fbe",
       "IPY_MODEL_70b9de467fc94d1eabdd30006ad0ac82"
      ],
      "layout": "IPY_MODEL_77f0cfa4398d44baa5f47a60eb34a63d"
     }
    },
    "033899679a5d469e8a0eb89d909e41ef": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "DropdownModel",
     "model_module_version": "1.5.0",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "DropdownModel",
      "_options_labels": [
       "f=x^2,  F=x^3/3",
       "f=sin x,  F=-cos x",
       "f=cos x,  F=sin x",
       "f=e^x,  F=e^x",
       "f=1/x,  F=ln x",
       "f=2x+1,  F=x^2+x"
      ],
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "DropdownView",
      "description": "(f, F)",
      "description_tooltip": null,
      "disabled": false,
      "index": 0,
      "layout": "IPY_MODEL_1096c3d772604ba5801734983040b550",
      "style": "IPY_MODEL_d107b2606d734ceeb61cc26845edbb07"
     }
    },
    "c8b349fddc37415393777b2df330d68d": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "FloatSliderModel",
     "model_module_version": "1.5.0",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "FloatSliderModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "FloatSliderView",
      "continuous_update": true,
      "description": "a",
      "description_tooltip": null,
      "disabled": false,
      "layout": "IPY_MODEL_2ee4751d36cf456aa54977fd4cf2c316",
      "max": 2,
      "min": -1.5,
      "orientation": "horizontal",
      "readout": true,
      "readout_format": ".2f",
      "step": 0.1,
      "style": "IPY_MODEL_8398b3e4479742528b9ec7e1b58808af",
      "value": 0
     }
    },
    "6eecef9ad947406dab6368001c2a7fbe": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "FloatSliderModel",
     "model_module_version": "1.5.0",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "FloatSliderModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "FloatSliderView",
      "continuous_update": true,
      "description": "b",
      "description_tooltip": null,
      "disabled": false,
      "layout": "IPY_MODEL_e3a1d5744c734f8a828aeb486af93fbc",
      "max": 3,
      "min": -1,
      "orientation": "horizontal",
      "readout": true,
      "readout_format": ".2f",
      "step": 0.1,
      "style": "IPY_MODEL_d4554b2845824c7c97dfa99ec7b218c8",
      "value": 1
     }
    },
    "70b9de467fc94d1eabdd30006ad0ac82": {
     "model_module": "@jupyter-widgets/output",
     "model_name": "OutputModel",
     "model_module_version": "1.0.0",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/output",
      "_model_module_version": "1.0.0",
      "_model_name": "OutputModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/output",
      "_view_module_version": "1.0.0",
      "_view_name": "OutputView",
      "layout": "IPY_MODEL_f54b949c7d6348e48861bfc8a81a904d",
      "msg_id": "",
      "outputs": [
       {
        "output_type": "stream",
        "name": "stderr",
        "text": [
         "/tmp/ipykernel_3694/3703978362.py:19: DeprecationWarning: `trapz` is deprecated. Use `trapezoid` instead, or one of the numerical integration functions in `scipy.integrate`.\n",
         "  return float(np.trapz(f(ts), ts))\n"
        ]
       },
       {
        "output_type": "display_data",
        "data": {
         "text/plain": "<Figure size 691.2x652.8 with 2 Axes>",
         "image/png": "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\n"
        },
        "metadata": {}
       }
      ]
     }
    },
    "77f0cfa4398d44baa5f47a60eb34a63d": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "model_module_version": "1.2.0",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "1096c3d772604ba5801734983040b550": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "model_module_version": "1.2.0",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "d107b2606d734ceeb61cc26845edbb07": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "DescriptionStyleModel",
     "model_module_version": "1.5.0",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "DescriptionStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "description_width": ""
     }
    },
    "2ee4751d36cf456aa54977fd4cf2c316": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "model_module_version": "1.2.0",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "8398b3e4479742528b9ec7e1b58808af": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "SliderStyleModel",
     "model_module_version": "1.5.0",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "SliderStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "description_width": "",
      "handle_color": null
     }
    },
    "e3a1d5744c734f8a828aeb486af93fbc": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "model_module_version": "1.2.0",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "d4554b2845824c7c97dfa99ec7b218c8": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "SliderStyleModel",
     "model_module_version": "1.5.0",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "SliderStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "description_width": "",
      "handle_color": null
     }
    },
    "f54b949c7d6348e48861bfc8a81a904d": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "model_module_version": "1.2.0",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    }
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}