7-the-discrete-cosine-transform.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib widget"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<figure id=\"figure-3\">\n",
    "<div style=\"background-color: white\">\n",
    "\n",
    "![](figures/dct.svg)</div>\n",
    "    \n",
    "<figcaption style=\"text-align: center\">Figure 3: A DCT can be treated as an N channel filter bank where the coefficients of the\n",
    "filters are the basis functions.</figcaption></figure>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 7 The Discrete Cosine Transform (DCT)\n",
    "\n",
    "\n",
    "The DCT is a method of performing energy compaction that is rather different\n",
    "from the pyramid method.  It operates on non-overlapping blocks of pixels\n",
    "(typically $8 \\times 8$ pixels in size) by a reversible linear transform\n",
    "process, such that each block of pixels is replaced by a block of the same\n",
    "number of transform coefficients.  If all the transform coefficients for a\n",
    "given block are transmitted unaltered to the decoder, then the original block\n",
    "of pixels can be exactly recovered by the inverse transform process.\n",
    "\n",
    "In practise the transform coefficients are quantised before transmission, and\n",
    "if energy compaction has occurred, then fewer bits will be needed to send the\n",
    "coefficients than the original pixels.  A key advantage of transform-based\n",
    "methods is that there is no expansion of the number of samples (the\n",
    "transformed block is the same size as the original block of pixels), whereas\n",
    "the previous pyramid method expands the data by\n",
    "$1 + \\frac{1}{4} + \\frac{1}{16} + \\ldots \\approx 1.33$ times, which is not very desirable for data\n",
    "compression."
   ]
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   "cell_type": "markdown",
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   "source": [
    "## 7.1 Definition of the DCT\n",
    "\n",
    "\n",
    "The one-dimensional form of the DCT is closely related to the Discrete Fourier\n",
    "Transform (DFT).  The 1-D $N$-point DCT is defined as follows:\n",
    "\n",
    "\n",
    "$$\n",
    "y(k) = \\sum_{n=0}^{N-1} C_{kn}\\ x(n) \\quad \\text{for} \\quad 0 \\le k \\le N-1 \\\\\n",
    "  \\text{where }\\quad C_{0n} = \\sqrt{\\frac{1}{N}}  \\\\\n",
    "    \\text{and } \\quad C_{kn} = \\sqrt{\\frac{2}{N}}\\ \\cos\n",
    "\\frac{k(n+\\frac{1}{2})\\pi}{N} \\quad \\text{for} \\quad 1 \\le k \\le N-1\n",
    "$$\n",
    "\n",
    "The equivalent inverse DCT is:\n",
    "$$\n",
    "x(n) = \\sum_{k=0}^{N-1} C_{kn}\\ y(k) \\quad \\text{for} \\quad 0 \\le n \\le N-1 \\\\\n",
    " \\text{where $C_{kn}$ is defined as above.}\\\\\n",
    "$$\n",
    "\n",
    "(This is actually the Type-II DCT, and the inverse is the Type-III DCT - other types have slightly different relative phases})\n",
    "\n",
    "We see that the forward transform is equivalent to multiplication of the\n",
    "$N$-point column vector $[x(0) \\ldots x(N-1)]'$ by an $N \\times N$ matrix,\n",
    "containing $C_{kn}$ at each location $(k,n)$, to produce the $N$-point column\n",
    "vector $[y(0) \\ldots y(N-1)]'$.  Similarly the inverse transform is equivalent\n",
    "to multiplication of the $y$ vector by the transpose of the $C$ matrix to give\n",
    "the $x$ vector.  In python3 + numpy notation these become:\n",
    "\n",
    "`y = C @ x` and `x = C.T @ y`\n",
    "\n",
    "Note that C is an orthonormal matrix since its inverse is just its\n",
    "transpose (its rows are othogonal to each other and have unit energy).\n",
    "\n",
    "The two-dimensional version of the DCT (as used for image compression) is a\n",
    "simple extension of the above 1-D DCT.  For an $N \\times N$ block of pixels,\n",
    "the $N$-point 1-D DCT is first applied to each column of the block to give $N$\n",
    "columns of coefficients.  Then the same 1-D DCT is applied to the rows of\n",
    "these coefficients to give the 2-D transform coefficients.\n",
    "\n",
    "In python3 + numpy notation, if the input block of pixels is matrix X, the output\n",
    "block of 2-D transformed coefficients Y is given by:\n",
    "\n",
    "`Y = (C @ (C @ X).T).T` or more simply `Y = C @ X @ C.T`\n",
    "\n",
    "where C is the 1-D transform matrix as above.  Note that in the 2-D\n",
    "transform, it does not matter whether the rows or the columns are transformed\n",
    "first (because the transform is linear and separable).\n"
   ]
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   "cell_type": "markdown",
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    "## 7.2 Applying the DCT to images\n",
    "\n",
    "Conceptually the 2-D DCT is applied to all non-overlapping $N \\times N$ blocks\n",
    "of pixels in an image (we assume that the image dimensions are exact multiples\n",
    "of $N$).  However it is simplest and most efficient to perform 1-D\n",
    "$N$-point DCTs on all the columns of the image first, and then repeat the\n",
    "operation on the transpose of the result to transform the rows.\n",
    "\n",
    "**First generate an 8-point 1-D Type-II DCT matrix C8**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cued_sf2_lab.dct import dct_ii\n",
    "\n",
    "C8 = dct_ii(8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Take a look at the function `dct_ii` and list `C8` to check\n",
    "that it agrees with the definitions for $C_{kn}$ given above:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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       ".output_html .il { color: #666666 } /* Literal.Number.Integer.Long */</style><div class=\"highlight\"><pre><span></span><span class=\"k\">def</span> <span class=\"nf\">dct_ii</span><span class=\"p\">(</span><span class=\"n\">N</span><span class=\"p\">:</span> <span class=\"nb\">int</span><span class=\"p\">)</span> <span class=\"o\">-&gt;</span> <span class=\"n\">np</span><span class=\"o\">.</span><span class=\"n\">ndarray</span><span class=\"p\">:</span>\n",
       "    <span class=\"sd\">&quot;&quot;&quot;</span>\n",
       "<span class=\"sd\">    Generate the 1D DCT transform matrix of size N.</span>\n",
       "\n",
       "<span class=\"sd\">    Parameters:</span>\n",
       "<span class=\"sd\">    N (int): Size of DCT matrix required</span>\n",
       "\n",
       "<span class=\"sd\">    Returns:</span>\n",
       "<span class=\"sd\">    C (2D np array): 1D DCT transform matrix</span>\n",
       "\n",
       "<span class=\"sd\">    Uses an orthogonal Type-II DCT.</span>\n",
       "<span class=\"sd\">    Y = C * X tranforms N-vector X into Y.</span>\n",
       "<span class=\"sd\">    &quot;&quot;&quot;</span>\n",
       "    <span class=\"n\">C</span> <span class=\"o\">=</span> <span class=\"n\">np</span><span class=\"o\">.</span><span class=\"n\">ones</span><span class=\"p\">((</span><span class=\"n\">N</span><span class=\"p\">,</span> <span class=\"n\">N</span><span class=\"p\">))</span> <span class=\"o\">/</span> <span class=\"n\">np</span><span class=\"o\">.</span><span class=\"n\">sqrt</span><span class=\"p\">(</span><span class=\"n\">N</span><span class=\"p\">)</span>\n",
       "    <span class=\"n\">theta</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">np</span><span class=\"o\">.</span><span class=\"n\">arange</span><span class=\"p\">(</span><span class=\"n\">N</span><span class=\"p\">)</span> <span class=\"o\">+</span> <span class=\"mf\">0.5</span><span class=\"p\">)</span> <span class=\"o\">*</span> <span class=\"p\">(</span><span class=\"n\">np</span><span class=\"o\">.</span><span class=\"n\">pi</span><span class=\"o\">/</span><span class=\"n\">N</span><span class=\"p\">)</span>\n",
       "    <span class=\"n\">g</span> <span class=\"o\">=</span> <span class=\"n\">np</span><span class=\"o\">.</span><span class=\"n\">sqrt</span><span class=\"p\">(</span><span class=\"mi\">2</span><span class=\"o\">/</span><span class=\"n\">N</span><span class=\"p\">)</span>\n",
       "    <span class=\"k\">for</span> <span class=\"n\">i</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"n\">N</span><span class=\"p\">):</span>\n",
       "        <span class=\"n\">C</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">,</span> <span class=\"p\">:]</span> <span class=\"o\">=</span> <span class=\"n\">g</span> <span class=\"o\">*</span> <span class=\"n\">np</span><span class=\"o\">.</span><span class=\"n\">cos</span><span class=\"p\">(</span><span class=\"n\">theta</span><span class=\"o\">*</span><span class=\"n\">i</span><span class=\"p\">)</span>\n",
       "\n",
       "    <span class=\"k\">return</span> <span class=\"n\">C</span>\n",
       "</pre></div>\n"
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       "\\begin{Verbatim}[commandchars=\\\\\\{\\}]\n",
       "\\PY{k}{def} \\PY{n+nf}{dct\\PYZus{}ii}\\PY{p}{(}\\PY{n}{N}\\PY{p}{:} \\PY{n+nb}{int}\\PY{p}{)} \\PY{o}{\\PYZhy{}}\\PY{o}{\\PYZgt{}} \\PY{n}{np}\\PY{o}{.}\\PY{n}{ndarray}\\PY{p}{:}\n",
       "    \\PY{l+s+sd}{\\PYZdq{}\\PYZdq{}\\PYZdq{}}\n",
       "\\PY{l+s+sd}{    Generate the 1D DCT transform matrix of size N.}\n",
       "\n",
       "\\PY{l+s+sd}{    Parameters:}\n",
       "\\PY{l+s+sd}{    N (int): Size of DCT matrix required}\n",
       "\n",
       "\\PY{l+s+sd}{    Returns:}\n",
       "\\PY{l+s+sd}{    C (2D np array): 1D DCT transform matrix}\n",
       "\n",
       "\\PY{l+s+sd}{    Uses an orthogonal Type\\PYZhy{}II DCT.}\n",
       "\\PY{l+s+sd}{    Y = C * X tranforms N\\PYZhy{}vector X into Y.}\n",
       "\\PY{l+s+sd}{    \\PYZdq{}\\PYZdq{}\\PYZdq{}}\n",
       "    \\PY{n}{C} \\PY{o}{=} \\PY{n}{np}\\PY{o}{.}\\PY{n}{ones}\\PY{p}{(}\\PY{p}{(}\\PY{n}{N}\\PY{p}{,} \\PY{n}{N}\\PY{p}{)}\\PY{p}{)} \\PY{o}{/} \\PY{n}{np}\\PY{o}{.}\\PY{n}{sqrt}\\PY{p}{(}\\PY{n}{N}\\PY{p}{)}\n",
       "    \\PY{n}{theta} \\PY{o}{=} \\PY{p}{(}\\PY{n}{np}\\PY{o}{.}\\PY{n}{arange}\\PY{p}{(}\\PY{n}{N}\\PY{p}{)} \\PY{o}{+} \\PY{l+m+mf}{0.5}\\PY{p}{)} \\PY{o}{*} \\PY{p}{(}\\PY{n}{np}\\PY{o}{.}\\PY{n}{pi}\\PY{o}{/}\\PY{n}{N}\\PY{p}{)}\n",
       "    \\PY{n}{g} \\PY{o}{=} \\PY{n}{np}\\PY{o}{.}\\PY{n}{sqrt}\\PY{p}{(}\\PY{l+m+mi}{2}\\PY{o}{/}\\PY{n}{N}\\PY{p}{)}\n",
       "    \\PY{k}{for} \\PY{n}{i} \\PY{o+ow}{in} \\PY{n+nb}{range}\\PY{p}{(}\\PY{l+m+mi}{1}\\PY{p}{,} \\PY{n}{N}\\PY{p}{)}\\PY{p}{:}\n",
       "        \\PY{n}{C}\\PY{p}{[}\\PY{n}{i}\\PY{p}{,} \\PY{p}{:}\\PY{p}{]} \\PY{o}{=} \\PY{n}{g} \\PY{o}{*} \\PY{n}{np}\\PY{o}{.}\\PY{n}{cos}\\PY{p}{(}\\PY{n}{theta}\\PY{o}{*}\\PY{n}{i}\\PY{p}{)}\n",
       "\n",
       "    \\PY{k}{return} \\PY{n}{C}\n",
       "\\end{Verbatim}\n"
      ],
      "text/plain": [
       "def dct_ii(N: int) -> np.ndarray:\n",
       "    \"\"\"\n",
       "    Generate the 1D DCT transform matrix of size N.\n",
       "\n",
       "    Parameters:\n",
       "    N (int): Size of DCT matrix required\n",
       "\n",
       "    Returns:\n",
       "    C (2D np array): 1D DCT transform matrix\n",
       "\n",
       "    Uses an orthogonal Type-II DCT.\n",
       "    Y = C * X tranforms N-vector X into Y.\n",
       "    \"\"\"\n",
       "    C = np.ones((N, N)) / np.sqrt(N)\n",
       "    theta = (np.arange(N) + 0.5) * (np.pi/N)\n",
       "    g = np.sqrt(2/N)\n",
       "    for i in range(1, N):\n",
       "        C[i, :] = g * np.cos(theta*i)\n",
       "\n",
       "    return C"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import inspect\n",
    "import IPython.display\n",
    "IPython.display.Code(inspect.getsource(dct_ii), language=\"python\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Plot the rows of `C8` using `plot(C8.T)`.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(C8.T);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "When we calculate the 1-D transform of an 8-point block of data, each\n",
    "transform coefficient represents the component of the data that is\n",
    "correlated with the corresponding row of `C8`.  Hence the\n",
    "first coefficient represents the dc component, the second one\n",
    "represents the approximate average slope, and so on. The later\n",
    "coefficients represent progressively higher frequency components\n",
    "in the data.\n",
    "\n",
    "The function `colxfm(X, C8)` will perform a 1-D transform on\n",
    "the columns of image `X` using `C8`. We can\n",
    "therefore perform a 2-D transform on `X` by using `colxfm` twice, once with transpose operators, as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cued_sf2_lab.familiarisation import load_mat_img\n",
    "from cued_sf2_lab.dct import colxfm\n",
    "\n",
    "X_pre_zero_mean, cmaps_dict = load_mat_img(img='lighthouse.mat', img_info='X', cmap_info={'map', 'map2'})\n",
    "X = X_pre_zero_mean - 128.0\n",
    "\n",
    "Y = colxfm(colxfm(X, C8).T, C8).T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In `Y`, each $8 \\times 8$ block of pixels has been replaced by an\n",
    "equivalent block of transform coefficients.  The coefficient in the top left\n",
    "corner of each block represents the dc value of the block of pixels;\n",
    "coefficients along the top row represent increasing horizontal frequency\n",
    "components, and along the left column represent increasing vertical frequency\n",
    "components.  Other coefficients represent various combinations of horizontal\n",
    "and vertical frequencies, in proportion to their horizontal and vertical\n",
    "distances from the top left corner.\n",
    "\n",
    "If we try to display `Y` directly as an image, it is rather\n",
    "confusing because the different frequency components of each block\n",
    "are all present adjacent to each other.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from cued_sf2_lab.familiarisation import plot_image\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plot_image(Y, ax=ax);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A much more meaningful\n",
    "image is created if we group all the coefficients of a given type\n",
    "together into a small sub-image, and display the result as an $8\n",
    "\\times 8$ block of sub-images, one for each coefficient type.  The\n",
    "function `regroup(Y, N)` achieves this regrouping, where $N$ is\n",
    "the size of the original transform blocks. You need to ensure that X has zero mean (by subtracting 128) before you start transforming it, otherwise the dc coefficient will be purely positive, whereas the\n",
    "others are symmetrically distributed about zero. Also, an $N\n",
    "\\times N$ 2-D DCT introduces a gain factor of $N$ in order to\n",
    "preserve constant total energy between the pixel and transform\n",
    "domains: we need to divide by $N$ *when displaying* to get back to the expected range.\n",
    "\n",
    "Hence we can display `Y` meaningfully using:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from cued_sf2_lab.dct import regroup\n",
    "\n",
    "N = 8\n",
    "fig, ax = plt.subplots()\n",
    "plot_image(regroup(Y, N)/N, ax=ax);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this image, you should see a small replica of the original in the top left\n",
    "corner (the dc coefficients), and other sub-images showing various edges from\n",
    "the original, representing progressively higher frequencies as you move\n",
    "towards the lower right corner.\n",
    "\n",
    "<div class=\"alert alert-block alert-danger\">\n",
    "\n",
    "What do you observe about the energies of the sub-images as frequencies\n",
    "increase?</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now check that you can recover the original image from Y\n",
    "by carrying out the inverse transform using:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Z = colxfm(colxfm(Y.T, C8.T).T, C8.T)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plot_image(Z, ax=ax);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Measure the maximum absolute error between X and Z\n",
    "to confirm this.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The DCT analyses each $8 \\times 8$ block of image pixels into a linear\n",
    "combination of sixty-four $8 \\times 8$ basis functions.  The following will generate\n",
    "an image comprising these basis functions (the `np.nan`s separate the sub-images as matplotlib draws them as transparent, and the `reshape` function converts from a matrix to a row vector):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "# Stack some NaNs\n",
    "bases = np.concatenate([np.full((8, 1), np.nan), C8, np.full((8, 1), np.nan)], axis=1)\n",
    "# Reshape\n",
    "bases_flat = np.reshape(bases, (-1, 1))\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "im = plot_image(255*bases_flat@bases_flat.T, ax=ax)\n",
    "fig.colorbar(im);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-danger\">\n",
    "\n",
    "Explain how this image relates to the DCT coefficients.</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.3 Quantisation and Coding Efficiency\n",
    "\n",
    "We are now going to look at the effects of quantising the DCT coefficients\n",
    "fairly coarsely and determine the entropies of the coefficient sub-images.\n",
    "At this stage we shall quantise all sub-images with the same step-size,\n",
    "since they all are the same size and have unit energy gain from the\n",
    "quantiser to the output image (due to the orthonormal transform matrices).\n",
    "\n",
    "First quantise the transformed image Y using a step size\n",
    "of 17 to give Yq.  Then regroup Yq to form\n",
    "sub-images of each coefficient type as before, to give Yr. These sub-images have different probability distributions and we can take advantage of this later in coding them efficiently. Hence we get a better estimate of the number of bits required to code Yq by looking at the entropies of each of the re-grouped sub-images separately.\n",
    "\n",
    "**Write a function `dctbpp(Yr, N)` to calculate the total number of bits from a re-grouped image Yr, by using `bpp(Ys)` on each sub-image Ys of Yr, then multiplying each result by the number of pixels in the sub-image, and summing to give the total number of bits.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cued_sf2_lab.laplacian_pyramid import bpp\n",
    "\n",
    "def dctbpp(Yr, N):\n",
    "    # Your code here\n",
    "    pass # This just does nothing at the moment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-danger\">\n",
    "\n",
    "Visualise Yr and comment on the distributions in each of the sub-images. Use the function `dctbpp(Yr, N)` that you have written to calculate the total number of bits, and compare it with just using `bpp(Yr)`, explaining your results.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-danger\">\n",
    "\n",
    "Now reconstruct the output image `Z` from `Yq` and measure the rms\n",
    "error (standard deviation) between `X` and `Z`.  Compare this with the\n",
    "error produced by quantising `X` with a step-size of 17 to give `Xq`.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***As with the Laplacian Pyramid, we really need to contrast compression ratios and visual results on compressed images with the same rms error. Re-use your step optimisation code to calculate the (non-integer) step size required in this case for the same rms error as quantising X with a step-size of 17.***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-danger\">\n",
    "\n",
    "Calculate the compression ratio for this scheme compared to direct quantisation. Use `dctbpp` to calculate the number of bits needed. Contrast the visual appearance of the DCT-compressed image, the directly quantised image, and the original image.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## 7.4 Alternative transform sizes\n",
    "\n",
    "So far, we have concentrated on $8 \\times 8$ DCTs using C8\n",
    "as the 1-D transform matrix.  **Now generate 4-point and 16-point\n",
    "transform matrices, C4 and C16 using `dct_ii`.**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-danger\">\n",
    "\n",
    "Repeat the main measurements from the previous section, so as to obtain\n",
    "estimates of the number of bits and compression ratios for $4 \\times 4$ and $16 \\times 16$ DCTs when the\n",
    "rms errors are equivalent to those in your previous tests.  Also assess the\n",
    "relative subjective quality of the reconstructed images.</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "This analysis is in fact slightly biased because with larger transform sizes the function `dctbpp(Yr, N)` will use a greater number of smaller sub-images on which to calculate probability distributions. It may be better to use the same N in this function even when the actual transform changes; however whether this is more predictive of actual coding performance depends on what scanning method is used in the coding scheme.\n",
    "\n",
    "<div class=\"alert alert-block alert-danger\">\n",
    "\n",
    "What happens in the limit if you use `dctbpp(Yr, 256)` (i.e. the entropy is calculated independently for each pixel)? Why is this the case, and why isn't this a realistic result?</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-danger\">\n",
    "\n",
    "Can you draw any conclusions about the best choice of transform size for the\n",
    "Lighthouse image?  Try to postulate what features in other images might make your\n",
    "conclusions different, and suggest why.</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here"
   ]
  }
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