{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CDI example loading data from a CXI file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import h5py\n",
    "from numpy.fft import fftshift\n",
    "from scipy.ndimage.measurements import center_of_mass\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# This imports all necessary operators. GPU will be auto-selected\n",
    "from pynx.cdi import *\n",
    "from pynx.utils.math import smaller_primes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filename\n",
    "Change to your CXI file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = \"/Users/vincent/data/201702-BraggCDI-Pt/alignment_S2280.cxi\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  CXI input: Energy =     0.00keV\n",
      "  CXI input: loading iobs\n",
      "  CXI input: loading mask, with 1582092 pixels masked ( 2.312%)\n"
     ]
    }
   ],
   "source": [
    "cxi = h5py.File(filename, 'r')\n",
    "if '/entry_1/instrument_1/source_1/energy' in cxi:\n",
    "    nrj = cxi['/entry_1/instrument_1/source_1/energy'][()] / 1.60218e-16\n",
    "    wavelength = 12.384 / nrj * 1e-10\n",
    "    print(\"  CXI input: Energy = %8.2fkeV\" % nrj)\n",
    "else:\n",
    "    wavelength = None\n",
    "if '/entry_1/instrument_1/detector_1/distance' in cxi:\n",
    "    detector_distance = cxi['/entry_1/instrument_1/detector_1/distance'][()]\n",
    "    print(\"  CXI input: detector distance = %8.2fm\" % detector_distance)\n",
    "else:\n",
    "    detector_distance = None\n",
    "if '/entry_1/instrument_1/detector_1/x_pixel_size' in cxi:\n",
    "    pixel_size_detector = cxi['/entry_1/instrument_1/detector_1/x_pixel_size'][()]\n",
    "    print(\"  CXI input: detector pixel size = %8.2fum\" % (pixel_size_detector * 1e6))\n",
    "else:\n",
    "    pixel_size_detector = None\n",
    "print(\"  CXI input: loading iobs\")\n",
    "if 'entry_1/instrument_1/detector_1/data' in cxi:\n",
    "    iobs = cxi['entry_1/instrument_1/detector_1/data'][()].astype(np.float32)\n",
    "else:\n",
    "    iobs = cxi['entry_1/data_1/data'].value.astype(np.float32)\n",
    "# This is the detector mask\n",
    "if 'entry_1/instrument_1/detector_1/mask' in cxi:\n",
    "    mask = cxi['entry_1/instrument_1/detector_1/mask'][()].astype(np.int8)\n",
    "    nb = mask.sum()\n",
    "    print(\"  CXI input: loading mask, with %d pixels masked (%6.3f%%)\" % (nb, nb * 100 / mask.size))\n",
    "else:\n",
    "    mask = None\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Centre & crop data\n",
    "You can skip this if your data is already centred and if the arrays dimensions already have a prime factor decomposition with factors not larger than 7.\n",
    "\n",
    "You can also change `max_size` to a larger value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Center of mass at: 128.36392729369913 228.5233212385262 293.2362391873246\n",
      "Centering & reshaping data: (257, 516, 516) -> (256, 256, 256)\n"
     ]
    }
   ],
   "source": [
    "max_size = 256\n",
    "if iobs.ndim == 3:\n",
    "    nz0, ny0, nx0 = iobs.shape\n",
    "    # Find center of mass\n",
    "    z0, y0, x0 = center_of_mass(iobs)\n",
    "    print(\"Center of mass at:\", z0, y0, x0)\n",
    "    iz0, iy0, ix0 = int(round(z0)), int(round(y0)), int(round(x0))\n",
    "    # Max symmetrical box around center of mass\n",
    "    nx = 2 * min(ix0, nx0 - ix0)\n",
    "    ny = 2 * min(iy0, ny0 - iy0)\n",
    "    nz = 2 * min(iz0, nz0 - iz0)\n",
    "    if max_size is not None:\n",
    "        nx = min(nx, max_size)\n",
    "        ny = min(ny, max_size)\n",
    "        nz = min(nz, max_size)\n",
    "    # Crop data to fulfill FFT size requirements\n",
    "    nz1, ny1, nx1 = smaller_primes((nz, ny, nx), maxprime=7, required_dividers=(2,))\n",
    "\n",
    "    print(\"Centering & reshaping data: (%d, %d, %d) -> (%d, %d, %d)\" % (nz0, ny0, nx0, nz1, ny1, nx1))\n",
    "    iobs = iobs[iz0 - nz1 // 2:iz0 + nz1 // 2, iy0 - ny1 // 2:iy0 + ny1 // 2,\n",
    "                ix0 - nx1 // 2:ix0 + nx1 // 2]\n",
    "    if mask is not None:\n",
    "        mask = mask[iz0 - nz1 // 2:iz0 + nz1 // 2, iy0 - ny1 // 2:iy0 + ny1 // 2,\n",
    "                    ix0 - nx1 // 2:ix0 + nx1 // 2]\n",
    "else:\n",
    "    ny0, nx0 = iobs.shape\n",
    "    # Find center of mass\n",
    "    y0, x0 = center_of_mass(iobs)\n",
    "    print(\"Center of mass at:\", y0, x0)\n",
    "    iy0, ix0 = int(round(y0)), int(round(x0))\n",
    "    # Max symmetrical box around center of mass\n",
    "    nx = 2 * min(ix0, nx0 - ix0)\n",
    "    ny = 2 * min(iy0, ny0 - iy0)\n",
    "    if max_size is not None:\n",
    "        nx = min(nx, max_size)\n",
    "        ny = min(ny, max_size)\n",
    "        nz = min(nz, max_size)\n",
    "    # Crop data to fulfill FFT size requirements\n",
    "    ny1, nx1 = smaller_primes((ny, nx), maxprime=7, required_dividers=(2,))\n",
    "\n",
    "    print(\"Centering & reshaping data: (%d, %d) -> (%d, %d)\" % (ny0, nx0, ny1, nx1))\n",
    "    iobs = iobs[iy0 - ny1 // 2:iy0 + ny1 // 2, ix0 - nx1 // 2:ix0 + nx1 // 2]\n",
    "    if mask is not None:\n",
    "        mask = mask[iy0 - ny1 // 2:iy0 + ny1 // 2, ix0 - nx1 // 2:ix0 + nx1 // 2]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create & initialise the CDI object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "cdi = CDI(fftshift(iobs), obj=None, support=None, mask=fftshift(mask), wavelength=wavelength, \n",
    "          pixel_size_detector=pixel_size_detector)\n",
    "cdi = InitFreePixels() * cdi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Init the object support & a random object\n",
    "For Bragg CDI (without a beamstop) you can usually rely on auto-correlation to get a first estimate of the object support. Calling `ScaleObj()` is only necessary if a mask is used.\n",
    "\n",
    "There are several options for the object random initialisation, use `InitObjRandom?` for details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "    canvas_div.setAttribute(\n",
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       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
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       "    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",
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       "        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",
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       "        'canvas'\n",
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       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
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       "\n",
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       "};\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>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cdi = AutoCorrelationSupport(threshold=0.1) * cdi\n",
    "\n",
    "cdi = ShowCDI() * ScaleObj() * InitObjRandom(src=\"support\",amin=0.8,amax=1, phirange=0.5) * cdi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solve the object using RAAR & ER\n",
    "The important parameters below which can affect the reconstruction are the support update ones. You can try:\n",
    "* `SupportUpdate(threshold_relative=0.12, method='max', smooth_width=(2,0.5,600))`\n",
    "* `SupportUpdate(threshold_relative=0.3, method='rms', smooth_width=(2,0.5,600))`\n",
    "\n",
    "both should work in this case, but depending on datasets one may work better than the other\n",
    "\n",
    "See the other support update options by typing `SupportUpdate?`\n",
    "\n",
    "You can make more complex combinations of algorithms simply by multiplying the operators (ER, HIO, RAAR, SupportUpdate, CF,...) as you see fit.\n",
    "\n",
    "Note that the recipe below should work on a majority of trials, but will sometimes fail. You can restart from a random object. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "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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       "<img 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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RAAR #  0 LLK=   7.227[free=  1.501](p), nb photons=2.179479e+06, support:nb=210945 ( 1.257%) <obj>=      3.21 max=   1179.13, out=58.622% dt/cycle=5.7350s \n",
      "RAAR # 50 LLK=   0.947[free=  0.356](p), nb photons=2.932234e+07, support:nb=194218 ( 1.158%) <obj>=     12.29 max=   1314.53, out=8.186% dt/cycle=0.0168s \n",
      "RAAR #100 LLK=   1.010[free=  0.360](p), nb photons=2.977872e+07, support:nb=183784 ( 1.095%) <obj>=     12.73 max=   1282.94, out=8.846% dt/cycle=0.0186s \n",
      "RAAR #150 LLK=   1.003[free=  0.418](p), nb photons=2.962149e+07, support:nb=160305 ( 0.955%) <obj>=     13.59 max=   1269.48, out=8.823% dt/cycle=0.0177s \n",
      "RAAR #200 LLK=   0.822[free=  0.423](p), nb photons=2.887883e+07, support:nb=127109 ( 0.758%) <obj>=     15.07 max=   1236.75, out=7.826% dt/cycle=0.0187s \n",
      "RAAR #250 LLK=   0.698[free=  0.328](p), nb photons=2.860738e+07, support:nb=113786 ( 0.678%) <obj>=     15.86 max=   1244.48, out=5.599% dt/cycle=0.0177s \n",
      "RAAR #300 LLK=   0.714[free=  0.334](p), nb photons=2.878732e+07, support:nb=112895 ( 0.673%) <obj>=     15.97 max=   1243.28, out=5.733% dt/cycle=0.0178s \n",
      "RAAR #350 LLK=   0.714[free=  0.319](p), nb photons=2.877460e+07, support:nb=112568 ( 0.671%) <obj>=     15.99 max=   1242.78, out=5.607% dt/cycle=0.0178s \n",
      "RAAR #400 LLK=   0.740[free=  0.320](p), nb photons=2.908311e+07, support:nb=112756 ( 0.672%) <obj>=     16.06 max=   1240.86, out=5.705% dt/cycle=0.0187s \n",
      "RAAR #450 LLK=   0.727[free=  0.312](p), nb photons=2.888538e+07, support:nb=112447 ( 0.670%) <obj>=     16.03 max=   1240.93, out=5.574% dt/cycle=0.0178s \n",
      "RAAR #500 LLK=   0.762[free=  0.314](p), nb photons=2.928423e+07, support:nb=111626 ( 0.665%) <obj>=     16.20 max=   1237.93, out=5.755% dt/cycle=0.0177s \n",
      "RAAR #550 LLK=   0.756[free=  0.297](p), nb photons=2.915630e+07, support:nb=111377 ( 0.664%) <obj>=     16.18 max=   1238.50, out=5.603% dt/cycle=0.0176s \n",
      "RAAR #600 LLK=   0.814[free=  0.298](p), nb photons=2.981764e+07, support:nb=111229 ( 0.663%) <obj>=     16.37 max=   1234.73, out=5.779% dt/cycle=0.0188s \n",
      "RAAR #650 LLK=   0.782[free=  0.291](p), nb photons=2.935410e+07, support:nb=111182 ( 0.663%) <obj>=     16.25 max=   1236.16, out=5.630% dt/cycle=0.0182s \n",
      "RAAR #700 LLK=   0.821[free=  0.295](p), nb photons=2.990288e+07, support:nb=110975 ( 0.661%) <obj>=     16.42 max=   1234.33, out=5.776% dt/cycle=0.0181s \n",
      "RAAR #750 LLK=   0.783[free=  0.288](p), nb photons=2.939798e+07, support:nb=111037 ( 0.662%) <obj>=     16.27 max=   1236.30, out=5.602% dt/cycle=0.0178s \n",
      "  ER #800 LLK=   0.825[free=  0.296](p), nb photons=2.994033e+07, support:nb=111173 ( 0.663%) <obj>=     16.41 max=   1234.34, out=5.768% dt/cycle=0.0185s \n",
      "  ER #850 LLK=   0.194[free=  0.202](p), nb photons=2.499268e+07, support:nb= 99371 ( 0.592%) <obj>=     15.86 max=   1239.46, out=3.224% dt/cycle=0.0173s \n",
      "  ER #900 LLK=   0.193[free=  0.200](p), nb photons=2.499960e+07, support:nb= 98171 ( 0.585%) <obj>=     15.96 max=   1236.96, out=3.268% dt/cycle=0.0170s \n",
      "  ER #950 LLK=   0.193[free=  0.200](p), nb photons=2.500156e+07, support:nb= 97815 ( 0.583%) <obj>=     15.99 max=   1235.99, out=3.265% dt/cycle=0.0167s \n"
     ]
    }
   ],
   "source": [
    "sup = SupportUpdate(threshold_relative=0.3, method='rms', smooth_width=(2,0.5,600))\n",
    "plt.figure()\n",
    "cdi = (sup * RAAR(beta=0.9, calc_llk=50, show_cdi=50)**20)**40 * cdi\n",
    "cdi = (sup * ER(calc_llk=50, show_cdi=50)**20)**10 * cdi\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save result in a CXI file\n",
    "Type `cdi.save_obj_cxi?` to get the full documentation about the function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# cdi.save_obj_cxi(\"result.cxi\")"
   ]
  }
 ],
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