demos/dpc/dpc_demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Differential Phase Contrast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "current_folder = /home/edill/dev/python/scikit-beam-examples/demos/dpc\n",
      "/home/edill/dev/python/scikit-beam-examples/demos/dpc/SOFC does not exist\n"
     ]
    }
   ],
   "source": [
    "# Download the data for this notebook\n",
    "import download\n",
    "download.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### notebook requirements\n",
    "- clint\n",
    "- matplotlib\n",
    "- scipy\n",
    "- numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fetching package metadata: ..........\n",
      "Solving package specifications: ............\n",
      "# All requested packages already installed.\n",
      "# packages in environment at /home/edill/mc/envs/beam35:\n",
      "#\n",
      "clint                     0.5.1                    py35_0    file:///home/edill/mc/conda-bld/linux-64/clint-0.5.1-py35_0.tar.bz2\n",
      "Fetching package metadata: ........\n",
      "Solving package specifications: ..............................\n",
      "# All requested packages already installed.\n",
      "# packages in environment at /home/edill/mc/envs/beam35:\n",
      "#\n",
      "matplotlib                1.5.1               np110py35_0  \n",
      "numpy                     1.10.2                   py35_0  \n",
      "scipy                     0.16.1              np110py35_0  \n"
     ]
    }
   ],
   "source": [
    "# install the dependencies for this notebooks\n",
    "!conda install -c ericdill clint --yes\n",
    "!conda install scipy numpy matplotlib --yes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# all the imports\n",
    "import os\n",
    "import tempfile\n",
    "from subprocess import call\n",
    "import scipy\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from pims import ImageSequence\n",
    "import zipfile\n",
    "import time as ttime\n",
    "from skbeam.core import dpc\n",
    "%matplotlib notebook\n",
    "\n",
    "dpc.logger.setLevel(dpc.logging.DEBUG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Set parameters\n",
    "start_point = [1, 0]\n",
    "first_image = 1\n",
    "pixel_size = (55, 55)\n",
    "focus_to_det = 1.46e6\n",
    "scan_xstep = 0.1\n",
    "scan_ystep = 0.1\n",
    "scan_rows = 121\n",
    "scan_cols = 121\n",
    "energy = 19.5\n",
    "roi = None\n",
    "padding = 0\n",
    "weighting = 1.\n",
    "bad_pixels = None\n",
    "solver = 'Nelder-Mead'\n",
    "images = ImageSequence(os.path.join('SOFC', '*.tif'))\n",
    "img_size = images[0].shape\n",
    "ref_image = np.ones(img_size)\n",
    "scale = True\n",
    "negate = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Demo the incremental updates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "/* Put everything inside the global mpl namespace */\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('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",
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       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
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       "    this.imageObj = new Image();\n",
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       "    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",
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       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
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       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
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       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, 0, fig.canvas.width, fig.canvas.height);\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",
       "    {\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.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",
       "            /* 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",
       "            evt.data.type = \"image/png\";\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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\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",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             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",
       "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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";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.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",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\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).html('<img src=\"' + dataURL + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\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",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(nrows=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dpc_gen = dpc.lazy_dpc(ref_image, images, start_point, scan_rows, \n",
    "                       scan_cols, solver, roi, bad_pixels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processing 0\n",
      "processing 100\n",
      "processing 200\n",
      "processing 300\n",
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      "processing 500\n",
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      "processing 14600\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/edill/dev/python/scikit-beam/skbeam/core/dpc.py:275: RuntimeWarning: invalid value encountered in true_divide\n",
      "  c = -1j * (kappax * tx * (1 - weighting) + kappay * ty * weighting) / div_v\n"
     ]
    }
   ],
   "source": [
    "for idx, intermediate_state in enumerate(dpc_gen):\n",
    "    if idx % 100 == 0:\n",
    "        print('processing %s' % idx)\n",
    "        phase, amplitude = dpc.reconstruct_phase_from_partial_info(\n",
    "            intermediate_state, energy, scan_xstep, scan_ystep, pixel_size[0], \n",
    "            focus_to_det, negate, padding, weighting)\n",
    "        ax1.imshow(phase, cmap='viridis')\n",
    "        ax2.imshow(amplitude, cmap='viridis')\n",
    "        fig.canvas.draw()\n",
    "        ttime.sleep(0.01)\n",
    "# provide a final update\n",
    "ax1.imshow(phase, cmap='viridis')\n",
    "ax2.imshow(amplitude, cmap='viridis')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Demo the non-generator implementation. \n",
    "Note that this takes a long time to run! "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/edill/dev/python/scikit-beam/skbeam/core/dpc.py:275: RuntimeWarning: invalid value encountered in true_divide\n",
      "  c = -1j * (kappax * tx * (1 - weighting) + kappay * ty * weighting) / div_v\n"
     ]
    }
   ],
   "source": [
    "# Use skxray.dpc.dpc_runner\n",
    "phase, amplitude = dpc.dpc_runner(\n",
    "    ref_image, images, start_point, pixel_size, focus_to_det, scan_rows,\n",
    "    scan_cols, scan_xstep, scan_ystep, energy, padding, weighting, solver,\n",
    "    roi, bad_pixels, negate, scale)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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",
       "            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",
       "        this.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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, 0, fig.canvas.width, fig.canvas.height);\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",
       "    {\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.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",
       "            /* 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",
       "            evt.data.type = \"image/png\";\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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\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",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             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",
       "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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";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.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",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\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).html('<img src=\"' + dataURL + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\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",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f362c632080>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# display results\n",
    "fig, ax = plt.subplots(ncols=2)\n",
    "ax[0].imshow(phase, cmap='gray')\n",
    "ax[1].imshow(amplitude, cmap='gray')\n",
    "ax[0].set_title('Phase')\n",
    "ax[1].set_title('Amplitude')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import skbeam\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.0.6+6.gbb38d11.dirty'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "skbeam.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "gist": {
   "data": {
    "description": "demos/dpc/dpc_demo.ipynb",
    "public": true
   },
   "id": ""
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}