Edge spread function analysis.ipynb

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    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy\n",
    "import scipy.signal\n",
    "%matplotlib notebook"
   ]
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    "## Calculate a perfect Airy disc from a given NA\n",
    "The theoretical point spread function from an imaging system consisting of a perfect thin lens is the diffraction pattern of a disc aperture.  From Goodman (pp. 76--8) we have the result that the amplitude in the sample plane is proportional to:\n",
    "$$\\left| \\frac{J_1(2\\pi\\omega\\rho)}{\\pi\\omega\\rho}\\right|^2$$\n",
    "This is for the Fraunhofer diffraction pattern of a disc with radius $\\omega$ as a function of spatial frequency $\\rho=\\sqrt{f^2_x + f^2_y}=kr/2\\pi z$ where $k$ is the wavenumber, $r$ is radius in the sample, and $z$ is the distance from the aperture to the observation plane.  In our case, the aperture size $\\omega$ is specified by the NA of the objective.  This is defined in terms of the angle of the rays farthest from the optical axis - $NA = n\\sin\\alpha$ where $\\alpha$ is the angle between the edge rays and the optical axis, and $n$ is the refractive index of the immersion medium, here air ($n=1$) or oil ($n=1.52$ for $100\\times$ objectives only).  As we are operating in the far-field approximation (because the objective lens is designed to perform a Fourier transform) As the wavenumber depends on refractive index ($k=nk_0$ where $k_0$ is wavenumber in vacuum)."
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    "## Calculate an edge response function from NA\n",
    "To try and avoid any approximations at all, we could just do it numerically.  In this case, the image of an edge can be generated by creating an edge image (with a perfectly sharp edge) then cropping it to a disc in the Fourier plane, and transforming back to get the original edge.  As that image is a function only of x (and not y), the truncation in the Fourier plane might as well also be 1D.  That means that the line response (which should be the vertically-integrated Bessel function) can be calculated analytically as a sinc function, and the edge response should just be a convolution of that with the edge.\n",
    "\n",
    "The line response function for a pupil that collects a maximum transverse wavenumber $k_p$ is:\n",
    "$$lsf(x) = \\int_{-\\infty}^\\infty P(k_x)e^{jk_xx}\\mathrm{d}k_x = \\int_{-k_p}^{k_p}e^{jk_xx}\\mathrm{d}k_x \\propto \\frac{\\sin(k_px)}{x}$$\n",
    "We can integrate this to find the line response, but it's probably as easy to do that numerically.  It's worth noting that the image should be assymetric - because the two levels are zero and non-zero, fluctuations around zero will tend to be suppressed while those around the bright edge will appear bigger."
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    "For an objective with $NA=1.3$, we would expect a PSF with $k_p=\\frac{1.3\\times2\\pi}{\\lambda}$ which in this case will be:"
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       " * 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\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 overridden (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",
       "    var width = fig.canvas.width/mpl.ratio\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 + '\" 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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { 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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\" width=\"662.6666666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f44fec9f950>]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kp = 1.3 * 2 * np.pi/0.53 # for green light\n",
    "x = np.linspace(-1, 1, 400)\n",
    "dx = np.mean(np.diff(x))\n",
    "lsf = np.sinc(kp * x / np.pi) # numpy defines sinc as sin(pi*x)/(pi*x) for some reason...\n",
    "edge = np.cumsum(lsf)**2\n",
    "recovered_lsf = np.diff([0] + list(edge))\n",
    "recovered_lsf /= np.max(recovered_lsf)\n",
    "\n",
    "# We can, of course, recover it more or less perfectly by taking a square root\n",
    "# (the more or less part is because we get sign errors)\n",
    "recovered_lsf_2 = np.diff([0] + list(edge**0.5))**2\n",
    "\n",
    "f, ax = plt.subplots(1,2)\n",
    "ax[0].plot(x, lsf**2)\n",
    "ax[1].plot(x, edge)\n",
    "ax[0].plot(x, recovered_lsf)\n",
    "ax[0].plot(x, recovered_lsf_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that:\n",
    "* The recovered line spread function from differentiating the edge is not the same as the true one, because we measure intensity (amplitude squared).  That also means:\n",
    "    * The mid-point of the intensity is not the true position of the edge (again because of the squaring)\n",
    "    * The \"ringing\" is only on the bright side of the edge, not the dark side.\n",
    "* ``numpy.sinc`` has an extra factor of $\\pi$ in it!\n",
    "* The FWHM of the recovered lsf is something like $180\\,$nm.  That is a little less than half what I'm seeing :(\n",
    "* The maths above is correct for *fully coherent* light.  This is correct in the limit of low-NA illumination in the microscope.  Fully incoherent light requires a larger illumination NA than collection NA (i.e. a very impressive oil-immersion condenser).  Realistically, though, this microscope has partially coherent illumination, as it does use a condenser lens with a non-zero NA.\n",
    "* See J. W. Goocman, \"Introduction to Fourier Optics\", third edition, Chapter 6.2, pp135-138"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\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 * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\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'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\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 overridden (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",
       "    var width = fig.canvas.width/mpl.ratio\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 + '\" 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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { 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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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f45202f8fd0>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kps = 1.25 * 2 * np.pi/np.linspace(0.4,0.6, 100) # for green light (and a numerical aperture of 1.25)\n",
    "x = np.linspace(-1, 1, 400)\n",
    "dx = np.mean(np.diff(x))\n",
    "lsf = np.zeros_like(x)\n",
    "for kp in kps:\n",
    "    lsf += np.sinc(kp * x / np.pi) # numpy defines sinc as sin(pi*x)/(pi*x) for some reason...\n",
    "lsf /= float(len(kps))\n",
    "edge = np.cumsum(lsf)**2\n",
    "recovered_lsf = np.diff([0] + list(edge))\n",
    "recovered_lsf /= np.max(recovered_lsf)\n",
    "\n",
    "f, ax = plt.subplots(1,2)\n",
    "ax[0].plot(x, lsf**2)\n",
    "ax[1].plot(x, edge)\n",
    "ax[0].plot(x, recovered_lsf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis of real images\n",
    "To compare this to experiment, I've taken lots of images of edges - generally as closely-spaced Z stacks, so that it's possible to be sure we've got the right plane.  The code below should load the (raw and JPEG) images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\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 * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\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'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\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 overridden (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",
       "    var width = fig.canvas.width/mpl.ratio\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 + '\" 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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { 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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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The loaded array has shape: (2464, 3280, 3)\n"
     ]
    }
   ],
   "source": [
    "from extract_raw_image import load_raw_image\n",
    "pi_bayer_array, jpeg, exif = load_raw_image(\"datasets/20180615_tanzania_characterisation/40x_plan_ac127_kohler/vertical_edge_zstack/image_010_x491859_y444923_z121551.jpg\", open_jpeg=True) # 10-bit values in 16-bit integers\n",
    "bayer = pi_bayer_array.array # this is a 3D array with 3 colour planes, but each colour plane includes only pixels with the relevant colour filter.\n",
    "plt.figure()\n",
    "plt.imshow(jpeg)\n",
    "print \"The loaded array has shape: {}\".format(bayer.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For ease of processing, we first flip/transpose the image so that it's always a vertical edge going from black to white, then fit a straight line to the edge so we can average along it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.   0.25 0.  ]\n",
      " [0.25 1.   0.25]\n",
      " [0.   0.25 0.  ]]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "analyse_edge_image.py:24: UserWarning: \n",
      "This call to matplotlib.use() has no effect because the backend has already\n",
      "been chosen; matplotlib.use() must be called *before* pylab, matplotlib.pyplot,\n",
      "or matplotlib.backends is imported for the first time.\n",
      "\n",
      "The backend was *originally* set to 'nbAgg' by the following code:\n",
      "  File \"/usr/lib/python2.7/runpy.py\", line 174, in _run_module_as_main\n",
      "    \"__main__\", fname, loader, pkg_name)\n",
      "  File \"/usr/lib/python2.7/runpy.py\", line 72, in _run_code\n",
      "    exec code in run_globals\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/lib/python2.7/site-packages/ipykernel_launcher.py\", line 16, in <module>\n",
      "    app.launch_new_instance()\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/traitlets/config/application.py\", line 658, in launch_instance\n",
      "    app.start()\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/ipykernel/kernelapp.py\", line 499, in start\n",
      "    self.io_loop.start()\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/tornado/ioloop.py\", line 1017, in start\n",
      "    self._run_callback(self._callbacks.popleft())\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/tornado/ioloop.py\", line 758, in _run_callback\n",
      "    ret = callback()\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/tornado/stack_context.py\", line 300, in null_wrapper\n",
      "    return fn(*args, **kwargs)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py\", line 542, in <lambda>\n",
      "    self.io_loop.add_callback(lambda : self._handle_events(self.socket, 0))\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py\", line 456, in _handle_events\n",
      "    self._handle_recv()\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py\", line 486, in _handle_recv\n",
      "    self._run_callback(callback, msg)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py\", line 438, in _run_callback\n",
      "    callback(*args, **kwargs)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/tornado/stack_context.py\", line 300, in null_wrapper\n",
      "    return fn(*args, **kwargs)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/ipykernel/kernelbase.py\", line 283, in dispatcher\n",
      "    return self.dispatch_shell(stream, msg)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/ipykernel/kernelbase.py\", line 233, in dispatch_shell\n",
      "    handler(stream, idents, msg)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/ipykernel/kernelbase.py\", line 399, in execute_request\n",
      "    user_expressions, allow_stdin)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/ipykernel/ipkernel.py\", line 208, in do_execute\n",
      "    res = shell.run_cell(code, store_history=store_history, silent=silent)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/ipykernel/zmqshell.py\", line 537, in run_cell\n",
      "    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/IPython/core/interactiveshell.py\", line 2714, in run_cell\n",
      "    interactivity=interactivity, compiler=compiler, result=result)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/IPython/core/interactiveshell.py\", line 2824, in run_ast_nodes\n",
      "    if self.run_code(code, result):\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/IPython/core/interactiveshell.py\", line 2878, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-4-263ce38b540a>\", line 5, in <module>\n",
      "    get_ipython().magic(u'matplotlib notebook')\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/IPython/core/interactiveshell.py\", line 2160, in magic\n",
      "    return self.run_line_magic(magic_name, magic_arg_s)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/IPython/core/interactiveshell.py\", line 2081, in run_line_magic\n",
      "    result = fn(*args,**kwargs)\n",
      "  File \"</mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/decorator.pyc:decorator-gen-105>\", line 2, in matplotlib\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/IPython/core/magic.py\", line 188, in <lambda>\n",
      "    call = lambda f, *a, **k: f(*a, **k)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/IPython/core/magics/pylab.py\", line 100, in matplotlib\n",
      "    gui, backend = self.shell.enable_matplotlib(args.gui)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/IPython/core/interactiveshell.py\", line 2966, in enable_matplotlib\n",
      "    pt.activate_matplotlib(backend)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/IPython/core/pylabtools.py\", line 315, in activate_matplotlib\n",
      "    matplotlib.pyplot.switch_backend(backend)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/matplotlib/pyplot.py\", line 231, in switch_backend\n",
      "    matplotlib.use(newbackend, warn=False, force=True)\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/matplotlib/__init__.py\", line 1422, in use\n",
      "    reload(sys.modules['matplotlib.backends'])\n",
      "  File \"/mnt/c/Users/rwb34/dev/nplab/venv/local/lib/python2.7/site-packages/matplotlib/backends/__init__.py\", line 17, in <module>\n",
      "    line for line in traceback.format_stack()\n",
      "\n",
      "\n",
      "  matplotlib.use('Agg')\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\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 * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\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'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\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 overridden (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",
       "    var width = fig.canvas.width/mpl.ratio\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 + '\" 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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { 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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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f4512f32690>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edge_slice = (slice(1182,1282), slice(1375,1675), slice(None)) #define the region we're looking at\n",
    "raw_image = bayer[edge_slice]\n",
    "kernel_rb = np.array([[1,2,1],\n",
    "                      [2,4,2],\n",
    "                      [1,2,1]])/4.0\n",
    "kernel_g = np.array([[0,1,0],\n",
    "                     [1,4,1],\n",
    "                     [0,1,0]])/4.0\n",
    "kernel = np.stack([kernel_rb, kernel_g, kernel_rb], axis=2)\n",
    "demosaiced = scipy.signal.convolve(raw_image, kernel, mode=\"same\")\n",
    "\n",
    "from analyse_distortion import find_edge_orientation, find_edge, reduce_1d\n",
    "from analyse_edge_image import locate_edge, reorient_image\n",
    "\n",
    "# Ensure the images are black-white step functions\n",
    "vertical, falling, line = locate_edge(demosaiced)\n",
    "image = reorient_image(demosaiced, vertical, falling)\n",
    "raw_image = reorient_image(raw_image, vertical, falling)\n",
    "\n",
    "# Find the step in each row of the image, then fit a straight line\n",
    "xs, ys = find_edge((image/4).sum(axis=2), fuzziness=10)\n",
    "#line = np.polyfit(xs, ys, 1)\n",
    "\n",
    "print(kernel[:,:,1])\n",
    "plt.figure()\n",
    "plt.imshow(image[:,:,1])\n",
    "plt.plot(ys, xs, color=\"red\")\n",
    "#plt.plot(xs*line[0]+line[1], xs, color=\"white\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After arranging the image correctly and fitting the line, we average together the rows of the image.  These are first shifted (according to the line fitted in the previous step) to avoid blurring the line.  In fact, this allows us to do sub-pixel sampling, because a not-quite-vertical edge is not always in the same place relative to the pixel boundaries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\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 * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\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'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\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 overridden (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",
       "    var width = fig.canvas.width/mpl.ratio\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 + '\" 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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { 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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\" width=\"518\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from analyse_edge_image import deduce_bayer_pattern\n",
    "\n",
    "f, ax = plt.subplots(1,2, sharex=True, sharey=True)\n",
    "\n",
    "def extract_aligned_edge(raw_image, width, channel=1, force_tx=None, thresholds=(0.25,0.75)):\n",
    "    \"\"\"Extract x, I coordinates for each row of the image, aligned to the edge\n",
    "    \n",
    "    raw_image should be an NxMx3 RGB image, with the dark-bright transition along the middle axis\n",
    "    width will be the width of the output rows (should be less than the width of the raw image)\n",
    "        NB this width is relative to the original image - as each row will only contain the \n",
    "        pixels with the selected colour, the rows will have half this many points.\n",
    "    channel is the channel of the image to extract (0-2)\n",
    "    thresholds specifies the region of I (relative to min/max)\n",
    "    \n",
    "    Return Value: [(x, I, tx)]\n",
    "    x and I are cropped 1D arrays, each representing the x and I coordinates for one row.  The range of x\n",
    "    will be approximately -widdth/2 to width/2, though there will usually be width/2 points.  tx is the \n",
    "    x coordinate where the transition was detected (i.e. the shift between the x coordinates and the pixels\n",
    "    of the original image).\n",
    "    \"\"\"\n",
    "    bayer = deduce_bayer_pattern(raw_image)[:,:,channel]\n",
    "    aligned_rows = []\n",
    "    for i in range(raw_image.shape[0]):\n",
    "        row_bayer = bayer[i % bayer.shape[0], :]\n",
    "        if np.any(row_bayer): # if there are active pixels of this channel in this row\n",
    "            x = np.argmax(row_bayer) # find the position of the first relevant pixel in the row\n",
    "            active_pixel_slice = slice(x, None, bayer.shape[1]) \n",
    "                # This slice object takes every other pixel, starting at x (x==0 or 1)\n",
    "\n",
    "            # Extract the position and intensity of all of the pixels that are active\n",
    "            x = np.arange(raw_image.shape[1])[active_pixel_slice]\n",
    "            I = raw_image[i,active_pixel_slice,channel]\n",
    "\n",
    "            # Crop out the part where it goes from black to white (from 25% to 75% intensity)\n",
    "            normI = (I - np.min(I) + 0.0)/(np.max(I)-np.min(I)) # NB the +0.0 converts to floating point\n",
    "            start = np.argmax(normI > thresholds[0])\n",
    "            stop = np.argmax(normI > thresholds[1])\n",
    "\n",
    "            # Fit a line and find the point where it crosses 0.5\n",
    "            gradient, intercept = np.polyfit(x[start:stop], normI[start:stop], 1)\n",
    "            transition_x = (0.5 - intercept)/gradient # 0.5 = intercept + gradient*xt\n",
    "            \n",
    "            # Now, crop out a region centered on the transition\n",
    "            start = np.argmax(x > transition_x - width/2.0)\n",
    "            #stop = np.argmax(x > transition_x + width/2.0)\n",
    "            stop = start + width//row_bayer.shape[0] # Should do the same as above, but guarantees length.\n",
    "            aligned_rows.append((x[start:stop] - transition_x, I[start:stop], transition_x))\n",
    "    return aligned_rows\n",
    "    \n",
    "aligned_rows = extract_aligned_edge(raw_image, width=100, channel=1)\n",
    "txs = np.array([tx for x, I, tx in aligned_rows])\n",
    "\n",
    "for x, I, tx in aligned_rows:\n",
    "    # Manually add back in the transition point shift to get un-aligned rows (!)\n",
    "    ax[0].plot(x + tx - np.mean(txs), I)\n",
    "    ax[1].plot(x, I)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The left plot shows the intensity (of the green channel) vs x position, while the right plot shows the same, but with a slight shift applied to each row so that they are aligned.  We've not done any resampling yet, just shifted the x coordinates.  NB the spacing between the points on this graph will be 2 pixels, because we only use pixels that have the correct colour Bayer filter on top of them.  If ``c==0 or 2`` (i.e. red/blue channels) we'll also only be plotting every other row.  Below, we plot the shift amount as a sanity check."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\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 * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\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'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\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 overridden (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",
       "    var width = fig.canvas.width/mpl.ratio\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 + '\" 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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { 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"
    },
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n7po9q8AJsH4XDwEwBaGDgYAAAAQfIVVjXLw2mdcPMUdZ2WNhs7b73L+mK+Py89P2XWSiJR1gXflVZr9K4BJMD4XDwGwhaGDAQAAAATfkXN1cvDaf1oS5ZVfUSS5UtcCHrX6qPz8Z/vPEhHRi8sy5Mc2HS0T8WuACTA+Fw8BsIWhgwEAAAAEX9JJltTqybn7qK6pVbEk+rKqFjBfM3h7bgUREY1cdUR+bHV6iYDfAsyA8bl4CIAtDB0MAAAAIPi2ZpfLwetvPk0nh8NB945nZY3yK+oV5w+Yliw/l1F8iYiI3l6XJT+2dJ9r5miwBozPxUMAbGHoYAAAAADBt+rgOTl4/dM3Sa+e5JJaJeSzWsB2u4N6cSWTimuuEhHRB5uOyY/N3XNayO8BwYfxuXgIgC0MHQwAAAAg+Piszu9t7Mzq/Dq3pHnFgbPyuTWN1xXLo69ebyciorHbWGKsqbaTQn4PCD6Mz8VDAGxh6GAAAAAAwTd510k5eB3/Td3fcdvy5ccm7jghn5tfUS8/fu/4BPnxaXGn5MfHbjtu+u8A5sD4XDwEwBaGDgYAAAAQfP/ezJYvz9ldSEREy/YVy4+NWn1UPjeloFp+fNDHqfLj8/aclh9/f1Ou2b8CmATjc/EQAFsYOhgAAABA8L2xxrWskS2P1QJ+aj6rBbzxSKn8+IvLMuTHl3IB81tfZJn+O4A5MD4XDwGwhaGDAQAAAATfS8tZDd8vM0uJiCi3jNUC7jshUa4FvDCZ7Rd+d0OOfI01GSXy4yNXHRHye0DwYXwuHgJgC0MHAwAAAAi+pxcccMn4XHtVmeyqvrmNiIjGfM2SXU3ZxZJdbT5aJj/+AjczDNaC8bl4CIAtDB0MQkVbh50yii/R5aZW0U0BAAA/VF65Js9ggqtHZ+yVg9f0oloiInI4HNRnXLz8+InKzlrAf+GWSy/fz+r97sqrlB9/dlGakN8Dgg/jc/EQAFsYOhiEinfWZ1NUtI0em7VXLvcAAADhIfqrPIqKttHrWJarq+/ERDl4za+olx8fwtUCTjxRRUREwxanyY9tz62Qz91bcFF+fMjcfab/DmAOjM/FQwBsYehgEApa2jqo1+g4+Ut9S1a56CYBAICXWtvt1DOGLeO9UH9NdJNCjt3uoB7ce1RW1yw/99pKVgv487RzREQ0YFoymy0urpXPTS+ulR9/dMZe038PMAfG5+IhALYwdDAIBXnlLAlIVLSNXluJGQQAgHBxpblV8Rl+6kKD6CaFnPrmNs29vkTK/b4f7TxBdrtDcVO4uOaqfC6fNOuhyXtE/CpgAozPxUMAbGHoYBAKvswsVQwMeo2OozrsBQYACAuVV64pPsMzS+pENynklNU1K96jDjvbK/1pKitt9Jc1R6mmUZkYq7GFBcunLzbKj/cZFy/iVwETYHwuHgJgC0MHg1AwYXu+4ss+KtpG6w6fF90sAADwQlH1VcXn996Ci6KbFHLyK+oV5Y54O4+xxFZPLzhAJyrZufeOT1AkFlMH0nY7ko5ZEcbn4iEAtjB0MAgFLyzNcAmAX1qO8g4AAOHgeHm94vObT9oEndKL9Pfu5pRelp+7f2IipRRUy38f9HGq4lx12aTmViSNtCKMz8VDAGxh6GAgmsPhoL4TEl0C4B4xNrrY0CK6eQAA4MGhs5cUn99fHMIKHrWE/Avy+/OrBQcUz1U3tijev8/2n9Wt9dvc2q44t/bqdTN/DTAJxufiIQC2MHQwEE29nKv/tCSXbJgAABC6+BnLqGgbfZpa7PlFEWZTZpn8/ryoCmodDgfdPZbVAn57XZb853c35CjOtdsdiveazyYN1oHxuXgIgC0MHQxES8ivkr/IH5+VQjMTCuS/D19yUHTzAADAA1veBUVQNjuxQHSTQg4/q/vGmqMuzw+ek6p5I3jyrpMu5/YZx4Ll0xcbzWg+mAzjc/EQAFsYOhiINm/PafmL/K9rs+jUhQbc3QYACCObj5YpPrfHb88X3aSQM2d3ofz+/GvzMZfn/8jVAuaP5ftdZ9MfmrxHfj637IoZzQeTYXwuHgJgC0MHA9H+suao/EW+IOkMORwOGjJ3n/zYJ6lFopsIAABurE4vUQRt73+ZK7pJIYevdjBpp+usbszW45oB8LYc14Rij87YKz+fXlxrRvPBZBifi4cA2MLQwUC0n89kX+R7TnaWzliQdEY3WQgAAIQWvo5tVLSNRq12XeIb6d7bmKO42au2JKVIMwDWCnD5m8QoOWVNGJ+LhwDYwtDBQKT6a22KL/ryy53LnYtrlDUli6qxxwkAIFTN5Zb3aiV5AqI/xWbK78+qg64JHrfnVmgGwEXVV13OfW5xmvz8rrxKM5oPJsP4XDwEwBaGDgYiHeZKZ9w/MZEcDof83K8XHpCfm7fntMBWAgCAO1N2nVQEbb9eiJU7ar/9NF1+f77KKnd5Puv8Zc0AuLGlzeXcF5ZlyM9vOlpmRvPBZBifi4cA2MLQwUCkVQfP6c4YLN3HltQN/jhVERwDAECnuqZWSj51kVraOoS1Qb1/9fFZKcLaEqqe5JYtJ510XbZ8saHFJfi9d3yC5nffyFUsYdaajBITWg9mw/hcPATAFoYOBiJ9uOWY/CU+cccJxXPll5X1gfMr6gW1EgAgNLW22+nh6cm6pXXMwu9vjYq20UOT9whrS6jiSxsdOVfn8rzd7qDeY+IV7+PA2do3Et76gtUJXroPNZetCONz8RAAWxg6GIj0zCK2zFlrGddvuCVj0+NPCWghAEDoOl5eL39G3jUmTthKmTe4bP6i2xKq7hmXIL8/BVUNmucM+jhV8T6+oLOX+v1NufI5c7FFyJIwPhcPAbCFoYOBKG0dduo9Nt7tDG8st0T60Rl7MaACAOAcLKpVBEyilkG/+vlhl+W7Ipdkh5rWdrvivam8ck3zPPX7+Lf12Zrnjd3GlpxPi8PNYSvC+Fw8BMAWhg4GohRWNcpf4HeOjtMcLFU3tlDPGDYYyDp/WUBLAQBCU/zxC4qAqbqhRUg7Rnxy0CUArmm8LqQtoaj26nXFe9N0vV3zvJiteYrzJu9yrRdMRDTVxpKOjd12PJhNB0EwPhcPAbCFoYOBKNtyWMmHofP26573h88O6e4TBgCIZF9mlnosmWOGp+bvdwmAz9aIaUsoOsuV9us1Wn95+OK9ZxTv4TKd/b1z95yWz/lg07FgNh0EwfhcPATAFoYOBqJMizslf4H/88tc3fM2HGEDvJ9OTcIyaACAb3y2/6wiYMouFbNK5onZKS4BcF75FSFtCUW5ZVfk9+XBSbt1z+NvDEdF22hbToXmeXyVhLfXZQWr2SAQxufiIQC2MHQwEIXf67R8v34Wy8tNrYoBwflLTSa2EgAgdM3ZXaj4fEwtrBbSjp9OTXIJgA8W1QppSyjad7rGY2ZnIqKjJXWK9zBd5z1cnV4inzNy1ZFgNRsEwvhcPATAFoYOBiI4HA76yeQ98hd42hn3AyU+M+auvEqTWgkAENombM9XBEw7j4n5fLxvfIJLAJyQf0FIW0LRzmOV8vvy3OI03fOq6pW1gPWWtG86Wiaf86JOpmgIbxifi4cA2MLQwUCE6gbll/ylq+6Tpby7gdWYRDkkAIBO6vq76w6fN70NDoeDesTYXALgzRql7SLVusPn5ffllRWHdc+z2x3yDd+fTU2i6+3ambR35XkXUEP4wvhcPATAFoYOBiKkFFbLX979pyV5PH/5frbf6Q+fHTKhhQAAoe9PsZmKoPPTVP3tJMHS0tbhEvxGRdtoZdo509sSqj5JLZLfl3fWaZc2ciqqvkoLks7QqQvatYKJiJJPXZSvN2TuPqObCyEA43PxEABbGDoYiMAPBrzZv5RezGpd3j8xEYmwAACI6LefpiuCzlkJBaa3oU6Vp8F5LEw+Y3pbAlFW10xf55RTQ0ub4deeEV8gvy8xW/MCvh7/nfjojL0GtBBCDcbn4iEAtjB0MBDhb+uzfRqwNbS0IREWAIDKL+ftU3w2iqgJW1bXrBkAT7Vp17ANRS1tHfTQN3kpRq3ONPz6o78+zrbxxAW+jYfPKv3Q5D0GtBBCDcbn4iEAtjB0MBDhF3NYUitvk7b4mgjLbnfQ3N2FFP1VHlU3tATaZACAkDNgWrIi6Pz7hhzT23D6YqNmAGzETKdZckovy+2+e2y84dd/h7vpuySlKODrFVax97zPOOPbC+JhfC4eAmALQwcDs11r7aCeXMKU4hrtLJdqikRYXtxB38xlyZy440SgzQYACDn3qrIvvy6gJA4/G8kf76x3v9c1lBw4U6Noe0ubdvIpf/Fl/9YeCjxRmXrW3W7HtiCrwfhcPATAFoYOBmbjB0t9xsVTh5df3L4mwnrriyz5/NdWok4iAFhLW4fdJej8zafpprcjvahWMwD+Yxh97sYdv6Boe02j+8oEvhq25KB87e25FQFfr6bxuqK9za3tBrQSQgnG5+KFfQCclZVFM2bMoBEjRtAdd9xBkiSRJPn2aw0ZMkR+XXl5ucvzBQUFNHPmTBo0aBB1796dbrzxRrr99ttpxIgRdODAAb/bvnPnTnriiSfou9/9Ln33u9+lgQMHks1m8/t6auhgYLYNR0rlL+3hSw56/bqM4kteJ8Ky2x30wKTd8vkvoE4iAFjMpavXXYLOJwVkBE46eVEzAB7xifef76J9mVmqaLu3K5O8xW/hSS2sDvh6TdfbFe2t9VBKEMIPxufihX0APHz4cDl45Q9vxcbGkiRJ1KVLF90A2BlYd+vWjZ588kl68cUXqW/fvvLr5s+f73O758+fT5Ik0Y033ki/+tWvaPjw4XTLLbeQJEm0ePFin6+nBR0MzDZuWz63R8z7hC2+JMLKr6hXnPvsItRJBABrOVfb5BJ0DpiWbHo7dhyr1AyARQTj/lpx4Kyi7Tmllw29/k++SbAVFW2jbAOubbc7FO0tq2s2oJUQSjA+Fy/sA+CZM2fS+PHjaefOnVRVVUVdu3b1OgCuqamh2267jYYOHUpRUVG6AfCQIUNo7dq11NKiTLazbNkykiSJbrjhBjp50vuMiIWFhXTDDTdQ165dKSODzV6dPn1anmEuKgo8kQI6GJiNL9vh614o/i66u+RZn+1XDmZQJxEArOaYxt7be8cnmN4Ofvb0ztFx8p8fnm5+MO6veXtOK97HfadrDLu2w+Ggu8aw96Wo2pjZ5bvHxsvXPH2x0ZBrQujA+Fy8sA+A1XwJgF9++WW6+eabqbi42G0A7M7QoUNJkiT66KOPvH7N22+/TZIk0Xvvvefy3Lx580iSJHr33Xd9aocWdDAwk93uoPu4pC1Z5+t8ev3fvUyE9fqqI4rBDOokAoDVqBM3OY+2Drup7ViZdk7+2Y9MZ1mpfzQh0dR2BGLyrpOK99Db6gTeaG5VLleubjSmKsGD3Daf3LIrhlwTQgfG5+JFbACckJBAkiTRlClTiIj8DoA//PBDkiSJ3nzzTa9f8//+3/8jSZIoLc116WZZWRlJkkRRUVE+tUMLOhiY6fwl5ZK9q9d9S9zBz+zqJcJq67ArguyoaNRJBADrseVd0AyALze1mtqOJSlF8s/mkz1FRdu8TnIo2odbjinave5w4JmanarqWxTXNirD9KMz9srXzCi+ZMg1IXRgfC5eRAbATU1N1KNHD7rnnnuotbXzy8TfAPi3v/0tSZJEEyZM8Or8K1euyPuUm5q09zn+4Ac/IEmSqKGhwae2qKGDgZniuUybA2en+Px6PhFWX51EWFnn61wGhKiTCABWwycU9DY/QjDMTiyQf/Yba44q2tLQ0mZqW/z19rosRbs/SQ18i5kTXyfZyBrDv5jDtgTtLbho2HUhNGB8Ll5EBsAffPABSZJE+/axvYP+BMDFxcXyz8vKyvLqNXl5eSRJEn3/+9/XPefBBx8kSZLo+HHvkwhpQQcDM83dXSh/Yb/1hXf9gadOhFVS6zrQW5R8RnNQiDqJAGAly/YVa37WHS+vN7UdH+08If9sPslhVLSNKq5cM7Ut/uLr9EZF22hGfIFh1yIxfJsAACAASURBVM4sYTdlfzo1ybDrPrsoTb6uLe+CYdeF0IDxuXgRFwBnZ2fTDTfcQCNHjlQ87msA3N7eTo899hhJkkQvvfSS1+1LT08nSZLojjvu0D3n5z//OUmSROnp3tX8c3Yk9dG1a1d0MDDNqNWZ8hf2ouQzfl1jsIdEWC8tz9AcFKJOIgBYyayEAs3PuvSiWlPb8Z8tefLPnpVQQPeMY1tQCqvCIznTcNXS7dFfBza5wEs+xcpEGZmQ8YVl7Ltu89Eyw64LoQEBsHgRFQB3dHTQQw89RN27d6faWuWXiK8BsDORVa9evaiuzvtkPwiAwYocDgf1m5IU8JItd4mwWto6qPeYeM1BIeokAoCVjN12XPOzLiHf3NnAd7nP5MV7z9BPp7LP+aMlviU6FIVfThwVbaO/rc827Npf55TL1zWyNvJrK1myxzUZJYZdF0IDAmDxIioAnjNnDkmSRCtXrnR5zpcAeOrUqSRJEt1+++0+lyvCEmiworK6ZsUAo87PRC18IqzfL1cmwjpYVCs/p06EhTqJAGAl/M1A/tiUae5sIL+yZ2XaORrMBZMphdWmtsVf/aclKd7DP648Yti1V6eXyNcducq46771Bdu3vGxfsWHXhdCA8bl4ERUADxw4kLp06UJPPPEEDRw4UHE4X/fwww/TwIEDKSFBu97e0qVLSZIk+t73vke5ubk+tw9JsMCKdhyrDCgBlpO7RFj8ksDXVx1BnUQAsKyRqnJvzmPFgbOmtuMPnx2Sf/bGI6U0bDHbm7rDwHJCwXSv6obp8CXGzdQu5PJS/GNjjmHXfX9TrnzdeXtOG3ZdCA0Yn4sXcQGwM/j0dMTGxrq8fuPGjfStb32LvvOd79DBg/5/gKIMEljNxB0sUco/v/T9xpBTo5tEWPw+rhUHztIDXJ3EY6iTCAAWMuIT9nl315g4+c9zTQ6G+NJH23Mr6JUVLKGUkeWEgqXD7nC5iTB4Tqph15/C1Rgety3fsOuO+ZotgZ+m2g4E4Q/jc/EiKgB2x9MS6Li4OPr2t79NN910E+3evTugNjr3D7/33nsuz82bN48kSaJ33303oJ9BhA4G5uEHSWsD3K+klQiroaWNesawAcyJynp6ZHqy/HfUSQQAKxkyd5/8+fbE7BT5zxN3nDC1Hb+cx9qRdPIi/XVteC3NrW9ucwmA+00xLlszX2N4dqJx2aWn2oITWENowPhcPATA33AXAB88eJBuueUWuvHGG2nbtm1eX7NPnz7Up08fqqioUDxeWFhIN9xwA3Xt2pUOHWL7HM+cOUPdu3enG2+80ee9xVrQwcAMLW0dihmK/IrAynTwe9+cd76TTrJMmw9O2k12u0O5F60gPPaiAQB442dcsqmXV7BlyB9sOmZqO34+c6/8s9OLaunfm1nA93Fioalt8Yc6P0VUtI16G1iv9821rDby8v3G3RDgywqa/W8OwYfxuXhhHwDbbDYaMGCAfHTp0oUkSVI8ZrPZPF7HXQB86623kiRJ1LNnTxo5cqTmsWLFCpfXOZdTl5SUuDznnOm98cYb6emnn6bhw4fTLbfcQpIk0aJFi/x6L9TQwcAMWecvy1/UfcbFU1uHPaDraSXCmrST3Q1/e11njeFnFh2QH0OdRACwEj7HAT/L+Jc1R01tx08m75F/dk7pZcVnsdmz0f44daFBcy91S1uHIdf//XLlHmmjfJpa7PKdB9aB8bl4YR8Ax8bG+rWfV81dAOzNnmF1XWH+dVoBMBHRzp076fHHH6du3bpRt27d6PHHH6ddu3b5+A7oQwcDM6w4wALWF5ZmBHy9Q2ddE2E9NX8/W2J9qHPf2QtLWZ3ELVnelS8DAAh1LW0dimCNT7T04rLAP2N90WccC8QLqxpp7p7T8t/f3+R/vgezHDlXpxkAVze0GHL9Xy9kN2Ljjht3I5bPLv26gdmlITRgfC5e2AfAoA8dDMzwzrps+Yt6enzgyTrUibD4GeaoaBsV11wlIqI/cnUSA913DAAQKmoarys+87Zms1qzTy84YFo77KoEUmV1zYobnmbPRvtjb8FFzQC4qNqYygH8EvGDRbWGXJOIaFNmmbCbHhB8GJ+LhwDYwtDBwAx8MqqE/CpDrsknwuKTrvSfliSXRgq3ZCwAAN4orrkqf7bdOTpOUQP95zP3mtaOpuvtiqDx0tXrtPFIqcsWlVC2PbdCMwDOOn/ZkOvfPzFRvubx8sDyX/B2cqUFn1vsWjEEwhvG5+IhALYwdDAItqr6FsWg4qJBy8r4RFg9uOzP73Mllv75JauTOD8JdRIBwBpyStmql59M3kPHy+vlv98/MdG0dqhnoq+1dpAt74L892cWmTcb7a8vDp3XDIBTCgNPnGi3OxTfT+cvNXl+kZeST7GZ6yfn7jPsuhAaMD4XDwGwhaGDQbDFH2eDoUdnGDczwS+z44/NR8vkc0ZzdRKnh1mdxObWdlqSUkQr086R3e4Q3RwACCH7TtfIn22DPk6l85ea5L/3jLGZ9pnB/9weMTZyOBy0n2vbwNkpprQjEHwyKf7Ynlvh+cUe1F9Tbte53NRqQIs7pXOz/kZ+t0JowPhcPATAFoYOBsE2Le6U/CX9t/XZhl2XT4TFHxVXrsnnTN7FspGO3x5edRI/SS2S277BwMyhABD++OWvwxanUV1Tq+JzsLGlzZR28BmU7xufQERE2arZ6VA3O7FA87vEmUwxEOoSS+0BVkDg8asAHgqD9xl8g/G5eAiALQwdzFqKqq9Sg0kDH2/9bmm6/CX9edo5w66rToSlNdswh6uT+K/N4VUn8W/rWeKwcNhHBwDm4Zftvvr5YWrrsOveCAwmPgFhvylJRERUVN0oP9Z7jHH1dINl/PZ8zQB4SUpRwNc+UcmWpv9ogrFL0wur2Pt8z7gEQ68N4mF8Lh4CYAtDB7OOVQfPUVS0jfpOSKTqRmP22QaqrcOuqFWZXWpMUhGnwXNSFQOWmK3HFc8vSWGzqO8YOPtshtdXsQzWd46OC7kbGwAgDr9C5J11nZ9t945PkB8rqGowpR1pZ9gy3Mdndd6AVOd9uN5uTD3dYHmfyxXBH0ZULEgvZu/PI9OTDWgtU3pJObuMrTLWgvG5eAiALQwdzDqeW5wmfxGuTi8x5Jp2uyOgPUt55VcUMwFGD4T+sTFHMQDYeaxS8bzzpkBUtI3+FJtp6M8ONr6GcVS0jWx5xtWPBIDwNiOeLduN2ZpHRET9pyXJjx05V2dKOxJPVMk/86n5+4nINTN07dXrprTFX6NWH2XfU9wNW+f7GoiEfNf3xyhaCcjAOjA+Fw8BsIWhg1kHP/gZty3w/a6t7XZ6av5+6hljoxUHzvp1jdXpJXKbnv/kYMBtUlMnwlIPtL7MDK9yHLynFxxQ/G7vb8r1/CIAiAhaCf6enLtPfizp5EVT2rEth5UQGvHNZ7zD4aCeXObjklrjMh8Hw4vL2M3GQVx5PefMeiA2HWW1el8wuFavVgkqsA6Mz8VDAGxh6GDW0GFXDjheWh74Fy1fYsHfDJPvcTO0k3aeDLhNanzpj2EadRD5+o7DlhgfgAfT47NSFIObhybvoQ4scQMAUuYIcO5V/c2nLN/C1znlprRj/WF2k/GVFYflx4NV+zYYfr3wgOJ3cP751c8Pe36xB/xN2lGrjxrQWqbD7lB8R5TVNRt6fRAL43PxEABbGDqYNVQ3KPdc9ZsSeEbI5ftZaYgeMf7t43piNgvi1MuTjbI6vYTe3ZBDhVWNLs/tOcmC+KHzjF1+Fmw/mbzHZU9a1nlj91ADQHj640qWI8CZrXgklzfAqG0wnvAB3l/WsADv0Rl75cfTi2tNaYu/+JuN/9mS5/amqq/mcokYP9hkfCJGPsfGmYuu34EQvjA+Fw8BsIWhg1kDv9fWedQFWG8w+qs8xfXO+biMrfaqcn+SWVlJeXyClsdmhVedRH5g4zw+TiwU3SwACAHDlxyUPxec9Wr/voGtuFmUfMaUdixMPiP/zH9szJEff2r+fvnxxBNVprTFXw9xNxsXJLHfZ9DHqQFfe+KOE/L1Ptp5IvDGqjwwabd8/WNlVwy/PoiD8bl4CIAtDB3MGviZTucRaBIUdRKmA2dqfHp9Etemn01NIofD/OW7yhId4VMnUV3SxHn8asEB0U0DgBAwmNurmlJYTUREY7exfcHT4gLPYOwNZTIuloWfL3+3Jcuc5dj+cDgcdNeYOEVbnX82oobxP7kM0/P2nDagxUqPTE+Wr59RfMnw64M4GJ+LhwDYwtDBrIGvCek81h0+H9A1+01JUlxv/eFSn14/O5ENjN5ca+zeJ2+drGyQ23Df+PCpk3iluVUzAI6KtlGlgJl0AAgt/aawWUvn1oiZCewzN/qrwDMYe2MCV0N38i6W5+FPsZny47EHjav/brSWtg7F5ytftuiuMXEB37j9M/c+rEwz/n34BVcKMKWg2vDrgzgYn4uHANjC0MGsgd9n5Dwm7vB/uVVDS5vL9WYmFPh0jT98dkh+7dJ9xX63JRAltU1yG3rE2ITMQvuj/LKyvuNjs9h+ui8OBXZjAwDCm8PhoN5j2BaJourOvZ+fprK8DW+vyzKlLf/afEz+mXN2sy0aIpZj+0NdSkhdWzfQ0kLBngl/ZhFL4IVSedaC8bl4CIAtDB3MGvjEHc6Dz8jpq9wy1z3Ff1vvfUmIDruD7hufYNhybH9dVCUHa2kLjzqJBVVs5vqecQk0aedJ+e9/DrN6xgBgLPWsZXVDCxERrTvMVgIZkcHYG++sY9moP0ktkh8fo1GmKRSd426S9hod5/LeXvzmvfXX0HlsL/TuIOyF5rcqbT5aZvj1QRyMz8VDAGxh6GDWwGf/dB4DpiX7fb2t2eUu1/OljNCpCw2KQUWgd9H9pZ7JvhxgYjCzZJ2vk9vcb0oSHSxiy/LuHhsv7P0EAPHUWf+dN/Z2HKtkn9cGZDD2xus6maenx5+SH+f3BocaPoHkA5N2E5EyAeHpADMrD5jG9ugeOmv8Ht3X+GzgGSWGXx/EwfhcPATAFoYOZg2/WnDAJWCNirZRQ0ubX9f7ONF1SbUvCUH42pDPLBKXuEmdTCpc9s/uO10jt3ng7BRqbbfTjyawupp7Cy6KbiIACFJU3Sh/FvQeGy8/nlpYLT9uRAZjb7y4jM1AbuJmIJekFPm1eshs6dzNxZ/P7KwU8NOpLP/F0ZLAVi/dy62EOnWhwYgmK/x1bZZ8/WWCthpBcGB8Lh4CYAtDB7MGrZqxUdE2yi71r27s2+uyNK/XdL3dq9f/m9sXNm5bvl9tMAqf4bOo+qrQtnjLlnfB5QbCW1+wf5MxX4fujAoABJcyu32S/Hh2qflZ759dlCb/zF15rNb7mowS+fGRq46Y0hZ/JORXye10ZtnnE0sFcrNRfQM2GKUA3w9ylmkQB+Nz8RAAWxg6WPhrbVd+yfLZQTdl+rcniK/hyB/eLgfjBxBf54gtgXH/RDZzml9RL7Qt3tqUWSa3+cVlGUREtPkoe+zh6clhk9ALAIyVUsBmegfPSZUfV8wMj4k35TNCL1jkt9H85tP0oLfDX/zn6gtLOz9rn/+E1VjellPh97UvXVUm2Gr0c0WWO+Gy1xp8h/G5eAiALQwdLPxVXLmm+JJ9l8u+OdV20vMFVOx2B/UZx/ZA9Yxh104+5flueH2zct9tSW2TP7+WYfpPY8vZRCXj8tXKtHNym51Jr2oar1MP7t8iGMvpACD0bc+tkD8HhnO5GfT2BgcTX4eW3+PK16YfOm+/4T+3w+6gxBNVcgkof6066PpZy++rXRPAvlo+wVbPIFUhmLKLJUgUvdoKjIXxuXgIgC0MHSz88cveHpi0m5btY6Uw/Fl6pi7BM4K7G+5NPUd+/+qDk3YLn6kc9DGbodh3ukZoW7y1KPmM3OZ/bMyRHx++hP1bLEkpcnMFALCqtdzy4j+uZJ/xLtmhGwPLYOyNBybtln9eXvkV+fGM4kvy449M9z8ho57l+9n3XNZ5/29sLtT4rOVvIi/e638Jp2Nlrgm2jMaXQPxg07Gg/AwQA+Nz8RAAWxg6WPhLyGf7RYfO2097C9id90dn7PX5evu5AHbAtGSK2cpKLE3e5XlGeX7Safn8P4VAyR4+QVhCfnjUSZwexzKojub2+/KDtRGfeJ+VGwCsQy/BlMPhMD3ngVY9YiKi/Ip6+fG+ExMN/7mvfn5Yvv6knb6vdHKaxn3Wjt3W+VnLLyueFsCyYv679PFZKX5fxx2+9vM760I32Rj4DuNz8RAAWxg6WPhbnc5mA179/DCV1SlncL1NXOUUyy0J+8NnhxSDrTfWHPX4+r+sOSqfvyDJ/7vnRvnNp+lye7Zmi92P7C29ARg/qOwRY6NLV68LbCUAiKB3g4xImRDR3ySI3mp3k+Sp9FKz4rPKbjd2JdBzi1nyrUBuBvI3eGcmFBAR0cyEAvmx6K/y/L72rjxWlurZRcEpS8V/X78ewsnGwHcYn4uHANjC0MHC3yzuy/pfm4+57OHll6V5Y8L2fMUdcb62pDNLpjtPzE6Rz088UeXvr2WYV1awmYJ1h8+Lbo5X3tvIluAtTGY3ERwOh2JP81dZ4RHQA4BxtII2JzO3fKjrrF9pZnXW65paFc8ZnQDqsVl75Wv3HhtPbR12v67zt/XZLttKlnLbiN76IsvvNvLlAF9eccjv67jDJ0x8aXlGUH4GiIHxuXgIgC0MHSz8fbCJlRyandg5GHpm0QG/gyR+adnKtHOUw+0x9rSUrbm1XZGo6fwlsQmwiJQz0isOnBXdHK+MWp0pt/nzNOW+65itbHb4nRCurwkQqZqut9OHW47RO+uz6WKD8ftw31nHgrZPU5W1X/mZ0Z3HKnWuYIyLqqRb19tZ0i11dYIL9caWAOrL1UWPirbR8XL/MvzzCa/WfpPwyqjAlV+eHEgg7Q5/g3rY4uDMMoMYGJ+LhwDYwtDBwh8fsDq/wP/J1QacEV/g/gIqj85gd9ZTCqupVlXKob5Z/04+n/Sjz7h4w5e9+ePvXEKTRcnil2R746XlGXKbv8wsVTyXxGVX7Tsh0e+ZDwAIji8OnZf76PR440vTuFvVYuaKl7M1V+Wf1Wt0nEvCw7vHspVI3pbQ84a6vm5UtI3WHvLvd+W3yDhL9hm1dNmopdTu8N8HT87dF5SfAWJgfC4eAmALQwcLf7+ct89lyTG/b3fUas/7dp2utSqziJZeaiaHw0H3jEuQH3NXS3cTV1PxuRC5Gx39lf5ywVD17CI2i7MrTzmL09zaTr25gWV6ca2gVgKAFn6P7l/XGj/z526W9+11WfJzS/cV61zBGJ4SXfWbwrZrBFquiFfTqLwpGxXtfwZk/vsz6WRnmT8+edUTs/1PXmVUMi130otq5Z/x85m+J72E0IXxuXgIgC0MHSz8/fgjVoYit6xzv+/uE1XyYwN9+AI/Wdkgv6732Hjq+GYG98m5bJAQf1w/kzJfk/Bfm0OjJMNHO0/IbZq444To5niF38eXWljt8jy/bC8YM0wA4L+x21jgE4y9nwO5PAvqfb7/2cJu+M0K8g2/zJI6+Wf1n5bk8rynzzF/nbnY6BIAD/Fz9lOrjnEut5LpQT/LFxVVX6XBc9jvH0g5JXf4Mog/mbwnKD8DxMD4XDwEwBaGDhbe1HUfnfus+KVpPWNs1NLW4eFKnfilX7+cxwYUf4ple1KX79efVeCXY4fKfls+Sdh/tgRnGZrRfjqVzZwcLXGtcbkyjWX+fGr+fgEtBAA973NbUIKR/fchLtNzjirT81QbuwnpLOsTLHzN90Efp7o8H6z9yEfO1Sm+96KiOzNNN/iRaIvfS3yisnN1k6el3e60tttpUfIZRXkofnm10Qqq2E3re8YlBOVngBgYn4uHANjC0MHCm7rUhHM/aHuHXfEFfLKywavrLeLqzPJL9/jM0OO25eu+/mdc4LY/yBlIvbV4L/ud/r4hx+P5+RX19Pvlh2jijhPC9jDfO54tOT91wfXfrpgboEVF24KSaAcA/PPmWpZ4z5cVON5wOBx052hW67e4Rlnrl/8M/8dGz593gYg/zmrQP61RIeDlFYfk5zccKdW4gn/4FU78cbDIt+0gdrtDkbSx9FIzEZFL3gtvSwkeK7tCT83f79Kuf2zMUSQIMxI/BoiKtvkUrENow/hcPATAFoYOFt74JWj9piiXoPFfxNtzK7y6Hp88i98vu+LAWflxvVqDl1VlL0IlKOPb7s1+aD4Dc9oZ8/fXdtgdivexrK7Z5RyHw0E/n8mSlW0+WmZ6OwFAG78Sxuhlqc2t7YrPh1pVLXAz68J+lVUu/6zfLU13eZ6/EeBu5ZCv+NI//OEsY+StRlUZp8tNnWWcfM1g3dzaTpN3naSeMcr29J+WRHu+2VccLNWNykzc11qDE2iD+TA+Fw8BsIWhg4U3fsnyrxcq78Dz9Q3n7C706nrDuCVrfFCVkM/uuOvttTp89pJ8zo8/2h0yd6L5khavrDjs8Xw+KYqIusHq2prOQZnaaC7ByrtezGwDgDlGfHJQ7pt3jfFtCa0nF+qvKT4f1DOLW7NZUPqbT12DUiOt5bJd/3Gla7D9r82sRN9cL7+DvLGMq9PLH74kfCQiqryifC/5jPp84sfCKv0M1pVXrtET3J5s5zHm6+N+Lcn21dXryhsil1Q3RCB8YXwuHgJgC0MHC2+fc3tB/xSbqXhuQZL2cmY9DodDsR+Kz9rJZ/vsMy5ec0C3JqNEPueFZRmB/3IG+TqHDQhHfHLQ4/kPc0lR1DU2zaAe4La2a5c5SuSWAT4wabecsAwAxFIvg/U2B4M3CqsaFZ/FanxZHD6PQzAs31/s9jtm4o4T8vNGJiCcEc/yOvSfxrbd9JuS5NPNhtMX9d9L/rpHzrnmYXCau+e04t960MepcjItM6hXDJVfdl0xBOEJ43PxEABbGDpYeOPLbcRsVSZ4iuP2Z/1iTqrHa6mXUl1pZjOP9deUs5LVja7Lm/mSD+72CZuNn732JmHUj7ibAL7WUDZCUTUblPUe6zrAdWpsaVPsBXRmAAcAsR6btdfj56W/+G0vP5vqmnmZX4kzYFqyYT9Xyzwu+Hv/y1yX5+fuLpSf97dMkRa+tN2HW44p3uuKK+6XK/OyzutvIeIrHyS5WcbM15l/64ssQ292eIsvi3fGwHrLIBbG5+IhALYwdLDw9t5G9uU7b89pxXN8qYheo+N0ZxKdDnEDJ63SD/dP1J4ddvrd0nT5+bWHzF86rIfPVOopIY36bvror4ObRVVLDlfW4iEP+wdfWJYhn7sgKThlNgDAN3yW5qhoGxVVX/X8Ii8ln2IzvFrbUU5dYFmB7x0f3KzA07gbsFoZpz/bz/IvvLnWt+XJ7vB7i5ftK1bccIhzU6ZPLbWwWn7dYFUW6998yr7PtmbrZ3Dmz9uUKSYXwwOTWCnEY7gRahkYn4uHANjC0MHC2++Xsyyb6w8rs2y2ttsVM4SnPdwZ3nCE7ZXV2jv264UH5OfVSbUcDociQM7UKN0jiqcZE556pvud9dkmtZJJO1Mr//zHZu11e+6SlCK3/2YAYL67xypL4KhLFQXC05aOCtW+1vYO9zc+A8HXO54W51qPnP9O+cNnxtVD5m/8fZlZqsh3odUOPTuPsRwazy1Wlqt6fRWrtR578JzuNQZMY1tm0n3MQm0UrVrGEP4wPhcPAbCFoYOFt8FzUuUvvuRTrsu0hnDLuGx57u+M8/Uj/73ZdbnaX9dmyc8v3qucbVTvW61vDn7yD2/x+5f7Tkx0e275ZWVJiVc/95w0y2j8ku1faZQW4fG/W8+Y0HrfASJRe4cyg3BUtLEl4Vans1wLIzWyPHubRM8I729iVQPUK5CIlEka1QFmIIbOY3usE09UKTL9+5J/gg/QX16hDND/wa2uWpisvbqmtd2uKKN0/lJTQL+Xv/hxQEpBtZA2gPEwPhcPAbCFoYOFN36/an5FvcvzfNDqaYnsn2NZ+R+t5E98gBz9lXK/Mb+ULNj7znzF18y9c3Sc23P55YNR0TYaZuCgzVtbPJQW4dntDuo3hS239HSTAwCCSx2AGt0vPdX5Vde2DWZQxn+/LNvn+p3Bfy8MUi0xDgRfb/7IuTrFXt57xiV4PevtLonXuG358nNTdp3UfD1fg7dHjH7CwmB7ZtEBfAdYEMbn4iEAtjB0sPClLn+glWhlDpeE5G8elvMO+pjdRU48UeXyPD/zoL5bzg8ktMphiKSenW5zMzg6cq5Oca6RgzZveZrhUeNrN/9nS57H8wEgeKrqlckEo6JttOFIqecXemnKLnYjUi/ZIL8dRevGqFH+uJItE9bK+5B1nuUzUCeZ8pfD4aDeY5RJn1raOhTbfU5daPDqWnySrn+pVj3NTmSZpj/cop3AK72IbVfpP82Y388ffP6NLVn6+5UhvGB8Lh4CYAtDBwtfZ7mZzV6j4zTL4GzPrZDPcZcBubXdTr24AYRWJsm9BSz5yuOzlMmk+KVwvuzBMsOV5lbFYLT+mv4yYT7BTFS05yRUwcDv6/V004KIaFsO+zceMC05ZOovA0QifsWJ81i+37hyanzW49mJ2lnqH53BkkIFc18qH3h9pRF48YkY73aT0d4XTaobvzWNnXVv+VlQb2848GWaPtqpLNPkqcQTEdGmo2XyOSJzMChuRGSUCGsHGAvjc/EQAFsYOlj4Si+uVQQ+Wk5WsiW9vcfE6y4NK6pmg7aeMTa63u5ayoEfzNypCrj5wUeo3YG+3t6hGDBdbNAvScIHk87f0+yAcmYCm3lQLzXXUnv1uqLNnpKdAUDwHC+vV/THqGgbzdldaNj1PS07JiL61QL2eZyQr70ktsPuoE9Ti2nu7kK6er3dr7Y8zf2ceI3sy97WNPeFOk+Dc0UPX4bP25UwH2xiNxPmqv6NNnqRwIsvA/X3Da7L0c3C/58w8mYLiIXxuXgIgC0MHSx88cGa3l7VlrYO6sntBztbo12OY89JNvP5BKUs1QAAIABJREFUhE6poGutykCy/HIzEXUOpPisp8fLg7fkzh8Oh0PxHpyr1d8TtzajRPE7RkXbqMnPwaG/xm9ne88m6+w9U3t2UZr8ms/2nw1yC0PTmYuNdLSkDjPgIBRfTs55TNhuXF30P3zGMv/rzXS+yGVJ3nRUuzTPl5kswFuSUuRXW/htM6mFrsmX1Nt06gxIyKVIajiBJTXczM3GelPvnUhZTkn9uRl3/IL83K8Xaicj/NdmFkDPTDC/ZrwTvw1mfpJrMjIITxifi4cA2MLQwcLXsn1sidZf1ujXWBw4O0U+T2tvr/par7vZd9pvCks+klHcWW7hXG2T/FiPGBu1tLnOHovGJws7Wam/P4xffuw8LtRfM7GlyuXkczUyq2rh96uJyFwtWl75Ffn332jgfksAX/FbRZzH+1/mGnZ9bxIejVrNArsVB7RviPE15N9ep73E15P+09j3gVbpu2Ak5DpwhtV1//lMViaOX6HUM8a7G5fubiZ4U47upeXsRsMXGnugzTKam/2eHmJbkMB/GJ+LhwDYwtDBwteknSwZythtx3XP4wdDenf6/7Mlz6tZx+c/OSift/mbmYWEfHanXETSKG/wgXvWef0axTPiWSDpPAqqvEuoYhR3sxJ6+ORdvcfG07XW0LsJEUwfJ7JkNq+FWBI2iCx8bVnnMWq1/g1KXz0+i93QPHBGu7ySNzfRnprPSgn9frl/NXr7epFsy5tzfLGDe3+fXcRWPtntDsWNTm/q4T63mK2c2ZVXqXiOv6n24492a77+sVlsr3WKxgy4WfjEaOMNXG0AYmF8Lh4CYAtDBwtf76zPlr/0FunUKSRS7il9T6NsBpEymYm7O9nvbshxGVgtSGJlOd5ca9xAz0jeDBqJlPvInMeRc/oBczC8vILNSqw/7N1sZluHnfpygz+RgzER+L18g0P0JgxEBn7vqPPwpTatJw9M2i1fN6/8iuY57pI7EXV+Xtw1hiU99HbJMM/hcCgSJ+ptr+ETcjlXDQWC36aiXu3Cz+gu1dkfzXO3hLuEW9nUM8ZGdlWSyQ67Q5F5uqhaXO6FOW6yWUP4wvhcvLAPgLOysmjGjBk0YsQIuuOOO0iSJJIk336tIUOGyK8rL3dN8tPU1ERr166ld999l/r370833XQTSZJEEydO9Lvd9fX1NHr0aLrvvvvolltuoa5du9Ldd99N//znP6m62pgBLjpY+OKD1k2Z2vu8iIi2ZrO6snp7mX4ymdWSTS/Wzxo6iwumncv63lnHAnF1IpFQMXQem+3YrbMMnIjo71yA7zz2nLxoYkuJhi1hs+zbcyu8fh0/czxxh+ug18r4ge9dY7QzogOY4fO0cy6fIb9aoP256yu7XZnPoEQnnwFf3ueDTa4B0WluuXBUtH+129XJBavqtZMLevvZ662FXB1kdeIp/vvprS88L+tWrgy6rHiurklZPaCxRVk9QJ3gq7nV3FwRvE9S2dadd9ZpVw64UH+NyuqaTW4ZBALjc/HCPgAePny4HLzyh7diY2NJkiTq0qWLbgCcm5ur+TP8DYBra2upd+/eJEkS/fCHP6Rhw4bRsGHD6Ic//CFJkkT/8z//Q+fPB77nBB0sfPGzmvtO689q8ku5+oyLd7mTXd/cpvgid5cleQM3u/G7pZ1lH4bM3Sc/prcnTbThXgaVr686ongvoqK1y3sEE/9+7i3wPvhef5j92wyekxq8BoagwdxMTlS0jSqumLtvG8BpERegOQ9+r2ogGluUn9V6SaVWHDgrn6OVH2KHapm2PyWK1OXlGlq0y8v99lN2o3ZrduCfpR/tZLPb6uRiiSeq5Ocenu45qOeTN6qz57d12N1+phwtYdtORJTL48UeZDdd/hSb6fJ8ZkmdvBc7pSCyVgeFM4zPxQv7AHjmzJk0fvx42rlzJ1VVVVHXrl29DoBramrotttuo6FDh1JUVJRuAFxcXEyjRo2iZcuWUXZ2Nk2ePDmgAPj9998nSZJo2LBh1NLCApKWlhYaMWIESZJEr732ml/X5qGDhSeHQ5l52d0+VXXdxLm7CxVBcE7pZfm5+8YnuM2iyycGGTAtma63dyiWwYlcBuYOP0PoLkkSP1hzHivTzpnYUqIB05Lln33Yi31sTuryIJFyt9/hcNA94xIUv7u7VQwAwaSVR0BvD6mvKq4oZx3bdMrabcpkGZFfWu66/JpPmuc8fM0bUKlqi16JvZHcTcXV6SU+/QwtfMbjear9zdUNLV7fzG1tVwa4WskO7xvPPldOXVB+x/JVGPi9yCLwGb21/r3/xm2X0qtpDKEH43Pxwj4AVvMlAH755Zfp5ptvpuLiYrcBsNqMGTMCCoD79etHkiTRoUOuySlycnJIkiS69957/bo2Dx0sPKlnbS97KC/BL5eOirbRqNWZ8h37r7LKvf4iP3+J7YvqEWOj3DI2u9x7TLzugEy0P8dmehXQ8sv1nIfZZSX4vby+Jo35xRw2EyoyK6mZ1DNRUdE2+jITmaBBDL6MmfPoGWMzpDzXqQusrvu94xN0z4vnSvg8rbH8etTqTJc2+rpqoqi6UfHZr4fPG+FvuSUeH1DHHnT9LH9kOruBqFf1gMjzEmciooen69+M5CsGiA4q+Rl9dUnEDrtDsW/cn+XuIAbG5+JFbACckJBAkiTRlClTiIhMDYAfffRRjwHwY4895te1eehg4Ynfw9V7TLzHwdW52iZFwo+o6M5lskXVVxWzAeo9VWqt7XbFHrS5e07Lf/YnkYpZ+Dvg7gZh/ODJeWglkQkWhyOwsiF8ZvA33JTGshI+KHAeswTW5ITIxidk44+rBtQTP8zVGHYXyBwsYit1tJZf/3zmXpf2+XqzzZssyUSqEj3xgZfo4XMkbMtx3c7y1hdZ8vPuavOWXmIrZnpoJLkiUt4QVeeCiNnKfq8pXtZrD5akk6z01i/n7VM8x9+kdjfbDaEH43PxIjIAbmpqoh49etA999xDra2ds2tmBsAfffQRSZJEw4cP110CHRsb69e1eehg4UmvFqI79dfaFDOhUdE2+tGERMWsoTeznXyQ+OuFrCalXobpUPDvzWxQ+nGifqIufvbVeWglkQkW9XL12qvXfXp9amG14t82VGfkjaRVd/Vv67UTwQAEGx+AGR107HET6PCOl9frBqdXVZ8xziPtjG/bBg5xwfgjbvbbTo87JZ83+mv9cn3eeoKra6/O3EykrGn/h8/0yzvlV7D3qO/ERM1z+JVTW1S5IP64ks1Er9KYiTaTuxseCzX2pMcfD81cHaCE8bl4ERkAf/DBByRJEu3bx75kzAyAm5qaaPDgwXISrOHDh9Pw4cPphz/8Id166600Z84cv66rhg4WnrZwy5Z/82m616+z2x2KWVv1seNYpcdrvLAsQ/O1n6QGvrwtWCZwyxL16hzb7crZV+dhZA1PT9R72FrafNuX19LWQb3HsL3hJyvNrWEswrrD513+zZ5bLHZPHkQuPjDij8KqwPMj8NtVnEkItbgr4ZN1/rJm+3Z68dnPSylgN9t+4Sbp3uK9+lmb/fHjj9hy3mNlrmWg+MD8RxMSdTPCZxR7DuDdbZ3hbxwbkd06ENlcHo+fqBJyqbc/RUXbaHpc4DPxEHwYn4sXcQFwdnY23XDDDTRy5EjF42YGwERE165do1dffdUls/TgwYPp8OHDni/AcXYk9dG1a1d0sDDE7z96e53v+4/2nLxIP9KY7fRmGZzeEr/kU+aWC/LF9Hg2CxGzVXsWokGVYdV5GFnD05OzNVfln3vn6Di/9g3yS919ySIdrvgamM7jgUnGJB0C8JVWIr2oaBsdLQm8nvhKrsTSnzWy/Tq529/KZ4vnj7UZJT61ZVce23fqLncEn6H49VVHfPoZah2qm5Sll1wT/TVdb1ds01Fnd3biZ9OHztPevsMn3OJXRzkcDuozjt1oPFHp2/Jxo+ntDW9oaVMkqRTxnQb+QwAsXkQFwB0dHfTQQw9R9+7dqbZWuSTIzAC4tLSU+vbtS927d6e1a9dSTU0N1dTU0Jo1a+i2226jm2++mQ4c8L62IAJga+FnNP2t+VpUfVVxF/vO0XHU5MU+tflJ2jPI5ZdDN+vwgiQ2C/HPb+oXq6kzrDoPM/c2e7uvzp2XlrMZ+vWHrZ8MSu+GTP017bIsAMH0qwUHNP8/elN+prqxhRYmn6EUjaW9RMrPXr3PMSLXEj6VXIKrCRpJuqKibbQw+YxPv+emoyzTtLuAyttZa2+oA3u90ktPcqXkduVpz2xvzfa8iop/rybtZCuHaq9eV37WNIv9rFEnp3TeOE3Ir1I87vzzPeMSdLN2Q+hAACxeRAXAc+bMIUmSaOXKlS7PmRkADxo0iCRJom3btrk8t3XrVpIkifr37+/XtXnoYOHpr2vZPrNPU4v9vk5jSxu9/2Uu3T8x0esMnfyAxnl4Kp8k2vL9bF/Ym2u1lzQXVLkmU4qKdr+/zWjpxWwv16Mz/Ksd+t5GlnV17h5zM1iL8PKKQ5r/br4m9QEwAr9HlT/c1R93cn6u9xod51J2h0iZ5E5dA1eNLw3Gl8njb5D15krp+Zrsb3V6iVczu3xt3kBvJhZ7uULmzbVH5fMW79UO7NdksPaP1Gk/v7rkX5tZLohjXGKpvhMShX/3VTcqt844S1rxCcjeWHOU7uRmgyNhe0y4w/hcvIgKgAcOHEhdunShJ554ggYOHKg4nK97+OGHaeDAgZSQoF+GIJAAuKysjCRJoq5du1JHh+sewI6ODrrpppuoS5cuigRZ/kAHC0/Pf8IyYW7N9nxDxhNfvsCPnKtzGdw9/8nBgNsQTGsPsX2ir36uvX0gs8T193IG92bxNsmNO/xy7/9syTO4haFnsCq7ufOIQ6IXMMDy/cU0bHEaJeR7t8+z35Q98v9BfpvJWi/KkvFld2YnumYw/heXzG/Obv1kfkRE/aclyeceOde5/NrhcNCDXEmcF7l8Du5mlLV8mspuKr6zTj/pnBE39ZyyzrPP6H5T9uiex38G6iUx5LcR6SXNW3HgrCKAdIrjykyFQvWDRtX2nbqmVnI4HIps35uPltEzi9jqhHWHI6NMXjjD+Fy8iAuA1Xtu9Q53WZgDCYAzMjJIkiS67bbbdM/5/ve/T5IkUVVVYMkX0MHC06Mz2BfbwSLfsncGqlJjqXD0V6EdaG3xYhken02Y398VFW0zbbnYtpwK+WeO8POmwipuz91rKwPbcxfqHA6HYqaL7xeBrIwAIOpMSufcT+pt/VT+/+MQbimupySBDodDMSOrFVi9sYbNbH62/6zb6/HLgJ35GdRJ9viEiHqzoHr0ZkfV+GzL9+tkW/YWX+7HXeKtjUfYPme95c0z4ln5P728EJsy2TLvl5azZd78iiJ3e7HN0mF3KP5dyy83K/JJREXb6GJDC43dxmaE/+3m3wxCA8bn4kVUAOyOWUugz507JwfZ5865ptcvLi4mSZLov/7rv6i9PbDaguhg4cdud9BdY9hSpqLqwLOL+qJD9fOjosWXgfCEv2P/64Xae+e357Lgkx+4Ou+om8GbmWpP4rnfVS+5i1XUNytnPt7nktboDWoBvMWXE4qKtnksK6YORF5ZcVj+84x497Wp1SXQoqJtVFanzKvAL1/+MtP9/v4R3Cqhr3M6xyz7T7PyeT+dmqT4zBvmY+b0ybu8W46tzkgdyHLhzdy+49+6qX7AZ4JWZ0V2GsMtD56mkxU5IZ99lj69gH1v8HuDx3tYim4W/uZJUXWjIvmY82YKfyP4ybn+rTAC82B8Lh4C4G8EIwDu06cP9enThyoqlPuDfvzjH5MkSfTLX/6S6uvZXrYrV67QkCFDSJIkeuWVV3z+HdTQwcLPJVUCDr1EIME0ULXPLd3kWWhfpXD1cQfrzBx8wQWfr6w4rMgkWlLbZEo7l3I1LN/6wvfs3kTKkhj+JtIKF3z207vHxisGfS+v0K8BCuAN9XaPyx5uhKlr7PIJ2sZ4qIFbVtfsEgDHqm4sPs0l2ErId7/Ef+QqVo5pdXoJERF9tp8t6X3188OKgPjxWSme3xBOzFYWQLoL7tXfV94kWtTDt99debqLqplurYR4/+ByJSzSSQCWrlNfd9RqVh5p2b7QWGnCl4fKK79Cf+JKODkDfH4PdY8YZXZwCD0Yn4sX9gGwzWajAQMGyEeXLl1IkiTFYzabzeN1PAXAzz//vHy9//u//yNJkuiOO+6QH3v++eddXuOc6S0pKVE8fvjwYerWrRtJkkQ/+MEP6JlnnqFnnnmGunfvTpIkUY8ePaiy0re6fVrQwcLPyUo26L9nnJjkU69+flgxwKi9et30NviCnxF4WCepFb+n7e11WfTAJPf1JoOBX1bo7xK1C/XKJeq+1hIOJ3wt0oGzUxQ3Oh6bFdh+Q4B9XIAYFW2j85fc3whTLzH+OJH1Z081cHO5xEr8jTgev8Tf003Hv29gAZ4zERQfkE/ZdVIxw93Xx+XJfLI9dxmkr7d3KH6nqnr/85bMTmTLlt19PjocDrp3PFuKrvX5zQeIeiuY+OXb/Pvz1Pz98uO2vNDINcDvHz9wpkaxFD/tTOf/FbvdQfdPZPvSzd4+Bb7B+Fy8sA+AY2NjA9rP6+QpAHY+r3dERUW5vEYvACbqXOr8xhtvUK9evahr1650yy230H333UcxMTFUVxd4TUEidLBwxA/yB8727a69Ufi7/+6SkYQKvryQXo3YWQlscPWfLXmKbK4HztSY0s6JO07IP9Pf8lbtHXYhs9cirDvMZu1fWp6hmOHoNTrO45JVAHf4MjJR0Z4zi5/jlvv2Gh3nUw1c/maO87hrTJxihU9fLnjx1BatJb58EqTNR8tcZp19yXXwF24/8ooD7vcjq5fn+mu0F8uWnfhyVFoZuF9YypaTb8nSHtOVXmLvT48YG9ntnTeb+X+HXJNujnoymCtpOD2OJQHrMy5ecROUv3ntbeUHEAPjc/HCPgAGfehgocdud9CSlCIa8/VxuqQxs/plJkvwIaqgPT9b+ofPQn+p6ZmLjXJ7e4+N1zxn3Da2r2vKrpP07KI0+e96tSSN9m8uy+vHie6zvLrzs6ksA+yhs5cMbGFo4WfM3/8yl663dyjqXXqasQNwh09KFxVto/Ri9zNm6hlDvmScXjImpy0a5eX4zx673aH4v116yX3d9ZkJfJKnPOqwO+huLhA9Xl7vsmTbl5U8/P5mT/XG+czY2aWXvf4Zam+vY+X/PCUV48+dn+RaDo6fxdXL8H2lWVl3uP5aG9VfU+YdqGkMjdVPv17IAn5+i5I6udlc7jNz1GrxCbxAH8bn4iEAtjB0sNDDZ/Ed8clB6rArlzgvTD4jP/+uh2V1wVJ55RrdPzGResZ43osWCsovK2c61O8pkXJJ34KkMz4N8IzCD9qWBrC37LnFLHj3pv5ouOLLwsxK6NyH+Ai3FHD/aXNm7sGa1h8uVXxueCqFxO8ZHjAtmXZzNXA9lTXj97fyh7M8kTrwutLsfj+yukyRev9nS1sHORz+J1Tkk2xty3H/GcMHZPsC6JO/X85qfm844v4zmV/R895G1+9Jb5aTt3fYFe95WV2zYgvS3WPjhdcAdvrd0nTN/z+fpymXd/PVDvpN2RMy7QdXGJ+LhwDYwtDBQsv19g4aMC1Z8QXmTGDixC9tm7LrpJiGElFza3vI7/11UidiuaqRiOXP3J6wlWnnFMGoWSV1+OVp3tQN1cMvTwwkkA51L69gA+K1GSVEpMyU+0UA7yHA52nnFJ8bm4+WuT2f357yizmpXuUecOLL8vxkMpsx/fFHu6m9w+7zcmU+qd+rnx9WZMIf9HGqfN5PudUimSXeb63iZ1ATT7i/McCvpglkzyz/M+M91PnexGWMHrbEtaQcnzTqeLn+cnK+lvOJynpFrXa9hIoi/HHlEcX/D72bGnVNylltdaZxCB0Yn4uHANjC0MFCC1+/0HncNz6BKq5ck88Ztdr7WpDQ6VqrMhGL1rI1fk/Y5qNlFLM1T/77zAT3JUyMolW6xB/8cm5/9xKHA37fW9LJzlqnH25hs8LTPewTBHBnSUqR29k0NVseCzKfW5xGJyrrFZ/j7vxnC/u8Gb89n3qPYcuVD5+9pLjWjyZ4Tli141ilIgDka/7+dS3LMP/Leazk224PgSzv8Vne50jgZ243epi5dYe/OZxR7H5rR2YJm41XZ8N3OBzUazSb+T7nJk8CP1OcUXxJsa/b31J1wfDmWjYucB6PTE/WnOHl81vsPGbO9h7wHcbn4iEAtjB0sNDR3mFXfDHxx8hVR+QvskhZ3moku6o+p9b+OfWeMD6RyGgPJUyMMnQea8OebwI6f/ADd3/LKYU6h8OhyHTqTAq0eC/bIsAP9AF8xWdxjorW3kvK25TJZh1fWp7hMmurtfXCSX1jk5/Rm2o7SRnFbDb50RmeM5yn8qXfPk5VBEjz9rDf44Vl3tcW5vWbwmaOs86739f7hg8Js9zh9zAXVDW4PbemUbnqhy9h1dzq/d5n9Uz3FK7+cczWPL9/F6P9k6uB7jyiv9JuH18CarLAVWTgHsbn4iEAtjB0sNCxPZclXOkZ0zlI4b/MnPus+k+LjARHRuODJa3Bk3pPGB9EvrM+25Q2KtrgIeGOO3zynec/cV3+ZwX1zco9kXXfDHD5ma+nFxwQ3EoIZ5O5YMebYIHP3/Dn2EyX/6P1zfp1V/nVH19lldOajBJFAMtnpH5q/n6Pbc86z+qB95uyR7EPl18+zAfGvmyXuI8rM3TqgvtglC+/NHeP+5sIelralKt4Lja4L6fkcDgUy5f55FvqOsHuSsXxNwg2Hy2jt75gW2Oc5aVCAV+ZwXnE6SwT5/+fekrOBuJgfC4eAmALQwcLDXa7QzH7997GHHI4HIo9oQ9O2k3VjS2KEjfulm6BEr+vLkcjEylfH/F4eT2tVe2hMwO/Ly2v3P/yGgeLauXrPOJh72G4KqjSTkbD11P90YREJHkBv6mDCk+1ufmbZu9uyKEO1coTd/stB33MlvOnFFRTxRVlPW9+j7A32f+Lqlnm+ztHxykySJ+tucr9jmzp9fR477YMOBwOn7Kt8+XdJu30b8ZRXd/8ervn+uZ82aet2WxLSVE1SwjWe4x2VQAnfmZ+xYGzihVYgWxTMZr6Zk3PGP0bLjml7OZI77Hx1NqOcnGhCONz8RAAWxg6WGjgE2tERduosKozcUVZXTPdy91p55P+REXbqLnVNZkTaHOX9dPhcLjUzlXsoVucFvT2ORwOupPbl8YPUn3FD/DuHB0n16+0Er5uKl8P+7IqyUtdk/tsuQB61MtKPS2p5zMPO5ef8jOlJyr1ky3xN+COfVNblq9l+//ZO9Moqaqr/Zf/DObLu96V4X0/vFlZhSjBAY2KwVlEjRo1TgkxmhijmJgYE4OaFDMygzI7MMlgizIJKPYEDTTz0HQzzzRj0zTN2EA3TQ919/9Dc+s859S5955b8711fmvdtaCGrlvddW7tffbez3MHqJt3mbbB8dyrhSqnebTtlc+1Yg8V/M9VEDUVqs/bV2PRrsxpE8EKVF++zmGe2uSNL1ir74iFzFYOE8Bb+tv72HedxT4DIxbt4TZS3YiGJRv8HQdDLQ4SVlxqauZmzOPZbNUkDx2fpx+dAPsYvcDSj2EY9OSHrP3tz5/ywc1kQYnUPNr1dRZC0TAeGsHEXhbv5OdrRT/MUxcucTN0qJqaLMQWv2qHFj87xPfjFKB6EbSoeW4Cq4gZhkHtoPVRVu3XaFR4LaeUW0cvTLL3PJdVOjFxtRpZaZTY7RDxnq14dJ21yfHcxSTVPJ4Yy2/mTVjO7JLE7x4rRFX9WomqPjJ+GXuNWOfyV0NXi8oMNBH/+0PLwBV7T0Ruvw82z2Tg3zT05RbufVeCOGW6EQXbnObVn4KY49PLCvqazELH5+lHJ8A+Ri+w9INf7MFQLm06wu/GNocN7svKPB4cYe8rqeHB1jVR+VJsr2toCruqEiSCky6DSidw/s2PO/xY8TC9Uk0eG8MqZ1ooThMrfxSsZcTkUeQd8KUefrniqKKyXH2+Xrr2N0M7Px4qyu6ix695vC1UYNEuqPM459ZqIooS93LqMMHNqt9Pim2cBBW2HxujNts/t6xC+rdDSyinn4Xq2U/Cd8jV3fNsRc1SDc71BkPOwmSY2Hed6byhokk9Oj5PPzoB9jF6gaWf5yeudQwO9hw/HxXMOFUjNDy/BTGTWYKf557jbF7upz1bZsLKT/BtxMmeJT10qjbyeq265cb9eg+ARZAbexOv8DYkG8MEmyoUqhm7OHOEajTeAgWQgiG+1V7G69PLIo81vcOf/Xh15LYvS+Uzo7ur+OuPufbDYYN+Dj695qEqJIXtuuYhqjDj+M1DipuqeL5te9nP0BIRLUjAOAn6Gqt+95XBJmY70AMQ1brtmLRiP/dezX/fPVStCp0qZpawTYYb+xY6+kSj6GanFHQ4adyj4/P0oxNgH6MXWHrBL+hgyN7bcISgCq13bd3x0hRWzZm2+iB3X+kh5hnZfkBLtTfRFVkn0OeznYLPpxM4L57jwxY3u/c3OJ9ZWMU6c6jRYNdIMOTcCYLXGLOt9E9w29RVch/h1eWsC+gOQbQORarMw8mP2KSjxFZP9OzdcBCvfUVKP9dtd8xStGQaXqz0GiJob6aqyi/qAZh2R5jUOs1Tz4YKOR6/VRAiSyV7YRO31/xtjo/HDddgKJfO1mmthExDx+fpRyfAPkYvsPSCCpPPfLTKtup3qamZHoQ5VhT10Djzt+msKijafSyVzPs2NPFzecdqkjvvtW4/8/m8fVD8ys1oPfJe4S7nJ3iMTlDhLhI8k6evO5SxgaomPRw+VUe9v9pGcyyqsDLwehsM5dI1Pew7QTqPYxVj83X+AUJMVt0Idu29i3fyAonBUIsdjwpiAh8MResBiIJ5Kp0nOLajUgnFDcbbBqol2SLov9tzvrovOyrrb7gsWoUWg05xkWt6AAAgAElEQVQbyYXbq6J+h8FQLr01K/M21tbtP0Uz1h9WEsc0DINugQ6B4t3VKThDjRt0fJ5+dALsY/QCSx9o4xIM5dKSXccdn7Pz2Dnq9H4x/WLkMltLDU00opongorPv4IWPSfvYORMbQMVbKuimovWXp92LNnFAt0HYqySIO8V7sroYC0eDMPg1NG3HeXVdVHkRqyoabIT3GzcV31e6TmoHG8edp6xOHtesK3Fg7XHPGalNDBXbgGUA56/ouVafWMz13obDOVSoeJIw+8nreOed0v/RVEJrihoda7e+fpVBG3Tvxjp3DZ94CQ/3qHyGiK4oTfcxeYvCkyaGwdoGdT7K/tq6ZryU1GfAdl3iBd5eWpJ5P04iWZpUo+Oz9OPToB9jF5g6QMrA4+MWq79SpNMz/nWgShWDHG+rMMgNn+3/oC15UVTczji4/mbcatj+ltytksfWltYqIJBdazCM5lKTV0jF4yKVkeHT9VxAbdd0qLJDm4fxNSY87YeU3qObIbWTp0dW46X72lpNR4qsUYSGVXEKpL/nLEx6n5M3oMh+1EZBGfhgyH5vGtTc5jz9D18ynljFedHVa5V4bDBVWKXxlBtfAWSNdUWcCKiN2ew71mzE+bfc9S7Y3A0BY9ZJWpV+ExmzGLWVv7SlPXpPh2NgI7P049OgH2MXmDp4VjNRc53VlQl1iSegbnWLXTjLGw6UMF10Q7rCj2KaAVDuXQ8BgsjVEpNhMDZQmjd85tiOHZPtAHRIJPG5jC1Bk/lfdWxeyprvI+oiKzaBo1dBiqfpdtAsKr0UMuG2UfFzJ7m9eny2dU+X22LPEam8Dxj/WHuHOz8hJH/zOHnh63UozE53XzEWTEez+d3E9SuVZjEi6J1KjzzEavkzi1Tb2PHzQXz9283DiMiKl6bxyrBS96LLN/DOmVu7rdQb8JnGDo+Tz86AfYxeoGlB2whu33Q4oyyU/ArKCIm+mhiuzCKJv1aQcGViDjP4GAotnmqicuZMIuqH6cdWyqYhcoNCRDVyiSW7mK/bysfz3uHsWrc0l16vi2bqbnIdwyo+J4ahsFVRs3Dzlf6ekiYdx5rGZnIAfVisb3Z5O+fM/Vo2ZywaJNUVaO2wYabfsFQLn2x/rD0cVi5Vrl2oTd9l2klSueCfsO/Gbda6TlIp/eLY1rPWK3+5eiW+eo/fMJawz9be8j2+eJnxzwOnqx1/R4yDfG9+eE9+Qkdn6cfnQD7GL3A0gPuoGuRntSAVd6/TS/l7usNFZh+C1h7NLbdTbZpu/tCqNCYFihuGGmToMdC9Tk+aL6QZBXrVILVcisbE5x/tFLf1WQH+8HSTKXqR9QyeytLfJbtOSF9fDhsSFuJVdqFUdF8+jp5QjYkfxe17p7nap4fW1yDoVwqs0je0Wd+/kZn3+wPl7Kq9htfRLdsy0Dl6DY98l2PJdzcb6Hj+5CBXsrX9S4gwzC49+vkEy7+XYOhlrGKS03+GKtAuzyVv70mdej4PP3oBNjH6AWWHmKxdNDEx7TVbCZWnHf610wmkDUSxE3wdjuRkBELd3MBkmyOzwk3wiwqNIcN37YB4+/7XxYqrt1BfAg3NTTZx/oDp7n1qSJgJFromMc3W+TjKnUNTdzjTMsd7FawsgB6ZNTyyGPybeaT3SZdU1cd4M7JahMMrZqmKGwWDYO55v/Mkc81izQ2hzlRwXX71eaYiVqSUBwZOuCiUilWOavP1XNJn4r4ZLu+hdzP6DAoNiXrTATnxGPZuNUkDx2fpx+dAPsYvcDSQ9+vt0e+dKzmsjSJZRb4OYpV9y7TWKV30or9kdvx7/TuAuu/09uzN3MBkooyqkjoSzavNzSGGTkZdw5mwj9+mFkzwd+31TwhVvxV2zQ1/iR/6zFufQ74xnlDpPLsRWkC/Pk6eRvxifO8mvLFhpZkVcVnF8X23CSGTswtq4j83HuGWdsVdZ1prZAvI9bvL6x0f7BEbgkl42wdvxnh1rMW7X7W7T/F/b5LDlqLG5rcPZRXA3/mo/hFCjMF9Jkeku8/uzwvo+Pz9KMTYB+jF1h6eB1mvtwEAprYWWBhdURE1Hk88+9EdU+sNNq1Hop2I62757mu1uAc4IdL97l7cxY8DcIxdjPMXgN/3zkW85yY9MSyIaHxDziHGwzlUvd5zj6y5ULbtHmMt2ifPnSqNvKYVt1yI4JCu6uYQN5Pe+ZHPU8U6Np7XM2iSYWqmvrIz7YTnuq3wF33CYprufEYR0GqFyerqw4fBBulq7rlUtilZgYKaM0sOcyJm5mz2nb8cvQK7jOg2vbtBQbn74y8r25z1f2VNclHx+fpRyfAPkYvsPTwW0i4ZlgIk2gSy+KdTHjsIUEV+VEIcLAFcdIKJkzVZZq1MFUnaKkzD9Gb1glsQ5y2+qCr51qB7W2JSqozAfx9W6lzbzvK7Eva9opWitZkD5h4BUO59KbCiAJ+fvB4v1DuQbujkimTo+jcsRq+kixujJ2r51t0T11unU4UR07X0fI9J6ixOWz5mLEwK/x3hZGcN8DCz811ZfW+k9zvqMnmnBCcH76530Ll1zNBD/hBeTu533fFGWfbp+cmrOGe46dK6cfF1toYmvSi4/P0oxNgH6MXWHrAGaQiG3sdTeLA4OuuIXw7ILa4rdzLWoWxbbqzhViZYRjcbJt5qFqtmPxm3OqYn2sFtiomYq44EzAMg6vgWG00iImFnX+rxt+gB3gwpKayjq3LeFitI3z8zweyVucLl+SzwSZi5TgdjgBYIVfxDFcVBxS52NBMV4MuwdYKtU1Cbo76/WLl1zPBBP/5iWu5v0dNXaPj8//8Ke/D7KQc7SUSbb+nSRw6Pk8/OgH2MXqBpQf0Xdyk4LuoiR+sItzafxF3n5UPZiF46T4yarn054rzaeahMmeIYBW6YFuV+zcoAedgX02AtZIbTl64RGMW76WF2xPzXkxEURu7ihkqx25QmPXT+BPshAiGrO2IEPRIxcNKdG0ZPP5+SNIMw17AqSzO6mYiyN3CxgUeG7PC8fG/m8CSSLcdTDiW8Yli8oyzzLHM3+L4iyhopbLhIGo8LI3B5i5Tcfu316QOHZ+nH50A+xi9wFJPQ1PYdQuWJn52VbEWxWt7FURuNwxeLXn/CaaWvKb8VOT2Owcvlv5cbH3Ew+1uOvrWYhU6HuZvZBYs4txzsnlrFgsad1clbq4R/45tetq3Nj/5wcrIY/00A61xR+dxfAurShKFm194WAmq5cHM+eNj+UQCN9i2VPAbnjia8YCFSnSyseuOkfEk2Ah9vVmuim3FYGhBfi1HreX2E/Adfnmqe0E7q3b263oXOD+Z+BnpYCixc9rpZhX87e8e6vy3NyneXU2v5ZQmfINTw9DxefrRCbCP0Qss9YgzYW79EDWxcfhUHfd7N4VURPuSE+dZRRGT2+stgiUMYPG4pf8iV3OnqFS60YXPpR2YwGNbpozz9Y2089i5hM3K4pxuIufcl+5m7ZD3vbfU9rE4qzhSQd1W40/EGX2rbg4E/Xvx6DxOPgox22ZcAkcsRDV2HLP4zbjVsb/JOMDrnEpS+IuRyyKPdzvCU7SDXS9vVbxGDgcxwlg80sU2dPNQtTMSZ8jrGvzjqY6bA+36Fjo/gYiamsN06+Xvq3Z9Cn31+8gkdHyefnQC7GP0Aks9WyvgC6eP2heOJn6qz9dzQYxpU3L8HH87bkhUnOGTZploC87PoZ9nMORu7rRNz/yEVxhE9VQr0ZmzdQ3UfkBLQGOnFusGbD8eszhxSuc4s/bcBHkyYvJeIfMrtWpd1fifG4W2V6eNEyKiGesPc89xSp7RZ/xPgs+4lcgeEdF4GFP4S05qxxRMnIS6RO4awhL61S7t1cSRkfITzv7kOMPd3+VoiUn7AUVRf0vVivtkqEDfIozPeJ0jp/nvOJWWcPG71I0vs0YdHZ+nH50A+xi9wFIPCnrcH4OghyY2xCqAOTu6r5rZlLTpwduUnBeElE7XRvtPDitgSdZbszbTbQNZoLVszwmlcxPb4o/VXIz/DRNRfWOz0s/FYP/mfgtd24yINIcNagVzjz3nJ85eA62pnJLaWSWsuvbsx+mprmnSi7i2giFrP15kyiqW9KDomlWL8EfF+yKPeV1QUv6thc0aEd8S3G3ultjfaByI14njDht32K0Si4YFbhR+odAd8vcE2AaiyKB5PPWh2jxxOkdJko0oFnhG8h0nsuf4ee45ZQnqWNLw6Pg8/egE2MfoBZZ6MCi3aqfTJJ7msMF9aZuz12U24ljhMC9gc1Cy0/2vmcxiY/jC3fTiZGZnNM7CM1TkTC1fFTlX76xMqgrOH1q1Vr85YyP3+vuq46tAnxbej4rqrirvgCDNUIdqNbaAqyQ9Gv9RVcNXq4Ih63EG5MOlLKG9/33WQm3VJvp+IduY+fcc3jO8yzSmIjxpxX7uPvw8u/HUTTRte7EOlF1V9t64+Ng9MXSr9Jq/LfL8rgqdGej7HasC8zuCkFUwpCaGRtQivNdhUBFd1S16A8PriN9xKtXcdftPcb/HJbu0k0Uy0PF5+tEJsI/RCyz1YGClffdSi6zNGNVbO0paI3/WT64QbYIekdPXHeIqOip+o0SxtaGp8vBIVm0p2HYs6n7DMOiOwYu51493Zndf9YWYKi0qYDCcs+ag7WOPnuVbO/WsWvYhE0Bq1S3XcfYU506xgtuqW660Q+LdBdsjj+n79Xbuvq6wSTZCmEVHSyFVVeRkgNeA1eXWbc3iRuKR0+5FHL8GVWYV4aXHxrAW8twt0dcwFfB7N5bv34amMKcP4SdwXEWlol+wjReIm1umBQaTgY7P049OgH2MXmCpBwMlv3izegVMZk011m+2sGDsibHR7W2ozrxib3RL833vsfuX7qrm2uUeHukstkPEKxurKpOqghXpKauiA2z0ITWPt2ZtlvwkdUoED1UVZVlV0EN7kYMAT3PYoDY91CtbGv9RDKJpeJgaAFYM+IYp/6KYWjAk79D4z5wtlpXcPl+xiue7C/jk+ClQVJ63MX2JBM4p5221TjKtRkncIFblK8/aj3zEM3Nsgird5vGfOelpOc80OsJ3mMrYjjgfn86NGz+j4/P0oxNgH5OtCyxRSrexgMFUIsWBNM5glWPt/lNERPQFfJk/PzHauuiJscxK55stvOWHYRhcVXlX1Tkumb26e56joAwR0QZIGG9zUGt2y7/nsNa/wfk7o+7HlnzzUBEJskO0kGnTw96uSBXDMLh5zG1Haxyf0wnaV7VlR/bxZWlF1OdbJXHrMY8JL4k2OEclCRvOqX64dB93H1aT357Nby7d5zL5SBbPT2TevtPXWbcZiwJIsboY3DOMJbVfbTpq+1hc89srnde8DJldXayCWn4Dba2c/hZERB8Xl3O/x+ELd6fgLLOPbI3PMwmdAPuYbFtgtZeaqPO4NXTPsCVpE2743QQWaHy+LnH2MBpn0A5l6e5qIiKasNxehfWFSdZ/r5MXLnGBQM3FRmpsDtM1PfJcBWxYpUq0MBqKRslasrE9E4/q8+oK1iIyBd2zdc7iKk7UXOQFW1SqTy9NYRXwicv3Oz5ek9kYhkHL9pyg3C3HqNFC1RzB9Y2HU+tu11lsXYxctIdLwmSdBC9DK/NUodMCz0Gch2/XhylUb62ILblLBK/bJPAIdoyotJJbgT7hPeZZi+RdauIFupyqxVaIdnfBUC6NKtLWaER8l5DTWAkRL9wWDCVW5FDDyLb4PBPRCbCPybYFhhYqryZQmMcND41gHoq6IpVacJbMbPOzq84QEf1temnk/o+LeVErtLS6vndBJBjEdsIvS53bGnO3sPY8WRt2PDjZBmF7IR6iXYsbZPN2sYjliGB1vU1Ptapyf2hl1VZIqedcfSPlbz0mVVCPheUws/9pDMG6eeyusv88/vUztu7HLyunDoOYuvv6A6ejHs8pPW/ghZKwy+R3E1iXiahQLasspwq0GhpgUxndeczZG12FmSXsd/KLkcssHyfa1Dm1rtuBf8NgKFqQLFvBrrSxCl1p2FUUDOXS3wXVc01iyLb4PBPRCbCPybYFhsGw3ZduMkHBCW0fkFrQCsNMTPt+vT1ymzifR0QU+pLN9omqw9jq++AI9nnC6pFdMGmCbchO3rZuWbLreORni9VlUXwLBb36LYi9PRDnJ81j5d7YZveQpVApV23T/moTm8nupG3HUo4pWnZj30LaURn/DDbajnWZVuL4eFyLeDhde7Fz4NM1B+lB2LhcvDN69vzxsdZCTbjB9fjYFZHbE5ncxQtuBNppAJQeYuMa8Sir7z/BC+VZ2e/gptdPe+ZLH6MKblIEQ/5TdI4VVOVW+b7686cbuN/j7yepqWlr3JFt8XkmohNgH5NtCwwv3Df0kdtZJJPGZn7HPxYFTU3s/OETUBC+bKeBAbKo0ErEV5C6C616U8ErFC01Ji7f7yo4+GQl+zkqQb0btleyKvW1vQq4qunsDSzx7jS8mD5dczDy/3j8LmVJRyKUQrGS9tvxahsFB0/WcudRczFxFlMae0R/2fYDiqRWYm7ASuWjo1c4Pv6P0N6JxyoHMSWxovvMR2xOcv7G6DlJnDU3xytMsGp97zC2cYPV1Gt7JVb8zi14DXplqvU1aMVe9l7i0QowDIPaD2B+wlbdUGvBcuf2QYtjfj0ifjMzGLIX+8om0MLrHUkXlEjncfxGwmNjnNehxj3ZFp9nIjoB9jHZtsCwNTUYSqzfqgqZtOOfjfwlh22ATFje0s786qfWHp1EfDuv2OqFyTEqimKQ2H7AIvFHRjFm8d7I41Wtk1Q5JZlTNnkbvDG7zd3KCcW07p5HtZdisw3605TopEPVE9kOnGdWbWc2DIPzQnZKfDSJo+JMXdTn4O6hS6iqJvb58n+CZ/VN7y50fDxWZvFwUhB/8gMmfrdgcyWXSMtar7G9tuQg3yK9EbzGb+7HznnVvpOR2xOplB4Lc8uYWNgzH1nblmHXyyOj1FTurcDxkoG58spjwbZjCXu9ccv4eXCZqn82MmkF27BVGQ3DMa5M+Oz6lWyLzzMRnQD7mGxaYIZhcIIjwVDqbVHQkzKe+SlNbPwLBJ9GF7XMOmHb78ySaFGynLWHIvdjlZeIn51CQRVRHMtJUAoTaTtBmFgwDN4KCGcf7x7KK7E2h/k1EqvlCKqKmkc8LdUm70DCLraj24GVfzuBH01iwcQPj4dGLLNseXVC3Fy54LBJI3pc4+fdjl+MZEF+0Y7j3FqXfYZw3YjCd+XQ7nt197xIFwb64SZ69t8tS3epCfGhzZtdoqzCFOigedLCK9xqfjoWRP/ajXoEiYiIZkEnUGeFzpr2A/hZah3LJIdsis8zFZ0A+5hsWmA1dY1RQdDSXdXOT0wgxTHMMGoSR7e5rH3StASSCWMhOEMqBmk4UyzOk2GQsNzB3qQ7WK4Mzou2KooXTHRNq5WjZy9ya8GsyqEiqLlJ4Bb0TjaPRAilmPOkwZCaWqkJzjfKlL41yWEhVAtxE8ZcS7F0GPz649Xcz9lrI64mbv78fCBbk1+st1fgR5ue1ftO2q5RwzDoqm7snMQ2b9E6yOz8mbaajRz8cfJ617+LRIKbFT/rZ11Zn76ObQjGO/uJG8JXW3ScfFTMOnD++llpXK+3u+o893fYV30hrp/nF7Cq7+RdbxgGXd09j/s9BkO51NDkrMiucUc2xeeZik6AfUw2LTD8sjWPz9Za+x0mgzngSfnsx6tT+toaXgStz1fbiIhP1mQtcXYWRaigLD4Xq47jHdp/sa1TRYXTLZg0mIk6tjx2hM2YsdCOLVa8VRE7LVQrC048ADZWTi2syKIdTAgs3jlCjTqYLD0/cS3Xwh4M5dILk9Yq+WQjWJkNhnKpeLf1JqZom4XrwEkBGOdTyw6focH5rEuj21y+S0OcdRY7PsT7j59ruX/Eoj2R29KtUI6z8q265VJzWK6wju2yoqWTW8SOE5lQ3qA869+7W+obm+mnl33bW3fPS4g1mx9Y52LO+nx9dCEhGMql6nOxjzVo5GRTfJ6p6ATYx2TTAsvfeizqoj3MRRtlIsAZJF2JSj0ysQ9U5d505GzUc8qgMnJrfzbP2xzmd8L3VfOVKAzcnILbLtOYh+jklQdsHxsLfwePzzGXE2y0sgh9yeaX15SzYOj63gXUpOC1iojWLuYRrwKzYRicF+u2o+qeqdXC7L0O1lLD6CK2mfLPGRvJMAzq/dU27m/xWk6pq8/Y7YP4lmY7L3VUGm7dPc+V3cv18FnbeeycrRaAOGcvVjLFSrR5rUD13f4K6rvJROyQsmpRT7ReAapty0QIcewhEd/XOWsP0T3DluhRCACVtp3E2ETnAPNwshXTuCeb4vNMRSfAPiabFtiE5eVRF+1U77qjPUyiZz01zohBrNjOVX4iuiXOan5PFDQTg955G1mF1Um8hVOcTYI1B37uTCXr+95jle95G5lC88WGZu534ibRJIpONs0jXtV1sZp36sIlV8/HWVA31WNN7KBis5nghcMG1/EQDLlr+8fENBjKpfcLd1s+tuQgs+z5+cAiW0szRNbSnAMK6S8K7cpiUhCWVE9v7c9XlImIXp/ONqbSnZCFwwa1hnW/X3ItJCLbSngs4DX5geHFUa20XaYxkcKJy7VvbzKoquGv2XZdGVsrojvpgqFcWrf/VArPODvIpvg8U9EJsI/JpgWGu+3mkYi2TDe8CYHfSMlutya5TBasPi42CK2LksrgifN8daeuoSXRxZm5G/tGJ3docXJ19zzbGSk7D9FEgG2Lr0wtoWM1/Pxv5dmL3ONRxGrqKncVaawmiIf5u4sFnN9r0zOfs3NSARXA7ZImTeLA3zmqgDc2h+nlqazr4freBUp/z6bm6O6CrjabmNj18+joFdRvQfQIhIxLTdEtyyj+9LQg/oSf+essBIE6woaT2bb9uwlrI7c5zSSnAkzSSw/JBaKwgp+IqvXuqvPUCjYbPirmNwJQZ2H2Bu3bmwyivgdtRBvR0guPgm1yGytN7GRTfJ6p6ATYx2TTAntJYs1yz7DUyve/MIkFPKmeP9YQzQBF0ecnro2qVspsqcRg+FhNS7KYt9XenqOhKUzX9GAVlR2V1orj94OH6DIHwaxYWABqs4+NWcEF8+hLaoIV49ddiletLmfWLh0GFXHBbTwesMssvFRVwUpTrLPNGnegd+6XpbwPtNhBobI5crauIeoa/twE601MUcFd1e9UbAeuudhIS3axOfIHRyzjHl96iG2GtR9QJP2ZvxJslYiIHh65PHJboYUPbirBGfvFO+VdEmidNmJhYjaSeoDAWNte+XTkdF3kvgdH8GrcmsQjtujbCcuhKCQeM9K4gXPkdB01uhzV8QLZFJ9nKjoB9jHZtMDwy908rumRJ21XSxYY8Ogd09SDX95PfbiK9lXL25tF2vaKthHCquqfpsgVXB8Zxf7ec8sqpI8hIroN1GlLD522fFysYCvorf0Xca2gskQA7UI6DCpyVW3N3cI2Bh4fu4JTw15/IPb3ZqfGrQJ6rt707kLXFWSNe1BgTlRCFzeWVLyBD5+Knj+02wwZVcREpt6csZFTFLbb2BE7JBqbw1Ht1Aj6flup++Pmpzm3jOte9A5OBygSNqdUfr3Ctu2Pi+P39iZqGW/A68RLU9ZH1ieKkSXj2qhpAT+LG2w+i6hcjkcifN5jwRSSu//96PZ5r5NN8XmmohNgH5MtC8wwjIj6o3ikUhCHbzHTX+apBm1ZHhm1nGtjvtnG+qPDoOgkrr9krlakK/gOD8y1bhe8theba0yGN7U4o4i2SGJljijaxxgrMk6IVbdfjmbt3d9sqYz5PaCicCwVXHGGOJ5qtMYZwzC4z7WsA0K2sWSHTMnfbhMTx14GfLODpoLvrNWmFREvnnV19zwi4lvwRaGggm18q7WM13JKuWRBRX8g1eC8rZVKNnZSTVt9MGGvLVYWc7cci/odadui5IGVdqvqPxG/qYSHaSuYanCDRKYi7mWyJT7PZHQC7GOyZYGJra6YDG88LJ91SjRNzWGuHfTQKR2Apxqs1Nw7bCk3z2RXSXpI0ob3t+ksoP1giVxRFoXXrJK25rDBfTYrzqgnm6qI1TaV18O2bBTJcgJVYv85YyMXMMejcD0eFNRj9QPtBF0gX206GvO5aJy5cKmJ+5ydOB8tWoa+vCrdAdher7KJ+dfP2Br9uLicZpUcifz/tzb6D9srWaLd7rJ4W+XZ6KqwyZdgb/drC3s7VDN+r3CXsupyKlFRXO6Mgn0JnMk1DIPz+f75wKKo37lb4TuNOlj9l22KmvT9ert0Df5nzhbL5yQLcXZ5/kZ/XdOzJT7PZDyfAJeWltKQIUPomWeeoR//+McUCAQoEHD3th588MHI8yoqoi8OtbW1lJOTQ2+88QZ16NCBvvvd71IgEKC+ffvGde6GYdDUqVPp3nvvpe9///v0ve99j6666ip6/vnnafv27XH9bKLsWWClh1j72s/6LeRaU5MhOiSj+ry9arAm+eDnoP2AIq5d97Ex8soNkTw4eNpmvtEEE+72AxZJH3NO8FVMljcldh+Yx11DrGfgMRi2qnDLwACp79fbObulIfmx25jg/Oa/51jPb9rxL6jI91uQXtsZv3MAfGWvsvCVxY0lFWVubM3Hw2oTs/M4Pln7ZgubhX9i7ErL18HrxG2X251F/9PTkLCiQvQfJ8sry9gx0vurbVG/n1SO4lih4rn7xFg2y5zo786DJ2upDWxOvwJCacFQrmtLNo06+Lu226hEBfcbwMM5Xk/oWMARpmDI2dvba2RLfJ7JeD4BfuqppyLJKx6qTJ06lQKBAF1xxRWWCfCmTZukrxFPAlxfX0+PPvooBQIB+sEPfkBPPPEEde7cmdq3b0/f+ta36LPPPov5Z5tkywJD0Z8nxq7kFEhTddHcUanutadJDvg3uKFPISeKZSemg5+XKZdVkdGPdHW5vPVKVJCWVcHsKhRsQoEAACAASURBVEuJBFuRzeOtWdaJJFbLfjFymeXjRP4heK1i4tp1Vuy2Y5hYx5q8ToEWWKtKnSYx4MyslTCUyswpMnvDkajPsF0ihhX/JbuOc0JWDwwvtnydlXtZpdnsDAmHeWsk7OBBf/e/TZd3J2Dr6L9mbuKSbPQXTyc4Iy3rsjAMg7MTW3pZzTqRYAcJHjKlfU3iwHEdmR+zyYuTWUcPboak2lGDKFqROl1t2MkiW+LzTMbzCfDQoUOpd+/etGDBAqqqqqIrr7xSOQE+ceIE/eAHP6CHH36YgsGgZQJcXl5OXbp0ofHjx1NZWRn1798/7gT4pZdeokAgQH/+85/p4kXepuTYsWN0+HD8qnvZssDGwpfq36aXcv6U7y6Iv5KuAl6sU60+rWlBrLpMXM6ErF612cHGyuGooj3U1ByO8gm1AsVdRCEgIqK9x9ls4U975ifkfcp4WaimmFUxK3AOMhhSr0z/4RPWxvjZ2kOcaEo86stdZ6kFaHaUwcx32175uqKURPK2Os/FYtXpE4X2+E/AxgwPK3/Ym95dGHnMloqztHb/qcj/7xy82PJ1Fu1giTIqvN/Yl1W8tlYwf+wRC9kmz9sW6tKfCBZs+BoPjVDfYEomXzhsCO6rPs/93pOhn3GpqZnbuDAPK3ExTWJ4dwHfuWPFk6Bm/gZsdrrZJE0U+Hm1W3teJVvi80zG8wmwiJsE+IUXXqDvfe97VF5ebpsAiwwZMiSuBHj9+vUUCASoQ4cOSVUrzZYFhm2Yg/N2cpYor+XENk/olrllbE5M9JHUpAbRemVwPmv5s6tO9gHvy34LdtBRoWpb3xhtn2SCCeGE5dFKmSjElcxKULe5W7lzDobsxa0Mw+DappfsUrMgeWwMqzTnbT3GebHK7KJU+fOnzgI9TtQ3NnOiOnbWVJr4wI2PFy3aglWrTiZWAjyygL2hifcMPnr2Im2pOBv5/03vWoveiWrxJncNYeJxq/exrg9sb7byF8bqdedxa2hmCQve7eaRUwm2mMvWKirf242MxIts1jsW5XeNOmKHghWo7I4bP7cNlHd5JBPsLgqGWtTDVZlbVkFvzthI247WOD84TWRLfJ7JZG0CXFBQQIFAgAYMGEBElNIE+NVXX6VAIEA5OTkxPV+VbFlgv5vALChy1h7iWqJ/9YH1LFgiQUEku2qjJnmISsAYgNvteuMX/VuzNtMGaO+8xSFpHZi7g3s9EVGYK1mMLuJbC+8cvNhxcw2TzqEWojgid0KL5JryU1yrp9Pvyo7nJ7I1HI/n5ONjVyTk52jsweDUqtVenBd3ot+CHdxn2Dxk84dVNfxmV31jM1fBbNPDutsCk9PfTVgbuf1RGCNAG7tuc7c4rhMxufy4OH5Rt0SzDirkHQZFJzRo5fR+YWI8gK3Ajg+3yY3GPaoK6e2gC2LeRrapf00PaxvBZIGdWcFQi+2eChVn6iIdXL+06E7JBLIlPs9ksjIBrq2tpVatWtG1115LDQ0trX+pTIBbt25NgUCAysvLqby8nAYMGEB/+ctfqGfPnrRyZeIStmxZYGj7Ury7mtYfwPm01MxfqQiMaJJLYzNfFcKAbvhC64AOKx+vfrqBvt7MxHScKiFY+ZfNHaKFSjK/jDGod9rlN8EW8d+MU5uZFa1tRAumWL0aEyW+033eVr0OUwB6TVvN5o1cxKpOss0hkbdBmO2+91glShb4omXSDQpKzggmAy9PLYncbqWAjHPvVorwq8GH+q4hS7iNsR4uROaSyR4Yx2jTM59LaC5caqJrerDuiWTb+J26cIlrYX9zxsakvl62g8nsMxYdak3C9+emI2e5/6da2BNF7oKhXLrDZqwBWbqrOmpzLBPJlvg8k8nKBPitt96iQCBAy5axuYZUJcD19fUREa2JEydGzheP5557LpKYx0M2LLCm5jC1FvwWxaA8FRdArt3PJtnSJBdsgUUVWll7ssksbF8cv4az5Okyzb6af/gU/1nbL/h9zgELlc7jktcKuUwQDJlZ4lz9xPbsNj3z6VKT/ToRbSmqz9dTfSN/W+XZi7Y/wwq0ZVommaVWBTcCMnn33+u8oiA0KM7FOvGXHNaRgN0Jss4C/Lx3vDw/eraugfss1lxslL4OVmdfn14WuR19cnFmucs0ZwVdTMjb9S3kKpx2m2+pRHQqqGtgCQ16qN/07kKpqneiwc1DFZE0TeygQFwnC4E40R9eXE/JsPCzA0cSgqGWrg6VKrS4Gbz3uLMHeTrIhvg808m6BLisrIy+9a1v0UsvvcTdnqoEuKqqKpLofvvb36Znn32Wdu3aRTU1NTRv3jz60Y9+RIFAgN555x3ln2kuJPG48sorfb/AZMluo+DJaydilChwFvTTNQeT/noaOdjChRWGL2zaYcX2RWzd7G0x84eg7dbHxXyirdp6Fi+7q3gBG5XPfENTmPPMdqr6iLPRZoUNxYM2HTkb0/m3H7AIziN27+5dVUwJvHX3vIzd/U8XtZeaEuK3+isQy7HyXJ6j4J+L4CjLiEX8PPDFBv7viN68z17+2eJccFWNXMQJfza2b+Mm5kiYWcbzstpYOnSqNvKYVt1a7JLM/5vK8ulG/P1gQoMaAm98kbpqbNnhM7Sm/FTKXi9bKT3ENjutuuJwhMBseUYrpFTO04qFDadNLWSsoDSuYsGWDnQCnH6yKgFubm6mW265hX74wx/SyZO8tUmqEuDKyspIAtyuXTsKh/k2rby8PAoEAvS9732Pzp1TE3HJ5gQYW89+DkINHQYxdV4rG5tEgvNjeVtT4z2siebnA4uivjSDoVz6Zkul5XPWlPPqsVh9EhNaGdjq+ZQg5oKCbH//vMziJ8RPY3M4MgrwzEerlOe1fgttn+OW2b9Xscpl8iBU2hdur7L5CdZgIh7Pjn1Tc5iu7VWgnNRnE+UnLtC1vQromh55cVXZifhZcKvrq1slZJzf/npzZVRnD4KaCzgjfLXNc0ywPbnXfLbBJYrhmWCyv2Cz/DpyupavlqHSsdUGQTqQJTSi/ZGV77nGu6CnrtU8L1qbmaJXOF62cm/y4ygTcbPVaU0jvWEdB0OZ6x+sE+D0k1UJ8PDhwykQCNDkyZOj7ktVAnzu3LlIAvzee+9JH/O///u/FAgEqKgoPuW9bFhg6Gf6LFQZnv5oVeT2VLRX3QaJ1/oDOuhOFx1hdhAPu4B/eyU/T6hS3ULQf1isPA0t2BW5vdvcLQl5j1acOH+JvtlSqWxpRET0XiE7PyuPUxO0+kLbEhSw+mztIdfnLVamjtXE1kZt8ptxzH/WqmU1G0E143jU8Q3D4OZFrTYsUIvh5woqsqhAu2LvCa4FcsVefv0OttBcwA4Qq4oV2uQNymPzy8NBDO8dsFx5QPAbliHqD+DvRzz3dIIJjXleYvfIyQR0CGgyC7G9WTbPixtWpu0RajNYbf4kA7x24LFuv3O3wGs5pdxzes7PjBl8kWyIzzOdrEqAO3bsSFdccQXdd9991LFjR+4wn3fHHXdQx44dqaCgwPI14hXB+v73v0+BQIBmz54tvb9Dhw4UCATo888/j+nnm2TDAsOgBYU0Xv+8LHL72MVy4ZJE0Rw2ON9YcQ5UkzqwEo9H2WHrttqKM3wb/c39WOu0ymaGYRhc8J4DLfC4Gz3gmx3WPyRNoGL6E2PtBfis7GPenMFEgkbG4OErVs8uxCm2MgASPS2uw/j1x2xjwMq7VwVxNtBqwwUTKxUPbFx3m4+c5TYyxNbjt2YxwSzUXLh9EKtkWgXL3HPh84pV5b/ksKoyVkfX2gTg2HmAx/bKzLFiwYTm68sJzTjQPEiVa4ImtYgbNDKtBlELg4gf7cpJ4WgXinbhodJd9wwUP4KhXPr9pNj96ZNJNsTnmU7WJcCi4JTVMXXqVMvXiDcB7tSpEwUCAZowYYL0/muuuYYCgQB9/fXXMf18k2xYYBh8o9gItrklu/Im7q6er3eeU9EkB/HLzzz2VVu31Z6rb5Q+Jxiy99JF8PP2wiRmrWI1V5gplLiwfJpioZ4brwI6Com16pZL4TgFeFDF+/73i+P6WX6hsZmf976+d0HMtiZ7j0fPCsqQWRVZYRgG1/K8/8QF+idc20UfYZyxnbb6YOT2TiCmtnR3tfS1Xp/ONkdxxOGL9Uw85/mJbA3fqFBVJrIev4i3oyGRyLQqnpuwxvL3rPEP1/VmGzQyj3TZWMEboIA+JsmFBARHh/BQ0Ve5ZxgvnnX30CXJP+EYyIb4PNPJqgTYjlTaII0aNYoCgQA9//zzUfcdPnyYvv3tb1MgEKAjR45Inq1ONiywZ6GqMauE/b4wWH9xcnI9BlF456c91ZQKNcnh95PWSb84j5+TC+IQEYWFCj4mY1ZWKiLoHdy6e16kKobzxJk4i3Sshp+1QmVYEdEv2QTtlLpMc1b7FeFmi/sUOj/BAVGZW0U4xe/g79g8YhXDWl3OdBfutLEmkamGW1F7qYl77MkLl7jxgbdn817DOC+M8/14u1W16GVQsJ4KAlW5W5hlmdkNYRgGN1ds192Ds/CqiX+qwU2F0UV76Vx9I/f+Ntp0ymi8jejhLoLr7T9zWooGvS3m4pMNirLh4bRBYxgGt9EXDOXSVd1yHR0O0kE2xOeZjk6AL5OMBLht27bUtm1bOnqUnyM8d+4c/ehHP6L/9//+H1flrauro8cff5wCgQA99thjrt+DSDYsMNx1RzEWVPZVEWCJh5V7eQ9ITfpAKxPVxI6IOMVo81CZWzQJhw1qP4B9Fk0hGfQitlOiThfNYT7AtxOgwtnJgbksGMLW6FhaKNfu50XI4sUwDK6dNpXiLZnKZ2sPRX2+7cYC7FD9e4uzwnZdGGK1+FJTM+XAOWNXBRHflozBPHqHzt4g30DGiidumspm3C818Um83Uba05Luk+t7W49SpQNUuO/79XbK38qS/pv7pcb+SJMe0K2gYFu0WGG3udHe3iNcenknihehwwMT2u4Onto1F+XdXCriWakmG+LzTMfzCXBubi7dfvvtkeOKK66gQCDA3Zabm+v4c5wS4Keffjry837yk59QIBCgH//4x5Hbnn766ajnmO3UBw8ejLqvsLCQvvOd79AVV1xBd9xxBz3zzDP0f//3fxQIBKhVq1ZRSXMs+H2BiR6k2K66taKGC0KSWZXFOconP5SbzGtSwz+gZcs8Wne3btM0wRneyN/SZTKHu9ZmC9mTH0TP3GUa+N6X7pK3jRIR/W06Exf5qHhf5HasCN4+yH0CKxNfiRcMoD5cus/5CT7nndmboz7f8zfG9h0zaQWr+Dv5+/L2Vtbz9HuOR88Lo3cptrIbhkFteshVw7E12qpd8skPV0nX5KYjZyO3m+MAZ4T5dLvxFvzMmcc9wzJrQ3RUEUto3pyxkf4zZwv3f41/wY0fmZ0XikeZjgCTV6bGxk8Eheewyw8V32Wg2jUeVuJ16cTv8bkX8HwCPHXq1LjmeU2cEmDzfqsjGAxGPccuASYi2rx5Mz377LP0ox/9iL7zne9Q69atqWvXrlEWTbHi9wWGF7vW3fOoCdpVTwlzuclsg8SAMJYWUE3iwIDOPH7Wb6Hj87B10jzcKuUugwpS2175VNfQxH2R2yWX6QR9TnNsVJwxgJoB1Wxch1d3z3M9w4uCJ88q+MWqgO3aTkFTNvCQpD031pm+wfls5jv0pb2+QicFBWUiotJDbISg/YCWzoudx9hoSRsYLRGrPGdqmQgXbtJY2Xo9PJJVwtAjtPwE/zk2DCNKIM+uQorCi5m6ITpt9cHIub04eT3XQRXrhojGG/wlh3VHTVgevTbQEs9MkPHaLFr8JQvDMDhBuX4LmL6G0/cDbsbikYluAH6Pz72A5xNgjTV+X2BLd1db7rSLsyA7j6l5KseCm4BQk1ywxc9NFQZblc3j3QXbXb12Q1OYs2Ep2HaMU6XNVHssrA6arW8yMHEoBL9fUUTMrY1KzhoWlP8xQfP6RVBVjqUq7SfO1zdSK8mMO85xuwFVlN8v3G37WGwLnrfRerxo6S52Le80vJiIohNd83O1/wS/8YkbLlbq0Ah2PGB7fPV5vg37YkMzV5lu28teyVo2t5jKqpkK2L6OnsCtuuXS6Vp1+zSN9/j3HLY2hhXsirpfdn3HGEtFULCpOUw1dfEVG0RXAPzMov2eDHwsHn2+2mb7vHTg9/jcC+gE2Mf4fYFh4IyqnSb3gyLo4p3Ja4FxExBqkgsKeZjHLxUsX/76WWnU8yYudy9ahSIz/5q5iQsyM8kOBcG2yL9/Xmb5OPS63nCQJfOGYVDbXmyzSaYwagcqftq9vhvEZMZudtPvrN4nr4r8Zlxs1fYXLRSYZbw0hT0WBadEZBZbhmFw62dLxVki4pXLbxPm9HvNd7Ydw88xtmWLIzXV5+pp4+Ezkf/f6qCSjt7E8W4yJAucc8bj6Y8yq1KtSTyo1t9DMkvbYRBbF+ZmLY4FOHVS1VxspDsHL6ZreuTFNe6D42vX9S7gBPycZuqxGw+PRG2sJhK/x+deQCfAPsbvCwwv6KZqIYJVPbvWznjBuTO7IE+TfMYu3hv15ffby56GdoS+jG6dRnVZVfJAVObGvoVc5e3wKTVLpVQzp9S5zU1UwxVFRbCqVmxhP2MFblok0rIMVU8zcQYsVXxUzDYY0ArFjcgbgl7bTr6cuCFk13KNgld/+IT5dv5iJGvdLtjW8loF29gae2TUcu7nYDeOlSVXO0iqxc0anC3eV32eEzh06iT5YEn0tQfF4jIBTC7wGF2UOosbTXqw22g0DIPaQMfcnstz9QdP1kZua9XNfgQAbcR+HccoC67vh0Yso+PnojszrMCYEDe6nCrH6cDv8bkX0Amwj/H7AsOq3QdLor/A34bWzqGSlp9E8dgYuSWHJvXIdoC7THOeAR0kqd6UHnKvklt7qYkLJPCI1XYm2awpP8UFDTLENuczQrvkr0GoxEp91wordel4wXOaW+as7u9X0IoLfdOdgkkrUO285KB9Wz/aqPS3qMgS8cH56xCcYwX5k8tzfFbJMhHR6KK93HsVEf2GD5ys5e6/tT8T7So7fIYKtzM3ATHZFvkUOpLMA32GM4Ejp+uizjEYYtV1jX/5zGbd1DXwNmSmZVlNHX/dN+39ZOBG5h1xqPnjd/gfJ6+nxuYwdw4odiqC1zf0+27dPU/Z0jBV+D0+9wI6AfYxfl9gKFz01aZoAQ+U8LdTuAyHDSo7fIaO1VyM6TywdWjt/mh/PU3qmL4u2u5Fxb4BA3DziPXzYGXFlEl+oIgYFMvO89ApVgm4SlIJQPEht6rLbypWCd2iogicDeD1qWBbFWdNtMfG9kpGs+CZLSaQIu8XMjEy0csXGZIv7wLoPo9tjpgJtKhkjGDwLBM/a2jig+mqGr41Hsdmlu05wYkAPePQJoyPNQ+Z2m46uSD4LQdDudR+wCLXwnUa77Fgc2Xkby7alx09y/vBNzS1JIthF+v97yACd1W3XE6U1A0oemXaHv0MbO02HbHerHl+Iuv6m7zyANeBddDhWpVq/B6fewGdAPsYvy8w9G6VVetmQEtO53HWbbBm8tOmZz5VnnWX9IQFH9V91ZnnN5dNyIJQFQGMHKF607p7XsyemLM3HIk6h2t6OFsxpYvG5jAX5OyXeCbiLOQtklnIPlDp6/u1O/GwLtNKuKAlUaAqL9o2ZRPHavjA9sT5S1yShyrIKpw4z6vrX7hk7689cTlLSF+1UePGRHdwHhNiw42pv37WosqOc75iVRk3wH4/ia9yEUULa4mCPb8C27IFmyttq2YiKLwW6+832YgWUsFQLnWdlTp/V036wPnve4fxLcE4Z3tDn0LuvluErggrnvqQ98E+6jKWMkG1anMz9UFQsS+yWVOodr9wexXdNWRJ5P9uR3OSjd/jcy+gE2Af4+cFJrZkmi07CF7w7x4qn98yDIObFZlV4q59U/SJjFcBURMfOD9kHirCZKJ65J1xtHCdqW3g2iyDITUrpnSCgcLyPSei7kdP1gcuq/QimKj8bbo7+6jOYL/htn3aDrTEkqmeZgO4Hu4a0nINRBGrT1xuOOyoZNZE1/Zy9lefVcI2gzrbzOJj9Qg7CHBDy/TltvKjFh8vq9iK84SXmvhuh99PWhe57/N1h2nC8vLI//+SYz9Ksf7Aae5nB0OxjVEkG7Q+MhN9jf/ZUsEErW56l/8+wll3MVbq9L6alRl6fgdDvFCiG2SdfWjRhBZ8IlgU2Xj4DFcRdhLsSzV+js+9gk6AfYyfF9j2SrZj+VPwiEREf1JZRQ93PoMh9xWovWCT0aaH/Dw0qWOZROV0vIUfKIJ2D8FQ/H606K2LyUem0nkcCzC+kAQYKJQlUw+eBVVvtwIovwRRJVPoKBH0/4a10mWiDUYqQFGo16e3zNZiBdXt72WZTRVJRsE2tRlaq3b1dfvZfLrpD4yf1VnChonTzC6K+lzVLTfqeo26EuOXldNIGKNxqpSib7F5OLWIpwO0u7mqm/1cp8Y/4BhLq265XNs7tkc/MZZvj34GrMystBQuNjRHffZjVYK+GdqdzST6dYsNMkRUcT969iJnTebW1jDZ+Dk+9wo6AfYxfl5gGFjJKlJE0cIO4rwXEdEYQTVYJqZlBxqvxyP8oEkMsirM5+uc5/DKoMU3GOKFeGJh6qoD3M97eKS9gE666TpzU+Rc3yuMrpZiK6tstrIYNhBUEiPknmGs+oy+rPGCGgCZZkeTKp6bwJJF09YL52RfculT+2Wp+kwsES+wZtdVgX7B8zcyPQfZfHqn4dYVqRV77RN0rGCLrZ5EvFfqe4W7aGAu20TpNd9+s6DiTLTAVM3FzOsIwmpaPGq9Gm8hClpht5qdsNwrU9mIilXHCBYCcAPJLWLMZo6kqYzYiOvvUlMzjV/GOjhenlri+nySiZ/jc6+gE2Af4+cFphrEoXiCbH4FA69gKJeG5LtrlcTWWXHnVJN6xIp+MKTW4ofdAsFQ/GrElYKoSLwV5WQzfCETK5IJxqHCZ+jLaKsiTCza9nLXCYE7/pttBE7c4qZ91Y80hw26HmyPTG9PrJJ2stg8tGLcMne/U/xc2Hl44owferY3NoejhGywzVH8vJQeYhtZZsXYzf0DoGug91fb+Nnk/J1Rj0fEsZyru2fm3H/XWWyzy61gnca7hMOGpS0f2ge+8QV//X9rFtsUGr5QPk60dBffQWWXqNqxr/o8t37Mrj08PyuveNzENkeO4rnWJRs/x+deQSfAPsbPCwx3BO125tGzUrQoOnXhEveFYAY9bvhkJav0ZdoOYzYiJrLBkJr4hSjukwgxpidBUOfFye4qbalmZom9hyP6JMssxU5e4H9/5+rVKl9O/sLx8Pk69p5kgkh+Z3cVCyZbd8+juoYWwapdVSwpbdMj35XYG7aV95wv99lFxKqMlRUJzqWK1kq3D1rMrWX8eRVneEsUbEO+TpJwr9pn7+sr2ii5USgXEwwrS7F0s6vqHD0+dgW9NGU91TqImGn8xY19mQc2Wl+h8rIYA6mseZkFmKxTyAlc3ziLjB7Dv5uwVvpc7Ar8xchlRMRfA6/pEbuwZTLwc3zuFXQC7GP8vMCwLWfCcutWG1SYNVsATeaWRSsGu22VxMrYv+dkZ5tlJiFWXoOhXCo95CzGcamJnx9KxCwqVsvQ2iUTQREUWSs/esmK64godjV0cW5LJmYXK9id8eSHzu26fgM3NR4dvSJyu9hm6Eat9R9fsIRwdJHzuMh5oSpq5YV9bS9Wqd5dxVsz4QziB0v4kRXRsstuzpGIV2o2g2RkMmxovjK1hF6Fz/2kFdGfe5F2fViC4eQbrNGkmnuHLY18PlfsZWKHOAIzYtEe7jm45qyqr4PydnLrMhiKrSMOVdx/C6J5C6GS+9CI6HVLxLdxmxue4myynYdwqvFzfO4VdALsY/y8wH4xkrXM5W+1TlZ628yOvAHBnHmYVhuqvDObtQdlq9JsJiGqcgdD6l6n2C6Ku+OxUt/YTG98sZF+N2Gt1Fook0BxoFbdmA+kya8/Xh25f06pXAgFK3VrytX8sMXK+8WGxHklo3L1gxZBk59BAZhuc/nKTfsBRa7/VkS8z+b0dYccH28YBqeILlsHojevaEWHCtG4ESOb4RU/T2bV2wTFfp78IDpAR7G3zuPWcO9XJg4ncudgtgasKlUaTbp4YizrSsKOuD9NYSJ0U1bx3U+fSRJLERSPM4/2A6Lt8pwYBgUFFJ0rc7DhIyIaAWM8/5rJnovfS5j0pxs/x+deQSfAPsavC8wwDK5isO1ojeVjPy5mVThsyWlqDnPtQObhtlUVvzgS6WGqiQ2xohgM5dKxGrUK17sLtlMwlEu/+mBlVOXI74gVcJwPIyJb4SET9FA17Suc2H+Ctay3TvDMJCoIZ6NAHY5/zCzhk7dnYUNDvM8O0WdTBZzx3ijRYTh1wd5beDBUl+6ABPO+96JFrmov8dXtk0LFGdXKn5sQbcskqkg/Cd6mKp/pR0YxheV4hfQ0mkTzh0+Yzddna9kGFnr4oggdEVHuFmal9tiYFeKPJCI+scZDtBlz4p8wcoDzxodPsVGKVt1yqUkySoFjOugljqJvOWudN+1ShV/jcy+hE2Af49cFJs4b2nnvWolUydSCgyH3YkV44Y9V9l+TOAzDoKuEuW4xoLbjyOm6jJoTSiUdBrGq4Op9vBqzUxJDxI8bqLSLEvHelIn2SkZBtHaSaqGfqWto4taB2FaMLY9uOld+pvA5EOn4Hmu7lM3jO1kTTVsdPV8YDMlVqMNhg3uM2PKIP+tPEvFEVK2+a8gSLuEv2mHtgWrym3FsY8FJNVqjSTVWdkJ2axTn5q3s/PC6gMehU+5swHD9oN+vOLZRfS56VAbH4vD7B/3gB3wTn7hlIvFrfO4ldALsY/y6wDZCO0y7vvaBbclBlujeCq0zOLt7TQ/Woud2bgsrEqvLE2fhookdbGWWBdQaOThrif6qzYK4sNzSzgAAIABJREFUj1VQ020uCzQG5dkr5ppgcIWiJ4lAnAfNps8BbvBd37sgalNnVBGziLKa6xMRW5VV5+lQDE62SYibIDe9G70JsgjmdvGwEtnB7qBdVee4+3Au/2/To8dduE2TvoV01xBm0aVyfX8ZgvCRwiylRpNuUNUcr9E/s1Hi315Zw11LRMQ5/zY98yP/djNeQcSPEIjtytfB9/qOynNRz7UqRnxUvC9ye5dpmeMG4Nf43EvoBNjH+HWBfQ1zXL8cLW/JMTkqiCKZoinYqoZBixsPU8MwqE0PdrHfqzhrqkkuON94o8MGiYaBAkcohHJamKs+b6HwjL67MislGajc+ajDWnaL2CmSTYq3aAEla/VFAcBfSWZhZRyrkV9LncC2S1kLotMmiMzaLBiKnms2ubX/oshjROu7kfAZxRlDE7HVEsdkVCy6cORG7KLQaNINztj+Z06LMKPTBqcoLCnqQ6Dy+k975nMbXnPL5HoRMhqbw1zXiqgXgH7xy/dEz/JiBxMm3nlbWQu3lYBWOvBrfO4ldALsY/y6wD5cynb0nLwom4SL6oGTtVFJMQaDboQbRGP5M7UN8b41TQLAL0qrli1NNNgVgWroaC11TQ/rOV0US3l+opoAkCg6lEiiFKYlbXN+5fXprNVR5l9beohViGVVVxlYqXXqvOHOxaLt0iQfAlTZhqZM2C4YsvYkxfW/SkhCcZ64x7zoBPpsnfy1gqFc2lftvMFZ39hMs0qOUNGO41nVcaDxBuOhA+K1nJYOCHF91VzkNzhFJWXxOrpQ8NpFQawPljgrxZscOc1bpokbbE9Dh9K8jXxiHQ7zYntop4cV7DY98zNG38Ov8bmX0Amwj/HrAsNWS5WZDmxTXrXvJCe13/G9pbTnOPOKa9srX/k8MDG4untexlxYs52HR7LqvrYiUcfKggLHCH5u422KgZCq6vKUVcnz0RY9hjNdiTuRYOuuzNJLVEu201EwWbyTtSJ3Gl6sfC5WbZcmaNckq1aLoofmMXWVXHQQ178o1IWuALLvjqbmcNTrmIeqmJ5Gk6nI1pqTEKFhGFxbs+iqgNZhf5y8nvMU7i7ZZLJiLYgWygoRr9pY8YndPtilJArjiSrz6cKv8bmX0Amwj/HrAvv9JNZSN231QcfHo+Lp7A1HOLGedxdsp4oz/M6jqggSXrA7DLJODDSpBZVbE11V9DPFu6sjvzdsRRWVca3YdIRVCFVbz8cuZh6T/1Rsm3bDTe+y2bZEWFt5gerz9dz1rKomuvJtGAY3U7e1wlpJ3wSD587j1dfVUEnbJTJpxf7I/a9azPU+ACrk5rHAQnQQK0WicvPbYFs3wqKCjL8XbpPgovMmgUaTyRRsY90W5shJ6SGmqXKrhcUQthev28/P9ZruCcFQS1cFrmeZ0JwV2IknsyjDwsdgYSNtRyVrw27bKz8qib9toLXAY7rwa3zuJXQC7GP8usDuA8VCK0sWBH0khxXs4qoJy/eciGoBsppxFPlmC5tFtrIH0KSe301g3p2vJLiq6Gewo6F197yI1cSM9SzxsfM2FWfFVGZEBzm0pMaLWxEjP4CiUXYbc6iDgJ6gVnywhG1WuLH4GSdpu0TQvxNb7xGcIzYPK4GdFyax9f/5Ot7iCduxPyqObscm4n1D8WiUWK9oNF5idTmbt7/zsjUcdnY8YNHZgdeKgm18VwVWZsctK+dsk9x0YOFmqEygbrjNdWLZnhOR+2Q6LqguLV4T0oVf43MvoRNgH+PHBdYcNjjVZhXhKZz7woD4ut4FdKmpOcoD9bjirODUVXzrjyYzQFEzVTEmTfSs19HLrWKoovn6dOvEJxaV4G5zWXvskHx1Ox5V7Nph/cr7hSxQtNNI+DMErrLZXJE+0D7c9+vtyufzhcMGSt+vtzv+XPT4dLr2d5nG3pdox4VWKVMsWqjR+sg82vRUH43RaDIVrJSais6ow/BrCxtI9NJFeyKi6I20MnDpcCNCiWt8YG70eIJdvDUb/L1l7wE7P8TqcbrwY3zuNXQC7GP8uMBEAauLDc5VJisfSbPdLtZZQQw0rSoXmtSDVR7txemO9gOYgq7Z6jYwl8109ZxvX6W9BRR4Sw85+8S+AcrTKkmYW56xEU7xKzgiYlXlJCIa8A37u4a+jG5NFvnb9NKY/laowirrlOk6i3kSj7CwDhoD1SHzOG0hOvjPGewzNXYxL8Lz/ERWHRYDeRMcmTGPmxPsUa3RpAMxfmpsDnMty1Y2Qa/lsLU/bll55HbDMKhdH14pvaqGH8FQVd/HLg/ZfL9dxx0Ko/71s+jqMXavOAmnpgo/xudeQyfAPsaPCywHlGbbD1Cbu0VxHjy+gAAIZwVV5uGIeIN1mdKqJj1gVdEqoNbIkVlYvDXLeW7ShG+VixZfEnlpyvrI41Xm+d3y4mT282UWPH4jHDaoHVj32LV956xhG4N2re0mncexKtCskiOOjzdxsjnCFkqxYmuCVapgqKVF30p0EGcFxa4Cu/lgE/xMmodWk9f4AVEQ6uSFS9xG/tuz5Rv53PwtxDqiavqpC5eoOcwXFFTU04mIOr3P5vxl3TqouXL7oMXcfdhF0uer6E3vBWCdmSnCmH6Mz72GToB9jN8WWE1dI90Mhu0qVQsiax9JVPVEA/a1+9XM27Gdzipw06Se0kNnqF2fQrq530I6cLLW+QmaCGifM+Zy9exlhbZRE9zF/3TNQcfX+zVU29x4RqqCVcuPi8udn+BxcI67VTd7PQOcm1NJ8O6HAHXprmrlc9pawa6/MvskbK+0SqxxdjEYyqXbbNTI+0NlWwyGcYPGqiUeuxLM4xcjM8c/VKOJFbHbrfzEBeoBKu2y1mMiayE7jK2u610QEZ/CUTOZZ6/svH4KStPbK6OLEPuqmVuHaMeH31uy7hS8BslEstKB3+JzL6ITYB/jtwWGu3zX9y5Q9vU8LfGRfFTwm3wQ5r5UhLWI+GqZVTVBkx7qGproUpNze7yGB+flzUDnqQ+dq2Ym2M76fqF9tZgo+TO6/56z2dX5eB1UebUStDE5eLKWS5YbmuxFnm6AVsdtR9W6ZIiIDp+yV9l/dPSKyH1WXQOHTtVyP8OuioNiOWJFCwUUV+yVB+aYEJjHUx+uUn6/Gk0mc6swpuKUPBLx/sF/BqV29PDGTSIUnZpZ4iw6JdoYyWzZxGozPgZfT7aJVnOxkXuuqs5LMvFbfO5FdALsY/y0wHZXneeMzt1UcwzDoLa98rkL4HuFfGscJrNW9hoiuMu5KkOk9TWaePgU2mJfmNTSFnvvMJY0OO3mD8lnlYJ/z3Gei8c1ZKXqGw9o0eFGuMmrzAIxGCerooamMF3VjV0T7bQPRIE0NwFkTR0ffJ6t42d37x7qfB0VhQp/P2md5evZibb9HOxQNhw8LX0+fobFtaDReJ1Ow/lODpyLt1JInlUiv65MXM7mh9Fx4R/QRTFSYQxpM1jo3dCnUFqhDUe1VrPrFW5sLd0t705BfQrRyikd+Ck+9yo6AfYxfllghmFw1hYd31vqurrXSfCRFIMftM6xEkcRzwnN4XdXqc25aDSZzJJdx7l1RkScyIlT5W/ySqbU+ZKCByTOq7qpKqpiVw30I1NAKVXFAgyTT6vAkYjoyGm+iuvGEigcNqgVJNqHTvFjCTfCZ8BOfwG9PO08o1H0UPQhVfm8oaCOeVj5E2s0XgPn4OdvPMp1YORvlXdgoI4KVnp7WyjDD85nnUQqG6EolPfwSOvuDvQjxlE19O6WtU8T8YKIbjQMkoVf4nMvoxNgH+OXBVawjRexKtqh1qKMoDLqz/otjGrDQ+uMT1bazzkSEZ2r56sapy5ccn1OGk2msbuKzVm16ZFP9Y1yayQrUKnzl6PtvbENg0+MDiZhXhtb92TqoH4DvTTtkkQT3Fi0m9kuPcSsTW7pv8j1eWGSu6XibOT2cNjgqtB2n4EnoRW//zfyWUUi+yo4WuiVW1S8UWjRPLSdmsYv/AlE3qauOkB3gP6JVRdOycHTkcfg/P3LFjoouAn1h0+suzVMsJIsblohj41hyXrulpZk/YIg7FV9Xt6d0nUmG88ZWpB4yz23+CU+9zI6AfYxflhg9Y3NdM8wVqV4cfL6mAQMULFZFhjaWWfIECsiYkKt0XgRMZhA8ZBgyNl2bP0BeaAkQ1QkTcYm0meQzKgEYl4HZ7h7zLO3rCLi1V3tkkrchLSr0FiB1/CVe1mb83lhI9HK2oiIv0bbiQ7mbmHVpCfGrozc3tjM+1SjCCLy1aajUQmwyu9So/ECb8I6Gl20lxsP21V1Tvqcvcf5jVEzBkPP7IJtTMMBK8adHLQIiHh9FzurPVT1N10D9p9gwn9XdbOOxUYXsc3Bv01P/2aoH+Jzr6MTYB/jhwWG/m1Xd8/j5j7cUHLwNP20Zz616ZkvbX1D6xzROkOGzFBeo/EDPwOl9enrWALZtle+43NRWMkuGCGiKL/IZIiWYTLz9Ef+FzLqDgJOKtZsHxezCrmVBygRXxWNZR728bHRlRsiuS+pFVsrauiuIUvol6NX2CbKS3dVS4NvsWtHnEWWPd88BuVpmzuNP+gDbcvdBcG3qhp59fTEeV6kqvZSExmGQdf2Yq3HGFehOvS1vQocixZohWan78J5hl+25FsH9kg/t9l0xe8Cp+6kVOCH+Nzr6ATYx3h9gVXV1HMXWLsKhQpnahssTdkHgHVGb4mPnAhWujoMUvMj1mi8ACYrWCG8c/Bix+fWNQjtaDZiSWhr0aanc3IdC0U72ExzNljZoPjMB0ucO1nyLFRcRUYu2hN5XCztwFZCO7uq2Ebitb2cNxINw3AMptEv9A74zFaf4zdc6hvlGy4boN3TPEYVaT9xjT8YAWsZR8Ps1oTYPVFxpi5aufkiU2U+Jdxntdlk8kuYQ/7aRoR0EHS4dJvbUilGj9/HxlgntptAaOv63s5JebLxenzuB3QC7GO8vsCwVefW/ou4C2yiwQCv66xNjo9fvJMF1g+O8H9grcke/pKzgQsozH8/PlZt11zVLqfs8BlufSeDNeUsGVJJ4L0OzuRNdfBsJuIrNXb+mN0VvELt+Otncj/mZGwkYtv+Te8ujNyOVkqtuuVavlecgzePicu1z7vGH3wCQoWowu+0ASWKIW6E67fo7y36+u6olLdWm9z0Lus6Kj10xvJxE5azjhVTmA7fj938sGijdOJ8enVbvB6f+wGdAPsYLy+w0kP8LryKMnM84IX1tRzn+RBsp9EekRo/0R+6IdB2QnWGttP7THHdzlN7+Z4TkceZitOJBhO8G4UgzY90Hrcm8n7nlFY4Pl5sC7aq2GOL4oTl6hZ0JqEvWScBjpgkYyNxXzWbCbymR17kdqw2X2cztnKshm/LDoZaRgE0Gj/wZWkFtxGkukGIivEr957kKq+yluKOYE20eKf194CoO2HVhk1ENLeMnfszl0da0LbM9K63AhNtKxu0VOHl+Nwv6ATYx3h5gaHi5+NjVyRdZMqtWE5OlonraLIHtDLCQ0VVmIjot+NZEma3cYXtt6rVZbccEGaS0932lmzQ0qRgm9zSRORmmPkusQgKn4Lr8dwy58RaZLCkdZGIaN7G6IA2XsQE1pwr3qjYcSAG5MFQi12MRuMHcCwED6e52CfGrow8dsHmSs5v+88SmzC0lsxZa72BtAcEtq7pkUdhm1hvGWya3jusZdMU54LfL9xt+x6e/IC9B5UNwmTi5fjcL+gE2Md4dYGJ8yNWQVkiwUDs2Y9XOz4exWMyQVFQo0kUqOCJB/o82vEGzKGOsVFUn1lyOPK45yassXxcPIjiLU4q1l7HSm3ZDgwKv7QICrH6s2LvCdfnhd66r08vi9yOdikqvtEq1NTxVW1zdGb1vpOR2+4eusTy+YbBWzMFQ7m0cHuV5eM1Gi9RIplxD4acxe3+8AmbF85Zc5Abi5Dps2BiOszGdghF58yk1ortlayjx+ziwPOys3Ij4jUShi+0T5aTjVfjcz+hE2Af49UFVg6y9ld3z0tJ1aYQgv5HRjnbfAwrUG+70Wi8BAYZeNglswi2UNtZWkxawbwfX5VUEBLBxQbexzjdc1/J5pb+iyLvddORs85PIH7DYsSiaLEncZ7PyirFDqsOG1T5f+OLxHjtNjTJ7Y6w3fohh3ZrbJUMhnJp1T61zQSNJtNBSyM8Xv+8zPZ5/xA2NjHxnCLRGxi+cHfk/n/NtNZVwW66302wT8KPC0J2dQ1N9Mio5ZH/O3W9oADY3x3eb7LxanzuJ3QC7GO8usBQre/mfgudn5AAVkF14J5h1tUBk95gJTAgTnVqjSaTqLnYKA2Q7NrYkPHLWHeErDXOhBOeswmQ4kGs5h04WZuU18kU2vRgiaqqZdz7hSxQlSk8i3PCsfg1fw3zgr/6gHnzDnLpW6zKNT3Y7Hr5iZbfwzdb5OcgAyvewVAubTxsLcyj0XgJUQ1ddf1hzNNvwQ5O66FoR/SM7+frWIfPb8dbd/jgDO/bszfbnoOoRn3kdB236Vd6yL5bEGeI0SM8HXg1PvcTOgH2MV5dYCv2Rs95JBvV+TCTf81k7T3aIkPjN1Dx0zzQv9UOHCewE4jDSnEfBeuxWLmxr5oqtde51MRXu4/bWFAhszYciTxHNoeLHTmtu9vP6FmBs3v3geAZ2myp+K+rgn/zrRUtf/PZ8D472wTkRLwtSzCUS3uOn0/YuWk06aS+sTnq2h4MOc/PjhCs0HCzTdYVsnS3WmuzUweKCGoWoIq8mRDbUXroDN3cbyE99eGqhG64xYJX43M/oRNgH+PVBZa7hYnj2Pm6JRIUYmjby9mTtMs0por6yUpnuxGNxktgW5l5rC5XawPFboq7hlh3U/x7zubI494rTFzyI3Ln4MWR11lTfippr5NuRO0EK89zEfTNbT8gevNvHdz/84GxWRVhV8/PoKvn9ellkds/Kt4X08+Wcfsg9jdft7/lb56zhs0b/3Gy/bwxCrkFQy2+pxqNX2jbKz/q+j5phb3V15RVTBxR3CC6ILnWoJ1Ymx750o0zwzDoDrg+q4jNPThiWeTxuKaDIWsfY3y9TMGr8bmf0Amwj/HqApuxPvniOCIVZ+q4C6mT6jQGSLNKjqTkHDWaVNFlWklUgKQ6+4kzZm16WHvL/m263Bs20TwEAZOsVc8vqPrcioiqyWIwi63DsW5IimrcZjCMc4SfKbbYq9BpOGvPXLq7moh4q7u/fmYvXIgbnMFQLp2pbUjYuWk06abDoKKo67uVAJ7J/I3M+hHt8azG1MTRCZn+ws5j57jHnFQYr3huAou9us1lQlxes7nzanzuJ3QC7GO8usAmLmfiOHYzhIlENEk/V99o+/jHxrAd0Pytaq2hGo1X6Pv19qgAycojVkRU4bVKHpKV/Ig8/RGz8Plqk3/tbNDzuJ2LYDAcNqgNiFztPMZvdGDlx6lyasXpWvn1Fe3uEvm3eXwsuz6brfujitRnzlHBNhjKpYamcMLOTaNJNw+PjO7wsfNsJ+JbmvGwm6e/AUZpNktE+VAd/kmHuXyTv3/Oukbw+vHA8GKl52cKXo3P/YROgH2MVxfYCFAPfGuWvShCohCVQ+3M2ImI7h3GTN5jsQXRaDIZ3IRymwQYBp9Q7a6Sz08+laTkRyRViXa6wVbmOwcvdvXcB6BiOjhvJzc//F6hukiNFU0S8Roi4oR0zEptIugMHTqzN7R06AzOZ4Jb3R3m/3AD6JoeeQk7L40mE+g8bk3U9b3MQegNxxjwsLOBxO4bmULzb8atjtyvqqWCaxNbuZ0UpDMNr8bnfkInwD7GqwsML3Cq3qOJQKYcakUsdiMajVfI33qMC3La9XHXXqbiG4uzXE7Vh3j462es1Xr8suS1Wqeboh3qNj8iL0+Nbnl/YuxKGlW0h/44eX3ktqE2fp5OYDVoe2WLMFX7AawV00nB1Q0vTWHnPG31QSIi6gMqtjLfUgQtXG56NzVOBBpNqnj10w1R691JIR9HLPAYnLfT8jkvwrVjsqCVcraugVPo31KhFkehdRoe/5Qo2GcyXo3P/YROgH2MVxfYW7OYOM6IFJqVo/ejqRwqwzAMLllWtRvRaLzClgp+t9+tGvsz0HZsNVuGc2jrDyQu+RF5eza7ngxP4fUk1Xy1ic3oPS1Rc7ZjTmmFNKgUDzGIdQOKkZmCatgpsDeBSsuy+XIUXXNSvMUOCLfVdI0m08Fronk4zbmLoy3mYWePF/qSqbwPzOU3nfB61X5AkbK6/BegEYOH1+wovRqf+wmdAPsYry4w3J2cuNxemTCRYIC2dr+1WqxoI6A6G6nReAVxZvNJGzsjGa/lOAtcXd+7IPKYHZVqAluxgB0l7y5IXUdJqvls7aHI+/zDJ+tcP7/00Gl6d8F2umfYEmmAGQzl0tebK2M+P1QWL9h2LOo66jR24gYM8M1NVLRb+XCpveI0CjE+6LKartFkOmhBFwy1iOY5CX+Gw7ynunnYjS6MLmLV2tc/L+PuQytJN6MVi6DTBY8Jy73V3ePV+NxPeD4BLi0tpSFDhtAzzzxDP/7xjykQCFAg4O5tPfjgg5HnVVREVytqa2spJyeH3njjDerQoQN997vfpUAgQH379k3QuyB65ZVXIuewcmViDLq9usBQ5W/G+sMpe12cV1m807ol88R53m6krkHNbkSj8QqGYdC1vViC+qcp7sSPekO7qSzpbA4b3Bpy8m+Mh/cLWTvrv+ekRlMgHYxbxlSO7ebynDAMg/YcP08fFe+jZz9eTa26sXk7VW9hGaicP7PkcFKvo70l7c6obO5UyV4OvsW/n+R+M0GjyWTGLubbiH9moeQsgqNf5mHXAWflMd4cNjg/3zwXQqIbD5+RJsAqFkqZhFfjcz/h+QT4qaeeiiSOeKgydepUCgQCdMUVV1gmwJs2bZK+RqIS4KVLl3LnkO0JMCosu7kwxgsqCtpVOvafuBB5XOvueRnlLafRJArcEHIrRodzWq9PL4u6v+Yi3053ti55NjMfFycmMcx0kpXon7xwiYp2HKdDp+xnBJ34M3T2TFheTuVwHb06wdfRIflMuKvb3BbBqxcmrY3c9oXDxmo4bFDXWZvo0dErqORg8trzNZp08Kngn3v/+8VKz0N7MfOw895duZd5wt8BowSlh85wa9/JdQM5crou6hyCoVxatU/Npz5T8Gp87ic8nwAPHTqUevfuTQsWLKCqqiq68sorlRPgEydO0A9+8AN6+OGHKRgMWibA5eXl1KVLFxo/fjyVlZVR//79E5YA19fXU5s2beiGG26gu+66SyfAlD6F5ecnsgDJrvKM85FaIEXjV1BISJzfcmJWCdv5/8241VH3Hz3Le882NSfPZiYHWoNfjNHGxwtgq3e/BZk3D/cOtCW/V7iLU5W18hKNlTFQ4TLFcXAu3WvVIo0mkeD8bTCkrhmAaygYyqXbBhbZPh43ua7qxq7zKDL33IQ1rs69rqFJmgAnUkMgFXg1PvcTnk+ARdwkwC+88AJ973vfo/LyctsEWGTIkCEJS4B79OhBV1xxBa1cuZI6duyoE2AirjUmlQrLXaaxCsUnNi1yq/axXc27hy5J2flpNKkEPRoXuJz9RM/I+96LFtDaVXUucv+1vQoSdcpS5m1kAk/PuBSH8hKceOAiNUuRVDIA5g57zt/KtRnLPiPxMGkFE7F69bKX/KOjWWdRwbaqhL6eRuMligVP35enlig97xVBLd4pcb7YwM/5V569SER8l18ss7vXgX6EedTUqVeRMwGvxud+ImsT4IKCAgoEAjRgwAAiorQkwFu3bqXvfOc71KVLFyIinQBTy/zZ1d3V7YgSyZszmEjKmMV7LR9XsK0q8rhHRi1P2flpNKmkrqGJxi0rp5w1B11XaLdX1nAJrtjeuuHgaeUqQrws3M7W68Mj/bte/5KTHvFAVXDu8B9fbKTcLcxq6/GxKxL6Wp+vYyJW5gzv/eA5vGyP9m7XZC/iHG3XWZuUnoebbOY6dgILGqWHTtPxc/VxV26xSzAYyqU2PfM9N4rmxfjcb2RlAlxbW0utWrWia6+9lhoaWmbPUp0Ah8NhuuOOO+h//ud/6PTplhkjnQBHt7dUn0+dwnL3eVsjrzs439rbbjYIO3Qe5659R6PJBkSBo/PCjBdWiDsNL07quawuZx0bdw3xb8cGzrh+vi514oGqTFvN5g7/OHk9Z2fy/MS1CX2t+RujLaHQdkvP9WqymQMna7nrs+rIxABBPXqYgi/4L6HzYsHmSppZwtb93UOXxJS4iq3YXryuezE+9xtZmQC/9dZbFAgEaNkyZm+Q6gR47NixFAgE6NNPP43cphNgitodtBNYSDQDc9nFvdf8bZaPm7LqgOvWIY0mmwiHDWpt08nx9ebKyH1PfpCY650V2TKz/+QHKyPvMx67omSBSelTH66i8aBa/VpOYsXJsOpvdunc2Lcwctu2o9Y+7xqN3xFt7sbadLwhKG4YDDmLyRHx6usTlpdznSq9v7KOs+xAq0yVVuxMxIvxud/IugS4rKyMvvWtb9FLL73E3Z7KBLiiooL+67/+i+6//37u9lgTYHMhiceVV17puQW2r/o8a2vpkdq2lpGL9ii1BMkEVjQaDQ9W3NaU877ashbVZLE/iWrDmcQDoNC6dJe1N2e6WLoLqv7vF3Oq1e+48AFVAdVn7x3WMl/cpkd+5DY76xaNxu80NYe5BDJn7SGl56HXeDCkJlLaaz6zJOs+byvn/x7rdarb3K3cefz58py/l9AJcPrJqgS4ubmZbrnlFvrhD39IJ0/ykumpTICffPJJ+u53v0u7dvHtIzoBJiqD2ZRb+y9K6WtPWK5WkRiUtzPyuB7ztqbwDDUa7/DEWFaR/GoTr7qbzOqfSHUau0pSSaa3+KL1ya39F0m9epPxWu0HLIoK+I9eFuPRaLKVdn1YR8Q3W9Q6RnBuPxjKpYMnna3RPipmYoroI/zTnvkxX4tRRToYahH26qHWAAAgAElEQVTV8xo6AU4/WZUADx8+nAKBAE2ePDnqvlQlwF9++SUFAgHq3bt31H26BZpoGSiDdkywMqgT09ex3c0/fGJdleo2d0vkcUPynWdgNJpsBBVDJ63gRZkwgHk7wdU/kdpLvK7AyQuXkvp66QIrKzuPnUv36USxr5qvxKPo4KiixKpWo8r4db0L6ILwGThdmzzfaY3GC6Cnr+qG2WpwwGjVLZcuNTknsDj6gMefpsRuSYd6AsGQvWhppuLF+NxvZFUC3LFjR7riiivovvvuo44dO3KH+bw77riDOnbsSAUF1tYc8STAL730Evc6ePz3f/83BQIBuvnmm6ljx440depU1z8f8eIC+2YLmw18YmxyZwNF8EJtZ5fy98/LIo/7cOm+FJ6hRuMdcKNoUB4vKoeete8u2J7U8zAMg1p1Y8HSoVPOVQuv0Rw2uIDwyOm6dJ9SFKIw2u8mMNGuyTa2c7Fw+FQd91rZ0gWg0ajyZWkFtetTSK9MLaFwWG0s5Pi5+ohLx2Nj1JTb1+0/JU2Ac9YcjPncxUq0yixypuHF+NxvZF0CHAgElA675DMRCbDKEa/NkhcXGM4GJloZ1AmZcIqMP05eH3ncp3FcxDUaPzMCZurfFGblOc/ahbuTfi7Y7udHAaRz9Y1cQHi2LvMqnJeaeE/Qe4Ytifx7Tqlz55UbTl7gk+3dVee5//t1DlyjcUOzYuKLLNhcSW/P3kzbK9Wuo0dO85tRidikWysk1Yt3Ho/5Z6ULL8bnfiOrEmA70uEDLKJboPnZwL/kpFbYYBW099wzzFpW/9mPV0ceN29jYgM3jcYv4EiBuJmVas/aOwYvjrzeuv2nnJ/gMSrPXuQCwkaXvs2pom0vJkSFKuGF26sS+jqinR62bl7by7q7S6PRJJaGpjDXgRMM5dJDI5Y5P9EGHKcIhnJpa4X3NjW9GJ/7DZ0AXyYZCXDbtm2pbdu2dPToUdvHmegEmJKqDOoEmsPfYiPA9YuRyyKPW7TDezuPGk0qWLTjeGSdPCgEPM9PZO2vqWhfe3AEW7NerBY4sec4q3D+tGd+uk/HEhTqwkNUCY+XsNASjrZbdtd2jUaTeG4byK/7wcJIjFtqLvIdL9Xn6hN0pqnDi/G53/B8Apybm0u333575LjiiisoEAhwt+Xm5jr+HKcE+Omnn478vJ/85CcUCAToxz/+ceS2p59+Ouo5ZivzwYMHld6LToCJ+oAyqKo5e6LYqxhE3gnVpLU+rCZpNIlg8xHmv3tj30Luvl+BZ62qAmk8PPnhqsjriYrUfkBUPc5UcPMQj2S0pV8HomBTwbv9riHW3T0ajSbxoEd5ouKm1y9rsXSZVpKAM0w9XozP/YbnE+CpU6fGNc9r4pQAm/dbHcFgMOo5OgF2T9eZmyIXyZGLEqsM6sRRoY2wyaKN0O/zhBpNIjhWw68nFB66/32mQFq8O/metb+ftC7yep+v855gihPL06ie74bfjFstTYCTIdrVfgCzXEHV8QeGFyf8tTQajTWv5ZRG1l+7voUJGdEwDIOOnK7z7Dy/F+Nzv+H5BFhjjRcXWJdpbDZQtE5JNmfrGrig7Fx9Y9RjwmFeUfbwqcxTW9VoMoHGZn72C5Oc9gNYS1zpoeR71uLM8YTl5Ul/vVSTt5Wpoj4+Vk2dNR10mVYiTYCTIdp177ClkZ/ffd7WyL9T7S6g0WQ7A3N3RNbf69PL0n06GYEX43O/oRNgH+PFBdZ5/JrIhXJWyZGUvnZDU5gLyqpqoudKzgtqq9pPUqOx5tb+i6SJLooh7Tl+Punn0XUW6ywZkeLOklQwq+RI5P09N2FNuk/HEvw7qHTbxMMjo5ZHfj5ugHQel7m/H43Gj+yrvkC3DSyim95dSDsqM8+jPB14MT73GzoB9jFeXGCPjl4RCVTytx5L+eu36cEC833VF6LuF9s6G5oyU21Vo8kEMAkx13NjM7/RVHn2YtLPI53aAqngk5VsxrXLtNSq57sB/Z/N44Y+hc5PjIGnP2Jz378G5f4XJ69PyutpNBprGprCMdku+RUvxud+QyfAPsaLC+zuocwbctW+kyl//Z/1Wxh5/S0VZ6Pu94raqkaTCbwIntnTVh8kIqIztfyowXnJqEGiGVawK/J6/5mzJemvl2pGF+2NvL9/zdyU7tOxZCR4Q5vHHYMXJ+W1cO67E8ycp9peT6PRaES8GJ/7DZ0A+xgvLrCb3rVPQJPNXUNYAi6z5uDVVotSfn4ajZd4e/bmyHp5r3AXEREdPlXHJUDhFFQFPirex2bQPvffDBrO2PWavy3dp2PJZKhUm8fDI5cn5bVe/ZS1Pd/YlwkXvjljY1JeT6PRaFTxYnzuN3QC7GO8tsAMw6DW3fMigcqBk7UpP4eHHPxCi3dXR+6///3ilJ+fRuMlsPJq+npvr6xJevuryKdrDkZe848+bIHtNndL5P0NLdiV7tOx5MvSiqgE+Ncfr07Ka705Y6N03rjb3K1JeT2NRqNRxWvxuR/RCbCP8doCq73UxAUqJy9cSvk5OPmFLthcGbn/Vx9oNVGNxg70XzUTz7X7TyW9/VUEE69kJVzp5O+XPTGDoVz6cOm+dJ+OJUU7jkclpC9PTY6PZ7e5W6UJsB9nwDUajbfwWnzuR3QC7GO8tsCqauq5QOVSU7PzkxLMC5PWRl7/i/XRfqFfrD8cuf/5iWtTfn4ajZdAe55HR7fY82AS9NCIZSk5j8LtVZHXfGRUclpu08lLU6JnrTORkoOnoxLSZLUk9/9mhzQBNlvxNRqNJl14LT73IzoB9jFeW2AoMNUmTQJTODcm8yGesLxci6loNIpsgISn/YBFREQ0f+PRyG3PfLQqJeexat/JyGvePXRJSl4zlfxmHFM5/rK0It2nYwle45M9szxi4W5pAvzBkr1JeT2NRqNRxWvxuR/RCbCP8doCKz2EwXJ6BKZwbmzM4uhACYOqt2ZtTsMZajTeAQWvWnVr8XvNgXncVFnSbD5yNvKaN/dbmJLXjJeyw2eo68xNtHB7leNj0W6qUOHx6ULs8klmRfbj4nJpAizb2NRoNJpU4rX43I/oBNjHeG2BLQWBqU5pEpjqPo/NjQ3O3xl1P/pY9v16exrOUKPxDvWNzVzyUVVTzysyT0+NIvO+6guR17ymR15KXjNe7r9s3XNtrwKqqfv/7N15eBRVuj/wE0ESFZVtFi93JqgguDGigIwLGfQqMjIERHQUZ5gRdS4OI4L+LiAiArIpAoK4IQRQcGMNgQABwpKELSGELSEJBLKQjZAEspCtv78/NKer0p3O2n2qqr+f56nnIVXVVW/n6bd531TVOa6nitJOHxepYPq4+iopq3RoSD/fneyWc2kHPtMuqw44PtpCRORJZqvPrYgNsIWZLcE2agaYGqRogKkZm0/JGCatdxwtVDuty9xtCQoiJDKXezRT0MSl5WO2ZmTo8Ws8MyevEcYXaIjKKpsu3thU11PC1TV/uVHYbDZ0eWeLRxrSHw+nOm2A1x0x7i3iROQdzFafWxEbYAszW4J9e+CcLFKGLzmgJIb5YadlDGO/j3XY/tpK+zPCX+5xz5ULIit5bG64zJmwk1l4d/1x+fP0TZ4ZkfdKjRHmLyoYYb4hisv08Tqbkq2azWbD7Zrp487kXPFgpA33wPQw3XvbFJfhlvOExF1w2gCHHr/glvMREdWX2epzK2IDbGFmS7DPd9uf2frfb6KVxPDVnjMuB7nSjhLNW+mI6vbXL/U58+b3sfLnBWGeGZCoqsYV1fMXiz1y3sa6eOWqLt4fDqXWum/N28yzL5d6MNKG0/5BxH98CHafznHLebSP1GiX8IRst5yPiKi+zFafWxEbYAszW4LN0dwa+f9+UjPAlPYq9EtfO16F/suifXJ78FH3XLkgspI3NAPLzQ87jZHLD8mfv9531mNx3P2e/VbskxmFHjtvY6Tnl+iatsXhtc/tm3NZ3ywXl1V4MNKGG7I4QhfvkfOX3HKeA5r5prXLgTMX3XI+IqL6Mlt9bkVsgC3MbAmm4tbImrRTtAx2MkVLv4/sVy928UoCUZ0+CLHPxzpx3TE890VUva5sNrfeM+y33h48m+ex8zaGdtAu//EhmBpc+/fh2dwiud+tE0Jgs9k8GGnD/UMzZ7H/+BAkZbvnlu1jaQVOG2AjPyNNRN7BbPW5FbEBtjCzJZh2CiJP3RpZ0/aTWTKGJ+ftcdiufX4t+pyxi2giI9A+VjBy+WEMWLBX/rzlmOeex+ynufV2V7yx/3h1PF3fvL3x3ZF67XvvlK0ejLJxtHcEuPOW7eScK04b4KTsy245HxFRfZmtPrciNsAWZrYEeznIfmvkUg/eGqkVmZQrY3h49k6H7V3ftY9gmpDJQoqoLhti7XdVDFq0D4/O2SV/3pvonuc/nRmkeXxho8EfXzickqdr2lwNChiVbL/V96FZjt9ZRjN5w3Hdeystd8+I3BcKSpw2wGmXjP38NxFZn9nqcytiA2xhZkuwYZ/bb4388bDnbo3Uik3NlzH0mLZdt628skpXSGXklyiJkchMIpPtf1TqM3MHekzbLn+ua3qf5vTCV/bBuFYfNPYAdnsTc3TfNf3nO96NUq2uu1aMZu62BBlvl3e2uO2W7YKScqcNsNFHACci6zNbfW5FbIAtzGwJ1n/+HlmkhB7PVBJDYtZlGcMdk7botl0qKtMVUpdLy5XESGQm2udZb5+4GZ3fsU/Z467nP515dYV9CrMle8947LyNoW1q/ceH4IHpYbXuu+5Imtzvmc8iPRhl4yzZe0bzvrbX/YJGqvkHy+rF6IOEEZH1ma0+tyI2wBZmtgR7aNZOWaREJuUqiSGjxuirFZVVctv5i8VyfacJIaiqMvZgM0RGUFjq/Eqc//gQZBV6bsqesZrpl+ZtP+2x8zbGxqMZut/TrS6+b1ZGpcj9/r70oIcjbbgfDqfKeP/0Ubhbz6X9Y0v1wu9tIlLNbPW5FbEBtjCzJdg9U+zTlBxPL1ASQ0GxvlgvKLFf5T2RYR9s5p73jD/YDJER2Gw23bPzqq7GGWGU+frSNonVS15RmdN9F4cnyX1eXxXj4UgbLvqc/fnmfwYdcuu5ur+/Tfc77PrulrpfRETkZmarz62IDbCFmSnBqqps6DTBXqicu1ikJI6yCv1tcxcK7M/57tfMK9ln5g4l8RGZkXbgq+rltombPTplz2zNPOPj18R57LyNsUJzVbd6ScxyPujeHBO9L+DnP4gsCEvEqysOIz7TvfMx95m5Q/c7vG/qNreej4ioPsxUn1sVG2ALM1OCXa5xm2RtVzs8ocs79qtV2mcUwzTP5T0xb7ey+IjMZuhnkQ4NXff3PduMfLrLfqX03wa/UvrlnmSH31dksvPHQrSjKk8z+JVtT3tMM/WV//gQ/JF/uCQiAzBTfW5VbIAtzEwJVvPZ23LNs7ee9oep9tvm4tLso9RqB5sZsjhCWXxEZjPq22iHhs7TU/YERZyV5/7HMmM/K7sgLNHh9xVcy9RNZnq22dMGLtyn+x32mxuuOiQiIlPV51bFBtjCzJRgCZn20ZdVP6elG4xLc9XFbIPNEBnFlI0nHBo6V1P7uMNP0fY/YD37ubFHS9berl29BEU4nxvdTKNbe9qwL6J0v8M/f7JXdUhERKaqz62KDbCFmSnBDqXYB0bp+UHtU354whPzdstYwk5myfXaWyjNMNgMkVFoB2pS1YSGHr8gz/3UAmM3Qs7+YDB3W4LTfbXzG39n8PmNPe0fyw7qfodDTTBNFBFZn5nqc6tiA2xhZkqwnfH252sfU3ybWuCnETKWDbHpcr32qsyEtcYfbIbIKLRXX1XdhrwvMVee+5E5nr39uqEmrI1z+H3V9p3zl0X223w3xTm/Tdpbvf5tjO53+NLXB1SHRERkqvrcqtgAW5iZEmxDbLosUgI/Vft87YtL7FdUVmuuqExaf0yu/yCEg80Q1dee0zkODd1/Vh/xaAxHzl+S5+4xbbtHz91QY7474vD7emXFYaf79vvIPtBTeEK2hyM1trd/PKr7Hb5ay++QiMiTzFSfWxUbYAszU4Kt3H/OMH+lr+2Zujc0ReknOxIVRkhkLvGZhQ4N3cR1xzwaQ2KWfZyBLpOMPR/saysPO/y+aht4r+cHYXKf6HN5Ho7U2N7TjJDtPz4Eb3zn2T+6EBE5Y6b63KrYAFuYmRJM+4zg69+qfb72Tc2oqgvC7I3uy0GH5Pql+5wPSENEjvKKyhwauplbTnk0hgsF+pHmyyrUjTRfl78vPejw++r74S6n+3Z7N1Tuk5DpfK5gbzVri34wMTPMk0xE1mem+tyq2ABbmJkSTPt8reoi5Z119ludZ262F+nDPrePKPrj4VSFERKZi81mQ+d3NuuakUU7PXsXRWGNucYvKZxrvC41Ry/2Hx+CuyaHOuxXUVml2yftUrGCaI1r4Q79dFJTNp5QHRIRkanqc6tiA2xhZkowbdOp+vnaGZtPyVgmrbffpvnUgr1yfejxCwojJDKfP87coWtGapvWx10qq2y686fmGbdZHLRon0MD7D8+BCVllbr9Cor1TX1BcbmiiI1pyd4zut/PnNB41SEREZmqPrcqNsAWZqYE+89q4zxfOz/stIxl7Pexcv3Ds+3zA0ck5bo4AhHVNEgzurr/+BCsiU7zeAx3TrbfLnzqQqHHz19f2qnYXF3hTc/X39ZdUWnc27pVWH3wvO73s5BjNxCRAZipPrcqNsAWZqYE087X6OkrQzVprxpoRw39w9Rtcv3R1HyFERKZzysr9AM7bT2R6fEYtANGHU4x7oBRj87Z5bQBrvm9k5BpH9ir27uOt0h7O+3sAjUHNSQiUsVM9blVsQG2MDMl2NDPIpVeGdJadcB+1WD4kp9HpLbZbLhtov0ZxjM5V5TGSGQ22scc/MeHIDLZ83dRaKcM2mXgKYO0jbp22XEqS7df9Lk8ua3nB2GKojWubScydb+/b/afUx0SEZGp6nOrYgNsYWZKsCfn7ZFFyjYFV4a0tFcNBv8y9UhJWaWukMq+XKo0RiKzWRCmH5DoWFqBx2MYuND+bO2muAyPn7++7pmyVcZ593v2f/9wSD/4XnhCttzW76NwNcEaWERSrvLb7omIajJTfW5VbIAtzEwJph0gJyr5otJYtp/MkrE8OW8PACC7sFRXSJWWV9ZxFCLSqvk85tncIo/H8Ncv98vzf3/ovMfPX1/aEbP7z7f/cXBxeJJuv01xGXLbXxbtUxStccWcv6T7zG05xsELiUg9M9XnVsUG2MLMlGDaqxzH0z1/ZUgrUnPV4KFZOwEAyTlX5LrbJ26GzWZTGiOR2ew4laVrRnKvXPV4DCOX259DNurzoDWnNhq53D7/+LRN+hHyv9P8UeGFr/Yriti4tM9IG/22dyLyHmaqz62KDbCFmSXBak5Pcv6i2ulJjqbmy1jum7oNABDrZB0R1d+xtALld1GM+c4+2vyCMGOOCHzlaoXu9zRl4wn57ze+O6LbVztg3yuaAfvoZ6l5xbrf5f4zau8uIiICzFOfWxkbYAszS4IVlOjnsswvLlMaT1K2/apBl0lbAAD7Eu1XhR+Zs1NpfERmdOVqhXy2VdXzqpPWG2e+8drkXL7qMHJxzUH5qs3b7nzKNvpZ7hX975Kj9xOREZilPrcyNsAWZpYES7uk/yu96rksM2rMrVleWYUtxy7Inwcs2Ks0PiKzikzKxXsbjit7zGHmllMyjyesPaYkhrrUvGq5WfPd03/+Ht2+0zadlNsmbziuKGLjqjl44emsy6pDIiIyTX1uZWyALcwsCXbqQqEsUO6crH4uy4Ji/RXpgpJy/HA4Vf783BdRqkMkokZYtNM+EvV/Vh+p+wUKJGbZ70C5Y9IWHEqxT3X0wHT9VEfj18TJbXNC4xVFbFw2mw33/DK+RKcJIci57PnnzomIajJLfW5lbIAtzCwJdvCsvcDrPUP9XJblNQahycgvwdf7zuoGpSEi81kWYc/jfwYZM4+1z0r/Yeo2nNEMwHfrhBBUVdkH4Ht9VUytI0TTz1ZEpaD3jDD+gYCIDMMs9bmVsQG2MLMkWJhm2qHHP96tOhwAQJdJW2RMSdmXdXOYvsln7YhMSXsnxzCD3smh/YPggzN2oLBUf0dKXpF9jIS/Lz0o16+MSlEXNBER1ZtZ6nMrYwNsYWZJsHVH0mQRN3hxhOpwAAD3Td2mGzhluuZZu3fX81k7IjMyw7P8e07nyBj/9FE4bDYburxj/4NcouY51mc+i5Tr1x1JUxg1ERHVl1nqcytjA2xhZkmwFVEpsoj7+9KDqsMBADw0a6eMKTI5l8/aEVmAtrns++Eu1eE4tfVEpsOgV31m7tB9H1V7ct4euX77ySxVIRMRUQOYpT63MtM3wNHR0Zg1axaGDBmCjh07QggBIRr2th5//HH5urQ0x7+iFxUVYeXKlRg9ejR69+6NVq1aQQiBKVOmNDrmKVOm4I9//CNuvvlmXHvttfjv//5vDB8+HHFxcY06pjNmSbBPdyXJIu7fq2JUhwMAeGLebl1h+fq3fNaOyOyiz13SDCi1XXU4Tm2ITXe4I+bphXvluuCjGXJf7R/qopI5xy0RkRmYpT63MtM3wIGBgbJ51S71FRQUBCEEfHx8am2AY2NjnZ6jMQ1wRUWFfH27du0wYMAAPPvss7j99tshhECrVq3w008/Nfi4zpglwYw4NcngxREypg2x6fib9lm7/edUh0dEjXC6xgjLRvT9ofMyxr9+uR8AMGKZ/fsnKOKs3PfeX+ZV9h8fgmNpaqaWIiKihjFLfW5lpm+AZ8+ejcmTJyM4OBiZmZnw9fWtdwOck5ODdu3a4cknn4S/v3+tDXBycjJGjhyJL774AjExMZg2bVqTGuBevXphw4YNqKyslOurqqowadIkCCFw4403Ijc318VR6scsCTZx3TFZxM3cfEp1OACA4UsOyJhWHTiva4jXH0lXHR4RNUK6kzm+jSbIyUjV4344KtfN3ZYA4Ocpfm6dYH8vZ3OLVIZNRET1ZJb63MpM3wDX1JAG+MUXX4Sfnx+Sk5NdNsA1zZo1q0m3QNfGZrOha9euEEJg+fLlTT6eWRLs35qpPBbtTFQdDgDg1RWHZUxL9p7B/3xsvyV6xyk+a0dkRgUl+hGV84vL6n6Rh32+O1nGN+rbaADAzM3au2R+fkymuKxC9144xy0RkTmYpT63Mq9tgENDQyGEwPTp0wHAEA0wAAwbNgxCCMycObPJxzJLgmmn8lgemaI6HADAm9/HypgWhCXiwRn2QWgOnOGzdkRmVFFjju+0S8WqQ3Iwb/tpGd/YH36ecu2rPWfkuldWHAYAZF8u1b2X0vJKV4clIiKDMEt9bmVe2QAXFRWhU6dO6NatG8rKfr4CYJQG+IEHHoAQAsuWLWvyscySYEM0txcbZSqPSevtt2XP2HwKd00OlT+fzChUHR4RNVLXd+1TCiVkXq77BR6mHRNh4rqfx0RYG2OfKm7ILwNjncm5ItfdPnEzbDabyrCJiKiezFKfW5lXNsDjxo2DEAK7d++W64zQAO/bt08OhHXhwoUmH88sCaa9vTjMIFN51LzlUHulJTXPeFeNiKh+HpgeJnM5+lye6nAcvLfhuIxv2qaTAIDdTqZvikvLl+v+MHWbypCJiKgBzFKfW5nXNcAxMTFo0aIFRowYoVuvugEuLCxEly5dIITA+PHjG/Ta6kSqufj6+poiwYx4e/GCsEQZ08tBhwz/3CAR1U/Ah7tkLu8+naM6HAf/95P9D24fbf15wKvj6QVy3V2TQwEAkUm5ct3Ds3eqDJmIiBqADbB6XtUAV1ZWokePHmjfvr3DKMsqG+DKykoMHDgQQgj07t1b3pZdX2ZvgI14e/GSvfZn7rRzcBp15Fgiqh9tPofENf1Om+b2n9VHHAYFzCrUP+9bUlaJrScy5c/95+9RHDUREdUXG2D1vKoBnjt3LoQQWLp0qcM2lQ3wq6++CiEEunbt2izTH1UzQ4LVHJTGKLcXrzpgn4tTe8tkt3dDVYdGRE3w3BdRMp9/OJSqOhwHNUegB4CyCsfBu9ZE258LHvpZpOKoiYiovsxQn1udVzXAAQEB8PHxQd++fREQEKBbql/Xp08fBAQEIDS09kanORvg8ePHQwiB3/3ud0hNbd5izAwJll9cpivsCorLVYcEANgQmy5j6qSZa7PnB2GqQyOiJtA+0rB031nV4Th46Wv7HOTf7D8n13d/f5tcfzQ1H8sjU+TPI5YdVBgxERE1hBnqc6vzugZYCFGvJSgoqNZzNFcDPGfOHAgh8Otf/xoJCQlNOpYzZkiw1LxiXQNcWWWMkUzDTmbp4qpe+s0NVx0aETXBG9/ZbzH+ZIcx5h3XevbzSBnfmmj7HUn95obL9TtOZeHTXUny53+vilEYMRERNYQZ6nOr86oG2BVP3wL91VdfQQiBNm3aIDY2ttHHccUMCXYiwz64y93vbVUdjhSZnOu0AR60aJ/q0IioCSaus09xNnPzKdXhOBi4cJ/TZ5SH1bh1e3ZovG6keiIiMgcz1OdWxwb4F+5ogLt27YquXbsiPT1dt/6nn37CNddcg9atWyMqKqrBsdaXGRJs/5mLsojrM3OH6nCko6n5Thvg4UsOqA6NiJpAO8VZ9Ty7RvK4Zlq4nfH2aeFGfRst1y8OT8K76+3TJX0QclJhxERE1BBmqM+tzvQNcEhICB588EG5+Pj4QAihWxcSElLncepqgAcPHiyP97vf/Q5CCHTs2FGuGzx4sMNrqm+nTklJkeuys7PRqlUrCCFw7733YsSIEU6X9evXN/p3Us0MCbZdc6vxE/N21/0CD0nKvuK0Af7XymjVoRFRE3yywz7F2RvfHVEdjoOHZ++U8UUm2QdF1Da80zadxJvfx8qfF4QZ71ZuIiJyzgz1udWZvgEOCgpq0vO81epqgKu317b4+/s7vMZZA5ySklKvZ5CbY4AtM1U/5awAACAASURBVCSYdiTTZww0kumFghKnDfDbPx5VHRoRNcHX+87KfB65/JDqcBw8MH27jC/m/CW5fn7YaV3jPnK5fbTorw04mBcRETlnhvrc6kzfAFPtzJBgQRH2YtRII5kWlJQ7bYDfDz6hOjQiaoIfDqXKfH7uC/c9gtJYd7+3VcannRf9m/3ndI9iPP+lsadzIiIi58xQn1sdG2ALM0OCLdTcjvif1ca5HbG8xvzE1cvH20+rDo2ImiAk7oLM56cX7lUdjoPbJm6W8Z3NLZLrQ4/b4+4/fw+eXrhX/rz52AUXRyQiIiMxQ31udWyALcwMCTZDMyDNOwYbkKbLpC0ODfCSvWdUh0VETbD7dI7M54APd6kOR6fmH94yC0rltkMpebr5yAM+3CV/3n06R2HURETUEGaoz62ODbCFmSHBJqyNk0XcrC3xqsPR6TFtu0MD/N3B86rDIqImiD5nbyQfmB6mOhydwlL9oxf5xWVy25kc+8B8t03crPt+ij53ycVRiYjISMxQn1sdG2ALM0OCvb4qRhZxn+5KUh2OjnY0VmfzchKR+cRnFsp87vZuqOpwdLIvl+q+b0rLK+W2ms2xdjmddVlh1ERE1BBmqM+tjg2whZkhwV76+oAs4lZGpagOR+fJeXscCk3eakhkbmmXinU5XVFZpTok6fxFe2ydJoTAZrPJbTabDV3ecXwsw398CDLySxRGTUREDWGG+tzq2ABbmBkSLPDTCFnErT+SrjocncGLIxwKTe20JERkPvnFZbqcLigpVx2SlJB52eXV6T4zdzhtgAtLjfMeiIjINTPU51bHBtjCzJBgj80Nl0Xczvgs1eHoDF9ywKHQTOSthkSmVnOgqXQDXT09mpov47pv6jaH7dqRn7VLZZXNydGIiMiIzFCfWx0bYAszQ4L1+iBMFnGHUvJUh6Pz2srDDoWmdlRWIjIn7Vy7RrqrY/+ZizKuP87c4bB9xLKDDt9Jd0021nPMRETkmhnqc6tjA2xhZkiwbu+GykIuPrNQdTg6Y7+PdSg2r1ytUB0WETWR9tGL1QYa2T08IVvG1e+jcIft43446vCd1HuGsUayJiIi18xQn1sdG2ALM3qCGflWRACYtP6YLr6ag9IQkTlpp197b8Nx1eFIoccvyLgGLNjrsH2mZt502SjPDfd8oERE1GhGr8+9ARtgCzN6guUV6QejMdpALjWLzXumbFUdEhE1g+WRKTKvh30RpTocaf2RdBnXM59FOmz/as8ZhwZ40KJ9CiIlIqLGMnp97g3YAFuY0RPs3MUi3dXVKoMN5PLJjkRdofnQrJ2qQyKiZnBA86ztvVO2GubOjtUHz8u4Xlyy32H72pg0hwbY2X5ERGRcRq/PvQEbYAszeoIdTy8w9NXVJXv1V1uenLdHdUhE1AwKissNOY/usoizMqaRyw85bN99OsehAX5t5WEFkRIRUWMZvT73BmyALczoCRaZnGvoq6vaqzH+40Mw1MktiURkTto5dXfFZ6sOBwCwODxJxvT6qhiH7do/GlYv4344qiBSIiJqLKPX596ADbCFGT3Btp7IlEVc//nGu7q6ITZdV2iOWHZQdUhE1Ez+oZlSaHF4kupwAAAfb0uQMb31o2Njm1VY6tAAT9l4QkGkRETUWEavz70BG2ALM3qC/RRtf57t2c+Nd3U17GSWrtAcvfqI6pCIqJnMDo2Xuf0fg+T2DM3Ae5PWH3PYXlZR5dAAf7Q1QUGkRETUWEavz70BG2ALM3qCLd1nf97tn0GOz7upFpV8UVdoTljrWJASkTlp7/B4Yt5u1eEAAN5df1zG9EHISaf7dH9/m+576fPdyR6OkoiImsLo9bk3YANsYUZPsAVh9lGW3/jOGFdgtOLS8nWF5szNp1SHRETN5HTWZZnbt03cjKsVlapDwts/HpUxzd3m/Mpuv7nhuu+lb/af83CURETUFEavz70BG2ALM3qCTd90UhZx764/rjocB0nZV3SF5sIdiapDIqJmUl5ZhS7vbJH5fSKjQHVI+PeqGBnPp7ucP5c87Iso3ffS+iPpHo6SiIiawuj1uTdgA2xhRk+w//spThZxc0LjVYfj4EJBia7QDIo4qzokImpGTy3YK/N7bUya6nAwcvlhGc/X+5x/34z6Nlr3vRR2MsvDURIRUVMYvT73BmyALczoCaYt5D4LN95zbIWl+rlCf4pWXyATUfMZ+32szO8ZBnjEYfiSAzKeVQfOO91H+5yw//gQ7D9z0cNREhFRUxi9PvcGbIAtzOgJ9tLX9mLPiM+xVVTqR1zdeiJTdUhE1Iy+3JMs8/ulrw+oDgdDP4uU8aw74vwPbvPDTuu+l46nq791m4iI6s/o9bk3YANsYUZPsEGL9skibkOsMZ9ju2OS/RnByORc1eEQUTPaczpH5nfPD8JUh4M/f2K/JXvLsQtO9/lm/zldA3zuYpGHoyQioqYwen3uDdgAW5jRE6zfR/bRTHfFZ6sOx6k/aWJMyWWhSWQl2ZdLdc1k7pWrSuPRjvC8K8H5d2Lo8Qu6mC8qjpmIiBrG6PW5N2ADbGFGTjCbzYb7ptrnszyckqc6JKe2nchE//l7ap2ShIjMy2az4f5p2+X3UESS2rs8Hpq1U8YSlez82d5DKXm6BtgI0zcREVH9Gbk+9xZsgC3MyAmWkV/CqxhEpNwLX+2vc+RlT+mhacZjU/Od7qP97vzD1G0ejpCIiJrKyPW5t2ADbGFGTrDQ45myiHto1k7V4RCRl5oabJ+P/O0fjyqN5c7JoTKW+MzCWvebuy0Bj8zZiR8OpXowOiIiag5Grs+9BRtgCzNygs0JjZeF3qhvo1WHQ0Re6ofDqfK7aODCfcrisNls6DSBg1sREVmdketzb8EG2MKMnGDa+S4/3228OYCJyDscSyuQ30V3TNqCisoqJXFcrajUPRaSVViqJA4iInIvI9fn3oINsIUZNcFsNhvunbKV0wsRkXKl5ZW4VXPlNSn7ipI4CorLdQ1wQUm5kjiIiMi9jFqfexM2wBZm1AQ7m1ukK/Qul7LQIyJ1HtNMP7QpLkNJDFmF+imZyirUXIkmIiL3Mmp97k3YAFuYURNsQ2y6LPL6zQ1XHQ4RebnXV8XI7yRVU56laP4weOuEENhsNiVxEBGRexm1PvcmbIAtzKgJph119c3vY1WHQ0RebuGORPmdNHL5YSUxxGcWyhjumhyqJAYiInI/o9bn3oQNsIUZNcGe/TxSFnrLItTOu0lEtP1klvxOeni2mmnZjpy/JGO4f9p2JTEQEZH7GbU+9yZsgC3MiAlWUVmFbu/a57qMPndJdUhE5OVS84p1z98WKhiXIDI5l3OjExF5ASPW596GDbCFGTHBtLf53T5xM0rLK1WHRERezmaz4e737CPTH07J83gMu+Kz5fkf49gIRESWZcT63NuwAbYwIybYD4dSZZE3YMFe1eEQEQEAhn5mfzRj5f5zHj//5mMX5PmfXsjvRiIiqzJife5t2ABbmBET7J11x2SRN35NnOpwiIgAAJPW27+b3ll3zOPnXxuTJs8/9LNIj5+fiIg8w4j1ubdhA2xhRkywgQv3ySJv1YHzqsMhIgIArNx/TmkD+u0B+/lf+vqAx89PRESeYcT63NuwAbYwoyXY1YpKdH5nsyzyjqcXqA6JiAgAcDglT3433f3eVo/Pw/v1vrPKp2IiIiL3M1p97o3YAFuY0RLsaGq+LPDumLQF5ZVVqkMiIgIAFJaW60aCTs0r9uj5P92VJM89evURj56biIg8x2j1uTdiA2xhRkuwlVEpssAbvDhCdThERDoPz94pv6O2n8zy6LnnbkuQ5/5/Px316LmJiMhzjFafeyM2wBZmtAR768ejssCbsvGE6nCIiHRGLj8sv6MW7kj06Lmnbzopzz15w3GPnpuIiDzHaPW5N2IDbGFGS7An5u2WBd7amDTV4RAR6Wivwr7+bYxHz60dIX/m5lMePTcREXmO0epzb8QG2MKMlGBFVytw6wT783VJ2ZdVh0REpLMpLkN+Rz02N9yj5x73g/0OmY+3n/bouYmIyHOMVJ97K9M3wNHR0Zg1axaGDBmCjh07QggBIRr2th5//HH5urQ0xyuTRUVFWLlyJUaPHo3evXujVatWEEJgypQpTYo9ODgYffv2xY033ogbb7wRAQEBCAkJadIxtYyUYAfOXNSNsFpV5dkRVomI6pKUfUV+T906IQSl5ZUeO/fr38bIc38Wnuyx8xIRkWcZqT73VqZvgAMDA2Xzql3qKygoCEII+Pj41NoAx8bGOj1HUxrg+fPnQwiBli1b4qmnnkJgYCCuu+46CCGwaNGiRh9Xy0gJtmTvGVncPf9llOpwiIgclFdW6aZqS8j03J0qLwcdkuddFnHWY+clIiLPMlJ97q1M3wDPnj0bkydPRnBwMDIzM+Hr61vvBjgnJwft2rXDk08+CX9//1ob4OTkZIwcORJffPEFYmJiMG3atCY1wAkJCWjRogV8fX0RFWVvBk+fPo327dujZcuWSEpKatSxtYyUYKNXH+HzbURkeI9/bB+rICTugsfO+8JX++V5vzt43mPnJSIizzJSfe6tTN8A19SQBvjFF1+En58fkpOTXTbANc2aNatJDfCoUaMghMCYMWMcts2bNw9CCIwePbpRx9YyUoL1/XCXkqKSiKgh/rUyWn5XfeLBkaCHLI6Q511/JN1j5yUiIs8yUn3urby2AQ4NDYUQAtOnTwcAjzbAv//97yGEwL59+xy2paamQggBf3//Rh1byygJll9cJgs7//EhSM0rVh0SEZFTH26Nl99V/1l9xGPnfWrBXnne0OOZHjsvERF5llHqc2/mlQ1wUVEROnXqhG7duqGsrAyA5xrg/Px8+QxxUVGR0306dOgAIQQKCwsbfHwtoyTYntM5srDrMW07bDYOgEVExrTuSJr8vhqwYK/Hztvvo3B53vCEbI+dl4iIPMso9bk388oGeNy4cRBCYPfu3XKdpxrguLg4CCHQtm3bWve57777IITAsWPHGnx8LaMk2KKdibKw+/vSg6rDISKq1bG0Avl91fXdLR4bsb7PzB3yvAfOXPTIOYmIyPOMUp97M69rgGNiYtCiRQuMGDFCt95TDXBkZCSEEOjYsWOt+zz88MMQQiAyMrJex6xOpJqLr6+vIRLslRWH7fNbbktQHQ4RUa2KrlYoeWTjvqnb5Dnj0vI9ck4iIvI8NsDqeVUDXFlZiR49eqB9+/bIzc3VbWMD7D4PzrBf2Qg7maU6HCIil/6ouRrrqduRu767RZ7zdJbnpl8iIiLPYgOsnlc1wHPnzoUQAkuXLnXYxlug3SO7sFR3NSX7cqnSeIiI6vLS1wfkd9aSvWfcfj6bzcaBAomIvIQR6nNv51UNcEBAAHx8fNC3b18EBATolurX9enTBwEBAQgNDa31HBwEq/62n8ySRV2fmTuUxkJEVB9TNp6Q31sT1jbtD5H1UVpeyT8UEhF5CSPU597O6xrg6uazriUoKKjWc3AapPqbuy1BFnWvrTysNBYiovpYuf+c/N4a9nmU2893qUg/Vdzl0nK3n5OIiNQwQn3u7byqAXbFk/MAjxo1CkIIjBkzxmHbvHnzIITA6NGjG3VsLSMk2N+WHpRF3ae7kpTGQkRUH1HJF3VTt7nbhYISXQNcXlnl9nMSEZEaRqjPvR0b4F+4owHu2rUrunbtivT0dN36hIQEtGjRAr6+vti/f79cn5iYiPbt26Nly5ZISmp6s6g6wWw2G/6gGdl0b2KOsliIiOor5/JVXUOaV1Tm1vOdybkiz3X7xM1uPRcREamluj4nCzTAISEhePDBB+Xi4+MDIYRuXUhISJ3HqasBHjx4sDze7373OzmSc/W6wYMHO7ym+nbqlJQUh23VV3pbtmyJAQMGIDAwENdddx2EEFi4cGGDfw/OqE4wm82G1LxihMRdwMzNp1BQzNv6iMj4bDYb7p2yVTalh1Ly3Hq+kxmF8lx3v7fVreciIiK1VNfnZIEGOCgoqEnP81arqwGu3l7b4uyZXVcNMAAEBwfj0UcfRevWrdG6dWs8+uij2LRpUwPevWtMMCKixhmyOEI2pd8dPO/Wc0WfuyTP9cD0MLeei4iI1GJ9rp7pG2CqHROMiKhx3v7xqGxKp2866dZzRSblynM9MmenW89FRERqsT5Xjw2whTHBiIga54vdybIp/ceyg40+zqWiMkzZeAIfb0uodXCrHafs08X9z8e7G30uIiIyPtbn6rEBtjAmGBFR42ib0qZclf1wa7w8ztoY54/YbIrLkPv8ZZHj9HhERGQdrM/VYwNsYUwwIqLGScktkk1ppwkhKC2vbNRxRi4/LI8zNdj5rdQ/Rad5dN5hIiJSh/W5emyALYwJRkTUOJVVNnR5Z4tsTE9mFDbqOM9+HimP8fqqGKf7rNx/Tu7zt6WNv92aiIiMj/W5emyALYwJRkTUeE/O2yMb041HMxp1jP/5eLc8xrOfRzrdZ8neM3KfV1ccbkrIRERkcKzP1WMDbGFMMCKixnv92xjZmM7bfrpRx+j5QVidzxIv3JEo93njuyNNCZmIiAyO9bl6bIAtjAlGRNR4H29LqPP2ZVdsNv1t1F0mbYHNZnPYTztQ1v/9FNccoRMRkUGxPlePDbCFMcGIiBpvQ2y6bEz7z9/T4NcXl1XI11cvl4rKHPabGnxSbp+y8URzhE5ERAbF+lw9NsAWxgQjImq8ExkFuqu3lVWOV29dycgvcWiA4zMdB9OauO6Y3D5zy6nmCp+IiAyI9bl6bIAtjAlGRNR4JWWV6DTB3ryeu1jUoNefzCh0aIDDE7Id9hv7fazcPj+scc8aExGRObA+V48NsIUxwYiImubh2Ttlc7ozPqtBr41MznVogH84lOqw36hvo+X2L3YnN1foRERkQKzP1WMDbGFMMCKipvn70oOyOf1yT8Oa0y3HLjg0wJ/sSHTY7x/L7OdYHpnSTJETEZERsT5Xjw2whTHBiIiaZtom+wBVDR2h+buD5x0a4HfWHXPY7/kvo1xeISYiIutgfa4eG2ALY4IRETXNqgP2JvaZzyIb9NrPdyc7NMAjlx922C/w0wi5fUNsenOFTkREBsT6XD02wBbGBCMiapqDZ/Nkc9r9/W1O5/Gtzawt8Q4N8MCF+xz26z9/j9y+7URmc4ZPREQGw/pcPTbAFsYEIyJqmryiMl0Dm3vlar1fO2FtnEMD3OuDMIf9Aj7cJbfvOZ3TnOETEZHBsD5Xjw2whTHBiIia7r6p22SDuv/MxXq/7n+/iXZogG+dEIKKyirdfr1nhMnth1Lymjt8IiIyENbn6rEBtjAmGBFR0z37eaRsUL89cK7er/vrl/sdGmD/8SHILCjV7df9fXuDfSytoLnDJyIiA2F9rh4bYAtjghERNd34NfZbmd8PPlHv1z21YK/TBjg2NV+3X5dJW+S2pOzLzR0+EREZCOtz9dgAWxgTjIio6ZbsPSMb1L8tPVjv1/1x5g6nDfBWzUBXVVU23ba0S8XueAtERGQQrM/VYwNsYUwwIqKm2xWfLRvUh2btrPfr7pwcKl/3wHT7c74ro1LkPsVlFY0eZIuIiMyH9bl6bIAtjAlGRNR0qXnFuia1uKyizteUVVTpXvPiEvvzwB9ujZf7XbxyVbdf0dW6j01ERObF+lw9NsAWxgQjImq6qiob7tA8p3s8ve6BqnIu6xvbqcEn5b/f+vGo3C89v0S3X2VV/ecZJiIi82F9rh4bYAtjghERNQ/tgFbrj6TXuX9S9mW5f5dJW7AiKkX+/NLXBzT7XbHv984Wd74FIiIyANbn6rEBtjAmGBFR8xi9+ohsVOduS6hz/8MpeXL/Xh+EYeuJTPnzE/N2y/2OpxfI9fdM2erOt0BERAbA+lw9NsAWxgQjImoe88NOy0b1f7+JrnP/sJNZuoY3NjVf/nyvptGt2SgTEZG1sT5Xjw2whTHBiIiaR/DRDNmo9p+/p879f4pOk/s/+3kkLhTon/UtKasEAOxLzJXrHp2zy91vg4iIFGN9rh4bYAtjghERNY/oc/YrtfdP217n/tq5g0cuP4yKyip0mmBvgM9dLAIAbNdcKX5yXt2NNRERmRvrc/XYAFsYE4yIqHmcv2ifCqnThBCUV1a53H/utgSHUZ97fmCfC/jAmYsA9FeWBy3a5/b3QUREarE+V48NsIUxwYiImkdxWYXuFuaswlKX+7+7/rjcd/qmkwCAgQv3yXUbj2YAAH44nCrXPfdFlNvfBxERqcX6XD02wBbGBCMiaj53v7e13nMB/0czavSinYkAgJHLD8l1X+05AwBYqZkeacSyg25/D0REpBbrc/XYAFsYE4yIqPn86aNw2azuis92ue/flh6U+67cfw4A8M66Yw5Xhb/ckyzX/Wtl3aNLExGRubE+V48NsIUxwYiIms+wz6Nks/rD4VSX+w5aZL/dOfiX250/2ZEo1/17VQwAYEGYfd2b38e6/T0QEZFarM/VYwNsYUwwIqLm8/q3MbJZ/XRXkst9+364S+67NzEHAPDDIfvzvsM+//l539mh8XLdhLVxbn8PRESkFutz9dgAWxgTjIio+UzZeEI2q1M2nnC5b/f3t8l9j6X9/LxweEK2XNf3w10Ox3w/2PUxiYjI/Fifq8cG2MKYYEREzefTXUmyWX39l1uYnamssunm/D1/sRgAcOpCoVx3x6QtsNlsmLA2Tq6bHRrvqbdCRESKsD5Xjw2whTHBiIiaj+4WZhdTFuUXl+mmTCooKQcAXCqqsb64HGO+s48W/cmORE+9FSIiUoT1uXpsgC2MCUZE1Hx2xdtvYe73UXit+6XkFsn9bp0QgqoqGwDAZrOhy6QtcltC5mX8a2W0/PnLPckeeidERKQK63P12ABbGBOMiKj5HE8vkM3qPe9trXW/2NR8ud99U7fptj0yZ6fctud0Dv6unS4pKsXN74CIiFRjfa4eG2ALY4IRETWfrMJS3S3MJWWVTvfTDnb1pxpXiod+FqmbSum5L+o/tRIREZkf63P12ABbGBOMiKj5lFdW6Rrg1Lxip/ttiE2X+wR+GqHb9voq+1RKi3YmOp0vmIiIrIv1uXpsgC2MCUZE1Lx6TNsuG9boc5ec7rMiKkXuM2LZQd22qcEn5bZJ64/hiXm75c9hJ7M88RaIiEgh1ufqsQG2MCYYEVHzenLeHtmwhh7PdLrPJzsS5T5jvjui2/blnmS57ZUVh/HonF3y532JuZ54C0REpBDrc/XYAFsYE4yIqHkNX3LAPmjV/nNO99Fe5X1vw3HdNu3t0YMW7UPPD8I0V5TzPPEWiIhIIdbn6rEBtjAmGBFR83rz+1jZsH68/bTTfcb+UPs+UckX5bbeM8Jwz5St8ufj6QWeeAtERKQQ63P1TN8AR0dHY9asWRgyZAg6duwIIQSEaNjbevzxx+Xr0tLSat0vIiICAwYMQNu2bXHDDTegV69eWLFiRaPiLigowMSJE3HXXXfhuuuug6+vL+644w68+eabyM7ObtQxa2KCERE1rxmbT8mGdcLaY073eTnokNxn6b6zum1na8wRfPvEzfLn5JwrnngLRESkEOtz9UzfAAcGBsrmVbvUV1BQEIQQ8PHxcdkAr1mzBi1atICPjw8CAgIwdOhQtGnTBkIIvPXWWw2KOTc3F126dIEQAr/97W8xaNAgDBo0CL/97W8hhMAtt9yCc+ec31rXEEwwIqLm9dWeM7JhHbn8sNN9ntFMdbQ2Rv9/SnFZhW4kae2Snl/iibdAREQKsT5Xz/QN8OzZszF58mQEBwcjMzMTvr6+9W6Ac3Jy0K5dOzz55JPw9/evtQHOy8vDTTfdBCEE1q5dK9dnZWWhc+fOEEIgPDy83jGPHTsWQggMGjQIpaWlcn1paSmGDBkCIQT+/ve/1/t4tWGCERE1r/VHNM/w1pjiqNpjc8PlPjvjHUd21t72rF3yisrcHT4RESnG+lw90zfANTWkAX7xxRfh5+eH5ORklw3wnDlzIIRAYGCgw7Z169ZBCIGBAwfWO8YHHngAQgjs37/fYduRI0cghMCdd95Z7+PVhglGRNS8IpJyZcP60KydTvd5YLrrqZIe/3i30wa4uKzC3eETEZFirM/V89oGODQ0FEIITJ8+HQBcNsB9+/aFEALffPONw7aysjL4+fnBz89PdzXXlYceeqjOBviRRx6p17FcYYIRETWv01mXZcPaZdIW2Gw23XabzYbO77h+rlc7krR2qaqyOexLRETWwvpcPa9sgIuKitCpUyd069YNZWU/33LmqgG++eabIYTAyZMnnR6vZ8+eEEIgLi6uXjG+//778opybbdABwUF1etYrjDBiIia16WiMl3TWlBSrttedFX/jO/FK1cdjqEdJbp6uWPSFk+9BSIiUoj1uXpe2QCPGzcOQgjs3r1brqutAS4sLJQDaxUWFjo93uDBgyGEQHBwcL1iLCoqQr9+/eQgWIGBgQgMDMRvf/tbtGnTBnPnzq3XcerCBCMial5VVforvEnZ+iu86fklusa2vLLK4RhzQuMdGuDu72/z1FsgIiKFWJ+r53UNcExMDFq0aIERI0bo1tfWAGdkZMgGuKLC+fNZw4cPhxACq1atqnecJSUleOmllxxGr+7Xrx8OHDhQ7+MA9kSqufj6+jLBiIiaWZ+ZO2TjGpV8UbftREaB3Hb3e1udvn55ZIpDA/zgjB2eCJ2IiBRjA6yeVzXAlZWV6NGjB9q3b4/c3FzdNk82wOfPn8c999yD9u3bY+XKlcjJyUFOTg5WrFiBdu3awc/PD3v37q3XsQA2wEREnvSXRftk47rxaIZuW2Q9BskKPX7BoQEO+HCXJ0InIiLF2ACr51UN8Ny5cyGEwNKlSx22efIW6D/96U8QQmD9+vUO29auXQshBHr37l2vY7nCBCMian4vBx2SjevX+87qtm0+Zm9u//yJ8z9kHjl/yaEB7j9/jydCJyIiibM+NgAAHOlJREFUxVifq+dVDXBAQAB8fHzQt29fBAQE6Jbq1/Xp0wcBAQEIDQ2Vr2vOQbBSU1MhhICvry8qKysdtldWVqJVq1bw8fGp96jStWGCERE1v//7KU42rrO2xOu2rTpwXm57cYnjSP8AkFHjOWH/8SEIrGVOYSIishbW5+p5XQNc85nb2hbtKMyupkEqLy9v0DRIUVFREEKgXbt2te7Ttm1bCCGQmZlZ9xt2gQlGRNT8PtqaIBvXcT8c1W1bHJ4kt73+bYzT15dXVqHTBH0D/NcvnTfLRERkLazP1fOqBtgVV9MgzZkzR05bVNO6desghMDAgQPrdZ6zZ8/KJvvs2bMO25OTkyGEwA033FDrM8f1xQQjImp+2kGs/rb0oG7bzM2n5LaJ647VeowHpofpGuB/LDtY675ERGQdrM/VYwP8C1cNcF5eHm666SYIIbB27Vq5Pjs7G507d4YQAuHh4Q6v69q1K7p27Yr09HTd+u7du0MIgSeeeAIFBQVyfX5+Ph5//HEIITB8+PAGv4eamGBERM1P+5zvUwv0z/lqb4+eExpfyxGApxfu1TXAo76NdnfYRERkAKzP1TN9AxwSEoIHH3xQLj4+PhBC6NaFhITUeRxXDTAArFmzBtdccw18fHzQr18/PPvss2jTpg2EEBg3bpzT11Rf6U1JSdGtP3DgAFq3bg0hBDp06ICnn34aTz/9NNq3bw8hBDp16oSMjAynx2wIJhgRUfM7lJInG9cHpofptv1rZbTc9uWe5FqPoR1Iy398CMZ+H+vusImIyABYn6tn+gY4KCioQc/z1qauBhgAIiIi8NRTT6FNmza4/vrr0bNnTyxfvrzW/WtrgIGfb3V+9dVXcdttt8HX1xfXXXcd7rrrLkyYMAF5eXn1eet1YoIRETW/lNwi2bjeOiEElVU2ue35L6Pktu8Pna/1GBPXHdM1wK5ulyYiIutgfa6e6Rtgqh0TjIio+RVdrdA1r9mX7QMg9p+/R64PPV77QIYLwhJ1x5i2yfksA0REZC2sz9VjA2xhTDAiIve4c3KobF5PZNjHcugzc4dcv//MxVpf/93B87oG+MOttT8vTERE1sH6XD02wBbGBCMico++H+6SzWt4QrZc3+1de2Mcn1lY6+t3JWTrGuBFOxM9ETYRESnG+lw9NsAWxgQjInKPoZ9Fyub1x8OpAIDS8kpdU5tZUPvc8CczCnX7Ltl7xlOhExGRQqzP1WMDbGFMMCIi9/jfb+yjPS8OTwIAZBeW6pra0vLKWl+fV1Sm2/eb/ec8FToRESnE+lw9NsAWxgQjInKPyRuOy+Z1avDPA1idzros190xaYvL19tsNnR5Z4vc/6fo2mcgICIi62B9rh4bYAtjghERucfCHfZRnEevPgIAOHjWPj9w7xlhdRwBeHj2Trl/SNwFd4dMREQGwPpcPTbAFsYEIyJyD+0ozs9/GQUA2H4yS657Yt7uOo8x7oej8B8fgk4TQnD+YrG7QyYiIgNgfa4eG2ALY4IREbnHjlP2ZvexueEAgB8Pp8p1wz6PqvMYl4rK8NWeM4hIynVztEREZBSsz9VjA2xhTDAiIvc4mpovm917p2wFACzZe0aue2XFYcUREhGREbE+V48NsIUxwYiI3CMjv8RhxOePtibIn9/+8ajqEImIyIBYn6vHBtjCmGBERO5xtUI/52/apWJMWn9M/vxByEnVIRIRkQGxPlePDbCFMcGIiNznD1O3yYb3yPlL+PeqGPnzp7uSVIdHREQGxPpcPTbAFsYEIyJyn//5eLdseLedyMRLXx+QP3+z/5zq8IiIyIBYn6vHBtjCmGBERO7zwlf7ZcP77YFzGLhwn/x5U1yG6vCIiMiAWJ+rxwbYwphgRETu88Z3R2TDOz/sNB6Zs1P+vDcxR3V4RERkQKzP1WMDbGFMMCIi95m+6aRseN9Zdwz3Ttkqfz6WVqA6PCIiMiDW5+qxAbYwJhgRkft8sTtZNrwjlx/SjQqdmlesOjwiIjIg1ufqsQG2MCYYEZH7rI1Jkw3vnz4K1zXAhaXlqsMjIiIDYn2uHhtgC2OCERG5z97EHNnw3jrB3vzeNnEzbDab6vCIiMiAWJ+rxwbYwphgRETuE59ZqLvqW730mLZddWhERGRQrM/VYwNsYUwwIiL3uXjlqtMGuN9H4apDIyIig2J9rh4bYAtjghERuU9VlQ23Tdzs0AAPXhyhOjQiIjIo1ufqsQG2MCYYEZF79Z4R5tAA/2PZQdVhERGRQbE+V48NsIUxwYiI3OvphXsdGuAx3x1RHRYRERkU63P12ABbGBOMiMi9Riw76NAAT9l4QnVYRERkUKzP1WMDbGFMMCIi93r7x6MODfC87adVh0VERAbF+lw9NsAWxgQjInKvOaHxDg3wsoizqsMiIiKDYn2uHhtgC2OCERG517KIsw4N8LojaarDIiIig2J9rh4bYAtjghERudemuAyHBnhXfLbqsIiIyKBYn6vHBtjCmGBERO514MxFhwY45vwl1WEREZFBsT5Xjw2whTHBiIjc60zOFYcG+EzOFdVhERGRQbE+V48NsIUxwYiI3OtyablDA3zxylXVYRERkUGxPlePDbCFMcGIiNzLZrOh67tbdA1wRWWV6rCIiMigWJ+rxwbYwphgRETu98icnbL5vee9rarDISIiA2N9rh4bYAtjghERud+QxRGyAX549k7V4RARkYGxPlePDbCFMcGIiNzvtZWHZQP89MK9qsMhIiIDY32uHhtgC2OCERG536T1x2QDPHzJAdXhEBGRgbE+V48NsIUxwYiI3G/RzkTZAL/x3RHV4RARkYGxPlePDbCFMcGIiNwvPb8E90/bjjsnhyIyOVd1OEREZGCsz9VjA2xhTDAiIs8oq6jClasVqsMgIiKDY32uHhtgC2OCEREREREZB+tz9dgAWxgTjIiIiIjIOFifq8cG2MKYYERERERExsH6XD02wBbGBCMiIiIiMg7W5+qxAbYwJhgRERERkXGwPlePDbCFMcGIiIiIiIyD9bl6pm+Ao6OjMWvWLAwZMgQdO3aEEAJCNOxtPf744/J1aWlpte4XERGBAQMGoG3btrjhhhvQq1cvrFixotGx22w2BAUF4dFHH0Xbtm3h5+eHW2+9FS+88AJOnDjR6ONWY4IRERERERkH63P1TN8ABwYGyuZVu9RXUFAQhBDw8fFx2QCvWbMGLVq0gI+PDwICAjB06FC0adMGQgi89dZbDY67tLQUTz31FIQQaNeuHQYOHIhhw4bhgQceQIsWLfDNN980+Jg1McGIiIiIiIyD9bl6pm+AZ8+ejcmTJyM4OBiZmZnw9fWtdwOck5ODdu3a4cknn4S/v3+tDXBeXh5uuukmCCGwdu1auT4rKwudO3eGEALh4eENinvEiBEQQuDVV19FSUmJbtuFCxdw/vz5Bh3PGSYYEREREZFxsD5Xz/QNcE0NaYBffPFF+Pn5ITk52WUDPGfOHAghEBgY6LBt3bp1EEJg4MCB9Y7x4MGDEEKgd+/esNls9X5dQzHBiIiIiIiMg/W5el7bAIeGhkIIgenTpwOAywa4b9++EEI4vS25rKwMfn5+8PPzQ2lpab1ifOWVVyCEwMqVK+u1f2MxwYiIiIiIjIP1uXpe2QAXFRWhU6dO6NatG8rKygC4boBvvvlmCCFw8uRJp8fr2bMnhBCIi4urV4y33XYbhBBITk5GcnIypk+fjtdeew2TJk3Cvn376nWM+mCCEREREREZB+tz9byyAR43bhyEENi9e7dcV1sDXFhYKAfWKiwsdHq8wYMHQwiB4ODgOuMrLS2Vx/vqq69kvNrl+eefl415UzDBiIiIiIiMg/W5el7XAMfExKBFixYYMWKEbn1tDXBGRoZsTCsqKpwec/jw4RBCYNWqVXXGl5mZKY/XsmVLPPPMM4iPj0dBQQHWrVuHDh06QAiBt99+u+43+4vqRKq5+Pr6MsGIiIiIiAyCDbB6XtUAV1ZWokePHmjfvj1yc3N12zzVAGuPd88996Cqqkq3ffPmzRBCwM/Pr9YrzjWxASYiIiIiMj42wOp5VQM8d+5cCCGwdOlSh22eugVae7wPP/zQ6T6//vWvIYRAWFhYncdzhQlGRERERGQcrM/V86oGOCAgAD4+Pujbty8CAgJ0S/Xr+vTpg4CAAISGhsrXNfcgWG3btoUQAj/++KPT7b179673FWVXmGBERERERMbB+lw9r2uAaw44VdsSFBQkX+dqGqTy8vIGT4PUr18/CCHw5ZdfOt3euXNnCCGwcePGeh2vNkwwIiIiIiLjYH2unlc1wK64mgZpzpw5EEIgMDDQYdu6desghMDAgQPrfa758+dDCIEXXnjBYdv58+fRsmVLCCGQmprasDdRAxOMiIiIiMg4WJ+rxwb4F64a4Ly8PNx0000QQmDt2rVyfXZ2trxaGx4e7vC6rl27omvXrkhPT9etLywsRIcOHXDNNdforvIWFxfj6aefhhACf/7znxv8HmpighERERERGQfrc/VM3wCHhITgwQcflIuPjw+EELp1ISEhdR7HVQMMAGvWrME111wDHx8f9OvXD88++yzatGkDIQTGjRvn9DXVt1OnpKQ4bNu6dSuuvfZa+Pj4oE+fPhgyZAj+67/+C0IIdOrUyaFpbgwmGBERERGRcbA+V8/0DXBQUFCDnuetTV0NMABERETgqaeeQps2bXD99dejZ8+eWL58ea37u2qAAeDo0aN45pln0KFDB1x77bW47bbbMHbsWIcpmhqLCUZEREREZBysz9UzfQNMtWvdurWcC5gLFy5cuHDhwoULFy5qF19fX7Ru3Vp1m+DV2ABb2G9+8xu0bt3aEInORpxLbQs/H1zqWvgZ4VLXws8IF1cLPx9c6lo8+Rlp3bo1fvOb36huE7waG2Byu+qEJ3KGnw+qCz8jVBd+RsgVfj6oLvyMeBc2wOR2/FIhV/j5oLrwM0J14WeEXOHng+rCz4h3YQNMbscvFXKFnw+qCz8jVBd+RsgVfj6oLvyMeBc2wOR2/FIhV/j5oLrwM0J14WeEXOHng+rCz4h3YQNMbscvFXKFnw+qCz8jVBd+RsgVfj6oLvyMeBc2wOR2/FIhV/j5oLrwM0J14WeEXOHng+rCz4h3YQNMREREREREXoENMBEREREREXkFNsBERERERETkFdgAExERERERkVdgA0xERERERERegQ0wEREREREReQU2wEREREREROQV2ACT25SUlGDy5Mno0qULfH19ccstt+Cf//wn0tPTVYdGHlBcXIz169fj5Zdfxh133AFfX19cf/316N69O6ZOnYorV67U+tqgoCD06tULN9xwA9q2bYsBAwYgMjLSg9GTChcvXsSvfvUrCCFw++23u9yXnxHvkpOTg7feegt33HEH/Pz80LZtW/To0QNvv/220/2Dg4PRt29f3HjjjbjxxhsREBCAkJAQD0dNnnLo0CEMGzYMt9xyC1q2bImbb74ZjzzyCJYtWwabzeawf2VlJebNm4d77rkHfn5+6NChA4YNG4ZTp04piJ6aKjo6GrNmzcKQIUPQsWNHCCEgRN0tTmP+H4mIiMCAAQPQtm1b3HDDDejVqxdWrFjRXG+FPIQNMLlFaWkp+vTpAyEEbrnlFjz33HPo3bs3hBD41a9+hTNnzqgOkdxsyZIl8j+hO++8E8OGDUP//v1x4403QgiBbt26ITs72+F1Y8aMgRAC1113HQIDA9G/f3+0bNkSLVq0wPr16xW8E/KUESNGwMfHp84GmJ8R7xIdHY327dtDCIG7774bzz//PAYMGAB/f3+0aNHCYf/58+dDCIGWLVviqaeeQmBgIK677joIIbBo0SIF74Dcac2aNWjRogWEELj//vvx3HPPoV+/fmjZsiWEEHjxxRd1+1dVVWHIkCEQQqBNmzYYOnQoAgIC4OPjg+uvvx4HDx5U9E6osQIDA2W9oV1cacz/I9WfNR8fHwQEBGDo0KFo06YNhBB466233PHWyE3YAJNbTJo0CUII/PGPf9Rd6fv4448hhEBAQIC64Mgjli9fjtdee83hL+oXLlxAjx49IITACy+8oNsWFhYGIQTat2+PxMREuT4qKgqtWrVCmzZtkJ+f75H4ybN27NgBIQRee+01lw0wPyPeJScnBx06dMD111+PjRs3Omyv2awkJCSgRYsW8PX1RVRUlFx/+vRptG/fHi1btkRSUpLb4ybPqKiowK9//WsIIbBq1SrdtlOnTqFdu3YQQmDXrl1yffUfZ7t06YKsrCy5fs2aNRBCoHPnzqioqPDYe6Cmmz17NiZPnozg4GBkZmbC19fXZQPcmP9H8vLycNNNN0EIgbVr18r1WVlZ6Ny5M4QQCA8Pb/b3Ru7BBpiaXVlZGW6++WYIIXDkyBGH7d27d4cQAtHR0QqiIyOIioqCEAK+vr4oKyuT6wcMGAAhBObPn+/wmjfeeANCCMydO9eToZIHlJSU4Pbbb8ddd92FxMRElw0wPyPeZdSoURBCYPHixQ3af8yYMQ7b5s2bByEERo8e3dxhkiLHjx+HEAJdu3Z1ur36O2HOnDly3Z133gkhhNOrfIMGDYIQAmvWrHFbzOR+dTXAjfl/ZM6cORBCIDAw0OE169atgxACAwcObHrw5BFsgKnZ7dq1y2UBO23aNAghMGXKFM8GRoZRXFwsb1G6cOECgJ+boOr/tNLS0hxes3fvXt49YFHjx4+Hj48P9u7di5SUlFq/P/gZ8S4lJSW48cYbccMNN6CkpKRer/n9738PIQT27dvnsC01NRVCCPj7+zdzpKRK9R/M6mqAv/76awDA2bNn5W2v5eXlDvuvXLkSQgiMGDHCnWGTm7lqgBv7/0jfvn0hhMA333zj8JqysjL4+fnBz88PpaWlzfIeyL3YAFOzq37+atiwYU63h4SEQAiBIUOGeDgyMorqv9pfe+21uHr1KgAgNjZWPiPuTFFREYQQaNu2rSdDJTeLi4tDy5Yt8fLLLwOAywaYnxHvUl2IPvLIIwCALVu2YOzYsRg1ahTmz5+PjIwM3f75+fnyD2tFRUVOj9mhQwcIIVBYWOj2+Mn9Kisrcfvtt7u8Bbpt27bIy8sDAKxfvx5CCPTq1cvp8U6cOAEhBHr06OH22Ml9XDXAjf1/pPrOxpMnTzp9Xc+ePSGEQFxcXNOCJ49gA0zNbuzYsRBCYOzYsU63Hz16VA5WQd7plVdegRACf/nLX+S6jRs31ll4VA82cfnyZU+ESW5WVVWFXr16oUOHDrh48SIA1w0wPyPe5YsvvoAQAs8884zTQW6uu+46rF69Wu4fFxdX5x9A7rvvPgghcOzYMU+8BfKAiIgImff3338/nn/+eTkIVvfu3XWPYn3yyScu/wBfUFAAIQTatWvnqfDJDVw1wI35f6SwsFB+79T2x7PBgwdDCIHg4OCmvwFyOzbA1OxeffVVCCEwadIkp9uTkpLkABTkfTZv3gwfHx9ce+21OHr0qFy/atUqCCHw8MMP1/ra6ukNal75IXNasGABhBAICgqS61w1wPyMeJdZs2bJ0Zx9fX2xePFi5OTk4Ny5c3j77bflXSSxsbEAgMjISAgh0LFjx1qP+fDDD0MIwSmzLCYuLg633Xab7g8krVq1wltvvYWCggK534wZMyCEwPDhw50ep6KiQn6uyLxcNcCN+X8kIyNDfq5qGyBt+PDhTu9EIGNiA0zNjg0w1SY+Ph5t27aFEAILFizQbWNz413Onz+P1q1bOzxnxQaYqlU3KzUHMao2bNgwCGGf5oYNsHdavXo1fH19ERAQgIMHD6KoqAiJiYlyRPn7779fPmrDBtg7sAGmurABpmbHW6DJmfT0dPj7+0MIgXHjxjls5+2t3mXgwIFo1aoV4uPjdet5CzRVq75dVQiBnJwch+1btmzRNby8Bdr7JCYm4tprr0XHjh11Uy5WGzhwIIQQ+OyzzwDwFmhvwVugqS5sgKnZcRAsqikvLw933XUXhBD45z//CZvN5rAPBzjyLkIItGnTBgEBAbrlwQcfhBACfn5+cl1mZiYAfka8zYYNGyCEwPXXX+90+6lTp3RX6zgIlvepnlVi5MiRTrdXj+r817/+FQAHwfIWHASL6sIGmJodp0EirStXrqB3795yMJvKykqn+2mnJkhPT3fYzilurKXmgEaulpSUFAD8jHib8+fPQwgBHx8feQurVkREhEOhymmQvEv1bc7O7ioC7Ff7+vfvD4DTIHmL+k6D1JD/R1xNg1ReXs5pkEyGDTA1u7KyMvmXsurBSbS6d+8OIQSio6MVREeedPXqVTz22GOyACkrK3O5f2MmpydrcXULNMDPiLf5wx/+ACEEtm3b5rCt+nnOxx57TK4bNWoUhBAYM2aMw/7z5s2DEAKjR492a8zkOe+99x6EEOjbt6/T7e+++y6EEPjXv/4l1915550QQmD9+vUO+w8aNAhCCKxZs8ZtMZP7uWqAgcb9PzJnzhwIIRAYGOjwmnXr1kEIgYEDBzY9ePIINsDkFpMmTYIQAg899JDuVrSPP/6YV2i8RGVlJYYMGQIhBB599FEUFxfX+ZqwsDAIIdC+fXskJibK9VFRUfD19UWbNm2Qn5/vzrBJsboaYH5GvEv1gDX33nsvLly4INfHxsaiXbt2EELgxx9/lOsTEhLQokUL+Pr6Yv/+/XJ9YmIi2rdvj5YtWyIpKcmj74HcJyYmRt4pUv2cb7X9+/fjhhtugBACYWFhcv2SJUvkQJzZ2dly/dq1ayGEQOfOnWsd6IjMoa4GuDH/j+Tl5eGmm26CEAJr166V67Ozs9G5c2cIIRAeHt7s74Xcgw0wuUVpaal8lu+WW27Bc889J3/+1a9+hTNnzqgOkdyseoqb6ue9R4wY4XTJzc3VvW7MmDHyub/AwEAMGDAALVu2RIsW/7+9u0dpJA4DODyTFTExRYKNvWVKBREJOI1EG5ux1kZvIZ7AxtImVlZioTmChffwDlbqu5VBWV1XQQ37Pg+kCfOHGTJk5jefv149Ys//5b0AjrCOZLOzszO+Z3xzczOqqhrv4O7t7f0x/dOZ3qmpqdjY2Iitra1oNptRFEUcHx//wBLwlZ5eiVUURfR6vdje3o7V1dVoNBpRFEXs7++/mP7h4WF8cLbb7UZd17G2thZlWUaz2Yybm5sfWhI+azQaxfLy8vhTlmUURfHiu9Fo9GLMZ7Yj5+fn0Wg0oizLqKoq6roePzDrrcvwmUwCmC9zd3cXBwcHsbCwENPT0zE/Px+7u7txe3v707PGNzg8PPzQ/Z3PDYfDWFxcjFarFZ1OJwaDgdeWJPEvARxhHcnk8fExTk5Oxr/37OxsrKysxOnp6ZtjLi8vo9/vR7vdjna7Hf1+P66urr5xrvlOFxcXsb6+Pj7L3+12o6qqODs7e3X6+/v7ODo6il6vFzMzMzE3Nxd1Xb/5gCMm23A4fHdf4/n75p+P++h25Pr6OgaDQXQ6nWi1WrG0tPTX/yImkwAGAAAgBQEMAABACgIYAACAFAQwAAAAKQhgAAAAUhDAAAAApCCAAQAASEEAAwAAkIIABgAAIAUBDAAAQAoCGAAAgBQEMAAAACkIYAAAAFIQwAAAAKQggAEAAEhBAAMAAJCCAAYAACAFAQwAAEAKAhgAAIAUBDAAAAApCGAAAABSEMAAAACkIIABAABIQQADAACQggAGAAAgBQEMAABACgIYAACAFAQwAAAAKQhgAAAAUhDAAAAApCCAAQAASEEAAwAAkIIABgAAIAUBDAAAQAoCGAAAgBQEMAAAACkIYAAAAFIQwAAAAKQggAEAAEhBAAMAAJCCAAYAACAFAQwAAEAKAhgAAIAUBDAAAAApCGAAAABSEMAAAACkIIABAABIQQADAACQggAGAAAghd9K/C36D+HyUQAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f450a34d150>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1)\n",
    "ax.plot(txs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we're happy that the shifts are all vaguely sensible (I wouldn't expect them to vary by more than a few pixels from a straight line) we can start trying to average the lines together.  Below, we average all the points together with a moving window, currently with a width of two pixels (might decrease this).  The moving window looks pretty good for now.  The spline fit looks really good, and agrees well with the moving window, which gives me confidence it's working nicely.  It would be good to have a more rigorous way of choosing the number of knots, though."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\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 * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\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'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\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 overridden (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",
       "    var width = fig.canvas.width/mpl.ratio\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 + '\" 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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { 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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\" width=\"490.6666666666667\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f44ffe9f8d0>]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.interpolate import UnivariateSpline, LSQUnivariateSpline\n",
    "\n",
    "def sorted_x_and_I(aligned_rows):\n",
    "    \"\"\"Extract all x and I coordinates from a set of rows, in ascending x order\"\"\"\n",
    "    # First, extract the x and I coordinates into separate arrays and flatten them.\n",
    "    xs, Is, txs = zip(*aligned_rows)\n",
    "    all_x = np.array(xs).flatten()\n",
    "    all_I = np.array(Is).flatten()\n",
    "\n",
    "    # Points must be sorted in ascending order in x\n",
    "    order = np.argsort(all_x)\n",
    "    sorted_x = all_x[order]\n",
    "    sorted_I = all_I[order]\n",
    "\n",
    "    # If any points are the same, spline fitting fails - so add a little noise\n",
    "    while np.any(np.diff(sorted_x) == 0):\n",
    "        i = np.argmin(np.diff(sorted_x))\n",
    "        sorted_x[i+1] += 0.0001 # 0.0001 is in units of pixels, i.e. insignificant.\n",
    "    return sorted_x, sorted_I\n",
    "\n",
    "def average_edge_spline(sorted_x, sorted_I, dx=0.1, knot_spacing=2.0, crop=10):\n",
    "    \"\"\"Average the edge, using a spline to smooth it.\n",
    "    \n",
    "    Returns an array of interpolated x coordinates and an array of correspoinding I values.\n",
    "    \"\"\"\n",
    "    xmin, xmax = np.min(sorted_x), np.max(sorted_x)\n",
    "    ks = knot_spacing\n",
    "    spline = LSQUnivariateSpline(sorted_x, sorted_I, np.arange(xmin + ks, xmax - ks, ks))\n",
    "    sx = np.arange(xmin + crop, xmax - crop, dx)\n",
    "    return sx, spline(sx)\n",
    "\n",
    "f, ax = plt.subplots(1,2, sharex=True, sharey=True)\n",
    "\n",
    "aligned_rows = extract_aligned_edge(raw_image, width=100, channel=1)\n",
    "for x, I, tx in aligned_rows:\n",
    "    # Plot the aligned rows in the background\n",
    "    ax[0].plot(x, I, color=\"gray\")\n",
    "    \n",
    "sorted_x, sorted_I = sorted_x_and_I(aligned_rows)\n",
    "spline_x, spline_I = average_edge_spline(sorted_x, sorted_I)\n",
    "ax[0].plot(spline_x, spline_I, linewidth=2, color=\"black\")\n",
    "\n",
    "def average_edge_binning(sorted_x, sorted_I, dx=0.4, crop=10):\n",
    "    \"\"\"Bin points by their x values, and average each bin.\n",
    "    \n",
    "    sorted_x, sorted_I: data, in order of ascending x (flattened)\n",
    "    dx: bin width, default=0.4.  Too small, and you get empty bins.\n",
    "    crop: use this to ignore some pixels at the start/end.\n",
    "    \n",
    "    Return: x, I_mean, I_sd\n",
    "    \"\"\"\n",
    "    xmin, xmax = np.min(sorted_x), np.max(sorted_x)\n",
    "    binned_x = np.arange(xmin + crop, xmax - crop, dx)\n",
    "    binned_I_mean = np.empty_like(binned_x)\n",
    "    binned_I_sd = np.empty_like(binned_x)\n",
    "    w = 2.0\n",
    "    for i, x in enumerate(binned_x):\n",
    "        rr = slice(np.argmax(sorted_x > x - w/2.0), \n",
    "                   np.argmax(sorted_x > x + w/2.0),)\n",
    "        binned_I_mean[i] = np.mean(sorted_I[rr])\n",
    "        binned_I_sd[i] = np.std(sorted_I[rr], ddof=1)\n",
    "    return binned_x, binned_I_mean, binned_I_sd\n",
    "\n",
    "binned_x, binned_I_mean, binned_I_sd = average_edge_binning(sorted_x, sorted_I)\n",
    "\n",
    "ax[1].fill_between(binned_x, binned_I_mean - binned_I_sd, binned_I_mean + binned_I_sd, color=\"gray\")\n",
    "ax[1].plot(binned_x, binned_I_mean, linewidth=2, color=\"black\")\n",
    "ax[1].plot(sx, spline(sx), linewidth=1, color=\"red\", linestyle=\"--\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\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 * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\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'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\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 overridden (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",
       "    var width = fig.canvas.width/mpl.ratio\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 + '\" 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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { 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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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f4502678a10>]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1,2, sharex=True, sharey=False)\n",
    "\n",
    "\n",
    "def numerical_diff(x, y, crop=0, sqrt=False):\n",
    "    \"\"\"Numerically differentiate a vector of equally spaced values, with x\n",
    "    \n",
    "    Returns the mid-points of the x coordinates, and the numerically\n",
    "    differentiated y values (scaled by the difference between x points).\n",
    "    If a \"crop\" argument is supplied, it crops either end of the data by\n",
    "    that amount (in units of x, rather than simply datapoints).\n",
    "    \"\"\"\n",
    "    crop = np.argmax(x > np.min(x) + crop)\n",
    "    if crop > 0:\n",
    "        cropped_x = x[crop:-crop]\n",
    "    mid_x = (cropped_x[1:] + cropped_x[:-1])/2.0\n",
    "\n",
    "    if sqrt:\n",
    "        diff_y = (np.diff((y - np.min(y))**0.5)/np.mean(np.diff(x)))**2\n",
    "    else:\n",
    "        diff_y = np.diff(y - np.min(y))/np.mean(np.diff(x))\n",
    "    if crop > 0:\n",
    "        diff_y = diff_y[crop:-crop]\n",
    "        \n",
    "    return mid_x, diff_y\n",
    "\n",
    "ax[0].plot(*numerical_diff(binned_x, binned_I_mean, crop=5, sqrt=False))\n",
    "ax[0].plot(*numerical_diff(spline_x, spline_I, crop=5, sqrt=False))\n",
    "ax[1].plot(*numerical_diff(binned_x, binned_I_mean, crop=5, sqrt=True))\n",
    "ax[1].plot(*numerical_diff(spline_x, spline_I, crop=5, sqrt=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\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 * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\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'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\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 overridden (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",
       "    var width = fig.canvas.width/mpl.ratio\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 + '\" 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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { 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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\" width=\"256\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f45029c0810>]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1,1)\n",
    "ax.plot(*numerical_diff(spline_x, spline_I, crop=5, sqrt=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analyse_edge_image import deduce_bayer_pattern\n",
    "\n",
    "f, (ax, ax2) = plt.subplots(1,2)\n",
    "subsampling = 10\n",
    "\n",
    "def average_edge(image, line, subsampling=10, bayer_pattern=np.array([[[True]]])):\n",
    "    \"\"\"Average along an edge, returning a subsampled marginal distribution.\n",
    "    \n",
    "    image: the edge image to average.  Should be a vertical black-white edge.\n",
    "        This should be a 3D numpy array - though the third dim may be length 1\n",
    "    line: the coefficients of a straight line describing the edge - 2 elements\n",
    "    subsampling: how many bins each pixel is divided into.\n",
    "    bayer_pattern: 3D boolean array representing the Bayer pattern.  Default\n",
    "        value will assume every pixel has valid values for every colour channel.\n",
    "        \n",
    "    Returns:\n",
    "        subsampled_edge: a 2D array with the edge function for each colour.\n",
    "        \n",
    "    ==============\n",
    "    Bayer patterns\n",
    "    ==============\n",
    "    * If bayer_pattern is None, we assume the camera has true RGB pixels.\n",
    "    * If bayer_pattern is a scalar, it should be the side length of the unit\n",
    "    cell of the Bayer pattern.  \n",
    "    \"\"\"\n",
    "    xs = np.arange(image.shape[0]) # for convenience, X values of the image\n",
    "    \n",
    "    # We need to make the average wider than one line to allow shifting\n",
    "    margin = subsampling * int(xs.shape[0]*np.abs(line[0]))//2 + 4*subsampling\n",
    "    # To take the average, we need the sum and the number of terms:\n",
    "    total_intensity = np.zeros((image.shape[1]*subsampling + 2*margin, image.shape[2]))\n",
    "    total_n = np.zeros_like(total_intensity)\n",
    "    bw, bh, n_channels = bayer_pattern.shape\n",
    "    # Repeat the bayer pattern to make up a whole column (NB it's >1 row wide)\n",
    "    bayer_col = np.tile(bayer_pattern, (1,image.shape[1]//bayer_pattern.shape[1]+1,1))\n",
    "    bayer_col = bayer_col[:, :image.shape[1], :] # In case the image is not an integer number of cells\n",
    "    \n",
    "    # Calculate the shift for each line in the image\n",
    "    y_shifts = -(xs - xs.shape[0]/2)*line[0] # Use the fitted line\n",
    "    dys = np.round(y_shifts*subsampling).astype(int)\n",
    "    for x, dy in zip(xs, dys):\n",
    "        #y_shift = float(dy)/subsampling\n",
    "        #ax.plot(np.arange(image.shape[1]/2)*2 + y_shift, image[x,(x % 2)::2,1])\n",
    "        rr = slice(margin+dy, -margin+dy) # this aligns our row with the others\n",
    "        total_intensity[rr,:] += np.repeat(image[x,:,:], subsampling, axis=0)\n",
    "        total_n[rr] += np.repeat(bayer_col[x % bw, :, :], subsampling, axis=0)\n",
    "    return total_intensity[margin:-margin, :] / total_n[margin:-margin, :]\n",
    "\n",
    "bayer_pattern = deduce_bayer_pattern(raw_image, 2)\n",
    "edge = average_edge(raw_image, line, bayer_pattern=bayer_pattern)\n",
    "for i, col in enumerate(['r','g','b']):\n",
    "    ys = np.arange(len(edge))/float(subsampling)\n",
    "    ax.plot(ys, edge[:,i], linewidth=2, color=col)\n",
    "    #ax2.plot(ys, scipy.ndimage.filters.gaussian_filter(edge[:,i], 0.5, order=1), linewidth=1, alpha=0.5, color=col)\n",
    "for i, col in enumerate(['r','g','b']):\n",
    "    ax2.plot(ys, scipy.ndimage.filters.gaussian_filter(edge[:,i], 10, order=1), linewidth=2, color=col)\n",
    "    #ax2.plot(ys, scipy.ndimage.filters.median_filter(\n",
    "    #                 scipy.ndimage.filters.gaussian_filter(edge[:,i], 0.5, order=1), (10)\n",
    "    #        ), linewidth=2, color=col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ss=10\n",
    "f, axes = plt.subplots(1,ss)\n",
    "for i, ax in enumerate(axes):\n",
    "    edge = average_edge(raw_image[i:,:,:], line, bayer_pattern=bayer_pattern, subsampling=ss)\n",
    "    for i, col in enumerate(['r','g','b']):\n",
    "        ys = np.arange(len(edge))/float(ss)\n",
    "        ax.plot(ys, edge[:,i], linewidth=2, color=col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# This is an older version of average_edge that produced a pleasing plot...\n",
    "\n",
    "f, (ax, ax2) = plt.subplots(1,2)\n",
    "subsampling = 10\n",
    "\n",
    "# We need to make the average wider than one line to allow shifting\n",
    "margin = subsampling * int(xs.shape[0]*np.abs(line[0]))//2 + 4*subsampling\n",
    "total_intensity = np.zeros(image.shape[1]*subsampling + 2*margin)\n",
    "total_n = np.zeros_like(total_intensity)\n",
    "y_shifts = -(xs - xs.shape[0]/2)*line[0] # Use the fitted line\n",
    "#y_shifts += (xs % 2) # Compensate for diamond pattern\n",
    "dys = np.round(y_shifts*subsampling).astype(int)\n",
    "for x, dy in zip(xs, dys):\n",
    "    y_shift = float(dy)/subsampling\n",
    "    ax.plot(np.arange(image.shape[1]/2)*2 + y_shift, image[x,(x % 2)::2,1])\n",
    "    for i in range(subsampling):\n",
    "        rr = slice(margin+dy+i, -margin+dy+i, subsampling*2)\n",
    "        total_intensity[rr] += image[x,(x%2)::2,1]\n",
    "        total_n[rr] += 1\n",
    "average_edge = total_intensity[margin:-margin] / total_n[margin:-margin]\n",
    "ax.plot(np.arange(len(average_edge))/float(subsampling), average_edge, linewidth=2, color=\"black\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bp = np.zeros((2,2,3), dtype=np.bool)\n",
    "bp[0,0,1]=True\n",
    "bp[1,1,1]=True\n",
    "bp[1,0,0]=True\n",
    "bp[0,1,2]=True\n",
    "\n",
    "np.repeat(np.tile(bp[0,:,:], (3,1)), 4, axis=0)\n"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "py2-nplab",
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   "codemirror_mode": {
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   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
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