workbook 2 - flat.ipynb

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    "# Task #2: find the Master Flat!\n",
    "\n",
    "What is the flat? In spectroscopy, the flat is a frame obtained pointing at a screen that is uniformely illuminated by a lamp. The values of its pixels are proportional to their sensitivity. The sky twilight is not used in spectroscopy because sunlight has features in its spectrum.\n",
    "\n",
    "Why do we need to divide by the flat? Because the detector has pixel-to-pixel sensitivity inhomegeneities.\n",
    "\n",
    "How? All bias-subtracted frames must be divided pixel-by-pixel by the Master Flat. This is obtained combining all the flat frames into a single frame using one of the methods used for computing the Master Bias (mean or median)."
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    "# Importing all needed packages\n",
    "# Standard packages for data visualization\n",
    "import numpy as np\n",
    "import scipy as sp \n",
    "import matplotlib.pyplot as plt   \n",
    "%matplotlib notebook\n",
    "\n",
    "# Packages for reading astronomical data stored in fits files and accessing file paths\n",
    "from astropy.io import fits  # to read fits files with python\n",
    "import glob  # to find pathnames\n",
    "\n",
    "# Packages for importing ad-hoc modules \n",
    "import importlib\n",
    "import sys\n",
    "#importlib.reload(sys.modules['data_reduction']) # uncomment when you edit the module data_reduction.py\n",
    "from data_reduction import *\n",
    "\n",
    "# Other\n",
    "import datetime\n",
    "import timeit\n",
    "from regions import PixCoord\n",
    "from regions import RectanglePixelRegion"
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    "For start, let's save into a list the paths of all the fits files that have been bias-subtracted in our data directory and let's display them below."
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       "['/home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130145_b.fits',\n",
       " '/home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130148_b.fits',\n",
       " '/home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130147_b.fits',\n",
       " '/home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130155_b.fits',\n",
       " '/home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130144_b.fits',\n",
       " '/home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130146_b.fits',\n",
       " '/home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130149_b.fits',\n",
       " '/home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130132_b.fits']"
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   "source": [
    "# Directory of the data \n",
    "path2data = '/home/masi1109/Documents/PhD/ObsII/not2mattia'\n",
    "# List of filenames that have been bias-corrected\n",
    "fnames = glob.glob(path2data+'/*_b.fits', recursive=True)   \n",
    "fnames"
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    "# Flat checks: lamp, high counts and history\n",
    "\n",
    "In the cell below we access each bias-subtracted frame, read some basic information within the header and compute some pixel statistics. For each flat frame we print:\n",
    "\n",
    "-> path name\n",
    "\n",
    "-> lamp used\n",
    "\n",
    "-> fame dimension in pixel\n",
    " \n",
    "-> total number of pixels\n",
    "\n",
    "-> chosen region of interest within the frame\n",
    "\n",
    "-> mean, median, standard deviation value of pixels values within the chosen region\n",
    "\n",
    "-> percentage of pixels with values higher than a certain threshold\n",
    "\n",
    "-> information on the history of the file: has this file been bias-subtracted?"
   ]
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      "/home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130148_b.fits  lamp = Halogen 2 Flat AT2017dtj  frame = 2148 x 2102 nPixels = 4515096\n",
      "Coordinates of the reigon of interest (xmin, xmax, ymin, ymax) = 300 1800 0 1500\n",
      "Image statistics: mean = 112355.98945857912  median = 112355.98945857912  std = 65133.6429082305\n",
      "In the region of interest 54.54 % of the pixels have a value higher than 100000\n",
      "HISTORY:  Master Bias subtracted on 2021-02-19 17:32:48 using master bias file /ho\n",
      "me/masi1109/Documents/PhD/ObsII/not2mattia/master_bias_mean.fits\n",
      "\n",
      "/home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130147_b.fits  lamp = Halogen 1 Flat AT2017dtj  frame = 2148 x 2102 nPixels = 4515096\n",
      "Coordinates of the reigon of interest (xmin, xmax, ymin, ymax) = 300 1800 0 1500\n",
      "Image statistics: mean = 113450.77512480134  median = 113450.77512480134  std = 65552.00103641904\n",
      "In the region of interest 55.05 % of the pixels have a value higher than 100000\n",
      "HISTORY:  Master Bias subtracted on 2021-02-19 17:32:47 using master bias file /ho\n",
      "me/masi1109/Documents/PhD/ObsII/not2mattia/master_bias_mean.fits\n",
      "\n",
      "/home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130149_b.fits  lamp = Halogen 3 Flat AT2017dtj  frame = 2148 x 2102 nPixels = 4515096\n",
      "Coordinates of the reigon of interest (xmin, xmax, ymin, ymax) = 300 1800 0 1500\n",
      "Image statistics: mean = 111027.97094835687  median = 111027.97094835687  std = 64504.600947380866\n",
      "In the region of interest 53.95 % of the pixels have a value higher than 100000\n",
      "HISTORY:  Master Bias subtracted on 2021-02-19 17:32:47 using master bias file /ho\n",
      "me/masi1109/Documents/PhD/ObsII/not2mattia/master_bias_mean.fits\n",
      "\n"
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    "# Doing the necessary checks on the flat frames and printing them out\n",
    "\n",
    "COUNTS_THRESHOLD = 100000\n",
    "FLAT_PX_PERC_MIN = 50\n",
    "\n",
    "# Lists of flats: filenames, frames, masks\n",
    "flat_names = []\n",
    "flat_frames = []\n",
    "flat_masks = []\n",
    "\n",
    "# Choose region of interest, where you compute statistics and model the flat later in the workbook\n",
    "xmin, xmax, ymin, ymax = 300, 1800, 0, 1500\n",
    "        \n",
    "for file in fnames:\n",
    "    hdul = fits.open(file)  # reading the fits file (headers and pixel values)\n",
    "    \n",
    "    # An HDU (Header Data Unit) is the highest level component of the FITS file structure, \n",
    "    # consisting of a header and (typically) a data array or table.\n",
    "    \n",
    "    if hdul[0].header['IMAGETYP'] == 'FLAT,LAMP':\n",
    "        flat_names.append(file)  # add to the list of flat names\n",
    "        lamp_type = hdul[0].header['OBJECT']  # to check if Halogen lamp is on\n",
    "        xdim = hdul[1].header['NAXIS1']  # lenght of x axis\n",
    "        ydim = hdul[1].header['NAXIS2']  # lenght of y axis\n",
    "        n_pixels = xdim * ydim  # number of pixels\n",
    "        \n",
    "        flat_frames.append(hdul[1].data)  #add to the list of flat frames\n",
    "        \n",
    "        # Computing statistics of the pixel values within a window exluding 10% on each side of both axis\n",
    "        stats = ImageStats(\"flat_frame_statistics\") # define the object where saving the statistics, name is optional\n",
    "        stats.compute_imstats(hdul[1].data, xmin, xmax, ymin, ymax)\n",
    "        flat_mean = stats.mean\n",
    "        flat_median = stats.median\n",
    "        flat_std = stats.std\n",
    "        \n",
    "        # Counting percentage of pixels with higher values than COUNTS_THRESHOLD in the area of interest\n",
    "        flat_mask_high = stats.counts_of_interest(hdul[1].data, xmin, xmax, ymin, ymax, COUNTS_THRESHOLD)\n",
    "        flat_masks.append(flat_mask_high)\n",
    "        flat_pixel_percentage = stats.px_perc\n",
    "        \n",
    "        # Checking that the master bias has been subtracted\n",
    "        bias_check = hdul[0].header['HISTORY'] # will be printed below, check for each frame! \n",
    "        \n",
    "        print(file, \" lamp =\", lamp_type, \" frame =\", xdim, \"x\", ydim, \"nPixels =\", n_pixels)\n",
    "        print(\"Coordinates of the reigon of interest (xmin, xmax, ymin, ymax) =\", xmin, xmax, ymin, ymax)\n",
    "        print(\"Image statistics: mean =\", flat_mean, \" median =\", flat_median, \" std =\", flat_std)\n",
    "        print(\"In the region of interest\",  \"{:.2f}\".format(flat_pixel_percentage), \n",
    "              \"% of the pixels have a value higher than\", COUNTS_THRESHOLD)\n",
    "        print(\"HISTORY: \", bias_check)\n",
    "        \n",
    "        if flat_pixel_percentage < FLAT_PX_PERC_MIN: \n",
    "            print(\"\\nWARNING: the percentage of pixles with a value lower than\", COUNTS_THRESHOLD, \n",
    "                  \"is lower than \", FLAT_PX_PERC_MIN, \"%\\n\"\n",
    "                  \"Please choose a more representative area of interest.\")\n",
    "            \n",
    "        print(\"\")\n",
    "    hdul.close()\n",
    "\n",
    "flat_array = np.array(flat_frames)\n",
    "flat_masks_array = np.array(flat_masks)"
   ]
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    "# Plot of a flat frame and the region of interest\n",
    "\n",
    "Below we want to plot the rectangle defining the region of interest in a flat frame, as well as to mark the region defined by those pixels whose value is higher than the chosen threshold."
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       "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\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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       "<img 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peDPEzpuAIgpKPIAmAWQXmevThg2Fd5tFNrl32vbIxHyzYLAhgCYBX+W858Dfv0OB1sVwQGAIaIAwJBLjR3AfoZ/OfS14QLWAD8pPFwLAg0nUDqxSrlWWTmBXtenCQxqMNIG5GRAoAewNLBL5el5P4/2uo1BL3WbC3nSb0Vw+7JDvfy3nZn3lw19krNfFwB74AaGAxhqSwGAIZdqA2A/XT+PG1gX/hoCYHa+oHYCzCwI0QDQBYYpEPTAnnWfg6AGMU0hyAleXnj0Lq+7XfbfqDmrdUBP2++ZLnJ26Df1uzegr1bIt83wb5fDwG4QlJzAAMAQUQBgyKVaADhc4M9zpd7EBXTCoHaSkk5gWfmAGXmBrYWFUzmCTUPGHuDrgUPYN5BrAWpbgT8tJ1RzAR3h327k/WWFfPn/q5bi0QYE9jMUzHOvAwBDTAGAIZf+bAFQOvg2PcBLMKidXBx5gI2GAXpeEGwMhm2Fg7VwpORspQCIL5ee00uAzHmvOp8rB/S8MMihPhP2rHSEbuT90f+pvjqA1kVoFwAwCYLhAIYUBQCGXMoCwH6DHz/Y8vtthYBbCANrJ642IDAFgI1cQckJksKDFlS0OTRw5Mslh6wpCHqcytT7SIBrga4GtG2NBuFe/ttqK+zL/y+s/58sB7Au+GnHE+240y8XMBzAkKIAwJBLbgDsd7Vvtx1AyfHLDAV7oTA7BJyAQe/JuLETqDlHTWDOs50FQ5ZT5nXdPNt6odLzOfjfIm2fA36pfVDT8ZMc5WyXLyP3T3LQW3P8moAgv/jsIvTVhsAAwBBRAGDIpSYA2HPoSzmD2kG7qROYCYD8xNU4LNwPJ1ByBVMh4hxnsM2QsgWGHhjTQNIDnhqsWpDq/fty3T8PCEoub8PwbzLvr9chX+lCjv8vNwkD9xAA3SAYABgiCgAMuVQXAPGg1Hf4awJ8XYTAFBh2EwIlx0ZzdRpDoBUWtgCkG1DoASoL7nLDzd712uu3Gd61wvhW2NcJgdrvqhvg19rIhT3rYrJP4EcB0ATBAMAQUQBgyKWmDuArEgI5/PGQcIPwbyMAbOAGNgbAFPSlHrfhYNUFvzrruvXe3czp48uawDxz/NzwZ+UAOl2/xs4fB78mjp8WWfAci7oAgZEDGPIoADDkUhMHcNiMbsFfi+5fKy5gw3Cw5eo0dgG1dRoMarDXTRewLij2GhybwmBLcM9/O92APunCqFH4ty7spZzAYTAiBBzyKgAw5FIdAOz3gTAbApvCoeQmNHQBe5kP6HEGa7t/XofQ42D1C/6GKyxa34fmttZw+jwgmAWBKRe7TdfPCve2BYTDDAYDAEMpBQCGXMoFwH4f/Ezwo8vagD2PI1gDBhu7gBkhYesE3pZTlAWKdaBPcxBzgXG4OHdNP4f0d3fJ8avl/GU4gdL/RCsOYDfBbxiAYABgyFIAYMilHAD0Hpj6AoGa0+ddlguI3F2oAYDZjmADp0+CQc3lodt3DQY198oLgNL2fy4OohfwNOi1wLqhy2f9NtoGQAv2XAAo/d91y/kbRg5gAGAopQDAkEt/9g4ghUB+vxsngBQQth0a5ifWmjCYOqlLTlDX3UAJYiTYsVwvCwY90FgHIK3P3QT6Uq8lfZctgB+/73GT64Z8Ww39cqdPuiDLAbthDn0BgCGvAgBDLnkBkB506EGI3g6LIR3Q24JBLceoAfjVDgXzE3BmGNjr/HQNBC0XKwU1KXCyYEqDt9T2dUAx53Vy4NPzHdWAwOyQr+b+ZfyOWwn3Shdjr0DXjwNgCQQDAENEAYAhl3IA0At7wyIMzG+75fw1gMHauX9O8PM6ORIEaMs8TlJjILQcQAuULPDLhbO6wCitk/4u7e9MOX4twrd0IVALBOvmsTYBP8n560bYlx5f5rJlwwACAwBDkgIAQy7lAmDlwOMIDfd0rmANCDUobAqIqZykbjmBDUEwBXnSNl0ZGtRYsGNBmgWCKYizXtsDnBbopT6v9vyWh7Zfc0LBqvPngEHpN97Y+evGSB1HhsEIAAxpCgAMuVQHAPsCd3VgsFtDOgE1CANnQV9LEKid6OuARFdHbtgztb3lukmP60KhBa6px5r72AD26DLNCZYuDpLwVzP867kYSrp+kgvYJgBay/sMfhUIDAAMEQUAhlxqCoDDBgIlh4/fdgsCpRNTL0LCFhA6TvLaiZ8DgASLXQW9Os+zwsYa9Fkgl4IwT4hX29b7N7fgBkr7UNufORcOTULAjUK+3YI+6RihHWOGAfxFEUjIUgBgyKU2AHDYwKB28M65wm8Khb0AQCn01sVhOUoe16nnwwIzDa5SYVptWSqEm3IXU2Db0tBC/R5oTIZ/MxxA6vIN6xCw5PjxY8swcQIDAENcAYAhl9ruA9h3CJSgkIOgdFBvyxHUQlVGuCuVI2WG21oCPCs87AGFYTesnD4PqHEIy8nZqxsSzv3bnECn7S+PU5wdBu6FA9gNCNQuJvmxot/HMwS+cABDhgIAQy69IvoAaq6fdtCWrujbdP60E5UDBrPcwIagZ62XINByBXMcppRL1RUQTIFZajvrOZ4wcw4Yap+rxncp7VcNDLV9nwWDDuev0eD/S5ew5dJjr8unOXwaJHYB7FLLeAi4uB8AGCIKAAy5VDcErPUAHDaQaB3Iuz0kCOxW/l8LYd0cUNTcpK4BnAeKPE6bBm2WyycBnQV6Fkh6P3MN4JOAPLXes3+TAFiz+MMNgpbj160wsHT86MOwjqNiHmAAYIgoADDkUm4I2AK/YQN/KSj0uAB1gE9yJhzgVwsGUyfjmlBYxyG0gGNYDSsUnHLmPM6hBJFeoHNu34bDWsfpK23Df1+Zod9aTmA3oY+DHz0eWMeQPsCgdBwOAAxxBQCGXGrqAHIAHPZg2AtnsGGYS80FbBICTmyfA3/Weo8j1VPY6/Z7eABOqyjOdTIzQU+7r+1PDwiaTqCVx1o3/6/brl8fwa4O/KkjADBEFAAYcqntKuBhP7rlIGh5ShlAWCsMzN2/LgzuGmlA4QG+vrmGuXBlhWhbdvXaAEBp3/D9UgfszYuJGmHfRvmA3YJBDfyGERSa8BcAGGIKAAy51GQuYH5w4lesfQO8fkCgFAZuEA7OdgFbhEDLHUrBRArm6oBe31zEOhDnAbtUcUkuaCa+OwnivU5uUxhsBfq6GfpNOYLDYKi9/6IIJKQoADDkUpO5gFPg13cY1MCQ328bAhu4gLVzALvo+mmQZz3Ogbe2tmkFznK2SeUMtv05Mr4jL9S5Qc8CwMwcwFqOXzfcvhTwWdv3CQTDAQx5FAAYcinXAbQg0Lp6HdZDOznw+14I5NCXCYBJCOTuS4+GBhcWoOUuH/GjpbYv2n5qDHw1ATAb/rT/o264fcNoSG1eXBAYABgiCgAMuVQnBCxVpWmwlwuAPQXGupCX6wgmAFAKlWU5gF0M/XpgUIIRyX3yOFV/9qDY7cKTBACmwLArFwcZOYC1QsHd+N/0unvDABS1QpDS4wDAEFEAYMilOkUgEgQOu2rfHAC0HMCmAFjD+XM5gF0OB3tggUNcXUjpFfh1FSZ70Nw553kpR7BXzl/r4d8mQMgv+oYp8FkgGA5gyKMAwJBLdULAyavR4QqCVvinG86fFspqmv9ngV9DIPSCQg78aW6g9jq5oNYPl7BfzqT0vpbDqu2nRo6g5EC3BYH8/6cN8LOAUAK/YQyBKgwGAIaIAgD7rHvvvRemT58Oe+65J3Q6HbjzzjtL6zudjjgWLVpUbDNhwoTK+vPPP7/0Ops2bYLp06fD6NGjYY899oDZs2fD888/7/6cdRpBa6HgYQF/qYN3KvTTJ+evFgD2OAdQAkAJIviypiDVL9hq8/17/TdY+6G2K6iBXwICa7t/3Qz/SseBYQJ+WtN9qxo4ADBEFQDYZ61ZswYuvPBCWL16tQiATz/9dGncdNNN8KpXvQp+9atfFdtMmDABLrvsstJ2zz77bLH+xRdfhEmTJsGRRx4JAwMDsHbtWhg3bhzMmjXL/Tlz5wLWDkbWAYtvNywGP+B3yxVsG/56AHZtwaAFghKEpGCpKUS1CWH9htLUZ6oNeV4QVOBP+h3XuhhqAwCl/2G+rN/HIQX+UsfMyAEMWQoAHEaSAJBrxowZcNRRR5WWTZgwAa6++mr1OWvWrIGddtoJtmzZUixbsWIF7LLLLu5/9DamgtMq14YV8HHQ08JB2vq2IDABhdnOX49cQA5qqXVtQpL0Xho8Wi6YB+K8n7mXAOiBY+l7T+2bFPSLy6XfXtv5f910/qSLv2E+rAvqAMCQpADAYaQUAP7nf/4nvPrVr4bbbruttHzChAnwhje8AcaOHQsHH3wwXHHFFaXw7sUXXwyTJ08uPeeZZ56BTqcDd911l/heO3bsgO3btxdj8+bNjR1ADfiGJQBaYDgM4E8tBNFOtF0AvRTgWa5SDqh4YSoFNjlQVBfuegF8+1++pCj0qPN+1vfTyuDwlypOaqP4o1tAqF0Y9hnyPOsjBBxKKQBwGCkFgAsXLoTXvva18Nxzz5WWL126FO655x549NFHYfny5fC6170OPvrRjxbrzzjjDJgyZUrl9XbeeWe4/fbbxfeaO3eumHtYBwBTwDdsAfASdsuhTwLDHODrhQPY5epfCSAk4JAAywNQGtRJsOmBOQtAU5DYFZBrGR69oNt1GMzNUb1saeUCp6cOoPS/Lf3/p44VfR5WC64AwBBXAOAwUgoADzzwQFfe3h133AGdTgd+//vfA8DLADh16tTKdqNGjYIVK1aIr9HEAdQORnXz+/oCiNoBPQWFuQ5hZu6f5Qaa4NdS1W8KEvj6XPBIAZzH1WoCdXXeezgMz+dNwbL0vXn3swh/DhBslPfX7RCwFwL7AH9aDqBZABIAGGIKABxGsgDwvvvug06nA4888kjydX77299Cp9OBBx98EADqhYC5cotApIOQBnTDNh9QcwNyAC/HEWyrAISffNtydRSok9alYCzlxHlcqxyHK/UeuTD15zJSf0tq/9R2/2o4gX2HQOsCr9/HornVY2ky3CtdgAcAhogCAIeRLACcOXMmHHLIIa7X+d73vgedTgc2bdoEAENFIFu3bi22WblyZdeKQJIHIQEApYPasBuaQ9AG/Dkh0Mz/awEELVDTgM/jDLUFdJ71luuXhLs2Z+jo02wfTaCwzsVAW05gdujXygds6vjxxx4nsM9wyO+LF+MBgCGiAMA+69lnn4UNGzbAhg0boNPpwNKlS2HDhg0FvAG8DF+jR4+G6667rvL89evXF8956qmnYNWqVTBu3Dg4/vjji22wDczRRx8NAwMDsG7dOhg/fnzX28BYEKjBXl9hMHVwTzkHPQLBbub/aUAnneg1cNC25bd1wC61TPt8bgAcwSML7nLdQCf8uSGwLug1cQKHAdxZx8XURXcAYIgrALDPuvvuu8Vii5kzZxbb3HDDDbDbbrvBtm3bKs9/+OGH4dBDD4UxY8bArrvuCgceeCDMnTsX/vjHP5a227RpE0ybNg122203GDt2LMyaNQt27Njh/pxtAmDdA1zPoZC7A/zE0Bb0ZYR+s9w/evLNhEAL/DSg057vcZ3qrMt5DQsKs8a8Jc2dPf78YeIUeqC/NgS27QB2A/5yLwiHCRR6Lq4DAEOSAgBDLjUBQO8Var8Pqllg2CYEchBkj3mFZNsOoHTy19alYMELZm05cW0AYmsgl/Oc1HNbhEIviEvra4GgVIDkDAUnIfCSpTIA1gVCfrE3jJw/C/qs9WYhSABgiCgAMORSmzmAHuj7swDCJiFgHsZquwgkAX/ek7rXJWoLOHKhJgc6a4GdBWzzhPXcIRxG7l7d53XL/avl+lkh4BwI1KBPcwO7DIVeuJOWp46tAYAhTQGAIZfqzgUsHcA8cNcXAPQc4LWTRh0IdIJfVsg3w/3TgC7lBjWCihpA1BX3LvWZUhCXAkPP63bp+2r6vXKAlx63CYG1QVBzA+s6gSkAHAbDOqZGDmAoVwGAIZfqOoDSlalWpdZX+POCYJthXycEZinFSWkAACAASURBVAOgFopTnDvJses2dDV9/VZgVAMuC/68OYBeF3GYDu23kR0Sln6TdUK/3YQ/Kez7ZwKB/DhqrQ8ADHEFAIZcqusAWrAnHbRyikV6AoBN3L2GAKidFF3gl+kC9hs4ug5IWuFFkzy+nM/dw5y/bo7GDqAAgbzIqRUIzAVD7X99GACfdeyTjpemGxgAGCIKAAy5VMcB1A5GGvClKtn6AoP0hNAtIHTk/CXBr0b4VzvB9xTYegU+OcDn3SblDradC+h8jaZ5ldbrWM5g3TCw9PvOgsBuDO2CcJiNnCK7cABDXAGAIZeaVgFbV6V8vXZl23Pw4wDIQbAu7CWgL7vgw+n68RN2T8CrKeh4IaqbFbnaZ9Gel/NZMj93zwGdvbcEicmwsLPyt7YL2Gb4l9/yC8BhNnIvqAMAQ1QBgCGXmlYBpyBPCmP09eAqHfA5/DUBQafz1zYE9gT8hmu4sy6YpcBTqgZOvXcOzHpAtQffqQZ/bRSD1CoC4aHgbrqAw2RoF8XSxTQ/5gYAhrgCAEMueQFQPOgYbp/l+GnLegaJ3AWQILBLAJgNgUbhR6s5fzkw4nHJ2nDRegU9FsS1Db25sNqj7ysFgdKy0u/S6Qb21AW0Lu7mCsuHAfhZBXbaBXYAYIgrADDkUlszgXgcQM/9rgKfdALg0Cct88Bh2yHgTBemNtxpVa1Wtau0XoOVYdo/zwV6fQgFD4chAV8FAKXfaFuh4G47f310BHOOdSkYDAcwpCkAMORS2yFgyRVseiDsOhRakJcLfgYEZoV4nQUfLtfP09NunjCs9dpz2mic3EYFb9PxZwhubQNgBfoahoJrh4O7Hf7VLgx7DINJly8AMORUAGDIpTYAMHXA0g5+XYPA1IG8bWfhUna/DQDMcPvcoV8N1qxtOMxp0NdWT7yM57udz9z3r1M8knrPPuf5NYFA+rhNEHS7gd1wAKWLv9zjSMsw6MmbVi++AwBDRAGAIZeaNoKWDlyaC9jTvD9+kO8mACbgz13okQF/KvxYgNZ0XCHcStCkbHvgxUtbBcDWhvW31YG9JjAofZ+5300Xv0MX/LVdGGJdcHnBzwODPYY+CwS9x9gAwJCkAMCQS00AUDtwSQcrCwy7An4S/PUI+Dj8me5fRo5fluPVTQCsG/L1gEldeOlWiLkpiNXd1nrscVvrQqbxfFdRCHcBDRh0uYBN4S8FhNZFYo/BzzqeWuk3B8wNAAyVFQAYcqmtIhDroKXBX8/zALvl+jVx/2qGfdUTtgRn84Xl3YRCa1kOCDVx4jSnsk1IrANg2t+W+7ju35naF46/OwmADhfQHQLWgLDN8HCfoE8DQC16EjmAIa8CAEMu1WkD471CTeUKtg53/H43gC/h/vGTWtPq3kb5fdpoCIT7X7ZUdv4slzAHBHNdwLpOWC7keR09DUhzQdXznVnfs7Te+9mNbdsKA/NwsBsI24K+FBD2wfnT1icvvgMAQ0QBgCGX2soBtApC+HKrMKRVIOy242fAYNP2LtRpcZ+wc8EvFwRzQVN6Xl34qgkryXUSGEmPNRjTlml/e13wtva19h7W32yBaSaA96wgpNsuIAfDPrh+qeOlevwNAAwRBQCGXGp7KjhrWdeBr5sOID/Z9CDnLwkuueA3X7hPl9WByDqAaMGbtW0K8CzItD6jB448f6MGadrflvr+LLDM+du099Ken4LIK6oFSWpYONMN7KkLqLmB2vGkDy5ghIBDdRQAGHKpW30AtfXSAW/YOn/8hCPdCuErFQLbCvN6gEKCPQkGpeX8NXIhsRdDcuC07yYFlxZMae+TgrHU9jkAmPu8pt+r9h0kHEATADMKQ7KcQMmRbwMIezC84V/JIQwADFkKAAy51OZMIBrsaWFfyx1s5AL2yO1Lhn4zwrtm6NcLfRoA8uUaAHruc0iUXrtbwOcFljqQlHLCXmmjLswmQFCEwJq5gtkg2A1nkB9XWnYFteNiEvgCAEOGAgBDLnW7Clg7qA076LMcwAwI9IR+OfBluX/asJw7a2jAZ20vPacXEOiFlBzwS32fTf6ebgFkr8FUgj/2WAoJm8DnqBLOzgls4gRqx5IeOIBZTl8AYMihAMCQS20AoHSgkg5s0sGtlgMoHbCbQqBU1OEAv9xwLz9BuqEvBYIegHPC4b5X+rZLuowpKMyBKwv2/tydOs932Mv31r5/LRXBkR9Y1/1z9QmUoK+JG2gdY7oIf9pxVLuALi0LAAwRBQCGXGobAC0n0AOHSfCTDtRtgR8HQKfbl1v0kYQ+r/OXA2kC5OFIwR8uk7ZXIbPbQNJL8JMczjbyItsAv5Sby7eTHtf9W5zudd0KYRcA9qJIpItuoOT+aUCoQWI4gCGuAMCQS23mAKYgUAsBN3IA23T8ao7cat9G+X01Q70c+DjUaeu013GHlC1YSUFPCkosV7BbDlrq+7cgrc7fqH1fue4s3zfW414BYI12Mdn5gG3AIHcAW4BBT/jXurCuHGMDAENEAYAhl9roA6hdqabCHW73r81QrwSBbQOgAoHZeX0px0dx6qTHGvBZw+MUijBogYW0vluwVud7leDM+nya86b9vdp3YYFaCrQ1d6/mxYIbbCUQNMCwbji4tguoQWCuS8gjEC2BYG7un7RtAGBIUgBgyKVuOIDagSsFg0kA5PBXBwZbgD7TqVCgr/Q4x2VynsCzAW9BPgxK76NBoCuP0IIoC8yk76kORFqQasGsBwBT+8z6DF7gc47snM5cAKQgaABg0g3McAHduYES/DVxAaVwcAMQtI6PqbBvaXkAYIgoADDkUp2p4DyhXuuAlXWQlA62bbl/NeHPzP/z5Pt54STjpK+5dkkIXLCkDIQ1wTALOCyolaBPg0IvRKYcvrpwlQHoyddpCfpagb068KeBIANCV6sYIx+wUX5gHfdPcwNbcgGlaIh13IwQcMijAMCQS21PBZd7AMt2/XKdvhacP+sE5HUAs5w/JwAkwY7D3AJhaMsTIMihU3rcCH5yniu9Bl9nAV8N4O7VyP0+pVC9to+y9pfmuHoA0eMEOsLArQBgN0ZLYWArHJyCxADAEFUAYMilbhWB8AOWBn/JHMC6oV4JBGtAoPeEJAGg2jrDCkU6YC8JgBbUWQCowaMDBjmA1ILBboFiF+Guzb/RyuFMba+BnxfgJfc467uVHMAm4eBMGJQu2LoGhVJEoiX3TwsLJ4+xAYAhogDAkEvdbASdvGrVnMCm0FcjzMtPGqbLlwN+nv59jpO7O5/P4+wtVJZJyzVQTISCrc+fAtyuhDFrApn1Wbzw6wEuDcI8AJdyZHOH52+vwF9NEEyGhNuqDpagrw13sOXwr+b88eNohIBDlgIAQy7VAcAU1FnbWqEP0f1r4vplOn7Zbl/dsG8GfKiwl3LvNNhLPfa4gw5X0Os0aX+rB6jq5kha8OT9fDlAlrvc856pbZoAoPZ8EwL5fXprFIe4cgIdMFgntUOMDmiQ10UATEVJUhfSB8wNAAyVFQAYcqlbVcBW6MJztdsK/NUAvmwQzC36MMAleeL2uHvUzeNjAbtduMQHglp4uGbhSF0ISTlxGjB64ezPYjjyM9Vtrf3lcHo15zPpDjrCwSoE8v+xth3BFPxZMMiPUy1BoAaF5rE1ADBEFAAYcqlXbWCsHJbWnL/MsG8t5y9xgjLdv0xnKsvlyxkcAL2uoPSZUjDREgBqjpQGf7XhSgMk/vq5fx/fXvvetP3uATfrd8O3t6BeeU/pN5uEwUwIrIBgDQDMBsFcCGzZDdSOh1kpNQGAIaIAwJBLbQNgMlTRJgRqbp8DBN2On3QS8s7wYTh/IrBYDlwu9AnbTKwDhSln0AJDCxZbgETR2Uu8psthretypoDNA8xN1tcd2ms4/m6XC0hBUCuIyq0UdsCglNvrDgnXgb+aEJi6SNYiJwGAIU0BgH3WvffeC9OnT4c999wTOp0O3HnnnaX1M2fOhE6nUxqHHnpoaZsdO3bArFmzYI899oDRo0fDcccdB5s3by5ts2nTJpg+fTqMHj0a9thjD5g9ezY8//zz7s+ZA4A5cKeFea2r3dJBtAvOX60wbwb4lSDQ6fy5TuISjAmQN5FA3kT2uJXhBUL+GTUA9IBTygHLXSc5XdZ9C46053YDxnK20/aXtu884f8aYK66gA5HsGlOYM8BsAUI1PL/XBfcAYAhogDAPmvNmjVw4YUXwurVq1UAfM973gNPP/10Mf77v/+7tM3ZZ58Nb3zjG2Ht2rUwMDAARx55JBx88MHw4osvAgDAiy++CJMmTYIjjzwSBgYGYO3atTBu3DiYNWuW+3N2AwBTB62kA1gX/hrk/nlDvBT63BW/3uIOfrLOHBMXVsFPWsZhMekOdgMONdDSoFhYLoZkLVDywJUHDtsaKYjzvo7HtU24w5X1Od9RjjPoBEH+f2ZCYLdCw7lASI9fNdw/7dZ1XA0ADBEFAA4jaQA4Y8YM9Tnbtm2DUaNGwcqVK4tlW7ZsgZ122gl++MMfAsDLkLnTTjvBli1bim1WrFgBu+yyi/sfvWkIONf5S7qBLef9cScgGeo1nL/KlG4Z1b6iI4W30gk8Eb7lkKdBoAWDEvRZz6kNhU0h0QN3uYN/jtTn8gCS5bx5vhsvqEnLrffqNswnXFgR/jLyA91uoKNSOBsEm+QAOnMDPcfR5LoAwBBRAOAwkgaAY8aMgde//vWw//77w+mnnw7/9V//Vaz/yU9+Ap1OB5555pnS8yZPngxz5swBAICLL74YJk+eXFr/zDPPQKfTgbvuukv8LDt27IDt27cXY/PmzV1pBJ0DgrUBUDlobxw3Hp7efcwrYmwVHluj2GZMeltzKM/v9/cxEkbT79n7/JG+PzeOG99+OLhG+NcKBVth4ADAkKYAwGEkCQBXrlwJ3//+92Hjxo3w3e9+Fw4++GA46KCDYMeOHQAAcNttt8HOO+9cea0pU6bAmWeeCQAAZ5xxBkyZMqWyzc477wy33367+Fnmzp1byT1sMhWcJ9ybSmau5AA2yPM74NKl8PTuYwA6nRgxYsRQx9O7j2nHBeRuXw0Q9IZ+1eNuAGCIqNPvDxAakgSAXFu3boVRo0bB6tWrAUAHwGOOOQbOOussAHgZAKdOnVrZZtSoUbBixQrxfdp0AL3wl4LC0rIWAfDFV72q7y5DExdHdeb40JbXGfx9+P0ag/9N/H4b31XutvxzaZ9R2x/S+1p/t/b3S49zvte6rm7qM0iPXynjxVe9qgDA7HYxqeKPTPjzHEc9xSABgCGqAMBhJA8AAgDst99+sGDBAgDoXgiYq402MNLByZMb6AoBX7q0CoAMBulBfP/LhgDw6d3HVPP+eGGHUelrFnrQ2Q2M/D+zyjeRgzdxEbmlY7GwTBt1t9Xu41jI7kuf25GDmJtraBWvaDmR/LbyGovsoplkjqX2PeSORew28Z2an4Nvbz3fel/lexBzHrW8QW+hSGalcNZUcuQ+PT64ALBOKNgJglIedE66TXFMDQAMEQUADiN5APD3v/897LLLLvD1r38dAIaKQFatWlVss3XrVrEIZOvWrcU2K1eu7GkRiAcMU2FflwOYUd3LD/BioUcO6EmQ1wQALaDwQhk+tob0/NyRAkbpM6dgpMYoQZwBbCnYzAIoLzRZsGV9N9Jy67217doYjr+5USGJUCQiNpLOaBljFWlZECgdH1qvCnYWgZjRkAQQlo6hAYAhogDAPuvZZ5+FDRs2wIYNG6DT6cDSpUthw4YNsGnTJnj22Wfh05/+NKxfvx5+/etfw9133w2HH344vPGNb4Q//OEPxWucffbZMH78eFi3bh0MDAzAUUcdJbaBOfroo2FgYADWrVsH48eP71obmLrDe3BTAZAfgBPVvioAJnr7JWcp0E5MxhRlKdfPBQ0pmHPC4D5XDQ1pm9Jy6z08ziJf73Sa1HUCpGSBHv9+U9+5BrA5IJUaOe6sB7wXs3WpfcUh34JWsk5yX00QdLiCbjew6ZzCigPIIVCEQikqkXL/nI5gbvQkQsAhSwGAfdbdd98NUrHFzJkz4U9/+hNMnToVXv/618OoUaNgr732gpkzZ8JvfvOb0ms899xzMGvWLBg7dizstttuMH369Mo2mzZtgmnTpsFuu+0GY8eOhVmzZhWFJB71wgG0QsCVken8Se0dSgd450wenimqvOBXgT8N+iT3SThBa8AmARwFPA34+Hrt+TnvrYJirvuUA1NeKOPPkZzUOkBmgZUGWxrMa98bX2Y9z3MxYH0e6+83HEEOghMp/HEQVNrFuGYRmcf+Fw1H0HIDUxeIrYaDW84HjBzAkEcBgCGXeuEAarl/kiOYzP9LwJ8IgDnQZzkPxtRuyendyInRC30SyEnAJm0jPae0bMlV5Vvvulw49IKSBR/SujrwZ70+/azcQUs9R4JICboScEb3k+bMSt95NqTnwrwG5jmuYB0XcL7w/2aEg739Ay0A7Eco2Bvy1Y6fAYAhrgDAkEvdBkAtvKEeAJ3un9Xw1QOA6onDA36G61fJ+/M4f+Rk6wW6Cqxp8LbkKnkbPqTl3s+ggIvpVHngw3K8KIi06dRp6yw4Sjl+mX8//z69vwG+Lb9QSDm/lX2owW4qjK+BoNZg2moc3bBApGsASNNRGjqB1kWyBnyV5QGAIaIAwJBLbQKgFcaQDnZNwr/WzB4aAGZN36a4fK5p3QQANMO9i+WTtcuV4wCnAR4fSx338fWWMiDU7htuoQdyklCUcta8YKeBpuSqWeBmPc+x3HJUcd3eV2eAuPQ7yIB4a98V3781DBCsAKE0owu7gHKHhRUg1ELByRzhFAx6cgEt509YlsqNjhBwKEcBgCGXcgEwN0fFSmhWIdAo9ki5f5UDfAoAtUpeKQRlwZ/R5kWEPwEgRLji0KYB3lLhlg5pmbROcwdzHEfFccpZ7nYJJcByhFs1+LQ+hwtSjWXq3219xznfv/e3Yjm/XoivC4PUBTTcQMlZT0Kg0wkUc4Tr5ALmuH81qoFTxSABgCFNAYAhl+o6gLlXqanwhjf8m5zTV3AAk4UdFAAN6DPhL9XqhYcsBYAxT9gSnHngbulVL7tIju1EMNTgMgcovI6UAo8aPHngUNs2xwHj722BnQm2Vr4l3//SMu35qX3A95cE/ZLz64VB+ltOwKCrWrhJ30BHSFgtElPmBW81L9BRCOK90I4QcEhTAGDIpV4VgVg5gBX3z1H5W2npovX5atDIWTrpFGGqBUtk94+fzKSwrwYiFtxJ6xLAV4CfsGzvq4cGfWwCpAYOVgjZ40B54FCCkUVpgEs5jiZUZX4e9bUt8JO+B69rJ/0+tGVeR1iDQa87yH/nRr6gmRvohUCtUMSAQDNHONcJzA0JZ1QCa6k0EQIOpRQAGHKp1wDoCv/mhn5ZmJce4M18Pw5/RlGHWt0rwZ9U7auEDE3HT4A3DnUSxJljmW87CSD5+iQsWuHolGulAZIEeHWBTQNRybmUXDlte2k9Pk6F8TWnV3ssgZt336TcX+mzGBCYhMJUoYjWM1CAwkp42FktzI8PrQCgx/1z5P5pOdORAxjKVQBgyKV+AGCuA0gPxJ6mzioAOqt7XcUdOQ2eLedPAADLrROBb5kCd8vI4MsMGNTgr7i/7KoKCFpuYsVB1NzMlIPIgKsUVrUg0IJM+r6pbVMOXQrsLCBO3XcObZ9YEO+F+8p3JjiDUn6mJ0cwOYOIAoBitXACAvnxwQOBjZ1AZx6g5gBq1cABgCFJAYAhl9qaC9ibv2JWA2f2+3MDoLevXwoCE46fCYBa8r9xIlddu2XC+IKw/gvKthwMpfscEunrfeGqKlhmhJSTYKOFNfl9CaDrwFgdN86CWc2145CmLRd+B/w3YcGbywnOdICTf7sFhBoMWu1itLQKT0g4USWcbBNVtyjEUxhihHxTx0gzPBwAGCIKAAy51A0H0Gr3UscB9Dp/IgDmzt6RAj8D+prAn+jqaaDH73+BDGsdGRO+yLb9gvAcaT1fJ7mMCshoYJMcGmhhSDUFjm06bhpM1hhZUMZc3H2WKpBuucEpx5it16DT/L40RzBRQbwvdwOtauHc3EDmBCYdwEQ42NUiJhMAs8K94QCGEgoADLnUNgB63L+cHECv62fmADrcPndrF+/0blro1wAIE/wMmCtBHQG0CV8cGtb2dBt+6xoCUHCotdwqFRSXlB9XIIQDYA7IJaDMWu9x6DSAauzScdjmMJ7rAC8zXsfhDO59tQDbLByvtdzR3EB3biDrH+h1AbUUEa8T2Gi6uET4N/eYGgAYkhQAGHKplzmAVm6LJwfQAkA1xycX/qTco4Uy+Lnm9NVy/iQXiJ2QKYRpgDbhi1fBhC8tFoGOA2Bp2ZcWDw18TNfxbYXXKkGg4CipkCQBhgIeJiQyAJRg0Q1gy4RtBKD1PM4CPA3ecofk3jK3ll8giPcll9dyC7X9xPMqPVXDVlhYcwG13EBjFhE3ACogaLqALbSBqeUCBgCGiAIAQy71ei5gDn2lx5eUoc/rAJpJ3kboN7efnzifrwZ+GvxpIUB2QufwVxkSpHGIo+MadusZ0usIMKjmDXqgywKglKO2pLzOgj/6nhzuLCCt5dZZYVjp75ScOg5nRqje69pa68V9KaUD5EKgUpyjQqCnXUzDvoGV40MNCGwlDHzJUpcDqDmBpccBgCGiAMCQS70GwAr00VEz/OsGwHlLbOePTt9m5Pm5wr0UAGmCvAVCwonddOy8wMah7xpjfPEqeZnwXiKQGBDoBj8NNhi0UQA0QSwFYSlYS31u4bPVcu0EB06EtmXC70O4YBB/Q9LFRCJVwJv3yWGwEpb3OoFWqxhvaNgICyfbRLUVDna4gPRYWNv9CwAMMQUAhlzKAcBUfp8n98+EwJT7Rxs+Gw2eKwCYW+ErOH7F40UJ8HO0ehEhwXL7uMMnwZwEdteSW239tcL22msqsKkBigp3KaiQtuewRZ08DeRyQcy7Df8bJadMWpYKuQqOHIcylxuccokTIX4xzcAKHyvffyUcnOMGKikWSQh0OIEpAMwNA4sQmBkG1lJkIgcwVEcBgCGXuuUAphKcLQfQ2/NPa/JcOsAL84lWcoeMkK84nRur8JUAUMz5WyJAi+T6cdDjMPYlAequZUNaxseX2S29L4Ei/wxSSFj72xg0VIAi4YRJoFb5LhE+PCAmgShz19TXkSAo18VT3DrJtdv7C0qOppUGQH83lmMs7Uv+PAFCU/uG7g/LCawUhzjmFlbdQCsnMMMBVAEwt0VMRmNoCwDDAQzlKgAw5FJTAJQOVlpoQ3ssAWBu2DcFgOJMHlpvP62di9HU2ZzWjef+CUBROYlrIVoN7jjMcagbHHtdtwj2um5RaZkKgRJUUmCQ3EHDLcoKP5LvqARjZP0+SxVYtEAy4brxUKq13nLuvH+zCHQatGm5nlJepxXm9zi8UoGQVQykhYcJBIr5gZobyOfOToGgEgrm//cVB1BoFI3Hl67CnxIC1nKmk45gAGCIKAAw5FI3cwA9BzUOgHXz/jwOoNnaRcj7m8idP6G4Q3X8hIrfUvhXgg/pxI7gpUHZl+WhgR5dhveLZdcurj6WXEULJgg8VMBWcrioy6XAlbh8ECwogKTgywuhUmjU83rm61vhWClH01uoo33/fF9Z+48DvgaEUj6otm8EF1B1AyUQ1FzAVANphxuodgmoEQquBYJGCFiLnFgX2gGAIa4AwJBL3W4EbYV9WwNAq80DAqDm+FmtXbRwlBbqVaZ2qxRBMLCpQB93+KhLh4B2bRXy8HEBdtfb6/a6blFxWwI/9n4Vt1ByBVNhY8lZouOa6rIUYOF36YIxK+9N+0yOogkV6qRlElBpjynUWd+zBeX8eZ6Rcgyl0LLm5vLQsAWA5P9HzAlcvKTiACZzApXq4MrxoSEEZucBCpCXSpdJLgsADBEFAIZcahMAtQOVOw+wQd4frfalB/jkVG5Wrp8AfuJcswb4VcK+UkiUQgADP8nJo+C21/WJcV0Z9Pa6YfD+DYPjuurgMFgsl1xHDxBqeYyakyVBlRCKRAdQBDoLzjQAo9tp0Gp9fk8Yli+34C3l1mkApzjFpX0oXGDsdd0i+72170T47ivOrVYgojiB9H/N0zcwp0DE7BM6jxxTrIpgBoJ128FIx0ktNGzmBgYAhogCAEMudbsNjCfU0QgAhSbPSQD0tnURCjxM8NMaPAt930THj94XwrklsLuB3fL7FiDeQAZzAkVoFABUdQlzwsYpp0mAPgpbGPZ1h0tz4Sy13PM8CX7p+lTBjuYGC86wd4iOr5UTSvehFXZWnFQpNKy2iVGmkhNnEBHcwIkc/hZWw8GmA+hxAruQC2jlS7suvAMAQ0QBgCGXmgBg6gClXb1qANgk7Ev7/IkA6J3GzdPahYd7PTN8XG04f8zdKYVpObRJEMeBTltnPUcCSO4iMoew5Ax6wsVfZgDEAYeHjjk8MfjY+wtX2VCiPVeDbglWU/CXCqfS70Za7wm5s9B/DvRZ7q7k/laAn8Mg35c81C+5qgoEqk2jjWrh7L6BKQdQmzrO0xNQcAHdoWDlGFg3vSYAMEQVABhyqds5gNZBTgVA1u9PBcArllTcPxEAlUKPHPCrzOObyvOj8PeFsvNXtPWQQIKGeFOw163hcRMT8FCBCAmELMDgECXlR9KQrOXKScCSkwtnbWMV52jLDVdOeiyBt5jXKeR0mjDvgP3KPk25lAYEVgpGPDBo9QzkbqBWIMIgUATAeTUgUHAERQh0toGRAC/VGqZYHgAYIgoADLmUC4Cp6rTcyl/62OUAcvBjc37yA7yrylcBQE+4V5ztQuk9VzoZCuCnun7S+MpCe9lXFg4Nvo303Bw30QkNZqhYgr+U68THlxZX4UMLnUoQJgGb5silXos9TwQ67uZZLpyWwynd1wDdShHQ7pPX4cCpDgkIebHIoONdacmzrHzBVIJAqbKe9w3kLWMcTiC/QFRdQAUCt5XLAgAAIABJREFUKy1iWqoElmAvBYARAg5JCgAMudSNIpCcq1rVAfTm/gnTPYkA6GnxIoGfEOalJypzijGp2pfnfw2OSthXgrvUWM7uL2fL+JCgsU7o2Mo5ZG4U/Vs1t8uEQjq+eJUNiJrbmAAbrRCm5NAqjpz2GhYkq+BHfwtSnqbk1Gqhfcvl1fap8JmK36jm+EoOKnED1ZYx2jRyihPoDQlLhSEmADohMGuO4Iz8v1SoN0LAIY8CAEMutQWAKefPgsMUAKaKPnizZ80BpIniWmsX0/HT5vKV5vTVqnx5aw8p7KtB33IB7pYvhL2+aiz76uDgYChBIwLgcsE1TAEiz1O8YZEMhRxgEmFHzVnb67pFL3+XHD6M8KmWF1cBMCPM6oI57W+SoMqCsaYh/DZeR8o/ZftNDflzR5BXcSuhYBUCrdzARToIpgCwMmuIUgiiFoR4QLCFHMCoAg55FQAYcik7BHxJ3oFJAkOzCMTr/inwVwHAVLUvOXmIIV/ezoWHe6++quJqmC1I0BWRgITDH95+VQA/BLsbF5Qf47IbF5Tv821wcKjkIWL+vhwQJSjUoOGGRVUASriHktNUPL6mJqClXDRteMKsqeeknLm2Bv39SLAvucspp1D52zRQLmBQq/DmECg4gvz/rhIezi0O8QBgwgX0VAWLoWAOgo7wb7SBCdVRAGDIpW63gdHyWEQAlJquOsK/vNWLBIBqmxcr10/q58dbumhTnUnQx1w/1fmTwItDHwe9mxYMPb6J3eI2y8lzqUPIXURpmQSKGjDWcZY0h8lYNuHaakNr8Tm47gZlvQY4/LNaYGuFYXOhTVrOXVgL7LT0AL7f6LZ8mddh5N9ByhGUcgMlEEwBoAWBiabRlQiBMW+wFQq2QDAX/jxuYABgyKsAwJBL3WoEbSUvqw5gbtsXZX5feoCvgB/L96u0d1HgT+zntywBflrrEQv+aBiWQ99NbCDc3Tz4+GYBAPm2HB75MnorgSKCAn8sAUkOFHqgicFWAYBWOFWDlZz3TQFQGw6ddF/6fqXcTm3ZV4x9SR/z35oGid7vhbmDYm6g0ipmwherOYHJQhFWIGI1i54oAaAHAlMzhLSQB2gdJyVHMAAwpCkAMORSm30Ac/pYSYUgUvuXbABcoAAgz/fLDPumWruYzp837IsDT8g3MpC7mUHd164cWn6zsJ4+j7+WBozcTZTCxhI8SPmJUlWyBYV8WQKuioIE/hzttaXXy4VT6/na38ihzlO8I4X8+fct5XpqoX4J7Dn0p94vFwaJI+jKDbR6BvKwsJQTOHibCgeLDuCCoeOJCIGZs4PkhoCtC2NXpCUAMEQUABhyqQ4AankpVv6KdEUrAqCz+AMP1FKjZxMAJedPcP9K7V2WMfBj01yZrh+pQMVKUrPgY7lwYkZY+9qVQ7f8Pl1GHUEOh9pjzV3ky3iomIIDukc0t5AXr9BlEiSlIIt+Z9cZAOKBTasqWgupau+lOZ/8708BXSqfU3LzJAdXcnj5a/B1NyXeR6ssT4EgzQ2k1dye3EAKg4P/g6WQMG8Xg07gIgEEJQCkLWI8oWCHC1inIbQEgJ6L6mJ9AGCIKAAw5FI35wJOtTLQQsDeli/aLB94gN+6+5hq2Fdy/qRZPHhLl1y3j/f348UHGozQkzEFtEHAm/D1lwferwCgsby0joMkBUwNGLX8QstZsmBHAjDuNknb4XL8HrXX0l6fw5g1tFw5+hpaQU3KrbOcuhTUSWF+vm8kN1jaHp3kmxbI78/BX9qHKSdXKxCRikQsCJSmklPmEtYaRm/V2kRduaRaFGLMEZxdDNJgOrjUxXUAYIgqADDkUremgkv1uLJyAM3cP+YC0hCOCoCpnD9t+jYr30+DP6VnXaUClZ4s6QlVCvnevKAAv2LcMr96f/CWgiIf0jrRReS3llMo5Rla4WMOTRyOrLw3Ch7XEzDjldIS7KXATwPW1OPUc1OQR8Pu0nfJw/U8jC8BnxfqpffVPksq9K+5gUJltxgWNuYV1trFiCFhq1k0B0DeKNpqC6O0hmm7EES7SI4QcMirAMCQS92eCo5fsaZyAFX3jzmAFfdPqPLbOmYwBCxN6Ybun1Thy2fzoFW+Wi8/3tNPau4r5bXxsC8P+X6NQN6tg+MW5Rbv84HPZ6DIAZAulxxH0TW8mUHHjWwZd6+0XDS+XIJEKSctlQsngdhy4T1T+Y4Y6pbgVgqrWkOr2Ja+Sw5zmPvJIR2XS6kBgxcQ4vOk9AEO+hQUpf3JwV3LFTTa+1hOoHcaOSksLLmAW8cMXSBaU8bVagmTgkBnEUh2LmAAYIgoALDPuvfee2H69Omw5557QqfTgTvvvLNY98ILL8B5550HkyZNgtGjR8Oee+4JH/rQh2DLli2l15gwYQJ0Op3SOP/880vbbNq0CaZPnw6jR4+GPfbYA2bPng3PP/+8+3O2DYBa7koqzJF0AAn4pQBwKwXAVINnrcp38CRTqlCU8vtYZW8l3KtVqUphxBuHTvQlaJMA79bE4M+hEHmLAIv8MX9/Kews5RhyaODuFs9t5ECBz6eOqAZtNyxKh561UKrksvHPIOXOSbDneS2rQEfL2ZQgzXBpuZurOb3cORb3K95qeaKS0+vJERTa7ZRcc8kJlJpH89xA7gZK8wgPRgJUALTyAXNawtQEQCs/OnmsDQAMEQUA9llr1qyBCy+8EFavXl0BwG3btsExxxwDq1atgieffBIeeOABOPTQQ+GQQw4pvcaECRPgsssug6effroYzz77bLH+xRdfhEmTJsGRRx4JAwMDsHbtWhg3bhzMmjXL/Tl7DYDWFS49mGrun1T1y5s9qwBIqwWtFi9WM+e6eX508HAkz/mTXL9b58Pet82Dvb8x7+X735hXPC4tY2PCLfOL9aX7t84vPU8FSO4aCu7hhK8rxSnc0eKulnSLEEwhUQLJmxa8/F1qhQ5SHpvkxGnhU6lKmrub0nNScMdAr/geFYATw/lsH6iPb5k/5OxaFxNku9It378pIOQAruUICiBohoOl3EChcXSlb6cyY0gBgGOGisRK84VLuYAGBGa1hMmYEk6LmoiAGAAYIgoAHEbiACjpZz/7GXQ6Hdi0aVOxbMKECXD11Verz1mzZg3stNNOJedwxYoVsMsuu7j/0bsZAs6pCkYALCVaWwBozO9bOsAblb5ic2etqTPO48vnmrVcP6taVHL+aK7fLfNl2LtNHvvczpZ9g93H15Ke/43yNiXoJCApuoXMSdLCxsVjGsKkECFVMVv5hjcvGOpzp+UjapAmOWySA0eLI6zKait3kqyX8i05wFXC8ZYrKzm3EugxsC/tZ/46GlRKIWTNFdRAMFElLOYGesLC1lRyQjiYOoATF5WniWziAmoVwbmtYFIX02K6TQBgiCgAcBjJA4Br166FV73qVaV/0AkTJsAb3vAGGDt2LBx88MFwxRVXlMK7F198MUyePLn0Os888wx0Oh246667xPfZsWMHbN++vRibN2/uSRWwFfqtACCf8k0DQA5/iwwAtMK+VyecP+748Vw/bRYJCQDxpIgnSA5AePKnjh5C3oorSsC3z4oryre3D4Egf4ygp64XgLHiJmrhZgoNHGbQ2ZIKEph7WIIMBAoKVzcy8Fq+sOpM0VspTC2FVqXlgiOn5dBJYVQx5CoBHQ/NS7mezJGljq7m4HJXmDrIfJ9yx1jLJ1VBlsMydVmtim+lSKRRz0ApFMzCwqXjw6IlehhYygf0tIVpWAiSE/6NHMCQpADAYaQUAD733HNwyCGHwMknn1xavnTpUrjnnnvg0UcfheXLl8PrXvc6+OhHP1qsP+OMM2DKlCmV19t5553h9ttvF99r7ty5lbzCNqqApQNVCvhMALSKPwz3jwNgDvxVCj1yQr5WnzmpXQhP8Ef3jzlvJWCjwDc49l15OUwkjzkQTiT3KfghUFIQ5MDI4VGDwtItd54EiBBDyBpoWZCGACg9R8mfo6FRCtyWI8dDsSLg3UrCrVJ19i0CvEkunRCmRzivLONgd1v1Md3v9PekucpqSoDiEJb2jeSY8hzBVEiYt4pxuoFqSFhoEcMBkE8Vx13ASoPoGvMDiwDohD/NIQwADGkKABxGsgDwhRdegBkzZsDb3va25D/nHXfcAZ1OB37/+98DwMsAOHXq1Mp2o0aNghUrVoiv0YYDmArtWo6gBYVW3z+el4MHaKnRswqACfgrAPCaxeVK38GTDw9TJd0+Ldz7VQaABBwqrt8g0E0kgz+uQCAZFAD3Ya+hDgUItfAyh5diuVZ0gqBrtLWxcuGKdaxohjuJYgscyXmjTiYPoZJllXw6KfxKX0Nw6Tgs09sKlFHYVsL+CHYc2kU3eNBBphcAJWeZfQaafmDliIph/5sZBKIbyHspemYPSUBgZR7hL9g5gRoAVvIBFyZyAef7IDA3BzAFgwGAoZQCAIeRNAB84YUX4O///u9h8uTJBdRZ+u1vfwudTgcefPBBAKgXAubKzQF0tSTQEpWNAhDVATRy/yby8K8EgAL8FbN7pJw/KdePtrJIQR9vkcELGVgFZ8n5IzCGwLbvystfvl11Gey78vKXb/H+IAQiEOJjep86hvR59LmWm1gBj9uYo8RBhRehaBXIihOmwWEBiTcukMOpHMg44Hkqp52OpphLp7xWBQId+ZwVIJf2jbaNcLFgAj9bRp1D0R2Ucge1whH87Uu9EiVH0JMXSPNz6VzCXxAqgy0AJE2iLRcwe3aQhg5g6hgaABjSFAA4jCQBIMLfQQcdBL/73e9cr/O9732vVCiCRSBbt24ttlm5cmVPi0BSeX/e/L8D5i6tFn9olb8LFQDkSd4IgFLBh1Tsge6fNIUbd/y0sK/l9tF8P+5WUffstnkVtw9Bbb9vXgb7ffNl8MP7+HjfVZcNwR0dBPQKcBx8rcq2g6/B4bECD4JLWFnGc8x4OJk5S2pxgvJ4r5sWyFApABh/fZ7XWHLibhNgzQh/V5xRCfC+IcCdEH4Xw/OWu0tcXrqPONTzx9IyMZ1ASgNgIeeKWyoVjkitYywIvL4KgpX8QG0KuURRCM8R5o2iKxAouYBKKDgLAB0OoOc4GwAY4goA7LOeffZZ2LBhA2zYsAE6nQ4sXboUNmzYAJs2bYL/9//+Hxx//PEwfvx4eOSRR0ptXrDIY/369cVznnrqKVi1ahWMGzcOjj/++OI9sA3M0UcfDQMDA7Bu3ToYP35839vAeB0/0QHMaPxcCt2QKd5KAEhmCShcAanBs1LlqzZ0tqZyowAoVa/SAgKSGyaFfKnTt/8/X1qCv/3/+dISyOF6DojUMaSPKwBJ4JC+rwQLUji5CDeTZZh3VgpXslw0qUChAm23VMFtr5sWqM6aFna1QqrF5+KwJoTltbCrVq2tOm7ktgR07L4EcPTigO+P0m+HgT+/qJCAUMo3VQuHeM6gUDhSyg9ER5D3D+RhYatnIHUCWc/AFASmAHAihT8Ggd0GQC3Skky1CQAMEQUA9ll33323WGwxc+ZM+PWvfy2u63Q6cPfddwMAwMMPPwyHHnoojBkzBnbddVc48MADYe7cufDHP/6x9D6bNm2CadOmwW677QZjx46FWbNmwY4dO9yfs5tzAaeKQfgyd9+/BUuqoV8NAKXcPw5+vOBDmr5Nm79X6uknTenGqkpLoclBaKEnXHoCR0g74I5LC/DDccAdLw/+mC9HOKS30joKiXSZFTKm4WY13Ehy0MRQp7PghILcXl+7UiyEsPIVNQeuAnMS8PBiHCHHruLoaWFXBtGaSys+Zo7tft9kzi+5KOC39Pn7fVN4TbYvrfxSC+J5KF9snyM1kU61i7l+UbU6WJtHOAcA2XzBWluYFABq1cAFBBo5gJ4LaPX4GwAYIgoADLnkBcBkCMIJfckQsLPxs1T8oTmAvNGzGPK9xnD+eMgXT1LafLI3yuBXyVOj8MfCdxT+KNgduPoSOHD1JbD/P798/03fmlssw/HmO4eWcRjkgIhQiYBJgZCCougU8jAzcQvV0DFzwHiRSgGK3yjDFYe7fW4fBEADJCmgqLAmuZca0HFXzIA8yY3Lgj3FpeUhf+4A89QA3OcS8NNt6OPSfhY+Hw8TS9At5XJWWvpQJ5C3jNGaqPMqYa8TSHICeZEYB0B3X0ABAkuzgnhmBElcFEvHWTEXMAAwRBQAGHKpLQcwtxI4GwBZ6xce+qUNn0UA5NO7GcUepdk8pLl7v8IcC9riRSry+JpQoEByxBAkuOvHnT6Eujd9a24x3nznXPUxgiAFQPoa+JoaGFJApJ+DQwbPJeQ5iVroUsxlG7ylodOJHLhuHwJAEda0UOvt1dzKEqzdPk8MtUphbwpCdJnk6mn3S2F55tpRmJOgnO8TDnfavpQuCvB3Ye1TzQFWQZA6gTwnkDeSpnmB+P9EL7SMuYTVcLDRI7DSJeCqhAPYJAw8CIJ1poPTqn/FY20AYIgoADDkUp0qYK8DKB3ATADUmj5b7h+Bv4mLl1SSvMVef1qPv1R/P6mnHy5T8vyKkx/PY2PhSQoGFLrwpP3mO+eWxkHfubh0++Y758Jbvj2nAL+3fHtO8Zg6hW/59pzKa1EopIBAH1NQ5G6S5jxJbqEFVhQ0aF6cBmwTbp1f3oZAHq9+lfLcuHOJy8T8OQ5vUnENqdKWXDoph5MDnvTd4nLq6nJXmP5W6L7jFwN0cCikr605hhxetXB/xQ3UZhXhs4loeYEIgxIEfpn8D0uhYDZvcCVFRHAB1TDwAqMaWJoeLuUCOiIj0nG3AoQBgCGiAMCQSzkAqIWBpZwV7QpWDXVcUnUATQBcNHTALk36znJ8+Py+BQAy8CsqfbV8Px7ypWErPGndLIR9WRNgqcdf4f6tKodi8aSMJ3AEvknfuRje8u05MOk7F8NBZEz+7kVw0OA6CoF4H5+PyzkwIkxyaESIoC4kd5J4CJmCg+QMmoO1rZHy0vZdeTlMuGV+GRwJvKn5dQKUaoUyHOJ4eFZ6Da1KWwutU6iWnFoN6qT1dBluIznElovMXUINSgvHkgHwRPJ7RhAUW+hobiBCIG8Xo/UN5K1itEbRFgAuuaoKgLwtDAsDV/oCXpEGwBIEOqqAUxBYOp4GAIaIAgBDLtUJAafcPysP0HIBxfAvK/yQ+v7xZs9ZAPjlMgSaVb40X4mGrVh7F2n2B+748Tw4BAp68qcQh5A3aRD0cEz6zsVw8PcuLOAPl03+7kXF8+jtJAKACHwUFCks0vtv+lbZYaQAwUOMdBkPVUo5Z2JFslK5TJdNuHV+1a0zoFIqnuCDF8vsu2qo+IZ/Pl59LeXSSZAn5XRqjh1dzvcH357eavuUQz99Hn8N7iryv4EWCOF3YbqBHAalKeUwP1Dqo7lcAEBaHcwBUHICl10ldwkgF5GiC7igCoGunoA1egFaoV+1GCQAMEQUABhyqW4OoCdE4YE+LQRcwB9ecRu5fxj6VQGQNnrmvf54n79UY2ehyAPhT5vjlRc00FG4WsT94/A3iYAd3j/4excWAx/j7UEEEg/+3oWFU/iWb88pgSMODokUOKlbSAfPNZRcJupm0VAlhyLJZUKw0KBq31WXwd63zRPdNykkTeFNAjKaOyfl1lFgk6qypaprKf+Ofk/8Mf3+KLxxB5jDHAd5uv/ovp0k7FNpP0ufjxYf8X0nwTFvJyPOKOLpGeiZRs7ZJxAhUARAHgpezFxAYX7gAgKtELAGgTUcQCnaEgAYkhQAGHKpCQC2WQFcAKAR+lXz/8h8nzzEo7Z7kfL9eKWv1trl5gWlIg+pupf3nNMKEigA8pDvQQz43vr9z5fG2/9laEhQ+PZ/+XzxGGGPAyMHQnQSKRxq4MBhkLpL1EXiEIEhSlzPw8kIGhSupKrWfW6fVwItvj0viNjvm5eJbpaUByc5XlohhVRYwwcNyWqDh+6p68tdWw7t1OGl+4xeDFDoR4eY72f6vrhPKYTyXFGaf0grkXkoX8wLvFUJCdOcQOq2pxpH8+IQJR+Q5wjzuYIlF7A0RZzUFsYqBsmoAvZcNIspNQGAIaIAwJBLdUPAUogi1a7AHJfYAFhp+syrf1MA+CVyQrhGCPty9486fhIAklw/PsWYmOenVYeuGgozUniioV6EOA59b/3+5+GQNRfAW7//MujxdXiLz8Vt+DIaNuaP6aBAysEQoYGHlHneGoU/Ck3cGaPwxosT8PE+t88TYY3n0XHw5G4cghldzkPZFGCtwhop744CPYc96tRNYvf5oNtY0M73G78woBcD9Dka9FPXkYeJeVGKlPtJi3p4y5jSlHu0cTQNB3M3UCsMuV4BQBYOlorEKi6gJxdQKwjxzAuc0QbGyr0OBzAkKQAw5FIbbWCkAhArVOx2AB2Vv9T9w5YvJgAS968AQNrnT3P+WJFHpaGzUORB25jwYgWaX0YBiELBW78/5OxRuHvHDz4H7/jB54r7h6y5oDT4Nvy5fFvqKOL9yd+9qABE6hZSWKBgeJAAD9RF4mFjdAt5kQpuQ4GYFzwgfO278vJKGPWAOy4twRx/DocyOnguHV9nrZe2k8KxCFk8/Co5dAcNQtpBBNYkSKeurjRwXx6y5gJxHX8Nuq/5vtX+Zl6hzCGwUs1NezvS2V54hTB1BGnvQNouRpo1hEIgCwVXHEA2V3CyLUyqGMRTCZwAwOxCuwDAEFEAYMilum1gPC1gJOBTHUHuAJKwrzf3D9u90AN8Bf6483fdIjnnj8/le6MAfmQ2D6vAA10/HsakkEKdIXoyp+D2Nz88vwR37/jB5+CwH50Hf/PD8+Fvfnh+CexwGS5H8EMoxHX4+giDEhQiOHAg5GFkCQwpBE0iAEHhRypakHIK+XoJAC2Y406clNfIc+ykPEjegkcqquHOKAcp6TvkwEbD/lIKAII6hvqp+4vAh/uT7ke+T7ljjIOmDEigT6vGJVBHGOQzjJSmCpRmD7k1USWMF2VGYUipUfS1i0sRANEBlHIBHTODWGHgOg6gJwdQvPgOAAwRBQCGXGp7LmAPEGoAmJP7V+TrpAAQr/yvHTohVPr80TYvfC5fOmvB164st3dhuX50tonKNGmkKEEKK1JImjTo/nHH77AfnQfv+MHn4PAfnVeA32E/Oq/yGG/poEBIARLBEqERQREhAUGCwiEHB8mdQjiRXEHqgtFCFwkULWDbd9VllaIJCcToa9BcOd5Ghy/j63nrHes+H9ylk0KzUm4nBzcOawj1EvBRt5c7v3Q/47Y8hQDfE/e3lEuo5YNSAKQVwtp8w6UqYVYcUppKTppCTmkYLUIgB8BlMgBKEJisBmYQKDWErkBgZu6feiEeABgiCgAMudQUANWk5NwiEMMBlHL/aN+/fZaSTv8UAP9yTCXnT233wp2/GxeUmzsj9HHnT3D8Ko2NSdgX3T8aCqVAQuEPT9Ic8g7/0Xnwzh9/Fo5Y92l4548/WxqHD26L2xwuPJfep9BIHUUODVqoWXKocDnPL6NAKMEEz0Wj3wt31SZ952LY75uXVeCROlMS5HHHUspvlD5Xyu2kFdeSO8odPA5pFOz494ygbj3my+k+pbfWhQAdFPilvFH6t/IcQVosYuUFltxAMreyWiXM8wK1nMAbGABSEPzSYtj6l0KbqKuVMLDmBDrnB1bhr0YjaOtxAGCIKgAw5FJbOYDaAcrajo/cOX9Lzt/VQ9O8lQCQ5P2ZM3x8lbl+1HHAal9StViq8CVORtG8WGhjwvP9sIUHBR10Xai7R4HuXWs/UwK+d639DByx7tPFcoTCw390XmlbBL/DjUFhEAe6jhQoKFRQ54hCCwVD7njRHEOeg0YdRQ3IcNkBd1xagkru7HFI44DJC20Qvunn5sUTWusd/hweUqXfkeTu8u+PQh3dFxzm6L7AfawNCv/UJaa/Nfq69LNYIIh5itQppSAouYGFI0h7B94+r9ovUAsJ07xABQDF2UKuERzAweF2AQUnUOsJaALgpXnAZ90GAIaoAgBDLtWZCUSsQkss9ziA5qwflvt39VWlhs8VALy27ASI7V40AORh31vmVyoZKy1d2NRftCqVFwlQZ4rCHz1Bv/PHn4W/+8mn4F1rP1Maf/eTT8Hf/eRTcNRdn4Qj1n26eHzEuk+XBm5/+I/OqwAivj4FReoUUheRLschuU8UYGhoEkOV3Anjj6m7RCuV+e2Bqy+pFDNQ2NNC09KgOZfc1eSfURqSiyc5ffQ7ovuaO3Q8lE+dXGl/8H3D9yd3iOnFBIVDep/DPncEaR4iby3DQ8J8JhQ+XWBlXmEhJ1CEQHQClxM3UGgPQ0PBJQeQzBCSrAheuETOB5R6AjZ0AL0X1gGAIUkBgCGX2pwLWFqXEwKWZv5QAZC7fzjP7xevGjrA/+WYofwfKfQrFX1IVb6DA09KtMK35PqRWSrwZEeT4qVKXworNKfrMHKiRmfvqLs+CX/3k0/BMXd9ogC/KXd/HI6665PFOrzl9xEE6XIOiPQxDyFLj6kzyJ1DCRr4falIgTqINAeNOms43vStuWJrG5q3xt1IXtyifS7pM+Pz8G/D5bwARwrL8jxOyXnjjiyHOQpx3AXm2+E+xd8O7l/NNeb7/Z0//mwFMDnk8+9G6ivJi3q0JtKl3EDeLkaqEqb9OOnMIYYTiBBYOj6waeL2Xma4gBz+pFCwBICXLZX7AdYEQDHCEgAYIgoADLnUZCo4K+/PWxWsAmAq908J/7oBkMIfrfbl8CdN6XbbPBH8pLlepdYjNC+NNm2mIT906PBkTSHvmLs+Acfc9Qk49p6PFbdT7v44TLn743DMXZ8otkM4ROjD5+Fr0ddEB/Gouz5ZgAF1GjlU4GMEBuoW4i11kHhF8mE/Oq8oPOEOmRRWlnLj3nzn3JL7JlWzouv4jh98rlRIwT8HbasjgY6Uf0ehiOZOcgjmgCyFZumg3zOFNQpx3OXFbXFf4n6UnGK6DJ1lep+nGuBn5FXnHPCloqBJJCTM28XQfo9RpzCSAAAgAElEQVQ0L1BtE0NyA8VQMC0M4e1hyHzBpePDlxYPTRPHK4K9LWGoC5gzJZxzKjgJAMMBDFkKAAy51O1G0C74QwAkDVbN1i9S+PcLNgBWGj4vX1gt+kD4ow2esVHtrfMr07jxxs4U/OiMHryCleaecWeJh30leHvvvbPh2Hs+Bsfe8zF4772zS49xHHPXJwoopGCIy/H16OvS90KwoFBInSIKCdQ1omFmdJGkamSef8bDoAhpvMUNBcG3fHtOyYHj4VWp8pW/D/0cHN6k8Cz/Oyjg8UFzL/ExQjOFPcmF5YMCGw/54/6hTi/CPd23Evzj/sf1UvoA3Z+8qIjuG96Y/K3f/3xlJhNaIFKZV5jM6TyRFIYUMCg5gegG0sItyQUkEEiPD3SO8JxiENUBdFQC1ykCkY69UQUc0hQAGHKpTgg4lfunOYQuAExN+8bdv2Xl8G+pyu8vx1Qrf69jAEgrfTHnT5nSTertR50/OvsE9vbjzYBpHhrtyYZJ/BQM8KRMQW7K3R8vIG/afbOK8d57Z8Nx951buqUDXwfdQgkWMaSMQHDEuk/DlLs/XkAGDykjiPBwIoUaHsrmxQY8zCkVofAqZQyjHvSdi0vbSO1t+PN5fh2+p5RHdzi75fc1B08qwuFuKv2e6HfKv2sKcfid476iAM8Bj4I/dYn5vqbL8HUoZHIY1KrLEQRp/iPNz9Qqhen/Cw0H0/SKUoEIhUAEQeoEavMGk1AwdwBLALjMlwtYCwBrVgFrIeDS8TcAMEQUABhyqVt9AHMObFkAuGToCr0CgIMtX+gBnlYCVgo/aKsXOq8vCfkWOX/fKE/pRtu7UPCTijx4uxBeFYrOE55c8SRMoe+9984uQA+h77j7zoUZ/3pOcYvL6Hp6S+EQ3cNp980qQSG+FwVPBEWab0idQwSXI9Z9uuIeatXLfHBYQqjg+Wg0V27Sdy4ugbNUFMEhTqp+pk4mdeikz6mBHsIc/3s56FGgoo4sBT0JyDm8c4jj6+g+o7CPjyn00d8ZdwWlVAEK/BSIeS4kzd/UppajTaRpCkUpHMxzA9EN5DOHoBuo9QfUAJBDIAVAKQwsQaCnIXRmCNjrAgYAhrgCAEMutdkGJgV/yRxAY+o3OlG7VPlLZ/wQAZAXf3x1YQX+SlO70WIP1uOPFnvQ9i44Dyx1/Sj0UfePV1hy+MOTOwU3Cn0z/vUcOOGnZ8MJPz27BH90Gd4ed9+5BfjRx3ifg+W0+2YVIMhDy9RJou4SdawQIqirhbcUlmhlMs0/48UO3HnC507+7kUqXB4mgB0vlJDcLR6GpXl4vPeiFKalIVhauMO/Gwp69DuVoE2COQp+dD/RiwXqCNPfwLT7ZhW/Gdz3OHjaAN3XvMqcfi80F5TCIJ9eUALBt3x7TnEBxXMCS7OH0KbRPBxMewRSCBQaRFdSRL44lD6ihYI98wMn+wE2AEAR+iIHMKQoADDkUlsOYOpq1eUALlwiV/9qxR8s96/o80UBkPf8w/AvC/0WOX8k9Etz/Tj4Yd4SrfBFR4Pn+UnVp7zNBwUKhD8M81Loo/A341/Pgffdf1YBfSeuPxPed/9ZxTa4DpdNu29WsS0O6h5SOOQuIjqFCBwIGpKjRAtUJDiij7mDiMBEIYu3wMHXeev3P18CNOrMHUbcvFTolRdD0MIbGpaVWutI0Cvl6fHvhT7WgA6hjF8EcGg77r5zS+Anub8c+Ol9uoy+BgXO9947u5I/SL8H6pzysLDUE5LPLcwLRBACKQwi/JUaRt/CWsTw9jC8RyAHQDZPcAGBVi7gQqcLqBSCNGkErR5zAwBDRAGAIZfq9AH09P7LDgMnADBZ/EFm/CgBIG/4fMOisvvH+vxVKn0ZAPIqXwp/fDYK2jiYz+nLGz0jdFBXiLo1J64/s4C5D6w/Az6w/gw4cf2ZcOL6M8X777v/rGJbvI+vg4PCIgVGBEJ0DDkgUvDA7RBi8DHmDtJqZC23jbamoZXLGnwhnL39Xz4v9j+ksIfjmLs+UThzFPpoKJWux8/2rrWfqRRPcEeP/i1SiJyHabnDh98fdWKpW0cdPAroFOCpq4v78sT1ZxYXC7i/uUvMnWL6fhQ2ab4od3151TINC/NZRWi7GKl59Fu+PafkAmoh4VJO4GBVsDhbiJAPWHEAr1ksOoBiHqDUEoYUr5l5gC04gNqFdgBgiCoAMORSEwcwBYRZYWAEwIUMAGnun9D7rwR/GgDSli9fWVgp+qCh31LBB6n0nbjiihL80ZAvB0A66wUNgdFcP+pOHf6j80pOEQICPUG/7/6z4KQHTocPrD8DTnrg9ALiTn7wNDjpgdOLZdIthUK6LS5HSMRtKGxSSESg4GFoCivUgeIOoQQQvIUN/v28+pl+PwhZh6y5oAKN1N2THCsefpUKI6ibmYI5ycXj21G3jjt4EmBzp5cPBDwO7fh86gjzgfuV3qfb0/enEDjjX8+puL64Dzmg89xAaZ5h2i6GVgpjDi3vFYhNo2nD6NKsIXTKuK9dKU8XpwGgAYF8dhCzGKRLDqArHBwAGCIKAAy5VLcRtNmSoG4RCIe/RSz3Twv/EvjjbR5KYV9e+SsUffCKX+o88NAvDfviSYy6fjTsS/v70Tw2WjyBQEHhgMLfSQ+cXgDfhx/6CJz84GnF7UkPnA6nPnQqfPihjxTL+MDnf/ihjxQuIgdK6h5ypxBhASGDggt3qnguIQ1r0vxCWuRC3TCpUhVhDEHyb354fgXSaM9ECeYsJ44DqVWAQT+n1I6HAx8Ns/JbClw8dE/HCT89uwTr1PmlMEfdYNzm5AdPK+1P+lx6EcDdQQkIafEQhoan3P3x0m+a5lrymWF4z0ApJEynj5PyAun8wXzu4FIoePnCigtY6RJwjRAC9gDgosxCkAZ9AFNttQIAQ1QBgCGXvACogZ7l+tXKAdTy/6gDSIs/mPsnAiCd7WP5Qrnql+X9lfr8kWpf2twZT1YHsSpfOnMFrfKlIV8MUXIwoUn7NJTHwe7DD30ETn3oVDj93z4Ep/1sZgF/pz50ajFw+Wk/m1k899SHTi1uT33o1AIs6Tj5wdNKAIggQZehu0hhAT8vBcRj7/lYySHkTqGW50bBkBc54P2/+eH5KiDynofUhZTeF8GUfkbeSod+Hupw8pAt3Yd4nzum+B1R2KOAht8tD+9zF5jfx/3y4Yc+UuxLCv94+4H1ZxS3+Br8QoD+/nC/auFhWkFMnUCs4JaaR1MA5K1iMLWCF4fs/8+XlmYM2WfFFXJ/wJtJMciNZRCU2kQVx5BEGJjPDMJnBdEAkEJgUwdQjMAEAIaIAgBDLtUFQCn3T0tYrg2AEvxpuX/XDDV8LgHgV5jz91UCgDcvqPT7o86f1O6Fz+pBAZA6f3RWCdpzjhYt0JAmBQsKf9S1O+1nMwuYO+1nM+H0f/tQAYD4GG8R/Oh9DogIgxQsKQgiJOByCn7UXaIuFXWYaI4adZN4KJS6h5LTxIsicPlhPzqvBHTUneMFDLiMAgx9vxN+enYpr45Xzkphburu8VY8PIzL8zI5XFN4w++bghkFf1zG9xvdl7ivKfgj8POLCfpaPC0AIZQ+5q2HeH4gLYChxSH4f0BnU0E3kEMgTa+ghSE0FMzzAYtQ8C3zq7mAX5UdwNI8wbQdjFUNLIWBtX6AQiuYujOB8GNuOIAhTQGAIZeaTAVnhYWtZRoATtQAkLZ+uZq5fykApM4fmfGDFn6U3D8s+FhVnrQe273QVi9Sc2fa24+HfXnlKG33Qgs+6EmXnrAR4s76+SkF/J378Elwzs9PhtkDH4Rzfn4ynPXzU4pl5/z85AICz/r5KXDaz2aKyxAO8H04ZNB1PLdQAxrqImFYkVYj86IFDos8dIoQho7icfedC+/88WcrFa0U+iSnkYZiaS4dLaSgDqbUfod+dvp30VAtXc5d0/fdf1bJfZMcOg5zOCRHFx9TwP/wQx8pwT+9GDj93z5UWo+P8YIAB342XlxEw8R0//BcTqlKGAGQuoG8QpjOGsIhkAIgbQ+jzhRCp4oTHMASAF7DIJBODbdUnxqOh4FL8wK35ACmCu4CAENUAYAhl3IcQE++n6cQJAmAvPp3ydBBWOv9V8z3e70AgAiBeCL42pWlti9Y+Vtq9EymdkP3QYI/zPmjAIjTk9GwL4Z8aRUpDXMiUNCqXTwB48kax1k/PwXO+vkpBeSd+/BJBfid+/BJ8ImBfyyW4zbn/PxkOP3fPlTc4mvQ+9xhpCFk6iByt5DCDA1T8nAi5qpRcNJy3U746dnw3ntnV3oZUvfpnT/+bMWN4iFYCtXo8EnOnBTy5EUX9LPzqmweNqVwjE6ulMvJXT2EOg59p//bh+DkB08roI1eFJz181Pg5AdPK+0v3Lf4XHyM+5I6yPR3wd1h6g7i34B/KwVmdHap20qLdxAAD1lzQeEGSrmBtDqYQqDUIobmA2JBCIXAylRxgxeCUp/QUi4gzg+8jEEgyUcW8wAXMgAkEKjOBlIjBCyGgQMAQ0QBgCGXulEE4g1nSAAoNoAWWr+UCkC+PDQqIR5s+swBkBZ+kLYvfIo3BEBa9IF9/njIV3L9DiMtXvjUbjR8ScECYQBPxHgCR5CbPfBBOPfhk+BTG06ETwz8I3zmkffDpzacWDz+xMA/wuyBD5YGQiLeR0DkUEnDyvQ+DyPjreRcUQeJQxBCFUITz3/joUZaicyXHbHu0xUHkRanUIDD95KKXKgzx0OyPLRNPy/e8nAtX0YdPZqbp+VtcofWuqX7DB/jwAsC+ttB2KMXDnTdaT+bCec+fFLFGT71oVMrRUMY5qeuLZ9dhoaEacNuqWH0IWsuKBWFYGUwFocgBKIzv983L6sUhNBCLhEAv7oQtv7l7uU+oZYLuEzJA5SaQnMHUAoD00KQBjmAlWNvAGCIKAAw5FLTNjDSAamWE6iFgHnrF6n9y2DoF2f8KAHgV8uh36L6l873e9tQ0Qc6C9T9o82eMTw1iYR+OfzROWLpzBLo+mGYkjpXFD7QcUEYwJM0ghtCHg4EwM888v4SDCIQchjEZXiLr0/v0/AyzzWk7iCvSOaASMPCFBwoJFLg+vBDHym5gQhLUkgVAZA7dliwILW24WFr6mDynDwJBq0cSR7WpQ4ad1G5u0ddO7oPMKxPnVwcdL9RoKe/Fe4M43068KIA9z91C3mhkfR9UThHJ5BPH8j7BfIp5GirGDp/8EFCdTCmYxT5uSsvLxWElKaJE3IBSwBI5gl2tYMRCkF4HmBWL8AWQsCRAxjiCgAMudQkB1BMRjZyAt0OYG4BCLp/FQDcfSj8eyMr/BiEvwIAhWbPFPww/MtDv7zKl4Z8D//ReaXGwjzkiyFOCoDUQaOuDp7AEdwQ/D7zyPvh/Ef+Ac5/5B+K+5955P1wwaMnwAWPngCfeeT98ImBfyy5g3wZAgANHXOQQJigoWIEQ+pi0WIUdI0QHGhYUQojU5ikwIWQQV27kx44HY656xOVohQefpUqZTm04UAA5Y6dVHXLn0/z8uj3QfP08PuiTh8P5+N3TqFMgzXcn5/acGKxTIJ8ut3sgQ8Wt9QtRjjkQEkdRZprSAGe53vS8DsNB/NZXei8yrRfIM0J5M2ipXxAqTUMbRDNIbACgDwMzKuBl5E8QN4ORmgI7W4FUyMHUD3WBgCGiAIAQy7VnQlECv9mh33puHTp0AFVKAAp5f8tKwNg4f5JAMhm/djrpgVl+OM9/1ZdVpniDXOREPzoCQqrfXl7FzonLIU/WlDACwgQlk596NSSC4Qn6vMf+YfSyfz8R/4BLnj0BJjz2PFwwaMnwEWPzSiWXfTYDLjg0RMKOOThYoRFCoaSc4hAgIM6TxIQUmCgcCg5YBT+uItI+9dRZ41CIgXAkwdb1+BrUveQNsamwEdhhoZmrV6K+FmkMO5pP5tZycVDGOa5lzT8SsPyuC8o5PF9RF1dvpw+pqDPLwDw94PLtX3P0wLoPqT5nlIPQdor8Nh7PlYqfuJNo3mLGKyqRyeQhoOxLUzRH3AQACeuYDOE3MrawiAAvnb3oeMDB0CsBqZ5gKlqYJYDmNULsGYOYCUfMAAwRBQAGHKpbghYTERu2AiaA2AlBCzl/10z5PylABBDQqVZP0j+H5/r15rjF8NVGPqlPf6w0TPvTYcnQtoDjoYmqXPEK3yp44dgd9FjM2DOY8fDpRunw6Ubp8Ocx46Hix6bUcAf3sfHn3nk/QUk4uugG0RhA5fR0CF1lajbhJDAiw0QdGiVKa9epYNXuCJY8MpkCmrH3vOxEpDR8CsNpeP78XA1z7vjVbVaQQSHVhoSpy16eBENDe/SnEyap4kOHX7XGqhR+Lvg0RPg3IdPKsCObkddYu4Yn/vwScVy3Ja+P88VpBDIK8Ol9jHoBvJZQ2hhCALg4SwUjEVV2B5mEusRyAtCOACK8wTfxAFQcAB5HqAEgEuukgHQCAFzANz/sjwHMJkHGAAYIgoADLnURgjY6gNYFwCt2T9KLWC+TBzAYqqnwQP8a3cvh36x9ctg2JeHfmm/P1r0wZs901Yvh6y5oOjxh6EtPhsFbTDMK2AxfEZh4tSHTi2FAvHkjCCHwIfjosdmwOUbpxUwOP8X74U5jx1fLKPQR91ChEbqFCIUSq4QOko89EjdKx6qlIpLaCEDhyQJwHi+IS6fdt+sEljS4hnePgeBjbpYtNgFYVUKY3NI5ct4IQbN3eOhdB7Spbl31NmlLi0FNwzt0+UXPHpCAYK4He5zul8vemwGfGrDiSV3GF8Px6c2nFj6DUi5g7RghFaF83Cw1CaGQyDOGkLDwPh/hQCIhVY4Wwj+X9Im0UUuIFYFYy4gnSLuZsUBvF7IAxSaQquzgkjzAmuVwA1yAM0wcABgiCgAsM+69957Yfr06bDnnntCp9OBO++8s7T+pZdegrlz58Kee+4Ju+66K7z73e+GX/ziF6VtnnnmGTjllFNg9913h9133x1OOeUU+J//+Z/SNo899hgcccQRsOuuu8K4cePg0ksvhZdeesn9OZs6gI3y/ngIeLEQ/l1S7v+HB2Wa/1c4gBIAfnVhCQDR/StCRbfNK7V9kSp++Ry/6FLwJs98ajc6rRtteEyLHPCkSZ0/Wu2LoV88oSO4XbpxOly+cVoBfPN/8d7iMYVBXDbnseNLbiEupy4hOoo0p1Aa1C2SikoQWqlzxAsc6DppPW1hQvvWUTh7772zS5Am9cyjz6OwhmFZ+n70/XlFrdZHUQI+dG9ptTWv0KYOHYc9Dno0vI/AjgP3GYIbXUZv8XfD9ze+Jm7Hc0ppyJhXkGO1MF640MIa6gTSaQFpn0AMCdNZQw5ncwfT9jA4UrmAE7EtDBaD0IKQmxgAfmVhuRKY5gFK7WCUaeHEKeHm6YUgqRxATzeF6AMY0hQA2GetWbMGLrzwQli9erUIgAsWLIDXvOY1sHr1ati4cSN84AMfgD333BP+8Ic/FNu85z3vgUmTJsH69eth/fr1MGnSJJg+fXqxfvv27fBXf/VX8MEPfhA2btwIq1evhte85jVw1VVXuT9nnRxAK/+vdi4g5gBqDaB5+PdLi4uJ3E0A1KZ9o5W/LPSLAIghX3QeeMsXqc8fb+5MZ7OguX4YLkPnisIOz/9Cl4eeyBH6Fjx+LCx4/FhY/PhUWPD4sXD5xmmw4PFji/Xzf/HeAvjwuQh/NGyshZAROGhhCc8rxFtcRvPPuPvFix5mD3yw+JtpE2taGUvBCt3Rc35+cuEA8qpahELeC49CH83Fo/BGPx/fhrfjoXl8uM/wPgdkGo6lDiot1qEuLYdyuj8Q0nH95RunwfmP/EPJ0UXYp3CHzjC9GJDgkO5zCqXc8cViId4yhvYMxBxXLHrCVAg6BSJeNPFp4/icwbQ1DIaDSwBIIJADYNES5mYFAG8gAMirgXk/QGleYG1GEA6ALYeAwwEMSQoAHEbiAPjSSy/BG97wBliwYEGxbMeOHTBmzBi4/vrrAQDgiSeegE6nAw8++GCxzQMPPACdTgeefPJJAAD48pe/DGPGjIEdO3YU21x55ZUwbtw4twvY1kwgWlg4qw0MdwB5+JcWf3yJtX+5wQbAAv6+fuVQ+Hew+IPO+EHz/rDyEE88NPRLT1Tv/PFni5MYrfilrh8N/dJiBRpaxJwwDKfS0B91/ijgLX58Kix54hhY8PixxS3CIL8/57HjC2jEW+4QIhggRFAXiRadUAikAMiX0dAwzRvkTpIUEqXrKZghDB5337mlfnk81447kLyljtQnkX4u7njRlip0G1phK7XcofuSun4IgAjc9DunMEb3C32MTi93fOmgji/d35dvnAaLH59acpHpbwF/A9SN5AUo1AWkDappVTXmAtJZXfjUcTQUfBjLB6RNojH/dhJrC4O5gLQgBJtDY7EXLQYpAPC1gwDIXUDiAJamhvPMCywBYEt9AK2ZlgIAQ1QBgMNIHAB/9atfQafTgYGBgdJ2xx9/PHz4wx8GAIAbb7wRxowZU3mtMWPGwE033QQAAB/60Ifg+OOPL60fGBiATqcDTz31lPhZduzYAdu3by/G5s2ba/cBtFrC1JoJhDuAvAdgov3LXjcsenmqJ3qAHzzoF5W/t8wvWkVIuX8IgAeRqkM86dBZPhACMWxFnT86/yydXxaLPmgVKs1H4wUf1OXRXL9lTxwNS544pnS7+PGpBRgueeIYWPz41OJ5uByXUVC4fOO0kmuIMELDxdQ54tXG1M3iwCAVL1htSyhcUfiikPa++8+qhGG5MyfNmiK976c2nFiqwuWfl7bKQScMPxv/O3mIlxbf4PdDQ7l4n+dxUnjDfUNvcb8sfnxqsS3dhsI+7ne8T38P+Ji+LrqF1H3mVeMIgHwmEd7iB/sy0vmU6dzNNBSM7WHovMG0PyDNBcQ5g0uzgwwWhJTawdCZQTgALh+aI3iv66vzAot5gNK0cJgH6HQAmzSCliAwADBEFQA4jMQB8P7774dOpwNbtmwpbXfGGWfA1KlTAQBg3rx5sP/++1dea//994f58+cDAMCUKVPgjDPOKK3fsmULdDodWL9+vfhZ5s6dC51OpzK8IWA1BNEk/0/LAWQOIB6QK9O/UQfwKwsrDiAt/sDwL7oEE4kDSFu/YP4fNnvGnn/U+cMZP7DdC7p/vNoXB+0jR3P+MKxJ8+eo24YnZHT/0O374i+PLMa1v3w3XPvLd1eWf/GXRxYnf4REOni4WAMPnjtIQ5E094w7WrMHPli0r+GgpMEhzTejxQgUwmYPfBBO+OnZJYcRYY9uR6ttsdBCysXT2qnMHvhgxbnjBTI0P5K6fbRIg1ZuU/Djjh4FOAr9HP4psC154pjC4aPuLv2tUDcYLwD4QIcQ79MQM88RpPuMTzVH8zH5zC68MASrg9FBl+YNRucdcwEnOfoC7kPCwCUIlAAQjx3XsVxADoGJhtCiAzjfqAKu0QhaPfYGAIaIAgCHkTQA3Lp1a2m7008/HY499lgAeBkADzjggMpr7bfffnDllVcCwMsAeOaZZ5bW//a3v4VOpwMPPPCA+FnadADFK9G6EHjJ0qEplhYLDaCF9i9iCFhwAGnuHxaAFNO+MfcPQ0tvvnNu0ewZHYh3/OBzRcuXw0izZ6z6xXYvtN8fn+qM9o+joUle8YvJ+QhbeGJGcKPQd+0v3108/sqTfwvLnji6ePzFXx5ZgN/ix6cWj+ly6gZxCMR1kkNIcwul4oKLHptRCg3zilYaFkWooMUHHBR5X7wT159Zcuh4z0KpOIXDGw/JUmiTlkvFG7Q1Dy2iQBeUgh/NycP9SoGPAhjN50SY478DGuLn0If7d8Hjx8KyJ44W3WJ0jPlvAfc5TwvA/Uv3Ec2jpOF4dAG1ymA+ZRwHQMwJxP87zAekxSBiNTBpC8N7Ak74+pU6AN4g9ANkDaHVPECvA8jnA27D/QsADDEFAA4jDacQMJc3B7CSc+KAwewQ8GIFAKn7J4WASQHIXssVABx0/ibcOr9oFYHun1b5y+f7pQCIVYuY/4fwh+BH3T8Kf7zXH1aVIqDQKlCa18XDvdf+8t3F7bW/fDdc9+QRxf2vPPm3lWUUGq978ojSyR9BggIDdZkofFAooY4VwgwFGxoOpmFhBCVsS4KARFuaSIUlvE3KSQ+cXoJmPtMFhUd0IXkvPKlFCg3b4uvyVjn8MS2eoFXb1B2loXQKfghxPLyP62ieJ3dxcRl1+nBf020R+uk6ugzv088iOcO0SIhXNtM5hfE3zudI5hDI5wzG/oB0hhA6XzCGgNEF5KFg2hy6cAFvK88MUioCWb6wHAb2zAvMQ8CLEw5gC21gNPgLBzAkKQBwGEkrAlm48P+z9+3BUZZp9tRuzc7W1qJbOlUSLgkJAYwwkYViZBgNKghDgaZQEVNBRQpEFrmIzDAoEi4CQcRhUATRwIgiioYoyjCi3IIkBAjBBHIjSadDLsMUMsO4ZaG7+vz+SJ8n53v77aRzI7C/96l6K7dOCOlOvtPnPOecVfq+7777zmoCycnJ0dscPXo0yATyH//xH/Ldd9/pbVJTU9vNBBIK+DUF9sICgwQAQ1XAeQCg0f8L9s8KAANOQDZ/wP3Lfb8370zR/b9+xP4N+DQ48BmxLxz4jIq3MZlPearLHjgyTdkQzrzj+i+AHIAKjmwBOMOFHiBuQ3GCbCq+XTYV3y4bihNkS8kQ2VIyRNJKhsqm4tv1JUDhhuIEWVd0lwJAgEiWAQEIACRYLmSGydwZM2VjvI8BEu8LAjCxRMrMIQNAZtdYHgcAtLGLJtPHWXn8Nfl7M5k6vp35Ofw9M1NmsnzmzwVmHN7zW1s43Lqjya8z+GOGl4EbAzpmhdcWDtfHC9/veDzgMbG+aJhnXYDv9xWnR2sGJbuEbRI9R+VABjYDoiEJszuYdwF5HxAgkF3BJguI32EzEqZRAIiYqE3EAm5sBAD+nmrhLI0g1igYEwC2gAFsLBLGmUDc2DKATzcAACAASURBVMYBwA6eb775RvLy8iQvL086deokL7/8suTl5Ynf7xeReqB2/fXXy86dO6WgoECSkpKsMTDx8fGSnZ0t2dnZ8vOf/9wTA/P3v/9dbrrpJklKSpKCggLZuXOnXHfdde0WA9OYDBxOHEwo4GfuADa6/2djAEn+jXzTCwDN6BfO/ePsv77pi4My/wD8cOGB9AvgB+mXjR/M/iHyhSvP4ESF/IvdNAYybPoAAAQ4Y6kXLwH0AAABBreVDvaAQdzeBgoBHpgdZEDBwI+lYHNXDWwg3s+gwXS4mrl1bIgwmTQOR8bnJx+dHJShB4BoSs/chGLKsWbOnum+NeVtM5LFFq3DrlqWz1lm53083tFjsM/3A17n+wxAjx8feD9ux8ww3+cmU8yfz/c5pGEwvCz7I+6G5WCWgvGkh0OiAQTZGMIZgXfvf9rTEsIB0bZYGIRDm5Ew7AZmGdgDANNS7QDwtdWtawRpQgJu7g5gkyDRAUA3NA4AdvAcOHDAarZ47LHHRKQhCLpLly7y05/+VBISEqSgoMDzNb7++mtJTk6Wzp07S+fOnSU5OdkaBH3HHXfIT3/6U+nSpYssXry4XYKgw5WAWwwElzTsAAYxgGstDmA2gGxskH+DACCCYA0AyPl/LP9y4DOMH7j4DDHy/u7cN1fBH46594dqMq4fYycrLprMRgFQMQuECz9fyNNKhkpayVDZUjJEASDet7X0Ntlaepu+j9lC3IaBxOozIz0gAOwf3heKDWQXqblHyIAQIIibTExgxe0mDMaWFIz1gDx8bvLRyR6HrZlZZ4YaMwA0QZ4tD9Fk8czGFXZFm80szI6au3zMuEKSxdsAeabEb8r7+DiDOgZ3uH/5McNPBjYUJ3geB8wW4/NYHgYgNME8A0BzJ5AbXTgbEGwg3MGJh6crC4hYGISqAwiaIBA9wf0tZhCYuhgAqiN464pgAPhGgwtYZeCmGkFeDhMAhmAA29wJ7ACgGxoHAN2ENW0hAbdY9mUWEAAwRAi0h/0LgECrBGwDgIHeX7R/YPcPEjCWyLnrlwOfh3z2Wxn0pwW68wf2D2zFqIOzVM7CjhODP7OWDLEkkCmnn0hWAGg6PwEKzJ2+LSVDFOBtKx0s20oHy/azg2Rr6W2yrXSwbCkZItvPDlJWEEAQnwPAyIACr5vuYgYCbCgBKGTjAkvHplmE42U4eoaBFwNFZtp4LxLg49Gcx4PkZQaKZhOGDbCFcjmbkSg2iRu3wX6k6dQ2sxpNeRc/S5ZywcKCiQWoYyDHgBAgDp9ngnycTcW3KyPMTxz4ccH/1obiBM++oBkVw+ypCbyR/8iGEDz+sQvLTGDi4em6D8jZgPhdAxNodgUDBEIGBgjs/UEDExhN/cBWAPjmqmAZ2NwD5EDoteEzgGYWYHuZQBwD6MYcBwDdhDWtaQLht1uVARgAgR4A2FgINFfAbSDwFziNAUDd/zPcv5B+QwHAX/x5vjoUwf6x85ddv2AA2fSBrD+0XnDY84zcJI9RgNk107yBs610sGwtvU22nx0k288O0rcBAPExvA8XfL4dAAAAA+RjBhgMBhio4HXeQTNBorkraDJILJOatzFZQVN+XfDVOJmUM8kDFNlAwwyfyeZx7IoJ8sxdRwaJoYAfs3v4/wIAs7HDZFLNXT2+nyHZA9Qxi8vMHeR+gDcG87h/cX8D5OFxwC/5iQE/EWD52ZYdyXuc2LfE4xsgkJtaUBPHIdFcF4dYGLDsWLfglpBBf1qg4I8BIECgtRs4FABMS60HgMwCciD0K6uDjCBhtYEwAxgiCqa5ALDRJ9wOALqhcQDQTVjT3B1Am8xrk4ebDQCXvKzPqIPkX2YAQ0XABAwgTTGA0e8uD6p+g/OX5V+ue+O+XwZ/kH3vOTBbmz6w58TsH4wfU44/ohIZ5/3NOfmQJweOYzzYuGGaPbaW3iY7zg70AMEdZwd6DphBsD8M/HacHegBgbxDaMqGAAUMCJgptDlKGSCB9WIQBWAEyZQdsWyUSD0zygP8AMoezXncE5bNrzcm8fKeHv+8bQDQ5oRmKZcbNUzJl4EhABTv8jGYZuaVZV3T3GMDf7z3ic9l4GeCQPMJAj9G8Pmbim/3fG/sKDZ3PU0JHgygCQDx+wBTCLOACE7H7xR+z7gneIiFBYzftVCdwKYbmPcAwQJGvW0AwM2pDQzgJgMENuYEtnUCryIjSBMMYGt2AK2ZgA4AuqFxANBNWNOSHcCmMgFbdFgCXtOwZxMkAWP/DzuAhvwbmeYNeuXwZxMA2np/bQAQkRQIfOYeUzQbMACExGWCP65A445fNEM0ZvjAhZ8v1gB56WUD9PWMsngFgullA2T72UH6cXyOjSFkkMB7haZcyGDQ5io2mUEGdbbKOgZ+vE9oMnQs3UI2BgBkgAeACDYVX4tlXJbZzSBkjljhKBYztsU8tkw+ZkRN0MyMH4Nsk5m1SfimjL+19DbPTh8eJ8z24okCAB8fBoXmfc1MMINArpFjBpbjeLjWj2Xg5KOTFQROyJrqkYFhCIEMzNmAQ4yKOMQzwbXPmYB9PvS6gbED2POd5cEA8I1V3jxABoCBPECtg7NkAWp+aRN1cG1tAnExMG5CjQOAbsKa1jCATWUBthgABiRgrYAzO4BtGYBgADcHA8Ce7wTiXwIXAnb/cvYfol9M+feXhvmD2T+Wfk32j2VfOCPRbmEGCAOUcGAz73nhAg/mDsAuvWyAZJTFS0ZZvOwq7y/bSgdLRlm87Dg7UHaV99ePA+zhbf4aABRgEQE2bNKgyURBqgQQNFkjlrLZWWqGGQNsrQ9kFrLMCuYNrB7ennzssaB6OgBE7j0GE8eMog38MQBkJ67NuGG6d82mFWb5mE0znbf4OQMEslTLAA/3n7nXySCOnyDgtngb9ze/bjLF6WUDPOwym0tYEmYmkPMBuTOa42HwO2BKwWADwQKaAJANIWwGQR837wECAAbtAVI3MEBgEACEESQUA/hq4wAwLAbQyAJszQ6gTYlxANANjwOAbsKalsbA2KSI1lbBWSXg35MLmB3A68kBTPKvjQFU9g8AkORfsH8c/WLm/mEJ/e79TyvzB/cvdpfY+MFtHzB9sPGDA47hcOXAZwYLDAqYucsoi1dmj4HervL+squ8v34cL8EGMvDD5zGjyLIgS8sAF+b+IAAMjCkmO8gmCFumHX+M8+dME4XZb7usYIxMOzHRmj2I183IFfN7wffBUTcAr2YwthnMbIYz47bm3hyDY9PRC9mWAR+zfDbGjkEdf5zBH+5fvM73N5hhPGnA18soiw+6f23RQfi/MDBndpYbUMyKPhhC4AqGDMws4L2ZM3StAsHQMIRwJiBC2VkGBgDEHiCMXmYcjHUHkPcAN1AcTBgSsILAJiTgoB3AVjqAHQPoJtQ4AOgmrGkJA2j7A9Qq9i8MAOgxgLxK7J8pARsMIPK/FAAGDCAIjmUDCJs/sPuH/aNffvZbT+MHcv9Y/gXzBxAI2dfsqGWzAsuVLP2aQc/M0u04O1B2l/eT3eX99MK+q7y/vr2nPE7fZnAIiRiAEB9LLxvgkYfZIGACEIA8U4Y0Y0TAHjE7xiYI832mhGxmIJptJCtOj5bpJ5I9QA8gxOy0xcfNHmSANIAzc6+RAaxN5uUGFT7cx4z/F+/WAfhtKE7wMH4M+kwWDzIuS/nM6DH4A6DDEwTc97vL++mTBzxZwO3wOrOD+J7YSYwnJ8yMsnsaphxuYQELyAAQ6xFYleBsQLCAcAWbDSHMAg7c/WxQHiAyAREHAzewFQBuSW3YA2zCCKIsoJEFqBIws4AWBjDIBdxGETCOAXRjjgOAbsKalrqAmyMHh3UWBwPAIPbvFdr/W2/f/7MBQG7/QAQM9v8g/7L7d/Ce3ykARNcvDCBgJgD+xmQ+pY5fSFoIfOa9P+6inXPyoSCjAoAGgw/O9OMLPi7YAHq4eO8u7yd7K/rK7vJ+sq+ij+wpj9MDtocv9LvL+wUBCv53IAvadsXwOQCCLFHDTJBWMtQD8rBHxntwZvYgJGAGWWwmYcAHBpANJhyhA9aPK85YxjSbMpgRNMGcCRw5v8/M7mM3L14CSAHYs8TO0jszfeauJ9g7ADve78TruL2NBeYnDXhygMcNPy6YFebvk+Np+OfD7CvXxIHlxh4gAtAhA5vGEOwBggVkAMjtIGY9HEKhTQBotoLACBIEAE0G0NYJzIHQNgBoi4JJDc0AtgQANvq31wFANzQOALoJa1pjAgnnj1RToM8EgJoByDuAf/BWwFk7gAEAtzQOAKOp/9fc/4vftVCZhcF7fqfMX8IXz6gEzK0fvP+HhXa+uCHyhQ+bPyCdYa+N2ziYfWEACEYHDN+e8jgFfnvK42RfRR854Iv1vI8v8ACOGWXxsreir7JBzBThgHHEniC+B5MZNDPleCfNjDIx2U1TIuUAYmYPzaaMNYUjZObJhz3MHu/8mbt5DNqY8eOPmWyemX/I948Z1GzuQAL0sZOapVWWevEzBXgDYNtaepuHsQWY213ez3NfsdkHgNAEePw4wNvMEjNgxP1sxgZtLb0tSMJmiZwd1mZfMJhw7ANOPvaYgj+YphANAxZw9KGZMmL/HLnnwGyPIcR0AzMAZCk4SAa2AcDNTTCArxkSsMkAhgJ/K40omDaIgbH9rXUMoBvbOADoJqxpLQMY7rPWJkEgS8BGCLStBSQoAiYEAIT8i+y/GAKAfdMXS1xGSlD2HxhAGEAAALGYbqt9wz4TzB/MADL7x12yMCUsyr/PIxsiCoR3vJjJwcUbgA/ngC9WQR9emiwgg0KwhQwCwBCZUiKAorlPaLKDzGrxbiBkUAAlzrWztVyYuYK8GwhmcEZukgcggh1cWzhclhSMDQqyxo6f+TXBYjGYZKmTWUEGeWaPbqh2DYBB081rsn34eZrsHYM5sHf8eMDHcFu+T3HfA/SZjwe8jscFrwYwO8x7iiwFs1uaA6IR3s2GEGYB2RTCZhB2A3M7CBtChlhkYG4FgRuYncCcBxjEAHIW4KZVulrSWCewtoGwCzhUH7DFBNJcAGjbt3YMoJtQ4wCgm7CmNV3A5rNQ2zPTZknARgyMVQLmGjijAs4qAW+j3b9A/2+o+Bfe/xu853cK/nDhYQYQrR9c+8bgDwAQzl+EPiOrDjEnLG9CJrXt/JluX4C/vRV9JdMXowAQr++t6OthBQEaAfoYIPLX5r1BBoUMANlcwOwVA1YwiOaOIEugvCvI/cRbSoYE1aCZ0u2G4gSZc/IhD2vHu4UMqPlrmE0n7PQ19/pY7uTPNxsz+P9nOqVxX/LPiVlSBtQM8Pi+wP0NEIf7wmR0cRsAfRx+goDHxr6KPpLpiwkChcwaMhuM+5r/f3yfcKg35zKaMjA3hEAO5mxAMxIGwdAAgAwCuRoOABAyMJzAZi9w9LshdgAbcwKvDwaAzAJqG8iqRiTgNnIB20x4DgC6MccBQDdhTVvHwDS7Ao4ZwHAAIDuAX7cAwD+utALAGAKApgGE3b/M/pm9v8wAMgDExYv7fiFzcegzM3+8r7asYIwCDZYHwfxB0jMv+riQA/gd8MVKdmWUvn7EFy0HfLF64d9d3k9fB1sIcAjWCKABwA8H/64ZPWNjBPE6S4ccQs05g6FAE9g5gEMzOBkAEIwct5GAQeRdPt71AyA0Xbu23mV8fbBeDPQYvOL/Z7J9HLRsBnMDKLNZw5Ro+bCcazK5O84O9DDDuA3uYzxR2FMep08SAAIzfTH62OB/G8CPzSG8C4gYG3Zvc1MIMi5NQ4gpBTMIZDcwg0A2g5huYBhB0AxixsF4WEATAP5xpVcC3rQqeAeQAGDQHiC7gA0G0NMF3EoGsClA6ACgGx4HAN2ENS3tAm5MDm4TF3AoBzCzf8wABti/oB1ABoABNgDsH3YAOfwZ0S8s/3L8C+/+ockA4A/mj0k5k5T5Y+kXeX8AgJAXkX+HzDjsXvHul0323VvRV474ovVkV0Z5gB/ejws9GEBTMjZ3BfdV9PGwf8wq4X0cOo2XJlgI1TTB4dK217FrxnIxAz8Ar7l545U1ZWmXdwsBUiADM2jjAGvu5cXn2HYYzbgW/hhLvLwracay8D4n7+Ex0GbGD/cX7j/cRwzyzPfh9UxfjOyt6Othhxn87avoI0d80QoEWTJmphHfP0AtG1pwOM8RuY0L8xO18xoAEGf6iWTPPiA3g6AWjg9+D1kG/sWf53v2AMHosxEEeYCNAsBQDGCYUTA2AOjZAVzeNkHQIZMYHAB0Q+MAoJuwprkmkMYk3rbIAQwygPw+uAM4VANI5ObQDCDaP8AAAgCCAbz1k+e0+cMMfwb7wLt/HPyM3L/ko5M9zB/2/9j4gbBiuH7BnJj9rabrk0EBS3gMADN9MZJdGaVgkN8PIHCsMlIBAdhAlgXNfTFmBRkYcLwMN5EAGCJXDnInQBHLpWY9nRkuzS0ZbB6B63j+qfs9bluWfJnF455cMI8MLvFz558/g1LzfRzCzI5eZvxY4sXbbNLg/T02ZPDPm4Edy/pg83CfHPDFelhBfnzgfmY2+FhlpH6Mb8MMoCk1M4DFz4L3Ic1waAaBbAYBEEQ+JhhAdgPDCML9wJwLyHEwcAMP+LSeBbz1k+c8tXAwgiABwNwBjHprZcMeYCgAaErANgYwxA5gr5WtZwAb7QB2DKAbyzgA6CasaQ4AtP7haQIUhi0FGwAwek3DH1orA7jBcAAH2L9GJeBAADTMHzCAoP0D8i/AH4rosYME5m/0oZme2rek7Cm604QDlgMXPci/vPvHO2sANywNAmTZWB0cAL1jlZH6kkEg3mbplz8OELCnPE6O+KJld3k/BRcsGQOYNLYXaMrEpgzMLRZmpAxAlCkzApTZdu7mn7rfw77xfiGbSgAq2WHNe3hgKG0VarZGFK7TM4Ob8bXYRAEHtU1CN5lWZv1MoA7G17b3aa4E8BMAHDxGcN/j8cFPHpgl5L1C3N9mUDS7tiGjc1g3HMHzTj2oZiiuibMBQDMShkEgh0LjJRhAdgOzEcTsBQ5iALEHCABoysCv2SXgoD1AixO4PV3Anr/HDgC6oXEA0E1Y05IYGBMEms9Sm70HCAYQz6htPcChGEDDABL1lhcAIgAa5g+0fzAAZPPHkEDnL3L/Er54Jij7b9yXTwYBQOz+ceUb6t7g/OUqMwZ/cKcygGBHJ4AAS3e4cOdW9pDsyijPy2OVkZJb2UPfh9se8MXq+8AeMjA02SCATJaKGYia4AB7Y9wyYYYaAzywY5glU3acAhDbMvTSSobKovz7PHIsy7Pmfh5/zGzWwL+9pWSIxwFt7urx5/D/w9znM3uamSk1zTYAexzVgp877hfz8McA3gAKARBNAHisMlKZv3x/N8/78EQgt7KHh1nGkwAG/MxoshkETCBnMnIu4IKvxumTIbCAHA2D1Qm46eGwNyNhWAbmUGgGgdgDBABEGHSMRQKOemtl8B4gZwFiB9DiBIYMrCaQUH3AbgfQzRUeBwDdhDWtqYIzZeEWy8FgAF8mBvDlwDNtCwDUCrgwASCHP8fuWBq0/2fGv4D9Y+fvPQdme2JfOPwZu3+Tjz2mwc9g/3Dxwz4UmioAAiFXApiw4xfgChIfwBou0AB8AH35/m76NsAhs4J8e7wNAMHMEcuD+LfwPt47Y/Biax4xHcNmYwWy7my3MZk1NoqASQQDyCCPd/NM4AeG0QSAzFay6zpUTR6zmPw5ZjYfXjdNHGzsAKBGeLdp1AHYB/gz2Vub8QefwwwwHg/HKiMlz99dHwP8+GBpmCVnfF8A9bjfmBXFz5qf1EAG5naQeaceVEOICQJhokIeYOLh6ZJ4eLo+8UJH8N37n9aGnl/t/Y3KwAB/HAeDJ32QgU0GUCVgmxGksSgY3gNsKgh6RdvEwIT6u+sAoBtzHAB0E9Y01wQSaj+lNQ0gHgDINXC2DEATAG7yGkCCACDJv7gQ2No/wADC+AHwhwV0AMAHjkzTg8o3uH4h/U4/kaxMx6L8+zzSL/fRcrwIduJ4jw7snyn34nUwOLmVPaSoKkLy/N0lz99dTvu7Sm5lD8n3d5N8fze94OPij8/B6yZTxOwgs0EABwArAAkANRwszVlyDI4AnBgocci0yTCZrwMoAwCaJhLErpgyL+cTclQNmzJM5o73Gjlw2Qzm5pBtBrfcuIGflRnHA6DHhg3e22S2F+9nQA4wyGxtpi9G71/z/sYTAH5M4IkD7ns8cWCpGfK/DRxz7qFZFQcJGCYoNOHAHIUnTMgF5ExA7AIyEzhi/xz9/YQEDCcwXMAMACEBAwD2em+Z1N5AAHDritBOYI6CYQAYeGLKWYCNmkAaYwCb0QbS6C6gA4BuaBwAdBPWtEYCbooFbLYEvOal0CHQ6439v40vNvyhpggYDwC8oQEAIvwZEnC/QH8o9v9gAOH9P7QQ4MLDABC7SpB/wWLA+IEL3fxT9+tFkMOG4VjlOA1uguBdMPNCz9IdAB6f0qoukufvrh8D8MuujJLT/q5SVBXh+RgAAsAAM0rMDDHIYOMIh0qzW9mUPQGQON4mvWyAgjtm38DysfGAgdyWkiGy4KtxHkcv2CgARP66YKxMUIrgZf6+zLo1AD4T+PHeI0vfzPgx82cyffj5AWzhdf6ZmywePw5MFteU//H6aX9XyfN3l6KqCH2dnzTgsXDa31UfD7x7CPbZlPpNZzckem5WST0zSlcfkAmIfcA5Jx/SJ0z4/ZmUM0mSj072PNGy5QKaeYCQgGHo6hcAgZ5auEAjiAcAQgLmQOjmOIGb2AFkCTioC9i5gN200zgA6CasaUkOoEd6CLED2GwwaGMAUQPXmAEEETBpFgbwhuv0WT+koN4fLNHqt36B/T/TAALzBwAgGEDO/YP0y7t/YDMA/Dj42WT/uP1ibeFwD/gAkIAEZxo9AAoA+PL93RS8AQDm+7vJaX9XOe3vqkwgbgMQCKYQ8iCDBlNKBAjdV9EnyFQC+ZfZwAO+WA8AZBMEs31cY4bmEY6R4TgVNolsPztI5p+63/M+lnmZPQTg4/1KbrxgQGPu7nHThs28wSwfN3SYGX6cx8fmDjbigAHE/cDA3AR3DADxNj6HnwwA9PNjgQEhHj/MFoMR5B1EMy8S/08OhwYQZwDI+4CQgk0mcEZukpqowALiSZYpBXMrCCRgcw8QLKC5Bxi7Y2m9BHyDtynI4wR+k3YATQbw1dBOYAaAMbY6OGYAl61pAIDN7AMOBQYdAHTD4wCgm7CmtTuALWb+WP4NAMCevzcYQDiA173krYAzMwDfXKUO4FAA0Fb/BgYQ3b9DSP69c99c3f8D+wAGEOYPgL9JOZM8oc8c/cKxL3BHcq0Y2BMGHwBQvNjPF32AAL5oA9CVVnXxXOhxkWcgyCygyRKakjEbS5gZYkkawIDDpQEIGUCFChdmsGUycABcppt4W+lgWZif6AGIHCptSsjM8DGgYweuWb3GzJ4tsoUBpOniZUbUDGNmpy3LvfgZM/gz2V0THALMmfuguL/BBuM+xznt7yplVV30yQIDQ94R5NxAbpQxXd5cgWf2K9ukYK6IAxOIZhCAQLMfGG5gZgDv+HyeZgECBOJ32xYIHcQAAgCyDEwuYE8UTCgAGIoBbGQHMFzwF6664gCgGx4HAN2ENS3dAWxV5l9TDGA4IdDY/wMDCAC4dUUwAHy/Afz1+XCJsn/Y/2MACPcvd/4ij4ylX2b/AP5m5CbpRQ0XOQDAZQVj1PnLdWYALWz+MHPcTEcvMzXM7pRVdZGiqggpDbzE2wz28D4GBHn+7goyGQAAWLBUzICQdwXZEMKAh6vMABwguwI48s4ds4Js0DANGTvODpQVp0d7nNNsKDGdudg1ZDDKe4ucewdAZwvE5t5dvh1YMm7y4Ew9NtQw82dKuuZ+JsAbfu5FVREeNhD3KR4XeEyU0v1cWtXF81jA2/w+PIZYGjbjYnA/8/3GhhqAcO5f5p7mJQVj9XeCzSCQgJELmHx0srLsAIEsA8MIkvDFM8oADt7zO62G41o4sIDYAwzaAXw7sAP4x5XeTmBiAU0jSGNh0L2YAWykCs7FwLhpz3EA0E1Y0xIGMJTk2+ocQAsA7Lm2EQMIS8BNAED0/wIAYmGcA6AR/MzZf5B+AQDHZz2hJfbc+gHjh9n5u6xgjGajseuXM+0AADkEmI0fJggDu8PAzneuAfzh8EUety8LMIQmKMDHAQQYBAKA8I4gO0fZMMLGEbPZwtZjy+wafwzsID6HjSS4zeozIz2MIRg+duPy7QGueVeR2zMABDlc2azDY7kXt+V8Rnwut2pw+LJp7sB9i5c2Jg6sLh8AQbB8eFzgtmX0sqgqQvznuoj/XMNjAo8ZPA7438ATDJaYIf/j54L7FD9307GN3VawgCtOj1YnPPYBmQUECHw053GthjMNIWDhUQ2HmKZfUi8wh0KjFxh7gAiCb1IC3mSRgbEDaAOAgeQCTx9wG8bAhNq7dhKwm1DjAKCbsKYlQdCNxcG0hgHUP6gvN7iATQYwyAFMBhAbAEQDSO8P6hnAvumL1QDC7l+OfwH4G3VwlozJfEq7SRH9ggsU9pYQ/wLwN+/Ug7Io/z5ZlH+fpxkB+3/olOV2CQAVZs/Y8cuADKAAgK60qov4Ahd437mG16vPNVzcAfR8gfcxGACg8J3r4gEXDDQZlDD4M4ENgAJemvl2too50zyypzxOtp8d5DGTYN+MP3f1mZGeuBywfTZTBiRe3JZNLKZsbft+ARwZQJpGHezw4b7jGjd277LBhs0XR3zRHkMGS/u4X/g+A/jD/Yb7GXugkHcB8vx03+Pz8PXK6OvgCYEp/3PmoI29hfHG3AU020EYAAIETj+R7KmGgxnEBgARCYOe7l8avcADPn3W4wY2A6EZAPZ8Z7lEbSUQyAyg2QZiOIE9O8vYAwwHALIM3FLGz1RkHAB0Q+MAoJuwprUMYKuAn20H0DSAAADaW7QvwwAAIABJREFU9v8AAKkFpOc7y4MYQOz/YR8IErDZ/4ulcu795YsO5ChIwIh+YfDHoc/I/GPnL/poOZZkU/HtylyZHb8AWgAJJlMHwIcL+IXqrnK+OkKqz3WRuuoIqauO8ACAagMk4qKPr1VKDBHkQIAKjpJh93F2ZZQ1rgY7gXiZXRnl2YtLLxvgAVYAFgB9AF7sKGYwtqZwhGcfD7fhlhIGdWys4UxDZrZCOZz5/8HAzuzVZYDH+5Km2YblXgBugGswuQCAuF9se3wAhQB6uD0/CcDr56sj9HFSbTxu/IHHCz6fo2FY8sf/yeyF5vxGru/jXUCAPxyAv7l5463dwJNyJmk/MNzAiINBODt2dhHizmYQSMBmHIwCwBssADDUHmAoCfjlEADQFgWDNpA2koA9f48dAHRD4wCgm7CmLU0grY2BgQlEe4D/QCYQMwLGBIABBtDT9XnDdRoAzf2/yP/D4vjgPb9T8MfuX+z/IYeM9/8g/U45/ogaPwAC4XYE4wHgh9w/ZKYBAKaVDJX0sgEKJng3DIABjE+Zweb5AhdunwHscEGvJqBXHTh4v88AgGCWwCCxVMwmEjaPsFRo1tFxZAw3WIBdM2NGcAACwQByBAmk1l3l/WX1mZEKBs2AZWYGeW+N8/hgXGEHLsC32ZHM3x8+H5/D/zcAX87sYxBlc/QyUwdQBzAHpo5BPCRdBvW4He5nBna43/nJwfnqCP0YGMHqwGOBHxOcG8gML/8cWXLH45mr+/D4N1lADocGC4hdQJaCbXEwAIAAgWABf/Hn+TLg02eDomDYCBIEAN9a2WAECdUJbDqBWwgAWxsD4wCgm3DGAUA3YU1bNIG0avePJeC1IQCgTf7l/b9AA0jUWxYJmPp/mQG09f+a7l+wf6h+4+gXNH9MOzFRwZ/J/nH0C5y/CH1mBnBb6WCPecJs7TDlWEh2AAW4iF+o7uoBeLjI++hCXxd43/nqCGWE8LV4b9DcLWRQwM5Rm2OY3ah7yuPU8MDtFVxth/83myl4vw7mCt7bO+CLlTWFIzxyrOnG5fo6BmsMStnRbIYp80sORmaQx6xfbmUP/dpmVh8HMjOo4j09NvHwjqafAB0DdwZ8PgJypVXeJwB4LFys6eYBgD7jscKPB3MvFJIwDgAv727CFQwpmPcAEQwNMwgAIOKSsAsIJhAAMPnoZGXd8XsICRhu4F9+9lurDGxzAsfuWCp1jUnAm40oGAsD2BQADBkG3UwJuLHMVfPvrwOAbngcAHQT1rQ0CLrNXMDMAK5tRAJ+bbU3A5AdwAwA316hz/DrbrjOY/7AxQDmDwaAyP7j/T8TAE7ImqoXJvT9cu8vjB+IvAD4A/Dj2Be4V7GvBjnSVttlLuqbEt+F6q56ca+rjpBva6PEf66LfFMTKRdruikIKKuqv+DjdgwWT/u7Sl11w04h2EYADxx2keL74ZgSZo0AutgxzGwfGLM95XEeIwnHpOB2AHScqbe2cLj+3GC6YJcvM3W8+2fK7LyfByDLES18Ow5fZsMLO2X5bRxIqpB1mUktNQA3GFyAQ5Zrq+nj1eeCQSEAfx3dx3h8gAGsq46QC9Vd9TZ4P54wgFFmydlsjsF9BPCNFQY8rrHfygwgA0AcgED0A3MgNMxWyUcnKxPIAJBl4CEEAAfv+Z3uAdqcwHXMAG5bXm8EQSNIqDDoxiRgSxagNQzalgPYFn9DHQPoxhgHAN2ENS2JgWmzLEBzBzAAAINaQF6xhECHiICJeruBAawLMICQfyEHmfVvQyj8mevfRh+aKYmHp3vaP8D+QapC8wfYP659g+EDoc8bihPUKWn20LJ71Ax5BhgDu8OsTh2dizXd5GJNN/mmJlIuVHeVSzXd5ZuaSL24M9PDDKHJEgIsmnuD7CxlKRqMoQkGj1VGeuJs+CXvzbE5AgCLdwoB4Nixm+mLkXVFdymYM3f62PELFnB3eT9P8DK3awBoYj+PP86349uauYz8f2B2FHt+HM3C2XylBLTxM2ejBjt4Aepw+/MBAGcCQzwmGPBdqumu7wPow2MGHzdXCphxRpg47iP87CG3w6gDIIj9VjMSBjLwkoKx6gyGeQpPqlCvyGYQhEJzKwiq4dAJjF5gdgL3D7iBrTuA25YrC2hlAAOKgzYRGSAwyAgSjgTcBiYQBwDdNDYOALoJa1oDANvMCGJjANeSC5gjYFgGfnOVpwFEAaDBACL8Gaf/x8979v+GkPzL+39g/yZkTdXwZ7P3F9l/2P3DhQ3sH8AfGEDOp+MqMYAYzuPjTDeTiTNlPVzIcTH/piZSLtV09zA/eJ1fXqzppuARwJC/fjUBQwZ+HCRsxsfge+eaMkShmLtxAFVm0DFYQtyOmTsAsA3FCfo27/Px25CSuWrNrLljAMegDd+H2ZnMmX34HNtuH34G7OY1s/f4vq22gLcL1V09H+OPM8sHdhCfd6mmu97vl2q6y6Wa7vJtbZQ+NgD4+DFysaabZz3A3EGEEQkAkHc22dXNcnBayVD9HcATohWnR+uKBINANISABWQA+GjO42rCYiMIA0BTBg5VCccMYPS7BAB5B5CdwK9THZwRBh0OA9hoE0hrgZ/bAXRjGQcA3YQ1rdkBbBcAaPYAh4qAMTIAIf/2fGe5BwCyAxgF8WwAGRLYH+L6NzQOoPoNFx7Iv2AAufcX0S+QtlLPjNK+X1S+cTctt07A/Ys9MgBAjnphFojB34XqrnqhB+gD83e5Nlrfh9vhgv9tbZRKxGCJcDswQNgrZMMAQAabDzhDzowtAaPJL0MFHjPw4n28PH93jxMXQC6tZKiHYWQDjdm+gX093lcEuwfwiRgWBnMsyXMwMps6GLyyXMognuN2cNh8wUwfS/Rg99jEwfcZ3of7FwDwm5pIz5OAb2uj9PHwQ12s57ECcAhgaD4GTMaXATGzoVhn4FxGyMCoPMQBE7ji9GiPIxjh0HADwxHMkTAwZaGiEU5g7gYe9KcFcusnz2kUDDuBG5WAkQf4hjcPsMk2kMZiYNrRBewYQDe2cQDQTVjTkh3ANt0FbEQC9mQANuEABgA0GUC4gG/emaL7QGj/QAD0LwMVcAlfPONx/2LnCEvo3PsLBhAxFtj9W1IwVvedEPzMoc8cVsy5d7iIcswK5/wx2wMwwBf5y7XR8n1tjL6Oj31bGyXf1kYpKGRgiI8xKwjAAKCBt20uYjBXzGaZBhFm2hjYmd3G2JFj1pBlWP48fM6m4ttlX0WfINexGbhs5u6xU5mzFZmJZGDItwFAxP3E+30cl8N1fGzgwc+Id/bMnUzcD6ZMyxIus3bY+eT7DoDucm2050kB7nN+XPATBjwRwH3OKwDsUmZnMJhAjuNBteHW0tv0d2Bd0V3aD4yKOLCBpgyMeCXsASIYmvcAwQJyIDR2AcEAQgZGHqCVAdxGRpDNRifwxhe9eYABABhkBCEGsFcjALAtm0D4b7ADgG54HAB0E9a0JAi6qWejrQaAaw0AaO7/gf17oyEDMGprPfsXygQCAHjLR4s89W9wELIBBAwDhz9z8DNCa7nLlNk/dP5y3++WkiGePlp2qiIWBUAJ7B+MAHXE8IDt4Z2/72tj5PvaGL3A4yUAIV7WGcwQAwQGDZCFmW3irDgAFQ4ShpmBGcF8fzcFaCyJcruEKcMyswbGjj+PjRqbim/3OFN5Lw8vAfw4qsZk+QBq8DobWriCzTS6AKgD8AEYFVXV/4w4lJlNHBzVArm1lF7HfV1NoI6ZOhh7+P247YXqrgrsvq+NkW9ro+SHuli5XButL7+vjZHLtdF6wA4yMMT34Cegyuwls6bY2Tzgiw1qd8HKAxzBDAJTz4xSRzDHwsAMgl1AyMBwBHM3MIwgYAB/tfc3KgEP3O0NhL55Z0qQCUQB4NsGA2juATIAtBlBQjGARh2c2wF0cyXGAUA3YU1LJeBWxb+Y4A8A8A/EAIbKADQBYFoDA4iF7lA7gMwAQgIG+MP+3937n/Z0/8L8gf0/MIAzTz6sjAWiX7jxA+5fZP6hq5bbKticwOyfKf2WVXmdnJDqLtZ00ws3pD1c1H+oi1VgaF7k8RK3Z5mQdwMBBhkE8l4g3sc5ddxIUVrVRVk1MzbGrD9jEAVgAUnWlF/xNTYUJ1hNGGYkDbOPtg5lgFf+PlnGZkaWdx1xOwZGAMNmvA5kc85oZJbVNGswSGfmjkE77v9vaiIV3ON+w/3OoO+HulgPGMRjAYc/H8ASTzYg93M8DO5H3FfY00RFHPqXEQmDg2BoVMQtKxgjywrGqCOYO4KnHH9EO4KZBcQTNHYCww0MGRgAkJ3AfT5sYADrbrhOore/oE8ctRP4zVXBlXA2J/AfvFEwLdoBXNzKv6EOALqxjAOAV/lERUVJp06dgs5//dd/iYjIsGHDgj42YcIEz9e4ePGiTJw4Ua677jq57rrrZOLEifK3v/2tWd9Hc00gTQVCNwsU2lzAL1scwK9aDCCmBBwwgES/u9zzB77Phw0AsL9RAYf2D87/g/OX3b+48ID9m3nyYZmRm6S7f+j8ZeYPzkcswsP9y+CPI1GyK6OsWX+23S+AAb7IN3bADl6q6R70/h/qYpVZAlAACDhPgISdoyxHgwlEhIkZJwNgx0CPpVezAxcAjPfozOYMmBG2lAzx7OAxg8q3x/syfTFBQdbcfAKzBkvazHZxQDazgWagdikBd47qCWXgYMbV3MkD+ANAY9YO54e6WDlfHaH3J54M8H1sAkHzJV7HCsHl2mjPKgAALHYW+X5F7iG3uSCyh3cBuSMYO4HIBwQTiFxA5AEyE4h9QA6FZicwDpzALAH3+/h5zQL1AECYQNAJDCNIWmpwFExjRhC4gMMEgG3JADoJ2I05DgBe5fPXv/5V6urq9Hz++efSqVMnOXDggIjUA8CpU6d6bvP3v//d8zV+/etfS//+/SUrK0uysrKkf//+Mnbs2GZ9H82VgJvqAG4pAOy99GWJWucFgGoCWW8BgG8YAPDtFdJz23KJftfLALL8CwDI7l9T/kX92wNHpsn4rCc0g8wEgHNOPiRz88Zr/Mui/Pu06xeRFyz/IhYDF0bs/iErD3twkA99xPyB7WFWiAGbeSG3AUAAPdvHvq2NkrrqCA8rxGwTZEeTrTKdwwxazZ0xsGLM4vFeHW7LxhDUorHLFqAjt7KHbCkZYt3jYwDJgDC7MsrD4tn6bzmuhYOZAQyZ3QRo5Uo17mbG67zbh50/BvUA2za2zwb+cPj+ZEaXnxQ09rgI9VjB5/AuIr5f/n/hZ2D2QfNO4Pazg/QwCIQZZE3hCI8beMFX42TeqQc1FBqxMFOOP6IyMAdCI7IJodBwA8MIAgmYWcAgBnCbBQCyE5gZwPVNhEGHUwXHANAxgG7aYRwAvMZm9uzZ0qtXL/nxxx9FpB4Azp49O+TtCwsLpVOnTnL06FF9X3Z2tnTq1EmKi4vD/ndb2gUc6ploOO8LxQB6ACBHwLxqMYCEcAD33OZlAPGsPy4jRWMhzP5frn8bdXCWykto/sDLycce81yY2PwBKYuz/9CIAPAHRoQbLWBy4F00ACjsemExH8CApb3mXNhDvc2SMcuBABVgG9lMwiYFZgMhb7JBBAyb71wXj5zKfbYMsFj25f083rvL83eXDcUJCggBFLm1AoASQC27MsoTYs3ByZxxyPEs3LHLzCwALr4OGD3uZOa9P4A8Zvtsbl38nPGzDgXYec8TrF9zwZ7tgD0Ea4ydQs6PNNtC8v3dVAbmerg95XFBABDsH+8DcjYg4mDwJAv7tpOPPSaTciZ5jCDmHuDd+59WAIhe4PhdCyV+10J1ApsAMGb7CxL9bsAEgixAdgIzADSdwGsJBNoYwFUGAHQ7gG6u0DgAeA3Nd999JzfeeKMsX75c3zds2DD52c9+JjfeeKPccsst8swzz8g//vEP/XhaWppcf/31QV/r+uuvl82bN4f8ty5fviyXLl3Sc+7cuWa5gE1Q1yZ7gIstAPAPjQBAWwRMwARiSsAMALEPhPaPIUb8C9y/4758Unf/0P07+dhjyv5h/w/sHzLNwPytLRwuaSVDJa1kqJo/dpwdqD213I0LJyyzSQBSbPpgVoglvrY+AIGmvAxAYLpKTRDI+YF+AyRBKuaIFDB/fFuWWc0eYgaM20oHe1y3HKED4MfAkp3KqLfjwGsGeAhdBtCDqYN3H/E1uU6NMxTB+LGZg2V1NuIw8ObdTRPU8X1iAsC2fiywaxy7ob5zXnYT4JwNIdgHxBMeAEA8IQIA5HxAbgnBLiD2ACEBI4aJa+EQB4P9XRhBIAOzG7gxBtCTBRgCACoL+Mrq4CgY7ACuMpzAKwkE2iTgFjCA1ifaDgC6oXEA8Bqa999/X/75n/9Zampq9H2bNm2Szz//XAoKCmT79u3Ss2dPGTFihH58+fLl0rt376Cv1bt3b1mxYkXIfyslJcW6e9icIOgWS76hwJ8FAKoBhF3AjTCAkH+jt78QtAMICRgXAjP/D+wB2L/Ew9M1+oXZvxm5STLz5MMa/Dz/1P0y/9T9sij/Po19QdwFqrCYAUFvLbLp2A3LrBPLhLzUH+7OX0uBn00KNA0luB2DUQY+2HcDiGW2qPpcQ0QM181x9y3AIFg9rqbjXtrT/q6y/ewgBXhs3AAwMx3Kef7uHtMKN6DA5MCNKOyALTNAIDOI/H+ups8zA53NSjYAewA7vB4uc8u3b4/HhblvCBmbJX7e2eSmFLS8wBGMPUDUxKEScX3RMM8eIAAgHPbYAQQIBCNvysAMAJEHCCcwWkFu3pkS2AHsHMQAegAg2kCQBRiIgvEwgDCCmHVwLxqdwKleABgkATsG0E07jAOA19CMHDmyyd29EydOSKdOnSQ3N1dE6gFgnz59gm4XGxsrK1euDPl1WsoAtkn1W2sZwNfpcAvI1vr9v57blkuMAQDB/t3y0SLtAGb5Fwwgd/8y+MPyOe//IfvPjH2B8xfyL6RfOCKx+8f7UmBPuBIMDBocv7jo835XewHBpkAi7xxChuQdMWa46qq9NWcADSbTZuu8BZjjnEHeJSyr6iLbSgcHSbSQmtlVzCAU0Tpm/h6DQgZ+uB3LvgCMeJt7dXF7lu/ZvW1m8DGgbomEywC9Pe5vsJBwGsOognDw0sBeJ/YsuY0Fe4C8Cwgz1NbS27QmDmYQ/C4tzE9UAAizFZzAcAOzDDzq4Cx18d+5b64CwCGf/VYGfFrPAEIGNk0gvd5b5skCVABoiYJRAPhKEyaQFykKpp1NIK4JxI1tHAC8RqayslL+6Z/+ST766KNGb/fjjz/KT37yE3nvvfdEpOUSsDktcQG3VKZoEgC+sroeALIBBC0gzP6FCIGOfjcYAKL+rd/Hz+s+EPL/2AE86uAsGZP5lLp/0fzBABB7SdhTgvy74vRoXWjn1g9EvnAuGgNAGBO479eMBzGX+jvq2JgoSJZgtgAMuFECESicfcfxNlw1x65iBozMEDKg213eT6VcWyC1mbsHgMe7inw45gb3Q7UB6LDfx60bYGmxK2eyfuzsBfAzgfzVcB+HAphsRGHQDDCN/UvIwWABsQ+IthtUIIIF5Jo4BoEL8xNlzsmHVAYG8456ODxBQxwM9gBttXADPn1WQSCMIMwA9npvmcQgCmYrGUHAApITOOq11dYw6OYAwKAmEGcCcdMO4wDgNTIpKSnSpUsX+Z//+Z9Gb1dQUCCdOnWSQ4cOiUiDCSQnJ0dvc/To0XYzgQDUtRnzZ54AALS2gJgAEDldWxoiYLD/F4oBRPzLgE+f1fYPjn8BAMT+H6RfdP9OOzFRZuQmafYfR7/A/Yu+XzCAuOAB/KGfliNK4KJktyhYo6sVFNgAAu+0Yd+N9wIBpPwE7nwGCOPdQa5LA1jk3b3qc10koyxeAWYZgb7zxtsM+vBvVhsvwWZxBRvuB97xMx28ZlMH9/AC9HEoM+9X2iTfxkB3R97HnD2I/ycAPWR57HViFxAOdwaALAfjMABkIwjq4RAODQZwUs4k7ecGCEQtHFpBAAJZAoYbmP8+xO5YquqBMoAhAKAZBm1tA3kxuA2kUQawDQCgi4FxY44DgNfA/PDDDxIZGSnz58/3vL+srEyWLFkix48fF5/PJ7t375abb75Z/vM//1P+93//V2/361//WuLj4yU7O1uys7Pl5z//+RWPgWm1HNwSBpDkXwWAgR3AXu8toz/wnT3sHwAg9v9+tfc3Kh1B/sVuEZs/uPoNF6dF+fdpgC32/9YWDtfdJshcAIC7y/tpUC46fzmMmKVEBg8su16NhyVCdinjbf+5hpw7sGhovuAuWwArSI1mUwZXp4EpBQPIoLHauI3ZX2z2HPO+JYAos3bcu4vMPnxPNicvXuJnwm5dW0h3R99/zTmcJwnADuDMu5l4goM9QAaBO84O9JhCNhXfrqYQNoNwJiCkYMjAMIJMyJqqeYD3HJitLKDNCMJxMB4G8P2lEg0nMHcCpxmdwNgDRBRMOHVwzAKGcgG3AgC6LmA3ocYBwGtgPvvsM+nUqZOUlJR43l9VVSUJCQlyww03yL/8y79Ir169ZNasWfL11197bvf1119LcnKydO7cWTp37izJycntFgTdGOBrVQ2cAQA9LSChDCBvWhzA2+oNICYAvOWjRUEA0JR/0f6B6jeAv0dzHlfwN+X4IypLzT91vyzMT1T5F+wfGEAsu+Oih0gMgD+0Y+RW9tBFejBTAB5Xi/QbLjAw9wPRLAIHLJgxBoFm8wUDMZZbzxN4417kvRV9payqAZRxawpXqzHYA1uHA9kWX4MjbvAx5CDifjGr8wB4f6jzOmdt8u61Bvr4mP9fAHvsbXJOIhtCDvhiPVKwuQu4pWSIrCu6S+NgUs+M0mq4BV+N07pF/C6iG5hl4NGHZmoeYMIXz8gdn8/zMIAwgN3y0aLGAeBbK4OjYAAA2QUcigG0tIE0mgPYRgqKA4BueBwAdBPWtKYJpDFWsEUA8FULADQNIDYA+DYBwPeXBjGAkH/BBvySHMAj9s/R/t/Ew9Nl3JdPeswfaCSA/IvaN7B/ywrG6P4fs3/c+bu3om8Q+INkBgYQIAUX2GsNKNjAKjOBAE8sEbOcCDCGj2MnEKCQpWSwhLvL+yk7yGwewKU/AD5ZsuTgZfz72NUD6EPsCXYZuSINL/F+ZPVxBy/HunT0/dJe9zX+r6Zkz13B2AfkZpBd5f09LCCactgQsuL0aO0HxsrF3LzxnkxAsIDjs56QxMPTZfShmZoHCCOIjQUMYgADO4CaBfjWygYQCCewmQUYSgJe85J3B9DCADoA6OZKjAOAbsKa5u4AtgrwNQcA4ln2eksHcFpq/Y4OImACAdChGEAGgMwAogGE5d8HjkxT6Zez/6afSNbQZwBAxFdw5++20sG6+4fYF+T+YTeKs+uwq8aGgaZ2w66VAwbth7pYlUUhH5q9tvgYduUYIOJtsINgDPdW9PUANIA/BpUs5wIAMtC+UN1VvwduvuAQbABygDs2wJjuXXzdjv7Ztyf4w88L9y93HKP+D13BCIdGJAyz4mwIwR4gmnRQDcf9wAhgBwDkTECAQLCAAICD/rRAf+/hBK67sbNnB1CdwO8sbwCAtkYQGEFsDOAaLwDsZTKAvAfIJpC2kH/dDqAbYxwAdBPWtEQCbuqPUbNk4QAA7L00AADNCJjXCABy/t9mioAhANj7Ayp7v7Gzyr9o/wADCPB3z4HZ6v5F9RuMHzhsADF7f9cV3aXMH9g/OH859BmSGIKKIZdBtgSAuRbZv6YAA4AUABKDKluvMQNAjpkBIMT7AQA5o44ZPjanAOyZHbrm92JK2Szj4t9nQwc3Z+D/HE493/+Fg/uJndwI+0aQ97HKSGW/IQNzNBLvA3I7CFhArogDCAQARCSMrRUEtXC/+PN8/b1HHAwDwF7vL61nAOEEhgyMKJhNFicwycCeKJimJGDHALq5QuMAoJuwpqVVcO3CAK6vZwCRsdUoAAzhAI7dsTQIACL7D/2gHABtA4CIf0ELAaIoYPxYUjBWmT/T+AF5C/lnAH+5lT3U+YuYEt5NAyvV0Rf1tj5NgSAbWwbgBpbw+9oYBW+oS/umpl5eNLtzuaGEwR4+h1+awNNWvXa1x7R01AFoBgAEO8vRPQCAMIXAEMJycHrZANlxdqDHDQwAyM0gnA047cREKwBEjzfcwL/a+xsZEoiD4UaQBgDYOZgBNKNg3rA4gV8NzQI2ewfQNYG4aYdxANBNWNPcHcBQTF+LgWHgD2DvpQ0AUBnA9Y0AwDSvASRm+wsSozuAnRUAsvz7iz/Pl1/8eb4kfPFMkPs38fB0DX9+NOfxIPYPvb9g/5D5t75omGwoTtC9v22lg1XiAvMBCQyyL0wfHE8CpqqjL+xtfVrCggHUXazpJj/UxSoLyDt3l2vr5XSwgdyPy2wd3s/fiynbNsXY/V+R5Nvj4GfNUjAMIchlZEcwWED0YQMAIhoGMjC3g5hSMDIBORQa/d2Ig4EMPOSz3+oTv2AAeJ30/mBJQxYgKuHeXtFgAmksC5AYQA8AXN0MBtDlALpph3EA0E1Y05IdwMaeibaKAXytgQEM2wH8doABDOz/eSTgGzrLrZ88JwM+rZd/IQlB/h2xf46n/i0pe4okZU9R8weAHxbRufUj9cwo2VR8u+7+cetHRlm87K3o65F+0feLEGNEk4A5cSAjGFgwIDOdtJdq6psnsJMGNor39bjJ4lqMXbkWDsA3G2m4NQU5l8cqIzUD84AvVsEg7wLCEAIWEJEwHAszN2+8GrMmH3tMko9OlgeOTJMHjkzTPcDRh2ZqHiAaf7gXmBnA3h8sURlYASDvAAIABkCgKQGHDIO2VcE5CdjNFRoHAN2ENS3dAWxrCbj30gAAXGsAwEYyAKO2rvBGwLy/NCABNzCAqH+D9AsAeM+B2UH1b9j/Q/YfQmjhQlxSMFZWnxmplW8AgFtKhiiTAYYDfb9o/GDXLyJKOJakoy8XFppXAAAgAElEQVTk18IxAVxuZQ9l9xjoAZjgdo3VpTlQ2Lpjurov1nTzhH1DCoYMfMQXrVIw3MEcDYPfKTzJWn1mpDqCmQUEADSr4cZkPqW7gHfum6uZn2gF8QDAGxsAoEcGBgPITmCwgIiCedUOAFUCfjFMF7BjAN20wzgA6CasaW0VnHUfxWIKaSkAjNzwohcAGgYQRMBA/q1nAOv/wP/lxs6a/Yf+3yEBAwjcgmMyn1IGAe5f9P4if2zBV+N0/w/y79rC4Wr8gOsX0i/YP1S9sesXeX/sWIVs2dEX82vtHKsMNmDguJ/nlT8AgthrBRA87e8quZU9JLeyh6chZE95nOwpj/MYQraVDtZQ6DWFI4J2AbkZhGVgOPjNSBjkASIOJn7XQvkLMYB90xc3AECzEm6zEQWzkWRgWxRMYwBwhcsBdHPlxgFAN2FNc00gbfUHKwgEQgJmB7AZAbOJDCCGAxjyb9/0xR4GEOwf6t9++dlv5c59c+WeA7Nl9KGZWv827ssndbF82omJMv1EsspOYCCWFYyR1WdGyobiBFlXdJdsKRmilW/pZQP0gravoo/Kvsj5y/c3dMki3447Yjv64n0tnnx/aObU3PNzp32O6ZjmOB7styIXEAAQMjCcwXvK49QNnFYyVH+/1hXd5QGCC/MTtSeYHcHJRydrKDQzgHfvf1p+tfc3agYZuPtZGbj7WQ8A7PPhknojSCAQ2uME5jBo/A3aSAzgq8E7gEFO4KYkYMcAummHcQDQTVjTVgxga4OgPQzgqw0VcFGvrQ7tAA5kALIDmBnAugADOHjP7zT7b8hnv9Xu33sOzNb2j/FZT2j8C7L/0PgBIAjnLxo/uO93+9lBavzA7h92n8D8FVV568N4T62jL+TX4mkMALpz5Q8c1pCCEeANFhCu4Hx/N20IMQ0haAYBy84AEIaQmScflpknH/ZUw6EZJPHwdEk8PF2r4dAKwnuAfyEJuM+HSzx7gGgE0U7gtGAWUPcAX12tiQUIg1YTiI0BbKcdQJcD6MYcBwDdhDWtcQG3pQmk99KXJXLDi3YGcOOLDYGslgq4ntuW6/5fnw+9EvDA3fUOYCyD//Kz3+rFwbb/h9YPuH4X5ieqDLX6zEitfdtUfLu6frefHaRMBhbc0feb7++msRgwfnDrRUdftK/lU1QV0eHfgzsNh804CNWGK7gsYAhBHBLiYeAOBgAECwiH/eozIzUbEEw8ZGCYQRgAjs96QsZ9+aSMPjQzqBcYcTAMAPumL1YGkI0gkX8MMICcBxhgAZsCgNEvOROIm44dBwDdhDUdagIxJODIjS827ACuNyRgMIDm/t87Dft/sTuW1kvAN3oBIP7442LA4G/cl0/K+KwnNP4F7J+5+7ekYKysKRwhG4oTgsDfjrMDZVd5f804g8zFmX9FVQ2dtNwr+0OdMyK09PjPdenw78GdhsMGHDDc56sj1PWOgGgYotCMAwCYURYv6WUDNBSa6+HgCIYZBHuAAIDJRyfL+KwnFACC4Tdr4UwAGJeRojJwTEACxh6gZgGaMvAGAoEAgBYnsLaBhAMAWykFOwDohscBQDdhTWtiYFoNCI0YmMjXAwDwldX2HUDDAYz9PwaAN+9M8QDAAZ/WA8Bf7f2N7gSNOjhLw58fODJNJmRNVQMIQp/R+4vol2UFY7SpALt/YCzQ+cvMH/p+fQEGxEc9tWBHnPTbuuNzAPCqPVzpVxcAgcgFzPd3k3x/N8mujJIjvmg54ItVUwjWKTYUJ8iG4gRl3NcV3aUy8PxT98u8Uw/qE7Upxx/RajgAwHszZ+geIGRgtILYAKDNCezZA3zTAIAmA2i2gTgG0E0HjgOAbsKa5gJAW/Bzi9lAUwJ+/cWGHmBbBqClAi763XoDCBzAJgPIBhBkg4EBhHMwKXtKUPOH6fxF7RsuTFhaB/iD6/dYZaTuOqHuDaYP1JRxG0VHX6iv5VNW5QDg1Xq4M7iuOkKr4kqr6vcBi6oilAncV9HHExKNari0kqGyqfh2dQWvPjNSq+EQBzPn5EMyKWeSysAAgGMyn1KnPwAgQqEbYwCjAzKwBwBuDsEAGgCw5+/rAWBIBtC5gN1coXEA0E1Yc7VIwEEA8FUDAL5JAPCPDft/AIDY/+OydwBA7P+Z/b+Qf7H/x52/6CFNPTNKASAaPxD6DOkX7N/eir7K/pVWNew++QPOXzB/HX1x/r9yqh0DeNUfmEIQEI0cTIREgwnE7izHwWwpGaIAEPuAkIEX5d8n8049qJmAyO9EJqAZB5PwxTMaB/MX+vvQ7+PnG/YAEQUTDgDkLMBXVtuzAEPUwTkXsJv2HgcA3YQ1LQWAbXbCZQAJAMIAEvX2CgWAvT9YIn0+XCJxGSlBO4AAf2AARx2c5ZF/2f2LBXOwfwijxf7flpIhQeCPO3+zK6N056+oqqHpAwxgR1+Q/y+dC9VdO/x7cKfp+wgyMA4AYGlVFzWFHPFFqwy8u7yfuoEBAjcV366/i8gEREPPpJxJetgIgjiYEfvnSMIXz6gTmBnAWz5aJH3TF6sMHAQAzUYQ0wlsyQL0tIGkOgDo5sqPA4BuwpqWxsC0OwPIDuBNoR3AHAHT58MlcvPOFM8z/F/8eb6GP9+9/2m5c99cGX1opsZFYPdv2omJ2v6B+Bd2/qL5A40FkH53l/eTjLJ4BYB5/u6S5+8uRVUNspczfbTPOV/tXMBX++GmEOQC4vcC+YB5/u6S6YvRXcBd5f21Hm772UEKACEDL8q/zyMDIxR6yvFHVAZGN7DJALIE/JeABMwAkKNgFACaRhBbFEwoABiuCcQBQDdtOA4AuglrmssAtmkYtLkD+MaqegD4qoUBNACgaQAJxQCy/Dti/xy5c99cuTdzhoLACVlT5dGcx2VGbpJm/y34apwszE9UxgGBtJB/08sGKPsH8Meu36KqCDV/oB/V7fy1/XFy+tV/sO+K+KO66gitiSuqitCViWOVkZ5IGOzX4neO20HYDTzv1INB3cAIhQYAZAbQlIBv+WiR3LwzJQgAqhPYFgWzkWTgphhAUwJe3rYAUJ+QOwDohsYBQDdhTYcCQJMBfGNVQw3cawQA0QG8uSEAGhVw0dtfUAn45p0p0u/j54MYwIQvnlHzB+rfxmc9oeBv8rHHZEZuksw5+ZDMO/WgLMxP1P0/NH+sLRyuoc+IrEDfL1o/EPrMe3911RFBPbXutM1xDSrXxvmmJlIu10bLNzWR+qQIAdHYBQSDfsQXLXvK4ySjLF5ZQMjBcAVjF3BhfqK6gaefSJYpxx+RSTmTlAVMPDxdRuyfIyP2z9FauFAAMKgSbht1AtsYwMAT1LAYQCcBu7nC4wCgm7CmpUHQbQYGOQbGYADRvakMIAHAnu/Ug7/od5drA8jNO1Pklo8Wef7AI/z5js/nyYj9c+SeA7N1/y8pe4okH50sU44/ouYPm/y7oThB1hcNU/MHA0A0f6DhoCyw21RW1UUjXy7WdHPgrx2O+5leGwe5gPh9AACsPueNhjnii1YzFVh2/M5tLb1NASC3gkAGnpGbpM0gMIKA6WcZ+Bd/ni/nf/bv+veh/8fPKwhkABj19opgBvANIwz6tRB1cDCCOADopoPGAUA3YU1bMYCtjoJhAPgKAcDXvQyg7v8FImCiqQKub/piicvw7gD+kvb/IAclHp4u47580mMAwf4fx7+sPjNS1hYO135SyFLs/AX4Q7QFmg+qz3WRb2uj5Hx1hGP/2um4HMVr52AP1n+ui1yq6a6uYP+5LroHCBk4uzJKdpf303aQHWcHaizM+qJhsuL06KBMwBm5STLl+CMqAz9wZJoaQUYfmimjDs6SOz6fJ3d8Pi/IBQwGsPcHS6TXe8s0EDqkEcQmAf/BAIDGDmCvlQ4Aurly4wCgm7CmtS7gVrGAZhB0Wqq9BQQu4EA/py0DEPt/pgTMABDtAGAAOf4FDuD5p+6XJQVjFfytLxomaSVDJa1kqOw4O1DSywboojoW14/4ojXSwm8EPqPuzQFAd/5/P5CBkYcJUwibQY5VRmpH8K7y/roPCEcwdgHRzsNmEN4DTMqe4gGAMID98rPfev4+gAG0VcIpAGQGMAAAmQGMeqWeBTSbQIL6gB0AdHOFxgFAN2HN1dIE0nvpyxL55qoGAPgaAcA3LAxgYP8vZvsLKv/evDNF4nctDAKAaAGBHJR4eLpWv4H9m3nyYd3/A8MAALip+HZJKxkq20oHa1vBnvI4yfTFaKUV8s0QeouLnNtTc8edBjPIpZru8m1tlHxbG6WGELSE5Fb20GYQAMCMsngNXQcTDzMIACAYwJknH5bJxx6TSTmTlAUcdXCWrn7ACMJ/H2795Dm55aNFEpeR4s0CBAOISrg3VzX0kTcSBt2oBLzCawLpvbRtwJ8DgG7McQDQTVjTnB3Axlo/WtQIYgLAtFRvBuCGF60VcKYBBB3AcRleAHj+Z/8ud3w+TxnA0YdmagMI5N9JOZP04gH3L+RfgD9kkcEAsqc8ThfWsyujNPaltMrL/iH3z0mV7rhTvwt4qaa7Jxz6PLGA2ANEP/Ce8jjZW9FXQSBkYG4FgQyMVhCuhQMDyCzgr/b+xrMDGL9roYZBswTsiYLBHuCbqzxGkMgNL3oBIJtAbHVwLgbGzRUaBwDdhDUt2QFs0yxAloA3p2oLSOSGF4MZQGQAMgAMdAD3TV8st3y0SG795LkgAAj5Fx3ALP9OOf6Isn+Qf1H7BgAIEJheNkCX1CH/ZldGSb6/mwbbou3DGT/ccSf4wBH/bW2UAsDzga7gPH93ZQH3VvTVw0xgWslQWVd0l6wtHC6pZ0Z59gABACEDwwk8JvMpdQKbABAMIKKker1fLwNHv1sfMxW1lWRgWxj0K+ExgFwH5wCgm/YeBwDdhDUtDYJuaxm499IAAAxIwEEAMK2hAg4AMIYAYFxGvQO4P+0AMgAcsX+OjD40U8ZkPiUTsqaqBAzzx9y88cr+IfcP4A9htBll8bKnPE73/tD7i/0/SL8AgQ4AuuNO8MEuIH5P/CQDn/Z3lWOVkbKvoo8CQQBA5AIilmlt4XBZVjDGYwTBPu+jOY/LhKypCgBHH5opI/bPsTKA8bsWyi0fLZLeHywJloEhAZsAcIO3DSSIAQyYQGIaYQCdBOymvcYBQDdhTWtiYGygr1kg0DSBbEkNbgGBC5hr4AwGsM+H9Q7gfh8/HyQBIwD6ngOzPQAQ8u+0ExNlzsmHPAAQu3/riu7SINq0kqEa+ryvoo8cq4yU3Moeku/vFpT9Bwawoy+07rhztR5Ew1QHTFO+QDsIuoGxY7uvoo/uA6IjeH3RMFlbOFxWnxkpK06PloX5ifo7fPPOFAWAyUcnewAgsgBNBpCNIJCBPVmAAIBvrAoOg36VWMBGJGDeAYx9wTGAbtp3HAB0E9a0RgJuNftnMoBbUoNNIFwDZ3MAB0Kg+6Yv1mfzJgC8c99cZQDvzZwh47Oe0PJ4GEAQ/7Li9Gjd/1tfNMzT/QsAyM0fef7uctrfVRfaAQCd+cMdd0Kf72tjNBoGDSEwgmRXRkmmL0a7gcECppcN8MjAyARclH+fzDv1oMzNG6+1cAiEHvflk5J4eLoygAlfPBPEAAIA9vnQywDCBOKJgrHtAFIWICRgsIBBANBkAJ0L2E07jAOAbsKatnIBt/iYDCBLwBvJBLK5wQTSc1twDRwiYGw7gOj/RT/o+KwnVP6dfiJZ5px8SBZ8NU6WFIyVFadHy5rCER4DCPL/sP93xBctmb4Yyfd309o37P9drOkml2ujnfHDHXcaOXiChIDo6oAMjFBoPMmCIxju+22lg2VT8e3KAqIRBDIwWkHgBB6f9YQ8cGSajMl8Sp3ADAAH7n5WswABAGN31O8AeowgpgnkdXsfMMBf9EvOBeym48YBQDdhTUsk4FAMYKt3AMMFgBQC3ev9BgewDQDeuW+uyr/3Zs5QCRgVcMj/Q/0bM4BpJUNla+lteuHBhYjdv2j+8JH0i+w/d9xxJ/ThXMBq6geGGxgSMJhA/B6mlQyVTcW3y5rCER4jyPxT9ysDiEaQcV8+KeO+fFIjoO7cN1cB4Pmf/bvc+slz0u/j5yUuoz5GCnuA0eQEjvxjwAnMDOAGrwSsDODLTUvALgfQTXuPA4BuwprWBEG3pQtYASDHwJgA8I+B/b936hlARMBwDdyAT58NAoBgAMdkPiX3Zs5QBzB3AC/Kv08W5d8nqWdGKQO4rXSwbCsdrBIwXIlHfNGSW9lDs//Q+Xu+OsJJv+64E+bhbMA6Iw7mWGWkZFdGKQt4wBer/cDoBUZVIyrhwABOOzFRJWBuBEEmIDOAAz59Vm795DnNEVUG0AyDZgmYw6BNBvBlcgE7CdhNB40DgG7CmpaaQNo0AiZMAKgGkHe8GYB9PqwHgP0+ft4KADn+5d7MGfJozuMeAHhv5gxZmJ8oi/Lvk9VnRsqG4gTZUJwg20oHaxXV9rOD1AGM3l+coqoIlbGc89cdd8I7HAfjD6xRlFbVG0H2VfSRTF+Mxi3tLu8nO84OlB1nB2ol3PqiYbL6zEiVgVkCnnZiokrA4758Uu7NnGFlAAEA0QeMKBgAwJ7vLPdmAZo7gFwH5wCgm6tkHAB0E9a0ZQxMqxnAP670uoBfpxiYLcQAbmswgQAAxmWkSP9GACAYwHFfPilJ2VPUADIjN0nmn7pf2b+1hcNlQ3GCJwIGAdC7y/up+/e0v6v2/zr51x13Wn5YBsYe4LHKSDlWGalS8N6KvvpEDBKwaQRBIDRk4EdzHpcHjkzTHcAR++d4ACB2ACEDwwXMEjCyAD11cKFcwKFyAFe2LwDsu8gBQDfecQDQTVjTEhNIm4JANoHYACDqlwISMORfZgBNCZif4SMDEOAPLSAMACH/LsxPlDWFI2Rd0V1a/5ZeNkBZQOz/If8P7R8c/eIkYHfcCf9gD/B8dYQ66U/7u6r8m+mLkezKKG0EgQSMXuB1RXfJsoIx6uKfmzdeZuQm6Q7ghKypMj7rCasEzAxgfzKCWPuAzR1AZgBfNXYAiQGMMYOgTROIA4Bu2mEcALzKJyUlRTp16uQ5N910k378xx9/lJSUFImIiJB//dd/lWHDhsnp06c9X+PixYsyceJEue666+S6666TiRMnyt/+9rdmfR+tyQFsyhjSbAnYBIAbKQPQZAADPcDIAIzLSJG4jBQZuNvLAAIA3ps5QwEg8v+QAYgGEFTAgf3j/b8dZwdKpi/GAwAR++IP7AB+WxvlJGB33GnG+b42RncAIQUXVUVozNIRX7QaQfBEDNWMCIRmBhBRMI/mPC5J2VPUBZx4eLqMOjgrSAIeuPtZjYJhCbjXe8saXMBbV9T//dkScAJbJGArADSDoG0MYBs9kXYA0A2PA4BX+aSkpEi/fv2krq5Oz1//+lf9eGpqqnTu3FnS09OloKBAJkyYIBEREfKPf/xDb/PrX/9a+vfvL1lZWZKVlSX9+/eXsWPHNuv7uFp3AD0S8JuUA2jsACIDMJQLeMT+OUEM4KM5j8uU44/I9BPJMvPkwzLn5ENaAQcDyJaSIbKtdLBH/gUbAQCI8OeyQAfwpZruHX5Bdceda+kAACJCCZFK+B3LrozSRpCMsniPC5idwGDw2QiSfHSyTMiaqjuAkIFNABgUBB1gAD0A0DSBvO5lAK0xMGAAQ0nAy9a4HUA37TIOAF7lk5KSIrfeeqv1Yz/++KN06dJFUlNT9X2XL1+W66+/XjZu3CgiIoWFhdKpUyc5evSo3iY7O1s6deokxcXFYX8fLXUBt5kMjD+AtiYQSw+wRwIO9HbyDqDJAJoh0A8cmaYZgJCAF3w1ThfJEQGzpWSIbC29TbafHaRNBPsq+kiev7vWv5UF5F+0GXxbG+Xy/9xxp5kHMnB1APz5z3XRkPVjlZFqBkEYdFrJUGUBkQWINQ5EwUw7MVEmH3tMJWA4gW0AkBnA2B1LPRKwpw4uFADkJpCX649pArEygA4AummncQDwKp+UlBT5t3/7N4mIiJCePXvKhAkTpLy8XEREysvLpVOnTnLy5EnP59x3333y6KOPiohIWlqaXH/99UFf9/rrr5fNmzeH/HcvX74sly5d0nPu3LkW5wC2KQsYageQauCwAxj9bkMINHIA0QNs7gCCAQT4AwPIEvC8Uw/KsoIx2gMME8jW0tskoyxeu0gzfTHKSiACxm+0fzgJ2B13wj+mE7iaGMB8fzfJrewhuZU91AmcXjYgpASMQGgzC3B81hOSeHi63HNgtozYP0f+Sn8fBu/5nXYBcw5gkATMfcBQJppyAdtyAE0A6CRgN+0wDgBe5fOnP/1JPvzwQ8nPz5fPP/9chg0bJjfddJNcuHBBjhw5Ip06dZKamhrP50ydOlVGjhwpIiLLly+X3r17B33d3r17y4oVK0L+u7bdww5rArF1Ab9qAYBvrLL3AFtcwPG7FnoA4D0HZsuog7Mk8fB0Gfflkx4GEBIwXMAAgDCAoP5td3k/jwSM+jcAwPOBDMBvaiIdAHTHnWaeb2uj5FJNd08nMIAfnMDIAdxV3l9lYLSBpJ4ZpSzgjNwkjYGZfOwxjww86uAsuXv/00EM4IBPG9pATAnYEwOTFgCAzACGqIILmwF0ANBNO4wDgNfY/Pd//7fcdNNNsmbNGgWAtbW1nttMmTJFRo0aJSL1ALBPnz5BXyc2NlZWrlwZ8t9pCwbQ+geoLUwgDAA3EgA0cwARA0MS8C0fLbLmAJo7gOgBBgCcmzdeTSCrz4yUdUV3KQjEDuCe8jhJLxsgmb4YjX7B8ZEBxFXAueNO8863tVF6LlR39bSBAARmV0apESSjLF62nx3kqYNbcXq0LCkYKwu+Gidz88bLnJMPybQTE9UIgkYQ9AGfD8EAxmV4m0BQOelhAFkC3mjZAeQmkCZyAGNfcBKwm/YZBwCvwRkxYoQ8+eST7SoBm9PcHcB2YwFtO4AbCQBusTCA79en9vdNX6xB0DYTyD0HZmsQtNkDPDdvvMw79aDHBAL5F+5fZgBzK3vo/h/cvxequzoDiDvutPB8XxsjF2u6ycWabnKhup5ZR9Ym4mCO+KJld3k/ySiLl62lt0layVBtA0k9M0pWnB6tAHDmyYc1Cib56GRJyp4iiYenax8wA8BBf1qgALBv+mJPDIyHAcQO4JsWAGi6gF9uhgTcSgCo6zgOALqhcQDwGpvLly9Lt27dZMmSJWoCWbVqlX78u+++s5pAcnJy9DZHjx5tNxNImwO/cCRgIwaGASB2AHt/sER6f7BEdwBtAHD0oZkeCRgtINNPJMuM3CTtAYYDGBLw9rODPBmAuBid9nfVDmB/oMP0Yk03J/+6404LDurgkAVYWtVFjVbYuc30xcie8jjZVd5ftp8d5MkBBAO4MD9Rn9DxDuCErKmSeHi69gGbAJCDoAEAdQfwrZXeIOjGAOAfSAJ+MUwG0EnAbtphHAC8yueZZ56RgwcPSkVFhRw9elTGjh0rnTt3lsrKShGpj4G5/vrrZefOnVJQUCBJSUnWGJj4+HjJzs6W7Oxs+fnPf95uMTBBzzgXtYMJxMYAvv6ixwQStZUAYGAHkGNgTAn47v1Py6iDs9QEgh3AKccfkRm5STIjN0mWFIzVJhDIv4iBYRMI9pGOVUZKUVV9dynO+eoIuVjTrcMvpu64cy0dmEAQpF4deEIFFzAk4L0VfdWNv+PsQGUB1xXdpQzgovz7ZN6pB3UP8NGcx2VC1lTdAYQE/NcQDCAkYE8MzFsrGxhAroJ7PbwcQOcCdtMR4wDgVT7I9fvJT34iXbt2lfvvv1/OnDmjH0cQdJcuXeSnP/2pJCQkSEFBgedrfP3115KcnCydO3eWzp07S3JycrsFQZvgr10k4LQQJpAAADQZwJjtL2gOIHYAb/3kOc8z/Dv3zfXUwI3PekKSj07WHmC4gCEBryu6S9YWDtcImPSyAbKrvL8W0sOdWFZVf6Eqq6qXgcEAuiYQd9xp/gEABLOOEGg86dpX0Uf2lMfpDiDXwZk7gACAk3ImaR8wGMC79z8d5AIGAxiXkSJ90xdL7I6l+gQzais1gby5KtgE0hwX8HLHALq5MuMAoJuwpiUAsM1AoCkBpzUwgFGvrfbuAG42gqADJhAGgP0tADDhi2fkngOzZfShmR4XMORfNIHgIoIuYA6CZgn4iC9a2b8ywwV8obprh19I3XHnWjtsAoEEnO/vphLwAV+s7gDuKu/v2QFcWzhcswARAwMAiB1AAEBbFdzA3c/KwN12F3DM9he8EjAAYGMM4BoygTgA6KaDxgFAN2FNS4Ogg/4AtRQQMgB8c5U9B9AGAAPP0DkIOn7XwkYZQJhAko9O1qiImScf1hxAmEA2FCfI1tLbVALeXd5PASDciYiBqSb593JttNsDdMedZp5va6PkYk03qauOkOrAEyuEQOPlvoo+uoqxrXSwZgGaEjAHQU/KmSRJ2VO0Cs7mAh7w6bOeHMC+6YvtJhAAwLTUhiq4jeEzgB4JOFADF7vcAUA37TMOALoJa9oKALb4LHm5IQbmzVWaq+UxgbxhqYILhEGbLuDGdgDRC/pozuMqAc/ITZJ5px6UFadHy7KCMbK+aFhQE8iu8v6ypzxOcwDBTLATGBmADgC6407zzre1UfJNTaScr46Qsqp6AIgdQBiv9lX08TCAW0tv0yq41WdGWmNgYAJhB/A9B2Z7JOBbP3lO4nctlLiMFLnlo0XS50NvDEzU1hUS9faKhhzAN1Z5u4Bfa0EQ9NL6v3uxy90OoJv2GQcA3YQ1HVoFZ0rAbwQYwFftEjDkGJsEfPPOFK10ssXAAAAiBmbK8Udk2omJMu/UgxoEnXpmlEpKuMiklw3QC0+mL0YO+GIl399N2T+wFhdrurn9P3fcacEBAAQLCAYQQdAcA4Mg6K2lt2kOIANAmECmHH9EGUB0AYdiAG/95DmJy0iRuAxvFZw1BoYAYNRrq4MZwMYkYJcD6HqSOFQAACAASURBVOYKjQOAbsKaDo+BWWIBgJCAIQObQdDEAPb+YIkGQcfvWiiD/rTAGgNjywHEAQBccXq0Jwh6x9mBygCmlw3QpfRjlZHK/vnOdZEL1V11j6mjL6buuHOtHYC/C9VdgyRgdAGDAYQJBAzguqK7ZE3hCFmYn+jZAeQWkMTD0+XezBky6uAsGXVwlgLAv9zYWQEgJGBPDuD2F+qr4LgJxGQAbTuAliYQ6w6gYwDdtNM4AOgmrGkJAGwPF3DvpS9L5KZV9iDoN4wdQDSBUBUcGMDGgqATD0+XB45MC3IBo0geWYAbihMkrWSobCsdrC7g3eX9ZF9FH5WAS6u6qBmk+lwX+aYmssMvpO64cy0eMIB1JAED/AEA7imPkz3lcbKtdLDGNMGxDwZw/qn7ZW7eeJmbN96zAzg+6wkZk/mUtQoOOYAIgu79wRLp9d4yiUETyDvUBJIWIgZm3Uv1DODvw3cBqwTcRn9HHQB0w+MAoJuwpjUMYJvEwrAE/PqLKgF7cgDfsEjAFASN/T+bCcTMAZyQNVWSj06WSTmTVAaef+p+WfDVOFlWMEbWFg6XdUV3KQAEA7ivoo9k+mJ0Mb2oKkKDoCEFuxo4d9xp2blQ3VWr4BADA+k30xcjeyv6SnrZAMkoi5e0kqFqAllbOFzWFI4I2gGccvwReTTncXUBgwFkAPiXGzvLwN3P6uoIImDAAPbctryeAdxq2QHcQF3AYAB/T1VwLxIAXBkwgTgG0M0VGgcA3YQ1rY2BaTUbGAIARr0WAIFsAtmSqgCw5zvL1QXcN32x9Pv4eelvMYHcuW+ujDo4S2NgOAcQTmAAQPQBmzuA6WUDZE95nMZRwAWMLuCLNd3kUk13BwDdcacFB1VwddX1v0+n/V319wxAMLsySjLK4mXH2YHKAqaVDNUIGDCAYAF5B/CBI9PUBMI7gACA/QMZgDfvTPHIvx4AuDk1OAPwtdUeAAj2zwYATROIcwG7ac9xANBNWNOhO4ChAKDZBAIJeEuqJwYGdXCIgbF1Ad+5b67cc2C2jDo4S+vgAACnHH9Epp9IloX5iSoDry0crnVwm4pvD5KAj1VGah+wn0wg6AN2LmB33GneuVwbLd/UREp1gE0vqoqQ7Moo/V3Lrewheyv6agsIR8CsLRyuv7vYAUQMDNi/B45Mk3szZ8iI/XPkzn1zg3IAOQam9wdLNAS6UQZwo1cC9jCAqIJrxAXsGEA37TkOALoJazo8BoYB4MYAAHyFTCAbX/TGwGz1AkDsAMZlpEj/j5+Xgbu9DCCCoNEEMu7LJyUpe4pKwFOOPyJzTj4kC/MTZVnBmKAcwG2lgz0xMMwAllEOIABgR19M3XHnWjvoAT4fYADLqrpIdmWUGkEgAWeUxUt62QANguYuYDiAZ558WF3Aj+Y8rs5/MIAMAFkC5iBohEBHv1sPAHX/DwBw06oGF/Cr5AL+vdEFzAzgcpKAHQPopp3HAUA3YU1Lu4DbBQBueLF+ofoVkoDBAL65qkECJhMIJGAAQFsO4Ij9c2TE/jkqASdlT/EwgHNOPqQ7gKvPjFQGcEvJENlSMkT7gPdW9NVqKuQAFlXVM4D+c130guakYHfcCf9cro2WuuoIqauuN1WVBgAgx8Dsq+ijDuAtJUNkQ3GC5gCuOD1aFuYnqgFkzsmHZPKxx7QLmHMATQB46yfPSf+Pn7ebQN5Z3uAC3kzgj2NgzB3ANYYJhEOgHQB0c4XGAUA3YU1bScAtBoYUA6Ohqq8aMTC8A/jWSo2BsRlBTAn4js/nyYj9c+TezBlyb+YMSTw8XSZkTZXJxx5TJ/DcvPGyMD9RdwAZAIIB3H52kBzwxeo+Up6/u5QG+oB9ARbw29ooJwG7404zzuXaaHUB+wIScCm5gI/4ouWAL1YjYJABmFYyVNYV3SWrz4yUZQVjdI8XDuBpJybq/t+4L59UAJjwxTNWBjAuo5796/3BEonGDiADwC2WHcD1FgBomkAcAHTTAeMAoJuwprkmkPZkADVU9RUKgn7dkIAJAEICjt2xVG7emaJZgCYARB0cdgCTsqeoDDzz5MMqAS8pGCvLCsbIpuLbVQbecXag7gEe8MVqEDQk4LIACPQHomAc++eOO+Gfy7XRagDxB/b/0APMABA5gFwDBwfwsoIxsuCrcbLgq3HaAjLl+CMaAcMA0CYB9yMGMHZHQwh09LuBJhBLDqCGQJs7gGQCCaqBW25pAnEA0E07jAOAbsKalrqA2xT8AQC+urpBAl5vAYCbUz1NINGGCSQUAByxf47mAPIO4KScSSoBcx/wuqK7lAXcWnqbZJTFS0ZZvOyt6Ks7gGAB/QHwd7Gmm1ys6Sbf18Y4EOiOO8042P/zn+si+f5uUlbVRTJ9Mfp7hiBouIAZAJotIHPzxsv0E8kaBA0AeG/mjJASsAkAe723LLgFpDEG0KiBcwygm44eBwDdhDUtAYBtGgptA4DrDQZwkxcARr210rMHCAn4lo8WWV3AI/bP8biAk7KnyKM5jysAxO7Qgq/GSeqZUZJ6ZpRsKE6QLSVDZPvZQUFRMLg4cSXcpZruzgTijjvNPN/XxsiF6q7qpi8NtIBk+mL07K3oK3sr+sqOswNV/t1QnKAS8KL8+1QC5h5gBoCjD82UUQdnNQoAzRYQDYHekuqNgdloB4AhGUAKgkYGoAOAbtpzHAB0E9Z0KAOYUg/88FLlX46CsTCAUW+vCNoBBANodgHf8fk8uXv/09oHfG/mDDWBTMqZJNNOTJSZJx+WBV+N0zo4SMDYA0QYNC5ECKjNroyS0/6ukufvLnXVEXKpprtrBHHHnTAOM+WXarpLdWCXFr9P2ZVRunLBQdBbS2+TDcUJsr5omKSeGeVpAZl36kGZc/IhmXnyYSsAvHv/00E7gAiBjstI8UrAtAOoLuA3Q5hATAk44AK2ScAAgE4CdtOe4wCgm7CmtUHQjf5RCgcwMgMYqFSKWveS3QXMfcDblmteV1MSMFhAmEDGffmkMoBTjj8iM08+rH3AqWdGaRbguqK7dA9wx9mBHgbwiC9aGUAOg3YsoDvuhH8QAo1VCt+5hhYQ/K4d8MUqANxWOlg2FCfIhuIEaw3cjNwkrYGbkDVVo59GH5op9xyYLb/a+5sgBhAmkD4fLlEAaK2BCyEB9/wDAcCX1oTeAXzBAUA3V2YcAHQT1jTHBcwScJuxgQQAe/6BACBkYJMBJADIWYCQgPsZDGDCF894TCBjMp/SOrjJxx6TaScmypyTD3kA4Lqiu3QPcENxgmwrHSwZZfFaB3fEFy3HKiOlqCpC8vzd1QV8obqrfFsbJd/WRnX4hdUdd66FAwAIBtB3rl4CPuKL1ho4BLHDBQz5l1tAeP9v2omJQRmAow/NlDv3zZU7Pp8XBABv+WiRuoARAN1zG4G/P1IMDLN/MK0ZO4Axq0ObQBwAdHMlxgFAN2FNS1zAbSoFmwDQJgFvsjCA73izALkNhAHgr/b+RsOgEw9Pl8TD07ULGABw+olkWfDVOFmYnygrTo+WNYUjlAHELiDiYHgHMLeyh9bBna+OUCOIi4Nxx52mzzc1kXKpprtcqO6qIdBFVRGSW9lDmT8YQHaV95f0sgGypWSIrC8aJmsLh8vawuGSemaULMq/T+VfxDtNPvaYMoCJh6fLqIOzZMT+OXLH5/P07wMkYG4BAQAMMoE0VgUXYgfQZgJxANDNlRgHAN2ENa01gTRL7g0FAFMCAHDtS/qMOmgH0CIBAwCCAUQWoAkAEQY9+tBMGZP5lIzPekIl4MnHHpOZJx+Weace1D7gNYUjtBEE4G9b6WCtgwMzgbiK0/6uusgOENjRF1d33LnaD2KTIAGXBoLV8/zdPbt/AIA7zg6U7WcHaQD02sLhsuL0aDWBzMhN0t/rR3Mel6TsKZ4Q6BH751h3AD0A8P2lXgDINXA2CTjwhLVFDOALDgC6aZ9xANBNWNOSIOh2YwB//1KDDLyeomA2rQrOAgzsAMZsf0H6fLgkJAN4x+fzlAEcdXCWjMl8Sh44Mk2dwGAAUSQ//9T9suL0aJWA00qGBjGAkIBzK3toIwiiYGACcVEw7rjT+Pm+NkYu1XTX3T/EwHD92wFfrOwpj5Pd5f1kx9mBsq10sKwpHKEVcKlnRmkANPb/uAYOrP+og7OsJhC0gDAA1AxAbgF5c1WDBPx6IxLwS2sUAHoYwOUOALq5cuMAoJuwpj2CoJsFEG0A8JWGkFWVgM06uHeWKwhEH3Df9MVyy0eLPBLPkM9+K3fum6t9wPdmzlAGEGwBXMDzT90vywrGyIrTo2Vt4XBlAAEAEQiN/SREwQAAVlMjSEdfXN1x52o+kH+/rY2S6sDvDvb/cit7yJ7yOA1/3lvRV3aV95ctJUNka+ltHvkXGYAzcpM8BpDko5NVAr43c4ZGwJg7gHAAIwKm13vL6h3A2ywA0HQAh9gBtJpAQgHAxc34W+kAoJswxwFAN2FNc7uA25wFJAAY/TKZQLgOztwBDLSBhHICMwAEA3j3/qcVACYeni5J2VPUCII2EPQBp54ZpXuAaSVDZVPx7coAQgJGDEyev7uCQGSZwRHc0RdZd9y5mg8q4M5TBmC+v5sCwN3l/WRPeZwnADqtZKisKRwhq8+M1MxOZgCnHH9EJuVMkqTsKTIha6qMyXzKUwNnuoDhAO6bvrh+nzjQA+xhALeExwBiB1B7gFd5MwCDXMCOAXTTTuMAoJv/1965R1VZpv1/z0GdqVHKppWigeI5GTKdPHSALA+5UHmtzFxqmq+mjsfUNEvFE4oZ1fhGTjrqmzOmHdRyRi3NQ5TgCSQQUOQsyFvLnBzn15gzef3+YH8vrvvez4YtbMCG67vWvYBnP3vvh2fDfj77e518UnWKQPxSECJmAbeOe4V7avE4OOQB/tEMActKYBSBoBJYAmCvT+ZQL7cLiBBw1OeTDBdQVgIvTh9oFILEZ0UYDiCmgSTkh/DA+lOFgZTtHgtXWtycLpcEaT9AXboqWAC/yyVBVFrcnLKLynoAJhfcSccKgjj3DwAoewCuzupNcZl9uABkfloUzTw5lKamPEXjjo9i929o4rM0KGGyMQau1ydzHHMAUQDCDqBsAYMcwLXlAMg5gBL+XhVtYGwAdGoDowCoqiEpAKp8UlVDwDXiAMa5+2m9LsLAdiuYjQ7NoEUhiMwBBADCARzw2VQalDCZhnwxkYYljueRcBgHh1Dw0vRIWpXRj1tNyIkgCEkl5IfQsYIgdgFz3BNBcoqasbNR1xdZXbpupIWcvx9Ky3JkLxQH0sWSFnShOJDdPzSB3pvXgXbldqZduZ1pZ24obTnbjTZn30vrz9zH7t/S9EijAGRy8nAae2w05//JCSBwAHt9Msd4f+gsmkAD/mQBiC8h4Favu0PAcSIHcKVzH0BjFrACoKqGpACo8knVAUC/wKAEwFfiuKkqO4D2POCN7jDwJrMZNPIAO+2I9gBAhIFRCTzki4lcCDL22GijGfT8tCgOAaMhNADwvbNdeRoIIBC5gNIB/Mo9FURbwejSVb6ung/hFkmXS4LoQnEgw19WUXM6VRhIaYUtuAAEod8tZ7vRjpww2pTdgyuAV2X0YwBE/z/MAH766DM0LHE8PX54Auf/oQVMTwcA7LjdnQPoAIDcAma96ANot4D5vekAhrxs5gByCNjKAWy3VHMAVTUjBUCVT6pqFbANf9VqA2MD4Os+AKAMAVeQA9j947kcAkYlMApBHj88gZ4++gyNPTaaJicPpxkpT9LCtMGcB4hKYOQAoiH0jpwwnlOaVBBMxwqC6GRhSzpVGGg0hcZFr64vvLp03SgLrV++Ox/M/f9y3O5fWmELSioI5t5/cAABghjRCABE+Hd26hM0NeUpmnRiBBd2DU8aR4MSJvMEkL4Hp9OD+2ZT94/nenUA2763xATAP1kAWNkYuFctBzC24hxABUBVTUkBUOWTqjIJxK8hYOQALnqVQlbFeYSAOQcQeYAb3HmAIgQsK4Hv+nAhlVpVwJgHjDAwcgCRKA4XcHbqE1wJLEPAEgBlcrosBMkqam60g9FqYF26zHX1fAjPAEa/TNkAGhXAsvkz8v8AgGtPP8Du39L0SM7/m3RiBPcBxAxguH+yAvjePS8YAHjXhwupw7ZFXAUcYlcAYwzc2pVGDiDGwAEAjQrgVc5NoB0dQA0Bq2pACoAqn1TdIhCvb0i+AqJwABkARSuYoD94qQT+U3krGEwDaff+YkcH8P69z9OD+2bzxQAhYEDgmKNjOIcIhSCAQEwdWH/mPtqcfS/3IkNF8MH8tgyAJwvLepoB/r47H6zVwLp0uRfg73JJEBWea0YXissc85yiZnSsIIgdwIP5bbnvHxpAAwDjsyL4/3Nh2mCuAMYIOISA0f4lMmEK9Tkwo0IAlD0APQBQNoF2h3+NJtCWA2j0AKykClgBUFVTUgBU+aTrbQPj9xxAUQUc8rIXB/APAgBlDqDVC9AbAKIQBMngkQlTuBBkzNExNO74KJqcPJxmnhxK89OiuBIYM4HXnA6n9Wfuo03ZPWhHTpjhAO7Pa08nC1vSycKWlF1U1soCE0EAghoG1qWrbCEE/FVxcyp1r5yiZlz9m1xwJ7t/W85247U5+14GQPT/wwzgqSlPcQPoscdG0/CkccYIOFQAO4WA7TnAHAKWs4DXm3OAGQDfWMUfWL2OgXMAwPaL/QuAHRYqAKpMKQCqfFJN9gH0CQy9AaDsBWiHgEUzaISA5TxgGwB7ugEQTgByAFEJjJnAU1Oeopknh9LCtMG0OH0gxWb0p1UZ/WjN6XBae/oB2pTdg5tB78ntRAfz23IIGPCHauALxYF8sVMA1FXf15Xzrdn9Q+7fheJAHgGXXHAnJRUE84cqOIA7csK4Gfua0+G05nQ4rcroR6sy+jEAogDEBkC4f/0PTaMH982m+/c+X6kDKJtAGy1g/uiQ/wcAdJgC4jQGTh1AVW1JAVDlk6qaA+i3JUPADgDIbWDsHMAKpoHYk0B6ilYw/Q9N40rgIV9MpKGJz3IRCABwfloUF4MsTY+kuMw+DICoSNyV25kO5relg/lt6VhBEFcwnioMZADUPEBdusoWKoAvlbSkSyUtuWl6vhsA0VYJFfa7cjuz87c5+17aeKYnrT39AL2e+Qi7fwj/wgFEX88RR8YaAIgPfr0+meMBgLIApM3WpVz84bUH4BrRAsYXAKwoBLzEf++jCoAqKQVAlU+63irgykK/1w2JEgBXxpXl1LxWPg/YCAGvFQ6gCAOjGXS798uaQcsikHv3vED3732e7t/7PAMgmkEPSxxPI46M5RzACSdG0rwvh9D8tCieM7o0PZLHwgEC3zvblfuT7c9rT0kFwcZUEIS1cLGr64uvLl11vVD4Uep2/gB/Oe4G0McKguhgflvan9ee9ue151zb9852pU3ZPWhTdg/Ox8X/5dzUx4wZwGOPjeYCkMcPT6DIhClc/PXQ/pmODqAEQGMCiO0A2gD4hrsH4O/NKSBGCHiFdwcQSwFQVRNSAFT5pOstAqkS5F0HABpFIG8IAHSaBrKprBIYIeA27y5xBEAUgjy0fyb3Aoz6fBL3Anz66DNcRYhKYLgMgL/VWb15IsiOnDDamRtKu3I782i4pIJgbmWR7Q4Dl7r7Af5QWp4AX9cXYl26anshFQLTP74S7h+Kp44VBNGxgiAO/27L6cL9N+UEkNczH6HlpwbQwrTBNDv1CXYAkcaBHoDSAQz/dBb3ALRzADEHGA6gLz0AZRGI4QDGWUUglYWAKwPA62gRowCoklIAvMG1fPly+u1vf0u/+tWv6Pbbb6eoqCg6ffq0sU9ERAS5XC5jDRs2zNjn4sWLNHLkSGrSpAk1adKERo4cSX/72998Po7rDQH7NRS8yFxtVsZxV30AIFcCoxegLAT5kwmA7d4vCwF7A0DkAaIXIELAGAc37vgompHyJM1Pi2IXcPmpAdwSBoUgyE0CACbkh1BywZ08Ezj/nGceoATBur4g/6csPZc/joXQLxxAhH8Lz5WPf8N87T25ndgB3HimJ713tiutP3MfbTzTk1Zn9eYCkKXpkTTvyyFGA2jk/w1LHE9Rn0/i4g8UgPT6ZA512z2PAbD0tsYeFcDGDGAUgMgpIDIE7K0HYEU5gHD+AIDaB1BVA1IAvMHVv39/2rhxI506dYpSU1MpMjKSgoKC6B//+AfvExERQePHj6fS0lJe3377rfE4jz76KIWGhlJiYiIlJiZSaGgoDRw40OfjqEoI+HrCvZXuIxzANisdcgBtALQcQJ4G4nYA23+w2ADAbrvnUc9P5nAIGACISmAAIJLIJ50YQXNTH6OFaYNpYdpgLgSJy+xjuICyGARTQZIL7qTkgjsZAPPdEHixpIXCSg0sDa//OBYaP9vhX8z/RfsXVP+i9QtCv2tPP0Drz9xHa06HG/N/vTWAlmPg7Py/rrte9ABA9ABEAUirP8eUh383egHA/7F6AEoHcKVoAyMAUIZ/NQdQVZNSAPyR6euvvyaXy0WfffYZb4uIiKDp06d7vU9mZia5XC46cuQIb0tKSiKXy+XhJnpTdRxAvziB0gGM9VIF7DANhAtBNsewC9ju/cVlANjUdAC77Z7HrWAwFSAyYQoN+GwqAyAqCDESDmHg2Iz+tPzUAKMQZFN2D+4FKPsBAgJPFZaNt8JUEDS91RCwf5cW2Nz463JJEF0sacHVv/lu5y/HPf4N87RRUIXq3y1nu3Hj5zWnw7n9y/JTA2jel0NobupjNCPlSf7ghgIQOID4/4YDeP/e56nnJ3MqB0B3YRk7gJgD7A4ByxnAHAJ+zbMJtBECdgj/KgCqalIKgD8ynT17llwuF6Wnp/O2iIgI+vWvf0233XYb3XXXXTRr1iz6+9//zrevX7+eAgICPB4rICCANmzY4Pg8V65coUuXLvE6d+5clXMA/RIOXlT+1QMAMQ5ujQWA68vawHhrBSMBsOuuF9kF7PXJHHr4wHPU9+B0zgMc8sVEGp40ji8iU1OeotmpT3A/QFkEghAw5gLvyAmjPbmdeCzc4fzW7GjgAofG0JdKWtLlkiCFFj8udQB/HOtiSQt2AAsFAKJ/Jty//XnteeoHABAO4Oqs3rQqox/n/837cghX/044MZJGHBnL+X9DE5/lHoCAv/v3Pk/dP57rEQLmCmABgEYF8AbRAgYA+GaZ+xe8WhSA2GPgbACMUQBU1Z4UAH9EunbtGg0aNIgeeOABY/vatWtp3759lJ6eTlu2bKFWrVpRnz59+PaYmBhq166dx+O1a9eOli9f7vhc0dHRHnmF19sGpqbyANusiOM3VC4EkQAopoEYvQDfKZ8GYgNgl7+WAeC9e17gmcAYCScbQo84MpbbwSC5XPYDhAMo28HA/duZG0qH81vzBe1kYUvKcfcFRMPbr4qb0+WSIA0F+xks6voYdDkv/J0D/OCElxY3p2z37F8UfmD02968DrQntxPtyAmj9Wfuo/isCO7/tzqrN7dlQvXvzJNDadzxUfzhTYZ/ByVMpr4Hp9PDB56j8E9n0f17n6duu+d5OICOBSBvW+FfpybQyP+zAfBl7zmARgh4kQKgquakAPgj0u9+9zsKDg6mc+fOVbjfiRMnyOVyUXJyMhGVAWD79u099mvbti2tWLHC8TGq6gBWVABSLRisCABlK5i3hAu4QeQB/knkAW5dSu3eLwfA0tsaU9jO+YYD+ND+mdwLEA4gwsBIJMfFZd6XQ2hpeiQXgsRm9OeLEhLUMasUBSGoBkZzaFz8AIDaGNp/66vi5nV+DLq8Lzjesv0LKn9PFQbyh6WD+W15xjaqf9H0ec3pcHo98xGu/l2cPpBmnhzKEIjiLbR/wQzgAZ9NpYcPPEcP7pvNE0C67Z5HXf76IucIlzZt7DECDn0A8SHTcQqIlQPIAChyAD0cwGVeikAUAFU1IAXAH4mmTJlCLVu2pLy8vEr3vXbtGjVo0IC2bt1KRFULAduqyig4v1YDYxIIABCfqn9fXgQS/OYqsxWMVQncarO7F+DWpdT2vSUeAGjnAcIBHPDZVJ4KgiRyJJUjD9B2AeOzImj9mfto/Zn7jGpgmQso8wCRCyhDwXV9Yf5PWeoA3tgL0z9k1S+ccbv1CxpAb8vpQpuye9DGMz0pPiuCx7/FZfYxpn/MTn2CZqQ8yf3/hieNo+FJ4+jxwxMo6vNJNOCzqdT34HSeAIIikC5/fdExBBwiR8Ah/8+eAmLnAK42ewB6zAFeUXEOYPvFCoCqmpEC4A2ua9eu0eTJkykwMJCys7N9uk96erpRKIIikKNHj/I+R44cqbEiECe3r9ogKBzAtssrcQARAl4f6wGAIe48QCcHEHmAmAv80P6Z1PfgdKMp9IgjY2nEkbFcCTwj5UkOAy9Nj+T8o9VZvY1iEAys35vXgQtBkNieVdScsorKmkIXniufEax5gP5ZCoA35rpcEkQ/lLb1gD84f5iYk1QQTMkFd9LevA5cULUjJ4y2nO1G8VkRHPpdndWb4jL70NL0SO7/hwIQFHA9ffQZI/yLHoAo/ujpbgFz919eKgdAtwNoAKDdA9CpAvgNB/fvVWcA9NYDUAFQVZNSALzBNWnSJAoICKBDhw4ZbV6+++47IiLKycmhxYsX0/Hjxyk/P5927dpFHTt2pHvuuYf+/e9/8+M8+uijFBYWRklJSZSUlES/+c1varQNjN+XKAJpuzyuDP5kDmC8lQf4x5VmQ2iRB4iRcBIA7/7LS5wH2P3jufTgvtke7WDsqSDjjo/iMDAKQhB+is+K4J6AmFSwLacLbcvpwj0BD+e3NsLAaAxdfK4ZXS4JosslQXSppKWGgqu5is81q/Nj0OW50PT8ckkQA2C2qPo9WdiSZ/9i/NuOnDCe/oEQMP7X4jL7cEHW/LQo/nAGAJSFH4MSJvP4N4SAe7kbQN/9l5cobOd8xxCwnAFsVACvcygAQfVvRU2gFQBVxE6I4AAAIABJREFUdSgFwBtcToUYLpeLNm7cSERERUVFFB4eTk2bNqWGDRtSmzZtaNq0afTNN98Yj/PNN9/QiBEjqHHjxtS4cWMaMWJEjTSCtl2/St+QfAXGyhzANxwKQdbHeuYBimKQ0qZNGABDP1rADqAcCwcHEHOBET4ae2w0jTs+imcDz059ghanDzRCwauzehtVwYBAhLGQ1C4ng6AiGNXAOiau+utUYWCdH4Muc2HmL9q+FLvDvvhAlFQQzJNzUPm7J7cTvXe2q9H0OT4rglZl9OPcWzSAnvflEJqR8iSnaow5OoZGHBlLwxLHc/hXAiCmfyD/r/NHCzwBcOtSzgFkAJQTQKQDGG/l/1U0BQRzgJcrAKpqVwqAKp9UFQC8LsCrAgC2flVMA3FXAge/ucqcBrKhvB8gene1ZgewCb/Bd/5ogQGBcAExFQQ9AYcmPkvDEsdzIcjk5OE0I+VJmvflEG48u/zUAHo98xHOR8J8YDSGBgSip5mcEZxT1IynhGBCiLqA1VvqAN5YC86fnPph5/0lF9xJCfkhdDC/LR3Ob0178zp49P6D8yeLrxanD6T5aVE078shNDl5OM//HXN0DE/+ePzwBC4A6XtwOoV/Oot6uYu/kP8XtnO+CAE3Ka8AFlNAjPw/pwpgh/w/OQUEAMjwpw6gqpalAKjySVUFwBoJAcdYALhahIHjrUKQDVZD6D+XTwSRABj60QIK2zmfuvz1Rbp3zwvU010IgnYwcioI5gIjDxAuIIpB0BNwdVZvLgYBAKIaGACIiuBjBUFGUQguiF9pPmC1V1aRVgHfaOu788F0oTiQLhQHMgDCAU8uuJOLPw7nt+bGz8j7w/g3GfpF7i3y/+amPkZTU57i9i8o/gAARiZMof6HptHDB54z8v/u3fMC3f2XlywHsInZAFq2gLH6/xkA+EZ5A2gDAF/2AoDLFABVtSsFQJVPuiEAEA7gsjhOqjYA8A2rEnidCANb/QBDtiwzQsCdBQB23VUGgWgNYTeFfvzwBHr66DPcE3BqylMcBp6d+gTNTX2Mlp8aQLEZ/bk5NFrCoIEtqoLhAKIgBNXAaIdxoTiQq4LVBazaOlmoIfQbZWHcGwCwtLg5j3tDKoSc+QvnD7l/+DAVnxVBr2c+Qqsy+jH0wf2beXIozUh5ksYdH0UTTozk/1UUf0QmTKFBCZPp4QPPGQCI8G/oRwvorg8XmgDodv8cw78WAHoUgHjpARiysrz5s+0AGvCnAKiqISkAqnxSnQOgaAPj1QG0AXCtVQjy9gpjKki5A9iEOu2IptCPFhgA2Eu4gABAFIMMTXyWxhwdw/3FEApGX0A4gRgPBxDEeDgAIApCUBSC8Fe+2wFEUQjyANEyo64v5D+mZecA6vmr/YVij4slLTj0i7/x/HPlDZ8xJxv5sXtyOxm5fxvP9PQI/y5OH8jwNzf1MZqd+gSHfsceG01jjo4xij8Q+sX8X0z/wAxgQCAXibkB0KgABgA6OIAMgD6EgB0BUPQAVABU1aQUAFU+6YaqAo6J4zdUx0IQCYB2Q2j3aDgbADtuj6a7PlxoVAP3/GQOF4PIPEC7GnjCiZE0I+VJIxdwYdpgis3oT6sy+nkAIPKYduV2pj25nWhvXgc6nN+aKx9PFQbywpxg2RtQnUBz2efDhuS0Qu/zlZ226/n1/0KjZ3yVo97Q+iWpIJg/CMmZv8j925bTxWj78nrmIxSb0Z+WpkcauX9wAJH7JwFQ9v5D/h9Cv2j/EvrRgrIQcFMzBMwFIJuWe4aA1640G0A7tYBxCAEb8KcOoKqWpQCo8kl17gBKAFwWV/6G+uor3GrBsRJYhIHtfoA2AMIFlFNB7t/7PD24bzY9tH8mt4QZlDCZhnwxkQFQFoRgRNzc1MdoaXokVyZiRJycE7wtpwtPNkAu4MH8tuyEyKKQYndRCKqC66OLZYPZ1fMh7CrhNkxRwTm6cr4MrGUlNYoQfihta4TWFfxq7nW7ej6ELpa04LSGC8XlDdAx7WN/Xns6nN+aEvJDaE9uJ9qf15525IRx3qxs+rw6qzfFZvSn5acG8IcuuH/o/Tf22GgacWQsV+4j/Nv/0DQe/wb3D85f2M751GlHNHXcHm28PxjVv3b/P9ECRub/sfv3ugWAK8tbwNjun4cDuMh/ANhhoQKgypQCoMon3RAOoJ0DGFceBmYAfMMaCfdHKw/QDYGttyyj8w4A2PmjBewCdv94LvX8ZA5PCehzYAZFJkzxmA085ugYevroMzThxEgjF3B+WpRjc2i0sEBCO5xATAhB+wv0B0STaIyJQ/uMur6w+xsS5M8IGdr7ANzk/hdLWnBuGfononr6QnEg7c9rzw4qHCgAYmlxc4YTPO+F4kBHKPQFECWYy8Kd+gaX+H0B4RdLWtBX7l5/cs4vxrwdKwjiUW97cjvRztxQ2pbThXbmhhp9/+zCD1Tew/lD2xcUfqDxc9Tnk6j/oWm8MPsXvf+67nqRiz/u+nAhddoRzQ7g+aZNOP/PowBEtn+RAGjn/8X5NgXEwwFUAFTVoBQAVT7pehzA6kCg1/taDqANgBwCtmcCr/UsBAneVOYCnrdyAAGBshoY7SHQDkb2BByWOJ4vMhNOjKRJJ0bQhBMjeQbp3NTHaH5aFPcFlEUh8VkRtDn7XtqcfS9PN7D7AyYX3MkXyXx3LmCpmBX8Y3QBvYHQd+eDjdvg4kmoAlDJ31vOkb16PoQuFAdyiBGO0+H8MgCR+wAI8935lShMwH7y+eXxyeO0Yc92IeF8Of2+P8bX7noWAB5fvxKTPvLdC/l+KPjYn9eexyWiXdLGMz15pOL6M/exm46wLyZ+YOYvnD+779+QLybyWEe4fw/um83h3y5/fZEbQDs5gKgAxvtH0P+uKC8AWbvSzP970yH/z+oBaMwAdnAA/R0C5rGcCoAqIQVAlU+60RxAVNQZDqC3QhAAoBUGlgDY/oPF1P6DxR7FIHAB79/7vNEOJurzSQyBTx99xmgMjRFxc1Mf49wkJKvL9jCbs++l9WfuYydQtohBLlRSQTCdKgzkcXHZReUVwrJHYF06TP6AGRm6/e58MJW6AU0CBKAN2+HwITSO/QBxF0ta0OWSshmy8mdUnwIUvzsfzO4qnue788H8mBK45fNLCMfrAQCV1a5wGOV5qi0ArIsxeNL1u1TSkuEvXzR7zipqTicLWxp/56j4BQDKwg858QOVv3D+ZqQ8acz8nXBiJId+hyY+y21fBiVMNoo/JACG7ZxPYTvncwVwh22LGADPN21iVv/C/fPW/89L/p90/0K8AKBHCxg/OIDGXHYFQJWQAqDKJ10PANYIBHoDwDgBgPZEENkORs4GdlcCSwBs+94S6rBtkREGtmcDAwIfPvAcQ6DdEgZhYIyHQ37SvC+HsAsYnxXB/QGxJADuye3ETXDRJBpOIHICMTO4VISF6woAr2dSiZ2L90NpeU84CVhfuX83CRB2axy0EJHQh5/RSLu0uDlty+nCP6P4ANXV2C4BsND9GABAwJ3tEuJnjDIDKF4oDmSolL+LDFEDCG3X099gWBcACIjH741zih6XcsYvJn4g7Cvhb8vZbhz6XX/mPorPiuDCKlT+ovhqaspTRuUv3L8hX0zk6l/874Z/OssY/Ybcv7Cd86nzRwuow7ZFRqP4802blLt/GP/m0P6FC0AwAs6L+8fhX18cwGoCoAF/CoAqSwqAKp90QwPga57tYAwARDGIuzE0XEAbANt/sJg6bo/mnoDIBUQoGD0B4QQOSphMgxIm0+OHJzg6gVNTnmInEL0BURjyeuYjtDQ9knMCMSUEg+7RKBrzguEE5p8rzwmUoUw7hFpVR7Aq9/MVMmRYFcf8Q2lbBij5+wD6AHNoFgyHDfBbKJyl0uKy8wK3FNC4K7cz346ec6hARWgdOZYITwJesGQBA4ATDiS+4vm+cv8u+efKQT2nqBmHny+XBBnj/gCGdnGPDCVXFca+Kq75JtgyJH71fAi3ecHXHFHsgeImFDztz2vPzh/Ab1N2D9qU3YPWnn7A6PmHti9L0yNp3pdDaN6XQ2hqylM04cRIA/7wgQzwF5kwhUe+hX86y6j8RfgXlb+ddkRT+w8WU7v3F5cD4K1NuPrXY/qHHf61R8DZALjKcgBja84B9IA/BUCVJQVAlU+6XgD0OwSKHMB2S+O4os4jD1DmAtr9ACUAblpO528t/4QPAIQLeNeHCzkXEGFgQCDyARFWGvLFRHYCcQFCKAotKZAPiNylVRn9eFYwwsGbsntws+g9uZ34AokKYbSIAcAUC/cLoeDqOkiAjuu5T6EYtYbjANjA1QKgflXcnMODMoyb787ZKxZOXbF7W6kFVIUCtFBJmi9AECFzfN2W04WhOdvtoOJnOYMZzmpywZ0MltJpRQ4bjhHOVmlxGXACSBFGxrECZnEf/C42KGHJ0DMcR5kHeT1ur3xtamrh2BCux7kC+OYUNePefmjxgjxXwN+e3E7cI3NTdg9u+AzwQyEV+mvOT4uiGSlPMvih8ENO/ZAj3wCAaO7eUxR/yNBvx+1lAOjhAEoA3GC1fwEAxpf3/2MHEBXA9gi4lZb7V9EYuOsAQPm+qwCoqkwKgCqfVBUA9CsE2m1g3J+oPSqBkQcY7yUMjLFwfzIBsM3WpdT2vSXU7v3F3BOws8gF7LZ7Hk8HkQUhMhSMquARR8byRQmtYeamPkbzvhzCEOjUJBqhLoS+cGHclduZQ8JwUAA7gAvkt+FC7C2cWJmbZDuJuA/W5ZIgI+fw6vkQyilqxu6PnT+HSluAKpw4/AxIQm7jqcIyJw2gi7xH2TQ4X8AZYA7b0FIkq6g5w917Z7vyY2DSBPLQjhUEsTuFMGVywZ3cegfPA6dQQigAHMeA4zlVGMjwgxBztmjqLZ1HnAs4jtJZxGsKAAYMSugCtOM1AWzjtmz3a+Mv2MNj4/nwWuM47Nm+eP2SC+6kYwVBHuPdkPOHSl84f+jzF5fZx8j7Q6sX2e4FIxlRjW+7f5EJU6jvwemc93f/3ufZ/eu2ex4DYKcd0dRh2yJq/8FiY1Tk+VublM/+/V8xAWStc/4f2lJ59P+zC0BiHcK/Tg7gIt/fJx2hTwFQ5UUKgCqfdEM4gItMBzBkVZxnIYiYC+wRBgYAuvMAbQBs9/5iDxdQNoaGExj+6SxuJNv34HQOAw9NfJbbwow5OsYIBaMyeN6XQ2hx+kBafmqAx7i41Vm9aeOZnuyE2M2i4QriQgrAwZLFIah49aUiVS67qERe8AEXABPASlZRc4/8OBkKhbOHECyOE+5ZdlEzzm9MK2zBYW7kPeJ7OHoAOeSRyebZct+ThS0prbAFbc6+l7/HecP3SQXBxn1wPwmfcBMLzzXj27DgcJ0qDDRCnbgN4AnXFiCLn+EuSiBE7iPyDHG+UEyCcy2XU8ucq+dD6FRhoJF3Kd06fwAhYFVCLF4/+RqizUtSQTC72rLVy5az3TzGvMH9i8vsw83VkVeLvL9JJ0bQ00efoaePPkNjjo4xCj8GJUzmnn8S/pD7h7m/oaL1S8ft0dTu/cXUZutSThE5f2uT8ty/jbHl0QSn8K8PAFhZC5jqhoAVAFW+SgFQ5ZOq6gD6DQQdANAIAb8mGkJLAJQQiEIQ92g4CYAhW5Z5uICyMfTdf3mJm0PDBXz4wHPU58AMHhGHUPDwpHE04shYevroM+xOIFkd+YC4oC1Nj+SZpmtOh1NcZh+PZtFwSDAaCw1z0UbjVGEgpRW2MPLYMD4OEAYItIEQuXjYjvtdKA40wA9QJ0O8AMC0wvIJD8iTgzsGEIRDJx09wCBChNlFzehYQRBDGNxOgBpgAr8vqkgxSxkuE9qKHMwvmwO85nQ4JeSH8G0J+SH82An5IR4gCSiUkA2gAUjiewAqjkGCZHLBnQyP2A9QhP0kTML9lGFjOJGlAqYBhwByFM7IqnCA4anCQKMaGa83wrUSHG0olH8nMs/P7rUoQ77yHOH1SC64kx0/9PnDbF+0QkJFPBxxTPlAs2cUUiGlAi2X0O4F7p+c9ysbPod/OovhD84fev/d9eFCuuvDhdwJoO17ZVM/PABQTv5Yt9K38W8OE0BkAQgDYEUhYH85gAsUAFWmFABVPqk6AOgXCHRyAF8WDuBrVhj4TYc8QGs2MAPgrWV9vkK2LGMA7LBtkREKDv1oAc8I7ikKQh7aP5N7Aw5KmMxzgnFRGnFkLEPgpBMjOHQlewQivIX2MHJm8Jaz3YyG0Ttywnh+MKBFAkWO5TTJYgo4NQA+NOcFvCGnTk4cwQUeF3m4eSjIKD7XjA7nt+a8NoR4ES6VIU/pqMlq5qyi5nQ4vzVlFTU3QoUAKsAuqkYl7MlqaYDG4fzWtDevAxcaxGdFGBXVGDOG3nPYhttxX0CihBk5sg8L0Ajow/7ye1S74v4AWuwjFypl4RSeLGzJYWeZ/4iQMcLpADL5PcLRgEfcJiuTsQ0wKXM2pcuI/a6cb81/TxeKA9kdxWstf2eMdwP04cMMij2Q9rDmdDityujHH4bgkC9NjzSaPUvnD047Kn4R+h2UMJkB8KH9M3neL/53Ze5f2M75Ru5fu/fLwr+tLQDk8O/6isO/yEO2p38wADpVAC/zdAA9JoH4AIEVgt8CBUCVpxQAVT6pugBYbQi0AdD9hmoXghjtYLzlAbrbwTgBICDQ7guI3oDIHer1yRx6aP9MevjAc9T34HSuCsa8UekEylFxCAdjbvD8tChamDaYm0XjIvh65iM8+H7L2W4cLkPSPCAQgAKHCRdiWcAAZw4AIEONyEuD65QvXKevHPbBfWWRREJ+iBHqzBFLAp8EPUDcqcJADg8iLAtAQtEAYBcgaOeSJeSHsMOHcDnOz8H8trQ6qzf3VtyV25kbbsOVwmPI4gTAGo4BDYuRh4ljkl+xL/ra4f6oepWOJn5H6XjaYWjsDydR9oGURScyHxHOKuAsqSDYCMXLUG2pAEeZcyhBUvbyk8Us8u9Mgj0gHucBML4rtzNtOduNWx3ZAIi/ecBfbEZ//r+YnxbFeX/os4mKX8z5RdHH44cncO4fHHq0fen+8Vzq/vFc6rZ7Hrd+6eyu/u24PZrbv4RsWVYGgLdaAIjqXxn+XePg/v3eYfybDP/GVtwD0GsRSCUQWCEAqgOocpACoMon+QMAqwWBdhUwZmqiECTOwQWMd2gKLWYDGwD4Tgy1dr/x2wBoF4TASZBzguEEojIYTuDQxGdpWOJ4nhksi0Nmpz5BM08OZSfQbha95nQ4rTkdzm1iNmX3MFxAwAuAQzqBuBgD6OC02c4RwE5WayLECcgD1CE/D9uRt7c3rwPfB1CHhWMCBMkFlwwACEDD1525oXQwvy0DHaBtT24n7h2Hhbwy3A/nZlduZ4rL7MOPgRY7O3LCaE9uJ9qW04VDk4BAFCfISlXZsgSA6HRseAwJpxIGAX978zrw6yadXAl+Ms8RLpsMn9t5iNIlBKABzmXvQ1mlLPP2JDjig4JMKZAfBGQltYRWgLl0/uD6bcvpwgVOCPki5w+j3WIz+htNnpE3Ozv1CWPMG3r9Ycwb0i8w8QPNnmXPPxRyydYv3ty/1u/EeAKgw+QPBsB4z/AvTyt6xWr/IvP/bAD0VgRSAfxVGvZVB1DlRQqAKp90QwOgOwzsNBfYoyn02vI8QPkG3+rPMfzJv83WpdTm3SVGGPiuDxdSqNUgutcnc4xwcN+D02nAZ1MNNxCuBHIC7bxAOTsYjgfCXwgJy7AwGkZvPNOT3SwZ0pQgKHPQZH88wCDAAUUV2UXN+P6APPv+CE3KbTtzQ9m9k7NdZbgWACQhCbOPAVr2LNiduaGc9whow+8sc8kAcztzQ3m03racLnxbbEZ/hsJduZ3pvbNdaWduKO3J7UTvne1Ke3I7sTuFPoxwWeFe4dhwP/wMNxGj/PAc8hix4BICHPGzbI+C11C6jHvzOhh5hQBrWfQCBw65lADD/XntPSqps62/BTjFTpXOdkoBvpetdvA6A3RlaxcAOVIa4Gqj/ZHM90N1vIQ//G9I8Hv66DNc7CFDvlgI/SJXVzZ87rZ7Ho98k5W/7d4vy/1rs3Upj30zAHC9NfnDzv2T7V8qKwDx4gBWNQewUtdPAVDlRQqAKp/kMwAu8A5/1YJAGQJe8mr5J+pVFeQBviGaQq+xXEDLAcR84FabYxgAZTEI8gDlnODuH8+l+/c+z21h+hyYwVXBKApBeEoWhow5OoZdwBkpT3pMDUHYC3NP4QjKptEAFlkcAhCU4VHknAEc4CahAAFtUFCEgBCndO9kJacMS8L12ZETZjh8ssJWhlHh0skQKbZLKAOYyZAhYA4OKLZvzr6X74uiAjhNyDVbnD6Qcyl35IQZ+2w805O3YyHkbruFEjZlQQOaGOPYULhj/z5yf7i40r2EY4bXUbqah/Nb8zk+WdiSz6GdAyqroU8VBtKe3E4cZkY+IQo1ZOgW7i6ajcs2PLJYBbCJ3EdZ3ZuQH8Lwh3O/IyeMGzvD8cNUj9czH+FWSAC/+WlRDH4zTw6lmSeHsvOHOb8AQEz6QEN29Pzre3C64fz1+mQOdd31ojHvt7MY+dbufU/3zwMAN1TS/Nnu/1fRBBAH96/CFjBeALDSli8KgKpKpACo8kn+BMAqgaA3AHw5ruJ+gHI28B/MYhADAN9eQa3+HMOh4DbvLjEKQjpsW8TNoWVrGDSIRlXwQ/tnGj0C5aQQQCCS15ETCBdw5smh7HygQhhhMYCgDYEAC8CGdNPgNqEaFk6cnYMGGDtWEMQg4lRkIR0qmSO3Ofteo3gC7pgMkeJnNLm23TOECO1CAUCXnJSyLacL55GtPf0AbTzT0wgrIr8M52l+WhSDnoQR9JyDM4Wq6/isCGM0H44L38PVAiTCecSxomAHIInHxWuFc4DHABACKrENrylAFK+rPP92SB3bUYSxIyeMoV0WtMgiFYA8bs8WYV1ZpIKf8UFAQp/8WwPw4ne3p3qg5RHy/WShB4qk0D8TjZ7tKR+y1Qtcd8AfQr/3732eiz7Q7082fZbuX5utS8vcv3fKPgQ6OoDS/XvLKv4Q8IdohCP8VTQCzqkApDoAaMOfAqDKkgKgyiddFwBeJwT6BIMVACBCLB5hYLsnoOUC2g4gXEBAYNv3lhgTQhAGtotCeopQMHICEQ6WOYHDEsfzyDjZvkIWhyA3EAUiaByNkDB6BgJ8ZLsYhB+lQ4WLM3LOZCsUCXcIJW/L6cIQKJ07CXO4yMOhWn/mPnZ+EPoE1EhQAhTBMcPxbcvpQhvP9KQdOWHcCHvjmZ4MdnD2JOghpAggBtihofba0w9wkcHc1MdodVZvY/Yyei7CWZX3WXM6nAEbYXcchwRMbNuW08Wo2sZx4vXB/oBKwK0ESzkHGuCH1xTFPzIcjddH5iXK/EO8du+d7WoU0sChRT8++YFA5mTK71HI4vS8MtwLtxTnA+cNaQzSzUbIF3mvcP7QLklO90C7FxR8yGKPQQmTqe/B6ezA2y1feorwL8a9Ie9PNn1G+gfcv+C3zS4Bxtzft4TzZ49+cyr+WGVV/1YEgNIFrAAArwv6FABVXqQAqPJJ1w2A/nYCHQCwjXQA5Vzg1zwBkCHwrXII9ADAP5WtVptjPNrCSAjs7M4FhAsICMSouPv3Ps9OIEAQoSokq6NthR0Snpw8nMNecAMx+H5VRj9aldGP4jL7UHxWBIfUkFgvgQsukgQEQAIKHACFMhcNgIb9cZFHKBJfJWTGZ0V4hT6EWrEAUPKYN2X3MNxNmSMG2AVESIjDxIj4rAi+j503uTqrN81NfYy/B+Dh8fGY8rlQgCOfC0CK+24805OfV+4jfwdsw3MCUlH5KnvgSTCUoW7kJwKwkBcJsIe7itsROsbPm7J7GI3EAfAAeunqShB0KmbB/WQeIwAVLu17Z7vyecBrgv6WcPzw94zefviwg+p4VPqicAoNngF+ssmz3etPOn/o94ewL3J54fyh6hcAGLJlWdnItz8t9wRAGfp9ywr9ovWLL82fnQCwojnAFgBWyfVTAFR5kQKgyidVCQB9hMCqtIHxCAG/YlUD//4Vj9FwdkXw+VvMKj/pAspcQFkVLBtEI6eo2+55DIKoDEZhCMJSSFBHxSJAED3MMMcU4S6Mj8NCpTDCwnBTMCorPivCcMykyySBDKAGeJMhWcAG9ofzJIsjcB8Z/ozN6G+Ea3fmhtLGMz2NHDCEWOOzIhiEAEmAMTn7Fb+bvU0WD+C22Iz+fLssKkBLncnJw/l7hB5jM/pTfFYE3xePKR9ndVZvhkEJoYAaHAtgEL+LDaJYeAw57QKwCFCUbqYcjYY8RZkXCfiSwA9IxGux/sx9/HpLQJegLiFSVlXjsfCzHN0mw9ZwoQHJEswBfijwkD39ZK6fHOmGtkmo9EUOLca7IewrZ/zaOX/37nmB8/4Q+pXgx1W/W5eWu3+VAaBd/PGm2/1zav4s3T8HAGy7vJIcwOo4fxWBoAKgSkgBUOWTqgyA/oLAShxAmQfIYeDXvQCgGwINANwQWw6BwgVs/U4MTwiBC9hxe1lRCApCuu4qbw8jK4ORF4iRcZgaIiFweNI4rg6WI60QFkZIDAnxmCACR1BCD1wXwATAS4ZR4TbBkcNtyCeUU0hk6FMWTsjbtpztRrEZ/T32t8Oqcr4rfgZMxWdF0NL0SCPXMS6zj8cC/KJfHHrFIY8MRQUAZYQZJycP55xKGXpcldGPFqYNZqDGcy9Nj+SfAYEARbivcuF4AKgyxw0ghK94HOnmAjJtaLSdRhkWx7kHJMrXQxa7wHGVuZNyP9u9s/Mb5d+GDfm4P/7e8HrL6l4Jf+h56TTPd8KJkVzlK6d6AABlxS/Cvv0PTTPavQD+ZLNn6f7Jdi+o+AUA4kMf4M9oFH9LE++NnyuY/CGbPxvVv7GW+xfjW/i32u6fAqDKkgKgyidVOQTsr3CwDYDukUohXiAQAOjoAq5joizYAAAeeUlEQVQBAAaYALgxloLfXsEFISgKwZi4NluXsoMACEQ4GE6gbBTdS7SIkQ2jIxOmMAjKXoEAQNkvEKFhFIogJDw/LYqhCMAk28XAkZIgCIcJF3+7IAIOFkJ3ADXp2AFAAJtrTz9A89OijJApgAcOHeAG4BOX2YdnIGMtPzWAXs98hBtiA9TwM6ANVaMAQAmBAEGEGLFt3PFRRsNtQHRsRn+anxbFjYcxcgz74bnxuDjfOH64jLEZ/T2OG/fBNttplGC75nQ4vZ75CL9+cAZxDmXOpzz/+Fm+tjLsvDn7XgZuuME2JGIbPhTI4hdZWY0PBXD6ZIhbAizCvfZ5QLh3bupjHOrFB5vJycPZ/X766DNcMIWwLxw/gN+Az6Z65PphTjeq8zHpQ+b9Af5Q8SudP6R/yJFvBgB6y/2zKn89ev9JABRVwIYD6BQC9hX+FryqAKiqshQAVT6pWg6gnyGw3ZJX+Q3VMQxst4RBLuD/mH0BGQBvcSd5u8c9cShYACBWm3fLw8F2YYh0BGVIGGHh8E9nGaPjcFFDpbBsGYOkd7gjk06M4HYxEgJxcV2cPpDdJMCEDF/KnCx58UY+Gm4HXMltWDJkKcOj89Oi+DnhoklXDY8JgAI4yca/sgUOXCIUwQDeEDqU++F2bMf9JMiNOTrGcJ/kY89OfcJwp/BY9vMALOX3cBuXnxrA9wdE4vWR017ghEnHUp4b6YDK8D4gEa8fnD0ZcgW8y6+YrQuwtHMV8dojbw/QKIFPFrPgg4QM8645Hc7wviqjn5Hf5zTCDeFeQB/W2GOjubULCj0Q8sUHJjvkiw9Z+F/D/x0+kNlFH3D+kPfHRR9w/v60vOw9YIPVJ/SWgIrdP9n6Je468v+8TQFxCP9W2/lTAFQ5SAFQ5ZOqDYA+wp+vANjGBkBrLJwRBl5tuYDuGcEGAKLR60Z3KPjtFUY+oGwQ7TQpBCAICLR7BWIhUf3hA89xErsdFpYgiLYXY46O8ZgiAhi04QKAJfOvkNMGSJOOnMx/A4RgP4QjZV6ezJNbldGPpqY8xeFZQB0gRy5AESABodqFaYONFjgAs8nJwxnGEA6f9+UQ3hffY5qKHBmGfWanPkHDk8bxfnCf5Pd4fpmbhjAlnmfel0NocfpA4+fZqU8w7MxOfcKAUfm9fCx5Ox4P3wMc5bmSkInzCygElNu9ImWoGpNlVmX043m7uF22FrLDzhL4Af3YF0AqnVgJxjh/OEczTw41Qrzjjo/iMK+c44swLyrnUUWPNi+AP4R8u388lx13fC+rfTtuj+awL6p92763hAu80PA5+E/L+UMfA+AGBwB0mvrx+/L3GeT+eXX/Yq0egA4AaDd+9uk9UwFQVUUpAKp8kl8A0F8u4OJXy95Ir9cFtKaDlANggDknGAD49oqyfECHUDD6A7b/YDFXFiIkHLZzPiegowcZ5pBiMD3Gx6FSGDAo5wlHfT6JXRGEhnERleFhAA3gQoZBcWGWcAFABCwihImLNyAQIVS54FTh59iM/jQ5ebiHu4VjsJ00HCcAQcIeKkAx9mtqylO8fcKJkewg4SvChzgPAA1ZUT05eTgNTXyWHwePi0IbPK58LhwDwpQATzhZCGMCdOz2PTNSnmQ4lyFPeR/Z+xGPiXMCYJyfFsWPBUgEFGLhNQUgytA04F+GoSWk26Fo/E3YIXrZs0/mSTrBH17juamPGX38JPyNOz6KRhwZy/Oy4fjJMC+qezHVA2kUMuwL8Ov5yRz+0AXnD/+TqODnKR9i5GOrzTEm+Ml5v+tEkdgtAeXw5wUAZe8/e/SbDYA+hX/9mfenAKjyIgVAlU/ySwi4Ok6gHAW3xA2A7pCKhwtoQ+DvX3FsC2MAoLs5NEMg8gHdFwgbBNEeRjaKhhsIJzD0owVcHIILlSwSQb9ANI6WjqAMC2PBEUS1JBYgBe4XnBfpZMkwqQzPye3yfjKMKveT4T0A3JijY4yKZScHCF9R3SwdONn3bWrKU5wDiQVgG3d8FEMc4AL3wddxx0dxeBHwMeSLiQx8MuQ4OXk4PX30GeO50H4EzyshG88rx/gBGLE/ihokPAIm5TmQIX15nmwHEkuGsAGCAGtsA+hLIJMjBgHm8gMAgFAupw8A2I60AxmCl9NscA5kDivONwo80A9Twh9SISITphhFU0ibCP90FrdbwocpmesnF+DPccavCPsaAOjO++OGz+tWGu8Pxsi3N8TIN7v4w2r+XKEDKAtA7AbQvoZ91QFUVUMKgCqf5DcArG5VsHQAAYF4o5WFIDIU/JoDCL7hAIDuN34PCERhyOYYY1qIzCcCCCLsJEEQ00O67nqRQ1XIX0J+4MMHnuNmtoBAjJNDWBj9A+1iEQlIuAjDKZNOFrYDMBC6lGHTSSdGGOFlCW+4P4AFa8SRsR6QJ/sZ4mcAmsxrlIAgq0ARFkQVKMKFskXIuOOjjHMh7yt/HpQwmcEZuZUjjoylccdH0bDE8TxlAl+xD45HwqHdqgTbZM866XjJx8V2/P6y0lt+782RxOthh5qlmwpwhKsI4JYhbAmXEvBlWF6GpBGCtnMb8RgSjOW4NlS0o7BjyBcT+auc4YuvdpgX4IfemrK3Hyp84brLXD84f7LaV1b64v9YVvyy8/fHlTwtyAMAkUZizfyVrV+M8K+XCSB2E2gn98+vrp8CoMqLFABVPsnvAFhVEHQAwBBfAPB1z6IQAwDliKd1bgB0VwYDBIP+d0V5i5h3yvMCAYKYHQwQRL9ALDSPRrI63Ixeom2MnSMoh9zb/QMBRrjgAooAF9KZspvs2lAHcAP4wNWRTpYESwl1UZ9PMp5PTnCQLT4w0UECH1y5xw9P4NYfqP5EmxxUS0d9PoldUThIcJNQPCC/x8zYvgenc04l7oNzhzDk8KRxRiGCBE6ADG6X27BdjviTuW14LDwfbpduLh5DLpwrQCUcTgmF8rWwQ9a4TTqr0oGVjjF+BsTLxwLwy9vknF685jhGe1wbXhMUdGBJxxuNnB/aP5N7aCLUi95+cNEBf3D6ZLgXjh/+F9u8W97qBfl+rf5c7vo5wh8+BL5lpog4zvv11vrFyQGULWBiPPv/cfNnfxd9KACqKpACoMon+RUArzMU7AGCEgCdWsG8UgEEegNAa0oIh4PdCeGyRyCPjENlsIBA2SsQENjZDYDID4QbKBtI93S7gXAGEfrChREXSYSHAUMAIuQLwjXDlBEAhIQLXKhlfhagDNAjQ6i2c4XbcNEf8sVEA/ikQ4b7S5dOAqt0iAAMctoDCgPQABi3AYYBxPI84PZhiePp8cMT6KH9M9lFhfOE55KhdjwWxvbhceFGOkEkgFW2LhmWOJ5dRrwOgD48jnRyUfUNiLRDprhduqROcC3zH/E9Xm+ZEykdRtsllqFufBDA/eVXGTYH2MpqXpwbvJ54/fBhRqY+2FM84Pb1tCp87cbOAD80aMdcXxv+eMbvn91hX7ejz3l/GwT8iX5/HgD4P2bol/P+vIx+8wj/OoyAM9y/6s75VQBUXacUAFU+ye8AWJ18QDcAtl1uhYAdpoJ4hIBRFbz6FY8QD08JEfOCOS9IFoe4XUBcUOyxcQBBAKDMDQQIImldXuCQ1yRhEG4IwsN2iBjVw4AVG0qk2yXDqoANQAlABM13JaBJSLO3jzk6hgZ8NtUDePC82Cbbe+C4AGU2uEloAOQBIGSuGMaBAYhlj0VZTPPQ/pl8P9laBPfBvjIsKd0qeY7l8dmtSgCtcl/sL7fLvE75WklnV54/+RrJMLh0FHEbXle4i7KlkA2REtCdQFF+AJC5kbbrKY/XKcQroU8WeAD6EO6VUzzw4ajb7nlc2Yv/ndCPFjhO9ZDhXi74cDv10vmDq88f7pD3t9ac9mG8P1jw51T44RT+rSj/z2j+7Ou0j+rk/ykAqiwpANYzxcfHU6tWrahRo0bUtWtXSkhI8Ol+NxQALnq1DP5EJbDHXGAvLWFkHqCHA/iHl41JIRwOWifcQNkr0F0YIvMCbUdQFonY+YEoEsFFDjAIEEQIDK4IHEHkSuFiKoFHwgdCp4AuODMSMhCqA4Ag1CxDqAjJAuIksAxLHE8PH3jOeF7AG1w1AJ6c5ADgw/dywgNagMjqaFkVKgEYUAxH6aH9M7ltCB7j/r3PMxwOSpjME1kAJYBG5KFhX4AdFo4r6vNJfM7lfngM7Ct/L/t73E++btLldHIzAeAStgDX9muL186+r8ynRDhbupS2S2uHqGWIW4Z5JbQDqvGa2bN6EeaVbl8vUdwhx7ihp1/YzvnU2Q1+cP3g+CEPF6HeEBR6/Lm8v58R8kVqh0PYV/b7cwRAp9CvNwB82TP/z3D/llxH2NcGP60CVvlBCoD1SFu3bqUGDRrQunXrKDMzk6ZPn04333wzFRYWVnrfGgFA+WbmAxBKAGy31MEBXOlcCeyYC/j6K3Q+wAzxBK152TkUvD7Wa59ADwh8x+wZCBhEOwo4g3Z4GPmBWNIRRJ4gIBAVxLJ6GCAjnS/5PRwrGS6VzacBarICGYAnw6nyvoC98E9nGeAnXTN8lY6dDT9ytit+FxsAURwA0APsyfMBuMBX3Kfb7nkMz8ivRNGNLL7B9w/um83gIqe34DjksQIisU02+JavjQ2vuA9+llArXzfpaEoXUzqQgxImGyF06fxKl1W6w9hPAr3sPwmYlPvJx8Yx4AODBF8J6/K1AvTB6ZNj25xm9wL68IFJun4yz48BUE73eMdq7izDvQA/O+xr9fozAHC19SHSIf+Pw792A2gbAN25fz4XfVS38lcBUOVFCoD1SN27d6eJEyca2zp27EgvvPBCpfetcQC8XifQhsBY7yFgj1Dwaw4A+MYqfvNnN1CGgtetNCCQq4Nlmxh3cYhsHA0nUOYISgi868OFXMVoF4xIZ7DrrheNohE0lQYEAQjtvoJy6oh0qSSUye0AE8CHDLn2PzTNgEsA3v17nzfcMgl6EuqQ7yWdNuwnQ9yyKEBulzmRsiEwAFBChpy80uWvLxoTWeSsZntSCyZMyGIcHIesTpU9HOUx2lCJfZDHaYOlBEEZ3rfhEdAsXUac3z4HZniFfwmQQ76YSAM+m2oUZMCltfMp5TYZ0rVbtsgpHXZBh3T9AHvS8UMTZzjfcPpCRZgXeX5w/eD4tXt/MX/IkpN6jB5/7ipfOd7NgD8Jfm+Vu//o98cAGBBgVPwy+DmFf50qgC33z6nfn0+FH1oEovKzFADrib7//nv62c9+Rtu3bze2T5s2jcLDwz32v3LlCl26dIlXUVERuVwuCpm2kNo+v9z7mnOda657ye8rWG1eMFfISzEUsjCGWi+KoVZL3GtpDAUvi6HgmGVla3nZCloh1spldKZJE7rkctFFl4vOBDTxYTUuW7dUsm41V7b4aq5feayz4qu3ldP0Zq8r172ctvmyfNv/JuPns7f+qsLHcjpGb8fq7T7Xc7u9KjtntbWcXhdvXys7/3m3la3y1+Imj9fF/Bn727eXP5YvK7fpzeJxzMfz5XXwZTn9X9j/O/b/WKX/k1j4H/bh//2iy0WXXC4606QJBcWa7yP8vrIshlerpe61JIZaLS5brRe5V3QMhSyIoZCXYjzew7Ac3/Pk++T1vrc6rYreu59fTiHTFpLL5aJvv/22ti5NqjqUAmA9UUlJCblcLjp8+LCxPSYmhtq3b++xf3R0NLlcLl26dOnSVc/WuXPnauvSpKpDKQDWEwEAExMTje3Lli2jDh06eOxvO4CFhYXkcrmoqKjI2H6jrnPnzvEbWV0fix5v3S89Xj1ePd7K17fffkvnzp2jH374obYuTao6lAJgPdH1hoBtXbpUlgN46dKPIzdEj7dmpcdbs9LjrVnp8apUCoD1St27d6dJkyYZ2zp16nRdRSA/ljcgPd6alR5vzUqPt2alx6tSKQDWK6ENzPr16ykzM5NmzJhBN998MxUUFFR63x/bG5Aeb81Kj7dmpcdbs9LjVakUAOud4uPjKTg4mBo2bEhdu3alzz77zKf7XblyhaKjo+nKlSs1fIT+kR5vzUqPt2alx1uz0uNVqRQAVSqVSqVSqeqdFABVKpVKpVKp6pkUAFUqlUqlUqnqmRQAVSqVSqVSqeqZFABVKpVKpVKp6pkUAFU+KT4+nlq1akWNGjWirl27UkJCQq0fw/Lly+m3v/0t/epXv6Lbb7+doqKi6PTp08Y+ERERHmONhg0bZuxz8eJFGjlyJDVp0oSaNGlCI0eOpL/97W9+P16ncXp33HEH337t2jWKjo6m5s2b0y9+8QuKiIigU6dO1cmxEhEFBwc7joX63e9+R0R1f24/++wzGjhwIDVv3pxcLhft2LHDuN1f5zMtLY3Cw8PpF7/4BQUGBtLixYvp2rVrfj3eq1ev0pw5cyg0NJRuuukmat68OY0aNYpKSkqMx3B6TebOnWvsU1hYSAMHDqSbbrqJbrvtNpo6dSp9//33fj1eIqLRo0d7HEuPHj2Mfa5cuUJTpkyh2267jW666SYaNGiQx1ix2jpeb2POXn75Zd6nts6vL+9d/jp3hw4doq5du1KjRo2odevWtGbNmus6VlX9kQKgqlKhf+C6desoMzOTpk+fTjfffDMVFhbW6nH079+fNm7cSKdOnaLU1FSKjIykoKAg+sc//sH7RERE0Pjx46m0tJSXPdj80UcfpdDQUEpMTKTExEQKDQ2lgQMH+v14o6OjqXPnzsaxfP3113x7bGwsNW7cmLZt20bp6ek0bNgwat68Of3973+v9WMlIvr666+NY923bx+5XC46ePAgEdX9ud29eze99NJLtG3bNscLvj/O56VLl+iOO+6gp556itLT02nbtm3UuHFjeuWVV/x6vN9++y316dOH3n33XTp9+jQlJSVRjx49qFu3bsZjBAcH05IlS4xzfvnyZb793//+N4WGhlLv3r0pJSWF9u3bR4GBgTRlyhS/Hi9RGQA++uijxrF88803xj4TJ06kFi1a0L59+yglJYV69+5Nd999N/373/+u9eOVx1laWkobNmygn/zkJ5Sbm8v71Nb59eW9yx/nLi8vj2666SaaPn06ZWZm0rp166hBgwb0wQcfXNfxquqHFABVlap79+40ceJEY1vHjh19miBSk/r666/J5XIZvQwjIiJo+vTpXu+TmZlJLpeLjhw5wtuSkpLI5XJ5fCKvrqKjo+nuu+92vO3atWvUrFkzio2N5W1XrlyhgIAA+sMf/lDrx+qk6dOnU5s2bdj9upHOrX3B99f5fPPNNykgIMDot7ZixQoKDAyskgvo7XiddOzYMXK5XMYHq+DgYHrttde83mf37t3005/+1HAOt2zZQo0aNapW02BvABgVFeX1Pt9++y01aNCAtm7dyttKSkropz/9KX388ce1fry2oqKi6OGHHza21dX5td+7/HXu5syZQx07djSea8KECdSzZ88qH6vqP1cKgKoKVd0ZwjWps2fPksvlovT0dN4WERFBv/71r+m2226ju+66i2bNmmU4QOvXr6eAgACPxwoICKANGzb49fiio6M5vNeqVSsaNmwYuw+5ubnkcrkoJSXFuM/gwYPp6aefrvVjtfX999/TbbfdRjExMbztRjq39gXfX+dz1KhRNHjwYOP2lJQUcrlclJeX57fjddK+ffvoJz/5iQEWwcHB1KxZM2ratCndfffdtGzZMiPkt2DBAgoLCzMe5+LFi+RyuejAgQN+Pd7Ro0dTQEAA3X777dSuXTsaN24cffXVV3z7/v37yeVy0cWLF437hYWF0cKFC2v9eKX+7//+j37+85/T5s2bje11dX7t9y5/nbsHH3yQpk2bZuyzfft2+vnPf05Xr16t8vGq/jOlAKiqUCUlJeRyuejw4cPG9piYGGrfvn0dHVWZ4zNo0CB64IEHjO1r166lffv2UXp6Om3ZsoVatWpFffr04dtjYmKoXbt2Ho/Xrl07Wr58uV+Pcffu3fTBBx9QWloa7du3jyIiIuiOO+6gCxcu0OHDh8nlcnnkfI0fP5769etX68dq691336Wf/exnxvHdSOfWvuD763z27duXxo8fb9yO/4HExES/Ha+tf/7zn9StWzcaMWKEsf3VV1+lQ4cO0Zdffknr1q2jX//61/Tf//3fxu/Xt29fj8dr2LAhvfPOO3493q1bt9Jf//pXSk9Pp507d9Ldd99NnTt3Zrd08+bN1LBhQ4/H6tu3Lz377LO1frxSK1eupFtvvZX++c9/Gtvr4vw6vXf569y1a9fO+NBGVP6/cf78+Sodr+o/VwqAqgrl7eK3bNky6tChQx0dFdHvfvc7Cg4O9kiStnXixAlyuVyUnJxMRN7BtW3btrRixYoaOVboH//4B91xxx0UFxfn9U153Lhx1L9//zo/1n79+lWau1eX59YbAFb3fMoLLlRcXEwul4uSkpL8drxSV69epaioKLrnnnsqDSt+8MEH5HK56MKFC0RkAq5UgwYNaMuWLTVyvND58+epQYMGtG3bNiLyDjF9+vShCRMm1OnxdujQwae8vdo4v07vXf46d04ftr744gtyuVxUWlpapeNV/edKAVBVoW7EEPCUKVOoZcuWPoXkrl27ZuTW1GVYlajsDX3ixIk3dAi4oKCAfvrTn9KHH35Y4X51eW7/U0LAV69epf/6r/+isLAwho6KBBhFHmNdhVShtm3bct7ljRoCTkhIIJfLRampqZU+Tk2fX2/vXRoCVtWFFABVlap79+40adIkY1unTp1qvQjk2rVrNHnyZAoMDKTs7Gyf7pOenm4kW6MQ4OjRo7zPkSNHaqWw4sqVK9SiRQtuK9KsWTNauXIl3/799987Fi3U9rFGR0dTs2bN6F//+leF+9XlufVWBFLd8/nmm2/SLbfcYuSBxcbG1kgRCOCvc+fORnV4RfrLX/5iFIqgMEA6n1u3bq2VoooLFy5Qo0aN6O233yai8kKGd999l/c5f/68YyFDbR7v6NGjPaqrvammzm9l713+Ondz5syhTp06GY89ceJELQJROUoBUFWp0AZm/fr1lJmZSTNmzKCbb76ZCgoKavU4Jk2aRAEBAXTo0CGjbcN3331HREQ5OTm0ePFiOn78OOXn59OuXbuoY8eOdM8993ArBaKyViBhYWGUlJRESUlJ9Jvf/KZGWqvMmjWLDh06RHl5eXTkyBEaOHAgNW7cmM9bbGwsBQQE0Pbt2yk9PZ2GDx/u2LakNo4V+uGHHygoKMijF9qNcG4vX75MJ0+epJMnT5LL5aJXX32VTp48yRdrf5zPb7/9lu644w4aPnw4paen0/bt26lJkyZVagNT0fH+61//osGDB1PLli0pNTXV+HsGfCYmJvJ98vLy6N1336XAwEDDoURrkEceeYRSUlLo008/pZYtW1aprUpFx3v58mWaNWsWJSYmUn5+Ph08eJB69epFLVq0MM7vxIkTqWXLlvTpp59SSkoKPfzww46tTGr6eKFLly7RTTfd5NgLrzbPb2XvXUT+OXdoA/Pcc89RZmYmrV+/XtvAqLxKAVDlk+Lj4yk4OJgaNmxIXbt2NVqv1Ja8NXbduHEjEREVFRVReHg4NW3alBo2bEht2rShadOmefQq++abb2jEiBHUuHFjaty4MY0YMaJGmiujD12DBg0oMDCQHnvsMcrIyODb0bi4WbNm1KhRIwoPDzcqmmvzWKFPPvmEXC4XnTlzxth+I5zbgwcPOr7+o0ePJiL/nc+0tDR68MEHqVGjRtSsWTNatGhRldy/io43Pz/f698z+i4mJydTjx49KCAggH7xi19Qhw4dKDo6mv7f//t/xvMUFhZSZGQk/fKXv6SmTZvSlClTjDY2/jje7777jvr160e33347NWjQgIKCgmj06NFUVFRkPMY///lPmjJlCjVt2pR++ctf0sCBAz32qY3jhd566y365S9/6dGvkqh2z29l711E/jt3hw4donvuuYcaNmxIrVq10kbQKq9SAFSpVCqVSqWqZ1IAVKlUKpVKpapnUgBUqVQqlUqlqmdSAFSpVCqVSqWqZ1IAVKlUKpVKpapnUgBUqVQqlUqlqmdSAFSpVCqVSqWqZ1IAVKlUKpVKpapnUgBUqVQqlUqlqmdSAFSpVCqVSqWqZ1IAVKlUKpVKpapnUgBUqVQqlUqlqmdSAFSpVCqVSqWqZ1IAVKlUKpVKpapnUgBUqVQqlUqlqmdSAFSpVCqVSqWqZ1IAVKlUKpVKpapnUgBUqVQqlUqlqmdSAFSpVCqVSqWqZ1IAVKlUKpVKpapnUgBUqVQqlUqlqmdSAFSpVCqVSqWqZ1IAVKlUKpVKpapnUgBUqVQqlUqlqmdSAFSpVCqVSqWqZ1IAVKlUKpVKpapnUgBUqVQqlUqlqmdSAFSpVCqVSqWqZ1IAVKlUKpVKpapnUgBUqVQqlUqlqmdSAFSpVCqVSqWqZ1IAVKlUKpVKpapn+v/nCLYhF98amAAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\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"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f2f50a4f150>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plotting one flat frame as an example (highlighting the region of interest) and one mask for high counts\n",
    "# flat frame\n",
    "b = flat_array[0]\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "ax.imshow(b, origin='lower', vmin=np.median(b)-2*np.std(b), vmax =np.median(b)+2*np.std(b))\n",
    "\n",
    "# rectangle of interest\n",
    "center = PixCoord((xmin+xmax)/2, (ymin+ymax)/2)\n",
    "width = xmax-xmin\n",
    "height = ymax-ymin\n",
    "reg = RectanglePixelRegion(center=center, width=width, height=height)\n",
    "patch = reg.as_artist(facecolor='none', edgecolor='red', lw=2)\n",
    "ax.add_patch(patch)\n",
    "\n",
    "# high-counts mask\n",
    "plt.figure()\n",
    "c = flat_masks_array[0]\n",
    "c.reshape(b.shape)\n",
    "plt.imshow(c, origin='lower')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lamp has a shape: need to fit a 2D Polynomial\n",
    "\n",
    "Before combining the flat frames into a single Master Flat, it is important to fit a 2D polynomial in order to trace the shape of the lamp in the cross-dispersion direction. \n",
    "\n",
    "The dispersion direction is the one along which photons of different wavelengths disperse in a spectrograph (y axis). The cross-dispersion direction is simply the one perpendicular to the former.\n",
    "\n",
    "Below we fit each flat frame with a 2D polynomial and plot the:\n",
    "\n",
    "-> the flat frame\n",
    "\n",
    "-> the best polynomial model\n",
    "\n",
    "-> the relative residual, i.e. (data - model) / data\n",
    "\n",
    "-> the normalized flat, i.e. data / model\n",
    "\n",
    "The last frames plotted (last column on the right) is what we want to combine to obtain the Master Flat becuase they have been corrected for the lamp's shape and they only contain the information on the pxel-to-pixel sensitivity variations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/masi1109/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:26: RuntimeWarning: divide by zero encountered in true_divide\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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\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=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2D Polynomial fit of the region of interest...\n",
      "Normalized flat frame created with shape  (2102, 2148)\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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\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=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2D Polynomial fit of the region of interest...\n",
      "Normalized flat frame created with shape  (2102, 2148)\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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\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=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2D Polynomial fit of the region of interest...\n",
      "Normalized flat frame created with shape  (2102, 2148)\n",
      "\n",
      "Total time taken for modeling the flat frames:  14.86 seconds\n",
      "Time per frame:  4.95\n"
     ]
    }
   ],
   "source": [
    "# Fitting each flat frame with a 2d polynomial\n",
    "from scipy import interpolate\n",
    "import warnings\n",
    "from astropy.modeling import models, fitting\n",
    "\n",
    "# If you want to adjust region of interest where to model the flats:\n",
    "xmin, xmax, ymin, ymax = 300, 1800, 0, 1500\n",
    "\n",
    "norm_flat_array = [] # define array of normalized flat frames\n",
    "\n",
    "# Measure time for modeling the flat\n",
    "start_time = timeit.default_timer()\n",
    "\n",
    "for flat in flat_array:\n",
    "\n",
    "    x, y = np.mgrid[xmin:xmax,ymin:ymax] # define grid for the region of interest\n",
    "    z = np.transpose(flat[ymin:ymax,xmin:xmax]) # frame data: y-axis is the first and x-axis is the second  \n",
    "\n",
    "    #p_init = models.Polynomial2D(degree=7)\n",
    "    p_init = models.Chebyshev2D(x_degree=7, y_degree=7)    # for a better fit use Chebyshev Polynomials\n",
    "    fit_p = fitting.LinearLSQFitter()\n",
    "    p = fit_p(p_init, x, y, z) # fitting the region of interest\n",
    "    \n",
    "    x_frame, y_frame = np.mgrid[0:xdim, 0:ydim] # define grid for the whole frame\n",
    "    poly = np.transpose(p(x_frame, y_frame)) # go back to axis order of original matrix \n",
    "    resid_rel = (flat - poly) / flat\n",
    "    norm = flat / poly\n",
    "\n",
    "    # Plot data, model, residual and normalized frame\n",
    "    plt.figure(figsize=(10, 2))\n",
    "    plt.subplot(1, 4, 1)\n",
    "    plt.imshow(flat, origin='lower', vmin=np.median(flat)-2*np.std(flat), vmax=np.median(flat)+2*np.std(flat))\n",
    "    plt.title(\"Flat\")\n",
    "    plt.subplot(1, 4, 2)\n",
    "    plt.imshow(poly, origin='lower', vmin=np.median(flat)-2*np.std(flat), vmax=np.median(flat)+2*np.std(flat))\n",
    "    plt.title(\"Model\")\n",
    "    plt.subplot(1, 4, 3)\n",
    "    plt.imshow(resid_rel, origin='lower', vmin=0, vmax=2)\n",
    "    plt.title(\"Relative Residual\")\n",
    "    plt.subplot(1, 4, 4)\n",
    "    plt.imshow(norm, origin='lower', vmin=0, vmax=2)\n",
    "    plt.title(\"Normalized flat\")\n",
    "    \n",
    "    norm_flat_array.append(norm)\n",
    "    \n",
    "    print(\"2D Polynomial fit of the region of interest...\")\n",
    "    print(\"Normalized flat frame created with shape \", norm.shape)\n",
    "          \n",
    "elapsed = timeit.default_timer() - start_time\n",
    "print(\"\\nTotal time taken for modeling the flat frames: \", \"{:.2f}\".format(elapsed), \"seconds\")\n",
    "print(\"Time per frame: \", \"{:.2f}\".format(elapsed / len(flat_array)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Combining the normalized flat frames into the Master Flat\n",
    "\n",
    "How to combine the bias frames into a single Master Bias? \n",
    "\n",
    "Same as for Master Bias! We will use two methods:\n",
    "\n",
    "1) compute for each pixel the mean value along the stack of bias frames\n",
    "\n",
    "2) compute for each pixel the median value along the stack of bias frames\n",
    "\n",
    "We will then create a fits file for the Master Flat obtained with the \"mean\" method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\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"
    },
    {
     "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\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"
    }
   ],
   "source": [
    "# Computing the master flat using a function defined in data_reduction.py module\n",
    "# Two methods of combination are available: (1) mean or (2) median\n",
    "\n",
    "# need norm_flat_array\n",
    "\n",
    "master_flat1 = get_master(norm_flat_array, method=\"mean\", n_clip=2)\n",
    "master_flat2 = get_master(norm_flat_array, method=\"median\", n_clip=2)\n",
    "\n",
    "b = master_flat1\n",
    "plt.figure()\n",
    "plt.imshow(b, origin='lower', vmin=np.median(b)-2*np.std(b), vmax =np.median(b)+2*np.std(b))\n",
    "\n",
    "c = master_flat2\n",
    "plt.figure()\n",
    "plt.imshow(c, origin='lower', vmin=np.median(c)-2*np.std(c), vmax =np.median(c)+2*np.std(c))\n",
    "\n",
    "# Creating a fits file for the master flat obtained with the average\n",
    "hdu = fits.ImageHDU(master_flat1)\n",
    "\n",
    "hdr = fits.Header()\n",
    "now = datetime.datetime.now()\n",
    "now_string = now.strftime(\"%Y-%m-%d %H:%M:%S\")\n",
    "hdr['COMMENT'] = \"Master flat frame (average of flat frames) obtained on \" + now_string\n",
    "hdr['IMAGETYP'] = 'MASTER FLAT'\n",
    "empty_primary = fits.PrimaryHDU(header=hdr)\n",
    "\n",
    "hdul = fits.HDUList([empty_primary, hdu])\n",
    "master_name = path2data + '/master_flat_mean.fits'\n",
    "hdul.writeto(master_name, overwrite=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dividing the object frames by the Master Flat\n",
    "\n",
    "The Master Flat rapresents the best estimate of the sensitivity factor of each pixel. We want to divide all other frames that are not bias or flat frames by the Master Flat pixel-by-pixel.\n",
    "\n",
    "Below we do that, leaving a comment in the header of each newly created fits file. The original files are kept unchanged. The new files are named with the suffix \"_b\". \n",
    "\n",
    "We print below the name of the new flat-normalized files and their image type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Master flat divided, frame /home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130145_b.fits of image type:\n",
      " OBJECT\n",
      "New fits file created for the flat-normalized frame: /home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130145_b_f.fits \n",
      "\n",
      "Master flat divided, frame /home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130155_b.fits of image type:\n",
      " OBJECT\n",
      "New fits file created for the flat-normalized frame: /home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130155_b_f.fits \n",
      "\n",
      "Master flat divided, frame /home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130144_b.fits of image type:\n",
      " OBJECT\n",
      "New fits file created for the flat-normalized frame: /home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130144_b_f.fits \n",
      "\n",
      "Master flat divided, frame /home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130146_b.fits of image type:\n",
      " WAVE,LAMP\n",
      "New fits file created for the flat-normalized frame: /home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130146_b_f.fits \n",
      "\n",
      "Master flat divided, frame /home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130132_b.fits of image type:\n",
      " OBJECT\n",
      "New fits file created for the flat-normalized frame: /home/masi1109/Documents/PhD/ObsII/not2mattia/ALAe130132_b_f.fits \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Subtracting the master flat (mean) from all other frames that are not flat frames\n",
    "\n",
    "hdul_master = fits.open(path2data+'/master_flat_mean.fits')\n",
    "\n",
    "for file in fnames:\n",
    "    hdul = fits.open(file)\n",
    "    \n",
    "    if 'FLAT_DIV' in hdul[0].header:  # if flat has been divided already we skip to the next frame\n",
    "        continue \n",
    "    \n",
    "    imtyp = hdul[0].header['IMAGETYP']\n",
    "    if imtyp == 'WAVE,LAMP' or imtyp == 'OBJECT':\n",
    "        \n",
    "        hdul[1].data = hdul[1].data / hdul_master[1].data\n",
    "        print(\"Master flat divided, frame\", file, \"of image type:\\n\", hdul[0].header['IMAGETYP'])\n",
    "        \n",
    "        comment = \"Master flat divided on: \"\n",
    "        now = datetime.datetime.now()\n",
    "        comment += now.strftime(\"%Y-%m-%d %H:%M:%S\")\n",
    "        comment += \" using master flat file \" + master_name       \n",
    "        hdul[0].header['HISTORY'] = comment\n",
    "        hdul[0].header['COMMENT'] = comment\n",
    "        hdul[0].header['FLAT_DIV'] = 'Yes'\n",
    "        \n",
    "        new_file_name = file.replace(\".fits\", \"_f.fits\")\n",
    "        hdul.writeto(new_file_name, overwrite=True)\n",
    "        print(\"New fits file created for the flat-normalized frame:\", new_file_name, \"\\n\")\n",
    "    \n",
    "    hdul.close()\n",
    "\n",
    "hdul_master.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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