Profiles_Gibraltar_getdepth.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from netCDF4 import Dataset, MFDataset, num2date\n",
    "import matplotlib as mpl\n",
    "#mpl.use('Agg')\n",
    "%matplotlib notebook\n",
    "import matplotlib.pylab as plt\n",
    "import numpy as np\n",
    "from matplotlib import cm\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "from cmocean import cm as cmo\n",
    "from matplotlib import cm\n",
    "from mpl_toolkits.basemap import Basemap\n",
    "import multiprocessing as mp\n",
    "\n",
    "import sys\n",
    "sys.path.append(\"/pf/a/a270046/hierarchy/pyfesom-dev/\")\n",
    "\n",
    "import pyfesom as pf\n",
    "import gc\n",
    "import datetime\n",
    "import os\n",
    "\n",
    "import sys\n",
    "import gc\n",
    "import datetime\n",
    "import os\n",
    "from cartopy.util import add_cyclic_point\n",
    "import math\n",
    "import xarray as xr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AGUV_salt_2078_2107.nc  BOLD_v_2078_2107.nc     GLOB_u_2078_2107.nc\r\n",
      "AGUV_temp_2078_2107.nc  CORE_salt_2078_2107.nc  GLOB_v_2078_2107.nc\r\n",
      "AGUV_u_2078_2107.nc     CORE_temp_2078_2107.nc  REF_salt_1921_1950.nc\r\n",
      "AGUV_v_2078_2107.nc     CORE_u_2078_2107.nc     REF_temp_1921_1950.nc\r\n",
      "BOLD_salt_2078_2107.nc  CORE_v_2078_2107.nc     REF_u_1921_1950.nc\r\n",
      "BOLD_temp_2078_2107.nc  GLOB_salt_2078_2107.nc  REF_v_1921_1950.nc\r\n",
      "BOLD_u_2078_2107.nc     GLOB_temp_2078_2107.nc\r\n"
     ]
    }
   ],
   "source": [
    "ls /work/ab0995/a270088/THOMASR/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### load climatology"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/pf/a/a270046/hierarchy/pyfesom-dev/pyfesom/climatology.py:83: RuntimeWarning: invalid value encountered in greater\n",
      "  self.T = np.copy(ncfile.variables['temp'][:,:,:])\n",
      "/pf/a/a270046/hierarchy/pyfesom-dev/pyfesom/climatology.py:92: RuntimeWarning: invalid value encountered in greater\n",
      "  self.S=np.copy(ncfile.variables['salt'][:,:,:])\n",
      "/work/ab0995/a270046/miniconda2-install/lib/python2.7/site-packages/numpy/lib/nanfunctions.py:703: RuntimeWarning: Mean of empty slice\n",
      "  warnings.warn(\"Mean of empty slice\", RuntimeWarning)\n"
     ]
    }
   ],
   "source": [
    "# load climatology\n",
    "clim = pf.climatology('/work/bm0944/a270046/DATA/climatology/', climname='phc') # climname='phc'|'woa05'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "#### do everything for CORE (LR) first"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The usejoblib == True)\n",
      "The joblib file for python 2 exists.\n",
      "The mesh will be loaded from /work/bm0944/input/CORE2_final/joblib_mesh\n"
     ]
    }
   ],
   "source": [
    "# load CORE mesh\n",
    "meshpath  ='/work/bm0944/input/CORE2_final/'\n",
    "mesh_core = pf.load_mesh(meshpath, get3d=True, usepickle=False, usejoblib=True)\n",
    "\n",
    "# load LR data; open the mean of temp over the last 30 years\n",
    "fl = xr.open_dataset('/work/ab0995/a270088/THOMASR/CORE_temp_2078_2107.nc')\n",
    "f_coretemp = fl.temp.data\n",
    "fl.close()\n",
    "\n",
    "# load LR data; open the mean of temp over the last 30 years\n",
    "fl = xr.open_dataset('/work/ab0995/a270088/THOMASR/CORE_salt_2078_2107.nc')\n",
    "f_coresalt = fl.salt.data\n",
    "fl.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mesh=mesh_core\n",
    "dataT=f_coretemp\n",
    "dataS=f_coresalt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "364.74921981951758"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mesh.lump2.sum()/10**12 # total ocean area in million km^2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### define box in front of Gibraltar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# box definition\n",
    "bbox_lon_start=-30\n",
    "bbox_lon_end=-5\n",
    "bbox_lat_start=40\n",
    "bbox_lat_end=20 #30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
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       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the region as a test\n",
    "\n",
    "# find 2D indices inside the box\n",
    "bbox_lonrange=np.logical_and(bbox_lon_start<=mesh.x2,mesh.x2<=bbox_lon_end)\n",
    "bbox_latrange=np.logical_and(bbox_lat_end<=mesh.y2,mesh.y2<=bbox_lat_start)\n",
    "box_2dindices=np.logical_and(bbox_latrange,bbox_lonrange)\n",
    "box_2dindices.shape, mesh.n2d, np.sum(box_2dindices)\n",
    "\n",
    "#\n",
    "# get data at that level\n",
    "level_data, elem_no_nan = pf.get_data(data, mesh, depth=0., verbose=False)\n",
    "plotfield=np.zeros(mesh.n2d)\n",
    "plotfield[box_2dindices]=1.\n",
    "\n",
    "# for checking level data\n",
    "fig1, ax1 = plt.subplots()\n",
    "\n",
    "cmap=cm.RdBu_r\n",
    "\n",
    "#-- plot\n",
    "map = Basemap(projection='robin',lon_0=0, resolution='c')\n",
    "x, y = map(mesh.x2, mesh.y2)\n",
    "\n",
    "levels = np.arange(-2., 2.+.1, .1) #-- contour levels for temp\n",
    "\n",
    "plt.tricontourf(x, y, elem_no_nan, plotfield, levels=levels, cmap=cmap, extend='both') #cmap_correlations256\n",
    "\n",
    "map.drawcoastlines(linewidth=1.0, linestyle='solid', color='0.3', antialiased=1)\n",
    "map.drawmapboundary(linewidth=2.0, color='black')\n",
    "#cbar = plt.colorbar(orientation='horizontal', pad=0.03);\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from matplotlib.backends.backend_pdf import PdfPages\n",
    "saveFIG=True\n",
    "if saveFIG==True:\n",
    "   pp = PdfPages('/pf/a/a270046/hierarchy/new_figures/'+'gibraltar_box.pdf')\n",
    "   pp.savefig(fig1,bbox_inches = 'tight')\n",
    "   pp.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_profile_inregion(bbox_lon_start, bbox_lon_end, bbox_lat_start, bbox_lat_end, mesh, data3D):\n",
    "    \n",
    "    # find 2D indices inside the box\n",
    "    bbox_lonrange=np.logical_and(bbox_lon_start<=mesh.x2,mesh.x2<=bbox_lon_end)\n",
    "    bbox_latrange=np.logical_and(bbox_lat_end<=mesh.y2,mesh.y2<=bbox_lat_start)\n",
    "    box_2dindices=np.logical_and(bbox_latrange,bbox_lonrange)\n",
    "    box_2dindices.shape, mesh.n2d, np.sum(box_2dindices)\n",
    "    \n",
    "    # initialize profile array\n",
    "    profile_wgtmean=np.zeros(mesh.zlevs.shape[0])\n",
    "\n",
    "    # for every model level...\n",
    "    for idx, depth in enumerate(mesh.zlevs):\n",
    "    \n",
    "        # get data at that level\n",
    "        level_data, elem_no_nan = pf.get_data(data3D, mesh, depth=depth, verbose=False)\n",
    "    \n",
    "        # set everything outside box to nan\n",
    "        level_data[box_2dindices==False]=np.nan \n",
    "    \n",
    "        # do an area-weighted mean; divide by area of box\n",
    "        profile_wgtmean[idx]=np.nansum(level_data*mesh.lump2)/mesh.lump2[~np.isnan(level_data)].sum()\n",
    "        \n",
    "    return profile_wgtmean, mesh.zlevs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/lustre02/work/ab0995/a270046/miniconda2-install/lib/python2.7/site-packages/ipykernel_launcher.py:22: RuntimeWarning: invalid value encountered in double_scalars\n"
     ]
    }
   ],
   "source": [
    "# profile for LR (last 30 years)\n",
    "profileT_LR, depths = plot_profile_inregion(bbox_lon_start, bbox_lon_end, bbox_lat_start, bbox_lat_end, mesh=mesh, data3D=dataT)\n",
    "profileS_LR, depths = plot_profile_inregion(bbox_lon_start, bbox_lon_end, bbox_lat_start, bbox_lat_end, mesh=mesh, data3D=dataS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### plot the profile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot everything\n",
    "fig1, ax1 = plt.subplots()\n",
    "\n",
    "plt.plot(profile_LR, depths, 'r', lw=3, label='LR')\n",
    "plt.gca().invert_yaxis()\n",
    "\n",
    "#ax1.set_xlim([0, 5])\n",
    "ax1.set_ylim([5000, 0])\n",
    "\n",
    "plt.xlabel('potential temperature [$^\\circ$C]', fontsize=16)\n",
    "plt.ylabel('depth [m]', fontsize=16)\n",
    "plt.legend(loc='lower right')\n",
    "\n",
    "plt.axis()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### same for the other grids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The usejoblib == True)\n",
      "The joblib file for python 2 exists.\n",
      "The mesh will be loaded from /work/bm0944/input/mesh_ref87k/joblib_mesh\n"
     ]
    }
   ],
   "source": [
    "# load REF mesh\n",
    "meshpath  ='/work/bm0944/input/mesh_ref87k/'\n",
    "mesh_ref = pf.load_mesh(meshpath, get3d=False, usepickle=False, usejoblib=True)\n",
    "\n",
    "# load REF data; open the mean of temp over the last 30 years\n",
    "fl = xr.open_dataset('/work/ab0995/a270088/THOMASR/REF_temp_1921_1950.nc')\n",
    "f_reftemp = fl.temp.data\n",
    "fl.close()\n",
    "\n",
    "# load REF data; open the mean of salt over the last 30 years\n",
    "fl = xr.open_dataset('/work/ab0995/a270088/THOMASR/REF_salt_1921_1950.nc')\n",
    "f_refsalt = fl.salt.data\n",
    "fl.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mesh=mesh_ref\n",
    "dataT=f_reftemp\n",
    "dataS=f_refsalt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/lustre02/work/ab0995/a270046/miniconda2-install/lib/python2.7/site-packages/ipykernel_launcher.py:22: RuntimeWarning: invalid value encountered in double_scalars\n"
     ]
    }
   ],
   "source": [
    "# profile for LR (last 30 years)\n",
    "profileT_REF, depths = plot_profile_inregion(bbox_lon_start, bbox_lon_end, bbox_lat_start, bbox_lat_end, mesh=mesh, data3D=dataT)\n",
    "profileS_REF, depths = plot_profile_inregion(bbox_lon_start, bbox_lon_end, bbox_lat_start, bbox_lat_end, mesh=mesh, data3D=dataS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### AGUV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The usejoblib == True)\n",
      "The joblib file for python 2 exists.\n",
      "The mesh will be loaded from /work/bm0944/input/aguv/joblib_mesh\n"
     ]
    }
   ],
   "source": [
    "# load REF mesh\n",
    "meshpath  ='/work/bm0944/input/aguv/'\n",
    "mesh_aguv = pf.load_mesh(meshpath, abg=[0, 0, 0], get3d=False, usepickle=False, usejoblib=True)\n",
    "\n",
    "# load AGUV data; open the mean of temp over the last 30 years\n",
    "fl = xr.open_dataset('/work/ab0995/a270088/THOMASR/AGUV_temp_2078_2107.nc')\n",
    "f_aguvtemp = fl.temp.data\n",
    "fl.close()\n",
    "\n",
    "# load AGUV data; open the mean of salt over the last 30 years\n",
    "fl = xr.open_dataset('/work/ab0995/a270088/THOMASR/AGUV_salt_2078_2107.nc')\n",
    "f_aguvsalt = fl.salt.data\n",
    "fl.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mesh=mesh_aguv\n",
    "dataT=f_aguvtemp\n",
    "dataS=f_aguvsalt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/lustre02/work/ab0995/a270046/miniconda2-install/lib/python2.7/site-packages/ipykernel_launcher.py:22: RuntimeWarning: invalid value encountered in double_scalars\n"
     ]
    }
   ],
   "source": [
    "# profile for LR (last 30 years)\n",
    "profileT_AGUV, depths = plot_profile_inregion(bbox_lon_start, bbox_lon_end, bbox_lat_start, bbox_lat_end, mesh=mesh, data3D=dataT)\n",
    "profileS_AGUV, depths = plot_profile_inregion(bbox_lon_start, bbox_lon_end, bbox_lat_start, bbox_lat_end, mesh=mesh, data3D=dataS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### GLOB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The usejoblib == True)\n",
      "The joblib file for python 2 exists.\n",
      "The mesh will be loaded from /work/ab0995/a270046/fesom-meshes/glob/joblib_mesh\n"
     ]
    }
   ],
   "source": [
    "meshpath  ='/work/ab0995/a270046/fesom-meshes/glob/'\n",
    "mesh_glob = pf.load_mesh(meshpath, abg=[0, 0, 0], get3d=False, usepickle=False, usejoblib=True)\n",
    "\n",
    "# load GLOB data; open the mean of temp over the last 30 years\n",
    "fl = xr.open_dataset('/work/ab0995/a270088/THOMASR/GLOB_temp_2078_2107.nc')\n",
    "f_globtemp = fl.temp.data\n",
    "fl.close()\n",
    "\n",
    "# load GLOB data; open the mean of salt over the last 30 years\n",
    "fl = xr.open_dataset('/work/ab0995/a270088/THOMASR/GLOB_salt_2078_2107.nc')\n",
    "f_globsalt = fl.salt.data\n",
    "fl.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mesh=mesh_glob\n",
    "dataT=f_globtemp\n",
    "dataS=f_globsalt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/lustre02/work/ab0995/a270046/miniconda2-install/lib/python2.7/site-packages/ipykernel_launcher.py:22: RuntimeWarning: invalid value encountered in double_scalars\n"
     ]
    }
   ],
   "source": [
    "profileT_GLOB, depths = plot_profile_inregion(bbox_lon_start, bbox_lon_end, bbox_lat_start, bbox_lat_end, mesh=mesh, data3D=dataT)\n",
    "profileS_GLOB, depths = plot_profile_inregion(bbox_lon_start, bbox_lon_end, bbox_lat_start, bbox_lat_end, mesh=mesh, data3D=dataS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### BOLD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The usejoblib == True)\n",
      "The joblib file for python 2 exists.\n",
      "The mesh will be loaded from /work/ab0995/a270067/fesom/bold/mesh_Agulhas/joblib_mesh\n"
     ]
    }
   ],
   "source": [
    "meshpath  ='/work/ab0995/a270067/fesom/bold/mesh_Agulhas/'\n",
    "mesh_bold = pf.load_mesh(meshpath, abg=[0, 0, 0], get3d=False, usepickle=False, usejoblib=True)\n",
    "\n",
    "# load BOLD data; open the mean of temp over the last 30 years\n",
    "fl = xr.open_dataset('/work/ab0995/a270088/THOMASR/BOLD_temp_2078_2107.nc')\n",
    "f_boldtemp = fl.temp.data\n",
    "fl.close()\n",
    "\n",
    "# load BOLD data; open the mean of salt over the last 30 years\n",
    "fl = xr.open_dataset('/work/ab0995/a270088/THOMASR/BOLD_salt_2078_2107.nc')\n",
    "f_boldsalt = fl.salt.data\n",
    "fl.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mesh=mesh_bold\n",
    "dataT=f_boldtemp\n",
    "dataS=f_boldsalt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/lustre02/work/ab0995/a270046/miniconda2-install/lib/python2.7/site-packages/ipykernel_launcher.py:22: RuntimeWarning: invalid value encountered in double_scalars\n"
     ]
    }
   ],
   "source": [
    "profileT_BOLD, depths = plot_profile_inregion(bbox_lon_start, bbox_lon_end, bbox_lat_start, bbox_lat_end, mesh=mesh, data3D=dataT)\n",
    "profileS_BOLD, depths = plot_profile_inregion(bbox_lon_start, bbox_lon_end, bbox_lat_start, bbox_lat_end, mesh=mesh, data3D=dataS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot everything\n",
    "fig1, ax1 = plt.subplots()\n",
    "\n",
    "plt.plot(profileT_REF, depths, color='blue', lw=3, linestyle='dashed', label='REF')\n",
    "plt.plot(profileT_LR, depths, color='blue', lw=3, label='LR')\n",
    "plt.plot(profileT_AGUV, depths, color='green', lw=3, linestyle='dashed', label='MR0')\n",
    "plt.plot(profileT_GLOB, depths, color='green', lw=3, label='MR')\n",
    "plt.plot(profileT_BOLD, depths, color='orange', lw=3, label='HR')\n",
    "\n",
    "plt.gca().invert_yaxis()\n",
    "\n",
    "plt.hlines(1000.,xmin=0.,xmax=18, linestyle='dashed', color='0.4')\n",
    "\n",
    "ax1.set_xlim([2., 18.])\n",
    "ax1.set_ylim([2000, 0])\n",
    "\n",
    "plt.xlabel('potential temperature [$^\\circ$C]', fontsize=16)\n",
    "plt.ylabel('depth [m]', fontsize=16)\n",
    "plt.legend(loc='lower right')\n",
    "\n",
    "plt.axis()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from matplotlib.backends.backend_pdf import PdfPages\n",
    "saveFIG=True\n",
    "if saveFIG==True:\n",
    "   pp = PdfPages('/pf/a/a270046/hierarchy/new_figures/'+'gibraltar_profiles_last30years.pdf')\n",
    "   pp.savefig(fig1,bbox_inches = 'tight')\n",
    "   pp.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### add PHC to the figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((33, 180, 360),\n",
       " -179.5,\n",
       " 179.5,\n",
       " -89.5,\n",
       " 89.5,\n",
       " array([    0.,    10.,    20.,    30.,    50.,    75.,   100.,   125.,\n",
       "          150.,   200.,   250.,   300.,   400.,   500.,   600.,   700.,\n",
       "          800.,   900.,  1000.,  1100.,  1200.,  1300.,  1400.,  1500.,\n",
       "         1750.,  2000.,  2500.,  3000.,  3500.,  4000.,  4500.,  5000.,\n",
       "         5500.]))"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clim.T.shape, clim.x.min(), clim.x.max(), clim.y.min(), clim.y.max(), clim.z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# find 2D indices of PHC inside the box\n",
    "PHCbbox_lonrange=np.logical_and(bbox_lon_start<=clim.x,clim.x<=bbox_lon_end)\n",
    "PHCbbox_latrange=np.logical_and(bbox_lat_end<=clim.y,clim.y<=bbox_lat_start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "climT_box=clim.T[:,PHCbbox_latrange,:]\n",
    "climS_box=clim.S[:,PHCbbox_latrange,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(33, 20, 360)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "climT_box.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "climT_box=climT_box[:,:,PHCbbox_lonrange]\n",
    "climS_box=climS_box[:,:,PHCbbox_lonrange]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((33, 20, 25), (33, 20, 25))"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "climS_box.shape, climT_box.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f5b9ad24710>"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot everything\n",
    "fig1, ax1 = plt.subplots()\n",
    "\n",
    "plt.imshow(np.flipud(climT_box[0,:,:]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "profileT_PHC=np.nanmean(climT_box[:,:,:],axis=(1,2))\n",
    "profileS_PHC=np.nanmean(climS_box[:,:,:],axis=(1,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((33,),\n",
       " (33,),\n",
       " array([    0.,    10.,    20.,    30.,    50.,    75.,   100.,   125.,\n",
       "          150.,   200.,   250.,   300.,   400.,   500.,   600.,   700.,\n",
       "          800.,   900.,  1000.,  1100.,  1200.,  1300.,  1400.,  1500.,\n",
       "         1750.,  2000.,  2500.,  3000.,  3500.,  4000.,  4500.,  5000.,\n",
       "         5500.]))"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profileT_PHC.shape, profileS_PHC.shape, clim.z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot everything\n",
    "fig2, ax1 = plt.subplots()\n",
    "\n",
    "#plt.plot(profile_PHC, clim.z, color='white', lw=6, label='PHC')\n",
    "plt.plot(profileT_PHC, clim.z, color='black', lw=3, label='PHC')\n",
    "\n",
    "\n",
    "plt.plot(profileT_REF, depths, color='#1f77b4', lw=3, linestyle='dashed', label='REF')\n",
    "plt.plot(profileT_LR, depths, color='#1f77b4', lw=3, label='LR')\n",
    "plt.plot(profileT_AGUV, depths, color='#2ca02c', lw=3, linestyle='dashed', label='MR0')\n",
    "plt.plot(profileT_GLOB, depths, color='#2ca02c', lw=3, label='MR')\n",
    "plt.plot(profileT_BOLD, depths, color='#ff7f0e', lw=3, label='HR')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "plt.gca().invert_yaxis()\n",
    "\n",
    "plt.hlines(1000.,xmin=0.,xmax=22., linestyle='dashed', color='0.4')\n",
    "\n",
    "ax1.set_xlim([2., 22.])\n",
    "ax1.set_ylim([2000, 0])\n",
    "\n",
    "plt.xlabel('potential temperature [$^\\circ$C]', fontsize=16)\n",
    "plt.ylabel('depth [m]', fontsize=16)\n",
    "plt.legend(loc='lower right', fontsize=20)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from matplotlib.backends.backend_pdf import PdfPages\n",
    "saveFIG=True\n",
    "if saveFIG==True:\n",
    "   pp = PdfPages('/pf/a/a270046/hierarchy/new_figures/'+'gibraltar_Tprofiles_last30years_PHC.pdf')\n",
    "   pp.savefig(fig2,bbox_inches = 'tight')\n",
    "   pp.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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q6cZvlDn8cLhRG5JlNbIvFK9nT9/XnHmWL58OUJDtXsGdR/q7u6u5O+dPHkypAJIIQFLJ0AF0NK/IOdPAiRQOgncT/FzFN6sLScAbZ5BtIMLpvwzBYFRgSoLWytbPOn/JJ5p8kyRPHvVAQ0Kvxy8hl8Pa5UlubxakCVfzXANvBqgZcWWOBSe41TxWK3H8H6H98W+wfwvH2vGMjz7ejnjrf6mQ75ERERA7umTXrzHj5u2qMrxOnbsqFj75N4+evMaEmbdkglQAbTkr8e5kwAJlD4CMoaftPjtmycsfiHG71euBtD+OaDpE4Dw7r2TdAfPbJmIkBhtX2k5+7TLp/f1kjUePH8tMs7fO+vPqZ1lPt0ZwuGjMCItc2+3fxsjNoxQQtFMbToV1jr7FgszZm73JCUlYd26dYrSJ9OzZWYK66oJkTl6pRevtPY1amRagTRxG5tIwKIIUAG0qM/FyZIACZRaAjHCmiZj+B3/GUjS96hV3rlcTaDra0DASMAm51f3nht78Nb+t/T2zgV4B+Cbnt/kmhKtKPxkiJdvdoXgy20X1XAvwucD/x3dHHV93PIcWiqq0gnF3sY4HZuvuy+2DNti1jlL790f9l2BTDF3/ewRRelbs2YN4uPjTc5ThmwZNGiQovj16dMHdnZFt0CafBAbSaCEEKACWEI+BKdBAiRQBglIj96re0UMv++A4E0mPXrhVQvo8qqe4peSkYIvjn6BlcEr9aDJvXMLeyyEq72rXrs5KrdikvHSqpM4fEXrqCHHfXuAP7rXr5jrI24m3MRPZ3/CHxf/wH/a/gcj6o0w2Te3HL4mO9+nMSYxFU8v3oUj4Rl4f/k2hP74ArLT9VPHaYbo2rWrovTJJV4PD/MEidaMzTMJlGQC4t9ulCIQcBf3xgqB3CBMIQESIIF8EUgVseROC+VNBm6+E2T6lopi6bHD83qKn+x4IfoCXt/zut6Sr2zvU6OPEiC5KJk85DimZOPpMMxaexpxOhk1ZLiX1/rUx5SutU3dgquxVyHz9m68vBEZ2TkOHlVdq2LDkA2wtTa/7UHG55PLur9u2oVDtk1g7anNt5twZjsiN32pzrNBgwaK0jdmzBhUr15dbWeh7BCIi4vTKPxS6zeOnl4GUJj/b2EZgMZXJAESIIFCEQg/mxO0+dSvJjN2QHr0NnhMcexAjU56YVySRaDnFYErsOjkIqRl5YQ3kXNwsnXCrDazMLjO4Dw9XQsz3xvRSUp2j7XHb+rdXr28M74e1RzNfD312jWVecfm4X9n/4ds8Z+u3Eq4hRO3T6B1pda6zYUu37x5E3/99RfWr1+PHbv3wL5hD3h2GQ9re0d1zIyEKCSc3ooKFSpAhm2Re/tatmxpdlbqA1kgAQshQAXQQj4Up0kCJGChBFKEcUE6dRxfmmv8PjiL2HzSo7fVRMCjmt6Lpmam4rfg3xRrWmSK/t7AxuUb45Mun6C6u3mtWJfvJIi9fpfwx4mbIjyLvhI3rEU1vDvIH9LxIzdxtXPVU/5shGL7aM1HMTlgMmp5iiXtQorc1yeDMkuFTx5Hjx7VjiQcR7zbDNZX/m4Fon12ICZ8Oxe9e/fmvj4tLZZIALn/DSYcEiABEiCBwhHQZOs4/osI3rwWSE8yPU6V5sLaNwXwHwLYaa1WsnNaZhrWXlyLxacX43bybb37rSCybQRMwrRm08yS0UMzeFB4HBbuvISNp28p8fM07fLs5miLj4YEYEDTKkrMvuMRx9HCx3Q8vL41+uK/J/6rLPVKy+TExhPh6+arO1y+y2lpaUpwZo3Sd/36ddP3iowo8cc2oFx3oUQL6VvDDvPeeR7OjszHaxoYW8s6Ae4BLNpPAPcAFo0f7yaB0kUg4U7O3j5p7bt7wfS7iSVbReFrPQmo1sqoT3pWOtaFrFNy4oYlhhldb+LdBC+3ehktfVoaXStswymR0WPBzhD8cz7CaAjp5TtQKH0zetfB7bQgbLm6Bf9c+0fxPF43aF2uFr1l55ehZ/WeqORSyWjM+zVIJW/Lli3YvHkz/vnnH63nrtg76FitEVKun1aHkGFk2rZti4EDB6JHv/748nAinulSC90b5O6Yot7MQpklwD2AYodJmf365nlxKoDm4chRSMByCciAzZd2AieE0he0CRAKnEmR1r4W40XWjmGADOJsIDITxobLG/DtqW8hPWcNpaFXQzzX/Dl0rtrZbPvXDl2OVBS/vRe1OXM1z7WzsYJc7h3UygG7I/7A1qtbcSdZKLg6ImP2SStkUUXG59u9e7ei9EnFLyhI3zHG2tENrs36wq1Ff9i6lUfk0hfwSOvGitL32GOPoVKlgiuZRZ0z77dsAlQAwSVgy/4R5uxJgAQeGoGkqJyYfUd+ELEAQk1PQyp6TUYJxW8cUCnAZJ/0zHRF8fvh7A+4FnfNqI8M6iyVrEd8HzGL4ifz4/4lvHrXHLsBmcvXUBxsrfFEGz/FilbF0wkyT+/ywOWG3ZT64fDDmCb+K6jIvXznzp1TrXx79+5Faqp+mBYrW3s41W4N5/od4VSnDax1lsifm78GHw9vVtDHsj8JkIAOAe4B1IHBIgmQAAncl4D05D0s4vadXg2IeHwmpUZnofQ9CTTsL/b2iSVfE5Ik9gX+fuF3/Hz+Z9xO0t/jJ7vX8qilKH69qvcqcmaM1IxM7Ay6g7Uid+9OkcUjPVPfscPKNlqki3PAuDYBmNSpJiq4affNNSrfSNm/Fxqfo+R6OngqS7tyn18rH+MlbBOvqjRFRkZi27ZtitInw7VID968RFr6KgyeZbLLmbB4ZAnnFGu5Pk0hARIoFAEqgIXCxptIgATKFAG5zCsDNcuAzTJwsylxFcuQzceIYyyU4M2m+oi22NRYJZzL8qDlStmwWw33Gni26bPCiaEvbKxtDC/nuy6tbMevRwul7yY2CItfbLLu0nQmbJyuw8Y1CA7uwYB9OJ5uPA0vtGxgNL7cYzes7jBcib2CfjX7oU3lNvlyPMnIyMDhw4fVZV1ZlnPKSypXrgyZhUMePXv2xJMrAnHuljZEW+e63pgoFNSudStQ+csLJK+RQD4IUAHMByR2IQESKKMEkqPFMu8vOQGbY3PxPq3ZNSduX72+aoo2U7QiEiOw9PxS/HbhN8iYfoZSx7OO4i0rlayiBEq+FpmohG+RIVyuRRp4H1ulwrHyWti6XhAhB/XncDhiv5jSVMNpKXXpcZwf0ThvyH1827dvR0yM8RKzHMfK3kks77aBW6MuqOKYjieaeilKX0BAgN4y96MBlZGYmgF5Hty8KurdJ91cfubIPiRAAjkEqADyJ4EESIAEDAncDsyx9p1eZTqEi/TkbSr29rV5BvBpZHi3Xl3u65Op0NZfWg/p4WsoTSo0weTGk9HVt2uhl3rlvj5p5ZNK37FrQmnNRaqV80CG100kZuorf7K73OsXnxYPN3u3XO42bk5OTtZz3ggMFNxyESt7ZziLvXwVWwlFuVJDZMmg10K8Krri1ZeFEm1Cnu4slsG71dZTCk10YxMJkEAhCFABLAQ03kICJFAKCchl3otbgYPfAFd2m35BD1+h9D0tlnnHAc5epvvcaw2KClKCN8uQKVkiRp2hdKjSQQmMLPfRyWXWgorc17cr+A7+EEu8O4Jui7iB4hlWaWJZN0TkFLZFZmI9ZUh3Eb+vvwjjMlRY0FpWL4cPDv6L1RfE/kUhUtnrVKUTuvh2QccqHe+r/Mkl3PPnzyvhWaSVb8+ePUbOG8rAOn+4ubkpy7nX/cfjbrodDEmE3E7AxYh41DVh3bMXDikUEiCB4iFABbB4uHJUEiABSyJw/RCw6RUg/IzpWUunjrYiYHO9fnku88qbZQ7c+SfmK7HyDAeTAZxlbDy5pOpf3t/w8n3r8SnpitK35Vy4ck4Qy6NWNvEiNEognFzPw8YlBFbWGchKqokO1TsrSt8jDSvCwVa7l1AuMbvau6JLtS5oWqHpfZebo6KiVOcNqfTdz3lDKrMy1ZpmL1+7du2UDBxzNwcp2UV0X7KusP7J5V13JzvdZpZJgAQeAIGC/7PzAUzKgh7BOIAW9LE4VRIwIiADN297Gzi53OgSbEVmjiYjczJ1VGpsfN2g5U7SHSWG35qLa5CZLayJOiL39A2oNQBPNX4KNT1q6ly5f/FOfCq2BUZAKn3/hkTmWPru3eZY7WfYCeXPUGTqtd2P74aHgwhDU0DJzMzEkSNHFCufDMQsy1lZhnY7/UErN2iBeo+MgKdffSye2EnJu6vfQ2TDuxmL/v/dh/rC0ieVvkcDKpm0+hnexzoJFAcBxgFkHMDi+LnimCRAAiWdQGYGcPQHYMeHgPDK1RP3qkDryTlhXFzK610yVUlIS8BP537CL+d/MXLucBJ7BaUH7ZP+TxYoI4Z05JAK39ZzETgmPHlzc57NznQxNSVUdK6IG/E38q0AxsbGKt66GzZswN9//427d40DQ+s+yM7eAa36jkSF5j0QYeuD8IRMXJUdxPbDFBvTc/Kv4o4dr3RFrQquukOxTAIk8JAIcAn4IYHnY0mABB4SgesHgY0zgQiD5V47Z6DLq0D76eKfxto4eLnNUubqXRW8SknZFpOq7+1qa2WL4fWGY0rTKfB28s5tCLVdCYwswp1sFUrfFqH0BYs9cbBOha3LBdh5CatfZDe1ryzUruCC3v6V4F1xKL46c1S51rh8Y3Tz7aYcMnh0XvsK5fMuXLgAqfBt3LgRMhCzDNuSl9StW1dd1j2R5Ycf/g3FLSUMor61U1orn+pobOWU86HylxdhXiOBB0uACuCD5c2nkQAJPCwCCSLY8j9zgFO/Gs+g0SCgz0eARzXjawYt0qFj4+WNWHhyocmUbTJ+3/PNn4efu5/BnfrVDOG0ceRqNLaez7H03YxJhpVtrAjRIvbz+Yr9fM6XxH6+TGH9s0FadDs0rVoJffx90LtRJdQRe+ekJGdUh5tLMrpW6wofFx/9BxjU0tLSFEVPKn3yCAkRziJ5iHTeeOSRR1Slr1atWmrvCiKFnFQAdUU6bHSu440a3qYtgLp9WSYBEnj4BKgAPvxvwBmQAAkUJwG53HtkCbBTLvdqgworjyxfF3j0U2FSe+S+M5BWs/239uOrY18hOFoETzaQtpXaYkbLGfD39je4oq2mpGdC5t2Vy7vbhaUsOkkbFsa+wlY4eO/Qdr5XsrLKxCdj7DDKv6PRNbnEPLK+2KeYi9y+fRubNm1SFD6ZfSM+XlgW85B69eqh22PDUC6gG66kuuK/o1ugorvYC2kg0pvYy8UemSIbR48GFYU10gedRXBmFwf+L8UAFaskUGIJ8G9rif00nBgJkECRCVz7V3j3imXdCJG+TVfshJWq62tAu2liudde94rJ8tm7Z/HlsS8hc98aSgOvBpjRYgbaV2lvctk1Vih524MilP18uy/cQbJQAk1JVkplU83wc/ODm5PWi9dkp3uNUkk9efKkurR7v+wbtra26NK1K9r2Hgprv+Y4FpGBLWFCSQ6Wimk0/hFK6pi21Y0eaWtjjdVT2qN6eWfYiTKFBEjA8ghQAbS8b8YZkwAJ3I9AonBi2PKGyNe70rin/xCgt7AGelQ1vmbQIh0ppOK39ZqID2ggVV2rKku9MqyKtZW+EiSVvr9O38LfZ8Nw6HIUMrIyxNJuEGwrCEU0TDw/W6t0lnO2Q8+GPujaoBHmnFyt9JXBobv7dlcO6TWc136+xMREJeuG3Msnj/uFaalQoQIeffRR9O/fH7169cK5O+kYvUSEwRHhXgzln/OmFUDZT7MMbXgP6yRAApZBgAqgZXwnzpIESCC/BGJvAD8PEArNZf07vOvnLPfW6qbfbqImLWl/hPyBuYfnIikjSa9HOYdyinPHiHojYG+jVeSyxHLoQbE3btXRUKH4hSMtI0uJ0WfndRgunodgbZez/JwR1xg+tq2UZdM+wpGjlVhOlRY1KR7lvkbD8g3v6zhy7do1RdmTe/l27Nhx32DMzZo1UxQ+qfS1bt1a5NHVKqytXLLgJpZu40VMQY1YiwBhbWp6Kcu7mjaeSYAEShcBKoCl63vybUigbBOIvpaj/MWIs0bkcm+310Ug56n5Wu6NTI7EOwfewa7QXZoRlLPcbze+0XhM8J+gBFLWXAyLTcbvR29g9bFQhEYlK81WdnfhWGUrbN3PCutdlqarcu7bJhL/7dXdpFWvc7XOen01FRmb7+DBg8rSrlT6zp41WNLWdLx3dnJyUrJvSIWv0yO9cSLSSom/16qGcfYS6bzRTezj+0c4o3StVwG9hJPJI6Iu9/hRSIAESi8BKoCl99vyzUigbBGIvCSUv4FAnLAAaqRmF2DId4B7FU1Lnued13cqyl9Uiv5y6NC6Q5XlXk1IF2ndk04c0tq3R+zrE8Y/fRGeu7buZ4SSp39BLhs3q1zXpPKnP4DYgRcdrcTmk8u6MjZfZGSkYRe9up+fn2rl69C5Cw5di1dyA3/+U6ASPPoxEXzZlAIoB3nzsYb4dFgTONnnb6+h3oNZIQESsEgCVAAt8rNx0iRAAnoE7lwAlgrlLz5M21y3NzDyF8DO2ItV2ymnlJieiM+OfAaZxUNXpML3Xof3oLHMyZy1q46EKopVZGKable1XF5Yzoa2aIFL1h1x5PY+kfzNCp2qdsKoBqOUfLs21rkrWXfu3MHKlSuxZs0a7Nu3D9Lyl5vIZdz27durSp+/f4738fsbAjF73n49D2M5hnToiE1Oh4eJtGs+Jjx9c3su20mABEoHASqApeM78i1IoOwSiDgvlD8Rxy9RxPnTSIP+wPAf8xXQ+cTtE5i9dzZuJOhYDsU4Pf16Yk77ObCzcsPKw9cVa9+J65qAz8Kpw0081zodGbEthROIcCoWy6ePt/YVy6c+kMuqR8InovGNupB7BX3dfTUzMzqnpKQoS7tLly5VLH15BWT29PRE3759FaVPnsuXN85UclVkEdENL6N5YKPK7rgdl2JSAdT04ZkESKDsEKACWHa+Nd+UBEofgbDTOcpfss6SrfTyHboYsLHL833TM9Ox6NQi/Hj2R7GEq92n5yL2DM5qMwtVbDrho7+uY+OZMCSl5VjiZKBmO+HQYVfuCKxt42GV6Y5JbYZjZKuaqOzhpPe81pVaQx6mRIkpuH8/pNK3evVqyFRsuUnDhg0Vhe+xxx5Dhw4dYGdnBxlEWuM4Ynjf0BZVsSMoRxmuVs4JQ5pXVQ5m4TAkxToJlG0CVADL9vfn25OA5RK4eRz4RSh7KRqrnHiVJo8DgxYJ5S/vX20h0SGYtW8WgqKC9N6/iXcLNHN8FvPXpeLSnYPqNRunqyIl215h9QvUc+rItolD/drXhfLXSO2bV0Fm3/jll1+U48qVK7l27dy5M0aMGAGp9GkycKQLpW/vxTtYe/wmpCVy16vdTMbgkyFlxrbzw4AmVdBaOH1YS/MkhQRIgAQMCOT9W9KgM6skQAIkUCIIhIqAzMuG6Wf2aDYWGDhfLMvmvsdOWvqWBy5XsnmkZWn38NlY2aFa9hAc2t8c+7N0rIn3XtbGWSiA7ueMXl0Gabaxyv158oYoEV9v1apVitJ34MABozE0DTLX7rhx4zB27FjUrFlTaZaWwjM3YrH2xA38deoW7iZo5yydT3oIZc9QHO1s8MHgAMNm1kmABEhAjwAVQD0crJAACZR4Alf3AytGAmkJ2qm2mihi/H0hlD9tfDvtxZxSWEIY3tr/Fg6Fi6DHOmKVXgVxoSNxNrWSTmtOUTpMDG5WBX2bTsf0vduRnpWuBH2WuXdH1R+FdlXaGQWBlnempqYqKdiktU+GbUlPl5k1jMXLywujRo1SFL+2bdsaeQf/JsLLvLZGLHObkLUnbppUAE10ZRMJkAAJGBGgAmiEhA0kQAIllsA1YUFbPhxIT9JOUcb36/sxhPakbTMo7bi+A2/uexPx6dpcuNnZVkiL7IK0u71EZg5bWNlFITvdU9xpjY51yot9fb6QgZqlRU3K47cfh4wFKJ06Krsap22T1joZq08qfdKTV4ZxMSVyD5+Mzzd+/HglI4e9fe7x9rqLeHw2YglX5tzVSBUPRwwW+/rkXj8KCZAACRSWABXAwpLjfSRAAg+WQIZY/vzzWX3lr+OLwl333VyVP6mULT2/FF8c/QLZ4j+NZKV5IuXWSGQm1xJNWcKpYz8cfTajrcdYvN31Wfh6OWu6qufX27yulnULly9fxrJlyxTFT+7xy01kyBa5xDty5EiT3rum7qvg5oAudb1x+EoUHhVx/IYIpa9dzfLc12cKFttIgAQKRIAKYIFwsTMJkMBDI3BkiYiOfFX7+E4vAz3m5Kr8yfy7nxz+BKuCV2nvEaX0mJZIiRgg9D5H2DnEolLt9YjJztnfdzJxBdKtB4teUjHMXWJiYhTvXWntk/H6chO5l0+zr0/u8TMUmTN44a4Q1CjvgtFt/QwvK/UPhgTAy9meQZpN0mEjCZBAYQlQASwsOd5HAiTw4Agki+XU3XO1z/MRTg6PvJmr8icDO8/cPRP7bmqVs+xsa6SEDRVx+1qJcbLRuvFV3LBejhidZeHUzFQcCDuAWp7GCqDcx7d582YldMtff/2Va/5dDw8PPP7444ri17FjR6N9ffIlUtIzsfTAVSzYEYK4lAzI4NEDmlaGm6Nx6Jqqnk7yFgoJkAAJmJUAFUCz4uRgJEACxUJgz+f64V56v5+rt294Yjie2/4cgqOD1alkZzoi+cZYZCbVga3YU9e/Uyi23/kW0Em0UcmlEj7s+CHaVG6j3icLiYmJ+O677/DZZ58hPDxc75qmYmtri379+in7+uT+PkdHR80lvXOW2Mv358mb+GLrBdyMSVavyawii/dcxsu966ttLJAACZBAcRKgAlicdDk2CZBA0QlEiXh5h7/XjlNHOG3U7q6t65RkXL/p26bjdnJOIGR5KSutHJJDJ4izD+SeuoWjW8BfePEGrf8TNxNuKncPrD0Q/2nzH7jZuyl1+UdCQgIWLVqEzz//HDJFmylp3bq1YumTnrwVKlQw1UWv7Yd9V/DhpkC9NlnpXr8CHm1i7Fhi1JENJEACJGAmAlQAzQSSw5AACRQTge3vCUvdvfh3VtZAL1E3IXtu7FGWfZMztJa1zGRfofyNR3ammwiKXE5R/irey3v7UaePMGPXDLzZ7k30qi6UynsSFxeHBQsWYN68eYiMjNQ0q2c/Pz8lVp/c29egQQO1PT8F6Vm8YGeIkpNX9m9SzQP/6dcAHWp75+d29iEBEiABsxGgAmg2lByIBEjA7ARCjwDn1mqHbT4O8DHOurEyaCU+PvyxXkq39LjGiqcvsu0xqVNNRdGysxEK5D1p4dMCm4dtVkK7yCYZtmX+/Pn46quvIJ08DEXG6XvrrbeUpV7rPOINGt6nW/dwtsNz3etg6cGreLVPA/QXnr3M1KFLiGUSIIEHRSD3wFkPagaW/Rx3MX2RxjMW7u6ySCEBEjAbARHCBT/2BUIP5gwpcvTiheOAmzZgc2ZWJuYdm6eEetF9rozvl3q7J1x89uI/ncdhXKvmupf1ytLKJ5U+qfxJ65+hSEeOt99+Gz179jTp0GHYPyYpDadF9o4u9UwvCadlZCkhaRxs884gYjgu6yRAAuYjIP+uS4ctIfIP47/45ntUiR2JFsAS+2k4MRIo4wQC/9IqfxKFjPmno/wliWDQs/bOwo7QHSoo6embGj5QOHvURLm6i5FhG4qdkTEYk73EKGOH3Ncnl3nlcq/c72co3bp1w5w5cyDPVnkEmdbcJz17f/73KhaKJd4M4eyxa2Y3aJabNX3k2d5Wa4XUbWeZBEiABB4kAf4mepC0+SwSIIH8EZBBn7e9re3rKqx+HZ5T63eT72Lilon6yl+mvbLfD9bpcK39X0X5kzccCT+CZeeXqfdKT96ZM2eiRo0a+OSTT4yUP2np2717N3bu3Inu3bvfV/mTnr1rj99Ajy924+O/g5SwLklpmfhq+0X1mSyQAAmQQEkjQAtgSfsinA8JkABw7Ccg6rKWhIz5Zy+WgIWERIdg2vZpCEsMU69npbuL/X7D4OC9GzYul3VyfgB1y9VF28ptcevWLXz66adKSJeUlBT1Xk1BhnGRe/xkxo78yvXIJExZdgyBYcYrSLfjUpUUbjKVG4UESIAEShoBKoAl7YtwPiRQ1gmkiTy/uz7RUqjoDzQbrdRD40MxYcsExKbGqtczU6oIy9+TcK+8HVlC+dOIFawwwX8CBlcYjHlz5mHJkiUmgzcPGDBAUfxkSJeCSkV3B8Qlp+vdRs9ePRyskAAJlFACXAIuoR+G0yKBMkvg+r9AcpT29WXYF2sbyD1/L+58UU/5y4hvgKSrU9C8SnVsGjMfTzV+SrmvqmtVfNT0I1xYcgEN6jbAwoULjZS/IUOG4Pjx41i/fj0Ko/zJBzna2eCV3vWUZ/p6OWH+E83x57SODOuiEOEfJEACJZkALYAl+etwbiRQFglcv+f1K9/dWcTHq9MD2cIjeM6/c3AxWruvLj2muUjtNlx0ssF341opQZ5fbvky/LL9sOH7DRjy0xBkZGToEZTOHCNGjMCbb76JgACRTs4MMrhZVRF+BkoqN3r2mgEohyABEnggBKgAPhDMfAgJkEC+CVw7oO3q107J9/vjmR+w5eoWtb26S0OcDRom6jmhVJztbRAcHIyPPvoIy5cvR2amTo430UvG7ZPZOt544w00amQcR1AduBAFGcdveMtqhbiTt5AACZDAwyNABfDhseeTSYAEDAlI79+bR7Wt1Ttg/839+Pr412qbt5M3xtV6C68fva62PT1xAlat/BVZWVlqmyzY2NhgzJgxmD17NurXZ55dPTiskAAJlGkC3ANYpj8/X54EShiBsJNAhtZDN6J8Tby651UlcLKcqa21LeZ1m4eE9GRY2SQqk88WwaB/XbFcT/mztbXFpEmTFKvgzz//bBblT8b5O3ZNZ29iCUPH6ZAACZBAQQhQASwILfYlARIoXgLXhAPIPcm2c8a0898hPi1e04RZbWYh4VoC5h9/Hs41FsLaIRzZ0mp4T+zs7DBlyhRcvHhR8fqtXbu25lKRz3M3B2H4twdErL9ApGboLzEXeXAOQAIkQAIPmACXgB8wcD6OBEggDwI6DiAXXD1xIVYb1qWLZxcsfW0pztU7B9fGrrBGklACFyEhaCwcHBwwefJkvP766/D19c3jAYW7tPfiHfy0/6py83e7L+NufBq+GNm0cIPxLhIgARIoAQSoAJaAj8ApkAAJCAJy/951rQPItmy5xKvk6oT9XXt8M/kb+Iz0gXdj4Rl8TzKT/eCIqrh8+TKqVKmiaTbrOToxDTN/O6WO6WhnjWndzWdZVAdmgQRIgAQeIAEqgA8QNh9FAiSQB4E7QUBKjNrhuKODUk6PSUfQB0HwaOcB795a5S8rrTySbz6B6t4Vik35k+Fn3vjzDCJEVg+NvPFYI9Su4Kqp8kwCJEACFkmAewAt8rNx0iRQCgnoWP9kbo0zDvbIysjC9QXXYWVnhSpPai18tsLulxw6Hsh0gYNt8f0aW3v8JjadCVdhd69fAWPb+ql1FkiABEjAUgkU329OSyXCeZMACTwUAlFnNqnPDRTKX7KI3Re2LAzJIclwSnVCi5gWsLGyEQnerNDB/QVkpfko/e2LUQFs7ueJpr6eynPKu9jj0+FNIYNJU0iABEjA0glwCdjSvyDnTwIWTkAusy5YuABDI3Zo4jrjuHDqiNoVheyT2Xj33XfxwgsvwNPTE0fDjyIoKgghIc3FW19V3rw4s2/UEku9vz/bHgt2hKBxVQ8l24iF4+b0SYAESEAhQAWQPwgkQAIPjcCtW7cwceJEhDsdxfNNhRPIPTkcZ4Nn607Gi9dehLu7u6YZrSq1Uo5ZQafVtuJcApYPsbOxxoxeOfl+1YeyQAIkQAIWToAKoIV/QE6fBCyVwO+//67E7IvLisNz74pUalHaIMuvPbUWNaq3zPXVMmXy3XsSFB6P0Kgk+Ho5a5p4JgESIAESuA8B7gG8DyBeJgESMC+B2NhYjB8/HiNGjBA6XxS8H/VGOSutQpfh4Jqn8idn06VeBXVSUSJMy6SfjyAuRbqOUEiABEiABPJDgApgfiixDwmQgFkI7N69G02aNMEvv/yijGfrYQuvbl5w1bHo2TqWQ3hiuHLk9tDHAipjUDOtV/CFiARMX34cGZnaZeTc7mU7CZAACZAARDB9CgmQAAkUM4HU1FS8+uqr6N69O65fv64+reqQqrC2txYKoI7i5uCOhScXot/afnhz35u4FHNJ7a8pSE/cucOaoGX1cpom7L14F+/8dQ7SqcQcIpXJyIRU3InXxgA0x7gcgwRIgARKAgEqgCXhK3AOJFCKCZw+fRqtW7fG559/rqecde/fHd6P5AR2ds3WKoBpdg7YcHkDMrIysO7SOiwPXG6SjqOdDb4f11Ls/XNSry87eF1N2aY2FqLw8qqTqPPG32j5wTbMWXe2ECPwFhIgARIo2QSoAJbs78PZkYDFEsjMzFSUPqn8nTlzRn0PR0dHfP311+g3px9Ss3Ksay46S8A30uIU5U/eIGP+TfCfoN5rWCjv6oCfJrSGm6PWn+39jeex7XyEYdcC1R2EcqmR6KQ0TZFnEiABEig1BKgAlppPyRchgZJD4Nq1a+jRo4ey7JuWplWgmjdvjmPHjmH006OxOni1OuFaDuXVckiyVnnrWb0n/Nz91GumCnUquuHbsS1ha50ToFmuAL+w8gTO3Yo11T1fbeWc7dR+MUl0LlFhsEACJFBqCFABLDWfki9CAg+fgNx/Jx08pKOHdPjQiLXI6jF79mwcPHgQjRo1ws/nfkZKZormMmo5ab16Y3U8gic1nqT2yavQsY433h/cWO2SlJaJSf87KnL4ap+hXsxHoZyzvdpLehlTSIAESKC0EaACWNq+KN+HBB4SgcjISIwcOVIJ8RIXF6fOombNmtizZw8+/PBD2NvbIzI5EquCV6nXu/t2h4tYLtZIwj1LXttKbeHv7a9pvu/5iTZ+eKZLLbVfuFD+Jv98FElpGWpbfgvlRNo3jUgLoLkcSzRj8kwCJEACD5sAFcCH/QX4fBIoBQS2bNmCgIAAyODOujJp0iScOnUKHTt2VJt/Pv8zkjOS1fqzTZ8FUrUKY8da/dDQqyEmNp6o9slv4fW+DdC7UU6OYHnPmZuxeGnlSWTp7DHMz1i6S8Bpwhs4UVgUKSRAAiRQmghQASxNX5PvQgIPmEBSUhKee+459O3bF2FhYerTvb298ccff2DJkiVwc3NT26NTorEyaKVa71atGxqVbyQUwHi1rZ5PS6zqvwrtq7RX2/JbsBHWw69GNRN5e7Xp47YKh5C5m4PyO4TST2YV6ePvg1GtffFs19q0ABaIHjuTAAlYAgGt65wlzJZzJAESKDEEjh49irFjxyI4OFhvTv3791cUPx8frSVO00Hu/dOz/jUT1j8pOgogHNwg4/wVVpztbfHDk60xaMF+yGVgKd/tuYya3i4YJZaJ8yP1fNzw3bhW+enKPiRAAiRgkQRoAbTIz8ZJk8DDI5CRkYH3338f7du311P+nJ2d8d1332H9+vUwpfzFpMTg16Bf1Yl3qdYF/uXFHr8M4WSRoeOs4ai13qmdC1jwcXfEDxNawdleG87lzT/PYn/I3QKOxO4kQAIkUDoJlDYF8G3xmeSOb7mhSK4pybNuFNkmoi5dExPEcUMcsr+hvCsabopD3r9LHPnfhS46U0igNBMICQlB586dMWfOHEhFUCNt27ZV9vo988wzuVrvlp5fiqSMJM0tmNp0ak5Z1/onW4QF0BziX8UD80c1F/PJGS1D7AN8dtkxhNzWLjeb4zkcgwRIgAQskUBpUwDlN/hXHNKEIP8vIs9jxCHFVRybxbFXHF7i6CuOyeJ4URwaeVUUJoijlzhkigI51hZxOIuDQgJlloD0gv3+++/RtGlTJZSLBoSNjQ3ee+897Nu3D3Xq1NE0G51jU2OxImiF2t6paic09s4J2xIWdUFtVwpmUgDlWD2FQ8ibj4k9hvckPiUDE0V4mNuFDA+jGYdnEiABErB0AqVRAcztmwwTF+T7zhGHDOwl8zt9Jo7nxKERaZKQbefFIVMUvCUOGRF2iDgoJFAmCURERGDgwIGYMmUKpNOHRurXr48DBw7grbfegq1t3tuJfzn/CxLTEzW3qta/y7GX8cLfE9R2peDgoV8vYm1ixxoY20679+96VBJ6ztuNXw5eQ2YBvYOLOBXeTgIkQAIlhkBpVACbC7oylcAVccjl3xrikNJUHCfEkSUr9+SIONcSh7QOSmthDXHINo3I2A8nxSHHpJBAmSOwadMmNG7cGBs2bNB79+nTp+P48eNKjl+9CyYqCWkJeta/jlU6okkFuRtD/OW6fRJ+OkvJSqOLNL6bT6RDyTsD/NG5rnbcOGEJfEvsCRy6aD/O3Mg7Y0hcSjqmrziOHUHy1wqFBEiABEoHgdKmAP4mPotc75Huhx3EIZJC4R9xyCVcqeDFiENXou9V5DV5SDHVR3Mtpwf/JIEyQGDp0qUYMGAA7t69q75t5cqV8ffff2PBggWQTh/5kZXBKxGfpt1390yTZ9TbgqOC0ShVGuTviWd1wMlTUzPb2dbGGovGtMBjAZX1xjwllL+BC/dhzrqziE02Tvl2VsQRHPDffdh4Ogwvrz6FmzHa+IV6A7FCAiRAAhZGIO91Gwt7GTFduXSrERmUbKI45D/vpTIoHUKqikNXyt2ryGsaZdjw/z6yzw3dmwzLMsWVzHAgpU+fPsph2Id1ErAkAosWLYK08unKsGHDFC/f8uXL6zbnWZYhX+Tyr0Zaihh/LXxaaKoIjg5GV10FsLI01BePuDnaYaFQAkcE38bb68/hWmTOcrbMHbz0wDVsOhOGNx5riMHNqqqOLDKfsKafzAjyvLAErprSHnZCoaSQAAlYFgEZsF4eUnRzlFvWW5hvtvf848w3YAkbSWplUgEcKA75T/9PxVFFHJpl4BdFWe4BrCsOKZfFMU8cC2RFiIwhIRXJGeKQy8mGIi2DsULg7k4joSEc1i2TwKefforXX39dnbxcQpUWv6lTp6qKkXrxPoXlgcvxyeFP1F7f9fwOHarKf48J87zQvDqu6ICNl4JQLuveX8lHxLbbLjPV/sVVSEnPxLe7L2HRrktIy9D8Osh5WtuaXvhA5BWuK2IByjm+Iix/a0/cVKfydOeaQlGUCw0UEiABSyUg01V6eHjI6cs/pBGozElp+2fsCPEFNeYJuQy8RBxSgftXHGvFIff0vSsOR3EEiOMVcWiUPVHEInHI//v4i8NJHB+IQzqD/CEOCgmUagJS2ZHhXXSVP+nlu2zZMkybNq3Ayl96Zjp+OvuTykxm/NDN7nEr8RZck2O0yp/sWaWZ2r84C452NnipZz1seakLutSroPeoQ1ei0O/rvfjk7yAkC0XxgyGNUaei3CacI4v3XsHWc+GaKs8kQAIkYJEESpsCOFZ8BbkMnCCOo+KQFrye4pDuh7Ktjzi6iiNSHNIOvFgcX4tDI5+Lwv/EsU0cd8TRXhwyXEzOWpEoUEigNBJQLF2vvKIEeNa8n9zWIHP7jh49WtNUoPOGyxsQkaR1nHgmQD9GYHJ6MgY519Afs1JT/Xox12R2kJ+faq3sD6wkgkdrRMYMlBbCXvP2YO/Fu1g0ujmchNKokR1BtzVFnkmABEjAIgmU9iXg4v4oXAIubsIcv9gJZGZmKsu7ixfLfw/liJOTE/7880/07t1b01Sgc2ZWJgatG4RrcdeU+2p71MbaQWthbWXwb84dwsi+57Ocsd3FFt2X5b/fHo4kpGbg620X8OP+q0bhYR5pUBHtannhsy3BSlzB8e2rF9gi+nDeik8lARIwRYBLwFrHB1N82EYCJFDKCaSnp2P8+PHQVf7c3NyUjdKFVf4ksq3XtqrKn6xPCphkrPzJC7dOyj9zpPKDWf7VPM7w7Opgq+zt2/hCJ7SqLn2/tCItfl9svYAJHWqIfMK+VP60aFgiARKwUAIG/xy30LfgtEmABApMIDU1FSNGjMCKFSvUe728vLBjxw4l3ZvaWMCCXE5efEZrTazmWg39avYzHkX0Q5iuAvhgl3+NJ5TT0qCSO1YLT9/PhjeBl4v0I8uRVOEsIvf/9ftqL/aJZWEKCZAACVgyASqAlvz1OHcSKCSBxMREJcbfunXr1BF8fHywe/dutGrVSm0rTGH3jd24GH1RvXViwETYWtuqdbUQLxwpEuVW23tSjCFgNI/I79na2gojWvlixytd8UQbP2Hx0955+W4ixv5wCM//egIRTCmnBcMSCZCARRGgAmhRn4uTJYGiE5Bhi/r27Yt//vlHHczX1xd79+5Vsn6ojYUoKNa/01rrX0WnihhUe5DpkXStf7LHA/IANj0Z062ezvb4eGgA1kztAP8q+qGe/jp1Cz2+2I0f913BrdgkyNAyFBIgARKwFAJUAC3lS3GeJGAGApGRkejRowf27dunjlanTh1F+atbVxMOU71U4MLh8MM4ffe0et+T/k/C3ka7jKpekIWwU9qqq4ja5FZJWy9hpRZ+5bBuekeRUq4R3MReQY1Ix5H3NpxH57m78OLKE5pmnkmABEigxBOgAljiPxEnSALmIRAeHo5u3brh2LFj6oD+/v7Ys2cPqlevrrYVpbBYx/rn6eCJ4fWGmxzum5Pf4OwZndjqJWj51+SERaNMJzehY01sF8vCg5rJePJayRRhY7aci8ATiw8iOjFNe4ElEiABEiihBKgAltAPw2mRgDkJXLt2TXHsOHv2rDpsy5YtsWvXLsj8vuaQU3dO4VD4IXWosQ3HwtnOdL7gfTf3oUKMNrsGHrIHsDrpfBQqiniBX49qjhWT28LXS8aL18qBS5Ho+tlOrD4SiiyhFFJIgARIoKQSoAJYUr8M50UCZiJw8eJFRfkLCQlRR+zUqRO2b98Ob29vta2ohSWnZeKdHHG1c8UTDZ/QVPXOMkZg5N1A+Ij4g7JTVw0AAEAASURBVKpYgAVQneu9Qoc63tj2clcMbKpvDYxLycBra05jxHcHEBhWJjNMGaJinQRIoAQSoAJYAj8Kp0QC5iIgLX6dO3dGaGioOmSvXr2wefNmTR5Mtb0oheCoYOy6sUsdYlSDUXC313ea0FwMjQ9FjSQDxagEOoBo5pvX2cHWBvOfaI5hzasadTt2LRr9/7sP74s9gnKvIIUESIAEShIBKoAl6WtwLiRgRgJHjx5F165dERGhTcc2cOBArF+/Hi4uLmZ7kvT8XXBygTqeo40j5PJvbhIUHYRmIgahRrKcvACZBcSC5aNhAWhSzUN5A52IMUpGkR+El3CfL/fg4GWZgZJCAiRAAiWDABXAkvEdOAsSMCsB6eX7yCOPICoqSh33iSeeUHL7Ojpqc96qF4tQWBW8CrtCd6kjDKs3DOWdyqt1w4L13UsYHxuvNqdXDoBeoD31iuUUpCVw4egWSrq4jS90xrRutWFno1UFb8YkKw4iH20KZLgYy/msnCkJlGoC2t9Qpfo1i+3lmAu42NBy4MISkPH9Bg0ahOTkZHWIyZMn49tvv4WNjY3aZo7CubvnMO7vcUjPSleG83L0wpqBa+DtlMvewvQUpH3fBfZ3gtXHRw5fgvKNR6j10lIIuR2PN/44i0NXtEq4fLf6Pm748vFmaGQQV7C0vDffgwQsgQBzATMXsCX8nHKOJJBvAjKzR//+/fWUv5deegnff/+92ZW/2NRYvLL7FVX5s4IVPun8Se7Kn3yLbe/oKX9oN61UKn/yVetUdMOvT7fDnP6NYG+rXWwJjojHwAX78M2uS8oSsexLIQESIIEHTUD7W+lBP5nPIwESMCuB4OBgjBw5Emlp2jh0b731FubNmydWWM1r7Jf7/t7c/yZuJmhDuUxtNhXtq7TP/Z2CNwOHvtFerySWfnu+o62XwpJMKTexU01sfL4TXBy01tcMESJm7uYgjPj2X4RGJZXCN+crkQAJlHQCVABL+hfi/EggnwQ+//xzPeVv7ty5eO+998yu/MnpLD2/VG/fX/vK7fFMwDO5zzQuDFg3TXtdxgcc/pOIruygbSvFJRkSMDFVJ+zNvXc9fj1GSSe38vB1SKWaQgIkQAIPioB5zQIPatYl5zncA1hyvkWZnsnt27fh5+eH1HvetRMnTsQPP/xQLExO3D6BpzY/hczsHIVG5vtdPWB17o4fWVnAL4OBK7u18xm0EGieu6ewtmPpKZ29GYsvtgZjZ/Adky/Vq5GPknfY27VsKMUmIbCRBB4QAe4B5B7AB/SjxseQQPESWLRokar8ySfNnDmzWB4YlRKFmbtnqsqfjZUNPuv6We7Kn5zFv1/rK3+NhwHNxhTL/EryoI2reuCnp9pg9ZT2aOHnaTTVf85HoO9XeyDPFBIgARIobgJcAi5uwhyfBIqZgPT2lQqgRh599FE0bNhQUzXbOSs7C7P2zsLtpNvqmC+2eBEtfFqodaPCjaPAjg+0zZ5+QP8vjcK+JKUnYXXwakgFs7RLm5rCU3pqB6EMtkYffx/oWvzuJqTh6aVH8R+RSSQ+JcezurTz4PuRAAk8HAK2D+exfCoJkIC5CCxbtgx37miXFV9++WVzDa03zvenv8e/t/5V27pV64Yn/Z9U60aFlFjg94lA1r0sGMJaiGE/Ao45AZNlf6lUfnbkM/wZ8icS0hMQlxaHyQGTjYYqbQ3SKad7/YrKEZmQitl/nMGWc1rL30qRS3hbYAQqibzD7w9ujOZ+5UobAr4PCZDAQyZAC+BD/gB8PAkUhUCW2F/35ZfConZPmjZtqgSA1tTNdT4YdhCLTmqtjFVcquCDTh/A2iqXXyHSoWGDUERjrmmn0H024NtaWxclef+lmEuK8icvyKDSGRqFUa9n6a2UF3v+vh3bEp+PaApXB+2/yaU18OytOAxZ9C8m/3wEweHa4NmllwbfjARI4EERyOW394N6PJ9DAiRQFAIyp29gYKA6hLT+mTvky52kO3h9z+vIFv9JsbW2xRfdvoCHg9aSp05AUzj1K3D2d00NqNEZ6DRDW9cpjW44Wq2FJ4ZjZ+hOtV5WCvKbDW9ZDX+/2BlyidhQtgXeRh+xP/DlVScZNsYQDuskQAKFIkAFsFDYeBMJlAwCMsafRipXroxRo0ZpqmY5S2vca3te09ub92qrV9HYu3Hu498NATbqOKHIXL9DvxfmPm0cPN2bO1ftjKqu2lzAKwJX6F4uU2VfL2clePQrveoJ66hxkIa1J24q8QPLFBS+LAmQQLEQoAJYLFg5KAkUP4FTp05h+/bt6oOef/552Nvbq3VzFBaeXIijEcKR4570rt4bTzR4QlM1Pmekin1/TwHpidprg8XSsXsVbd2gZCMUQ90x5fMuRF8w6FV2qjYiePTzPepi4wudULeiq9GL34hOhswtTCEBEiCBohCgAlgUeryXBB4iAV3rn7OzM6ZMmWLW2ey5sQdLzixRx6zuXh3vdng37yXm7e8B4afVe9BGzKl+P209l9LgOoPhaOOoXHW1c8WV2Cu59Cw7zQ0ru2ODUAKndK0lkuxp5WRoDPp+uQdrj99g8GgtFpZIgAQKSED390oBb2V3QYCBoPlj8FAI3Lp1CzVq1EB6ek6okOnTp2PBggVmm0tYQhhGbBgBme9XioONA5Y/uhz1vern/oyL/wDLh2uv+4hl4snCQmmXo9hpL5guLT69GO727hhQewCcZaYQikrg0OVIvPLbKUjrn648GlAJHw4OQDkXe2w4fQtRiWkY1dpPL/ewbn+WSYAEcggwELSIxsUfhiIRoAJYJHy8ubAEZs+ejY8//li5XToQXLhwAXXq1CnscHr3pWemY8LmCTh9V2vJk5a/oXWH6vXTq8SLECbfdACS7uY02zoBU3YDFfJQGPUGYOV+BGRcwPf+Oo/fjt3Q61rBzUEogY3xzvpzuBWbAl8vJ8zoWQ+DmlWFXE6mkAAJGBOgAkgF0PinomAtVAALxou9zUAgMTERvr6+iI6OVkYbPHgw/vjjDzOMnDPE3MNzsSxwmTrewNoD8UHHD3Jf+pWp3pYJ5fCyjvfugPlAyyfVMVgwH4Et58Ixa+0ZxdqX16j1fFwxs3d9yBRz5vYMz+u5vEYClkCACiBTwVnCzynnSAJ6BP73v/+pyp+8YM7Az9uubdNT/up41sEbbd/IW4E4IJaedZW/RiLvb4vxenNmxXwE+vhXwpaXuqBHg4p5DnohIgHP/HIM3++5nGc/XiQBEiibBOgEUja/O9/aQglkZmbiq6++UmffunVrdOrUSa0XpXA84jje2v+WOoSTWMb9ousXue/Hk8GeTywHtr+r3gMPX2DA10ap3rQdClaKT4tHZHJkwW4qA73lsu+SJ1vhk6EBcLY3HV5HYnCys8HQFtXKABG+IgmQQEEJUAEsKDH2J4GHSGDDhg0ICRFx9u6JOQI/ZwtFbnngckzaMknNyCGHf7v926jlWUvzKP1z3C1gxUhg3TSdVG/i18kw4TXs5Knftwi1Tw5/giHrhuCfa8LBhKJHQC7rjmrjpwSPblldP1VcTW8XVBRK4sRONSCVRQoJkAAJGBLgDmFDIgWrcw9gwXixdxEJdOnSBXv37lVG8fPzw6VLl2Brq00fVtDhkzOS8f6B9/HX5b/0bh3dYDRmtZ2l16ZUpNXvpLD6bZ4N3PMQVjv1eg/o+KJaLWph5/WdeGHnC+owj9Z8FLPbzs47A4nau2wVMrOyMW35MTWfcHM/T6yY3E7kWs6Gi056OV0q8/4RsRbF9XHtqSTqcmG5bBDgHkCR1alsfGq+JQlYPoEjR46oyp98mxdeeKFIyl9ofChm7JyB4OhgFY7MzTujxQw86W/CgSNWeJ/+JRS8kG1qf6Xg6gP0F8vSDR7Vby9ibf+t/XojbLqyCUfCj+CdDu+gS7UuetfKekV6+1Yrpw2dI/V0pzyWhmOS0rBY7A1MTs/Et+I8tHlVTO5cE3UqupV1lHx/EigzBLgEXGY+NV/U0gno7v1zc3PD5MmTC/1K+27uw6gNo/SUv3IO5fB9r+8xofEEfacPqU0cXwosam+s/DV9Aph20OzKn3wx6Xwyt/NcJTag5kXvJN/B9O3TFUVQ08ZzwQksP3RdUf7knWkZWVh5JBQ95+3BxP8dwfHr0QUfkHeQAAlYHAEqgBb3yTjhskpgx44d6qtPnDgRHh4eaj2/hazsLMiAy9O2TUNcWpx6m395f6zqvwptK7dV25RCTGhOiJf1z4slX21/uFYCnlgFDPkWcPbSv8dMNbnH7dFaj+KPQX9A5gvWSMcqHdHKp5WmyvM9Arr7eYTKnqe0q+Vl0ot4R9BtXAiPz/NeXiQBEigdBLgEXDq+I9+ilBOQ3r+3b99W37JNmzZqOb+FhLQEvLHvDewI1SqS8t4hdYbgjXZvKNk+1LE0Vr8tbwgTkYFC0HQ00Pcjscao73ig3mvmQkXniljYYyH+DPkT35z65v7p6Mz8fEsZTujLWpHfLw9pWd0LP0zwQsjtBPyw7wrWiLRy0hLo7WqPwWI5mEICJFD6CVABLP3fmG9YCghERkYiSwZcvic+PmLfXQHkUswlvLTzJVyNu6reZWttqzhVDK87XH/JV1r9pMVPN7afvMutck6Il3p91DEeVEFaA4fUHYL+tfrDzsbuQT221D+nTkVXfCxCybzSux5+OXANns52cBShY0xJaFQSrMVew6qeIssLhQRIwOIJUAG0+E/IFygLBCIiRKo1HSmIAihDqLy5700kZSSpI0ir2rxu89C0QlO1TXqE4tj/gK0iFqCh1a/ZWKDPh2YN8aJ9cP5LeSl/B24dgDymN5+ub83M//AW3VM320fe9j/j1/R2dcCMXvWML+i0fLolGJvOhOGxgMp4unMtBFQr+BYEneFYJAESeMgEqAA+5A/Ax5NAfggURgHMyMrA/BPz8dPZn/Qe0dKnJT7v+jm8nby17THX71n9dmnbZMmtCjBQpHWr20u/vYTVZMDoOf/OQXhiOPbc2IMPO30If2//EjZLy53OjegkRfmT4WbWn7qlHHIfoVQEu9evqFgGLfftOHMSKJsE6ARSNr8739rCCOju/7O2toaXV96OF9Ep0Zi6baqR8jeu0Tgs7r1Yq/zJZeUjP+R4+F7epU+l+ThguvDwLeHKn5z0F0e/UJQ/Wb4UewljNo3BwpMLkZ6ZLpvKhBRgC2CBeRy6HCUMxPp2xYOibdLPRzHzt1MFHo83kAAJPHwCVAAf/jfgDEjgvgR0LYAVKlSAjY3pfVpyoHOR5/D4hsdxMEwob/fE0cZRCanyWuvXYGd9bw9d9FXgl0HAxpfFkm+CpivgLpwAxq4BBokcv46WscwnFdtG5Rup75CZLeLbnfpWUQQvx15W21koHIFhLath96vd8VTHGkap5/o0Fh7hFBIgAYsjQAXQ4j4ZJ1wWCegqgHnt/5OesuM3jUdYYpiKqZprNSx7dJkSUkVplFa/w4uF1a8DcGWP2k8ptBgv4vodAOr01G8v4bXanrWVd5zebDpsrbQ7W6TTi6rwlvB3KPL0dEyA2dC31hV5bDGAr5cz3h7gjwOzeuA//RqgkrsjZMq5ng0L5pBkjrlwDBIggaIT0P6mLPpYHIEESKCYCNxPAZRLnXOPzMWqYBGbT0dk/LyPO3+sTZ8mrX7rngOu7tXpJYru1XL2+tXpod9uQTWp6D3b9Fl0rdYVs/fNRkhMCGa2mglfN18LegvzTNVgtdY8g94bxcNJcO5aGxM71sTNmGTILCSmZM+FO1gqPIufFhlG2tT00vc0N3UD20iABB4oASqADxQ3H0YChSOguwewYsWKeoNEJEbgld2v4NQd/b1YU5tOVRQimd5NxJABjoq9fv+8DaQn6t2PlhOAXu+L5V6Z2trypWH5hkpQ678u/YWhdYda/gvl8w2sYFoRy+ftBe5mb2utWABzu/F7kWJuX8hdbAuMQFPhMTxZOIz0E8vFtjZceMqNGdtJ4EESoAL4IGnzWSRQSAK5WQCPRRzDK7teQWRKpDqyq52I7Sasft18u+W0RYk9cOtEXL9r+9Q+SsFDWMYG/heo3V2/vRTU7G3sMazesFzfJCk9CdGp0ajqWnqCHusGgi5OC2CuUHUunLsVqyh/mqZTN2Lx/K8nlBiCMufwhA41aBHUwOGZBB4SAf5T7CGB52NJoCAEDBVA6ZG5PHA5Jm+ZrKf81fGsg5X9V+Yof9Lqd+g74JuOxspfq4k5e/1KofKXH65fHf8KQ9cNxe8Xfjfybs3P/eyTNwEfsT/wue51IJeLdUUuGR+4FEnlTxcKyyTwkAjQAviQwPOxJJBfAlLZ010C9vLxwqx9s7Dx8ka9IfrU6IP3OrwHZztnIPJSTly/a/v1+sDDT3j3CqtfrW767WWoJr2jfw36VXnjdw+8i23Xt+Hd9u/Cx8WynRl0F4DN7wJSsB8QGVh6Zp/6mNa9Nn4/dgNL9l7BdZFJRMrTXWoVbDD2JgESKBYCVACLBSsHJQHzEYiNjUVaWpoyoF0FO6y2XY2wy1ovX7nH7+WWL2N8o/Gwkmt/B78Btr0LZCTrT6L1ZKDnO4CDm357GavJZXNd2X9zP4asH4JZbWYpqeZ0M2ro9mO54ASc7W0xvn0NjGlbHf+cF0G6L95Fq+qmc0inZ2Yp1sHOdb1pISw4at5BAgUmQAWwwMh4Awk8WAKa5V/XAFdUm1INYRla5a+cQzl81vUztK3cNsfqt246cF2EcdEVz+o5Mf1qdtFtLbNlGSpGpsB7+9+3cTvptsJBZhKRnsPSetrDzzI9ofX3AD5sG6D+j5f0FO7buLJy6F/R1jacvoUZq06hno8rJneqhUHNq8DB1kbbgSUSIAGzEuAeQLPi5GAkYH4CYeFhqDCgAqrPqA5bV+2/2RqXb4zVA1ajrU8r4MCinL1+hspfm2eAqf8CVP70Pkynqp2wduBaDKg1QG1vUbEFulXrptZZeHAE5DaHxXuuKA+8EJGA19acRqe5O7Fgx0VEJ+ZYvx/cbPgkEigbBLT/Nyna+14uwu3yn6oi0zwMzBZFGJG3kkApIRCWEIavr38Nn2H6+9OG1R0mliz/A4dLu4Ddc4Fbx/XfuFwN4eErMnnU7KzfzppKwMPBAx91/kix+H129DN80PEDEdPOci1OIk2vxUpYbAruJKTqzf9OfCo+33oBC3dewmcjmqB/kyp611khARIoGgFzKYA1xDSCxBFRwOlIF7H24nAq4H3sTgKlmkBGVgZWBK7AgpMLkJyl3cuXnZGNdzrOwfAM8Vd3cU/xN+6MMYc2U8Rev7cBexfja2wxItCjeg909e0KW2tz/To0ekSxN6w6ch0/7MuxoMmHWdo+xiqeTtj3enesP3lLcRgJjohXmdWp6IqGlUtHjEr1pVgggRJAwJy/8T4Q77OigO/kLfrnbMIp4I3sTgKllYDM5fvuv+8iMCpQ7xWzI9Mw8EgKhicJi19kiN41pVKuptjrtxCoIcK+UApEIC/lLzgqGMdvH8eo+qNKnGKVkp6Jt/48i9+Ep62udK1XQbdqEWW5329EK18MF3mHpbPI93suoUEld7zetwFk0GkKCZCAeQmYSwE8J6YVU4ippYt75L0JhbiXt5BAqSKQKDJ0LDixACuCViArO0t9NwcRz6/PyTt4xiYZ1euL/xFGGvxVc60EdBCBnmVsP3sRAoZiNgIyYPTM3TMhcwofDjuMdzu+C3f7kmGNuno3EVOXH0dgWJze+8r4ezN61dNrs6SKtF5KBVYeaRlZVP4s6eNxrhZFwFwKYEAh3zpW3FfYewv5SN5GAiWPwI7rO/DRoY8QkaTdReEsFL8paXYYFnYbHuXk/igDK4inH9DxJaDZGMDOseS9VCmY0YeHPlSUP/kqMl6gtMp+2uVTNKnQ5KG+3ZZz4Zi5+hTiUzPUecigy18+3hSPNNDfL6p2sMACLX8W+NE4ZYshYC4F0GJemBMlgZJEIDwxHJ8c/gTbr29Xp+WemYlx8UmYkJACx3Tt/j+1g3d9oPPLQGOR6sxGP9OC2ocFsxAYUHsAZJxATaq9mwk38eTfT+LFFi9ivP94KHmWzfKk/A2SIWLlfbYlGN+JPLu6ElDVA4vGtICvFy3AulxYJgESyJ2AbvD43HvxSm4E5FqQiNMbC3f3krEslNtE2V6yCGRmZWJl8ErMPz4fSRk5GRLKZ2RifFwcRscnw1E4gRjK8bBMfLg3FStPJsDO3sHwMuvFROBu8l3M3jsbB8K0gQpsrWzx+8DfUduzdjE91XjY23EpeE7k0z18JUrv4pi2fnirfyM42lmuB7PeC92nIvc9bjwdhqEtqpa4PZn3mTovlyACceJ3rYeHh5yR/EN/H0UJmmdxTqU4LYDjxMSniqOuOLxMvIQMWlCczzfxSDaRwMMnEBgZCJmCTDp7SKmcnoGnYuMwNCERDjKTh4HEejTEqEXHsDkkRym8fecuqlatatCL1eIi4O3kjW97fYsfz/6o7NHMzM7ESy1feqDK38HLkXhuxQnc1QmV4mhnjY+GBAhFqFpxvXqJG1fud3xp5UlIL2FrsSNiSPOy8+4l7mNwQhZPoLgUMJGHCm+KI1wc+8RhsGtdtFBIoIwRkA4Fi04uwrLAZZBKRI20dEwSit9jQvEzuZBb+xGx1DsT4ane2PxyA5VWeHg4FUCVxv/Zuw74KIrv/4X03kOoCb13kN4VUak2RAVRsGBFVKwI+FNARbHrHysCKoJUld6kKL33BAihJgRSIJWE/3ub3N7eZS/1LrlL3uPz2JnZ2ZnZ717u3r55pXQKvNU7uvlocLDoZSeXKWn3SmNmDpD8zcaTtO17lByDjDPWDvbC1w+3Ubxkja3lu8QOIY/+uAMXSRPK9PbiQ5RWLlC2vcv3Y5e7syECthIAn6I1ryG+i/iGDdcvQwsCDoHAxpiNYIeCC9cvoEF6Bh4nwa/v9RRzt46ce2nUP8fGr3pbpR5GJgZaMqSG07ZJuXQQaFOlDZhLgxJTM/ESOXqsOWJ0DOJ572wehvfvaQEfd93XhtJYWpnMwQ4hkwc1xZOzdynzswMM4/PrEx0pgLdYM5XJQ5FJHRoBWwmAbIm8kFiEP4f+eMjiS4oA55plJ4/V0avRIi0dbyQkomdqjgbDZGzSMKHZvUDXF4EqTUxOsX2pu7s70tJyrmMNoJB9IjD3yFxE+EagS/WSxWI8dD4RY+bsxpkrOfahfLfOJOS8fmdjPNYlosLavt3eNAwPtK+J33bEKB+A7aevkENMFJ7uWc8+PxCyKkHAjhGwlQDI1tLyF2nHD16WZlsE2Mlj/vH5+HTXJ2iaHI/vSPDrQAJgHqpMWpxWD5LgR+FcAuvkOc0NHBctLCwMp0+fVs6LAKjAYHf/7bq0Cx/s+ECJ4Tiq2Sg80/oZuPDzLSJxVo8JSw4pMfAMl1bxdcOXD7ZBuwg9c2pDr4pxZIeXf8kmMjo+Rzj+mNLF9aHQNw3DfCoGAHKXgoCVELCVAPgKrW8V8Tri5VZaqwwjCDgEApw54h3K5BEQsw3fJCShJW355iFnD6DtyJwAzn4FO3SIAJgHQbtqSM5Ixvh/xqsBvL8/+D0UgZBiBlb1rlqotVrK6tG5bhA+G9Yawd7i+c1Aerk5U7zDVrjvmxyv7Of71EfdEEl7WKgPmXQSBDQI2EoA3EdzsB3gMuKzxNHEWcRaYpPmPtoGKQsCjowAO3n8Hzl5XNzxDd5OSEBDcvLIQ24ULuiWx4GOT9MvGWdCLByxAGgg0QAakLCfo7eLN55s8STe3/4+MrJzBP69cXtx77J78W6Xd9GrVq98F1tQVg+xcTOFr02tAEwa2BQc/7BVTX/Tk1ITBASBQiFgKwFwEM0+j5gMm5QYO5SyQEgQKL8IbI5eh+2rXsbdl6IRcUPH9NUziIQ+iorUnoQ/j6L/YFWpYszuIAKg/X2OeJv+/ob3o2VISzV1HK8yKSMJn+/9HN1qdCMbPv2v24qS1cPaT214x3BrDynjCQIVCgH9b6SSQzCVhjhFPIT4cMmHkxEEAftEIC4xBpv/fAIdT25DV8rgYU43fcJQqfMLtN37COXpLf42lWgAzZG1z3rDwIaY13+e4vG9NGopPGirf3r36brCn2T1sM9nKKsSBCoKArYSACMIwFeJRfirKJ+kCnaf2WkJOLj8RdQ4uARDdAS/TLLrc+n2Ciqxg4dzyW23RAB0nA+Yp4sn3uv6HjpU7YBK9K+Of17nHktZPR6krB5vV6CsHo7zVGWlgkD5Q8BWAmAkQeVd/uCSO6rwCKRcQfyGKXDf9RNaZOW18Uv0qwaf3hPhwiFdnKz356UVAJOTk5GSkgJPT8n7as+fx4F1B+ouT7J66MJitcYDZxNx9moK7mheOOcbq00sAwkCDoaA9X6hTG/8XapOJ/6RWIKWmWIjNUdEIPkiMrd8gps7vkdQVl6v3rM+wfC99R34NR9Glq9s+mpd0gqAPDIHg65du7Z1J5HRbIqAaVaPG3CvuhAZ8T0R7lu7wmX1sAXQWZQq5ZuNUZix+jg4aHTjqr6IoIwpQoKAIKCPgK0EwEY0HYevP0a8iNiSF/D/6JyQIGC/CFylj+7Wz5C9exZcdDR+Bzx9ULn7eDTt8BwH7LPZfWidQHgSdgQRAdBmcFt9YPOsHm6hK+Divxtu/gfx1C1vVqiUblYHN3fA3WeuUso8/smhDAQZlK953l7Mf6oTXJys/0KWO6UcBAGHRsBWv1jZhUDlJvVxKkQ/e+5CMT2QSATO1iBUjhCIO05ZrGfg5oHfUSk7r1fvFg8PnGs9DAN6T1EM/W1957zl6+Vl1GYsXLgQQ4awj5WQvSNgntXDyTMSnuHfmSybt4vf7PAm2H5QqPgIvL3kIH7+l/UNOfQCxQh88bYGhqocBQEVgaSkJPj5+XGd/0tST1Sggq00gLUrEIZyq+UJgQv7gU3TcfPwUjLfv0lsSqs9PbChdls8cusMdAkovR8Wtvfjlwz+0mKSUDCmz8Vea3pZPYKcG6Jb9fuw6tx8ddnsMbw/bj+m95gO9iQWKh4Cr9/RGFsiLyMq7roywBfrI9G9QQjahgcUb0C5ShAoxwjYSgA0voKVY/Dk1soRAme2KYIfTqxSbkor+LH+729vT/wWVBWDO7+G/zW4F5U5d28pE9sBGgTA8+fPl/LsMl1RECg4q0c/bIjpjre2vIXE9ERl6NNJp7Hy9EoRAIsCtFlfD1cnfPpAawz+cgtukE0g2wW++sd+rBzbHRJM2wwsqVZ4BEr/V6zCQy4A2BUCieeA2XcDP/SFQfgzrI9dPX738caAGtXwT/uH8OnQlUqw37IQ/nhNderUMSwNhw9LhCUVDDsqpJLt2e87Y9D/882Yv+usycqe7VUPs0d1UFO69azZEwsGLEDr0NZKPz4+3YoyxAiVCIFmlB1kXN8c7Xy9UG98QmnjRPgrEaRycTlFwFoawM8In1nEu4qIExu8TCP+nPhEEa+V7oJAyRA4+jewhH5wU6+ajJNCzhwLSPCb5ecDZ79aeLPjm+heo7tJn7KoNG/eHCtWrFCmPnDgQFksQea0gMDJuGuYu+0MFpDQxw4fWvLzcKHctS3Ru5Exm4vhfJhXGH64/Qd8e+BbDKk3RDdgtKGvHAuPwJPd68LN2QkPUVxFdxdHNzUv/H1LT0GgKAhYSwB8lib9j7ioAqAHXfMM8WJiEQAJBKFSQCAzDVg9Adg+02SypMqV8KuvD+YQJzu7YkSTEXiq5VN2Y5jPAqCBIiMjJRagAYwyOnImj7VHYzHnv2hsOnFZdxXNqvvi64faomagZecOThE3piWlCRQqEQKsfeUtYCbW+I3qWrtE48nFgkB5R8BaAiDjRPtoqFdEwCx/KxZxIOkuCBQKgTgKE7HgMQpSdNCk+zIvT0wNCkQyhYyo6lUVX5IxfouQFiZ9yrqiFQA5phxvA7dr166sl1Xh5o9NTsO87TH4ZfsZXEiklwkdahTmg+GdwnFv2xqKJkqnizRZCQG2t5y19TS+phiA3z/SXhw+rISrDFP+EbC2AMhCoJAgYH8IkMCEPbOB5ZShMDNFXR9v9/6PBL8/fXJCrHSr3g1Tuk6Bv7u/2sdeCo0bN4aTkxOyclPP8TawCICl83RY4N5x+ipmk7ZvxcELyMziKFam5EovD3c2D1MEvza1AigspNaVyLSv1EqOADt4/LH7rBL42SCIv7/8KOY92VGwLzm8MkIFQMBaAmBJde2SLaQCfNjK7BbTyMty2Vjg0EKTJRx2dcErocE44+KiePU+2+pZjGo+qkw8fE0WZqHi5uaGBg0a4MiRI0oPsQO0AJQVm6+l38CiPecwh2LLHbuUrDtydX8PPNSxFu5vV1N18NDtWMTGzOxMuFR2KeJV5b87C+NrjsTigxVHcSL2mskNbz99BRwQum14oEm7VAQBQSAvAtYSAKPzDi0tgoAdIBCzA/iDtnwTzpgsZhbZ+X0a6I9M0tIEugfiw+4f4paqt5j0sccKbwOLAGj7J3PsYrJi27eQNEzXybZMj3pQfLnhHcPRq1Go1bxMd1/ajZn7Z4JDwiSkJ2DrsK12+0Kih0lptf2w+VQe4a9FDT+82CsC9QOc1XBJpbUemcd+EHB1dYW7u7v9LMiOV2ItAdCOb1GWViERyKZkNJS7F+veBW4af8DjKU/vhJAgbKKAzkxtQtvgwx4fItQz1CFgYgHw999/V9YqGkDrPrKMG9lYeeiiss27/dQV3cH9PV0UTR97l4YH5ZgN6HYsZmNGdga2nN+iXh2bEgv2FBYyIsBb66/d0QiDKNYfU0SQJ165vRF61/dXQiVJkHQjVhWxxPFST506JUJgIR6+CICFAEm6OBgCyWRRsPAJ4NRGk4X/5+6G10OCcZnCQzA91uwxPNf6OYcKvaF1BLl06RLi4uIQEhJicp9SKRoC5xNS8Ss5dPxKjh2Xr6XrXtyqpr+i7burRVWbhhWJ8I0wmT86KVoEQBNEciot6XmMICebBlV8MLR9TSXfLwdJZ+EvJiZGUnPqYFYRmvgzULNmTWRkZIgAWIgHLgJgIUCSLg6EwHHK5LH4KSAlXl00Z/L4IsAPP/j54iZpD3xcffBel/fQq1YvtY+jFLQCIK+ZtYC9e/d2lOXbzTqzyYFgS9RlzCbbvjVHLoGqecjNuTIGtapGgl8EmtP2YmkQa6LdndyRlpXjXcwCYIeqHUpjarua4+r1DHy1IRId6wShT+O88RN5se8Maqa7Zk6ZKLnZdaGRRkHABAERAE3gkIrDInCDNDdrJlM0yi9NbuEsafteJa3fftL+MTUObIyPe36MGj41TPo5SiUiIgJeXl64fv26smQRAIv25BJTMilDR4wStPnU5RwMzUeoHeylBBC+r21N+NGWb2kSZ5mp5VsLx68eV6ZlW8CKRCkZN/DjltP4ZkMUkskBZ8OxOPRsaD0by4qEpdyrIFAQAiIAFoSQnLd/BC5H5jh6XNhnstblFNvvneBAXCO7P6b7G9yP8beMh5tTjjBo0tlBKpXpXpo1a4Zt2yh3MZHYARbuwR04m0i2faexdN95pGWSfagZUdxg3EqaJo7d16VuMCpzQxlRuG+4KgCyBrAiUCYF1eYUep+uOYHYZOM2PHv5cqgX9rAWEgQEAesiIAKgdfGU0Uobgb2/An+9RLH9jNqcVNKiTAnyx2JvMtKnLV8PZw+83elt9K/Tv7RXZ5P5eBtYBMCCoeUAwX/uv6A4deyLSdC9INjbDcNuqUlcC9UonIs9UG2/2qjmVQ0sCLYItq9g5LbCZxrF7/uePHvNqQ95WLesYX8xOc3XKXVBwBERsLUAyG5y4cRBxHqv1P84ImiyZjtAIC0J+PtlYP88k8Uc49h+tOV7io5M/GM6o+cM1PWva9LPkStaO8BDhw4hmzyeWTMolINAdPx1ZYuXNUoJtOWrR7fUDlScOm5vGgZXsvWzJ+J4lOycVJGIHTo4m8eNXGPMNrX8ydO3Mfg5CQkCgoBtELCVAOhNy51BPIJYbw4WBtnsOscdkwqFpKHU7xnilsQ8B//Ka/dz+HX5c+K2xPzK/y3xZGItcX00sS8x5y7m8Q4RG6gwYxj6yrEsEDhHj23BKOCqqcZgrq83Pg4IQEbu9t0dEXdgUudJdpPL11pQaQVAtgXkkAd165YfAbc4OHFWiPWUl5czdWw8Hqc7hBflib27TQ08TLH7GlKqNnuliphBhEPqPEihdbZGxVNIl4bo26SKZPOw1w+orKvcIKAnnFnj5lgIe4T4T+L1xFeIrUE8zpfEnEP4O7MBWSBcQfwD8W3EDYiXE7Mg+Ckx0yvEI4n5fBTxROKVxNyX84MVZgzqJlQmCHBsv3+/ANaSDJ/Nvr05lETp0d4MCsAGsvljcq7sjFfbv4qhDYeWyx8RrQDI98t2gBVVAOSwLfN2UF7ebWdwjsK56FFDChXyMGmYhrSuDm83W33l6c0sbVoEzsSn4OzVFHSuF6xtVsuv9mtEeZMrw5lS6gnZFgF2Jjtz5ozJJBxAuUqVKujUqROeffZZdO3aVT0/efJkMPfs2RPr1q1T280Ls2bNwqOPPgoe/+TJk+an1fqaNWswd+5cbN26VQndk56ejsDAQMW++c4778TDDz+M4GD9z4k6iBRKjICtvg0H0crmEI8o8QpNB1idW+1h2qzU7qH/+ZvjbeJs4oPEHxLzXopBAByT23aYjkwTiEmVhCHEc4kLMwZ1Eyp1BK7FAosovEvUWpOpd1LE99dCAnHJOeejzLZTH/X8CM2Cm5n0K08V/mKsWrUqLly4oNwWC4CDBw8uT7eY771wKrBd0Tl5ef8+oJ+X18WpEvo1q6ps87aPkLy8+QJq45MspH+xLpK25aMR6OWKDS/3ggdpY83JS4Rzc0hsVmctM3OXLl1Qr149ZZ6EhATs3LlTCTQ/f/58TJ8+HS+++KJV1xAfH48HHngAa9euVeZnQZHDWHFkA47h+O+//4KFw7ffflvp0759e6vOL4OZImArAZC3ZjebTmXzGm8L7yFm4c9AO6hQh5g1eywcRhBzm4GyqLCXuDUxC4AFjXGN+giVNgKRJPSx8HedhMBcyiaT0q/8ffEtcTZ9kTF1r9EdU7pOgZ+bX26v8ntgLaBWACy/d2q8s+sUFmTx3nNK7L6jlKpNj6r5uStbifdTcOBQH3e9LtJWSghwHuXvNp3Et/+cVNPpXUpKx49bT+HpnjlCRyktRaaxgMDo0aMxYoRRT8MBlJ988kmwJu/VV1/FgAEDVAHRwhCFbuYgzSxwHj9+HE2aNMHMmTPRuXNnk+szMzPx888/Y+LEier3m0kHqVgVAVsJgFtolU2tutKCB2ObPt7u1dLV3AqfYwGQSa8Pn2cqaAxdATA1NRUuLizzmpKbm5uucT4b7bPKW4+cSZOlNxb3TUtLA2s/zInf5CzlPuQ/qBs3jNul2mvtfn3OlVB5wxRK6WZQ4OasPtbFDS8F+2Nvbmw/jp02ptkYDG80HK6VXbW3aFIuT/ixALhqFQW9Jtq3bx/4M2hOdv98C/n3ERl3Hb/tOIfF+y6ogoT5vXarH4wH2lZD9/qBZALAf+o3VUzK7d9HIfHTYlVa3y87oxMwdv5BxFNAZy2xee6Vaxnqs9Ge47K112c+vtTzR4C3gb/44gssWLAAKSkpWLhwIcaPH5//RYU8y9vKLPzVqVMHW7ZsgZ9f3hd1/u0bNWoUBg0ahKtXDT/fhZxA042/D729vfP9/dX7ztQMUSGKthIAxxJ6vFe3jnhJKSFJbqGobjZXQG6dzxkEQH+dPmc1/fIbw+zSnCqrsJ3IDo2pRo0aSioaLvNbTLVq1bhoQqzqZnsKPerfv7/y1qV3btq0abpvRbwdOGnSJL1LsGLFCvz555+65+x5fcFOyZjY9Axc4w6YrH0dbRVMIHu/pFw7IZcMFzQ43gB7tuwh9e8eVBT8WrZsqeLCX6rPPPNMnhcHe36+vPj81jdx8juIdQnDGbfauOoSrN6rtuDn4YL72tbAQ+TUwcGb+W9gae62uLafI/59HL1yFH+f+hvbjm3DubhzaHo47/t0fviV9fdLRiVXpIbcqX0MuL1pFcXBw/NGMsaO5Z+IvGTtv9+8M0hLQQjwdmzDhg2xZ88enD59uqDuhTrPjmq//vqrsu378ccf6wp/2oHYzKUkNoCvvfYa3nvvvTy/vytXrsQff/yB//77D1lZvAFYsSln76zkGLCgZ041qKEu8TniU8TmaLMqqw9xcYhtAHlOVrtl5w4wgo4fELPEZWh7gcrPEtcnZjpJ/DHxF1whYqmNDan42+gX4sKMQd1UYo1hIgt0eqmHyosGRr1bKlj7DV1PQ+l0eCFcVo5HpQyjwjWzshOmBvhivg/t5udu+bYJaYN3O76LYA+jgFAa6zPgUZbPl8O/cEBoA7FNDRtva6ks12dYh97zNZzTW9+FxFTFoeM3ys0bR5oiPWpe3U8J2DygRTUTW7LypOFdcXoFXtnIPms5tPHujUo8S0Odj3r4cbu97DD83+Yz+GRtpBLK5bU7GqFNrZz3cVutj7cYWauUmJio+33M2AjlIFC7dm3FCeTHH3802QI24NOgQQNERUXh+eefx4wZMxSFRUmcQD7//HO88MILCKAoDZcvX1YEQcNc1jwaPgP8m8w50vXCYxk+f9w3LCyMp2dVJCuJKhxZSwNYh5DLuzcJnMlFtJaVkGUtHgt9brnjsZEPC5b8S7GQeCoxq9beI2ah7yXij4gN9BUVXiZeT8zC4NvEvBe7mJipMGPk9NT87+HhAebCEn8oi9LfMK6lbV7Deb0jq9QtbSnr9ee2MltfOgl8y2m7Ye9ck6WdcffCC0E+iKTtCQONajYKz7Z+VvH4NbQVdCxP+PEbOn+GDNsYLBCyJrowVGbP18Li2KyBw39wXt7VlJeXQ7qYE3uHDmjJeXnD0bKmuRI/p3d5er4RvhEmEMRlxqGhT0OTNkuV0ny+SenZCPLW/+57vHtdelYBlMotxOQHvzTXZwkjabeMwP79+1UP3tatW1vuqHNGz0SJu7FzCVObNm1MPgtKow3+4+9G/pzpkeHzxy+nFZ2sJQBGlBKQw2meH4kNvxCsIuJyL+J/iG8nZiFvHHEi8dfEnxIbaDoVSIWENcQcCIw/lf2IU4iZeLyCxlA6yn9WRoDTuC14DIiPNBl4oZ8/pvp7Iy33j9nH1QdTu05Fj5o9TPpVtAprOlu1aqV4zfG979q1y+EgSEzNxB+7zmIOeYeeJDs/PQoP8sTDHcJxL231BpAHaUWhWj6m78ycE7hhYOEEwNLA6GTcNXy06jj+oZiLG8f3Urx7zedlr95elMnDEYi1x6zxsgfikE7FeZkp6dpZI7Z582ZFU8daMjZnuu+++0yG3bBhg0XByqSjWSUuLk4R/EJDHePzYLb8clu1lgBoDhB/e8UR57VMz+nJr4whxGdyqoX+fxb1ZLZEB+lEd0snc9sn0ZHZEhVmDEvXSntREWCnlm3fAKtJGZtl3PJLc3bH64HeWJMb24+HbRLUBB/1+Ag1fNi6QIjfpjlsAtPu3bsdBpCD5xIxhwI2L9l7HqmUrs2c2FGgd6OcvLzdKGZcWeblNV9badU9XTwR6hmK2JQcz3d7yQkcm5RG27onlNiLBk3tl+sjMaF/k9KCxibzsPCnNamwySSFHPTgwYNo2jSvzWchLy9St5EjR4JZS+w0Vb9+fcVWznynirdM+/VjnYk+RUZGKkKk/llptTcEbCUAnqIbZW0d29Xp0UBq5HNsgydUURG4fpk2358GTnAsbiMd8w7Ac5SX9YKL8ePJQZ3Htx8PV6eKowUyIqJfatu2rXri8OHDynaw+Re22qGMC5yXd/nBC/iZtnn3nEnQXU0QafgeyM3LWyPAU7dPRWrkbWB7EQA5BM9XGyLxw+bTeYT2BaTFHXdbA0gcP8f7dHKwZ0McQPYAZg1dx44dFSFPbwu1UaNG+OGHHyzeKIePYS2iObE9Hm8Px8bmvNCYn5d62SBg/IW17vz0Dp8vseDHW7dCFRWBuGPAz4OA5AsqAjcptt+soFB84uOKrFxHDw9nD0zsNBF31blL7SeFHARYA2gg9mhj250OHToYmuzieIzi9XGmjkV7zuKqhby8HKiZ07P1axZGmSDkndDw4MJ9w7H94nYEuQfB3alsYxryn+P8nWdNhD9nUtWywP587/oi/BkemoMdzeMA2mr5/LI6e/ZsZaeCBUHWMgqVPQK2EgD5zvIT8PhX6krZ376soEwQyCCTy99HmAp/PlXxRmgI/sw2aofq+NXBxz0/Rl3/umWyTHuflIOpsieoIaYk2wHagwCYnJaJZRSzb97OGOyLMT5PLZ6elAmCU7Ox4Ne4qq/2lJRzEXim1TN4se2LYLvX0qD0G1k4fTlFN0+yp6szXri1Pt5cxBYywF0tquLlvg2V8DulsTZbz8F2d7z1ag9UHtM6cnifcePGgbONLF26VInzZw9YV/Q1WFMAfIHAZDbQJ1Rgb1xz8qcGP+KfzU9IvYIgsOpNshA9arzZBv3wRXhj/Bn5h9rWL6IfJneeDLaFEtJHgL27W7RogR07digdytIOkN/qd5y+qmj7OD2bnm0fL7J+qLcSwoWFPx93F/0bk1YFgSCPIJsiwc/s1OXr2EiOHOzM8d/JK3Alb+vdE26DExtimtH97WoqAv3wjhFoXoO/wssPsdNFadndlR/UCn8nHPx52LBhSv7fl156CT169IC/P4sC+sRbxSwscjgaIdshYE0BkF/1o3OXGkHHeOJLuXXDgbWC14i3EbOAKFTREDiyjHyvNTYk1dpgV89x+Hb14yoSzYObY2q3qUUK8aJeXMEKvLViEADLwhM4NjmNPHnP0fZgDE6SMKFH7i6VcSfl5eX0bB1qB8r2jx5I1JaUkQRf19LRhs4mJ5z/2xiFs1dN/fRYcN93NkGN2addqgsFX//g3pbaJikLAoVGgGMBbtu2TfG25pRwnAqOj1riVHRsR8hBzr/55hsRALXg2KBsTQFwFq2PmYmdQF4jXsoVIUFAQSDxHH0injOC4eqN1MFf4q1NL5G9QI7FAKdye7fLuyL8GVHKt6S1A+QtLA5nYesQEjeysrH+WJyi7Vt/LFY3bh8vugVpiVhrNLBVNfiKts/ic0zPSscnuz4BB39eMGABbK3544Vk0TM0F/4MC/yXYjIagjYb2uQoCJQUAdb4bd26FUOHDgWHk+nWrRs4IDXvYnh6euLSpUuKgHj9+nVFO6iXRauka5DrTRGwpgCoHbm2tiJlQQDZFO5j4RMUGOiqEYy7PsLHJxfh7LWzatvzbZ5HHf86al0K+SOg9QTmnM8sBLZr1y7/i4p5lmO//U6OAH/sPou4ZI6fnpf8PV0wuFV1RfBrUq10tFl5V+E4LcevHser/7yKyISc+JeTtk7CZ70/K5GWlLWym45fxrZT8Zh6dwvd7dzuDTgKVw6xMwcLfN0bBKNHg1A0ledmgKZcH4vqiMH9C3NNfv04vRtnLeI85pwajgXCdevWKXbMQUFBikaQ7QUffvjhfLeIy/WDKcWbq2TjufiXaBCx4Rf9JJWXEHMA5vJA/AtHmYck9VCBD/OfDyl537vGbs3vx3+dR+HxVcat39ahrfHj7T/SD5Z4ghqByr/EDiA+Pj4wRLXnbZMnn3wy/4uKcDYl4wb+PnARv5Mn7/bTV3SvZIe+rhSvj7V9tzWpAncXeX66QGkas29m45cjv2DGrhnIyDbGv2Sv99/u+q1IL0EZN7KxM/pKri3fZRy5YMxqtejpzmidm4JNM70SkuODlcfQirKqdK4bVC7sMQ1pwOT7WPukK1a5KJ8BQ19CiA1ajX80FQgyW2kA+RdgJvFIYnMh8w1qYweQ0cR5o8BSo1A5QyBmOyXfm2q8qYAIXOv7Dt5e+YjaxmEu/tflfyL8qYgUrsBewM2bN1cDQVvDEYSdA/adTVS2eJftO49rFANOj6pTrEbO0MFcM1CcdfQwstTGWj/e8tUSBzqf1m0aavsVbQPlF8qkMmnZYe1Qavkf0gTqCYCspXm1XyO1nxQEAUGg4iFgKwFwEkH5KDG7dU4nPkLM1IT4ZWKKAYKzxBOIhcozAmmUke+PURQUKFfWr0wfuXu+x/QD/4cL140xAMe2HQuOeyZUdATYDtAg+JXEEeTK9QyK13dO0fYdu5SsuxBXcgS4rWkVDCVtXxfS+ul5i+peKI0mCHAqQ4MASBtrGNV8FJ5u+TRcnPQ9o1kI9yDNqh7e3TTbudpJGoX5UJ5eCZyuxUTKgoAgYETAVgLgSJpiObFpIkHgP2q7N/fcSDqKAEgglFsiTRL+eglIOGO8xV5vYHMl8hw9YQz5ckvYLRjWaJixj5SKhADbAX733XfKNQcOHAB70nFU/8IQp/PaHHlZEfpWH76EDHIO0CMWJniLdzCFbwmsQDl59bCwRlv/Ov2x6ewm7I7djSldp6B9WHuTYbPpuRymrVwO0cK8O/oqFozprGzZmnSkSp1gL7A2lrfru9YPITu+EHSvH4xQ37INHm2+TqkLAoKAfSFgKwGQA1j9lc+tUiwQ9MjnvJwqDwjs+w04MN94JxHdkNT+MUxcxu8AOeTp7Il3uryDypUqG5rkWEQEtJ7ALPwdOnQIrVu3zneUmCspmE8pvBZQ+JbziWm6fX3cnDGAPHhZ28cevYUxANcdSBp1EXir41tgW0A/NzZByqHI2GR8sS4Sm05cRjxpZLXEsfrYZs+c+Ln8/lQnhJHAp6chNO8vdUFAEBAEGAFbCYCHaOwInsACRVA79xEqrwjERwF/825/LnkEAnfPxPs7p6v5TfnMy+1fRnXv6oZeciwGAhxGwcnJiUJ75Gyz83awngDI+XhXkZaPHTq2RF0mRwD9yW6hWH0s9N3ZvCo8KGOHUPEQYOFu6/mt6Fq9q+4AljJ8LN57Xrc/C4DP96mve441gEKCgCAgCBQFAVsJgG/RIn4nXk/MW8Fa4qSu7KZ4n7ZRyuUIgRukuWC7v4xrxpsa9AXWJxzD0ihjaMjO1Trj3vpGbaCxs5SKgoAhiwHnAmZiO8BRowj/XDp8PonCt3A+3nNITM00NJscQ3zcFGcO3uatTVuKQiVD4OL1i3hz85tKLt9Pen6CPuF9lAGj468rWTc6k/1k3RDvPJNwGwtz5xJyAjRzEO2OdYJoS5e2dhuG5OkvDYKAICAIFBcBWwmAQ2lB0cR/EnPOL2YmdjtjPkj8QC7TQSHWRxh/tXIb5eCACKx/Fzi/x7jw9qORENEFk5cMVtu8XbyVVG+yrahCUqJC48aNYRAAz53LEfSWkgcva/sOnCNHHB3i7cLejUIVbV9PEi6cycFDqOQIrDy9Eu/8+46S2YNHe2PTBHTb5YIdUVmIjqc82EQv922AZ3vn1ebx38OwW2oqgjrH5GsXESBhdRTE5D9BQBCwNgK2EgBHahbamMrMWmpOFWYtiQCoRcNRy1Gk9N3yqXH1IfTo+76LKVsnIj4tXm1/9ZZXEeYVptalUDIEnJ1z/pTdajZHdNWeuOW9NUin+HB6xE4DnJbt7jbVEeojjgJ6GBWn7XrmdUzdNhVLopaYXH4t1RkLTxxDdno1tZ3Ds+gJgNzBUrt6sRQEAUFAELACArYSAEWVYIWH43BDXL8MLNIEIXZyI5/v77Hq3CYsP220BOhRowcG1eX44ELWQOAiOXHE+DRFtSdmwiWgGhJ4UDPhj0OI3NWiKoaS4NcuPEAcOqwBfO4YHDeRNXfvb38/j/DnnNIeV2PI6iXbKGiT4pX6UxBU8vQVpw0rPggZShAQBIqEgK0EwCItQjqXAwTYo2DJM8C1S8abuf09xPuG4d31Y9Q2TnY/sdNEEUBURIpXyKRwLWuPxCq2fRsoH2+2XwvoRZBjr1EW+vqT8Ocj+XiLB7bZVYw9h2X550QepY1yAABAAElEQVQc2fNdxh3Nw/B0z3p4ptUzWBezDonpifBx8cHbnd7Ght3V8Ft0DKr5uVOqNQrPQtylbjD8KGWekCAgCAgCZYmArQVAtnLuSFyFeA2xRjqgmlD5QWD7t8DxFcb7aXgnbrYbhf9tHIer6VfV9jc7vIkQTzFmVwEpYiEylvPxxmAh5eO9fM00TIhhKKcbqRjZs4kSt68hxe8TKjkCLPTNI3tK9sTdGhVvkh2FPaVZAKziVQWTO03GnCNzlNh+Vb2rooH3NYzuVltx+BB715I/BxlBEBAErIeALQXAZ2mZ7xHzLxDb991GzAIg//rHED9PPJNYyNERuEg+PavY8TuXfKoCA7/AX6f/xtozaw2tuC38NtxR+w61LoXCIXCdskD8tf8C5pHgt4s0T7pEGtjUU7twbf9qdK8XgAnTOdSmkLUQcKZ9W47PdzEpLc+QrA1MTstUNKzs7du7Vm9Vw11Hx9M3zwDSIAgIAoJAGSBgKwHwAbqXz4gXEbMn8PfEBoqjwl/EQ4hFADSg4qjHDPJq5JAvWem5d0DGTUP+D7GVshSDeMNtBbgFgLV/ogUxIJL/ke3Kdp9JULx4/9x/HtczcmL8mV9VI8BD0fRtnfsx5s3/RjldqY4I2eY4FVRnvI9cSEbajSy0qRWQpzt/brs3CMbvu0/ALWQ10uP6wtfVG90oPAu3V2ajvlySz7gBCTkKAoKAPSNgKwGQ8n8pW7730DFIB4Bd1PaUTrs0ORoCq94E4o4aV911LG7W7o7J655Vw2DwyQmdJiDIQ++jYLxUSqBt3XQs2n1O0fbxdq8euTpXRr+mYYptXyeKEVeZtFN75hg1UyzMCBWMAOc+3pRrx8fH2OR0dKAg2POe7KR7cXi1iwhI/hw3Kl9Bj0Ze+KrvdAmdo4uUNAoCgoAjIGArAbAp3fzL+QDAW8Gh+ZyXU46AwJFlwM4fjCut3hbo9SYWRy7GP2f/Udt525e3f4X0EWBvULYtYxuzNUcukQOvvgDXpKqvIvQNovRs/p6muX61WicRAPVx1rY+/vNOBWtzWZm32K/Rlrs3pcEzUGZ2Jr7e+zW+O/EdblbOeTb/xq7GqugVuLPOnYZuchQEBAFBwKEQsFW4Fk43QDFALFINOpNk8aycsH8EEs8BS58zrtOVTD3v+Q4XKdbfBzs+UNuDPYKVrV+1QQoqAmcoKPD0lcfQZdo6PPrTDqw4dDGP8Ofj7ozhHcPx53Nd8fcL3fBI54g8wp86YG5BBEBzRPLW/T1cdFPhsTb12EXjV1N0UjSG/z0c3x74lgyZjYJ5p6qd0C6sXd6BpUUQcAAEIiIiaOegsglzRqGaNWti8ODB+OsvttLKS5MnTza5xnwMQ713794mFxfmOm1Oc5OLpWIzBIyvudadYgcNN5B4hs6wrLp4mPhfnXPS5AgIZJM92sIngFSNQ8JdH+FmQG28vfpJXMs0bl1O6jTJJNm9I9yeLdfI+XhXHLyoaPv+PRlvcSre2uXwLf2ahRUqE4RoAHOgTCVbyf9OxWPjsTikZNzAB/e21MWYw7HM33VWOVcv1FtJtca2fB1qB5nkP952YRsOxR9Sx3Cp7IKxbcbi4SYPk92frd6f1emkIAjYBAH+vmDu0qUL6tWrp8yRmJiIPXv2YOnSpQqPGzcO06dP150/LCwM/fr10z3HjY0aNdI9l9914eHhutdIo+0QsJUAyJ+av4m/I56Vu3z2/uXXgknEEcSPEgs5IgKbSa6P3mxceQvK/NdyKOYf+x3/XjDK9RzsuUfNHsZ+Fbh0kNKx8Rbvkr3nkJR2QxeJMF93JR/vfe1qIDzIS7ePpUatAGipT3ltj4xNxrqjsUpMvu2nryAjNwi2i1MlTBzQFF6a7VwDBpxbd+rdzZW4fJx71xLd1+A+bDq7CRvObkA9/3qY1m0aGgY2tNRd2gUBh0Jg9OjRGDFihLrm7OxsvPjii/j8888xY8YMDBs2DG3bkmmPGbGA98MPGvMfs/OWqsW9ztJ40l4yBGwlAK6gZT1DzBpAg6D3S+5SeXt4DLFGgsg9Iwf7RyCGlLvrpxjXGRAB3DkdZ5PPYvpO49tiqGcoxt8y3tivApYSUzKxmAQ+FvwOXzBuK2qh4PAitzauomj7WCtV3MwQWgGwom0Bf73hJP6guIjmlJl1E/9SzL5bm3AYUlPiQMzDbqll2qhTY1wndZ6E2Ydn46mWT8Hd2ZjRQ6e7NAkCDo0Ab+F+8MEHmDVrFpKTk7Fs2TJdAdChb1IWryJgKwGQJ/iaeDHxvcSsD+b9khPEvxPn/bamRiE7RyAtMSfky83ckCSV6eNzzw/IdvPGhA0vIJUCEBvonc7vUJgMX0O1whyzyYGDt3ZZ6GObPoM2yhwA3nYc2q4mhlA+3mDv/Mxlza/Ur5dnAfAGBWE+efk6GlQhO1Md6tEwJI8AGOrjhh4kUFchrWphKPtmtsUtXfZeH9t2bGGGkT6CgMMj4Obmhvr162P37t24dIn9NYXKKwK2FAAZswvEn5dX8CrcfS1/FUiINt52rzeAGm0x/+g87Ly0U22/t8G96FK9i1qvKIXjl5Lx0u/7cIC2e/XIkzJGDGhRDfeTbV+bWv5WjYlY3gRADqzMadbYK3o9pbpLSc/Cnrdv093O7VYvmOwkK6Mt5ThmoY81qQ1JWNRiovc8uO1y6mXFa/2P438oqds6VdMPAWPpemkXBMojAklJOTsWVark1Z6Xx/utqPdkawGwouJa/u776mlg36/G+4roBnTJ0Yr8duw3tb26d3W83C6/CEBq13JTYK3fj1tP4/0VR3U1fiyYsLbvLsrHq2ePZm0gHHkLmPMaf7/5FP4jLSpv4WqJ2/rQdrk5BXi5Yu/bfQvlLMPXsrZv+8XtZLM6X8ndeyM7xybzzc1vYuHAhfB39zefQuoVBAGOw8nxIfWoVqCn7meMHbvOXKGA+DoUSJ9NSxr+06TVziDttoHy62voUxrHI0eO4OTJk8pUAweyL6dQeUXAWgLgumIAxN/ufYpxnVxSFgjsmWOclbd+h1DWicpOSM5IRlRClHruyRZPwsulaA4M6sUOWDifkIqX5+9T8sNqlx/s7Yq729SgLB01UC9Uf+tS27+kZa22y5EFwJzgzJd14dgSqS8Acmd3Fyfda/Qax6wZg63nt+Y5FZcahx8O/oBx7cblOScNFQOB2f9G49O1bKmUl1a92F3XDIGFv74z/sl7AbW80Kc+Xrytge45jkV5QhPsPb++ugNYuZG1fv/99x/Gjh0LdgaZMGECLIVm2bBhgxIOxtISPvnkEzz/PGd7NSVL1/H316lTp1CrVi3TC6RmUwSsJQDWoVWavq4DLAUE564+IfdoeLXmb3hjrJDck3KwUwSySEOyZ65xcQ36AX41lPqBywdM4qO1Dm1t7FeOSyxkLdl7HhOWHKQ8sEavXvoewxPd62Acfem7ORdeKCkpVFoBsKRj2fJ6DtOyOfKykj5ND59eDUPJFo+1dDmrqB3sRU4yoYrmjzWp1qD2Ye3zCIAc1+++hvehV81e1phCxhAEHAKBkSNHgllLzs7OmDNnjuIBrG3XlvML58L9mjRpou2uli1dx99f3t7eaj8plA4C1hIAI8yWywLheuJPid8nvkjMFEb8GvFg4j7EQo6AQNRaIPm8caVtHlHL++L2qWU/Nz+E+4ar9fJaSEjJwJuLD+Kv/WziaiTOy/vRfS3RgWL4lTZpBUB70wDGJqVhLYVpWXP4kiL8pVOYllmP3aLY65njxNu5IzpFoKqfu+K9WzekeD8K1zOvW9RED643GF/u+RK+br7g8r3170VN35rmS5G6IFDuEejatasaBzAuLg6bNm0CawLHjBmjtLdv314Xg+KGcynudbqLkMYSI2AtAdB8IRz+hfdYXjQ7wYLgWGIWBLkPC4JC9o7A7p+NK/SpBtQzyu774/ar51oEtyiU4b16gQMWNlLKtvEL9uFSUrrJ6u9rWwNvD2gCH3cXk/bSqKSkpJhE7reXN+lD5xPxxsID2Hc2MQ8MLAyyw4YeTRrYVK+5wDYWfPfG7VVs+1ZFr8LvA35HHT9+FzUlzk7zQ78f0CyoGVycSv95ma5GavaEwPBO4Yqtrt6a2AZQj7idt4f1iO36LNG3I9rlsQG01NdW7eZxADn0C2cCWb9+PYYOHYrDhw+DM4QIlU8EbCUA9iS4yGXUIm2gM9MsnpUT9oNAMoUBOL7CuJ7WDyu2f9zAxvRaAbBlSEtjv3JW4q3LacuPYBbZCGmJv+CnDGmuZOzQtpdmedq0aThz5ow65QMPPKCWy7IQQqFY9IQ/XtMRC3ERi7PepIwkLItahgXHFyAyIVIdguvj2+vHoqwopgoqGFIoFALssGHJacPSAGx/ailEkaVruD2CzBvsjXx8fDBv3jwlk0d0dDQ+/vhjvPEGRXsQKpcIVLbRXbEFT6N8xm6czzk5ZU8IsOdvrpckQMZZLADmEudJ5R9fA7UMLZ8C4L6YBNz1+aY8wl/vRqFYMbZbmQp/UVFRSuBWwzPo3LkzHnzwQUPVpser5C25aM9ZHNXkztVOGOrjjlY1DWa/lCymhh9eItvIv5/vhvlPWSfcSkxSDPr83gfTtk8zEf54HUujlpInMcedFxIEBIHCIhAcHIy33nqLcmXfVFLBGULCFPZ66ec4CNhKA7iKIBhDvJ34FzM4HqL6U8RLzNqlam8I0BcAtNu/dXoAAUYbP639H2WWVLbU7O0WSrIeDkD85foofLbuBLIMXgk0oAe98U/o34QySdQs8y1vTtuUnp6zHc12gF988UW+3nklwYOvPRl3DWuPxGI1xefbSWnXGJZRXWsreOiNzQ4xiamZ6EPCcmghgzLrjWOprYZPDTBrNX8cgHxg3YHgNG6yxWsJOWkXBCwj8PTTT4M9eWNiYvDRRx9h8uTJljvLGYdFwFYCIMdRYOvR2cTsBHKcmKkBcTXiGGKJtUAg2DVFkxnnFWOIF7QZYbJcrQBYL6AevF2LZ7BvMqidVFjQGUdBnfeS9k9LrSmA84z7W9nF9s1ff/2lpGoyrO+pp55C69atDVWrHlMybqD/55tJALyeZ1wO1vzWXY11heE7m1fN0784DRxuyMc1bzgdFno58DhrAFuFtML9De/HbeG3Scq24oAs1wgCuQi4urpi0qRJeOyxx/Dpp58q+YH9/Y3afI4V+Oijj1rEy9PTE19++aXF83LCPhCwlQB4lm6vFTHbAQ4i7kzMdJKYhcIPiE1/WalByM4Q0Gr/PAJoU7+/yQK19n/sAFIeiLc95m47g/f+OoJUCvBqIM7ZO/bW+niqR104O9nKcsIwW8HHtLQ0vPDCC2rHoKAgvPvuu2rd2gVPV2dF86k3LmtEWcvn72nZ4F3vuoLaUjJTsPzUcvx+/HfSL1fCb/1/072EtX23hN2C+gH1dc9LoyAgCORFQBs5IO9ZYMSIEcoWMAt7H374Id577z2lG18XGxuLn3/+We8ypY2FRXMBkK8raE6LA8oJmyBgKwGQF8uuf2/kMteFHAmBVJLPDy82rrjlMMDZTa1zmA3ttlt5cADhcCXj/9iPDcfi1PvkQt0QL3wytDWakw2bvRAbZ7P9n4GmTJmCwMBAQ7XIx3MU0HotafLcKXYhp6rTI87Cceh8Em2rVkJHCnXD27rcVtOCd6TeGIVpO3blGOYfn48/T/4J/pwZ6HD8YTQJyhtfjDWDetpBw3VyFAQEAVMEOOhyQVS5cmUcPHjQpNvEiRPBXFQq7nVFnUf6Fw0BWwqARVuJ9LYvBA7MB26kGdfUerixTKWDlw8qXsCGRkd3AFl+4ALeWHQAV1NMnQZGdo7Aa3c0KlKmCQMmtjqyx69W29e2bVuMGjWqSNNx+jrOWczbt2vIps/glcvCriUB8O7W1cnb0VvJtetro3A33x34Dp/u/lT3XhaeWKgrAOp2lkZBQBAQBASBfBEQATBfeCrwyT28U59LNcics4qp5kVr/8falwjfCENvhzompWVi0tJDWLj7nMm6q/i6YToFde5WP8Sk3R4qL7/8MlJTU9WlsOOHk5OTWi9M4eHvt+VJX8fXRZGN3ynKUcoZOMyJw1bYOnRFl2pd8giArPVjh447a99pviSpCwKCgCAgCBQTAREAiwlcub7s/F7gwj7jLZo5f/AJrQDYIqQFpe8qe7s444ILV/rvZDxeIkcP3v7U0oCW1fC/QU2tbtOmnaO45bVr12L+fNLO5hIbYnfs2NFQLfSRw7NsjYo36c8p2NqFB1JqO1MtqEknK1TSSLN8k/55OHvkGa1xUGM0D26umBewwMeCX9Pgpnn6SYMgIAgIAoJAyRAQAbBk+JXPq7XaP/bsbXq3yX2yo4TWAaRlcEuT8/ZeSb+RhY9WHce3m05SrCvjan3dnfG/wc0wqFV1Y6MdlTIzM/Hcc8+pK/Lz88PUqVPVOhf42Ry7lKykXWOP3Y+HtjI5b6iw7d5XG6Lg5eqkbOneSvVeZNOXX+YCw7XFPZ5MOKnY9nF8vjEtx+DhJsaYktox3+3yLkI8Q8SuTwuKlAUBQUAQsDICIgBaGVCHHy4jBdhv1DChGQl/bqbhXc4kn0FCOjmJ5JIjOYCwrduL8/ZS8OJkw/KVY5d6QcqWb1W/vFopk45lWPnss8/AHnkGeuedd1ClShVkUG7dbafic+LzUYo1rUZzXN8GqBHgabhEPbIG8GfKx9uhTiDcyPHDVpSRlYHV0asVwW/XpV3qNOzk8VDjh3S9Auv411H7SUEQEAQEAUHANgiIAGgbXB131CNLgXR24M6l1qax/7hVq/3j8BzNQ5obetvtkQM5f0caP9b8ZVCAZwO5OVdWnDwe6RRBAZRpD9RO6cKFC0pcLsPymjdvDg7WyvTx6uP4ZqPRI9jQh48ctPkRcmQxJye61+4WcvGa9y1unbWR9yy9B6eTTucZ4mTiSey/vB+O9PKQ5yakQRAQBAQBB0ZABEAHfng2Wbo29l9IY6BGuzzTaO3/6vjVsfutupgrKYqt33bKXKGlZtV9laDO9av4aJvtsjx+/Hhcu3ZNXRs7fjg75/z59mwYkkcAdCXBtmu9YFhKYK8OZMMCx/zqUaMHTh8+rc7iWtkVfSP6KrZ95SV2pHpzUhAEBAFBwIEQEAHQgR6WzZd6ORKI3mKchp0/6EfcnLQCoD2Hf2EN1IJdZzF52WFcS7+h3gYr+p7uWQ/P96kPFpTslTgV3e4zCfhp9S6sc+8CJ++/kXXtipLrt3v37uqy24UHwM/DRYnPx/mJ2Z6va/1gcPDm0qAraVcQ6K4fg5CzdMw6PEvxEmeHDg7a7O/uXxrLkjkEAUFAEBAE8kGgdH4h8lmAnLIjBLTOH06U1aHF0DyL4+wMx68aMvvBbrfw4q+lK3H9Vh66ZHIP4UGe+Pj+lmhL3q72SNdJUN14PE6Jz7f+aKwal9AlqCY86lI4nqgtSlR+7do5M8nSZ7ugJtn6ldY2dmZ2JjbGbFRs+3Zc3IFV965CsEewdllKOcIvAvP6z0PjQP1UcXkukAZBQBAQBASBUkFABMBSgdkBJsmi0B97fzEulNO+eQUZ67mlQ/GHTAJA2+M23rqjlzB+wQFcJiFQS8NuqaXkrPVys9+P/R7S+D09d7d22WrZo14HvPJQH1Srxum0TSk8KG/cPtMe1qmdv3YeC44vwKLIRbicelkddNGJRXi8xeNqXVvQy96hPS9lQUAQEAQEgdJHwH5/CUsfi4o94/GVwPVYIwY6sf/4pHb719vFG/bkscnas3cph++v288Y74NKwd6ueP+eFkraMpMTZVThLBxZtD3topNT+JbagfAhATVZs2WdlXYNaVE74X/tNOX/nVtGq6b3g9i9GLF8hBLDz3wRS6KWYHTz0bpeveZ9pS4ICAKCgCBQ9giIAFj2z8A+VqB1/vCvBdTuobsurQDIAXvtJQD0ruirGPf7XkTHUxgbDfVtUgVT726OIG9jHmPN6VIrpmVmYUvkZSXtGufcfeX2hrivXd6cu2yT2J2cOg5SmrbsmL3YsfhHpJ87DGRnYe7KlXB1pa35MqJmwc0Q4hGC2FTji0J17+pgO7/B9QaL8FdGz0WmFQQEAUGgOAiIAFgc1MrbNYmUBi1ytfGuOPQLJQI3pzwBoEPLPgB0JjlKfLb2BL5cH0lb08YVc4DjiQOb4r62NcpMMGGhb+ne81hNAt+mE3FIy8xWF8jhWfQEQO7w4b0tMG/uHDw2fpza/+6770bfvn3Vuq0KWSRoJmYk6jp1OFd2xpD6Q8D5envW7Kl48naq1sluXgJshYmMKwgIAoJAeURABMDy+FSLek9s+3czVzjhlG6tHtQd4ey1s2CPTwOVdQy3yNhkCuq8DwdIW6al9hEB5OjRCjUD8wZA1vYrjfJEyjOcSoKgOf2jCIRZcHfJG4T50L49GDPmKfUSHx8ffPzxx2rdFoW4lDgsPLEQf5z4A3X96+LrW7/WnYaDN9/f8H6EeobqnpdGQUAQEAQEAcdAIK+axzHWLau0FgLZJPjt+dk4Wr1bAT/9VGja7V++gLeAy4LYhu6nLadw12ebTYQ/F6dKeLVfI/z2RKdSE/44C4e5s4kBExbuulE4Fi1V9XPH8I7h+OqhNnDWCTwdGxsL1valpxsdWObMmYPw8HDtMFYpZ5PQv+XcFoxdPxa3LbgNX+z9AheuX1Dazl0jrbAOBbgHiPCng4s0CQKOhEBEBAe+r4yff9Z891u4gcmTJyt9ub+BOQZpYGAgOnXqpKSjvH79uoWrpdmeERANoD0/ndJY2+l/gIQzxpksOH9wB20GkNp+teHn5me8rpRKFxPT8MqCfbSlavRA5akbUjDnj4e2RNNqtl9TYkomNhyPxWpKu7bxWBx6Uuy9z4e11kXgVrJBvEBr5th8tzYJRZOqvha3pDnX73333YezZ8+qY02cOBEDBw5U69YsTNk2BfOOzcsz5E1y8/gz6k882fLJPOekQRAQBBwfAQ7SzlwUCgsLQ79+/ZRL+Lvq5MmT2LZtm8IsSG7evBlBQXkjRxRlDulbugiIAFi6eNvfbFrnD68QoEHOH7jeQrUawLLY/l227zzeXHQASWnGoM78HTa6a2281Leh7naq3n0Ut232v6fx14EL2HH6Kji1nIE2HItV8vHqBZVmG8T7dZw9DNdqjy+//DL++YcE8lwaMGAA3n77bUPV6sfetXqbCICc1q9L9S6KbV/3Gt2tPp8MKAgIAo6LQKNGjfDDDz+Y3AALfbfeeiuOHz+upKr8/PPPTc5Lxb4RqGzfy5PV2RSBFLLnO7LMOAXb/jm5GOuaUuqNVBy/YgwA3SKkheas7Ytz/ovGc7/uMRH+qtF26tzRHfDmXU1sLvzxHa6jwMz/nbxiIvxxezIJpDvN0sxxO1Nh37L5Dfqzzz7LuYj+b9CgAWbPnq1suaiNVi50rNoRNbxrKAGcH2/+OJbfs1yx/WPBkB0+hAQBQUAQyA+Brl274pFHHgE7CC5bpvktye8iOWc3CMi3vN08ijJYyNkdQFaGceLWw41ls1J0UjRu3DRq3krT/o9t7N5fftRkRXe3ro5Jg5rC111fYDXpbKUKb+eupy1fA/G2c5/GlHqN2lvVKH56s127duHJJ43brez0sXjxYvj5lWw7+0zSGXy6+1MMbzIcrUJbGZatHjmEzze3fYNq3tXgUrn0cFQXIAVBQBBweARatMhRBly6ZJp1yeFvrALcgAiAFeAhW7zF+CjjKXcSNoLqGetmpfjUeJOWMM8wk7otKzNWHzcJjMyp3O5uU8OWU+qO3adRFfxV90KOPR/Z9NWitHIlpbi4OMXpIy0tTR2KtYGNGzdW60UtsKf2/+37P/x+7HdFaI9LjcOsfrN0tZHhvtZ3LinqeqW/ICAIOC4CSUlJyuKrVKniuDdRQVcuAmAFffDKbV85abz7wLq8X2msm5Xi04wCoHMlZ/i6+Zr1sE316MUkk8wetzetUibCH99dGG05//J4R6vd6I0bN3D//ffjzBmjE86ECRMwePDgYs3B2/RzDs/B9we/x/VMo1fentg9WBezDn1q9SnWuHKRIFDeEeCYnWeumAaRL6t7rkXhq/TCQ5XVegqa988//1ReLgcNGlRQVzlvZwiIAGhnD6RUl3NFowEMrJPv1FoNYKB7YKkE/2W7kvcotZvB34LDvLxxZ/E1Y/neYO7JHWTLxx7G425rUJjuJeozfvx4bNiwQR2jf//+iiG12lDEwsQtE7H89HKTq5wqOeGe+vegLJx2TBYiFUHAjhFg4a/vDKMDVlkuddWL3dGAzEvsmfjlNSoqCtOmTcO///6LNm3alOi7y57vtTyvTQTA8vx0C7o3rQYwiDSA+ZA2AHSQR+m4+q8n71ptuJdHu9RGeJBXPqss2al5O87grcUHkZl1E+xg8sAttUo2YD5Xc2y/GTNmqD3q169fYqePR5o9YiIA9q7ZGy+0fQF1/PIX7tVFSEEQEAQEAQsI8MsqxwE0Jw5TtWDBAnBsQCHHQkCemGM9L+ut9gY5f2jj/xVRA2i9heiPxCne3iXtn4ECvVzxbO96hqpVjzdorvf+PoIft5xWx52w5CDahgegvg3exPfs2YPHH39cncvb21tx+vD3L74jCQ/WNKgp7qh9B85fO4+X2r2E1qH6sQnViaUgCAgCgkAhEdDGAUxJScG+ffuU8C9Lly7FW2+9pWgDCzmUdLMTBEQAtJMHUerLYOHPkP6NJy9IANTYAJaGBnAuhX05GWe0Y3uRtmRt4fHLQZ2f/XW3iaaRTSHH3dYQ9UK9rf5YLl++jCFDhkDr9DFr1iw0adKkUHPFJMUgIT0BzUP0s7BM6jQJHs4eug4fhZpAOgkCFRABtrvjrVd7IF6LPZJeHMAvv/wSzz33HD788EP07NlTDRRtj+uXNeVFQATAvJhUjBbt9i/fMTuB5ENaG8Agd9tuAbNQ9snaE+pqGlTxxrD2NdW6NQvv/HnYRPjzcnXCpw+0VkK7WHMeHovtZoYOHYro6Gh16DfffFPxAlYbLBSupl3FzP0z8dux31DLpxb+GPiHbqw+Txf7/PGwcFvSLAjYBQLsdGHvdnd2AZTZIp555hklEwibtIwbNw59+/bV3SY2u0yqdoJA3g19O1mYLMPGCGgdQDilm2dgvhOWpg3gpyT8JZAQaCAO9OzsZJuP6ht3NkJ1fw9lKn7zXvRMF5sIfzzBa6+9hnXr1hluC3feeSc4z2Z+xJ693x34DncuvBNzjszBjewbOJl4EosjF+d3mZwTBAQBQaBUEHj//ffh4eGBY8eOKXbMpTKpTGIVBGzzq2qVpckgNkVAqwEMqpNvCJhs2irWCoDsBWwrOhl3DT//e1odvmfDEPRoQCnqbERB3m747pF26EP5fJeQ8GcrLcCvv/6Kjz76SL2LevXqYe7cuXByclLbzAs7Lu5A/0X9lWDO1zKvqac5gDPb+QkJAoKAIFDWCFStWlXZBuaoDe+++y6ys7PLekkyfyERkC3gQgJV7rppg0AXYP+XmJ6IrJtZKgS23AKe8vdR0nLl5Nl1qlwJb91l27AvfFONq/ri+5Ht1fuzdmHv3r0YNWqUOqyXlxcWLVqEgpw+ONi2VvDmAXrV7IWxbcaijj8J7UKCgCAgCBQTARbY3nnnHXz99dcWR8jvnPYi3t2YOXMmTp48qeQLHj16tPa0lO0UAREA7fTB2HxZWg1gEez/eF22cgLZEnkZa45cUm/9oQ61yBHDOvGwYpPT4EF2Pj6lmDqObyQ+Pl5x+khNTVXvi50+mjVrptYtFWr61sQDDR9Qtn5bBLfAuHbj0LZKW0vdpV0QEAQEgUIjwHnKT506pbDeRXzekOWDy/nlNeeX2VdffRVvvPEGpkyZgpEjR0pYGD1Q7axNBEA7eyClspwssq8rSggYjQcwr88WAmAWaf3+Rw4ZBvJ1d8bYW60TjPnguUQ8/vNONCFN38wR7cCaxdKgzMxMPPDAAzh9+rQ63euvv4577rlHrXMhg/Ixuzq5mrQZKk+0eEIJ53Jb+G35fgEb+stREBAEBIGCEGDBr7DUvXt3TJw4scDuLAAyCzkOAmID6DjPynorVULAGLd0CwoBo92GpPdA+LuVLF6d3o38vjMGRy8mq6ee71MfHPuvpPTn/vO495utuJCYhrVHY/HhymMlHbJQ12dlZWH48OFYs2aN2r9fv3743//+p9YT0hLw/vb3MXDxQLCzhx4FuAegb0RfEf70wJE2QUAQEAQEgWIjIBrAYkPnwBdqt3/5NgrIAqINAcPCn3Nl635sktMy8dEqo2BWO9gLIzpFlAjgbNIozlhzHJ+vizQZJ4qcTFjbaEstIBtBsw3MvHnz1Lnr1q2LX375RXH6SLuRhrlH5uL7A98jOTNH6OUcvo+3MAaHVi+UgiAgCAgCgoAgYAMErPtLboMFypA2QEDrAOLmSyFggvKdJF6zBWyL7d+vNkTh8jXKTJJLr9/RCK7OxVdOp9/IwvO/7sHKQ0Z7Qh762V71lBy/lW24BcyG1RwY9aeffsq9G4C95FauXAlfP18lfMsXe77ApRTTtf146Ec83ORhJYizeqEUBAFBQBAQBAQBGyEgAqCNgLXrYbUaQPYA5tQX+ZBWA2htD+AYSsL+/WajPUqnOkG4rUmVfFZT8ClXihno5Wr8aLuRMPnhfS0xsGW1gi8uQQ8W/saPH4+vvvpKHSUkJARr164FawB5K33a9mm4nmnMcMIde9boibFtx4rwp6ImBUFAEBAEBAFbI2D8lbT1TDK+/SCgDQJdQAgYXrTWBjDQw7oxAKetOIqMGzlxo1gOfat/4xLbu7G32pS7myPq8nVcItu/mSPaokUN69stmj9QDuo8ffp0tZk941avXo3GjRsrbRw/8bFmj+HzPZ8r9WZBzRTP3vZhtgtBoy5GCoKAICAICAKCgAYBEQA1YFSYorkGsIAbt5UGcOfpK/hr/wV19vvb1kTTapSVxArEqZ2+Hd5WGSnU190KI+Y/BOfC1Gb18Pb2xooVK9CyZUuTC4c3GY6t57diWKNh6Bsuzh0m4EhFEBAEBAFBoNQQEAGw1KC2k4nMQ8AU4ADCq7aFDSA7aWjDvnAO3pdut07YFwPSpSH48VycEJ23fpmcvJwQNjAMMx+fiQ4dOiht2v88nD3wU7+ftE1SFgQEAUFAEBAESh2B4lval/pSZUKrIMAhYCifrEoFbAGzXZstNIBL9p3DvrOJ6jKeJgeNUJ+iaeoSUjLwHDl7nEvQD6GiDm7Dwg8//IBnn30WlVwqIfiOYDT4oAECbg/AAa8DNpxVhhYEBAFBQBAQBEqGgAiAJcPP8a6+YnS4UBZfQBYQdljIyDZ66FrDCzg1IwsfrDCGfanu74FRXWsXCcsTl5Ix6MstWLbvPJ6gIM8pGRqhtkgjFb/zb7/9htGPj4Z/F3/Un1YfYUPDFA0gj/jbsd8QkxRT/MHlSkFAEBAEBAFBwIYIiABoQ3DtcmitA4grpVnzCs53mdrtX+5oDS/gmf+cVAIzGyZ+jcK+sM1eYWnd0UsY8tVWRMenKJccOp+E6SuPF/Zyq/RbvHgxHn74YdQaWws1Hq8B1yDToNVdqnWxyjwyiCAgCAgCgoAgYAsExAbQFqja85haB5CgOkUKAcO3VVIN4EXyyv1mY5SKUNvwAPRvUVWt51fg7ej/I+HxffIcpqJKXesF4/k+9dS6rQsc02/o0KHgbB9Ju5Lg08KYr1g8e22NvowvCAgCgoAgYA0ERAC0BoqONIY2CHQB9n98W+YaQE5NVhL6YOVRpGYa09BN6N+k0GFf9sYkYNryoybTj+wcgbfuagxniv1XGrRx40YMHjwYGRk52+JXN11Fs0eawcvXCy+0fQG3h99e6PspjfXKHIKAICAICAKCgB4CIgDqoVKe27QawEIIgFdSr6ho+Lj4wM3JTa0XtbD/bAIW7j6nXja4VTW0qln4+HytawXgBcoR/OnaE3BxqoR3BjXDsFtqqePZqpCYnoiMrAxE7Y9C//79kZaWpk714fsfYug9QxHmFUZrclHbpSAICAKCgCAgCNgzAiIA2vPTsfbasshRIiHaOGoBDiDcUasBLMn2L2/fasO+uLtUxvh+jYxrKWSJBcC4a+kY3Ko6bqlt3aDU5ktIz0rHr0d+xcwDM9HUoynmj5yPa9euqd0mTZqEl19+Wa1LQRAQBAQBQUAQcBQESmffzFHQKO/rTDxTpBAwDIc2BAxnsiguLT94ETtOX1Uvf6JbHVQj79+iEufxnTKkuU2Fv+yb2VgWtQwDFg3AR7s+QnJGMv5L/A/pAenqcjnu39tvv63WpSAICAKCgKMgEBERgcqVKyv84osv5rtsDnJv6Ovqaurs1rNnT/Wctk9YWBj69euHuXPn5js2n4yNjVVCadWpUwfu7u7ga++//37s2bOnwGulQ8kQcDQBcCjd7j/EHECODcnM1885xdg1NIk4OffYlI5amkwV3ofk8xuIzc+3oLaNxKzqOUs8kbh8kHb7l++olIJAp5HN39TlR1QMQ33c8GSPumrdvMBBog+TZ29Z0O5LuzH0z6F4Y/MbuHDdmKWE1+LbxldZEsf9mzZtmtj6lcUDkjkFAUGgxAhwukwDs5B244blMFo//vijxe86wxitWrXCyJEjFR4yZAgCAwOVNJjDhw9XhDlLCz5+/DiaN2+Or7/+Gk5OTuBrWThdsGCBEkh/yZIlli6VdisgYC5AWWFImw7BBmlfEo/NZ5a76Bz/UrNrJh8PERvoFSqMJL6NmOOfbCVeSexJzORNvIJ4EzGru/oRjyZ+gdjxKf6k8R5c6Va9Qox1CyWTPMDF1AD+tPU0Yq4YgzW/cntDeLnpWx9cS7+BJ2bvojAvW3BAEyjawvKs3pyQnoCjV0wdTVJPpeLUtFOIXRiLRx99FJ9++qnFL0SrL0gGFAQEAUHARgi0a9cO8fHxsCRobd26FUePHkX79u3zXQE7xnFQfOZ58+bh8OHDeP/995Vr/vjjDzDr0QMPPIDLly9jxIgRYGHw119/xX///YeZM2cqQim3s4ZQyDYIOJoAuJpgmEeskWTyAFMpT4uxYQwVPyQ+TMz7eROI2XJ/CDHTPcSMCe/tsZvnQWLu/yyx45NWA8gOIPQWWBBpt4CLYwN4mez1vlgXqU7TrLov7mlTQ61rCzFXUnAPxfdbc+QS0m9k43EK8BybZHS40Pa1VblXzV5oE9pGGT77ajZivo5B1DtRuH70OvjL6ttvv1W2PGw1v4wrCAgCgkBpIfDYY49RSK2biuCmN+f333+vvOxyv6IS20c3bNhQuWzZsmV5Ll++fDn27t0Lf39/JZ0maxMNNHr0aPTp00exueYXbiHbIOBoAmBhUJhDneKIdxKz9s5ArA2MIN5haKAjbyPvJW6d29aSjmx4wFvJBuL+JC0p2kFDm2MetUGgC+EBzDdp4gTiHlTk+/549XGwVs9AE+5qQgKU8Q/d0L4r+goGfrEZxyjDh4G429WUTEO1VI78JTSq3ihkr83GkVeOIHFbIkAxBwcNGoSff/5Z2aYolYXIJIKAICAI2BgB3n5lLeCqVatw4YKpycv169cxf/581KxZE3379i3WSpo1a6YImJcuXcpz/aJFi5S2gQMHwtPTsAln7Pbggw8q1y5cuNDYKCWrIlDeBMA+hE5tYo4szNq9D4ifJGZiAZApIeeg/n+VSoZzfNQ7z50NfbjsmGSuASzgLtJupIFTwRmoqBrAC4mp+G37GcPluKNZGDrUyStEso3gU3N2mwh7HCB6ybNd0TDMGGRZHaiEBX7jvXDN9MvOMCTbwkwYPQGHZx/GzRs50aZvv/12ZVvDxYWVxUKCgCAgCJQfBFi7x0Htf/rpJ5Ob4q1cjnrwyCOPFNvkJSkpSbm2SpUqJmNzhZ08+IWbBVA9MrSfOHECqalGEyK9vtJWPAT0DbGKN5Y9XLVes4jlVP6EeDjx/xEbvAr8qaylAKqczW3gPtW1J6nM55kM1+fUNP+/8cYbMHhHsbDAbJeUEm9clm81Y9lCie3htFRUL+B/jseB/DkUYu0+p3zTow3H4hCXzDvyOTSI4gN+cG8LuDk7GZqsevx639eYfXg2Pun1CTpU7WAyNj/Lf/75R23r3r07+A3Uzc1NbZOCICAIlE8E2OTlahrrBPJSTd+aunFQOVyUpbzfHDjf0ovzmaQzSnxRw0z59TX0scWRNW0vvfSSIgC+/vrr6hRsz8eevWz3XByKi4vD9u3blUt5B8WcTp06pTTVqlXL/JRSZ80jE7+wnz59Go0bN1bqJfmPszgxMxmC+ZdkPEe/trwJgHrPg0QPhViAO03M1qzbiJlYwuDt31lcIdpL/CAxa0YN28C3UPkkMXsF69KUKVPg6+sACsIMozYPrl6696JtNBcA/dz8tKcLLG+JNAqcTar6IjxIf06O5zd5YFMs2XsOl5LS8cnQVsV+4yxoUYtOLAILgExPrXkKU7tORb/a7OsD8JYEhzwwUP369bF06VLd7QlDHzkKAoJA+UFg3rF56veD+V0tGrgI9QLqmTcrwt+QpUPytHPDmJZj8HSrp3XPPb/ueUQlRqnn8uurdrJBgX+77r77bvzyyy/YtGkTunXrpjhksANI7969ERERgejo6ELPnJKSotj2sVDJGkDWILJ3rzklJ+eY+3h56f8ueHuzT2YO8TjWIK2Chsf88ssvrTGsw47haFvAvF5WxRjUMe65ZRbyWJBrQ8z7dCzYsdHCC8S/EBvoKyq8TNyU2IP4XWJWPS0mZlpInEU8mZjHbk78EvEXxI5NHASaslmoVAwB0N/NXHmqjpanwG9tW6Muq+2cr9cSBXq54hFK6bbw6S5Y+WJ3mwl/W85tweR/+dHmkFMlJyWDB9d4m4HDGBjIw8ND8Vzz8yua0Gu4Xo6CgCAgCDgKAubOIEVx/uDveg6Kb4gDyIJb165dFe3f1KlTLTqYOAo25XmdjqYB5O3cH4lzNxYVrRyXexGzCo5t/tjFlL0OoolfI/6W2EDTqcCvFWuI2bhsJzGrfzh2IBNr+W4nZkFxHHEiMauLPiV2bNLY8ik34qL/1qW9SXMNoK9r4bWc7Mxx+ZpR4OycjwCondPbQngYbZ/ilI/EH8G4DeOQdZPle3KApn/vd3sfrUJbgd9Y77nnHuVt1TA2hyFgA2khQUAQEATKOwK9evVC7dq1lfh7M2bMUBzeWDPI34sFEdvxtWzZEhwLkOnKlStKKBfeAuZg+bx1O2DAgDzD+Pj44OrVq2BnEz3SZl1yiB02vZuw8zZHEwBnEZ7MluhPSyc07ZOozGyJDtKJ7pZOOmx7hkHGzb0DV88CbyUxjeXfHPJx9YFz5cJ/XLTbv5y3t31EgGGoUj9yHt8X1r+AlBtGDF695VX0Ce+j2Jc89dRTOHDggLquMWPG4OGHH1brUhAEBIGKgcDQhkPRN1zf45VtAPWI23l7WI/Yrs8Sfdb7szw2gJb6lkY774CwJo+3bNlrl78XC2v7zHEAtZmRMjMzwVpFDjLN4x05cgTmjiC8tcwC4JkzZ3RvLyYmRmlnATM8PFy3jzSWDIHC/6KXbB65uqwR0Nr/8VpcChYAtRrAomz/8vBbI43bv61rBcDTtew+aq5OrpjUaRLGbRyneDU/0uQRPNT4IV6mEnB09uzZSpn/44Cn/AYsJAgIAhUPAXbYsOS0YQkNNyc3XdtAS/0N7bV89Z0fDOdL+8gC4OTJk8Ex+1joKq7zB6+bIyZ89913yjZwZGQkJkyYoHzXau+pTZs22L17N3bu5I24vGRoZ1tsvTAxea+QlqIi4Gg2gEW9P+lvQMB8C5gzgRRAxRUAb2RlY9upK+ro+dn/qZ1sXOhcvTNm9ZuFBxs9iHHteHef9v/pi+f5559XZ+b0RRz3qrBvveqFUhAEBAFBwMERYK9b1uQFBwejU6dOBWb/KOh2+XuUs4GwjSCHmDl5kn0pjWRwDGFHO70wL6w9ZEG0MNvQxlGlVBQERAAsClqO3LcYW8BaAbAoHsD7KIWbNvhzl3pBusj938Yo7DlzVfmC0O1g5caGgQ3xeofXUblSZSX90b333quGAuAvGv7Cka0GK4MuwwkCgoDDIMA5eDn12ubNm62yZhYoO3TooMQZZO2ilu644w60bt0aCQkJePrpp5Gdna2eZhvsdevWge0EtS/pagcpWAUBEQCtAqMDDGKuAbThFvAWzfavl6sTWtTI6z186vJ1TF1+lHL+bkXP6RtKNe8vf9FwknJtaIOJEyeiX7+ccDAO8DRliYKAICAIOAQC7AnMWkDO88vRFrTEbSEhIYrTSYMGDTBs2DB07NhRsT/kbWTOvhQaGqq9RMpWREAEQCuCaddDmdsAFiIMTGK60QmkKDaAWgGQM3+4OOX9mHHMPwOdT0hFzUCOymMdunj9Yr4Dvffee+A8lAbi2FBsoyIkCAgCgkBFQYB3PYpKxbmmZ8+eSnIEzjbCTiZaYqFv//79eOaZZxQN4OLFi5Wgz7w7s23bNnCaOCHbIVB2lvm2uycZWQ8B7RYwOUXAicMl5k/aLeDCCoCpGVm0rZugDty5bt7tX34bXLr3vNqnZ8NQ+HvSmqxA68+sx0sbX8IbHd7AvQ3uzTMi57xkbZ+BOAr9nDlzlBhWhjY5CgKCgCBQnhEwZOEo7D2yaYx2i9Zw3fr16w3FfI/aF27zjqzh++yzzxQ2Pyd12yKQVzVj2/lk9LJCQLsFXIjtX15mcQTAHaevUGgDoy1H1/rBee74wLlEnKQtYANx6jdr0IG4Axj/z3hkZmcqAZ+/2svhHI3E4QYMCca5ldP3sc0LGz0LCQKCgCAgCAgCFQkBEQArytPWagALsf17I/sGkjOSVXT83AuXEWOLJvtHsLcrGlbheNumtESj/WMbwT6Nqph2KEaNc3E+u+5ZpGWlqVeHehptR9LT03Hfffcpzh+GDp988kmJPd0MY8lREBAEBAFBQBBwJAREAHSkp1WStWptAAuhAUzKMM29WNgtYK39X6e6wbpp3U5rtH+3NwuDBwmBJSFO3j5m7RhcSTOGnnm8+eMmW8Ccl9KQmJzn4kDPHOhUSBAQBAQBQUAQqIgIiA1gRXnq2i3gQmgAtdu/DFFhBMCElAwcOm8UHLvo2P/xWN+PbI+ouGuKHaDeFjH3KQq9teUtRCdFq5cMqDMAz7V+Tq1zeBdt0u9mzZrhm2++0RVO1YukIAgIAoKAICAIlGMERAAsxw/X5NaKuAWs9QDmcQojAP4bFU/u/sZZu+ST/7duiDdevK2BsXMJSi+1fQmRVyNx/vp5dKjaAZM7T1aFu0OHDuGJJ55QR+e4Un/88Qe8vArOhaxeJAVBQBAQBAQBQaCcISBbwOXsgVq8nUxjHtxCpYFLM3ry8piFCQSttf+rFehJoV0KTjdncb1FOFHHvw7m3DkH/ev0x4yeMyjsTI6Hc1JSEu6++26kpBjvnSPSc+gBIUFAEBAEBAFBoCIjIBrAivL0tTaArgULZtotYM516eFccJy+LZHxKpqWsn+oHaxcCPEMwdRuU9VROdTMqFGjcPz4cbWN7QBZIBQSBAQBQUAQEAQqOgKiAawonwATAbDgPMDaLeDCaP84mDNn9zBQZ3IAKUtiD18O8WKgbt26gSPSCwkCgoAgIAgIAoIAIAJgRfkUFHULON24BVwY+z+t9y9Dah4AOiv7plVy/samxBb4xDiP5SuvvKL2q1KlCubNmwdOLSQkCAgCgoAgIAgIAiIAVpzPgIkGsGhbwIURAP+/vTMBr6rI9v0iE4FAIEwiU4JgIwqIoiIKMtmIV2hEsZVWQQYvir5Wrj5v+x4i2q3tcNVr49Aqgxdt8VP72g40KjJ4UUBtbUBFVIagDBLGJJB5uOt/kr1PnZ0z5CRn2En+6/tWdlXtqtq1f5WTs7JqWq8LQCzpe3K6tG/V3Ip6rn/9Yo9c/PhH8qdVP4i5DYxPphCRnbk7ZeJbE+WRzx+RikrvZtNmsQMHDsivf/1rz+HjSE9MTPQYfyeffLKZjWESIAESIAESaNIE6AFsKt3v4wEMvQLWnAMYaggY8+1MD6C/7V/e2rxXt345IY+v/F5ueeXLsKkfKjwksz+cLdif8KWtL8mdH93pOfHDrKisrEyuueYa2b9/v52MYd/hw4fbcQZIgARIgARIgAToAWw6vwM+HsDwDMBQHsDtOcclJ7/YZunc/uVAXpGYHsLLB3a189YmUKDG6y2rbpG9x/fa2dNT0iWpme8aprlz58ratWvtPJdffrnceeeddpwBEiABEiABEiCBKgL0ADaV3wSffQBDDwGbi0BCGYCm9y8poZmc17OdD9V3Nu+z9wds1kxk/Jm1P/sXR9LB27f18Fa7zqFdh8rc8+fae/3hxltvvSUPP/ywnad3796CLV+a4YEUEiABEiABEiABHwI0AH1wNOKIeRJIcngewFBDwJ8Y8//O6tFW0pr7eubeVgPQkvN7tpfObVKtaMjrc1uek3V719n5+rbrK48Nf0ySErzP2L59u0ydOtXO06JFC89mz23a1O78YrsgAyRAAiRAAiTQRAjQAGwKHV1WIqKeNFtC7AOIOX3mHMBgHsCy8grZuNO7AMS5/ctOPfJty55c+9ETBtbe+4dCk0+bLAM6DvCU75LWRZ65+BlpaZxlXFhYKJMmTZLcXO8zcMzbgAFVZewHM0ACJEACJOAhkJWVJQkJCR6dM2dOUCqPPvqonTclJcUn74gRI+x7Vn3I07lzZxk7dqzgGE6KewnQAHRv30SuZSXHfesKcRZwQVmBYOjVkmAG4Nd69m9+kTevc/4fvIGzR/SSrm1bSEpiglzaL7zVuO1S28nCMQtlQq8J8uzFz0qHFt79BWGozp49WzZv3mw1VWbNmiVTpkyx4wyQAAmQAAn4EsDUGEthpGEBXSBZsmRJwKk0Vh0DBw6UG264waMTJ06Udu3aycqVK+X666/37MoQqG6mx5cADcD48o/N080VwHhiiCFg0/uH7MGGgM35fy2SE2Vg97YoYstJ6aly19jTZN1dI+Xvtw2VNi3D34sPp5D8YegfBEe+mbJo0SLPPD8rbdCgQYINoCkkQAIkQAKhCZxzzjly+PBhzxxqf7nXr18v27Ztk3PPPdffbTsNC+4WL17sUey5unXrVntONs5eh1LcR4AGoPv6JPItMheAoPYQQ8BOAzAjNSNgm0wDEIs/UpL8/0ol6OKQ3p1aB6wn3BtffPGF3HrrrXaxjIwMz8kfqam1n19oF2aABEiABJoggenTp3s26Ifx5k/wTza8fMgXrmAHhj59+niKvfPOO+EWZ/4YEPD/bR2DB/MRMSRgLgDBY405dP5akVvknU+H+4GGgItKy+Ufu4/aVQzt7R2etRPDCBwtOuoz9Byo6JEjRzzz/oqLq7aewR8oDGNk6bwWCgmQAAmQQO0I9O/fX+AF/OCDD3z2T0XpEydOyOuvvy7du3eXMWPG1K5CR65+/fp5DExs0E9xHwEagO7rk8i3yNwDELWnBD8L2PQAJjRLkNYp/j13X6jxV1LmPZHjgt7t69z24zpPceYHM+X2NbcL9v0LJBUVFZ45ftnZ2XaWe+65Ry699FI7zgAJkAAJkEDtCMC7V15e7jOdBiUxlHv8+HHPDgv4J7sukpeX5/Eg4jhOivsIePfScF/b2KJIEajHEDA2XIYR6E8+3n7ITm6XliJ9O6fb8XACpeWlMmftHPn+6Pcenf7+dM9qXywAcQpO9li+fLmdjP9M582bZ8cZIAESIIFwCRSXF8tPeT+FWywq+bund5fmib5HaUblQdWV/uY3v5E77rjDYwDefffd9qMwLIyVvdOmTbPTwgkcPHhQPvvsM0+RCRMmhFOUeWNEgAZgjEDH9THhDgEXe4eAAw3/4n3WGwbgkFPa6x8LKSW+WQAAJExJREFU73+Jq7cdkF+c1Fq6ZQTfdBoreedvmC8b92+0EWGPv5ZJNct9+OGHAm+fJRiawNAvzvulkAAJkEBdCcD4m/j2xLoWj2i5N3/1pvTO6B3ROoNVlp6eLldccYW88sorsm7dOhk2bJh8//33ggUgo0aN8kyt2b17d7AqfO4VFBTIpk2bPEYlPIDYoxUrgynuI+DfteO+drJF9SFgegCTdJFEQnCDyRwCDrQCOLewVL7a6zUUze1fMDfwt8s2ydCH18hVf14v/8g+ErD1T296Wt7e8bZ9PzM9UxaMWiCpaKche/bskcmTJ3vmkyA5OTnZMz+lQ4f6zTs0HsEgCZAACTRJAs7FIOEs/vD8Ez9/vr0fYKtWrWTo0KEe7x9GbAItMGmSoF320vQAuqxDotIccw5giD0A8XzTAAzkAcTmzxWV3tZeaMz/W70tR44XV+0r9Xn2UUnS/f/8yZof1whO+rAEQ77Pjn5WnKuOS0pK5KqrrpJDh7xDztjuZfDgwVZRXkmABEiABOpIYOTIkdKzZ0/PTgpPPPGELF26VOAZvPLKK0PWiPmBZ555pmAvQAgW6W3cuFEwBIzpOX379pXx48eHrIcZYk+ABmDsmcf+ieYQcIg9ANE40wAM5AE0h3+xyXOPdt4h27c27bXfMbN9Szmzm/8j2S7seqFc2vNSWbFrhaQmpspTo54SzH9xCrYTwB8USzBn5eabb7aivJIACZBAvQjg7w6GXt0g/v4GxqJd2Mh5vnryMGSLVbs33XSTNG9eu7mI2AfQnItdWlrq2ToGU3RQ37fffitcCBKLXgzvGTQAw+PVMHObQ8Ah9gDEC5oGYCAPoLkABN4/a5UYhobXbDtoc5owsKt9z06sDqQkpshDwx4SHPF2ZsczpX/H/s4s8uqrr8qCBQvs9DPOOEOef/75gHXaGRkgARIggVoSwKKLWM67q2WzYpoNBuB9990n2LMPf8/ruvgDjcYUnYULF3qGgXFWO+Zu4+82xV0E/I/NuauNbE19CZjbqoTYAxCPyg2xCORAXpHsOHjCbpU5/+/9r3+WEj0f2JJQZ/9ihfHtg26XkT1GWkXsK3aTnzlzph3H3BLsKJ+WlmanMUACJEACJFB/AlhUB08e5lUPGTIk5OkfoZ4I7+HDDz/smbf94osvys6dO0MV4f0YE6ABGGPgcXlcmAZgXnGe3Ux/Q8Cbfzpm30dgSC/v/n+YG2jJGV3SpVfH4HsOWnmd1/z8fM/8E2xGagnOpLR2lrfSeCUBEiABEogMgTfeeENycnLk448/jkiFMCgxVxv7DMK7SHEXARqA7uqP6LSmvMRbb2Los3gLywrt/DiH1ym7D3s3asb+f51ae1fs/p/Rp8qfrztbfnfpaTJzWE9n0VrFsaoMnj+cQWnJnDlzPKd/WHFeSYAESIAE3E8AK4HxN33ZsmXyww8/uL/BTaiFNACbQmeXV63I9bxqCAMQmzKXVXrz+9uPL/uw1yuHRR6m9OyQJmP7nSw3De8lE8/qZt6S7Ue3CzZcDSWY8/faa6/Z2S688EL7YHE7kQESIAESIIE6E7DmbYdTQV3KjBgxQi655BKPFxCLTCjuIcBFIO7pi+i1pKLUW3dCcA9gQZnXu4dCoTyAWe1rNx+vVNtwy6pbPAbgdadfJ1f3udrvEXPYfBS70lvSqVMnjzGIScUUEiABEiCB+hPYtWtXWJVkZmYKjuF0ypo1a5xJfuMrVqzwm87E+BKgBzC+/GPzdPXq2ZIY3OY3h39RpkVyzSHgYB5A+zmOwPvZ78u+E/vkcNFhefLLJ2XDvg2OHOKZe4L9/srKqjyQOIYI51F26dKlRl4mkAAJkAAJkAAJ1J0ADcC6s2s4JSu8Q7oSwgNYwwB0zAEsLiuXfce8cwQx5BtKMP9j0VeL7GxZ6VkyusdoO44AJgnjpI99+/bZ6Q8++KBg+IBCAiRAAiRAAiQQWQI0ACPL0521+XgAU4K2MZQBuOdooc8JIJm1GAJet3edbD+23X7utH7TJNFxHB02EV29erWdB4eH33XXXXacARIgARIgARIggcgRoAEYOZburcmcAxjuELDDA7jbWACCF84yFoHg3sH8Yvu8XguI6f3r1KKTjDtlnHXLc8XGo/D2WdKrVy/BvlF1mXBs1cErCZAACZAACZBAYALBJ4QFLsc7DYmAuQq4nkPA2Ye8i0TatEiWti29HsW73tgin+46ImkpiTJjaE/5tzF9ZP/x/fLtkW9tWlPOmCI4AcQSbA56/fXXW1FJTU31bPbctm1bO40BEiABEiABEiCByBKgBzCyPN1Zm48HMPhq2lBDwKYH0PT+4cWt/QFPlJRLSlLVr9bJrU6WlZNWyq0Db5XM9EyZ9ItJPoxuu+02yc3NtdOeffZZz8HidgIDJEACJEACJEACESdAD2DEkbqwQnMOYELwLjcNwGT1FiY58u8yNoE25/8VlZbLz3pEnCXmPZwmMuvMWXLjgBsFR79Z8uOPP8ry5cutqMyYMUNwHiWFBEiABEiABEggugS838bRfQ5rjyeBcDyApd4Vvv73APRuAm16AH884h0axqv62x/QNP6QZ9GiRfZ8wcTERLn//vuRTCEBEiABEiABEogyARqAUQbsiup9PIC1HwJ2GoCl5RWCVcCWmF6+7ENewxD3exiLQ6z85hXbvixevNhOGjduHPf7s2kwQAIkQAIkQALRJUADMLp83VG7aQCGOArOHAJ2GoB71fgrr6i03ymrg/cYONMDmNEyWbBAJJi89957smfPHjvLjTfeaIcZIAESIAESIAESiC6B4BPCovts1h4rAuYQsGNOn7MJwQxA8wQQlDM9gIMyM+S3o0/VhSAnJCGxUI4VHZO2qYFX8r7wwgv2o7t16yZjx4614wyQAAmQAAmQAAlElwANwOjydUft5jYwITyA5lnATg+gtcoXL9WqeZK0T/Nu53JWjwyBQhb8c4GM+evtcuWpV8rUM6ZK57TOnnTrx/79++Xdd9+1ojJ9+nTBHEAKCZAACZAACZBAbAhwCDg2nOP7FB8PYPChWR8PoOMcYNMDmKlz/Pxt1Hyi9IQs27ZMUM/L374sD2x8oMa7L1myxHP0G26gDhiAFBIgARIgARIggdgRoAEYO9bxe5LPHMDgTl/TAGyZ5J3jh8abHkB/q3yR543v35D8knwEPYJj30ypqKiQhQsX2kmXXHKJZGZm2nEGSIAESIAESIAEok+ABmD0Gcf/CRVl3jaEcRKIcwjY6QH0VloVKikvkaXfLLWTz+p0lpx90tl2HAGc97tr1y47jYs/bBQMkAAJkEBMCGRlZUlCQoIsXer9e+3vwSNGjPDkM7fo+uijjzxpKG9q69atpV+/foLN/Xfv3u2vOqa5jEBwd5DLGsvm1JGAjwcwjCFg4xxgrP79ydjrL6tDWo3GLN+5XHIKc+z0Gf1m2GErYC7+OOmkk2T8+PHWLV5JgARIgARiQABTb/xN4XE+Olg+3Js6daqnSGVlpWdXh40bN8qCBQsE03xWrlwpgwcPdlbJuIsI0AB0UWdErSl1nQNoGID7jhVKabmxBUx7rwFYocZhQkIzeXvH2/Yr9G7bW4Z1G2bHETh48KC8+eabdhpO/UhODm6Q2pkZIAESIAEScBUBcy9XNGzv3r0yatQo2b59u8ycOVO++uorV7WXjfElwCFgXx6NL6Zz7qRS1ZLE4Da/OQcwNSnVKiXm8C8SzVNAfr98q5z7wIeSu+sGuaDNLOneurtM7zfd59g3lMFwQ2lpKYIewR8ICgmQAAmQQOMg0LVrV5k/f77nhKetW7dKdnZ243ixRvoWwa2BRvrSTeq1TO8fXryOcwCzjTOAWyQnSsfWzW2MWBxyML/Yo5elXyDvTL7ZvmcFMERgDv+OHDlSevfubd3mlQRIgARIoBEQGDBggP0WBw4cEMw3pLiTAA1Ad/ZL5Fplzv9DrSH2ATQ9gOYikN3GUW/OLWCw+bMluJeYUHNPv48//li+++47K5tw8YeNggESIAESaDQE8vLy7HfBPG+KewnQAHRv30SmZTU8gMG7vLDUe9avaQCaHkBzC5iqxSHeMjAA/Ynp/WvXrp1MnDjRXzamkQAJkEDsCZQWiRz17k4Q+wYYT8zoKZLsnX5j3GkQQWuTf3gC6f1zd5cFtwbc3Xa2rjYEzFNAkD+IB7C8olxKKkrsWk0D0MfLZ5wBvD+3UErKvXMMzePhrIqOHj0qr7/+uhWVKVOmSGpqw/0DZ78IAyRAAo2DAIy/Z853x7vM3ijSqW9M2oKFeNBgUpvVwiiPs91fffVVeeyxx6R9+/ayaNGiYNXyngsI0AB0QSdEtQk1PICBV90Wlet/wYZYBiBW+e42t4AxVgB//fM+owQWh3hXB1s3/vKXv0hRkbduDv9aZHglARIggfgRGDp0aNC52CtWrJCcHO/WXs6WYh9Ap2Bu99q1a6VLly7OW4y7jAANQJd1SMSbE8YcQHP+H9phGYA/5xVJSZnp5asa5t2dt1t+9/lVktV3kDTLHSlHj3WUTsbiENThXPxxwQUXyOmnn45bFBIgARIggTgSwE4MGJEJJFisF8wAtLyH2N1hx44d8umnn3q2gJk8ebKsWrVKkpJoYgRi64Z09o4beiGabQjHADTm/6FJ1lFwNbeAqfLyLflaz/StLJPD8qkkZ3wpa25c5dkP0Hydzz//XLZs2WIn0ftno2CABEjALQQw7w5Dr24QtKWBiHMfwA0bNsjYsWMFi/7mzp0rDz30UAN5k6bZTBqAjb3fwxgCLigr8KFheQDNM4BTkhKkc3qq5BTk+Gz8PO6UcZLRIsOnPCLm4o/09HS56qqrauRhAgmQAAnElQAWXcRo3l1c3zPKDx8yZIg88cQTnk2gn3zySbnpppu4ECTKzOtTfc0B/PrUxrLuIxCOB7DMu5oXL2IZgKYHMLNdS4+X7+WtL0tptXGphwrJDf1uqPHu+fn5smzZMjv92muvlbS0mnME7QwMkAAJkAAJNGgC06dPl4EDB0pJSYncd999DfpdGnvjaQA29h6u4QEM7PQNNAcw22cPwDTJK8mT175/zSY3usdoOaXNKXbcCmBF2IkT3j0COfxrkeGVBEiABBovgQcffNAz/xsLAHEsHMWdBGgAurNfIteqMLaBqWEAJrfwtMMcAsYRcMt3LpcTpV7DDse++RNz+HfQoEFy1lln+cvGNBIgARIggUZEAPMAL7roIikrK/McDdeIXq1RvQoNwEbVnX5epoYHMPA2MKYBmNAsQVISUjz/xZlDwFkd0uTqPlfLf478T+nfob8M7jxY+nfsX+PBmzdvFiwAsYTeP4sEryRAAiQQfwK13d/PX0tRNlR5LABBntdee83nFCh/9TEtPgQCjwfGpz18aqQJ1HEOIOb/4cN7QLeAKSr1bgGDff5gHGLYtyT3dHnps21yz9++lt6dWsnUC7Ls1pveP8z7w7YAFBIgARIggfgT2LWrdqeerFmzpkZjhw8fLuXl5TXSnQnnn39+rfI5yzEeOwL0AMaOdXyeVFHm+9yEwDa/6QG0F4AY8/9QkXnU2zf78mT9DwXy0sbd8l/rs+3nFBQUyMsvv2zHr7nmGsEKYAoJkAAJkAAJkIA7CNAAdEc/RK8V9fAAolHm/L/kxGbSpW3VvEDcM4eGexhnAOPYt9zcXGTxCId/LRK8kgAJkAAJkIA7CNAAdEc/RK8VdZwDaHsAD3sXe3TXLWASE5rZbTWNQ/MIOHP4t3///nLeeefZZRggARIgARIgARKIPwEagPHvg+i2wOkBTEgM+Dx/Q8C2kdesxOecXxzxZnoAraHhrVu3yieffGI/A96/UJOF7cwMkAAJkAAJkAAJxIQADcCYYI7jQ8w5gAm6AlgXdgQSfwagZeS16L5Edic/Lhv2bfCsDD5WUCr5Rd75hZYHcOHChXb1qampct1119lxBkiABEiABEiABNxBgAagO/oheq0wPYCJgbeAQQMKjbOAMQQMLx88gAktdktS2i7JKfta/nXlv8qb29+UwydKpFsGVgpXNR1zAIuLi2Xp0qX2u0yaNEkyMmoeD2dnYIAESIAESIAESCAuBAIvCY1Lc/jQiBMw5wDCAxhEnB7AQ8dL5HhxmaR2W2uXap3cWsZkjpFWKa3k438fJcVl5bLnaKHgiLg3Xn9NDh8+bOfl4g8bBQMkQAIkQAIk4CoCNABd1R1RaIx5Ekhi8O4uLPeeBQwP4I9HCkQSiiSp1Ta7YVefdrXH+LMSmiclSq+OrTxRc/FHnz59ZNiwYVY2XkmABEiABEiABFxEgEPALuqMqDTFOQcwyENKjeHiZPUWYhPoxOY/6zBvpV1q/Cnj7bAZ2LFjh6xevdpOmjlzJhd/2DQYIAESIAESIAF3EaAB6K7+iHxrfIaAg3sAyyq9izqSdMNoGIAJqfvtNjVPbC6Z6Zl23AyYiz+Sk5Nl6tSp5m2GSYAESIAESIAEXESABqCLOiMqTTE9gCGGgMuMvPAA5uQXS2VZKyk73lsSKlpJ77a9dR/AmtvIlJaWypIlS+zmX3755dKxY0c7zgAJkAAJkAAJkIC7CAR3CbmrrWxNXQhUGGc2BjkGDlWbBiA8gHvUA1iW39+j55zaQZ67pL/fFrz77rty4MAB+x4Xf9goGCABEogxgby8vBg/kY9zCwH2fXg9QQMwPF4NL7cxr0/CNABz8ort9z0pPVVaJre04y/r+b9JeipI25Yp8vSLr9rpPXv2lNGjR9txBkiABEggFgRSUlKkc+fO0r1791g8js9wKQH8DuB3gRKaAA3A0Iwadg5jWDdsAzC/yH73Tq2b22EEHl6xTfJ1ixjIkZ/yPVf8mDFjhiQkcGaBDYQBEiCBmBDAxvO7du2SkpKSmDyPD3EnARh/+F2ghCZAAzA0o4ado44GYGKzRF0E4usBtECUllfYxh/SyguqhlwSExNl2rRpVjZeSYAESCCmBPDFzy//mCLnwxowAbpqGnDn1arp4cwBNFYBS2Wi5BaW2o84Kd3rAcQxcKZUFFZ5AC+77DLp0qWLeYthEiABEiABEiABFxKgAejCTolok8LZBsbwFhY6RlE66RxAS44V+N4sL6zyAHLxh0WIVxIgARIgARJwNwEOAbu7f+rfOsOokxBnAZurgAtLKqVFjxeksjxVKoo7ix72pm2pOtf3qB8PYNeuXWXs2LH1by9rIAESIAESIAESiDqBhuYB/KMS2aKaq7pX9RXVbqqmDNDIR6rHVfeo3qvqlPs0AeUxdrlW9QxVU2pTh5nfvWHTAPSzh5/ZcNMAPFZYLElpOyQ5/Rtp3nGVHCnZbWc96scDOH36dElK4v8TNiQGSIAESIAESMDFBBqaAVihLHHERHvVvqqVqu+oWoJDad9TXafaThUuqZmqt6la8n81cIPqL1U7qK5XfV/V2uOkNnVo9gYi5lnA1dvAvP8+XremmAbgzycO+WQ4vcNpdvz8U9rLhLTtkvPGfXLo3cekmRqZWP1LiR2BQH0YuxbwSfUlwD6sL8H4lmf/xZc/n15/Ag3NAPz/+sr/VMX+I5h49ogqvHVtVCFXquKd5qliotrXqo+q3qpqyc0aQNpWVSxzvUc1WXWiKqQ2dVTlbAg/fTyAeE21dgMZgMYikEOFOd63q0zyOQKudfNEeffFP0nhjs/lxDdrZMyYMZKZiSFiSqwIBOrDWD2fz6k/AfZh/RnGswb2Xzzp89mRINDQDEDnO1+iCRibxJAw5ExVGIjwFFryuQZOUYVnL101SxVpluCojE2qZ1UnhKrDKtcwrj4GYGLANldUVgjUkmMlB62gtJCuuumzd3h3zZo1snPnTvs+F3/YKBggARIgARIggQZBwPut3iCa69PIizUG790VRioMvGNGHMGj1XHcswxef3lwHxKqDswt9BFXHz9zvED9nBgpVylSA0+PScJGqc42l+qJIeWFsIWrJLfiZylPqIqnJ3b2yf/8889b2aRDhw4yfPhwn/v2TQaiRsBfH0btYaw4KgTYh1HBGrNK2X8xQx2VBzm/A6PyEFYaFQLjtFYYdr9y1P64xlc40oZoHJaM5QGEm2uwIw8mxf1HdVqoOsyiXTUC64pKBvwd4O8Afwf4O8DfgYb3O4Dv8SYpDdEDeK321FOqV6l+6Og1DOX+RhWePms88zwNY7zS8txla/hc1U9VIRgXxfDvfyGiUps6qnKK7NMAViHnWwm8kgAJkAAJkAAJNAgCrbWV+B6nNAACt2obj6heGKCt8PJhe5ffq2Ln4v6qP6repmrJnRrIVj1DtYUqtpb5SdVcBRyqDs1OIQESIAESIAESIAESiAUBePWwchcrgKHwvOFqGoT9NP4/qidUYdljnqBT5mvCflV4Bdeqwhg0pTZ1mPkZJgESIAESIAESIAESIAESIAESIAESIAESIAESIIHIE5inVW5XxapmbNyHBTDYxsYUeE11KbCPx9Tp8TTzIzxJ9VtVeFG/UbX2SNQgJcIEotGHw7WN6HfTU46pEJToEKhNH6boox9UzVbFyMMu1etUgwk/h8HoRO5eNPqPn8HI9U9tagrVh1gbYI0YWn8XSzXtnyEq52cwBCDejh+BU/XRbaofjwU9/6b6s2qz6jRcYAiMNOKhglghXah6uSoWyFyhCgPybFVK5AlEow/x5YOV7+bvQeRbzhotArXpw7c1M3Yb6FldqINeUS6Q8HMYiEzk06PRf/wMRr6fgtVYmz40y+P7EtPA5piJjjA/gw4gjLqXQHNt2u2q+OJvbzQTBuAoIx4quFgz/NWR6b81/oIjjdHIE4hUH1pfPjDgKbEl4K8PR2sT4E2H0Vdb4eewtqQimy9S/cfPYGT7JZza/PWhs/w1mnBcta3zhhHnZ9CAwaA7CfyLNuuoKgy9MtVHVU1BOhbDHFT9h+pM1WDypd78d0eGuzWOspToEIh0H1pfPru1ufAIr1S9KDpNZ63VBIL14R81z9eq/6GKzyL6BV8u5j9qGvURfg59cEQ9Eun+42cw6l1W4wHB+tCZ+SNNWOhMdMT5GXQAYdS9BPCfzG2qVzqaOFLj+I8ILu9LVY+ozlINJJhT6Lx/k6Z9H6gA0yNGIFJ92ElbhC2QElTTVO9QxbD+AFVKdAn460N4z/GP2JOq2J6qo+oHqn9XDST8HAYiE930SPUfP4PR7adgtfvrQzM/dvnA5zHUtCZ+Bk1qDLueQDNt4TFVfPkHknl64+NANzWd//UEgRODW5HoQ3/NXK2Jf/B3g2kRJ+Dsw8f0CWWqMP4sOV8DzjTrHq78HJo0YhuORP/5azE/g/6oRCfN2YfmU57RiHUQhJnuDDf6zyA8BJTGQwBzvpJVg00ux9viwxFINumNcx03EQ+1WspRhNE6EohEH/p7dKUmBut3f2WYVjcCzj7EFwn4m4K+CNYn/ByatGIbjkT/+WtxsP72l59pdSfg7EOrplYauFb1aSshyJWfwSBweCv+BH6rTcBQAwTDSs+rHlE9SRWCI+7g5oZRiA/EGNXDqreoBhKsfCpQnaCKYWMMKZ9QDeUu1yyUOhCIRh+in7NUYWTgtJvbVTEEzD5UCFGQUH3YUp+5W/VxVUzHwNy/91T/phpI+DkMRCby6dHoP34GI99PwWoM1YdW2dkawHx4fA5DCT+DoQjxflwJvKNP36+ar7pXFV8o5pf8OI1vVc1TPaIKL96NqqY8q5HlZoKGYfR9qwpDEOUvV6VEh0A0+nCuNhUGB34vclRXqQ5XpUSHQKg+xFN/oYp5f+iTParPqbZVtYSfQ4tE7K/R6D9+BmPbj7XpQ7Roi+ojAZrGz2AAMEwmARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARJowAQyte0VqvOMd8ApJkibYqSFE/RXZzjlw807VQugvdBy1StU3SILtCFW23Dt4ZaGsR0kQAKxJZAQ28fxaSRAAiRQJwKVdSrlLYTyZh2ZGr9XdYA3S0RDeNYfVK9X/SyiNdevshe1+HWqb6qaPDRKIQESIAESIAESIIH4EIBhBs/UPMfjUzTezJEWThTlzX94h2scz5kSTiW1zDtV88Hzd1Et88cj273VbewRj4fzmSRAAvEnkBT/JrAFJEACJBCSQEnIHMEzOMvXx5gM/iTeJQESIIEGQMD8j7gBNJdNJAEScBmBVG3P/arfqRaoHlHdpDpX1ZTZGvlAda9qsepPqs+rdlANJf68dfCywYM3UvUu1Z2qRapfqY5XNSVTI8g7rzoRZVerVqq+qIp70MWqKIvwFFWn4B/mg6prnTfCiFvtvljLYIgYHApVP1f9papTpmkC7h1TzVf9QfVF1Raqllhtt+LWdb4GcK+HlcArCZAACVgE6AG0SPBKAiRQFwLPaKFrVf+sukUVBmEf1RGqMHAsuUMDn6jCCMxVHaQK42aI6tmqparBBMaaP/mjJiaqLlCFV+921TdU0YZsVX/yP5r4oOr/U31OdZ0qZIcqjK39qmjbUlVTfqWRdqoLzcQ6hh/Rcvj7+4Rqc9VZqstVL1FdowqBEbpI9e3qa5les1RhpLZWheEYTMAsELdg5XiPBEiABEiABEiABIISOKx3nwqao+qm6bGysk/VAObK/dpK0GumKrxW84y04dVpMIgsQVnkg8EGA9ASGJNIh4FnSW3rtPI/oAEYWz2thOrru3qFJw5GbjBB2wLNAbTaDWOzpVHJyRqGYfyVkfZXDX9txAMF8b6L/dy8V9PQjh5h3vOTnUkkQAKNjUBCY3shvg8JkEBMCcBoGawKIyuYWN4qeOnaqLZXhScO8fNU6yrwQMLIseRLDeSr9rYS6nBdpGXQrmlG2c4ahndumSqGmusrz2oFBUYl+zX8iurpqr2q08G2q+qF1XFeSIAESCBiBGgARgwlKyKBJklgjr71L1R3qX6jiqHYi1WdgvltGGqF0XNU9aAqvGCVqm1V6yIom+2nIOYhwsCsq+zUgmtUpxgVIIy/l4uNtLoG0e7v/BT+tjrtlOorvJjwsMJQ3qv6F1UMt6eoUkiABEigXgRoANYLHwuTQJMn8JYSyFK9XnW96nhVzPPD8KUl8PD9XRWG3h2qyAMjER41eNrq83fI9P5pVbag3voI5vl1V4XhCrlBdasqhpxjJdv1QX1Vx6nC83ia6kuqX6nWZvFMouajkAAJkIBfApiETCEBEiCB+hCARw/eKSjkGdVZqhepwns1WRVG3r+o/qRqCTyH8RJ44YLJf+tNvBeGgfNVYXzB2xkJgXGK+t5xVIbhX8jOqovnJxbHrKhWJFytCmNwtur9qhB4PDM8Id8fvXyjjJEACZCAl0B9/vP21sIQCZBAUySAvx+Yz+eULdUJ7auvWFABcXqk7ta0UIaYp2AUfhyvrtOf4YRbJaovq05UvcOIazAicpPW0sqoqYuGYSjDy4ihcYjFrypW9XNzdcS894OmDVFtXn0PlyzVCQhQSIAESMAfAXoA/VFhGgmQQG0ItNZM+1XfUt2kmqMKr97NqvtUV6lC/qY6RxWerOdUMWyLYWAMCddnqLY+ZWFowQiEJ61QNVd1l+pnqpa8oIHfql6hiiHtw6qRkmNa0QbVF1VhuM1SxUrp21UtwVA6vJDrVOE5xbDvTFV4BZepWvK0Bpaqgje8sJ1UYWBiTuY5qhQSIAESIAESIAESiBiBZK3pAdVPVQ+pFqjCewWDpJuqKTCivlSF0bVfFYZghiqMwUWqlmRqAGn3WAl6HV6dhoUYlkzVAPJhmNkpMORWGYn+6sTty1T/qQoDEHUtVnXKBk3AvbHOG0Hiwdpm3Rut5X+v+qMquMHw/KWqKTM08r4qjGm0cY/qm6qDVZ3yO01AXcgHzvD+3auKtvdQdUqwe868jJMACZAACZAACZBAkyKwVt8W3rdwvI0w8ipU4eXEUC0MZUssA9Cf4Wrliea1pVaONj2iGsg4jObzWTcJkIBLCGAOD4UESIAESKAmgX6aBENtkWplzdtBU5AfQ+M5qjAE3SIPa0OwBc8dbmkQ20ECJBAfApwDGB/ufCoJkIB7CZynTTtDFfMW81SfUg1H3tPM5nCutSjGqiMcb6JVJlLXP2lFGEa25GcrwCsJkAAJkAAJkAAJNGUCS/TlsdBiq+qYCIOI9xBwhF+H1ZEACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACdSBwP8CqqFUEiQSA04AAAAASUVORK5CYII=\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot everything\n",
    "fig3, ax1 = plt.subplots()\n",
    "\n",
    "#plt.plot(profile_PHC, clim.z, color='white', lw=6, label='PHC')\n",
    "plt.plot(profileS_PHC, clim.z, color='black', lw=3, label='PHC')\n",
    "\n",
    "\n",
    "plt.plot(profileS_REF, depths, color='#1f77b4', lw=3, linestyle='dashed', label='REF')\n",
    "plt.plot(profileS_LR, depths, color='#1f77b4', lw=3, label='LR')\n",
    "plt.plot(profileS_AGUV, depths, color='#2ca02c', lw=3, linestyle='dashed', label='MR0')\n",
    "plt.plot(profileS_GLOB, depths, color='#2ca02c', lw=3, label='MR')\n",
    "plt.plot(profileS_BOLD, depths, color='#ff7f0e', lw=3, label='HR')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "plt.gca().invert_yaxis()\n",
    "\n",
    "plt.hlines(1000.,xmin=34.8,xmax=37., linestyle='dashed', color='0.4')\n",
    "\n",
    "ax1.set_xlim([34.8, 37.])\n",
    "ax1.set_ylim([2000, 0])\n",
    "\n",
    "plt.xlabel('salinity [psu]', fontsize=16)\n",
    "plt.ylabel('depth [m]', fontsize=16)\n",
    "plt.legend(loc='lower right', fontsize=20)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from matplotlib.backends.backend_pdf import PdfPages\n",
    "saveFIG=True\n",
    "if saveFIG==True:\n",
    "   pp = PdfPages('/pf/a/a270046/hierarchy/new_figures/'+'gibraltar_Sprofiles_last30years_PHC.pdf')\n",
    "   pp.savefig(fig3,bbox_inches = 'tight')\n",
    "   pp.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}