Structural Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# Structural Analysis\n",
    "\n",
    "or **Spatial Modeling**, or **Variography**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Available Variogram Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Spherical \n",
    "\n",
    "Spherical model defined by an actual *range* a and positive variance contribution or *sill* value c\n",
    "\n",
    "$$\\gamma(h)=c\\cdot \\text{Sph}\\left(\\frac{h}{a}\\right)= \n",
    "\\begin{cases}\n",
    "c \\cdot \\left[1.5\\frac{h}{a}-0.5{\\left(\\frac{h}{a}\\right)}^{3}\\right], & \\text{if } h\\leq a \\\\\n",
    "a, & \\text{if } h\\geq a\n",
    "\\end{cases}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exponential\n",
    "\n",
    "Exponential mode defined by an effective range a (integral range a/3) and positive variance contribution value c.\n",
    "\n",
    "$$\\gamma(h)=c \\cdot \\text{Exp}{\\left(\\frac{h}{c}\\right)}=c\\cdot \\left[1-\\exp\\left(-\\frac{3h}{a}\\right)\\right]$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gaussian\n",
    "\n",
    "Gaussian model defined by an effective range a and positive variance contribution value c.\n",
    "\n",
    "$$\\gamma(h)=c \\cdot \\left[1-\\exp {\\left(-\\frac{{3h}^{2}}{{a}^{2}}\\right)}\\right]$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Power\n",
    "\n",
    "Power model defined by a power $0<\\omega<2$ and positive slope c.\n",
    "\n",
    "$$\\gamma(h)=c \\cdot {h}^{\\omega}$$\n",
    "\n",
    "The distance h may be anisotropic in 2D or 3D."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hole effect\n",
    "\n",
    "Hole effect model defined by a length a to the first peak (size of the underlying cyclic features) and positive variance contribution value c.\n",
    "\n",
    "$$\\gamma(h)=c \\cdot \\left[1.0-\\cos\\left(\\frac{h}{a}\\cdot \\pi\\right)\\right]$$\n",
    "\n",
    "To be a legitimate positive definite variogram model, the hole effect model may only be applied in one direction; that is, the variogram specified by the direction of hole effect, the range parameter in that direction, and very large range parameters in the two other directions, say, 1.0e21.\n",
    "\n",
    "Although not allowed for in the parameter file, a dampened hole effect model is also coded in the cova3 subroutine. The dampened hole effect model is:\n",
    "\n",
    "$$\\gamma(h)=c\\cdot \\left[1.0-\\exp{\\left(-\\frac{-3\\cdot h}{d}\\right)}\\cdot \\cos{\\left(\\frac{h}{a}\\cdot \\pi\\right)}\\right]$$\n",
    "\n",
    "where d is distance at which 95% of the hole effect is dampened out(the variogram magnitude of the periodic component is then 5% of c)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fiting a variogram model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Fitting the behavior at the origin\n",
    "\n",
    "<img src=\"img\\behavior_near_origin.png\", width=400>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Modeling the Continuous Component"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## GUI for Variography"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook\n",
    "import variogram_model as vm\n",
    "from gamv_yuhao import Gamv\n",
    "# import IPython widgets\n",
    "from ipywidgets import *\n",
    "import ipywidgets as widgets\n",
    "from traitlets import link\n",
    "from IPython.display import display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "gamv_yuhao.py:289: RuntimeWarning: invalid value encountered in true_divide\n",
      "  self.gam /= self.npair\n",
      "gamv_yuhao.py:294: RuntimeWarning: invalid value encountered in true_divide\n",
      "  self.distance /= self.npair\n",
      "gamv_yuhao.py:295: RuntimeWarning: invalid value encountered in true_divide\n",
      "  self.tm /= self.npair\n",
      "gamv_yuhao.py:296: RuntimeWarning: invalid value encountered in true_divide\n",
      "  self.hm /= self.npair\n"
     ]
    }
   ],
   "source": [
    "gamv = Gamv(\"testData/xihuSmall_sparse_gamv.par\")\n",
    "gamv.read_data()\n",
    "gamv.gamv()\n",
    "# fig, axes = data_analysis.graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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   "source": [
    "plot_dropdown = widgets.Dropdown(\n",
    "    options={i+1: i for i in xrange(gamv.ndir)},\n",
    "    value = 0,\n",
    "    description=\"Plot\",\n",
    ")\n",
    "\n",
    "def plot(change):\n",
    "    i = plot_dropdown.value\n",
    "    abscissa = np.arange(0, gamv.nlag+1, 1.0)\n",
    "    abscissa *= gamv.xlag\n",
    "    ordinate = np.insert(gamv.gam[i][2:], 0, None)\n",
    "    ax.cla()\n",
    "    ax.scatter(abscissa, ordinate, color='r')\n",
    "    ax.set_title(r\"Azimuth: {}$^\\circ$({}$^\\circ$), \".format(\n",
    "        gamv.azm[i], gamv.atol[i]) +\n",
    "                 r\"Dip: {}$^\\circ$({}$^\\circ$)\".format(\n",
    "                     gamv.dip[i], gamv.dtol[i]))\n",
    "    ax.set_ylim(bottom=0)\n",
    "    ax.set_xlim(left=0)\n",
    "    ax.grid()\n",
    "\n",
    "plot_dropdown.observe(plot, names=\"value\")\n",
    "\n",
    "plot_button = widgets.Button(\n",
    "    button_style='primary',\n",
    "    description='Plot',\n",
    "    value=False,\n",
    ")\n",
    "plot_button.on_click(plot)\n",
    "\n",
    "num_struct_slider = widgets.IntSlider(\n",
    "    value=1,\n",
    "    min=1,\n",
    "    max=3,\n",
    "    step=1,\n",
    "    description='Structs:',\n",
    "    disabled=False,\n",
    "    continuous_update=False,\n",
    "    orientation='horizontal',\n",
    "#     width='300px'\n",
    ")\n",
    "def num_on_change(change):\n",
    "    index = change['new'] - 1\n",
    "    for i, item in enumerate(struct_box.children):\n",
    "        if i <= index:\n",
    "            item.layout.visibility=''\n",
    "        else:\n",
    "            item.layout.visibility='hidden'\n",
    "            item.children[3].value = 0\n",
    "    \n",
    "    \n",
    "num_struct_slider.observe(num_on_change, names='value')\n",
    "\n",
    "main_box = HBox((plot_dropdown, plot_button, num_struct_slider))\n",
    "\n",
    "function_dict = {\n",
    "    'Spherical': np.vectorize(vm.spherical),\n",
    "    'Exponential': np.vectorize(vm.exponential),\n",
    "    'Gaussian': np.vectorize(vm.gaussian)\n",
    "}\n",
    "\n",
    "def plot_fit(change):\n",
    "    func = function_dict[type_1_dropdown.value]\n",
    "    abscissa = np.arange(0, (gamv.nlag+4)*gamv.xlag, gamv.xlag/10)\n",
    "    crange = range_1_text.value\n",
    "    sill = sill_1_text.value\n",
    "    nugget = nugget_effect_text.value\n",
    "    if crange != 0 and sill != 0:\n",
    "        ordinate = func(abscissa, sill, crange) + nugget\n",
    "    else:\n",
    "        ordinate = np.zeros(abscissa.shape) + nugget   \n",
    "    if len(ax.lines) != 0:\n",
    "        del ax.lines[-1]\n",
    "    ax.plot(abscissa, ordinate, color='blue')\n",
    "    plt.draw()\n",
    "\n",
    "nugget_effect_text = widgets.FloatText(\n",
    "    value=0,\n",
    "    description='Nugget: '\n",
    ")\n",
    "nugget_effect_text.observe(plot_fit, names=\"value\")\n",
    "############################################\n",
    "label_1 = widgets.HTML(\n",
    "    value=\"<b>Structure 1:<b>\"\n",
    ")\n",
    "\n",
    "type_1_dropdown = widgets.Dropdown(\n",
    "    options=['Spherical', 'Exponential', 'Gaussian'],\n",
    "    value = 'Spherical',\n",
    "    description=\"Type: \",\n",
    ")\n",
    "type_1_dropdown.observe(plot_fit, names=\"value\")\n",
    "\n",
    "sill_1_text = widgets.FloatText(\n",
    "    value=1,\n",
    "    description='Sill (Contribution): '\n",
    ")\n",
    "sill_1_text.observe(plot_fit, names=\"value\")\n",
    "    \n",
    "range_1_text = widgets.FloatSlider(\n",
    "    value=0.0,\n",
    "    min=0.0,\n",
    "    max=(gamv.nlag+1) * gamv.xlag,\n",
    "    step=0.1,\n",
    "    description='Range:',\n",
    ")\n",
    "range_1_text.observe(plot_fit, names=\"value\")\n",
    "\n",
    "struct_1 = VBox((label_1, type_1_dropdown, sill_1_text, range_1_text))\n",
    "############################################\n",
    "label_2 = widgets.HTML(\n",
    "    value=\"<b>Structure 2:<b>\"\n",
    ")\n",
    "\n",
    "type_2_dropdown = widgets.Dropdown(\n",
    "    options=['Spherical', 'Exponential', 'Gaussian'],\n",
    "    value = 'Spherical',\n",
    "    description=\"Type: \",\n",
    ")\n",
    "type_2_dropdown.observe(plot_fit, names=\"value\")\n",
    "\n",
    "sill_2_text = widgets.FloatText(\n",
    "    value=1,\n",
    "    description='Sill (Contribution): '\n",
    ")\n",
    "sill_2_text.observe(plot_fit, names=\"value\")\n",
    "    \n",
    "range_2_text = widgets.FloatSlider(\n",
    "    value=0.0,\n",
    "    min=0.0,\n",
    "    max=(gamv.nlag+1) * gamv.xlag,\n",
    "    step=0.1,\n",
    "    description='Range:',\n",
    ")\n",
    "range_2_text.observe(plot_fit, names=\"value\")\n",
    "\n",
    "struct_2 = VBox((label_2, type_2_dropdown, sill_2_text, range_2_text))\n",
    "struct_2.layout.visibility='hidden'\n",
    "############################################\n",
    "label_3 = widgets.HTML(\n",
    "    value=\"<b>Structure 3:<b>\"\n",
    ")\n",
    "\n",
    "type_3_dropdown = widgets.Dropdown(\n",
    "    options=['Spherical', 'Exponential', 'Gaussian'],\n",
    "    value = 'Spherical',\n",
    "    description=\"Type: \",\n",
    ")\n",
    "type_3_dropdown.observe(plot_fit, names=\"value\")\n",
    "\n",
    "sill_3_text = widgets.FloatText(\n",
    "    value=1,\n",
    "    description='Sill (Contribution): '\n",
    ")\n",
    "sill_3_text.observe(plot_fit, names=\"value\")\n",
    "    \n",
    "range_3_text = widgets.FloatSlider(\n",
    "    value=0.0,\n",
    "    min=0.0,\n",
    "    max=(gamv.nlag+1) * gamv.xlag,\n",
    "    step=0.1,\n",
    "    description='Range:',\n",
    ")\n",
    "range_3_text.observe(plot_fit, names=\"value\")\n",
    "\n",
    "struct_3 = VBox((label_3, type_3_dropdown, sill_3_text, range_3_text))\n",
    "struct_3.layout.visibility='hidden'\n",
    "##############################\n",
    "struct_box = HBox((struct_1, struct_2, struct_3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "        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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<img 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FiAAEgC9LUcA9Aqmxre1tam9vT2wYjZL4Ri337HEMk4gphI9GeNIACQAejuJAOgVTI3v6elRc3NzYMVslsIxbr9jiWWcQEwlejLGkQBIAPR2EgHQK8h4BBBAAAEEqixAACQAeluOAOgVZDwCCCCAAAJVFiAAEgC9LUcA9AqmxnOH+xhMHGMcrQqWWMYJxFSiJ2McCYAEQG8nEQC9gqnxnZ2damlpCayYzVI4xu13LLGME4ipRE/GOBIACYDeTiIAegUZjwACCCCAQJUFCIAEQG/LEQC9goxHAAEEEECgygIEQAKgt+UIgF7B1Pje3l41NTUFVsxmKRzj9juWWMYJxFSiJ2McCYAEQG8nEQC9gqnxs2bN0sKFCwMrZrMUjnH7HUss4wRiKtGTMY4EQAKgt5MIgF5BZgADBXOlmCGII8USyziBmEr0ZIwjAZAA6O0kAqBXkPEIIIAAAghUWYAASAD0thwB0CvIeAQQQAABBKosQAAkAHpbjgDoFUyN5/5WMZg4xjhaFSyxjBOIqURPxjgSAAmA3k4iAHoFU+O5w30MJo4xjlYFSyzjBGIq0ZMxjgRAAqC3kwiAXkHGI4AAAgggUGUBAiAB0NtyBECvIOMRQAABBBCosgABkADobTkCoFcwNb6np0fNzc2BFbNZCse4/Y4llnECMZXoyRhHAiAB0NtJBECvYGp8W1ub2tvbAytmsxSOcfsdSyzjBGIq0ZMxjgTAbATAFkmnShonaVtJoyQ9O0gLjZa0WNLU5HVXSzpN0roCYwiAMZ9FqiCAAAIIIFA1AQJgNgLgIZJ2lLSNpK8VEQAt8FlItOA4wu4EIenfkt5NAKzaZ5M3QgABBBBAoGICBMBsBMB8A02SdMMQAfDVkh6StI+kO5OB9u+rJdnf/bFfNzIDWLGPJ4URQAABBBCojAABkADYv7OOlPS9ZLYw/Xe9ko6W9L8EwMp8GK1qR0eHWltbK/cGGamMY9yOxhLLOIGYSvRkjCMBkADYv5OOl7RA0sv7/UWPpFmSriAAxnz4ClVZuXKlJk6cWLk3yEhlHON2NJZYxgnEVKInYxwJgARAZgBjPktUQQABBBBAoG4ECIAEwP7Nauf5/T65Yjh/DqBdPfxrSbsMdA7g5MmTNXbs2L5aBx10kJYvX6558+apqamp78/s2Y2jR4/WlClT+v7b7uO0aNGizW55YtP648aN2zQD1t3drWXLlmnOnDmb1nH+/PmaNm2axowZ0/dn9pvgmjVrNjtsarcImDlz5qb76dljg9auXauWFrumRert7dXcuXNZP/zov+RRb3w+cj9i+PnCz+dG//6w78OlS5dq1apVmjBhghYvtht+aAdJj9VNcg1cUbvKtdGXLZILP+wikJ9K2k7SBklPS9pYYON/krz+uOQq4O9KekLSUQVey0Uggd1joTcfbgPLZq4UjnG7HEss4wRiKtGTMY7MAGZjBvBESZelwp6FXgt+ByWzfXdLOlTSzUlb2X0AL5Z0ePI6C4R2H8BCvyEQAGM+i5tmINIznoGlM1XKZnJwjNnlWMY45mcY6Uu/Jz3pN7QKBMBsBMCYbilchQBYSV1qI4AAAgggUAEBAiAB0NtWBECvIOMRQAABBBCosgABkADobTkCoFeQ8QgggAACCFRZgABIAPS2HAHQK5gaz7ktMZg4xjhaFSyxjBOIqURPxjgSAAmA3k4iAHoFU+O5ui0GE8cYR6uCJZZxAjGV6MkYRwIgAdDbSQRAryDjEUAAAQQQqLIAAZAA6G05AqBXkPEIIIAAAghUWYAASAD0thwB0CuYGs8zLmMwa95x/Xpp6VJp9Wpp332l6dOlUaNiNj64Ss1bBm9vJcthGaOLY4wjAZAA6O0kAqBXMDXeHofX2toaWDGbpWra0cLfpEnSqlWS/bsFv/HjpRUrajIE1rRlnbU3ljE7DMcYRwIgAdDbSQRAryDjsyXQ2SnNmGEPpX5uu+2Z2UuWSMnzqrMFwtYigMBwCBAACYDeviMAegUZny2BtjZpwQJpgz2OO1lGjpRmz5ba27NlwdYigMCwCRAACYDe5iMAegUZny0BZgCztb/ZWgRqVIAASAD0tiYB0CuYGt/W1qZ2ZoHcojXtWGfnANa0pbtTqlsAyxhvHGMcCYAEQG8nEQC9gqnxPT09am5uDqyYzVI171hHVwHXvGUdtTiWMTsLxxhHAiAB0NtJBECvIOMRQAABBBCosgABkADobTkCoFeQ8QgggAACCFRZgABIAPS2HAHQK5ga39XVpSlTpgRWzGYpHOP2O5ZYxgnEVKInYxwJgARAbycRAL2CqfGdnZ1q4V5wblEc3YSbCmCJZZxATCV6MsaRAEgA9HYSAdAryHgEEEAAAQSqLEAAJAB6W44A6BVkPAIIIIAAAlUWIAASAL0tRwD0CqbG9/b2qskeC8biEsDRxbfZYCyxjBOIqURPxjgSAAmA3k4iAHoFU+NnzZqlhQsXBlbMZikc4/Y7lljGCcRUoidjHAmABEBvJxEAvYLMAAYK5koxQxBHiiWWcQIxlejJGEcCIAHQ20kEQK8g4xFAAAEEEKiyAAGQAOhtOQKgV5DxCCCAAAIIVFmAAEgA9LYcAdArmBrP/a1iMHGMcbQqWGIZJxBTiZ6McSQAEgC9nUQA9AqmxnOH+xhMHGMcrQqWWMYJxFSiJ2McCYAEQG8nEQC9goxHAAEEEECgygIEQAKgt+UIgF5BxiOAAAIIIFBlAQIgAdDbcgRAr2BqfE9Pj5qbmwMrZrMUjnH7HUss4wRiKtGTMY4EQAKgt5MIgF7B1Pi2tja1t7cHVsxmKRzj9juWWMYJxFSiJ2McCYAEQG8nEQC9goxHAAEEEECgygIEQAKgt+UIgF5BxiOAAAIIIFBlAQIgAdDbcgRAryDjEUAAAQQQqLIAAZAA6G05AqBXMDW+o6NDra2tgRWzWQrHuP2OJZZxAjGV6MkYRwIgAdDbSQRAr2Bq/MqVKzVx4sTAitkshWPcfscSyziBmEr0ZIwjAZAA6O0kAqBXkPEIIIAAAghUWYAASAD0thwB0CvIeAQQQAABBKosQAAkAHpbjgDoFUyN7+7u1pgxYwIrZrMUjnH7HUss4wRiKtGTMY4EQAKgt5MIgF7B1Pj58+drzpw5gRWzWQrHuP2OJZZxAjGV6MkYRwIgAdDbSQRAryDjEUAAAQQQqLIAAZAA6G05AqBXkPEIIIAAAghUWYAASAD0thwB0CvIeAQQQAABBKosQAAkAHpbjgDoFUyN59yWGEwcYxytCpZYxgnEVKInYxwJgARAbycRAL2CqfFc3RaDiWOMo1XBEss4gZhK9GSMIwGQAOjtJAKgV5DxCCCAAAIIVFmAAEgA9LYcAdAryHgEvALr10tLl0qrV0v77itNny6NGuWtyngEEGhgAQIgAdDb3gRAr2BqPM+4jMHMlKOFv0mTpFWrJPt3C37jx0srVoSEwExZxrTfgFWwjAHGMcaRAEgA9HYSAdArmBrf0dGh1tbWwIrZLJUpx85OacYMqbf3uZ3d1CQtWSK1tLgbIFOWbq3BC2AZA4xjjCMBkADo7SQCoFeQ8Qh4BNrapAULpA0bnqsycqQ0e7bU3u6pzFgEEGhgAQIgAdDb3gRAryDjEfAIVHgG0LNqjEUAgdoVIAASAL3dSQD0CjIeAY9Ahc8B9KwaYxFAoHYFCIAEQG93EgC9gqnxbW1tauewnVs0c44VvAo4c5bu7hu4AJYxuDjGOBIACYDeTiIAegVT43t6etTc3BxYMZulcIzb71hiGScQU4mejHEkABIAvZ1EAPQKMh6BrAhUcKYyK4RsJwJRAgRAAqC3lwiAXkHGI5AFAc5VzMJeZhvrSIAASAD0tisB0CuYGt/V1aUpU6YEVsxmKRzj9nuYJVcrK8wybvfWZSUcY3YbAZAA6O0kAqBXMDW+s7NTLQE37w1cpboshWPcbguz5H6FCrOM2711WQnHmN1GACQAejuJAOgVZDwCWRBgBjALe5ltrCMBAiAB0NuuBECvIOMRyIIA5wBmYS+zjXUkQAAkAHrblQDoFUyN7+3tVZM9x5XFJYCji2+zwaGWGb8KONQybhfXXSUcY3YZATA7AfA8SSdJssB2h6RTJd01QBu9SdLnJe0r6RlJN0o6XdLDBV5PAIz5LPZVmTVrlhYuXBhYMZulcIzb71hiGScQU4mejHEkAGYjAM6WdJqkwyQ9IOlcSR+Q9HpJT/ZrpRGSeiRdLulMSVtL+oakV0l6CwEw5oM3UBV+s43xxTHG0apgiWWcQEwlejLGkQCYjQD4oCSbVro4aZuRkv5sE05J0Et302hJ/0xm/36b/MVUSVdKeiEBMOaDRxUEEEAAAQSGU4AA2PgB0A7RrpV0gKRbU83WJckC3hkFGvBLyZ/NSWYAvyrpP8msYf+Xcwh4OD/BvDcCCCCAAAJlCBAAGz8A2qFbO3dvT0n3pnrke5Iek3Rygb55m6RLJb1OOZ/VyeHjvzMDWManrIQh3N+qBKxBXopjjKNVwRLLOIGYSvRkjCMBsPEDYKkzgK9NLg75eHLu35aSPiXpOEl7JzOB6e5jBjDms9hXhTvcx2BGOT72mHT33bl//vAH6e9/l/7xj9z/P/64tHGj9Oyzuf/v/0/Mlgx/lSee6NK22/J0mog9gWWEooSj3/G006Rjj31MO+ywgxWz/7EJocwtNsPV6EuhcwD/klzZaxd7pJfpkr4u6UWpP9xO0jpJ+0v6Vb/X9wXAyZMna+zYsX1/ddBBB2n58uWaN2/eplua2G9so0eP3vSYs56eHi1atEjt7e2bynV0dGjcuHGaOHFi3591d3dr2bJlmjPHjkTnlvnz52vatGkaM2ZM33+vXLlSa9asUWtr66bXtLW1aebMmWpubu77MwsDa9eu3fSEDTuBeO7cuawffpv135e/3KFtthmnf/5zon7xC+m227r1178u00tfOkfW2rvuKj3wwHztv/807bXXGG2/vXT//Sv10ENrdNhhrRoxQn3/fPObbZo2baZ22inXf3fc0aUnnlirSZNa+v776ad7tWTJXM2YMU9bbZW75c+KFZ3adtvReuMbc0Hr0Ud7tGzZIn3wg899Pq65pkO77jpOe+6Z+3w88ki3fvnLZXrve5/7fFx55XwdcMA07bxz7vNxzz0r9fvfr9G73vXc5+Oyy3Lrt+OOrB9+9F/WPh/28+jmm5fqj39cpbe9bYIWL15sPyoIgP2CTSP9p53nZ1cB28UcFgbPkXS8pD0KXAX8avvekDRT0mWSRkmybxi7YMT+zoJgemEGsJE6JWPbYjN8P/mJdNVV0g035Gbx3vY2adIkab/91Bf8XvzijKGwuQggkAkBDgE3/iHgfCN/WpJNA9hs3u2p+wDuLOluSYdKujl58TslfUaSTSNsTC4WOUvSTQU+FQTAwB8VNjOan7kMLJu5UoM59vZKS5fauW02OyztsYd0zDHSYYdJ++4rjbRr5Fk2CdCTcc2AZYwljjGOBMDsBMCYjnl+FQJgoKwdvk4fFg8snalShRwfeEC69FLpssukl7xEOu64XPCzAMgysAA9GdcdWMZY4hjjSAAkAHo7iQDoFWR8xQTskO6KFdIFF0jLl0vvfrf0kY/kDvHa+XosCCCAQFYFCIAEQG/vEwC9gowPF7Dgd+210mc/K915p/Txj0unnCK9/OXhb0VBBBBAoC4FCIAEQG/jEgC9gowPFbAreD/1KbtC156tLNntDnJ3OmBBAAEEEMgLEAAJgN5PAwHQK5gab7fCSd/SJrB0w5eywHfmmdL110sHH9yh73ynVdtu2/CbXfENpCfjiLGMscQxxpEASAD0dhIB0CuYGm/3NczfBzGwbEOXWrdOOu886ctflk48Mffvv/89jlE7nZ6Mkszdt5TPt98TR7+hVSAAEgC9nUQA9AoyvmyBH/5QOvVUaa+9pC9+UdrbnlXDggACCCAwpAABkAA4ZJMM8QICoFeQ8SUL/PnPuXP77Arfiy6Sjj+eq3pLRmQAAvUmsEXTrIMAACAASURBVH597iaeq1fnbto5fbo0yp5VwFKOAAGQAFhO36THEAC9gqnx9vi7/GPuAss2TCm7unfJEun006WpU3Ozfi996fM3D8e4XV7TlnUWCGraMq5lKlPJ9rXdv2nVKnU//bTGbLWVNH587rdAQmBZ5gRAAmBZjZMaRAD0CqbG27OO088+Dixd96UefVSyRz7feKP09a/nAuBAC45xu7tmLVOBQPbvFgJqPBDUrGVcu1Sukj26Z8YMqbdX85Pnk6qpKfcbYUvuOdsspQkQAAmApXXM819NAPQKMn5IAbuJ8wknSG94Qy782ZM8WDIukAoEmyQIBI3bFG1t0oIF0oYNz22jPbdx9mypvb1xt7uCW0YAJAB624sA6BVk/IAC9rP+nHOkRYtyP/vtZs48wYOG6RMgEGSrEQj84fubAEgA9DYVAdAryPiCAn//u3TssdIf/yhddVXuSl8WBDYJEAiy1Qx1eMi/1ncQAZAA6O1RAqBXMDWec4RyGLfdJh19tLT//tI3viFtt11pyDiW5jXYq2vWsg4DQc1axrVLZSslF/3Mv/RSzbHDAVwF7PImABIAXQ0kiQDoFUyN5ypB6Wtfk2bOlD7zmdyj3Mo55ItjXFPWtGVWrwKuxHZXomZcG25WqaZ7skLbXImyBEACoLevCIBeQcb3Cdj5fnY+97e+Jf3gB9Lb3w4MAgg8T6ASM5+VqMmuq3kBAiAB0NukBECvIOP1xBO58/3uu0+6+mpp991rCKWOZkZqSI1VqZRAJc59rETNSm0/dcMECIAEQG8zEQC9gqnxWXzGpV3kccQR0o475mb+XvQiP2iYIzMjPL/W346bKoT0ZSWufq5EzUC3/qVCHCu4fvVSmgBIAPT2KgHQK5ga39HRoVa723FGlrvukqZMkQ49VPryl+Nu6B/myMyIwiwz0tODbWaIZSV6shI1K7i/QxwruH71UpoASAD09ioB0CuY0fG33CIdfrj0iU9IZ59d3sUeFaers5mRinvwBsMvUIlZ6UrUHH4p1mAIAQIgAdD7ISEAegUzOP6nP5Xe+17p85+XPvKRGgaos5mRGpZk1SIFKnFeaiVqRm4ztcIFCIAEQG9TEQC9ghkbf/nl0sknS5ddlguBNb0wM1LTu4eVQwCB8gUIgATA8rsnN5IA6BVMjW9ra1N7Az/X8itfkT75SWnpUumQQwLh+pUKdcz4zEioZeV2eV1UxjJmN+EY40gAJAB6O4kA6BVMje/p6VFzc3Ngxdopdckl0qc+JV1zjXTggZVdr0Z2rKzc86tjGSeOZYwljjGOBEACoLeTCIBewQyM/9KXpHPOkezcvwMOyMAGs4kIIIBAjQsQAAmA3hYlAHoFG3z8hRdKn/uc1NUlTZjQ4BvL5iGAAAJ1IkAAJAB6W5UA6BVMje/q6tIUuzFegywXXZR7pu+110pvfGP1NqrRHKsn9/x3wjJAPzmPtGvpUk2ZPl2yf0aNCiiczRL0ZMx+JwASAL2dRAD0CqbGd3Z2qqWlJbDi8JXq6JDOPFO67jppv/2qux6N5Fhduee/G5bOPZC6krzzqafUsvXW0vjx0ooVhMAyaenJMuH6DSMAEgC9nUQA9Ao24Phvf1v66Edz5/xV+oKPBuRjkxpJgHtJNtLebKhtIQASAL0NTQD0CjbYeHue74wZ0rJl0jveMcTGZfwWKw2269mcQgI8TYa+qFEBAiAB0NuaBECvYGp8b2+vmpqaAitWt9TPfia95z3SlVdKU6cWEf4mTZJWrZIsCNo5UUGHxurdsbp7bfB3w9K5N1IzgL2S+j7d9hlfskRqkNM9nEIlD6cnSyYrOIAASAD0dhIB0CuYGj9r1iwtXLgwsGL1St16q/TOd0pf+1qR32sVPDRWz47V22PFvROWxTkN+KrUOYCznnpKCzkH0Akq0ZNuwr4CBEACoLeTCIBewQaYAezuzp3rd+650sc+ViRIBQ+NMUNQ5D4o4mVYFoE01EuSUx16b79dTW96E1cBD+U1xN/Tk07AZDgBkADo7SQCoFewzsf/6U/Sm98sHXecNG9eCRtTwRnAEtaClyKAAAKZFCAAEgC9jU8A9ArW8fi1a6W3vjV3g2c79DtiRAkbkzo0Fn0OYAlrwUsRQACBTAoQAAmA3sYnAHoFU+Pr6f5WTz8t2T2rX/hC6Uc/krbcsgyICl0FXE+OZahVdQiWcdyZs+TzHdc8FahEACQAetuKAOgVTI2vlzvcb9wofehD0m9+k7uf7bbbBiIElKoXx4BNrXgJLOOIM2VZwRn+TDnGtd/zKhEACYDe9iIAegXrcPz550uXXirZlb+veEUdbgCrjAAClRXgHN/K+gZUJwASAL1tRAD0CtbZ+O9+VzrlFOnGG6V99qmzlWd1EUCgOgIVvMq/OhvQ+O9CACQAerucAOgVTI3v6elRc3NzYMXYUjffnDvvz572ceihsbVDqiXnHPXcdJOa7b4006fzvFUnbK33pHPzqjo8U5YVnAHMlGMFO5QASAD0thcB0CuYGt/W1qb29vbAinGlHn5YsluYffrTuef81tySOueo7amn1M4Nd0N2US33ZMgGVrFIpiwreA5gphwr2J8EQAKgt70IgF7BOhj/5JO5271YAOzoqNEVruCMQ41uMauFQG0LVOgq4Nre6PpZOwIgAdDbrQRAr2CNj7crfo8/XvrDH6QbbpC22qpGV5hzjmp0x7BaCCBQiwIEQAKgty8JgF7BGh+/YIH0pS9Jt98uvexlNbyyzADW8M5h1RBAoNYECIAEQG9PEgC9gqnxHR0dam1tDazoK9XVJb3nPdIvfpE7/FvTS+qco46nnlIr5wCG7K5a68mQjRqmIljGwOMY40gAJAB6O4kA6BVMjV+5cqUmTpwYWLH8Uvffn3vE28UX557zWxdLcs7Ryquv1sSpU7kK2LPTsPToFRxbS5/v8I2rYkEcY7AJgARAbycRAL2CNTj+sccky6GWoewQMEvGBCp4BWfGJNlcBGpWgABIAPQ2JwHQK1hj4+2iD7t9nl35e8010siRNbaCrE7lBbJ8PiVXrla+v3iHmhAgABIAvY1IAPQKpsZ3d3drzJgxgRVLL/WFL+QO+/7619KOO5Y+vhZG1IJjLTiUvQ6pK6q7JfV1pP0mMHu2VKP3qSx7W9MDKzzzSV+G7CXhGONIACQAejuJAOgVTI2fP3++5syZE1ixtFI33ZR70sfy5bnz/+p1GW7HenXbtN6pGcD5kvo6sqlJWrJEammp+80bcAMqPPNJX8a0Do4xjgRAAqC3kwiAXsEaGf+3v0njx0s2+XPaaTWyUqzG8AhUeCZseDaqiHflXpJFIPGSRhEgABIAvb1MAPQK1sD4DRtyz/Z90YskmwQZMaIGVopVGF6BLJ4LV+EZwOHdobw7ApsLEAAJgN7PBAHQK1gD4887T7r88tzNnre3PcqCQBYFsjrzmcV9zTaLAEgA9H4MCIBewdT44Ti35brrpHe/W7rlFmmffQI3ZhhLDYfjMG5uRd86c5YVnPnMnGWFOhPHGFgCIAHQ20kEQK9gany1r277059y5/1dcIH0oQ8Fbsgwl6q24zBvbkXfHss4XixjLHGMcSQAEgC9nUQA9AoO0/hnnpEOPljafXfpssuGaSV4WwQQQACBYREgABIAvY1HAPQKDtN4O+/Pznm38/622WaYVoK3RQABBBAYFgECIAHQ23gEQK9gany1nnF5883S5Mm58/7GjQvcgBopVS3HGtnciq4GlnG8WMZY4hjjSAAkAHo7iQDoFUyN7+joUGtra2DF55dau1bad1/p9NOlmTMr+lbDVrwajsO2cVV+YyzjwLGMscQxxpEASAD0dhIB0CtYxfH2nN/3v1967DHp6qu5318V6XkrBBBAoKYECIAEQG9DEgC9gpUYP8CtLL75TenMM6Xf/EZ62ctKfOMK3h6jxDXh5QgggAACTgECYHYC4HmSTpJkge0OSadKumuQ/pkhaZak3SQ9Iel7kj5R4PUEQOeHMHz4ADez/d3XV+gN+4/SlVfmnvpR0sINckvi4sUIIIBArQsQALMRAGdLsqe7HibpAUnnSvqApNdLerJAk35S0kclnSBppaStJe0haTUBsLIf6ba2NrW3t/vepMDjrJ7eeju95ZUP6cAjd9QXv1hG+Tp7RFaIYxlMjTgEy7i9imWMJY4xjgTAbATAByUtlHRx0jYjJf05meG7vF8rbZf8XYuka4poM2YAi0Aq9iU9PT1qbm4u9uWFX1fggfZtIy7QT19ygm59+BXa2uJ8qUuBmho5Upo9W/IG1lLXpYjXhzgW8T5ZeAmWcXsZyxhLHGMcCYCNHwAtoK2VdICkW1Nt0yXpt5LO6NdKU5LgZ7OGpySHjFdJmiPpN8wAxnzwKlql32zdCr1NU3W1bvvCjdrrkzYJXMZSZzOAZWwhQxBAAIFMCRAAGz8AvkrSw5L2lHRvqrvtnL7HJJ3cr+OPk/RtSTdKslnAf0my8wftkLEdBn683+uZAay1Hxmp8/Uef3pr7bNxtU7f5Yf6+H2nSaNGlbe2nANYnhujEEAAgRoVIAA2fgAsdQbwCEnLJNllAj9P+naLJPhNl2Qzh+mFABj44e7q6tKUKTYJ61ySK3ZPbt9Vv3tmF113x47aYusyw19+VeroKuAwR+duaIThWMbtRSxjLHGMcSQANn4AtE4pdA7gXySdLqn/OYD5GcN0ALRzBm22cMAAOHnyZI0dO7avKw866CAtX75c8+bNU1NTU9+fdXZ2avTo0ZvCjZ3DsWjRos0ueLCbe44bN04TJ07sG2MP/F62bJnmzLGjz7ll/vz5mjZtmsaMGdP333ZH+DVr1mx282Q7QXjmzJmbzqWzHxZr165VS4tNaEq9vb2aO3duTa6fOdn2RaxfR0e3Zs5cpnvvnaNddsmGX37/vuc979FVV11F/wV8PqwnbeHzm/sMeX6+5H8O8fPP9/PZviseeughvj9sRqbE7zd7/dKlS7Vq1SpNmDBBixcvtrbeIfmOj0mWdVRlRB2ta7mrauf52VXAU5MweI6k45NDuoWuAr5K0k6S3itpXXLVsF0RbIeR7ZYw6YUZwHL3SgXHPfqo9F//JZ1/vvTBD1bwjSiNAAIIIFCXAswAZmMG0Jrz05LsGWN2le/tqfsA7izp7uSQ781JF28r6aJkxm+DpF8lF4vY6/ovBMAa/Ojb0z6eeEL68Y952kcN7h5WCQEEEBh2AQJgdgJgpZqNABgoa4en84fNyy1rN3r+6EelO++UvHeUKXcdhntchONwb0OtvD+WcXsCyxhLHGMcCYAEQG8nEQC9gqnxs2bN0sKFdsvG8paeHslOxbz0UumYY8qr0QijvI6NYBC1DVhGSUpYxljiGONIACQAejuJAOgVTI33/Ga7caN05JHSdttJV1wRuFJ1WMrjWIebW9FVxjKOF8sYSxxjHAmABEBvJxEAvYJB45cskebOzR363XHHoKKUQQABBBBoSAECIAHQ29gEQK9gwPi//EXaay/pW9+SjrA7ObIggAACCCAwiAABkADo/YAQAL2CqfF2z7X8/QqLLWuHfqdPl17wAg795s3KcSzWO2uvwzJuj2MZY4ljjCMBkADo7SQCoFcwNb6cO9zbVb+nnirdfbf0kpcErkwdlyrHsY43t6KrjmUcL5YxljjGOBIACYDeTiIAegUd4//xj9yh3y99SXrf+xyFGIoAAgggkCkBAiAB0NvwBECvoGP88cdLjz8u/ehH3PDZwchQBBBAIHMCBEACoLfpCYBeQRu/fr20dKl6brpJzQcemDupb9SoQStffbV03HG5Q7+veEXESjRODXvWanNW74IdvBuxjAPFMsYSxxhHAiAB0NtJBECvoIW/SZOkVavU9tRTat96a2n8eGnFigFD4Lp1uRs+n3ee9OEPe1eg8ca3tbVt9qD4xtvC6m0RlnHWWMZY4hjjSAAkAHo7iQDoFezslGbMkHp7n6vU1CTZjf1aWgpWb22VHnxQ+vnPOfTr5Wc8AgggkEUBAiAB0Nv3BECvYFubtGCBtGHDc5VGjpRmz5ba259Xffny3BM/fvMbadddvW/OeAQQQACBLAoQAAmA3r4nAHoFS5gBtEnCvfeWTjtNmjnT+8aMRwABBBDIqgABkADo7X0CoFcwdQ5gx1NPqXWQcwDPOUe65hrp1lslmyRkKSzQ0dGhVjtOzuIWwNJNuKkAljGWOMY4EgAJgN5OIgB6BW18chXwyquv1sSpUwteBXzPPdIb3yjddJP0hjdEvGnj1li5cqUmTpzYuBtYxS3DMg4byxhLHGMcCYAEQG8nEQC9gkWMf/ZZ6e1vl/bbT7rwwiIG8BIEEEAAAQQGESAAEgC9HxACoFewiPFf/3ruli92z79tty1iAC9BAAEEEECAADhoD4ygQ1wCBEAX3+aDu7u7NWbMmM3+8G9/k+yPvvlN6YgjAt+sgUsVcmzgza3opmEZx4tljCWOMY7MADID6O0kAqBXMDV+/vz5mjNnzmYVTzhBevJJ6aqrAt+owUsVcmzwTa7Y5mEZR4tljCWOMY4EQAKgt5MIgF7BQcZfd13uehC7AOSVr6zgG1EaAQQQQCBTAgRAAqC34QmAXsEBxv/nP7l7/n3iE7n7/rEggAACCCAQJUAAJAB6e4kA6BUcYPxZZ0nXXivdcgv3/KsQMWURQACBzAoQAAmA3uYnAHoFU+Pz57bce680frx08825/2cpTYBzhErzGuzVWGIZJxBTiZ6McSQAEgC9nUQA9AqmxtvVbXvsMUaTJ0t77il96UuBxTNUiqsE43Y2lljGCcRUoidjHAmABEBvJxEAvYL9xn//+9LHPiZ1d0ujRwcXpxwCCCCAAAKSCIAEQO8HgQDoFUyNf/zx3Mxfe7tkt39hQQABBBBAoBICBEACoLevCIBewdT4449fqYcfnqgVK6QR3KK8bFmeFVo23fMGYollnEBMJXoyxpEASAD0dhIB0CuYjL/rLrvgo0N33NHad/sXlvIFOjo61NraWn4BRm4SwDKuGbCMscQxxpEASAD0dhIB0CsoaeNG6eCDpTe8QbrwwoCClEAAAQQQQGAQAQIgAdD7ASEAegUlXXGFdMYZuQs/tjdRFgQQQAABBCooQAAkAHrbiwDoFFy3ThozRvriF6X3vc9ZjOEIIIAAAggUIUAAJAAW0SaDvoQA6BQ8/XRpzRrp+uuluXPb1G6XALO4BNracHQBpgZjGSUpYRljiWOMIwGQAOjtJAKgQ9Au/HjTm6Q77pD22kvq6elRc3OzoyJDTQDHuD7AEss4gZhK9GSMIwGQAOjtJAJgmYJ24cchh0j77CMtXFhmEYYhgAACCCBQhgABkABYRttsNoQAWKbgj34knXyydN99PPGjTEKGIYAAAgiUKUAAJACW2TqbhhEAyxDs7c0d8m1rk/7f/3uuQFdXl6ZMmVJGRYakBXCM6wcssYwTiKlET8Y4EgAJgN5OIgCWIThvnvSDH0i/+pU0cuRzBTo7O9XS0lJGRYakBXCM6wcssYwTiKlET8Y4EgAJgN5OIgCWKPinP0l77CH97GfSgQeWOJiXI4AAAgggECBAACQAetuIAFii4AknSBs25G7+zIIAAggggMBwCBAACYDeviMAliD4y1/mrvy95x5p552fP7C3t1dNTU0lVOSlhQRwjOsLLLGME4ipRE/GOBIACYDeTiIAFin47LPS/vtLRx4pnX124UGzZs3SQu4JU6TowC/D0U24qQCWWMYJxFSiJ2McCYAEQG8nEQCLFPzGN6TPfCY3+/eCFxQexG+2RWIO8TIcYxytCpZYxgnEVKInYxwJgARAbycRAIsQfOwx6XWvkxYvlo4+uogBvAQBBBBAAIEKChAACYDe9iIAFiE4e7Z0++3SDTdII0YUMYCXIIAAAgggUEEBAiAB0NteBMAhBO1JH+PGSbfemnvs22AL97fytmNuPI4xjljGOWIZZ8nnO8aSAEgA9HYSAXAIwcMPl3bZJXf4d6iFO9wPJVTc3+NYnFMxr8KyGKXiXoNlcU5DvQrHoYSK+3sCIAGwuE4Z+FUEwEEE7WbPxx4r3X+/tNNOXmrGI4AAAgggECNAACQAejuJADiA4DPPSPvuK510kvSJT3iZGY8AAggggECcAAGQAOjtJgLgAIJf+Yq0YIF0113SVlsVx9zT06Pm5ubiXsyrBhTAMa45sMQyTiCmEj0Z40gAJAB6O4kAWEAwf9uXSy+VjjqqeOK2tja1t7cXP4BXFhTAMa4xsMQyTiCmEj0Z40gAJAB6O4kAWEDwv/9buvFGacUKbvvibTDGI4AAAgjECxAACYDeriIA9hN85BFpzJhc+HvTm7y8jEcAAQQQQCBegABIAPR2FQGwn+AJJ0gbN0rf+Y6XlvEIIIAAAghURoAASAD0dhYBMCX4q19JkyZJ3d3Sq19dOm1HR4daW1tLH8iIzQRwjGsILLGME4ipRE/GOBIACYDeTiIAJoI262fh761vlc4/vzzWlStXauLEieUNZtQmARzjmgFLLOMEYirRkzGOBEACoLeTCICJ4A9/KJ1yivS730nbbedlZTwCCCCAAAKVEyAAEgC93UUAlPT009LYsdIZZ0gcwfW2FOMRQAABBCotQAAkAHp7jAAo6aKLpK9+VVqzRtpyy/JJu7u7NcYuIWZxCeDo4ttsMJZYxgnEVKInYxwJgARAbydlPgA++qj02tdKV1whHXqoj3P+/PmaM2eOrwijhWNcE2CJZZxATCV6MsaRAEgA9HZS5gPgrFm5x711dXkpGY8AAggggEB1BAiA2QmA50k6SZIFtjsknSrpriHazC5l+K2knSWNkvRsgddnLwCuXy8tXSqtXq3fNR+ovT/1Lt122wjtvXd1PrS8CwIIIIAAAl4BAmA2AuBsSadJOkzSA5LOlfQBSa+X9OQgTfR1Sa+QNJkAmChZ+LN7vaxaJa1fr2M2XqkdXrylvvbHw6RRlpFZEEAAAQQQqH0BAmA2AuCDkhZKujhpyZGS/ixplqTLB2jTIySdJalN0rUEwESps1OaMUPq7dWtmqCDdYPu33pvveKb7VJLi/sTz7ktbsK+AjjGOGIZ54hlnCWf7xhLAmDjB0A7RLtW0gGSbk21jZ2xZod3zyjQSjslh4ltxvClkm4gACZKbW3SggXauGGDDtJyvUU36/yR50qzZ0vt7e5PJVe3uQn7CuAY44hlnCOWcZZ8vmMsCYCNHwBfJelhSXtKujfVNt+T9Jikkwu0Uqek1ZIs0UwiAKaEkhnAa3oP0gf0LT2g3bVD09PSkiUhM4AxH2uqIIAAAgggMLgAAbDxA2CpM4Dvk/RJSfsnF328XdL1kraStKFAO/VdBDJ58mSNtTshSzrooIO0fPlyzZs3T01NTX1/1tnZqdGjR2vKlCl9/93T06NFixapPTVrZs93HDdu3KZHodlvecuWLdvstig29T9t2rRN98qzRwKtWbNms+fntrW1aebMmWpubu57r66uLq1du1YtySHa3t5ezZ07t7z1GztW+83+lPa99VIdvvELGr3l5Zqz337SihV95wAO+/rVuh/rJ1f/4YffcP78o//qvv/s+3Dp0qVatWqVJkyYoMWLF9vX5A7JhFDmMvOIDGxxoXMA/yLp9ALnAF4m6WhJvYmLXdlgIe8fSTD8dj+vzF0FvOTrz+i8tl51n3iBtn7T3tL06WEXgPCMy5hPI44xjlYFSyzjBGIq0ZMxjswANv4MoHWKnednVwFPlWRh8BxJx0vao8BVwPabwAtT7fVmm8CTtIukf0r6T5YD4H/+I73+9XaRgXTssTEfwnQVmwVt5Vlyblgc3YSbCmCJZZxATCV6MsaRAJiNAGjd8mlJrZLs3n63p+4DaPf4u1uSPcPi5gJtxTmAKZQFC6Tvfle6/XZpiy1iPoRUQQABBBBAoNoCBMDsBMBK9VZmDgHbI99231268krpkEMqxUldBBBAAAEEKi9AACQAerssMwHwzDP7Hv6hn//cS8Z4BBBAAAEEhleAAEgA9HZgJgLgww9LY8ZIN98sjR/vJRt4vF3BnL4yunLv1NiVcYzbv1hiGScQU4mejHEkABIAvZ2UiQBoD/+wp8BdPtBzU7yKyXi7PU7+9jVBJTNZBse43Y4llnECMZXoyRhHAiAB0NtJDR8Af/tbacIE6e67pV139XIxHgEEEEAAgeEXIAASAL1d2PABcOrU3K1fvvhFLxXjEUAAAQQQqA0BAiAB0NuJDR0Af/ELado06YEHpBe/2Es19Hi7S3v+aSlDv5pXDCSAY1xvYIllnEBMJXoyxpEASAD0dlLDBsCNG6WJE3MBcO5cL1Nx4+2ReflH1hU3glcVEsAxri+wxDJOIKYSPRnjSAAkAHo7qWED4I9+JJ1ySm7274XpZ6N4xRiPAAIIIIDAMAsQAAmA3hZsyAC4YYM0blwuAJ5mD9FjQQABBBBAoIEECIAEQG87N2QA/Pa3pXPOke69V9pqKy9R8eN7e3vV1NRU/ABeWVAAx7jGwBLLOIGYSvRkjCMBkADo7aSGC4BPP5276fO550onnujlKW38rFmztHDhwtIG8ernCeAY1xRYYhknEFOJnoxxJAASAL2d1HAB8JJLpIsvluz+fyNHenlKG89vtqV5DfRqHGMcrQqWWMYJxFSiJ2McCYAEQG8nNVQAfPJJaffdpcWLpenTvTSMRwABBBBAoDYFCIAEQG9nNlQAnD9f+sEPpNtuk0aM8NIwHgEEEEAAgdoUIAASAL2d2TABcO1aabfdpM5O6ZBDvCzljef+VuW59R+FY4yjVcESyziBmEr0ZIwjAZAA6O2khgmAZ50l3XKLdP31wzf7xx3uve2YG49jjCOWcY5Yxlny+Y6xJAASAL2d1BAB8K9/zZ37d911uad/sCCAAAIIINDIAgRAAqC3vxsiAM6cKT30kLRsmZeD8QgggAACCNS+AAGQAOjtnRYUDQAAHTpJREFU0roPgH/4Q+6+f3bhx957ezl843t6etTc3OwrwmjhGNcEWGIZJxBTiZ6McSQAEgC9nVT3AfBDH5Ls5s/f+Y6Xwj++ra1N7e3t/kIZr4BjXANgiWWcQEwlejLGkQBIAPR2Ul0HwO5uad99pbvuyp0DyIIAAggggEAWBAiABEBvn9d1ADzmGOnFL5a+/GUvA+MRQAABBBCoHwECIAHQ2611GwDvuEN661ul+++XXvlKLwPjEUAAAQQQqB8BAiAB0NutdRsADz1U2mcf6fOf9xLEje/o6FBra2tcwYxWwjFux2OJZZxATCV6MsaRAEgA9HZSXQbAFSukI4+UHnxQ2mknL0Hc+JUrV2oiNyJ0g+LoJtxUAEss4wRiKtGTMY4EQAKgt5NqOwCuXy8tXSqtXp272mP6dG3ccpQOPFCyGcCzz/ZuPuMRQAABBBCoPwECIAHQ27W1GwAt/E2aJK1aJdm/jxoljR+vaz71fzrxw1v2zf5tt5138xmPAAIIIIBA/QkQAAmA3q6t3QDY2SnNmCH19m7axo1bN2m/V/5J7/vIjjrjDO+mx4/v7u7WGLsrNYtLAEcX32aDscQyTiCmEj0Z40gAJAB6O6l2A2Bbm7RggbRhw6Zt/NEWR+kjL1iiB/62vbbZxrvp8ePnz5+vOXPmxBfOWEUc43Y4lljGCcRUoidjHAmABEBvJ9VuAOw3A/isRmjfEWt00gfW6+NL3uDdbsYjgAACCCBQtwIEQAKgt3lrNwD2Owfwyi3ep0+OuFD3/2NHNW03yrvdjEcAAQQQQKBuBQiABEBv89ZuALQtS64C3vDrNdr78jn6eNu2OuXUkd5tZjwCCCCAAAJ1LUAAJAB6G7i2A2CydZdfLv33f0v33SdttZV3kys3nnNbYmxxjHG0KlhiGScQU4mejHEkABIAvZ1U8wHwmWekvfaS7NqKD3/Yu7mVHc/VbTG+OMY4WhUssYwTiKlET8Y4EgAJgN5OqvkAeNll0vnnS/fck7sVIAsCCCCAAAJZFyAAEgC9n4GaDoBPPy3tsYf0mc9IJ5zg3VTGI4AAAggg0BgCBEACoLeTazoAdnRIF10k3XmnNLIOrv3gGZfedsyNxzHGEcs4RyzjLPl8x1gSAAmA3k6q2QBoDwB53eukL3xBamnxbmZ1xnd0dKi1tbU6b9bA74Jj3M7FEss4gZhK9GSMIwGQAOjtpJoNgP/zP9JXvyqtXi1tsYV3MxmPAAIIIIBA4wgQAAmA3m6uyQD45JPS7rtLl1wiHXWUdxMZjwACCCCAQGMJEAAJgN6OrskAeOGF0hVXSLffLo0Y4d1ExiOAAAIIINBYAgRAAqC3o2suAD7xhLTrrtKSJdLUqd7Nq+74trY2tbe3V/dNG/DdcIzbqVhiGScQU4mejHEkABIAvZ1UcwHQ8tOyZdIvf1l/s389PT1qbm727pPMj8cxrgWwxDJOIKYSPRnjSAAkAHo7qaYC4Lp1udm/zk7pkEO8m8Z4BBBAAAEEGlOAAEgA9HZ2TQVAu+HzdddJK1bU3+yfd0cwHgEEEEAAgWIFCIAEwGJ7ZaDX1UwA/Ne/crN/dvh30iTvZg3P+K6uLk2ZMmV43ryB3hXHuJ2JJZZxAjGV6MkYRwIgAdDbSTUTAM8+W7rlFun6672bNHzjOzs71VIvd60ePqYh3xnHIYmKfgGWRVMN+UIshyQq6gU4FsU05IsIgATAIZtkiBfURAB89FHpNa+RrrlGOvBA7yYxHgEEEEAAgcYWIAASAL0dXhMB0Gb/Vq6Urr3WuzmMRwABBBBAoPEFCIAEQG+XD3sAbKTZv97eXjU1NXn3SebH4xjXAlhiGScQU4mejHEkABIAvZ007AGwkWb/Zs2apYULF3r3SebH4xjXAlhiGScQU4mejHEkABIAvZ00rAGwkWb/bEfwm623HXPjcYxxxDLOEcs4Sz7fMZYEQAKgt5OGNQA20uyfd0cwHgEEEEAAgWIFCIAEwGJ7ZaDXDVsAbLTZP++OYDwCCCCAAALFChAACYDF9krNBcCzzpJuvbWxrvzl/lbedsyNxzHGEcs4RyzjLPl8x1gSAAmA3k4alhnAf/4z99SPRrvvH3e497ZjbjyOMY5YxjliGWfJ5zvGkgBIAPR20rAEwEac/fPuCMYjgAACCCBQrAABkABYbK/UzCHgRp398+4IxiOAAAIIIFCsAAGQAFhsr9RMAGzk2b+enh41Nzd790nmx+MY1wJYYhknEFOJnoxxJAASAL2dVNVDwPnZv5/+VHrLW7yrXnvj29ra1N7eXnsrVmdrhGPcDsMSyziBmEr0ZIwjATA7AfA8SSdJssB2h6RTJd1VoI1eImmBpLdJerGkf0j6nqRPS3q6wOurGgBt9u+226Sf/zzmA0AVBBBAAAEEsihAAMxGAJwt6TRJh0l6QNK5kj4g6fWSnuzX+LtKarE7aUj6vaTdJP1Q0vWSZg1nAGz02b8s/gBimxFAAAEEhkeAAJiNAPigJHvA7MVJm42U9Ock0F1eROvNlDRD0vjhDIDM/hWxp3gJAggggAACRQgQABs/ANoh2rWSDpB0a6onuiT9VtIZRfTJ1ZJ6JH14uAJgVmb/Ojo61NraWsQu4SWDCeAY1x9YYhknEFOJnoxxJAA2fgB8laSHJe0p6d5U29h5fY9JOnmIVjpb0imS9ktmDfu/vCrnAGZl9m/lypWaOHFizKc7w1VwjNv5WGIZJxBTiZ6McSQANn4A9MwAfjY5V/Adkn43QMv1BcDJkydr7NixfS856KCDtHz5cs2bN09NTU19f2aP7hk9erSmTJnS9992Gf+iRYs2u+LVfqsbN27cpgDU3d2tZcuW6aST5vQ99cOu/L3ppvmaNm2axowZ01fHfhCsWbNms1kzu0Js5syZm26nYneNX7t2rVpa7NRGqbe3V3Pnzg1bvzlz5myimT+f9St1/+Ln+3zgh1/6qAE//3K/QOe/P/h8bP75sO/DpUuXatWqVZowYYIWL15sXDskE0IxybKOqoyoo3Utd1ULnQP4F0mnSxroHEDrikMkWfh7ZJA3rvgMYFZm/8rduYxDAAEEEECgVAFmABt/BtB6ws7zs6uAp0qyMHiOpOMl7VHgKmC7QORbkvaR9E5Jfx2iqSoaALNy7l/e2H5rzc9ulvph5vXPCeAY1w1YYhknEFOJnoxxJABmIwBat9h9/Ozqgu0k3Z66D+DOku6WdKikm5P7/y2X9JSkZ5I2s1nSjck9BPt3XkUDYNZm/+wQcvqQRczHPHtVcIzb51hiGScQU4mejHEkAGYnAMZ0zPOrVCwAZm32r1I7iLoIIIAAAgj0FyAAEgC9n4rYALh+vbR0qbR6tc6693jd9vie+vm1W3jXkfEIIIAAAgggkBIgABIAvR+IuABo4W/SJGnVKj369LZ6zbMP6KdjZ+stqy6WRo3yrifjEUAAAQQQQCARIAASAL0fhrgA2NkpzZhh92nRufq0btZbdF3TEdKSJVJyCxfvytb6eM5tidlDOMY4WhUssYwTiKlET8Y4EgAJgN5OiguAbW3SggVau2FbvUYP6cc6Um8beYs0e7bU3u5dz7oYz9VtMbsJxxhHq4IllnECMZXoyRhHAiAB0NtJcQEwmQH8bO8Zuk7v1Aq9XbIbSWdoBtC7MxiPAAIIIIBAMQIEQAJgMX0y2GviAuD69Xr8wMO0y21X6vtbvE/v2OpGafx4acUKzgH07iXGI4AAAgggkBIgABIAvR+IuAAo6YLzN+gn3/qXbjrqQo0Yv680fXqmwh/PuPS2Y248jjGOWMY5Yhlnyec7xpIASAD0dlJYAPz3v6XXvEb69relQ+221Blc7HnI6ed6ZpAgZJNxDGHsK4IllnECMZXoyRhHAiAB0NtJYQHwwgvtodXSrbdKI7LwhGavPOMRQAABBBAoU4AASAAss3U2DQsJgE8+Ke22m/S1r0mHH+5dJcYjgAACCCCAwGACBEACoPcTEhIAFy2SvvlN6Y47mP3z7hDGI4AAAgggMJQAAZAAOFSPDPX37gDY2yvtvrt08cXSUUcN9XaN/fdtbW1qz8g9Dyu5J3GM08USyziBmEr0ZIwjAZAA6O0kdwC85BLp0kv7Hv+rLTL+2N+enh41Nzd790nmx+MY1wJYYhknEFOJnoxxJAASAL2d5AqATz0lvfa10sKF0jHHeFeF8QgggAACCCBQjAABkABYTJ8M9hpXAPzKV6SLLpLuvJPZP++OYDwCCCCAAALFChAACYDF9spArys7AK5fL73+9dL550vHHutdjcYY39XVpSlTpjTGxgzjVuAYh48llnECMZXoyRhHAiAB0NtJZQfAyy6TLrhAuvtuaeRI72o0xvjOzk61tLQ0xsYM41bgGIePJZZxAjGV6MkYRwIgAdDbSWUFwGeekcaMkc4+WzrxRO8qMB4BBBBAAAEEShEgABIAS+mXQq8tKwB+5zvSuedK3d2ZetSv15rxCCCAAAIIhAgQAAmA3kYqOQBu2CCNHSvNni19+MPet2+s8b29vWpqamqsjRqGrcExDh1LLOMEYirRkzGOBEACoLeTSg6A3/ueNGeOdP/90lZbed++scbPmjVLC+2eOCwuARxdfJsNxhLLOIGYSvRkjCMBkADo7aSSAuCzz0r77COddpp0yinet2688fxmG7NPcYxxtCpYYhknEFOJnoxxJAASAL2dVFIAvOoqaeZM6YEHpK239r414xFAAAEEEECgHAECIAGwnL5Jjyk6AG7cKI0fL510Um4GkAUBBBBAAAEEhkeAAEgA9HZe0QHwxz+WWlulBx+UXvAC79s25njubxWzX3GMcbQqWGIZJxBTiZ6McSQAEgC9nVRUALTZv/32k447Tjr9dO9bNu547nAfs29xjHG0KlhiGScQU4mejHEkABIAvZ1UVAC85hrpgx+Ufv97aZttvG/JeAQQQAABBBDwCBAACYCe/rGxQwZAm/074ABp+nTpzDO9b8d4BBBAAAEEEPAKEAAJgN4eGjIAXnut9P73Sw89JG27rfftGnt8T0+PmpubG3sjq7B1OMYhY4llnEBMJXoyxpEASAD0dtKgAdBm/976Vuld75LmzvW+VeOPb2trU3t7e+NvaIW3EMc4YCyxjBOIqURPxjgSAAmA3k4aNAAuX5479PuHP0jb2ytZEEAAAQQQQGDYBQiABEBvEw4aAA8+WJo0STr3XO/bMB4BBBBAAAEEogQIgARAby8NGABvvFE6/PDcuX8vepH3bRiPAAIIIIAAAlECBEACoLeXBgyAkydLEyZIn/uc9y2yM76jo0OtdrdsFpcAji6+zQZjiWWcQEwlejLGkQBIAPR2UsEAuHKldMghudm/nXbyvkV2xq9cuVITJ07MzgZXaEtxjIPFEss4gZhK9GSMIwGQAOjtpIIBcOpUae+9pQsu8JZnPAIIIIAAAghECxAACYDennpeALz99tyFH/bUj5e+1Fue8QgggAACCCAQLUAAJAB6e+p5AfDd75Z231268EJv6eyN7+7u1pgxY7K34cFbjGMcKJZYxgnEVKInYxwJgARAbydtFgBXr5be/GbpgQekl7/cWzp74+fPn685c+Zkb8ODtxjHOFAssYwTiKlET8Y4EgAJgN5O2iwAHn209MpXSosWecsyHgEEEEAAAQQqJUAAJAB6e2tTAHz44e21337S736XC4EsCCCAAAIIIFCbAgRAAqC3MzcFwNbW7ftu+HzJJd6SjEcAAQQQQACBSgoQAAmA3v7qC4C/+tU6HXjg9rrvPunVr/aWzO54zm2J2fc4xjhaFSyxjBOIqURPxjgSAAmA3k7qC4Dvfe86bb/99vrqV73lsj2eq9ti9j+OMY5WBUss4wRiKtGTMY4EQAKgt5P6AuBWW63TPfdsr91285ZjPAIIIIAAAghUWoAASAD09lhfADz22HW6/HL7VxYEEEAAAQQQqHUBAiAB0NujfQHw179ep/HjCYBeTJ5x6RXMjccxxhHLOEcs4yz5fMdYEgAJgN5OKvgsYG/RrI7v6OhQa2trVjc/bLtxDKMUlljGCcRUoidjHAmABEBvJxEAvYKMRwABBBBAoMoCBEACoLflCIBeQcYjgAACCCBQZQECIAHQ23IEQK8g4xFAAAEEEKiyAAGQAOhtOQKgVzA1vq2tTe3t7YEVs1kKx7j9jiWWcQIxlejJGEcCIAHQ20kEQK9ganxPT4+am5sDK2azFI5x+x1LLOMEYirRkzGOBEACoLeTCIBeQcYjgAACCCBQZQECIAHQ23IEQK8g4xFAAAEEEKiyAAGQAOhtOQKgVzA1vqurS1OmTAmsmM1SOMbtdyyxjBOIqURPxjgSAAmA3k4iAHoFU+M7OzvV0tISWDGbpXCM2+9YYhknEFOJnoxxJAASAL2dRAD0CjIeAQQQQACBKgsQAAmA3pYjAHoFGY8AAggggECVBQiABEBvyxEAvYKp8b29vWpqagqsmM1SOMbtdyyxjBOIqURPxjgSALMTAM+TdJIkC2x3SDpV0l0DtNFoSYslTZX0rKSrJZ0maV2B1xMAYz6LfVVmzZqlhQsXBlbMZikc4/Y7lljGCcRUoidjHAmA2QiAs5MAd5ikBySdK+kDkl4v6ckCrWSBb5QkuxphhKROSf+W9G4CYMwHb6AqP/nJT3TEEUdU9k0yUB3HuJ2MJZZxAjGV6MkYRwJgNgLgg5JsWunipG1GSvqzTThJurxfK71a0kOS9pF0Z/J39u+rJdnf/bHf65kBjPksMgOIY6BAXClmW7CME4ipRE/GOBIAGz8AWkBbK+kASbem2qZL0m8lndGvlY6U9D1J2/T7815JR0v6XwJgzIevUBV+sMXY4hjjaFWwxDJOIKYSPRnjSABs/AD4KkkPS9pT0r2ptrGQ95ikk/u10vGSFkh6eb8/70lmDK8oFAAfeeQRbb+9ZU0Wj8Axxxyj73//+54SjJWEY1wbYIllnEBMJXoyxtEC4M4772zFdkjyQEzhOqpi57g18lLpGcBXFjgs3MiebBsCCCCAAAKNJGATRX9qpA0qdlsaPQCaQ6FzAP8i6fQBzgH8vaRxqXMA7d9/LWmXAmHP/F4h6fFiwXkdAggggAACCNSEwHbJNQEba2JtqrwSWQiAdp6f3cbFbutiYfAcSXaod48BrgL+SXIV8HHJVcDflfSEpKOqvG94OwQQQAABBBBAoCICWQiABvdpSa2SLO3fnroPoJ0AcLekQyXdnAjbfQDtiuHDJdlvBRYILUDaOYMsCCCAAAIIIIBA3QtkJQDW/Y5iAxBAAAEEEEAAgSgBAqBPspQnjPjeqT5GtyeH2u18STtsvkLSmf3OnbT7Kv6PpDcmt+j5qiRzTC9DuRZToz7EilvLH0qaJumdkm5IhhRjgONzvnYrqM9J2k/ShuRJQAdiWVwDpl71UkkXSTpY0laS7pHUJun/sBzU0h4sYE+gsnPKt01OM7InTeWXan2eh/qZUHJDVHnAYI4TJJ2VfMZfIOkPkr4oaUkFvl/q3bGPhABYfveW+oSR8t+pfkaeL+kHyT0W7V6KX5a0l6TxySbYD777JH1D0meSp7H8VNIXJC1KXjOUazE16kds6DW1p9YcK+mQ5B8LgMUY4Lh5+LsmOZXD+nN98gvIr7AcugH7veIqSS9Ozon+V3IxnZ1iYzfKf4bP94Ce9vndMbnH7Nf6BcBqfZ6H+plQcjMMw4DBHO1pXy+RZJ/1f0h6u6Rlkk6Q9OPA75dGcCQAOpu3lCeMON+qbofnr6C2H3z2LOUTJc1PrpzO//b7cUkfk/S6ZCuHci2mRt2C9Vtxuz3BTZJspsruZ5mfASzGAMfnMG12ym4Ebz+4+y9YlvZpsacifT2ZxbeRL0zugrB/cr/Vz/P5HhR0UjKLb48bzf8MrFYPDvUzobROGN5XF3IstEZ29MSe7mV3/bBlKIOIfTG8MiW8OzOAJWClXlrq/QXLe5f6H2WHf0+RtFuyKfZIPrspt/2mll/s0JyFHLsZ5xZFPLllqBp26LlRFntizZXJF659WeQD4FAGOD7XAXYoyG7TdGEyI7C7JLvVk52usDR5TCQ9Wfwn5v2S/l8yK/3P5Ab5H0oen2mmWA5uWSi4VOPzXMzPhOK7YPhfWUwAtO/pbklzJH1bUjHf2xH7Yvh1ilwDAmCRUP1eVuoTRsp7l/oeZWHFfvuaLunaZFPs0IfNGNiXSH4Zk5yPZVdk2w+poZ7cMlQNe85zIywfTc77m5JsTDoADmWA43MdYDdrf0TSX5PzU20Gy86ntKcB2ZfISfRkSR8XO9R7aXLnBDvk+2hyOPiXkujLoSkLBZdquBXzM2Hota+dVwwVAG2G1Q772v9PTmZbi/nejtgXtaM0xJoQAMvbVcX8JlFe5cYYZbfQsd+4bDo9f+6FbVnEb1dD1WiEGUCbMbVZUTusZuHFFmYAy/ts5D+rF0iamyrxM0mrJG3NrFXRsPZ98TtJv0hm/mxm1T7r35L0NkkzsBzSkhnAIYmKesFgAdBm/W3yYUtJR6bu91vM9/ZQ3y8NNZNKACyq1wq+qJQnjJT/LvU30m6gbfdRPEbSdf1W3y5o6H+O0Mzk5PzBzgG0J7d8QpI9i7mYGvWntvkaW3DuSO49mf+M7pScR9kp6ZbUM6vz5xHhOPBev1+SPWS6UAC0q1jpyeI+MXYur51cbxd1rUkNuSOZUbVZViwHtywUXIr5mTbQ900pPxcb6TtroABo9/G9OunTo5MLvtJ7BMeUBgGwuB98hV5V6hNGyn+n+hlpN8y2q3uPSN1YO732drXbvclVwHbFsIU++7Da+Vn5q4CHci2mRv2IFV7TpuSKwfTf/lGS3QLBDqfboTcci9/LdqHRp5JzT3+T9KcdArZZKztHCMviLe9MfgH5ZHKrJ3vCkoXrd0myq6qxLGxpM0d2ONKCi935wB5KYLcjejo5BaEabkP9bC2+C4bvlYM52i2K7OfjXcnTvsy3/zKUQTHfL0PVGD6dEt+ZAFgiWL+XD/SEEV/V+h1ts1F2i42nkk2w/rKnqdhFH/knrfyXpEuS23DYlcF2q5jPluhaTI36VSy85vbDzG6BkL8PYDEGQ/VnMTUaxdFOBLf7sNnFRjYjaDb/m2xcMQ5Y5rDsIhq7bdObk8PndoqC3RfQrgy2BcvCnxib1b8s+Xlor8j/bDwouYditdyG6uNa/7wP5mi3fTk3dcg3/3zfG5Pzf/PbNpRBxL6odce+9SMA1sVuYiURQAABBBBAAIE4AQJgnCWVEEAAAQQQQACBuhAgANbFbmIlEUAAAQQQQACBOAECYJwllRBAAAEEEEAAgboQIADWxW5iJRFAAAEEEEAAgTgBAmCcJZUQQAABBBBAAIG6ECAA1sVuYiURQAABBBBAAIE4AQJgnCWVEEAAAQQQQACBuhAgANbFbmIlEUAAAQQQQACBOAECYJwllRBAAAEEEEAAgboQIADWxW5iJRFAAAEEEEAAgTgBAmCcJZUQQAABBBBAAIG6ECAA1sVuYiURQAABBBBAAIE4AQJgnCWVEEAAAQQQQACBuhAgANbFbmIlEUAAAQQQQACBOAECYJwllRBAAAEEEEAAgboQIADWxW5iJRFAAAEEEEAAgTgBAmCcJZUQQAABBBBAAIG6ECAA1sVuYiURQAABBBBAAIE4AQJgnCWVEEAAAQQQQACBuhAgANbFbmIlEUAAAQQQQACBOAECYJwllRBAAAEEEEAAgboQIADWxW5iJRFAAAEEEEAAgTgBAmCcJZUQQAABBBBAAIG6ECAA1sVuYiURQAABBBBAAIE4AQJgnCWVEEAAAQQQQACBuhAgANbFbmIlEUAAAQQQQACBOAECYJwllRBAAAEEEEAAgboQIADWxW5iJRFAAAEEEEAAgTgBAmCcJZUQQAABBBBAAIG6ECAA1sVuYiURQAABBBBAAIE4AQJgnCWVEEAAAQQQQACBuhAgANbFbmIlEUAAAQQQQACBOAECYJwllRBAAAEEEEAAgboQ+P+Hl4ixdbTfXwAAAABJRU5ErkJggg==\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(main_box, nugget_effect_text, struct_box)\n",
    "fig, ax = plt.subplots()\n",
    "# fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "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": "2.7.12"
  },
  "widgets": {
   "state": {
    "00c0eb72ee6d4badb14548dc4b39afb0": {
     "views": [
      {
       "cell_index": 15
      }
     ]
    },
    "7dd60cde0eab49de9a520abd078ada62": {
     "views": [
      {
       "cell_index": 15
      }
     ]
    },
    "da81d76ef0b54cea9734b7ad8899f8e9": {
     "views": [
      {
       "cell_index": 15
      }
     ]
    }
   },
   "version": "1.2.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}