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"colab": {
"name": "ADSP_06_Sampling.ipynb",
"provenance": []
}
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"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "RRl--UQN4z7W",
"colab_type": "text"
},
"source": [
"<center>\n",
" <img src=\"https://github.com/GuitarsAI/ADSP_Tutorials/blob/master/images/adsp_logo.png?raw=1\">\n",
"</center>\n",
"\n",
"### Prof. Dr. -Ing. Gerald Schuller <br> Jupyter Notebook: Renato Profeta\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "S66YOqXN4z7X",
"colab_type": "text"
},
"source": [
"# Sampling"
]
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "_-3BCfm14z7Y",
"colab_type": "code",
"colab": {},
"outputId": "c8db3efa-025d-4268-cbf2-2e5a87e364f0"
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"source": [
"%%html\n",
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/jAdkpMC4ZGo\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/jAdkpMC4ZGo\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
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"metadata": {
"tags": []
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{
"cell_type": "markdown",
"metadata": {
"id": "YQzDIw744z7g",
"colab_type": "text"
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"source": [
"To see what happens when we sample a signal, lets start with the analog signal s(t). Sampling it means to sample the signal at sample intervals T (example: 1/8000 s in the ISDN example), or the sampling frequency $f_s$ (8kHz in the ISDN example). \n",
"\n",
"Mathematically, sampling can be formulated as multiplying the analog signal with a Dirac impulse at the sampling time instances nT, where n is the number of our sample (n=0,… for causal systems). "
]
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "5J8XDZwK4z7h",
"colab_type": "code",
"colab": {},
"outputId": "9a18b8d3-e81e-4bb9-f262-72a9a6fc1328"
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"source": [
"%%html\n",
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/_YclokYvRk4\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/_YclokYvRk4\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
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"metadata": {
"tags": []
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{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "uK7vX6Kt4z7l",
"colab_type": "code",
"colab": {}
},
"source": [
"# Imports\n",
"%matplotlib notebook\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.ticker import FuncFormatter\n",
"from IPython.display import display, HTML"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "kP7T30hG4z7o",
"colab_type": "code",
"colab": {},
"outputId": "2193e7cc-b196-439f-ffa9-e81423a39cfa"
},
"source": [
"# Format local\n",
"CSS = \"\"\"\n",
".output {\n",
" align-items: center;\n",
"}\n",
"\"\"\"\n",
"HTML('<style>{}</style>'.format(CSS))"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<style>\n",
".output {\n",
" align-items: center;\n",
"}\n",
"</style>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
},
"execution_count": 4
}
]
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "ff1Jvjby4z7r",
"colab_type": "code",
"colab": {},
"outputId": "c3ad081b-283b-4a6d-876e-b9d47b7928a5"
},
"source": [
"\n",
"# Signal\n",
"dirac_sequence = np.ones(4)\n",
"\n",
"# Plot\n",
"fig = plt.figure(figsize=(10,6))\n",
"ax = fig.add_subplot(111)\n",
"plt.stem(dirac_sequence, use_line_collection=True)\n",
"plt.xlim(right=5)\n",
"plt.ylim(top=3)\n",
"plt.yticks([])\n",
"plt.title('Dirac Sequence', loc='left')\n",
"plt.xlabel('time', horizontalalignment='right', x=1.0)\n",
"xmin, xmax = ax.get_xlim() \n",
"ymin, ymax = ax.get_ylim()\n",
"ax.xaxis.set_major_formatter(FuncFormatter(\n",
" lambda val,pos: '{:.0g}T'.format(val) if val !=0 else '0'\n",
"))\n",
"\n",
"# Arrowed Axis\n",
"\n",
"for side in ['bottom','right','top','left']:\n",
" ax.spines[side].set_visible(False)\n",
" \n",
"\n",
"dps = fig.dpi_scale_trans.inverted()\n",
"bbox = ax.get_window_extent().transformed(dps)\n",
"width, height = bbox.width, bbox.height\n",
" \n",
"\n",
"hw = 1./20.*(ymax-ymin) \n",
"hl = 1./20.*(xmax-xmin)\n",
"lw = 1. \n",
"ohg = 0.3 \n",
" \n",
"yhw = hw/(ymax-ymin)*(xmax-xmin)* height/width \n",
"yhl = hl/(xmax-xmin)*(ymax-ymin)* width/height\n",
" \n",
"ax.arrow(xmin, 0, xmax-xmin, 0., fc='k', ec='k', lw = lw, \n",
" head_width=hw, head_length=hl, overhang = ohg, \n",
" length_includes_head= True, clip_on = False) \n",
" \n",
"ax.arrow(0, ymin, 0., ymax-ymin, fc='k', ec='k', lw = lw, \n",
" head_width=yhw, head_length=yhl, overhang = ohg, \n",
" length_includes_head= True, clip_on = False) \n",
" \n",
"# Annotation\n",
"plt.text(3.5, 0.5, r'$\\cdots$',\n",
" {'color': 'black', 'fontsize': 24, 'ha': 'center', 'va': 'center'});\n"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
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" 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",
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" \"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",
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"\n",
" this.image_mode = 'full';\n",
"\n",
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" 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",
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" this.header = titletext[0];\n",
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"\n",
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"\n",
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"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
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" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
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" $(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",
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"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option);\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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"
],
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\" width=\"864\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ulCQ7ceh4z7v",
"colab_type": "text"
},
"source": [
"The sequence or train of Dirac impulses can be written as:\n",
"<br>\n",
"$$ \\large\n",
"\\Delta _{T}(t):= \\sum_{n=0} ^\\infty \\delta(t-nT) $$\n",
"<br>\n",
"Remember that the integral over a Dirac impulse is 1:<br>\n",
"$$\\int _{t=-\\infty} ^\\infty \\delta(t) dt=1$$"
]
},
{
"cell_type": "markdown",
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"source": [
"The integral over the product of a function with a Dirac impulse is the value of the function at the position of the impulse:\n",
"\n",
"$$ \\large\n",
"\\begin{equation} \\int_{t=-\\infty} ^\\infty s(t) \\delta(t-nT)dt = s(nT)\\end{equation}$$ \n",
"\n",
"This is the mathematical formulation of sampling at time-point nT. We can now use this description to compute the resulting **spectrum** with the **Fourier transform**."
]
},
{
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"%%html\n",
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/9wODoG_H-jg\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
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"outputs": [
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"output_type": "display_data",
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"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/9wODoG_H-jg\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
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"text/plain": [
"<IPython.core.display.HTML object>"
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"metadata": {
"id": "D-2uuwjy4z7z",
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"source": [
"First, if we look at the Fourier transform of the analog signal or system, we get<br>\n",
"\n",
"$$ {S ^{c} } ( ω ) = \\int _{ {t= - \\infty } }^ { { \\infty } } {s ( t ) \\cdot e ^{{ - jωt} } dt} $$\n",
"\n",
"where the superscript c denote the continuous version, with $w=2\\pi f$ the angular frequency. If we now compute the Fourier Transform for the sampled signal $s(t)\\cdot \\Delta _T (t)$, with the replacement\n",
"<br>\n",
" $$s(t) \\leftarrow s(t) \\cdot \\Delta_T(t)$$\n",
" \n",
" we obtain the following sum (since only at the sampling time instances the integral is non-zero, as we see in eq. (1)),<br>\n",
" $$\n",
" {S ^{d} } ( ω ) = \\sum _{ {n= - \\infty } } ^ { { \\infty } } {s ( nT) \\cdot e ^{ { - jω nT} } } \n",
" $$\n",
"<br>\n",
"with the superscript d now denoting the discrete time version. Now we can see that the frequency variable only appears as $wnT$, and T is the inverse of the sampling frequency. Hence we get\n",
"<br>\n",
"$$\\omega T=\\frac{\\omega}{f_s}=:\\Omega $$"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "TarmzgFe4z70",
"colab_type": "text"
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"source": [
"This is now our **normalized frequency**, it is without a physical unit, since the unit Hertz in $\\omega$ and $f_s$ cancel. In the normalized frequency $2\\pi$ represents the sampling frequency and $\\pi$ is the so called **Nyquist frequency** (the upper limit of our usable frequency range, defined as **half** the sampling frequency). \n",
"\n",
"Observe that we use the capital $\\Omega$ to signify that this is the normalized frequency. The capitalized version is commonly used to distinguish it from the continuous, non-normalized, version, if both are used. Otherwise, also the small $\\omega$ is used in the literature, for the normalized frequency, if that is all we need, if there is no danger of confusion, as we did before. \n",
"\n",
"To convert a normalized frequency back to the non-normalized one, we simply multiply it with the sampling frequency: $\\omega=\\Omega \\cdot f_s$.\n",
"\n",
"To indicate that we are now in the discrete domain, we rename our signal to x(n)=s(nT).\n",
"\n",
"Its spectrum or frequency response is then\n",
"$$\n",
"X(\\Omega)=\\sum_{n=-\\infty}^\\infty x(n)e^{-j\\Omega n}\n",
"$$\n",
"\n",
"We call this the **“Discrete Time Fourier Transform” (DTFT)**, because we apply it to discrete time signals x(n). This can be distinguished from the Discrete Fourier Transform, because the above time signal has infinite length.\n",
"\n",
"Because n is integer here (no longer real valued like t), we get a $2\\pi$ **periodicity** for $X(\\Omega)$. This is the first important property for discrete time signals. "
]
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "7SLJbNy-4z70",
"colab_type": "code",
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"outputId": "acc0b7d6-5772-4a9e-c22a-36131b84aa10"
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"source": [
"%%html\n",
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/qqbWmiwMC3Q\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
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"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
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"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/qqbWmiwMC3Q\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
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"text/plain": [
"<IPython.core.display.HTML object>"
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{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "mmX0MUde4z76",
"colab_type": "code",
"colab": {},
"outputId": "2623870d-34ca-4b99-91a0-9ff8c2cc4096"
},
"source": [
"# Plot Poles and Zeros\n",
"from matplotlib import patches\n",
"plt.figure(figsize=(10,6))\n",
"ax = plt.subplot(111)\n",
"r = 1.5; plt.axis('scaled'); plt.axis([-r, r, -r, r])\n",
"ticks = [-1, 1]; plt.xticks(ticks); plt.yticks(ticks)\n",
"# Unit Circle\n",
"uc = patches.Circle((0,0), radius=1, fill=False, color='black', ls='dashed')\n",
"ax.add_patch(uc)\n",
"ax.spines['left'].set_position('center')\n",
"ax.spines['bottom'].set_position('center')\n",
"ax.spines['right'].set_visible(False)\n",
"ax.spines['top'].set_visible(False)\n",
"plt.xlabel('Re', horizontalalignment='right', x=1.0)\n",
"plt.ylabel('Im', y=1.0)\n",
"plt.title('Complex z-Plane', loc='right')\n",
"# Annotations\n",
"ax.annotate('$\\omega=0$', xy=(1, 0), xycoords='data',\n",
" xytext=(1.1, 0.35), textcoords='axes fraction',\n",
" arrowprops=dict(facecolor='black', shrink=0.05, width=0.5),\n",
" horizontalalignment='right', verticalalignment='top',\n",
" )\n",
"ax.annotate('$\\omega=\\pi$', xy=(-1, 0), xycoords='data',\n",
" xytext=(0.05, 0.6), textcoords='axes fraction',\n",
" arrowprops=dict(facecolor='black', shrink=0.05, width=0.5),\n",
" horizontalalignment='right', verticalalignment='top',\n",
" )\n",
"ax.annotate('$e^{-j\\omega}$', xy=(0.7, 0.7), xycoords='data',\n",
" xytext=(1, 0.7), textcoords='axes fraction', size=15,\n",
" arrowprops=dict(facecolor='black', width=0.5),\n",
" horizontalalignment='right', verticalalignment='top',\n",
" );"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
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"\n",
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" 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",
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"\n",
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"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
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" 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",
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" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
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"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
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"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option);\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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"
],
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\" width=\"892\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"hide_input": false,
"id": "lcbkBBbR4z78",
"colab_type": "text"
},
"source": [
"Here we can see that in general we obtain a $2\\pi$ periodicity in the frequency domain, because of the $2\\pi$ periodicity of the exponential function $e^{jw}$.\n",
"\n",
"Also observe that for **real valued** signals, the spectrum of the negative frequencies is the conjugate complex of the positive frequencies,\n",
"\n",
"$$\n",
"X(-\\Omega)=X^*(\\Omega)\n",
"$$\n",
"\n",
"where * denotes the conjugate complex operation, because in our DTFT, $e^{-j(-\\Omega )n}=(e^{-j\\Omega n})^*$.\n",
"\n",
"(we also have to use the fact that the conjugate complex of a real valued signal does not change it, to draw the conjugation out of the Fourier sum).\n",
"\n",
"This also means that for real valued signals we only need to look at the frequency range between 0 and $\\pi$, since the negative frequencies are conjugate symmetric (and because of the 2pi periodicity the range between -pi and pi is sufficient to look at). This is also again what the Nyquist Theorem tells us, that the frequencies between 0 and $\\pi$ (the Nyquist frequency) are sufficient to completely describe a (real valued) signal."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "paAL37QM4z79",
"colab_type": "text"
},
"source": [
"## Sampling a Discrete Time Signal"
]
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "iXDnc7Je4z7-",
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"So what happens if we further downsample an already discrete signal x(n), to reduce its sampling rate?\n",
"\n",
"**Downsampling by N** means we only keep every Nth sample and discard every sample in between. Observe that this results in a **normalized frequency which is a factor of N higher**.\n",
"\n",
"This downsampling process can also be seen as first multiplying the signal with a sequence of **unit pulses** (a 1 at each sample position), zeros in between, and later dropping the zeros. This multiplication with the unit pulse train can now be used to mathematically analyse this downsampling, looking at the resulting spectra, first still including the zeros. The frequency response now becomes\n",
"\n",
"\n",
"$$\\large X^d(\\Omega)=\\sum_{n=mN} x(n)e^{-j \\Omega n}$$\n",
"$$\\large =\\sum_{m=- \\infty}^ \\infty x(mN)e^{-j \\Omega mN}$$\n",
"for all integers m.\n",
"\n",
"Again we can write down-sampling as a multiplication of the signal with a sampling function. In continuous time it was the sequence of Dirac impulses, here it is a **sequence of unit pulses** at positions of multiples of N,\n",
"\n",
"$$ \\Delta_N ( n ) = \\left ( \\matrix {{1 , if n = m N} \\\\ {0 , e l s e}} \\right) $$\n",
"\n",
"Then the sampled signal, with the zeros still in it, becomes\n",
"\n",
"$$x^d(n)=x(n)\\Delta _N (n)$$\n",
"\n",
"This signal is now an intermediate signal, which gets the zeros removed before transmission or storage, to reduce the needed data rate. The decoder upsamples it by re-inserting the zeros to obtain the original sampling rate.\n",
"\n",
"Observe that this is then also the signal that we obtain after this upsampling in the decoder. Hence this signal looks interesting to us, because it appears in the encoder and also in the decoder.\n"
]
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"What does its **spectrum or frequency response** look like?\n",
"\n",
"We saw that the downsampled signal $x^d(n)$ can be written as the **multiplication** of the original signal with the unit pulse train $\\Delta_N (n)$. In the spectrum or frequency domain this becomes a **convolution with their Fourier transforms**. \n",
"\n",
"The Fourier transform of the unit pulse train is a dirac impulse train. But that is not so easy to derive, so we just apply a simple trick, to make it mathematically more easy and get converging sums. We have a **guess** what the Fourier transform of the unit pulse train is: we get Dirac impulses at frequencies of $\\frac{2\\pi}{N}k$ (fundamental frequency $2 \\pi / N$ and its harmonics). The fundamental (angular) frequency is $2 \\pi / N$, because our original sampling frequency was $2 \\pi$, and now we reduced it by a factor N.\n",
"\n",
"With a constant factor that becomes clear later, we get our guess to\n",
"\n",
"$$ \\large\n",
"\\delta_{\\frac{2\\pi}{N}} \\left ( Ω \\right )=\\sum_{ k=0 } ^ { N-1 } \\frac{2 \\pi} { N} \\delta( \\Omega-\\frac{2 \\pi}{N} \\cdot k)\n",
"$$\n",
"\n",
"Where $\\delta_{2\\pi/N} \\left ( Ω \\right )$ is (guessed to be) the Fourier transform of the unit impulse train (the Dirac impulse train). We just need to verify it. Its **inverse Discrete Time Fourier Transform** is\n",
"\n",
"$$\\large\n",
"\\Delta_N \\left ( n \\right ) =\\frac{1} {2 π} \\int _ 0^ {2 π} {\\delta_{2\\pi/N} \\left ( Ω \\right ) e^{j n Ω} d Ω}$$\n",
"\n",
"$$\\large\n",
"=\\frac{1} {2 π} \\int_ 0 ^{2 π} \\sum_ { k=0 } ^ { N-1 } \\frac{2 \\pi} { N} \\delta( \\Omega-\\frac{2 \\pi}{N }\\cdot k ) e^{jn\\Omega} d\\Omega \n",
"$$\n",
"\n",
"\n",
"$$\\large\n",
"=\\frac{1}{N} \\sum_{k = 0}^ {N - 1} e^{j \\frac{2 π} {N} \\cdot k \\cdot n}$$"
]
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"Now we have to prove that this is indeed our unit pulse train. To do that, we can look at the sum. It is a geometric sum (a sum over a constant with the summation index in the exponent),\n",
"\n",
"$S= \\sum _{k = 0} ^ {N - 1} c^k$ , $S \\cdot c = \\sum _{k = 1} ^ N c^k$ , $S c -S =c^N -1$, hence we get\n",
"\n",
"$$S =\\frac{c^N - 1} {c - 1}$$\n",
"\n",
"Here we get $c=e^{j\\frac {2 \\pi}{N}n}$, and the sum can hence be computed in a closed form,\n",
"\n",
"$$ \\large\n",
" \\sum _{k = 0}^{N - 1} {e^{j \\frac{2 π} { N} \\cdot n \\cdot k} } =\\frac{e^{j \\frac{2 π} { N} \\cdot n \\cdot N} - 1} {e^{j \\frac{2 π} {N }\\cdot n} - 1}\n",
"$$\n",
"\n",
"In order to get our unit pulse train, this sum must become N for n=mN. We can check this by simply plugging this into the sum. The right part of the sum is undefined in this case (0/0), but we get an easy result by looking at the left hand side: $e^{j \\frac{2 π}{N} \\cdot m N \\cdot k} =1$. Hence the sum becomes N, as desired!<br>\n",
"For $n \\neq m N$ we need the sum to be zero. Here we can now use the right hand side of our equation. The denominator is unequal zero, and the numerator becomes zero, and hence the sum is indeed zero, as needed!\n",
"\n",
"This proves that our **assumption was right**, and we have\n",
"\n",
"$$\\large\n",
"\\Delta_N \\left ( n \\right ) =\\frac{1}{ N } \\sum _{k = 0} ^ {N - 1} e^{j \\frac{2 π} {N} \\cdot k \\cdot n}$$<br>"
]
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"%%html\n",
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"source": [
"Now we can use this expression for the unit pulse train in the time domain and compute the Fourier transform,\n",
"\n",
"$$\\large\n",
"x^d \\left ( n \\right ) =x \\left ( n \\right ) \\cdot \\Delta_N \\left ( n \\right ) $$$$ =x ( n ) \\cdot \\frac{1}{N} \\sum _ {k = 0} ^{N - 1} e^{j \\frac{2 π} {N} \\cdot k \\cdot n}\n",
"$$\n",
"\n",
"Taking its Discrete Time Fourier transform now results in\n",
"\n",
"$$\\large\n",
"X^d \\left ( Ω \\right ) = \\sum _ {n = - ∞} ^ ∞ {x ( n ) \\cdot} \\frac{1}{ N} \\sum _ {k = 0} ^{N - 1} e^{j \\frac{2π}{ N}\\cdot k \\cdot n} \\cdot e^{- j Ω n} = $$\n",
"\n",
"$$\\large\n",
"=\\frac{1} { N} \\sum _ {k = 0}^ {N - 1}\\sum _{n=-\\infty}^{\\infty} {x ( n )\\cdot e^{-j(- \\frac{2\\pi}{N}\\cdot k +\\Omega)}}$$\n",
"\n",
"$$\\large\n",
"=\\frac{1} {N} \\sum _{k = 0} ^{N - 1} {X ( - \\frac{2 π}{ N} k + Ω )}\n",
"$$\n",
"\n",
"This shows, that sampling, still including the zeros, leads (in the frequency domain) to **multiple shifted versions** of the signal spectrum, the so-called **aliasing components**,\n",
"\n",
"\n",
"$$\\large\n",
"X^d (\\Omega)= \\frac{1} {N} \\sum _{k=0} ^{N-1} X(- \\frac{2 \\pi}{N} \\cdot k + \\Omega)$$\n",
"<center>\n",
" <img src='https://github.com/GuitarsAI/ADSP_Tutorials/blob/master/images/aliasing_components.PNG?raw=1'>\n",
"</center>\n"
]
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"**Observe:** The aliasing components **periodify** the spectrum now according to the **new sampling rate**, which is 1/N of the old sampling rate, hence the new period is 1/N the old period (of $2 \\pi$).\n",
"\n",
"**Observe:** The spectral components don't overlap if their bandwidths are below $\\dfrac {2\\pi}{N}$ for complex signals, or for a real low pass signal, it should be below $ \\dfrac{\\pi}{N}$! If we want to reconstruct the original signal, hence we need to make sure the aliasing components don't overlap by suitable filtering at the high sampling rate, to prepare for the down-sampling. Observe that the term „Aliasing“ in the literature is sometime only used for overlapping alias components, and sometimes more broadly, like we do here, to mean any additional shifted frequency component.\n",
"\n",
"Next is an **example**, also including the negative frequencies that now show up above normalized frequency 1 (**1** being the Nyquist frequency here), and showing 2 sine signals at different strength at normalized frequencies 0.4 and 0.35. This can also be seen as a narrow band signal, resulting e.g. from a passband filter."
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"%%html\n",
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/sB5HRZgqgIg\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
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"source": [
"# Signal Processing Parameters\n",
"Fs = 32000\n",
"T=1/Fs\n",
"t = np.arange(Fs//32)*T\n",
"\n",
"# Signals\n",
"w35 = 0.35*Fs/2\n",
"sine_35 = np.sin(2*np.pi*w35*t)\n",
"w40 = 0.4*Fs/2\n",
"sine_40 = 100*np.sin(2*np.pi*w40*t)\n",
"signal=sine_35+sine_40\n",
"\n",
"# FFT\n",
"from numpy.fft import fft\n",
"signal_fft = fft(signal)\n",
"freqs = np.fft.fftshift(np.fft.fftfreq(signal.size,d=T))+Fs/2"
],
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"outputs": []
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"source": [
"plt.figure(figsize=(10,6))\n",
"plt.plot(freqs/(Fs/2),20*np.log10(np.abs(signal_fft)))\n",
"plt.grid()\n",
"plt.ylabel('Magnitude [dB]')\n",
"plt.xlabel(r'$\\dfrac{Frequency}{Nyquist}$');"
],
"execution_count": null,
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" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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"
],
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iUb1IepcaYe8/0poqvwzDZIRJX5UsweBGDhpjKxoqgKLwlP6GLXlaenOachKj4ys9KxoquyzcqvQTjSqD1HnSjvk/VdCU+WfaZCMKPGjmj0IxMBJY2RFUxVYFJ7Sx6gtT0t3TkNWemRkpWdFU2WflVuFdqJRfYg6V9oh778Smir/TINkRIkf1exBIAZOGiMrmqrAovCUPkZteVq6cxqy0iMjKz0rmir7rNwqtBON6kPUudIOef+V0FT5ZxokI0r8qGYPAjFw0hhZ0VQFFoWn9DFqy9PSndOQlR4ZWelZ0VTZZ+VWoZ1oVB+izpV2yPuvhKbKP9MgGVHiRzV7EIiBk8bIiqYqsCg8pY9RW56W7pyGrPTIyErPiqbKPiu3Cu1Eo/oQda60Q95/JTRV/pkGyYgSP6rZg0AMnDRGVjRVgUXhKX2M2vK0dOc0ZKVHRlZ6VjRV9lm5VWgnGtWHqHOlHfL+K6Gp8s80SEaU+FHNHgRi4KQxsqKpCiwKT+lj1JanpTunISs9MrLSs6Kpss/KrUI70ag+RJ0r7ZD3XwlNlX+mQTKixI9q9iAQAyeNkRVNVWBReEofo7Y8Ld05DVnpkZGVnhVNlX1WbhXaiUb1IepcaYe8/0poqvwzDZIRJX5UsweBGDhpjKxoqgKLwlP6GLXlaenOachKj4ys9KxoquyzcqvQTjSqD1HnSjvk/VdCU+WfaZCMKPGjmj0IxMBJY2RFUxVYFJ7Sx6gtT0t3TkNWemRkpWdFU2WflVuFdqJRfYg6V9oh778Smir/TINkRIkf1exBIAZOGiMrmqrAovCUPkZteVq6cxqy0iMjKz0rmir7rNwqtBON6kPUudIOef+V0FT5ZxokI0r8qGYPAjFw0hhZ0VQFFoWn9DFqy9PSndOQlR4ZWelZ0VTZZ+VWoZ1oVB+izpV2yPuvhKbKP9MgGVHiRzV7EIiBk8bIiqYqsCg8pY9RW56W7pyGrPTIyErPiqbKPiu3Cu1Eo/oQda60Q95/JTRV/pkGyYgSP6rZg0AMnDRGVjRVgUXhKX2M2vK0dOc0ZKVHRlZ6VjRV9lm5VWgnGtWHqHOlHfL+K6Gp8s80SEaU+FHNHgRi4KQxsqKpCiwKT+lj1JanpTunISs9MrLSs6Kpss/KrUI70ag+RJ0r7ZD3XwlNlX+mQTKixI9q9iAQAyeNkRVNVWBReEofo7Y8Ld05DVnpkZGVnhVNlX1WbhXaiUb1IepcaYe8/0poqvwzDZIRJX5UsweBGDhpjKxoqgKLwlP6GLXlaenOachKj4ys9KxoquyzcqvQTjSqD1HnSjvk/VdCU+WfaZCMKPGjmj0IxMBJY2RFUxVYFJ7Sx6gtT0t3TkNWemRkpWdFU2WflVuFdqJRfYg6V9oh778Smir/TINkRIkf1exBIAZOGiMrmqrAovCUPkZteVq6cxqy0iMjKz0rmir7rNwqtBON6kPUudIOef+V0FT5ZxokI0r8qGYPAjFw0hhZ0VQFFoWn9DFqy9PSndOQlR4ZWelZ0VTZZ+VWoZ1oVB+izpV2yPuvhKbKP9MgGVHiRzV7EIiBk8bIiqYqsCg8pY9RW56W7pyGrPTIyErPiqbKPiu3Cu1Eo/oQda60Q95/JTRV/pkGyYgSP6rZg0AMnDRGVjRVgUXhKX2M2vK0dOc0ZKVHRlZ6VjRV9lm5VWgnGtWHqHOlHfL+K6Gp8s80SEaU+FHNHgRi4KQxsqKpCiwKT+lj1JanpTunISs9MrLSs6Kpss/KrUI70ag+RJ0r7ZD3XwlNlX+mQTKixI9q9iAQAyeNkRVNVWBReEofo7Y8Ld05DVnpkZGVnhVNlX1WbhXaiUb1IepcaYe8/0poqvwzDZIRJX5UsweBGDhpjKxoqgKLwlP6GLXlaenOachKj4ys9KxoquyzcqvQTjSqD1HnSjvk/VdCU+WfaZCMKPGjmj0IxMBJY2RFUxVYFJ7Sx6gtT0t3TkNWemRkpWdFU2WflVuFdqJRfYg6V9oh778Smir/TINkRIkf1exBIAZOGiMrmqrAovCUPkZteVq6cxqy0iMjKz0rmir7rNwqtBON6kPUudIOef+V0FT5ZxokI0r8qGYPAjFw0hhZ0VQFFoWn9DFqy9PSndOQlR4ZWelZ0VTZZ+VWoZ1oVB+izpV2yPuvhKbKP9MgGVHiRzV7EIiBk8bIiqYqsCg8pY9RW56W7pyGrPTIyErPiqbKPiu3Cu1Eo/oQda60Q95/JTRV/pkGyYgSP6rZg0AMnDRGVjRVgUXhKX2M2vK0dOc0ZKVHRlZ6VjRV9lm5VWgnGtWHqHOlHfL+K6Gp8s80SEaU+FHNHgRi4KQxsqKpCiwKT+lj1JanpTunISs9MrLSs6Kpss/KrUI70ag+RJ0r7ZD3XwlNlX+mQTKixI9q9iAQAydFsbp6zHR5+M3Z8tBpu0v9Ghs7rZKmygkXLBilLdiCM0xMVnp4ZKVnFaOpmrPkO/nNra/I77q2lFP22sptsRmjqS09QBQr1LlSTya+SJqqjHs2ZMgQGTp06FpZGjduLHPnzk3/3urVq9N/ftttt8nixYulc+fOctNNN8l2223nNDNK/Khmd4JjJBjFqswYDejeWv7Wa1snGmtM1Q5N5KZjOjqNzRKMYpWlZuRY8tLTJyuy0hNwi0Ro64hbJsgbMxanhX52WW+ngs98YIo89ObsosY6TbSOYASrrDWjxqNYoc6VKM55zEtTlZFyYqr+/e9/y7PPPrsmU7Vq1aRhw4bp/7788stl2LBhMnLkSGnbtq1cfPHF8uKLL8oHH3wgNWvWVM+OEj+q2dVgDAWiWJUZo5P22FLOO6i9ExGaKidcsGCUtmALzjAxWenhkZWeVRKJ4JXFVP3hn2/KY1Pn0FS5bXPu0QhdJYtEnStzB5zjhDRVGWEnpurhhx+WKVOmlMuU3FI1bdpUBg4cKOecc076z5cvXy7JTVZitk455RT17Cjxo5pdDcZQIIoVTZUhEQQqBaWtQMsJmpas9HjJSs+Kpso+K7cK7USj+hB1rrRD3n8lNFUZmSamavjw4VK7dm3ZeOON06/3XXLJJdK6dWv55JNPZKuttpLJkydLhw4d1sx0yCGHSJ06dWTUqFEVzp6Yr+Svsk8i/ubNm8uCBQukVq1aGavWD0+afcyYMdKjRw/ZcMMN9QP/ByNRrLYe/ExK+8TdW8q5B7ZzIl829sDtGsv1R+3kNDZLMIpVlpqRY8lLT5+syEpPwC0Soa2jbp8ok2YuSQv98KKeTgUPfPAtefztkkcRXMc6TbSOYASrrDWjxqNYJefKBg0ayNKlS3M9V6I45zEvTVVGyk8++aQsW7Ys/WrfvHnz0q/3TZs2Td599930K37dunWT2bNnpzdWZZ8BAwbIjBkz5Omnn65w9nU9q5UEjx49WqpXr56xag7/JRH40ysbpMvZu8kqObTVKqellY3duf4q6dfWbazTRAwmARIgARJwJnDtO9Xk06+rpOOu67rSafyo6VVl8sKqRY11mojBURJIzq59+/alqfK4ezRVHmEmqb799tv0durss8+WLl26pKZqzpw50qRJkzUznXzyyTJr1ix56qmnKpydN1WeNyaHdKj/2sSbqhw2FzwFSlvgZRc1PVnpsZGVnlUSieDFmyq3PYoxGqGrhBNvqvyrhabKP9P0q3Jt2rSRQYMGFf31v5+XhfruK+q7vgG2JXhKFCs+UxV8a+EToLQFX3gRBZCVHhpZ6VmVmaonnnhCevXqldvX4fmiCrc9ijEa1Yeoc2WMe6StmaZKS0oZl9wwJTdVyVf8Bg8enH7t78wzz0xvrpLPihUrpFGjRnxRhZJnTGGoPxhpqmJSSXG1orRVXLXYUWSl509WelY0VfZZuVVoJxrVhzRV/jVAU5WR6VlnnSUHH3ywtGjRQubPn58+UzVu3Dh5++23pWXLlql5uvTSS+Xuu++WrbfeOn2JxdixY/lK9YzcLQ5H/cFYZqr677GlDOYr1S1KI3NNKG1lLhyQgKz00MlKzypGU3XG6Mny37e+SBfp+htXbmTKR1NbeoIoVjRV+j3SRtJUaUlVEHfUUUelvzuVvJUv+W2q5Dmqiy66SNq3L/m9oLIf/x0xYsRaP/67/fbbO82MEj+q2Z3gGAlGsaKpMiKAgGWgtBVwScFSk5UeLVnpWdFU2WflVqGdaFQfos6Vdsj7r4Smyj/TIBlR4kc1exCIgZOiWNFUBd5YA+lR2jKwdOcSyEqPjKz0rGiq7LNyq9BONKoPUedKO+T9V0JT5Z9pkIwo8aOaPQjEwElRrGiqAm+sgfQobRlYunMJZKVHRlZ6VjRV9lm5VWgnGtWHqHOlHfL+K6Gp8s80SEaU+FHNHgRi4KQoVjRVgTfWQHqUtgws3bkEstIjIys9K5oq+6zcKrQTjepD1LnSDnn/ldBU+WcaJCNK/KhmDwIxcFIUK5qqwBtrID1KWwaW7lwCWemRkZWeFU2VfVZuFdqJRvUh6lxph7z/Smiq/DMNkhElflSzB4EYOCmKFU1V4I01kB6lLQNLdy6BrPTIyErPiqbKPiu3Cu1Eo/oQda60Q95/JTRV/pkGyYgSP6rZg0AMnBTFiqYq8MYaSI/SloGlO5dAVnpkZKVnRVNln5VbhXaiUX2IOlfaIe+/Epoq/0yDZESJH9XsQSAGTopi5cVU7dhEburbMTChn9KjWOW2QM8TkZceKFmRlZ6AWyRCW0fcMkHemLE4LdT1t6b4O1Vu+4uKRugqWSvqXIninMe8NFV5UPYwB0r8qGb3gCz3FChWNFW5b3XuE6K0lftCPUxIVnqIZKVnlUQieNFUue1RjNEIXdFUhVEKTVUYrt6z0lR5R+o9IeoPRpoq71tpLiFKW+ZAKAoiKwWk0hCy0rOiqbLPyq1CO9GoPkSdK+2Q918JTZV/pkEyosSPavYgEAMnRbGiqQq8sQbSo7RlYOnOJZCVHhlZ6VnRVNln5VahnWhUH6LOlXbI+6+Epso/0yAZUeJHNXsQiIGToljRVAXeWAPpUdoysHTnEshKj4ys9KxoquyzcqvQTjSqD1HnSjvk/VdCU+WfaZCMKPGjmj0IxMBJUaxoqgJvrIH0KG0ZWLpzCWSlR0ZWelY0VfZZuVVoJxrVh6hzpR3y/iuhqfLPNEhGlPhRzR4EYuCkKFY0VYE31kB6lLYMLN25BLLSIyMrPSuaKvus3Cq0E43qQ9S50g55/5XQVPlnGiQjSvyoZg8CMXBSFCuaqsAbayA9SlsGlu5cAlnpkZGVnhVNlX1WbhXaiUb1IepcaYe8/0poqvwzDZIRJX5UsweBGDgpihVNVeCNNZAepS0DS3cugaz0yMhKz4qmyj4rtwrtRKP6EHWutEPefyU0Vf6ZBsmIEj+q2YNADJwUxYqmKvDGGkiP0paBpTuXQFZ6ZGSlZ0VTZZ+VW4V2olF9iDpX2iHvvxKaKv9Mg2REiR/V7EEgBk6KYkVTFXhjDaRHacvA0p1LICs9MrLSs6Kpss/KrUI70ag+RJ0r7ZD3XwlNlX+mQTKixI9q9iAQAydFsaKpCryxBtKjtGVg6c4lkJUeGVnpWdFU2WflVqGdaFQfos6Vdsj7r4Smyj/TIBlR4kc1exCIgZOiWNFUBd5YA+lR2jKwdOcSyEqPjKz0rGiq7LNyq9BONKoPUedKO+T9V0JT5Z9pkIwo8aOaPQjEwElRrMpM1YndtpTzD27vtMqysb13bCI39e3oNDZLMIpVlpqRY8lLT5+syEpPwC0Soa0jbpkgb8xYnBb62WW9nQo+ffRkefytL4oa6zTROoIRrLLWjBqPYoU6V6I45zEvTVUelD3MgRI/qtk9IMs9BYoVTVXuW537hCht5b5QDxOSlR4iWelZJZEIXjRVbnsUYzRCVwkn1Lkyxj3S1kxTpSUFjkOJH9XsYNxFTY9ixa//FbVdUQ1CaSsqSKXFkpV+18hKz4qmyj4rtwrtRKP6EHWutEPefyU0Vf6ZBsmIEj+q2YNADJwUxYqmKvDGGkiP0paBpTuXQP946HUAACAASURBVFZ6ZGSlZ0VTZZ+VW4V2olF9iDpX2iHvvxKaKv9Mg2REiR/V7EEgBk6KYkVTFXhjDaRHacvA0p1LICs9MrLSs6Kpss/KrUI70ag+RJ0r7ZD3XwlNlX+mQTKixI9q9iAQAydFseIzVYE31kB6lLYMLN25BLLSIyMrPSuaKvus3Cq0E43qQ9S50g55/5XQVPlnGiQjSvyoZg8CMXBSFCuaqsAbayA9SlsGlu5cAlnpkZGVnhVNlX1WbhXaiUb1IepcaYe8/0poqvwzDZIRJX5UsweBGDgpihVNVeCNNZAepS0DS3cugaz0yMhKz4qmyj4rtwrtRKP6EHWutEPefyU0Vf6ZBsmIEj+q2YNADJwUxYqmKvDGGkiP0paBpTuXQFZ6ZGSlZ0VTZZ+VW4V2olF9iDpX2iHvvxKaKv9Mg2REiR/V7EEgBk6KYkVTFXhjDaRHacvA0p1LICs9MrLSs6Kpss/KrUI70ag+RJ0r7ZD3XwlNlX+mQTKixI9q9iAQAydFsaKpCryxBtKjtGVg6c4lkJUeGVnpWdFU2WflVqGdaFQfos6Vdsj7r4Smyj/TIBlR4kc1exCIgZOiWNFUBd5YA+lR2jKwdOcSyEqPjKz0rGiq7LNyq9BONKoPUedKO+T9V0JT5Z9pkIwo8aOaPQjEwElRrGiqAm+sgfQobRlYunMJZKVHRlZ6VjRV9lm5VWgnGtWHqHOlHfL+K6Gp8s80SEaU+FHNHgRi4KQoVjRVgTfWQHqUtgws3bkEstIjIys9K5oq+6zcKrQTjepD1LnSDnn/ldBU+WcaJCNK/KhmDwIxcFIUK5qqwBtrID1KWwaW7lwCWemRkZWeFU2VfVZuFdqJRvUh6lxph7z/Smiq/DMNkhElflSzB4EYOCmKFU1V4I01kB6lLQNLdy6BrPTIyErPiqbKPiu3Cu1Eo/oQda60Q95/JTRV/pkGyYgSP6rZg0AMnBTFiqYq8MYaSI/SloGlO5dAVnpkZKVnRVNln5VbhXaiUX2IOlfaIe+/Epoq/0yDZESJH9XsQSAGTopiRVMVeGMNpEdpy8DSnUsgKz0ystKzoqmyz8qtQjvRqD5EnSvtkPdfCU2Vf6ZBMqLEj2r2IBADJ0WxoqkKvLEG0qO0ZWDpziWQlR4ZWelZ0VTZZ+VWoZ1oVB+izpV2yPuvhKbKP9MgGVHiRzV7EIiBk6JY0VQF3lgD6VHaMrB05xLISo+MrPSsojRV/5gsj7/9RbrIzy7r7bbYjNHUlh4gihXqXKknE18kTVUke4YSP6rZI9mWtcpEsaKpilEtbjWjtOVWpY1ostLvA1npWdFU2WflVqGdaFQfos6Vdsj7r4Smyj/TIBlR4kc1exCIgZOiWNFUBd5YA+lR2jKwdOcSyEqPjKz0rGiq7LNyq9BONKoPUedKO+T9V0JT5Z9pkIwo8aOaPQjEwElRrGiqAm+sgfQobRlYunMJZKVHRlZ6VjRV9lm5VWgnGtWHqHOlHfL+K6Gp8s80SEaU+FHNHgRi4KQoVjRVgTfWQHqUtgws3bkEstIjIys9qyhN1ejJ8vhbfKbKbZfzj0b1IepcmT/h/GakqcqPdaaZUOJHNXsmWKDBKFY0VaANz3FalLZyXKK3qchKj5Ks9KxoquyzcqvQTjSqD1HnSjvk/VdCU+WfaYUZb775Zhk+fLh88cUXst1228m1114re+65p6oClPhRza6CYiwIxYqmypgQApSD0laApQRPSVZ6xGSlZ0VTZZ+VW4V2olF9iDpX2iHvvxKaKv9M15nxgQcekOOOO04SY9WtWzcZMWKE3HHHHfLee+9JixYtKq0CJX5Us1cKxGAAilWZqerXrZVccPB2TmTKxvbesYnc1Lej09gswShWWWpGjiUvPX2yIis9AbdIhLaOuGWCvDFjcVqo62vRT+cr1d02GBSN0FWyVNS5EoQ5l2lpqnLBLNK5c2fp2LGj3HLLLWtm3HbbbaVPnz5y6aWXVloFSvyoZq8UiMEAFCuaKoNi8FwSSluel5FLOrLSYyYrPaskEsGLpsptj2KMRuiKpiqMUmiqwnBdK+uKFSukevXq8q9//UsOPfTQNf/sT3/6k0yZMkXGjRtXaRU0VZUiggeg/mCkqYJvffACUNoKvrAAE5CVHipZ6VnRVNln5VahnWhUH6LOlXbI+6+Epso/03IZ58yZI1tssYWMHz9edt999zX//JJLLpFRo0bJBx98UG7M8uXLJfmr7JOIv3nz5rJgwQKpVatWDlWXTJE0+5gxY6RHjx6y4YYb5jZvjBOhWG09+JkU1/FdW8h5vbZxQlc2ttf2jeW63+7kNDZLMIpVlpqRY8lLT5+syEpPwC0Soa2jbp8ok2YuSQv98KKeTgX/8f6p8uS784oa6zTROoIRrLLWjBqPYpWcKxs0aCBLly7N9VyJ4pzHvDRVOVAuM1UTJkyQrl27rplx2LBhcu+998q0adPKVTFkyBAZOnRoub8/evTo9NaLHxIoI/CnVzZI/9+9Nl8lh225yglM2dgO9VfJCW3dxjpNxGASIAESIAFnAte+U00+/bpKOu66riudxt89vapMWVi1qLFOEzE4SgLLli2Tvn370lR53D2aKo8wK0pVzNf/eFOVw8Z4ngL1X5t4U+V5Iw2mQ2nLIIpKSyKrShGtCSArPaskEsGLN1VuexRjNEJXCSfeVPlXC02Vf6brzJi8qGKXXXZJ3/5X9mnfvr0ccsghfFFFTnsQehrU96L5TFXoncXnR2kLv3L3CshKz4ys9KzKTNUTTzwhvXr1yu3r8HxRhdsexRiN6kM+U+VfLTRV/pmuM2PZK9VvvfXW9CuAt912m9x+++3y7rvvSsuWLSutAiV+VLNXCsRgAIoVTZVBMXguCaUtz8vIJR1Z6TGTlZ4VTZV9Vm4V2olG9SHqXGmHvP9KaKr8M60wY3JLdcUVV6Q//rv99tvLNddcI927d1dVgBI/qtlVUIwFoVjRVBkTQoByUNoKsJTgKclKj5is9KxoquyzcqvQTjSqD1HnSjvk/VdCU+WfaZCMKPGjmj0IxMBJUaxoqgJvrIH0KG0ZWLpzCWSlR0ZWelY0VfZZuVVoJxrVh6hzpR3y/iuhqfLPNEhGlPhRzR4EYuCkKFY0VYE31kB6lLYMLN25BLLSIyMrPSuaKvus3Cq0E43qQ9S50g55/5XQVPlnGiQjSvyoZg8CMXBSFCuaqsAbayA9SlsGlu5cAlnpkZGVnhVNlX1WbhXaiUb1IepcaYe8/0poqvwzDZIRJX5UsweBGDgpihVNVeCNNZAepS0DS3cugaz0yMhKz4qmyj4rtwrtRKP6EHWutEPefyU0Vf6ZBsmIEj+q2YNADJwUxYqmKvDGGkiP0paBpTuXQFZ6ZGSlZ0VTZZ+VW4V2olF9iDpX2iHvvxKaKv9Mg2REiR/V7EEgBk6KYkVTFXhjDaRHacvA0p1LICs9MrLSs4rRVJ32j0nyxNtz00V+dllvt8VmjKa29ABRrFDnSj2Z+CJpqiLZM5T4Uc0eybasVSaKFU1VjGpxqxmlLbcqbUSTlX4fyErPiqbKPiu3Cu1Eo/oQda60Q95/JTRV/pkGyYgSP6rZg0AMnBTFiqYq8MYaSI/SloGlO5dAVnpkZKVnFaOpOv0fk+Xxt79IF8mbKre9zjMa1Yeoc2WebPOei6Yqb+JFzocSP6rZi8QEHYZiRVMF3fZcJkdpK5fFeZ6ErPRAyUrPiqbKPiu3Cu1Eo/oQda60Q95/JTRV/pkGyYgSP6rZg0AMnBTFiqYq8MYaSI/SloGlO5dAVnpkZKVnRVNln5VbhXaiUX2IOlfaIe+/Epoq/0yDZESJH9XsQSAGTopiRVMVeGMNpEdpy8DSnUsgKz0ystKzoqmyz8qtQjvRqD5EnSvtkPdfCU2Vf6ZBMqLEj2r2IBADJ0WxoqkKvLEG0qO0ZWDpziWQlR4ZWelZ0VTZZ+VWoZ1oVB+izpV2yPuvhKbKP9MgGVHiRzV7EIiBk6JYlZmqE3ZvJUN+vZ3TKsvG9t6xidzUt6PT2CzBKFZZakaOJS89fbIiKz0Bt0iEto64ZYK8MWNxWqjryyb4SnW3/UVFI3SVrBV1rkRxzmNemqo8KHuYAyV+VLN7QJZ7ChQrmqrctzr3CVHayn2hHiYkKz1EstKzSiIRvGiq3PYoxmiErmiqwiiFpioMV+9Zaaq8I/WeEPUHI7/+530rzSVEacscCEVBZKWAVBpCVnpWNFX2WblVaCca1Yeoc6Ud8v4roanyzzRIRpT4Uc0eBGLgpChWXkzVDk3kpmP49b/AEik6PUpbRRcMHEhWevhkpWdFU2WflVuFdqJRfYg6V9oh778Smir/TINkRIkf1exBIAZOimJFUxV4Yw2kR2nLwNKdSyArPTKy0rOiqbLPyq1CO9GoPkSdK+2Q91+JWVN1/fXXO6+2X79+UrNmTedxMQxAiR/V7DHsyc9rRLGiqYpRLW41o7TlVqWNaLLS7wNZ6VnRVNln5VahnWhUH6LOlXbI+6/ErKmqWrWqNGvWTKpVq6Za9axZs2T69OnSunVrVXxsQSjxo5o9tv1B/Qs3mZemKka1uNXMPtTzIiuy0hNwi0Roiy+qcNujGKMRuko4oc6VMe6RtmbTpmru3LnSqFEj1VqSG6qpU6fSVKlo6YNQza6v0E4kipWXt//xmSo7QlpHJShtmYZSQXFkpd81stKzQv2HM5oqtz2KMRrVhzRV/tVi1lQNHTpUBg0aJNWrV1et+tJLL5Xf//73UqdOHVV8bEEo8aOaPbb9Qf0Lt/CmKtPvVNFUmZYc+1C/PWRFVnoCbpEIbdFUue1RjNEIXfGmKoxSzJqqMMuNNytNlf29Q/3ByJsq+9rIWiFKW1nrRownKz11stKzQv2HM5oqtz2KMRrVh6hzZYx7pK05SlO1YsUKSf6qUaOGdp3Rx6HEj2r2GDcMxapYU7V69WrZ8twnUtS9eVNlWnIobZmGUkFxZKXfNbLSs6Kpss/KrUI70ag+RJ0r7ZD3X4l5U3X33XfL5MmTpUuXLnLMMcfIueeeK1dffbWsXLlS9t13X7n//vulfv36/skYy4gSP6rZjeFXlYNiRVOl2p6og1DaihEaWel3jaz0rGiq7LNyq9BONKoPUedKO+T9V2LaVA0bNkySv3bffXd588035cgjj5SHH35YBg4cKMnbAZPXrh900EFyyy23+CdjLCNK/KhmN4ZfVQ6KVbGmatWq1dL6b7ypUm0uOAilLfCyi5qerPTYyErPiqbKPiu3Cu1Eo/oQda60Q95/JaZN1dZbby0XXnihHH300fLGG29I586d5YEHHpAjjjgiJfHkk0/KqaeeKjNmzPBPxlhGlPhRzW4Mv6ocFCuaKtX2RB2E0laM0MhKv2tkpWdFU2WflVuFdqJRfYg6V9oh778S06Zq4403lo8++kiaN2+erjz532+99Za0a9cu/d+zZ8+WLbfcMn2+6pf+QYkf1ewx7ieKVbGm6sdVq2Ur3lRFITWUtqKA87MiyUq/a2SlZ0VTZZ+VW4V2olF9iDpX2iHvvxLTpir5il/hb1X9/Leo5s2bJ02bNpUff/zRPxljGVHiRzW7MfyqclCsaKpU2xN1EEpbMUIjK/2ukZWeFU2VfVZuFdqJRvUh6lxph7z/Ssybqueff17q1auXrjx5turBBx+UZs2apf97wYIF0qNHD5oq/7pYkxHV7AGXFCw1glXhG/xcf6dq5Y+rpM3fn0x58O1/wWThJTFCW14KByQhKz10stKzoqmyz8qtQjvRqD6kqfKvAfOmqkqVKpIcHH/+Kfv7yf/lTZV/YZRlRDV7uBWFy4xgRVMVbj8tZUZoy9L6XWohKz0tstKzoqmyz8qtQjvRqD6kqfKvAdOmSvsCipYtW/onYywjSvyoZjeGX1UOglXhG/xcb6p++HGVbM2bKtXeooMQ2kKvudj5yUpPjqz0rGiq7LNyq9BONKoPUedKO+T9V2LaVPlfbrwZUeJHNXuMO4VgRVMVo1Lca0Zoy71KGyPISr8PZKVnRVNln5VbhXaiUX2IOlfaIe+/ErOmKnnLn/az4447akOjjUOJH9XsMW4UglXhG/xcb6pWrFwlbc/jM1UxaA2hrRi4rKtGstLvHFnpWdFU2WflVqGdaFQfos6Vdsj7r8SsqUre/Ff43NT6ls5nqvwLoywjqtnDrShcZgQrmqpw+2kpM0JbltbvUgtZ6WmRlZ5VjKbq9/dNkiffmZsu8rPLerstNmM0taUHiGJFU6XfI22kWVNV+DzVm2++KWeddZYMGjRIunbtmq7tlVdekauuukquuOIK6dOnj3a90cahxI9q9hg3CsGq8A1+rjdVy1f+KO3OeypFzbf/2VYcQlu2iVRcHVnpd46s9KxoquyzcqvQTjSqD1HnSjvk/Vdi1lQVLrVTp04yZMgQ6dWr11oEnnjiCRk8eLBMmjTJPxljGVHiRzW7MfyqchCsaKpUWxN9EEJbsUIjK/3OkZWeFU2VfVZuFdqJRvUh6lxph7z/SqIwVZtuuqlMnjxZtt1227UIvP/++9KxY0f57rvv/JMxlhElflSzG8OvKgfBqvANfq43Vd//8KNsM5g3VarNBQchtAVectHTk5UeHVnpWdFU2WflVqGdaFQfos6Vdsj7ryQKU5UYp8RQ3XnnnbLJJpukFJYvXy4nnniiJMYqMVy/9A9K/Khmj3E/EaxoqmJUinvNCG25V2ljBFnp94Gs9KxoquyzcqvQTjSqD1HnSjvk/VcShamaOHGiHHzwwbJq1SrZaaedUgpTp05NX2Tx3//+V5KvB/7SPyjxo5o9xv1EsCp8gx9vqmJUja5mhLZ0ldmLIiv9npCVnhVNlX1WbhXaiUb1IepcaYe8/0qiMFXJspctWyb33XefTJs2TVavXi3t27eXvn37ymabbeafisGMKPGjmt3gFlRaEoIVTVWl2/KLCEBoK1ZwZKXfObLSs6Kpss/KrUI70ag+RJ0r7ZD3X0k0psr/0uPKiBI/qtnj2p2SahGsCt/g53pT9d2KH2Xb8/lMVQxaQ2grBi7rqpGs9DtHVnpWqD/jj7hlgrwxY3FaqOtr0flKdbf9RUWj+hB1rkRxzmNes6bq0UcflQMPPFA23HBDFYfkTYD77LOPJC+1+CV+UOJHNXuMe4hgVfiyCZqqGFWjqxmhLV1l9qLISr8nZKVnRVNln5VbhXaiUX2IOlfaIe+/ErOmqlq1ajJ37lxp2LChatW1atWSKVOmSOvWrVXxsQWhxI9q9tj2B/Uv3CymatmKldL+/KdT1PydKtuKYx/q94esyEpPwC0SoS3eVLntUYzRCF0lnFDnyhj3SFuzWVNVtWrV9KZq4403Vq0leWFF8rwVTZUKlzoI1ezqAg0FIljRVBkSQMBSENoKuJygqclKj5es9KxQ/+GMpsptj2KMRvUhTZV/tZg1Vf369XNe7fDhw6VBgwbO42IYgBI/qtlj2JOf14hglcVUfbt8pWx3AW+qYtAaQlsxcFlXjWSl3zmy0rOiqbLPyq1CO9GoPkSdK+2Q91+JWVPlf6lhMrZq1UpmzJixVvJzzjlHLrvssjV/b+bMmXL66afL888/nz7zlby18Morr5SNNtpIXRRK/KhmV4MxFIhgVfiyCddnqmiqDImnklIQ2oqHztqVkpV+58hKz4qmyj4rtwrtRKP6EHWutEPefyU0VRmZJqaqf//+cvLJJ6/JVKNGDUn+Sj4//vij7LzzzumzYVdddZUsXLhQjj/+eDnssMPkhhtuUM+OEj+q2dVgDAUiWGUxVd8sXynb86bKkIIqLgWhrSjArKNIstLvHFnpWdFU2WflVqGdaFQfos6Vdsj7r4SmKiPTxFQNHDgw/WtdnyeffFIOOuggmTVrljRt2jQNuf/+++WEE06Q+fPnS/KCDc0HJX5Us2uYWItBsCp82YTrTRVNlTUF0VT52BFEH/qoG5GDrNyoI3jxmSq3PYoxGqGrhBPqXBnjHmlrpqnSkqogLjFVy5cvlxUrVkjz5s3lN7/5jQwaNGjNV/vOP/98eeSRR2Tq1KlrMixevFjq1auXfh0weQ38uj5JzuSvsk8i/iT/ggUL1EYs49LS4UmzjxkzRnr06KF+vb2PeWPMgWCVmKqdLno+xXVclxZyfu9t1Oi+/n6ldBxWMvbA7RrL9UftpB6bNRDBKmvNyPHkpadPVmSlJ+AWidDWUbdPlEkzl6SFTr+wh1SpUkVd9Bn/nCJPvzc/jf/wop7qcT4CEax81I3IgWKVnCuT9xAsXbo013MlgnFec9JUZSR9zTXXSMeOHaVu3boyceJEOffcc+WQQw6RO+64I808YMAA+eyzz+SZZ55Za6bkrYYjR46Uo48+ep0VDBkyRIYOHVrun40ePVqqV6+esWoO/6UQWP6jyNkTN0iX033zVXL4lqvUS/t+pcg5r5eM3bn+KunXVj9WPQkDSYAESIAEiiZw7TvV5NOvS4zUtV1WioOnkrs+qCpTF1VNx17XdWXRNXDgL5PAsmXL0mf8aar87W90pur777+XTTbZxB+BdWSqyNAUhr7++uuy6667lhv9n//8R4444oj0Rql+/fqpqUpeZPH00yVvWSv7JC+puOeee+Soo45a51p4UxV0i4MkR/zXpuRlEztfXOxN1Q/ScdgLKQveVAWRhLekCG15Kz7nRGSlB05WelZJJIJX4U3VB0N7SNWqvKly2zX70QhdJVR4U+VfG1GYqlWrVsmwYcPk1ltvlXnz5sn06dPT36MaPHiwlL0owieaxBAlf63vk8y7LnM3e/Zsadasmbz66qvSuXNnKfbrfz+fG/XdV9R3fX3uZ165EKwKn4tyfabqq+9/kB2HlNyg8sd/81JJcfMgtFVcpfhRZKXfA7LSsyozVU888YT06tUrt6/DFz5T9cklvZxM1e/vmyRPvjM3XeRnl/V2W2zGaGpLDxDFCnWu1JOJLzIKU3XhhRfKqFGjJPm/yVv23nnnndRUPfjgg5J8/e6VV14xQz75EeKDDz44vZ1q0aKFlL2o4vPPP5cmTZqkdT7wwAPpGwD5ogoz2+alEMQfjFlM1dLvfpCdhtJUedn8wEkQ2gq8pGDpyUqPlqz0rCyYqo8v6SXVHG6qaKrc9hcVjepDmir/Ox6FqWrTpo2MGDFC9ttvP6lZs2b60ofEVE2bNk26du0qyYsfEJ/EzCU3UsnLJmrXri3JVwLPPPPM9GuBycspkk/ZK9UbN24syY8TL1q0KH3zX58+ffhKdcSmBZwT8Qfj19//IDuU3ja53lTRVAUUg+fUCG15XkJu6chKj5qs9KxiN1WfXtrL6SUXbmTKR1NbeoIoVjRV+j3SRkZhqpIfzE0MVMuWLdcyVe+995506tRJvvnmG+16vcZNnjxZTjvttLS25BmopL7kGamzzz57rZdJJD/+m8T9/Md/k5dVaD8o8aOaXcvFUhyCVSZTtewH2elC3lRZ0lBFtSC0FQOXddVIVvqdIys9Kwum6qNhB8oG1UpePKH5nHrvJHnq3ZKv/9FUaYhhYlB9iDpXYijnM2sUpiq5+Ul+B+rYY49dy1Qlb8d79tln5aWXXsqHFnAWlPhRzQ5EXfTUCFaFz0U531TRVBW913kPRGgr7zX6mo+s9CTJSs8qdlPl+jyWG5ny0dSWniCKFepcqScTX2QUpuqxxx6T4447Ln1defJcVWKmPvjgg/TteckzTMlvKP3SPyjxo5o9xv1EsMpiqpYsWyE7XzgmRc0XVdhWHEJbtolUXB1Z6XeOrPSsLJiqD4cdKBsWeVNFU+W213lGo/oQda7Mk23ec0VhqhIoySvJL7nkEpk0aZIkbwNMfhsqebNez575/qBd3htUNh9K/KhmR3HOMi+CVeFzUa43VWuZqh2byE19O2ZZvtNYBCunAo0Fk5d+Q8iKrPQE3CIR2ip8+18WU+X6kgs3MuWjEayy1owaj2KFOleiOOcxbzSmKg8YludAiR/V7Jb3oqLaEKyWFnyFz9VULf52hXS4qPSmiqbKtOQQ2jINZD3FkZV+58hKzyqJRPAqNFXTLz5QNtpA/0xV4dv/XJ/HciNDU5WFF0JXSb2oc2UWVtbH0lRZ36HS+lDiRzV7JNuyVpkIVjRVMSrFvWaEttyrtDGCrPT7QFZ6VjRV9lm5VWgnGtWHqHOlHfL+KzFrqurWrat+/WfymvJf+gclflSzx7ifCFaFX+Fzvala9O0K6cibqiikhtBWFGDWUSRZ6XeOrPSsLJiqDy4+QDbeoJq66MKbKtevDqonqSCQ2tITRLFCnSv1ZOKLNGuqkh/7LfssXLhQLr74Ytl///3T36VKPslvRCXPWQ0ePDj9bahf+gclflSzx7ifCFY0VTEqxb1mhLbcq7Qxgqz0+0BWelYxmqrCV6rTVLntdZ7RqD5EnSvzZJv3XGZNVSGIww8/PP2B3TPOOGMtPjfeeGP6SvWHH344b265z4cSP6rZcwfsYUIEq8LnolxvqhZ+s1x2ufjZdOW9+UyVBwWES4HQVrjVhM1MVnq+ZKVnZcFUTbvoANlkQ/1NVaGpcn0ey41M+WhqS08QxQp1rtSTiS8yClNVo0YNmTJlirRp02Ytwh9++KF06NAB9uO/eW43SvyoZs+Tra+5EKxoqnztnu08CG3ZJlJxdWSl3zmy0rOiqbLPyq1CO9GoPkSdK+2Q919JFKaqZcuW6S3VoEGD1iIwfPhwSW6rZsyY4Z+MsYwo8aOa3Rh+VTkIVoXPRbneVC34ZrnsWnZTtUMTuekYvlJdtdGAIIS2AMv0MiVZ6TGSlZ5V7KbK9XksNzLlo6ktPUEUK9S5Uk8mvsgoTNXIkSOlf//+csABB6x5purVV1+Vp556Su644w454YQT4iPvWDFK/Khmd8RjIhzBiqbKxNYHLwKhreCLCjQBWenBkpWeFU2VfVZuFdqJRvUh6lxph7z/QinGZwAAIABJREFUSqIwVcmyX3vtNbn++uvl/fffl9WrV0v79u3lj3/8o3Tu3Nk/FYMZUeJHNbvBLai0JASrwueiXG+qvvx6uew2rOSZql47bC43H7NLpWv0FYBg5at2RB7y0lMnK7LSE3CLRGir8Heq3r/wANl0o+KeqXJ9HsuNTPloBKusNaPGo1ihzpUoznnMG42pygOG5TlQ4kc1u+W9qKg2BCuaqhiV4l4zQlvuVdoYQVb6fSArPaskEsGLpsptj2KMRugq4YQ6V8a4R9qaozBVM2fOXO96WrRooV1vtHEo8aOaPcaNQrAqfC7q+K4tZegh26vRzf/6e+k07Lk0/sDtN5dbjuVNlRpezoEIbeW8RG/TkZUeJVnpWVkwVe9duL9U32gDddGFb//jTZUaW+6BqD5EnStzB5zjhFGYqqpVq673h4B//PHHHJFhpkKJH9XsGMrZZkWwoqnKtmexjEZoKxY2P6+TrPQ7R1Z6VjRV9lm5VWgnGtWHqHOlHfL+K4nCVE2dOnWtlScCfPPNN+Xqq6+WYcOGyWGHHeafjLGMKPGjmt0YflU5CFaFz0X9rmtLudDlpuqr76XTJSU3VQdst7ncehxvqlQbDQhCaAuwTC9TkpUeI1npWVkwVe8O3V8227i4myrX57HcyJSPprb0BFGsUOdKPZn4IqMwVRVhffzxxyV5rfrYsWPjI+9YMUr8qGZ3xGMiHMGKpsrE1gcvAqGt4IsKNAFZ6cGSlZ4VTZV9Vm4V2olG9SHqXGmHvP9KojZVyY//7rzzzvLtt9/6J2MsI0r8qGY3hl9VDoJV4XNRx3VpKRf10T9TNe+r76Vz6U3V/ts1lhHH7apap48gBCsfdaNykJeePFmRlZ6AWyRCW4Uvqnhn6P5So8ibKtfnsdzIlI9GsMpaM2o8ihXqXIninMe8UZiqZOMLP8kr1b/44gsZMmSITJs2TaZMmZIHK+gcKPGjmh0Ku8jJEaxoqorcrMiGIbQVGaI15ZKVfufISs8qiUTwoqly26MYoxG6SjihzpUx7pG25ihM1bpeVJEYq+bNm8v999+/5geBtYuOMQ4lflSzx7hHCFbzC56LOrZLC7m4zw5qdHOXfi9dLi15pqpn+8Zy2+94U6WGl3MgQls5L9HbdGSlR0lWelYWTNXbQ3pKzU02VBdd+PY/1+ex1JNUEEht6QmiWKHOlXoy8UVGYarGjRu3FtnEZDVs2FDatGkjG2ygf2gzvu35qWKU+FHNHuNeIVgVfoXvmM4tZNihNFUxaqeymhHaqqwmq/+crPQ7Q1Z6VrGbKtevDrqRKR9NbekJolihzpV6MvFFRmGqXnzxRdl9993LGaiVK1fKhAkTpHv37vGRd6wYJX5UszviMRGOYJXFVH2x9DvpeunzKbse7RvL7bypMqGjdRWB0JZZGJUURlb6nSMrPSsLpuqtIT2lVpE3VTRVbnudZzSqD1HnyjzZ5j1XFKaqWrVq6TNUjRo1WovPwoUL07/H36kKJxtUs4dbUbjMCFaFX+Hr27mFXOJwU0VTFU4LvjMjtOV7DXnlIys9abLSs4rdVLl+ddCNTPloaktPEMWKpkq/R9rIKExV8nW/efPmpV/5K/xMnz5ddt111/Rhu1/6ByV+VLPHuJ8IVllM1Zwl38nul5XcVP1q28Zyx/F8psqq7hDassqisrrIqjJCP/1zstKzsmCqpl7QU2pvWtwzVTRVbnudZzSqD1HnyjzZ5j2XaVNV9qO+jzzyiBxwwAGy8cYbr+GT3E699dZb0q5dO3nqqafy5pb7fCjxo5o9d8AeJkSwKrxtOrpTC7n0MP0zVTRVHjY9pxQIbeW0NO/TkJUeKVnpWcVuqly/OuhGpnw0taUniGKFOlfqycQXadpU9evXLyU6atQoOfLII2XTTTddQ3ijjTaSVq1aycknnywNGjSIj7xjxSjxo5rdEY+JcASrLKZq9pLvpNuam6pGcsfxu+XGEcEqt8UFmIi89FDJiqz0BNwiEdoqfKX61PN7Su3qxd1U0VS57XWe0QhdJetDnSvzZJv3XKZNVRmMoUOHyllnnSWbbbZZ3nzMzIcSP6rZzYB3KATBqvC26ehOzeXSw3ZUV0xTpUYFD0RoC77oIgsgKz04stKzSiIRvHyZKtevDrqRKR+NYJW1ZtR4FCvUuRLFOY95ozBVeYCwPgdK/Khmt74f66oPwarQVB21W3O57HC9qfp88TLZ4/IX0qXst00jufME3lRZ1R1CW1ZZVFYXWVVG6Kd/TlZ6VhZM1ZTze0id6hupiz7l3jfk6XfnpfE0VWpsuQei+hB1rswdcI4TmjVVHTt2lOeee07q1q0rHTp0kCpVqlSIZfLkyTkiw0yFEj+q2TGUs82KYFV420RTlW3/LI9GaMsyj/XVRlb6nSMrPavoTZXjVwfdyJSPprb0BFGsUOdKPZn4Is2aquQrf4MGDZLq1atL8v+v73PBBRfER96xYpT4Uc3uiMdEOIJVoan67a7N5fIj9DdVsxYtkz2vKLmp2nebRnIXb6pM6GhdRSC0ZRZGJYWRlX7nyErPyoKpenNwD6m7WZE3VTRVbpudYzSqD1HnyhzR5j6VWVOVOwnjE6LEj2p249uxzvIQrAq/wkdTFaNqdDUjtKWrzF4UWen3hKz0rGI3Va5fHXQjUz6a2tITRLFCnSv1ZOKLjMpUrVixQubPny+rVq1ai3SLFi3iI+9YMUr8qGZ3xGMiHMGq0FQduWszueKIndQsCm+q9mnXUO7u10k9NmsgglXWmpHjyUtPn6zISk/ALRKhrcIXVUwe3EPqFXlTRVPlttd5RiN0lawPda7Mk23ec0VhqpIf+e3fv79MmDBhLT6rV69On7VKfrPql/5BiR/V7DHuJ4JVoTGiqYpRNbqaEdrSVWYviqz0e0JWelZJJIKXL1Pl+tVBNzLloxGsstaMGo9ihTpXojjnMW8Upqpbt26ywQYbyF//+ldp0qRJuZdW7LST/r/O5wE1xBwo8aOaPQTD0DkRrApN1W92aSbDf6PvhZkLl0n34SXPVO3drqGM5E1VaIkUnR+hraKLBQ8kK/0GkJWelQVTNem8X0n9Ghuriy58+x9NlRpb7oGoPkSdK3MHnOOEUZiq5PepJk2aJNtss02OaGxNhRI/qtlt0ddVg2BVaKqO2KWZXElTpdusyKIQ2ooM0ZpyyUq/c2SlZxW7qXL96qAbmfLR1JaeIIoV6lypJxNfZBSmarfddpNrrrlG9thjj/gIe6oYJX5Us3vClmsaBKsspmrGwm9lr+FjU0Z7tW0oo07kM1W5CsZhMoS2HMozFUpW+u0gKz0rC6bqjfN+JQ2KvKmiqXLb6zyjUX2IOlfmyTbvuaIwVc8//7ycd955cskll8gOO+wgG2644VqcatWqlTe33OdDiR/V7LkD9jAhglXhV/gO79hMrjpS//U/mioPm55TCoS2clqa92nISo+UrPSsUKbq8FsmyKQZi9NCs5gq168OupEpH01t6QmiWKHOlXoy8UVGYaqqVq2akv35DwDzRRXhBYdq9vAr8z8DglUWU/XZgm9l7ytLbqq6t20o9/Cmyr8oPGVEaMtT6bmnISs9crLSs7Jgql7/+6+kYc3inqmiqXLb6zyjUX1IU+V/l6MwVePGjVvvyvfaay//ZIxlRIkf1ezG8KvKQbAqvG06rOMWcvWRO6tqTYJoqtSo4IEIbcEXXWQBZKUHR1Z6VihTddjN42XyzCVpoVlMlestlxuZ8tHUlp4gihXqXKknE19kFKYqPqz+K0aJH9Xs/gmGz4hgVWiMXE3Vpwu+lX1Kb6r23LqB3Nu/c3hIpTMgWOW2uAATkZceKlmRlZ6AWyRCW4WmauLf95NGNTdRF1349j9XQ6aepIJABKusNaPGo1ihzpUoznnMG4Wpeuutt9bJIvk64CabbCLJj/9uvLH+SjwPsL7nQIkf1ey++eWRD8FqLVPVYQu5+rf6myqaqjxU4WcOhLb8VJ5/FrLSMycrPaskEsHr0JvHy5ulN1WupmrAPW/IM+/NSxdJU+W213lGI3SVrA91rsyTbd5zRWGqkmeqfv48VSGo5MUVv/3tb2XEiBGpyfolflDiRzV7jHuIYFVojA7tsIVcQ1MVo3QqrRmhrUqLMhpAVvqNISs9qxhN1cn3vCFjSk2VqyFzI1M+mtrSE0SxQp0r9WTii4zCVD3yyCNyzjnnyKBBg6RTp06SvKDi9ddfl6uuukouuOACWblyZfrDwImxuvLKK+PbBUXFKPGjml2BxFwIglUWU/XJl9/IvleVPK/Ir/+Zk9NaBSG0ZZtIxdWRlX7nyErPCmWq+tw0XqbMKnmmauLf9pNGtfT/4Zimym1/UdGoPkSdK1Gc85g3ClOVGKmLLrpI9t9//7WYPP300zJ48GCZOHGiPPzww/KXv/xFPv744zy45T4HSvyoZs8dsIcJEawKjVGfnZvKtUd1UK+kcOwebRrIfSfxmSo1vJwDEdrKeYnepiMrPUqy0rOK0VSdNOoNefb9kq//uRoyNzLlo6ktPUEUK9S5Uk8mvsgoTNWmm24qb775pmyzzTZrEZ42bZp06NBBvvvuO/nss8+kffv2smzZMq+7MGzYMHn88cdlypQpstFGG8mSJSX/xajwM3PmTDn99NMl+T2tpNa+ffumN2ZJfNkneYPhn//8Z3n33XeladOmcvbZZ8upp56qrhUlflSzq8EYCkSwymKqPv7yG9mv9KaKpsqQkNZRCkJbtolUXB1Z6XeOrPSsUKbqkJvGy9TSm6rX/rafNHa4qaKpcttfVDSqD1HnShTnPOaNwlQlxmmnnXaS2267bY1RSUR48skny9SpU1PDNX78eDn22GPl008/9cot+XphnTp15PPPP5c777yznKn68ccfZeedd5aGDRumX0dcuHChHH/88XLYYYfJDTfckNaS1LT99tun9Z5yyilpraeddpr885//lMMPP1xVL0r8qGZXQTEWhGBVaIwO2bmpXOdwU1U4tlub+vKPk7rkRhTBKrfFBZiIvPRQyYqs9ATcIhHaymaqXpdn35+fLtLVkLmRKR+NYJW1ZtR4FCvUuRLFOY95ozBVEyZMkF//+teSvLBixx13TF9akbwRMDE0//3vf6VLly5y7733yty5c9PnrkJ8Ro4cKQMHDixnqp588kk56KCDZNasWekNVPK5//775YQTTpD58+dLrVq10ufBHn30UXn//ffXlJbcUiWG8JVXXlGVixI/qtlVUIwFIVhlMVUfzf9GfnV1yTNVNFXGxPSzchDask2k4urISr9zZKVnlUQieB1y48sy9fOlaaGvnrufbF5b/0zVSaNoqtx2GBON0FWyUtS5EkM5n1mjMFUJim+++Ubuu+8+mT59evqiiuSrgMnX7GrWrJkLqYpM1fnnny/JizQSg1T2Wbx4sdSrVy/9OuA+++wj3bt3T7+meN11162Jeeihh+TII49Mv66YvL2wsg9K/Khmr4yHxX+OYFVojH69U1O5/mj9M1WFY3ffqr6MPpk3VRZ1hTrMWWVRWV2IPqysJqv/nKzcdgbBK4up6j/ydXluWslNlashcyNTPhrBKmvNqPEoVqhzJYpzHvNGY6rygLG+OSoyVQMGDEif53rmmWfWGp78blYy5uijj5a2bdumN1d/+9vf1sQkt2/dunWTOXPmSJMmTcpNvXz5ckn+Kvsk4m/evLksWLAgvf3K65M0+5gxY6RHjx4q85dXXRbnQbD6+Mtv5YDrx6c4eu+wuVx75I5qNImpOvCGCWl819b15J5+u6rHZg1EsMpaM3I8eenpkxVZ6Qm4RSK0dditr8rbs79KC33xrO7SxOGm6uR7J8vY6QvSsS8N6i6bOzyP5UamfDSCVdaaUeNRrJJzZYMGDWTp0qW5nitRnPOYNypT9d5770nyUogVK1asxSb5aqDLZ8iQITJ06ND1Dkle2b7rrj8dMtdnqmbMmCHJmwgLP8lLKu655x456qijUlPVr18/Offcc9eEJM9V7bHHHvLFF1/I5ptvXq6WimocPXq0VK9e3WW5jP0FE5i7TOTSqRukK+xYf5Uc33aVerWFY7eutUrO2E4/Vj0JA0mABEiABIomcOVb1WTWt1XS8UM7rpQ6G+tTjXi/qry3pGpRY/WzMDJWAsk3pZJvfNFU+dvBKEzVJ598Ioceeqi8/fbb6fNUydf/kk/ZDwInz1a5fJLbnuSv9X1atWq11g8J5/31P95UueyojVjEf20qvG3qvf3mcu1v9TdVH87/RnqV3lR12bKu3HvibrmBRLDKbXEBJiIvPVSyIis9AbdIhLYOveVVeWdOcTdVJ907WcaV3lS53nK5kSkfjWCVtWbUeBQr3lT53/EoTNXBBx8s1apVk9tvv11at26d/i5V8pa95HepkleX77nnnv7J/CxjZS+qSN4OWPY1vgceeCB9A2Dhiyoee+wxSW7ayj6///3v09e080UVwbcutwkQ34v+cN7X0uOaF9M1HrRjE7mxb0f1egvHdmldT+4f0FU9NmsgglXWmpHjyUtPn6zISk/ALRKhrYNveFnenl3yoooJf91XmtbZVF10v7snygsffFnUWPUkFQQiWGWtGTUexYrPVPnf8ShMVfKdz+SlD8mb/2rXrp2aqnbt2qV/LzFWySvVQ32SrxsuWrQofXvf8OHD5aWXXkqnatOmjdSoUSN9A2HySvXGjRun/zyJTZ6f6tOnT7lXqievU09eq54YqeTtf3yleqhdw+RF/MFYaIx679hEbnIwVdPnfS09Sw0ZTRVGM9pZEdrS1mYtjqz0O0JWelZJJILXQTe8JO+UPlM1/q/7yhYOpuqEuyfKWJoqt00GRCN0lSyTpsr/ZkdhqurWrSuTJk1Kb6m22morueOOO9K36n388ceyww47eP/B30LMiUEaNWpUOfIvvPCC7L333unfT4xX8rtTP//x3+RlFWWf5Md/zzzzzDU//pu8Zp0//utf0MiMiD8YC41RFlPVect68sApvKlC6md9cyO0ZZVFZXWRVWWEfvrnZKVnFbupcjVkbmTKR1NbeoIoVjRV+j3SRkZhqpKv9yU3UsntT/JQXfLK8vPOOy/9MeDEbL3zzjva9UYbhxI/qtlj3CgEq7VM1Q5N5KZj9F//+2Du17L/tSVfHaSpsq04hLZsE6m4OrLS7xxZ6VmhTFXv61+Sd0ufqXr5nH2kWV39i6qOv2uijJte8vU/miq3vc4zGtWHqHNlnmzznisKU5W8We/bb7+Vww47TJKXViQ/tjtt2jSpX7++JM8v7bvvvnlzy30+lPhRzZ47YA8TIlgVGqNeO2wuNx+zi3olhWM7bVlPHuRNlZpd3oEIbeW9Rl/zkZWeJFnpWcVoqn5310R5sdRUuRoyNzLlo6ktPUEUK9S5Uk8mvsgoTNW6sCbPLiVfCyx7A2B86N0qRokf1exudGxEI1hNm/uVHHBtyXN+rqaqcCxNlQ0NVVQFQlu2iVRcHVnpd46s9KxQpqrXdS/Je1+UvP3vpbP3keb19DdVhabKdawbGZqqLLxQfYg6V2ZhZX1stKbKOljf9aHEj2p23/zyyIdgVWiMDtx+c7nlWP1N1VqmqlU9efBUPlOVh06KmQOhrWLqtDCGrPS7QFZ6VjGaquPufE1e+rD0x38dDZkbGZqqLLxQfYg6V2ZhZX2saVN14oknqvjdddddqriYg1DiRzV7jHuFYPX+F1/JgdeV3FS5mqrCsZ1oqkxLDqEt00DWUxxZ6XeOrPSsUKYq+fM9+bM6+bjeNtFUue0vKhrVh6hzJYpzHvOaNlVVq1aVli1bSocOHdb84O+6oDz00EN5sILOgRI/qtmhsIucHMGq0BgdsN3mcutx+puqwrG7taor/zp19yJX7j4Mwcq9SjsjyEu/F2RFVnoCbpEIbdFUue1RjNEIXSWcUOfKGPdIW7NpU5W8pvz++++XFi1aSHJrdeyxx0q9evW0a/tFxaHEj2r2GDcPweq9OV9Jr+tLbqpcTVXhWJoq24pDaMs2kYqrIyv9zpGVnlUSieB1wLUvyrS5X6eFvjhoH2lRX/9MVeFNletYNzLloxGsstaMGo9ihTpXojjnMa9pU5UAWL58ufzf//2fJF/xmzBhgvTu3Vv69+8vPXv2/J95SQXyvyigmj0P8fueA8Gq0Bjtv11jGXHcruplFY7dtWVd+ffveVOlhpdzIEJbOS/R23RkpUdJVnpWMZqqY+94TV7+qOSZKpoqt73OMxrVhzRV/nfZvKkqXPKMGTNk5MiRcs8996T/xei9996TGjVq+KdiMCNK/KhmN7gFlZaEYPXunKXS+/qX09p6tm8st/1Ob6oKx9JUVbq90ACEtqALzjA5WenhkZWelQVTNW7Q3tKy/mbqoo+541UZ/9HCNN51rHqSCgKpLT1BFCvUuVJPJr7IqEzVzJkzU1OV/LVixYr0t6poqsKKDtXsYVcVJjuClS9TtUvLuvIf3lSFEYaHrAhteSgbkoKs9NjJSs+Kpso+K7cK7USj+pCmyr8GzJuqwq//vfzyy+kP//br108OOOAASV5k8b/yQYkf1ewx7iuC1Tuzl8pBN5TcVPVo31hud7ipKhxLU2VbcQht2SZScXVkpd85stKzQpmq/a95UT6YV/JM1diz9pZWDfQ3VX1vf1UmfFxyU+U61o1M+WhqS08QxQp1rtSTiS/StKkqfFFFYqSSF1XUr18/PsoeKkaJH9XsHpDlngLBypep6tiijvzfad1yY4ZgldviAkxEXnqoZEVWegJukQht0VS57VGM0QhdJZxQ58oY90hbs2lTldxEJW/+S16pXqVKlQrXlLzI4pf+QYkf1ewx7ieCVaGp+tW2jeWO4/XPVBWOpamyrTiEtmwTqbg6stLvHFnpWSWRCF49rxkn0+d9kxb6wll7y5YON1VH3/aqvPJJyU2V61g3MuWjEayy1owaj2KFOleiOOcxr2lTdcIJJ6je8Hf33XfnwQo6B0r8qGaHwi5ycgQrX6aqQ4s68hBvqorc+fDDENoKv6owM5CVnitZ6VnRVNln5VahnWhUH6LOlXbI+6/EtKnyv9x4M6LEj2r2GHcKwertz5fKwTeWPFP1q20byR3H76ZGVziWpkqNDRKI0BZkoR4mJSs9RLLSs0KZqh5Xj5MP55fcVD3/l72kdUP9G4+Puu0VefWTRUWNdSNTPpra0hNEsUKdK/Vk4oukqYpkz1DiRzV7JNuyVpkIVoXGaL9tGsmdJxRnqnZuXkcePp3PVFnVHUJbVllUVhdZVUbop39OVnpWMZqq3454RV77lKbKbZfzj0b1IepcmT/h/GakqcqPdaaZUOJHNXsmWKDBCFZvfb5Efn3j+HTFrqaqcCxNFUg0ymkR2lKWZi6MrPRbQlZ6VihT9aurx8lHpTdVz/1lL9nK4aaq0FS5jnUjw5uqLLxQfYg6V2ZhZX0sTZX1HSqtDyV+VLNHsi1rlYlgVWiM9t2mkdzlcFNVOHan5nXkEd5UmZUdQltmYVRSGFnpd46s9KxiNFVHjnhFJpbeVNFUue11ntGoPkSdK/Nkm/dcNFV5Ey9yPpT4Uc1eJCboMASrqbOWyCE3ldxUuZqqwrE0VVDpVDo5QluVFmU0gKz0G0NWelYoU7XfVWPl4y+/TQt99s97SZtG+meqCk2V61g3MuWjqS09QRQr1LlSTya+SJqqSPYMJX5Us0eyLWuViWA1ZdYS6VNqqvZp11Du7tdJjW4tU9Wstjxyxh7qsVkDEayy1owcT156+mRFVnoCbpEIbWUyVbe+IhM/K3mm6tk/d5c2jWq6LThDNIJVhnKhQ1GsUOdKKOzAk9NUBQbsKz1K/Khm98UtzzwIVllMVeHYnWiq8pSK81wIbTkXaWQAWek3gqz0rJJIBK99rxorn6y5qXIzRkfSVLltMCgaoatkqahzJQhzLtPSVOWCOfskKPGjmj07sfwzIFi9OXOxHHrzhHSxe7drKCMdbqoKTdWOzWrLo7ypyl80yhkR2lKWZi6MrPRbQlZ6VjGaqt/cOkFe/2xxusgxZ3aXrRvzpsptx/OJRvUh6lyZD1XMLDRVGO7Os6LEj2p2Z0AGBiBYFZqqvdo2lFEn6r/+VziWpsqAgNZTAkJbtolUXB1Z6XeOrPSsYKbqyrHyyYKSZ6pcjdERt0yQN2bQVLntcv7RqD5EnSvzJ5zfjDRV+bHONBNK/KhmzwQLNBjBavLMxXJY6U1VFlO1wxa15bE/8JkqkHQqnRahrUqLMhpAVvqNISs9q9hN1TNndpe2vKly2/CcolF9iDpX5oQVMg1NFQS7+6Qo8aOa3Z0QfgSCVaGp6t62odzjcFNVOJamCq+f9VWA0JZtIryp8rE/1JUbRQSvfa4cK5+W3lS5GqPDb5kgk0pvqlzHupEpH41glbVm1HgUK9S5EsU5j3lpqvKg7GEOlPhRze4BWe4pEKySf2Em/+JMPllM1fZb1JL//mHP3JghWOW2uAATkZceKlmRlZ6AWyRCW75M1dMDu0u7zflMlduO5xON0FWyMtS5Mh+qmFloqjDcnWdFiR/V7M6ADAxAsCo0VXtu3UDu7d9ZTaJwLE2VGhskEKEtyEI9TEpWeohkpWeVRCJ47T38Bfls4bK0UFdjdNjN42XyzCVFjXUjUz4awSprzajxKFaocyWKcx7z0lTlQdnDHCjxo5rdA7LcUyBYTZqxSA6/5ZV0rVlM1XZNa8njf+RNVe6iUU6I0JayNHNhZKXfErLSs4rdVD01cE/ZZvNabgvOEE1t6eGhWKHOlXoy8UXSVEWyZyjxo5o9km1Zq0wEq2ym6idDRlNlW3EIbdkmUnF1ZKXfObLSs0KZqr2GvyAzSm+qXI3RoTePlzdLb6pcx7qRKR9NbekJolihzpV6MvFF0lRFsmco8aOaPZJtgZuqNz5bJEfcWnJTtUebBnLfSS5f//vJVLVvUkue+BNvqqxHfd8vAAAgAElEQVTqjn2o3xmyIis9AbdIhLaymKo+N42X5PcIk8+Tf9pTtm3Cmyq3Hc8nGqGrZGWoc2U+VDGz0FRhuDvPihI/qtmdARkYgGCVxVQVjqWpMiCg9ZSA0JZtIhVXR1b6nSMrPaskEsGr+xUvyMxFJc9UuRojmiq3/UVFI3RFUxVmt2mqwnD1npWmyjtS7wkRfzC+/tki+U3pTVW3NvXlHyd1Ua+r0FQl/wUz+Rd2Xh8Eq7zWFmIe8tJTJSuy0hNwi0RoK4upOuSm8TK19KbqiT/uKe2b8qbKbcfziUboiqYqzN7SVIXh6j0rTZV3pN4TIv5gzGKqCsfSVHmXg9eECG15XUCOychKD5us9KySSASvPa94XmYt+i4t1NUY0VS57S8qGqErmqowu01TFYar96w0Vd6Rek+I+INx4qeL5MgRJc9U7b5VfRl9sv6mqtBUbbN5TXlqYHfvTCpKiGCV2+ICTEReeqhkRVZ6Am6RCG1lMlU3vixTP1+aLvLxP+4h2zWt7bbgDNEIVhnKhQ5FsUKdK6GwA09OUxUYsK/0KPGjmt0XtzzzIFhlMVWFY2mq8lSK+1wIbblXaWMEWen3gaz0rJJIBK89Ln9ePl9cclPlaowOoaly22BQNEJXyVJR50oQ5lympanKBXP2SVDiRzV7dmL5Z0Cweu2ThfLb215NF9u1dX355wD9TRVNVf4aKXZGhLaKrRU9jqz0O0BWelYxmqpf3/iyvFV6U/XfP+wh22/Bmyq3Hc8nGtWHqHNlPlQxs9BUYbg7z4oSP6rZnQEZGIBg9eonC+WoUlPVpXU9uX9AVzWJQkPGmyo1NkggQluQhXqYlKz0EMlKzwplqrpd9rzMXlJyU+VqjA6+4WV5e3bJ1/9cx7qRKR9NbekJolihzpV6MvFF0lRFsmco8aOaPZJtWatMBCtfpqpd45ry9Jl8psqq7hDassqisrrIqjJCP/1zstKzoqmyz8qtQjvRqD5EnSvtkPdfCU2Vf6ZBMqLEj2r2IBADJ0WweuXjhXL07SVf/+u8ZT154BT9TVWhIaOpCiyOjOkR2spYMmw4WenRk5WeVYym6qAbXpJ3Zn+VLvKxM/aQHZrx639uO55PNKoPUefKfKhiZqGpwnB3nhUlflSzOwMyMADBypepatu4hjxz5l65UUSwym1xASYiLz1UsiIrPQG3SIS2snz9j6bKbX9R0QhdJWtFnStRnPOYl6YqD8oe5kCJH9XsHpDlngLBasLHC6Tv7a+la+20ZT150OGmqtCQ0VTlLhenCRHacirQUDBZ6TeDrPSskkgEr90vfU7mLP0+LdT1tqn39S/Ju3NKbqoePaOb7NisjtuCM0QjWGUoFzoUxQp1roTCDjw5TVVgwL7So8SPanZf3PLMg2C1lqlqVU8ePFX/9b9CU7V1oxoy5s+8qcpTLy5zIbTlUp+lWLLS7wZZ6VnFaKp6XfeSvPcFTZXbLucfjepD1Lkyf8L5zUhTlR/rTDOhxI9q9kywQIMRrCZ8tED63lF6U+VoqgoNGU0VSDTKaRHaUpZmLoys9FtCVnpWKFPV9dLn5IvSmyrX26ZCU/XI6d1kp+a8qXLb8XyiUX2IOlfmQxUzC00VhrvzrCjxo5rdGZCBAQhWhaZqt1Z15V+n7q4mUWiq2jSqIc/ypkrNLu9AhLbyXqOv+chKT5Ks9KxiNFUHXveSvF96U0VT5bbXeUaj+hB1rsyTbd5z0VTlTbzI+VDiRzV7kZigwxCsxn+0QI4pvalyNlUFt1w0VVDpVDo5QluVFmU0gKz0G0NWelYoU9Xlkudk7lclz1S5GqNCU/Xw6d1kZ95UuW14TtGoPkSdK3PCCpmGpmo92IcNGyaPP/64TJkyRTbaaCNZsmRJuegqVaqU+3u33HKLnHrqqWv+/ttvvy1nnHGGTJw4UerVqyennHKKDB48WNY1tqJyUOJHNTukGzJOimBVaKp2bVlX/v17h5uqAlO1VcPN5Lm/7J2RgH44gpW+OnuR5KXfE7IiKz0Bt0iEtrKYqgOufVGmzf06XSRNldte5xmN0FWyPtS5Mk+2ec9FU7Ue4hdccIHUqVNHPv/8c7nzzjsrNFV33323HHDAAWsy1a5dWzbddNP0fyeibdu2reyzzz7y97//XaZPny4nnHCCJLn/8pe/qPcbJX5Us6vBGApEsHr5wwVy7J0lz1S5mqpCQ0ZTZUhI6ygFoS3bRCqujqz0O0dWelZJJIJX50uelXlfLS/KGBWaqodO2106tKjrtuAM0QhWGcqFDkWxQp0robADT05TpQA8cuRIGThwYIWm6qGHHpI+ffqsM1Nya3XuuefKvHnzZOONN05jLrvsMrnhhhtSs6a9rUKJH9Xsim0xF4JgVWiqdmlZV/7jcFNVaKpaN9xMnudNlTlNlRWE0JZZGJUURlb6nSMrPSuaKvus3Cq0E43qQ9S50g55/5XQVCmYVmaqtthiC/n+++9lyy23lP79+8uAAQOkatWqaebf/e53snTpUnnkkUfWzPTmm29Kx44d5ZNPPknHrOuzfPlySf4q+yTib968uSxYsEBq1aqlqNpPSNLsY8aMkR49esiGG27oJ+kvNAuC1csfLZR+oyalRDs0ry0PDuispjv+44VywsiSsa0bVJen/7SHemzWQASrrDUjx5OXnj5ZkZWegFskQlvdrhgn878uOQv8a0Anp+eiet8wQabP/yYd++CATtIh52eqeHbQ6Quhq6Sy5FzZoEGD9Iya57lSRyXOKJoqxb6tz1RdfPHFst9++6Vf93vuuefk/PPPT2+mzjvvvDRzz549pVWrVnLbbbetmWnOnDmSGLEJEyZI167r/l2hIUOGyNChQ8tVN3r0aKlevbqiaob8LxCYtqSK3PJ+tXSprWqsljN3+FG97A+WVJGbS8c22mS1/L2Dfqx6EgaSAAmQAAkUTWDwG9Xkqx9Knt0+c/uV0qqmPtVlU6rJF98VN1Y/CyNjJbBs2TLp27cvTZXHDfyfM1UVmZVCpq+//rrsuuuua/7W+kzVz/fiqquukgsvvDAVaZmpSm6jRowYsSZ09uzZ0qxZM3nllVekS5cu69xO3lR5VHlOqRD/temljxbIiaMmpyvcuXlt+ZfDTVXhLdeW9avLMwN5U5WTVJynQWjLuUgjA8hKvxFkpWeVRCJ47X75WPnymxVpoa63Tb1uGC8fzv+2ZOzJnaRDi3x/p4o3VTp9IXSVVMabKt3+uET9z5mq5OtzyV/r+yQ3S5tssklRpmr8+PGyxx57yNy5c6Vx48ZFf/3v5/WhvvuK+q6vi4itxCJYvTj9S/ndXRNTBMm/MB86rZsax0sffinH3VkytnWDzeT5s/j2PzW8nAMR2sp5id6mIys9SrLSsyozVU888YT06tUrt6/D7zbsWfmy9Ot//3fa7tLR4WUTPa8ZJ9PnlXz9L3neNnnuNq8PtaUnjWKFOlfqycQX+T9nqorZIpebqhtvvFEGDRqUvtQieTFF8qKKv/3tb+mLKpLXsiefyy+/XK6//nq+qKKYzTA8BvEH47jpX8rxpaYq+Q2S5LW52k+hIduywWbyAk2VFl3ucQht5b5ITxOSlR4kWelZoUzVrhc/Kwu+KXmmytUY9bh6nHxY+kzVf37fVXZpWc9twRmiqS09PBQrmir9HmkjaarWQ2rmzJmyaNEiefTRR2X48OHy0ksvpdFt2rSRGjVqyGOPPZbeSCXPRSXPVL3wwgvpa9KTV6Zfd911aWzyNcB27drJvvvum5qrDz/8MP3nybNXfKW6VqZxxCH+YBz7wXw54e7XU0A0VXHopJgqEdoqpk4LY8hKvwtkpWcVu6n696ldZddWNFVuO55PNKoPaar87y9N1XqYJuZn1KhR5SIS87T33nvLU089lb6U4qOPPpJVq1ZJ69at5aSTTpLTTz9dNthggzXjkh//Tf5e8uO/devWTX8YODFV2tepJ4lQ4kc1u3+ph8+IYFVoqnZqXkcecbipKrzlalW/uowdtE94SKUzIFjltrgAE5GXHipZkZWegFskQlu7XjxGFpQ+U+V62/Srq8fJR6U3VTRVbnudZzRCV8hzZZ5s856Lpipv4kXOR1NVJLgchyH+YHzhg/nSr/SmaqdmteWRM/Qvm6CpylEcGadCaCtjybDhZKVHT1Z6VkkkglcWU7XfVWPl4y9LXlTxr1O7ym68qXLb8JyiEbqiqQqzuTRVYbh6z0pT5R2p94SIPxizmKrCW66W9avLON5UedeEr4QIbfmqPe88ZKUnTlZ6VihTtctFY2ThtyVv/3O9baKpcttfVDSqD1HnShTnPOalqcqDsoc5UOJHNbsHZLmnQLB6Ydp86Tey5JmqHZvVlkcdbqpoqnKXSNETIrRVdLHggWSl3wCy0rOK0VTte9VY+aT0purBU7pKpy35TJXbjucTjepD1LkyH6qYWWiqMNydZ0WJH9XszoAMDECwymKqCm+5WtSrLi+ezWeqDMhonSUgtGWVRWV1kVVlhH7652SlZ4UyVR0vGiOLSm+qXL/CR1Pltr+oaFQfos6VKM55zEtTlQdlD3OgxI9qdg/Ick+BYPX8tHly4sg30rXusEVteewP+meqaKpyl0jREyK0VXSx4IFkpd8AstKzitJUXTlWPllQ8kzVAwO6SOfW9d0WnCGa2tLDQ7FCnSv1ZOKLpKmKZM9Q4kc1eyTbslaZCFaZTFXBVweb19tUXjp739ywI1jltrgAE5GXHipZkZWegFskQlsdLnxGFi/7IS3U9St8+9JUuW0wKBqhq2SpqHMlCHMu09JU5YI5+yQo8aOaPTux/DMgWD33/jzpP6rkpmr7LWrJf/+wp3rhhV8dpKlSY4MEIrQFWaiHSclKD5Gs9KySSASvLKZqnyvHyqelN1X3D+giXXhT5bbhOUUjdEVTFWZzaarCcPWelabKO1LvCRF/MBaaqu2a1pLH/6g3VYW3XM3qbiovn8ObKu+i8JQQoS1Ppeeehqz0yMlKzwplqna+8BlZUnpT5foVvr2HvyCfLVyWLpKmym2v84xG9SHqXJkn27znoqnKm3iR86HEj2r2IjFBhyFYPfvePDnpnpKbKpoq6PYHnRyhraALCpicrPRwyUrPKnZT9c+Tu0jXrfhMlduO5xON6kPUuTIfqphZaKow3J1nRYkf1ezOgAwMQLAqNFXtm9SSJ/5U3E3VFnU2lfF/5U2VARmtswSEtqyyqKwusqqM0E//nKz0rFCmaqehz8jS70qeqXK9qdpr+Asyo/SmiqbKba/zjEb1IepcmSfbvOeiqcqbeJHzocSPavYiMUGHIViNeW+enFx6U+Vqqgq/OkhTBZVOpZMjtFVpUUYDyEq/MWSlZ2XBVLl+ha/QVI0+ubPsvlUDtwVniKa29PBQrFDnSj2Z+CJpqiLZM5T4Uc0eybasVSaCVaGp2rZJLXnS4aaKpioelSG0FQ+dtSslK/3OkZWeFcpU7Tjkafnq+5Vpoa6mqvsVL8jMRSXPVNFUue11ntGoPkSdK/Nkm/dcNFV5Ey9yPpT4Uc1eJCboMASrZ96dKwPunZSu29VUFX51kDdVUOlUOjlCW5UWZTSArPQbQ1Z6VhZMletX+NYyVSd1lt3b8KbKbcfziUb1IepcmQ9VzCw0VRjuzrOixI9qdmdABgYgWBWaqm02rylPDeyuJlFoqprW3kQmnLufemzWQASrrDUjx5OXnj5ZkZWegFskQls7DHlavi69qXI1VXte8bzMWvRdusjRNFVum51jNEJXyfJQ58oc0eY+FU1V7siLmxAlflSzF0cJOwrB6ul358oppTdVrqaq8KuDNFVY7VQ2O0JbldVk9Z+TlX5nyErPKolE8Co0Va5f4dvj8ufl88UlpuofJ3WWbrypctvwnKIRuqKpCrO5NFVhuHrPSlPlHan3hIg/GJ96Z66cel/J1/+ymKomtTeRV3hT5V0TvhIitOWr9rzzkJWeOFnpWcFM1QVPy9fLS56pymKq7uvfWfbYml//c9vxfKJRfYg6V+ZDFTMLTRWGu/OsKPGjmt0ZkIEBCFaFpqpd45ry9Jn6r/8VfnWQpsqAgNZTAkJbtolUXB1Z6XeOrPSsTJgqx6/wdbvseZm9pOSmiqbKba/zjEb1IepcmSfbvOeiqcqbeJHzocSPavYiMUGHIVg99c4Xcup9k9N1ZzFVm9faRF79G5+pggqIpsoLfkQfeikckISs3KAjeG1/wdPyTdlNVQZTdW//TrLn1g3dFpwhGsEqQ7nQoShWqHMlFHbgyWmqAgP2lR4lflSz++KWZx4Eq0JT1bZxDXnmzL3USy58HoumSo0NEojQFmShHiYlKz1EstKzSiIRvApNletzUYU3VTRVbnv9/+xdB5QUxRZ9S84557zknHNOBsSIKAiKgAQRDEjOYEBBQRFFCQqIEkSFJee45JxzjpLjhn9u9VZvTW/PTPXM7PTM/qpz/vmyU13h1uvqevXeu8+fte2QK8zPrnOlP7H1d19KqfI34h72Z5fw2/WyewiTrY/ZgVXYvkv03kzNUuWNUpU9XXLa2r+x3/CzAyu/TS4eOlJ4yYOqsFJYySNgraYdslVq8BK6/ySSDdQbpWrG21WpbjFlqbK24v6pbYdcKaUqftZWKVXxg6vPW1VKlc8h9XmDdmyMolJVNFsaWt5H3lIlxmMppcrn4uDTBu2QLZ9OwI+NKazkwVZYyWOFmnbgJSpVVuOiao5ZSRdvP2KTVEqVtbX2Z2075EopVfGzwkqpih9cfd6qUqp8DqnPG7RjY1y87xJ1i7FUFcmWhlZ4qFRlS5ucwgcoS5XPhcJHDdohWz4aut+bUVjJQ66wksfKLqWq5OAl9CDGUmVVqaoxZiVdilGqpr9dleopS5W1BfdTbbveQ7vOlX6C1ZZulFJlC+zWO7VL+O162a0jZP8TdmDlnVIVS3KhlCr75cfVCOyQrcBGxPnoFFbyK6ewkscqEJQqq3FRSqmytr521bbrPbTrXGkXzv7oVylV/kDZB33YJfx2vew+gMzvTdiB1aK9l6j7LC2mqnDW1LTyw/rS8xZJLrKmTU7blKVKGjt/V7RDtvw9R1/1p7CSR1JhJY+VXUpViUFL6OFTLabKqlJVffRKunxHc/+b1rEK1Q/NZm3CXtRWsiUPnl1Y2XWulEcm+GoqpSpI1swu4bfrZQ+SZXEYph1YeaNUifFYSqkKbImzQ7YCGxHno1NYya+cwkoeq0BQqqzGRSmlytr62lXbrvfQrnOlXTj7o1+lVPkDZR/0YZfw2/Wy+wAyvzdhB1b/7r1IPWbtYnMtlDU1rbJgqRKVqixpktP2gSqmyu9CI9mhHbIlObSAq6awkl8ShZU8VnYpVcUHhdGjp1FsoFaVqmqjV9CVO4/Zs1M7VqEGylJlbcH9VNuu99Cuc6WfYLWlG6VU2QK79U7tEn67XnbrCNn/hB1YeaNUifFYSqmyX35cjcAO2QpsRJyPTmElv3IKK3msAkGpsko2oZQqa+trV2273kO7zpV24eyPfpVS5Q+UfdCHXcJv18vuA8j83oQdWP2z5yL1nB1jqcqSmlZ9JB9T5ahUJaPtA5v4DTM7sPLb5OKhI4WXPKgKK4WVPALWatohW6EDw+hxhGapsqpUVR21gq7ejbFUdahCDYqrmCprK+6f2nbIFWZm17nSP6ja04tSquzB3XKvdgm/XS+7ZYAC4AE7sBKVqoJZUtNqC0qVGI+VJY1SqgJAhJwOwQ7ZCmQ8XI1NYSW/cgoreaxQ0w68RKXKKtlElVEr6JpSqqwtsg217ZArpVTFz0IrpSp+cPV5q0qp8jmkPm/Qjo3x7z0X6f0YS5U3SlXm1MloxyBlqfK5UPioQTtky0dD93szCit5yBVW8ljZpVQVGxhGT2IsVd4oVb90qEwNi2e3NmEvaivZkgfPLqzsOlfKIxN8NZVSFSRrZpfw2/WyB8myOAzTDqxEpapA5lS05uMG0tCJ8VhKqZKGzZaKdsiWLRP1QacKK3kQFVbyWAWCUmWVbKLyyBV0/Z7m/qeUKmtr7c/adr2Hdp0r/Ymtv/tSSpW/EfewP7uE366X3UOYbH3MDqwW7r5AvX7fzebtjVKVKXUy2qksVbbKj6vO7ZCtgAXDzcAUVvIrp7CSx8o2pWpAGD2J1GKqvFGqfn6rMjUqoSxV1lbcP7Xteg/tOlf6B1V7elFKlT24W+7VLuG362W3DFAAPGAHVqJSlT9zKlrrwlK14uAVGrRwP419pRzVKpKFxHgsUanacvIGC25+vlyueEPVDqzibTJ+aFjhJQ+ywkphJY+AtZr+kK15O85TwaypqWK+jGxwxUSlKoZsgu/lX75cjmoXzeJ0EpVHLqfr956w35VSZW2t/VnbH3JlNh+7zpX+xNbffSmlyt+Ie9ifXcJv18vuIUy2PmYHVlaUKjHg+fRnzzgoVRlTJaVdg5vS08goKjogjOG4ok89KpItTbxgagdW8TIRPzWq8JIHWmGlsJJHwFrN+JatXWf/o9bfb2KDOjWmJYWEhFDRAYvpaWQ0+9vUGKWqwKeL2L9zZ0hJGz9tKKVUTWlfmRqXVJYqayvun9rxLVfOZmHXudI/qNrTi1Kq7MHdcq92Cb9dL7tlgALgATuw+mvXBfpgjub+ly9TKlr3ifOYKv4hRl0oVWI8Fleq9py7Ra2+28jas5po0soS2IGVlfEFWl2Fl/yKKKwUVvIIWKsZ37Ileg/wSy1RqUJcFBL4Fuy3mA3cXSxspRHL6cZ9zVL1U/vK1EQpVdYW3E+141uulFLlp4UkIqVU+Q9rr3pSSpVX8PnlYTs2RlGpypspJa3/RO7WctegJrT++HWdOTBDqqS0e3BTmrL+JI1cdIjh9eXLZemVynnjBTs7sIqXifipUYWXPNAKK4WVPALWasa3bE3beIqG/nOQDeqzF8tQm6r5qEj/xRQRpVmqoFQVzZaW6nyxmv27aLY0tLxPPaeTqDhiOd1USpW1RbahdnzLlVKq/LeoSqnyH9Ze9aSUKq/g88vDdmyMC3adp95z9rD5uVKqoqOjqfigJXoSSeSz2nv+lk5ywZWq4f8cpF82nmLtfdS0GPVoWDResLMDq3iZiJ8aVXjJA62wUljJI2CtZnzL1piwQzR57Uk2qPcbFaU+TYo5KFWIi8qeLgU9O2EDq+OOYEhUqn5sV4malsphbcJe1I5vrLwYWsA9ahdWdp0rA24BfDggpVT5EMz4bMou4bfrZY9PLOOrbTuwEpWqPBlT0oa+sZaqxxGRdOvBU/YRvnHvMVUauUKf+uL369Cxq3d1pSp9yqS0Z0hT6jd/L80OP8fqvVEtH41qXSZe4LIDq3iZiJ8aVXjJA62wUljJI2CtZnzL1ge/76K/dl9kg3q3TkEa8ExJKtx/MUXGWKqgVKVLmZRe+WGzPvDDI5pTiqSJ6dLth5QlTXJKmjiR/luF4cvovwdP2b+VUmVtrf1ZO77lytlc7DpX+hNbf/ellCp/I+5hf3YJvzcv+9W7j2jmlrPUvkZ+ypwmuYczD57HvMHK01nO33me+vyhWaqMSlW7n7fSxuPXaVnvuizQucU36/Vu5nerSeduPoijVIkf9UbFs9HPHaoQ2ADRDz7wUL58UezAyhfj9raNuTvOU6GsqSlZ4kR073EEVS+UWapJu/CChROHsgwpk1KiRCFSY7W7kl1YeTrvqKhouv3wKWVMnczTJjx+zgpWkIVNJ25Q5jTJ6PaDp3T5ziNqVT63x30H44NW8JKZH3JIfRZ2mNpWy8fY/l6bvJm2nrrJHn2zej4a+UIZB6UKZBPJkyaidj+H682v/6QBuzx7buIGalYqO01uV9lUqZrcrhI1U5YqmWWxXOfKnUc0a+tZ6lirAGVIZf099rVcyU7ArnOl7PiCsZ5SqoJk1ewSfm9e9j5zdtP8XReocNbUtPLD+kGCtOfD9AYrT3sVlSqRCUpM7DuqdWkKzZ6WXhZuN2e9W42u3X2sK1WpkyWmA8ObU+cZ22nZwStsOJXzZ6S579UkTnDhreXq8OU7lC1tCuayYgdWnmLsq+cOXLxNz3yrue3w8k+P2lQmT3q3XdiF1+S1J2hM2GEqmyc9zXq3OqVJnsTtWO2uYBdWnsz71oMn1ObHLXT48l0a8UJpalc9vyfNePyMFaxwuYKximXdxw0oX+ZUHvcfbA+KeN16FEVYv6LZ03o8jfd+20Fh+y+z50Ee1Hz8OiYLKC9WzE1jXy5HhQcspmgtpIqgVOE/352xXe8zrFcdWnnoCo1ddpT9jTME4r/LD1/GFC4UpVR5vExuH+RJlt+qkZ+GtSrttr6xgpX30HLjLh6w61zpyzkEWltKqQq0FXEyHruE35uXvcqoFezgjhLevxFlS5ciSND2bJjeYOVZj0TIafLhn5qliitVEZFRVGHEcrr7KIL9fXirUowZsMPUbXo3CHi+ef8pfRTzLH44OrIFvTN9G60/dp3VK5M7Pf3Ts7auVPF/Oxsr+k0UEmJq0Th+9R41/notwdiBNpOGRNOh8LXUsmVLSprUN9YvTzH013Prj11zuGFGvxNer0DPSeQDs0O2MD5YO7k8VMqfkWa/W52SJYl1L/IXdlb6sQsrK2NE3YdPIunlHzbRgYt32KMtSuegSW9WstqMV/WtYPV7+Fn6dP4+h/7+6l6LyufN4NUYgulh4PXL3MVUqXotennyVgoJIdrYtyHlypAyzjS4y15iFxbeqqNWsJyAKFCqGoxdQ6eu39flYXTrMmwv52XSGxXpaVS0TjCEv8/tWoPCT9+kL5YcYdWypU1OW/s3YnTsolL1w5uVqHlpFVPla3k7e+MB1f1SIw4pmTMdLe5Vx3IXVt5Dy427eMCuc6Uv5xBobSmlKtBWxMl47BJ+qy87PiT8IyJ+ILrVL0yfNC8eJGh7NkyrWHnWi+NTolKVMmli2jmoCd188IRqfbZKr4hg58JZ01D3WTv1v8/Idu4AACAASURBVH3/RkU6c+MBfb7ksP43KL7dZu6k7Wf+Y38rlj0NLetdT1eq8LeVH9ZjbRkLFKpm49cxf//579VkH3SxrDly1UGpwzmjf7kIeuul/x+latmBy9T51x0OuIx5sQy9XjWfW1GwQ7YwqIZj19DJmEMe/i3egrsdtE0V7MLK6nRF+mw86+7Swmr7MvWtYCUyg/K2Z3WqRjWLOE8+KzOGYKqz79xNeu672HgmjB1KTeUCmRymge/gM9+upySJQ+jv7rVNL5oOXrxDLb+NdcmGUlVzzEq6ePsRa6t+aFYa9GxJavTVWr3tEa1KUfKkiemTuXv1v03rWIU2n7hBk9dpBBcoewY3Zf9faeRynTlQKVXxI2lDFu6n6ZvPsMZL505H//bUlCrxLOSuZyvvobu2rPxu17nSyhiDra5SqoJkxewSfisvO3zDZ4efpV86VKFyedIztjlOBYsz9tyuNQm33SgTVx2jQ5fu0revV9CVMDuWAnECRgXA03FYwcrTPvAcApKH/n2AOtQsSBduPXSwNuEmE/Frr06O/fC/XasgFc+Z1uFD/PWr5Vis1B/bz+tDWfJBHfrwjz36zTnPeyXmt+I3cbhlH7xwP2OTQu4TbolCYweHN6NUyRzdxJYeuExdDArF28UiqcPzDejKvadUxXAo+X7Ncfp790VmGYnvWBO4JcLKlzZF/FrMRPp7DvqAliXo3bqF3IqDv2QLMR6Xbj1iLomI9Sk+eAk9iYii4jnSMrekYc+XordqFmDj3Xf+NoEMxXigdDuZeK7gL6ysTgMHX7BslsiZjj363erj9OXSIzq2PFccftt97hblz5Qq3mXfClbjlh+lb1Yec5i2P3IfIX4L8bneuNnJrBXiYmCZbVs1H3WoVdDhEawd3NhXHbpMny444PDbzE7VqJZBsTz/3wOq/blmvdg9uAmLs4FLNmJchz1fmll7RQUK9aBUiXmlqhbMRJ80C3Vw20bMTqEsqWnQwtgx4IJs7ZFrNGe7RjCEsuj92gSl7WNB+frhzYqM0OL38HMEl/D4jnO2Ilsy6+PLb7VMf8Y62AdxMVmtYCbqVEfbszccu05v/rxVr5o2eRLaO7QpU3LxvcPeDhZHd8XXWLnrj/9u17lSdnzBWE8pVUGyanYJv8zLvv/CbZqw6hgtPaDF4qCs+rAeNfxqLft4gPAAfuPPl8vFlCgc1gr115IX/tm1RpwDtT+WBCb7l37YxNwTvY0V4uN1h5WvPgqiS9bYV8o5KFXYwAtmSaXTrPOxdahZgKZtOq1DWyFfBtp19pYD1Lh1HvjXft0ykT1dctr0aSMWKC0WfPxHLz5EP8bcjOLfR6/cpabj1rFqmz6N6w6zcPcFPX6Lt1UiQxSlTJeJdp69RV+8XJZeFXJicUVOtHBevPWQUcIXzJLaJyKCm8RZW8+wA4q7fC++6HDm1jM0YMF+h6Y4bbK79t3JlrvnZX+v/+VqOn3jASHWC+tfdfRKdumBWB/IT6faBalg1tT05/bz7OCPYqZEy/YXH/X8hZWVsSNXEOitURCrCOvk9jM3GdPmO7UL0s8btDQG+4c1I+yniF3yh+XKClYj/j2oj5PP/Zs25eOdrKL66JWMFAMXQS+Uz+0zwpTjV++yixSwo6J8MnePfsmEPY0XrA3mXqdoFrr/OILtV2IBI1+jEtkd/ma2H/I97dMWxalrvcIOHgB4GH2WGryE7j+JZG0hjrFHgyJxrNtwt+TvHup1rltI34v5IMD0B8ILLlf4O5Sqrr9p3gqtyueib9pUsCLCpnVdfdOsyJa7gfSes5sW7LrAyJjmvVdTXzN3z/ny9yX7L1PX3zRPAy4f70zbRisPX2Uu3FCaEfsG18tqo1fqXYM85KOmoS4vBXyJlZU523WutDLGYKurlCoXK3b69GkaMWIErVq1ii5fvky5cuWiN998kwYMGEDJksUyvOzbt4969OhB4eHhlClTJurSpQsNGjTIwQIyb9489rcTJ05Q4cKFadSoUdS6dWtpebFL+GVedjF2ik8IZAQ4SOAA0f+ZEvTi95sItzj7hjWjy7cfUfUx2qZjl0/+9E2nacjfsbd94kdUelEMFTlWLVq0oBsPIylHuhS6DKC/CauOE241Q3M4D2yGwumOZS10YJiebwoJesXbSFilMqVOqgctW5nLxLYVaNSiQ3Qpxv0Et+qrP6zv4NOfJU0y2j6wCYuPgnWKf2B2nv2PrTEKbklL5UpPTyOjaCQ7jGRlsvDJvFiXFbNxiQo2P4Dg8AkXOXy8C/bTlDtQv8uwEP53/wn1+WM3U9ZalMkZp0u4Pk5ac0L/Ow60viZigNL+yg+bmEtPuhRJ6Pq9Jw7jwHoNfq6k22WSeQ/dNuKmgohxl7qFqGmp7PTSpM3Migd6ZyQlxQHh2JV7Di6BOETwg6m3Y8DzuBF+e9o2ypUhBX3xcjnLTXqKFebfc/YuFuv0Y/vKPrWgi5ZcTAgKE2R4w/HrhIuRkYsOMkIBWIshkwtjaLV9sS+5AtAKVn3n7nWwhqDdXOlTsJggXHTAEyF9Kt9ae2Ghqjoq9oDat3lxeq9+4ThTAmHPor2X6JvXK0i9w7BK8YMvxxgyt+rwVX1Pw3+YxUEaO/+ubUX2J+yBsDxj/w4/dVP3FgD7arHsaXUlqlaRzDSzU3Uq2G+RTkCB5xHTWnJwrHdHkWxp2HvXd55jHJvMCzHkuZJ06NIdB08EeDG8N1NTqrgXgqu23H2L9py7xWJw4dbPL8TwDkEBxrcvIiKCFi9e7JO4WdFbAu/Ly5XyyMDg0zogA3lnukYQAmtU6mRJCN9ieONgjd+fvYtZ87OmTa7HkvMBgChqae+6Tsdj5T305aTsOlf6cg6B1pZSqlysyJIlS2jOnDn0+uuvU5EiRWj//v307rvvUrt27Wjs2LHsSQhlsWLFqEGDBkzZOnr0KHXo0IGGDBlCH374IauzefNmqlOnDlPQoEgtWLCABg8eTBs2bKBq1apJyYRdwu/qZccmAypgTultNpHuDQpT5zqFqdzwZexnuCogboeXee/VoEr5Hf3RpQDxshJ3veHN+OLwcvX2ffp3yQpKV6g8fTRvP3WpV4j6tSjBuuAfBbg/4qbNrPy6+TQLNp7xTlWqkE9zkzQr4gfGqFS9UikPI4uAKwh32XIHFRQl42EfzyBGC8xS9ceu0ZtALNThES2o2MAw/W/ATjx8JE+SiH104GbCFVfEAoguK2Zj4smGxcM9GLC+frU8k7NywzQZkmXMEw+BZusr4oh2QXW+yscslfjQ/r1HyztjVl6tnEdKcYjvjy6C43/ZcIp+3aLFBkCOahbJzCyecHfBbTgOFHD/hILwJDJKnw4onfNm8h0DnMgyJ6tAi9h6ihUsoTVjYhGXflDX5eWHu3fK+DsOuGJKA+QTSp08MYtrnNO5Oo1YdJD2X7jDcgnBhXr1kWusCVg0QK2dJ6Pv8PUUq+4zd9KifZecTh1WzIHPur8gkMUOh3pYSuGSygvPp2dsg7/L+N583Mx97K54QD42qgXL7fTGlC208fgN1jTfL+DS/sPa2IsXs7HDgsa/gSCeaVg8G5UaslSvivQVoEvnY8R+CzZcvp/xilv6NdIvG439YN7YA90VvufDTRCXl5xZEM+JShVne3XW3qYT16nLjB005PlSThWY2p+vovP/PXTAa9Bf+9keAjkunCUlhW9YQy8/733crLhXD32uZBz3THe4+OL3tUev0Vu/xFLZw+sG+zsKZAgXkqI3iNgnvqVDny/JCE1wyWgsnu5Z3s7LrnOlt+MO5OeVUmVxdb788kuaNGkSnTypBYXiv/v160dXrlyh5Mm1XEyfffYZTZgwgc6fP88sFa+99hpTvsLCYg+izZs3p4wZM9Ls2bOlRmCX8Btfdtz84wD+y1uVqciA2Pk4m8S/PWuzg1jRgWEscBM3ZGdvPtCrg9q7ZmH/BzqLmetTJE3EFAVPCpLqwjf90dNIavL1WjoX85Hhbe0a1ITFRfCPAm4fV/Spx36GFePG/cdUPIcWY8HrcIII3oboYiG6TuL3ng2LMAsYL81L5aBr9x7TjjP/0Qvlc+mJJF3NDcrEyWsa45RYEAe3oFsteuG7jexGGgQYj55GMbIKMXj6tcp5KWeGFDR+RWy8Beh74VfOPzK4wR21+JBLiLmr34MnEVRysHYoeaZsTsJN8Mlr95g7KYpZDINZw21+3ExbTmo5X2SUKtSDMpguJrYKBy+4z3z1ajnKmT4uu5eMvJQZspTuPtZYGM1KyzI56Ps3HBnfYGHD4RUuJdwix9/DCrUa0sMI8umBH+MSqZyN43ypYh52QQD3TijMcMEUC+QZcu2LAitRySFL9Bv83ztXl87lxfv39ICy4uAV6hRDVY34pq39G/uM6RC3+q2+26hDlCSGEQ633HCXHf7PQVpyQKPWNhbE1vzRpYYv4NXbQLxNlrTJKGOKxA7WBMjev/suMfcw/h7wh9r/Ek7rjmrKnlnxJnXGmRv3Wcxnr0ZFdeIL0aOB98e9HYz9870Te954Cbe2Jfsv6a5wnJn25UmbdJKek6NbMouTSELgbN5g6Ou/QLMmfdI8lDKmSkb9BJZE/O309fsOVqO/e9Si5yduJChYyCEIhYn/zawfxOFBMXdXsBfjQq1usazMzR6WUF4GPlOCRi6K3YPFPdHoxicmDeb1kBIC+yC8UFDEvQ11EOtbY0wsQRLq5EgZTav6NqGUyTXPFU/iuHBuEF3QP2xSjHpKxCm5w8rq78sPXnGgss+fORW7FEmbIgntG9rMwTrpqm0oYG9O2UpFs6dhechQPN2zrM7BWN+uc6W34w7k55VSZXF1Bg4cSLBgbd+umYHbt29Pt2/fpoULF+ot7dq1iypWrMgUr4IFC1K+fPmod+/e7H+8jBs3jsaPH09nzmg3w+6KXcIvvuyUKDEVjVGkkFMFt1LGkjl1MrpxX3NxgokepnqUyiOXm1pDwFxUPzSbu+l79fum49cZKUOvxsV0l54BC/bRzK1n9XZrFMpMv3WqZsnlB8n+8DEd+YKWlwLxSMbCXeH4R1/MJVWk/2LmOsBv+nkdKDCb+jViTUHxem7CBuaKNbxVafZh4rEZZqAA/4dPI+nBk0imjIiMf2b1+7cszly3ev2+2xTjj5uFsmB6fNShfCIOCxTtg4VAabMHZ7xdlbnj8OBpWKF4HhVni4m4r6HPl3L4ONcrlpWmv12Vtp2+Sa/E5NmSjeNoNXED7Tl/m3WHjz4ODpgLLHndGhTWFTdxPHy98De+HrhlxBq/FONyAqUPJCsV82VwS3JitIYZ5444jV/fcbRW83FzPPAMfw97bdYIQMzi1sS2MVckFzYj30DgP1jJUgs5p1yN84PGRZmliiu66AdKAYLvYUVY/H4dKplLuxhwVhBjAndS5CnjBYyQsOKB/IKP849t5xzcRMF+hpgjKFspkyWW2gesHlB429+sOEbjVmi5flBEtjS8d4ireaVyHodLIBz8gbM7pZLLb870KXT3WvSRNHEIu9AZs/gQTYmJqzKbpHgAvvNIs1gYlR787e6jp24JV7grItbw0LAmDkoVLs3m77zA4oeMcvni9xvjxBOJY+WHS1eLBLmEmxzcg0GagH/P2XbOgaqdz1V0oeNtpkqWmLb0b8RIPlIlTUK9GmskAFx+m5bMzlw33RUxvpHLL/bZfRe0/YJfrnz85x76c0csmY9Zu3C1G/bPQfbT+w2LUL7MqR3iXM2eGfxsSRoeE6eFgzkuGqF8cVp04zMgBNl19j/6XnBXNmsXLtw9Zu1iyhrkEpdgzsrhEc3ZGoCcKPz0Dfq3Rx3dfRNKDKeEF2NmRTIV/v1C+6hjtl74bexLpenmwwgavfgwye7dfMxwBX5+4gY9dxf+Dtfkfi01DxAQ5Xy78hg1CM0W74Q5+J6ZfU+hXK39uAEbT9dfd+iXI+JZSFwDUbnlsm51z3In37K/23WulB1fMNZTSpWFVUM8FJSlr776ijp16sSebNq0KRUoUIB+/PFHvaWLFy9S7ty5adOmTVSjRg0WfzVt2jRq27atXmfWrFnUsWNHevw41rVBHAr+Lv4G4c+bNy9dv36d0qVzfYCxMCW3VfGyL1++nMpXr0t/7LpM362JpW01e/iZMjlo0T7txvWjJkWpS12NRan5txvphIk1ZFLb8tS4RPwqVUUHaW5jX75UmllvUPr8uZf+2et4M/zXe9WpVMzhELfxSRPF5lzCQfqzJUfp2bI5qGqBTLTpxA16a1osPfZbNfLR9M2xShrH5o/OValC3gzEx4B4p9GtStGosCO6VeundhWofrGseh08u+XT+oRNecg/B2lWuPZRPzaiKR27eo9aTtBil1wVXITvGdSIrdcP67QgeBQcfHj+KrGf57/bTIdikk6atdu6fE6Cy9JPG05TtYIZaespjXbdWZn6ViWat/MC/RsjC+/VK0iT1mrjqFk4E+07fyeOBeeVSrlp9Aul2AeU0xbDneWf7jVoyYEr1PN3LR9X/xah1LGm+ySpLSdspGNXNQtcy9IIFi5KDb/Wku+2KJWdwgRiFT6P714vRziYofA147/93a0GlciZlkaHHaGpm85Qp9oFqG+zYk4xgPWyzPDYeBBnFZ8rm4O+ermMrqDxfsH+tqJ3bfYY3sNly5bTB1s0pWpim3IsvslZ+WLpUbZWsztVYXGNvOCQUnfsOua+F/5pfUqSOBFje3xhkmNSV7HdQc8Up/bV81H1z9boFybZ0yZnitmFW4/oz85V6fDle4TDPlzYyudNT2/X0hgCEW/z1tTtdDzm3a9VODNB3uFuxefZtW5B+rCJdjieBZfRf2Jv0yETdYtmoV5z9tCQZ0tQ26p5Wb0NxzU2NigpxsL3rCZNmsTJgQZ3JfyveiHN5XjKhtM0dvkx+vHNCjR3xwUHmRj3Shl6tqwWizdw4QGas/0C+2+8h1jbjtN30PYzGmlBqVxpCTIPKwXK92tOsrgzMLVhjNnSJacO03ZQsWxpGGMnJyPga/z18mM0SXhPjXNa1KMGi8vBPlR1zBp2aF7Vu45D/CXyib09Yyd90KgIda/vnFHy1y1nafgiLZXCwcEN2P7OsSozfIV+EMc8UXC4fn/OHlp2UIs3clWODGviMiZ00N8H6fdt56lH/ULUq1ERZhl6fUps/jyOL/5/wa6L9Mn8uBdV9YplobVHNQsM9sm+8/fr/4Z8TevgPtfXhNUn6NtVmlsf1q12kczU4Ov1ujvbqj61KW/GVEzuFu+PJWBC/dRJoql0noy09bS29vjOQYZQ3qmVn+33PWL2KmdYVS2QkcJP/8fWCu/f8kPOsa2cPwPN7lSVKV6NxsUmD4eC819MYl/0g73opYq5mHzIlHUf1WWyyd/DXg0LU48Ghdk7W+uLWBp3yMHcnReoXwzrIWS4H/bg6bHfP9TBOyn+jY+ha5389MP62MtjvietP36dVh++Rp82D9UtwpA1/I/nwltz9Bq9+6vmYsdLmyp5aMTzmpsp9mHsx6LcyMzdkzqIc4Rbv7GA6XhuF+1iTHyPGxXPSisPO7fs8jVrXSEXpUsW4vAeejI+T57BuTJLlizMMODPc6UnYw2WZ/4vlaqhQ4fSsGHDXK7Rtm3bqHLl2BsvKEr16tVj/5syZYr+LJQqWKMmT56s/+3ChQuUJ08eFktVvXp1plRNnz6dxWbxMnPmTHrnnXfo0SMtJ4WxOBsjlLFUqeLHv94VIF/vS0xn7jnmHjKr/2aRSPrtuHaj3LZwJFXLpqWC/3Z/YjpxN/b5Ammi6fS9EOpQNJIqZIlJF2/xrYmKJoqMJkrqIhfpukshNO+0Np6muaPomXzazd2PhxPRgf8cH+xZKoKKpCN6EEE0cldiyp8mmrqU0OqvuBBC/5zV2ulXLoLG7HGkDC+ePooO3447kJ4lI6hIeiJuYTCb4nslIik0fbR+YEadCpmjqEOxKBJx/6ZGBB27HUITD7q/sc+QLJqGVYqk8/eJvtwbO9ZkiaLpSVTsOoyrHsES8prhIY51YPkIuvAghKYedd83nkP/mZOTvubAEvLTMFcUtcofRfAgG7QjMT2IiB1LxcxR9GqhKJp8ODGdEmTl2XyRlDIx0Z+ntL4b5Yqi5/NHsbX/6XAiypeGqGXeuDeyw3cmphuPY9t/q2gkTT/mevyt8kdSw1zRBNnqHaPAcBxAAY+/TxPa4PiZrevVh0SjdjvKiTMRB76ZUxDtuxlCv8RgDBkolzmaMiaLpgJpiUAK9nG41h7esypZnb83XN6Ae58yGpsYmKmWnE/E/ofSu3QEa9eVbKJej5KRVDR9tIMs5k4VTbgEv/oohDoUi6RpBrmArF5+QHHeE7TXpXgklcwYrfeLdX+rmLZ+qy+G0F9nYteoUNpouvOE6HrMOtbNEUX50kSzPQZj+KScNjfZMmxnYrr5OIQ6hUYyrLde07AomDaaHkcSXXwQKy9tCkVSjexx9y/MbevVEJp1Iq4sDaoQQVlSxMW0fdFImnEsMeVNHc3cN/l8QtNHUbeSUbTnRuy6O5sL+sWYpxzR+n2pQCTVyYGUENoTQ3YkpltPtH+grrMi7mXjq0ew54/fJnoYGUJrL4XQsTsaJt1KRFKx9NF04YHjHuIK6xGVIihdLIeTQ1VRfvED1uB+BNFsA4587GHnYmXVWZ/4fojvI9bxg9JxZeKv04noxmOijsWQoJzoj5OJaOMVbZ7tikTStUch+nuBv5XMoO2/044mooO3Yvf1nCmj6aOykYT817wNyOjJmP2qbKYoOno7hB5Fuv9Woh/s/amSRNNX+5zvE/z9MOIH5e6+sH9y2esXnpgeSPT/UZkIypsmVlYx9ndCo2jSwUQO3zKsx+4brvd+1Nn/Xwj9dDjuO1EmYxTtM3xrMdYRu7Q5v1YokmrGvGcTDiQm7JsDK0RS8sREO6+HxNmzxf1i1vFE+jssvq9GecHeFxFNlDiE2Pp7UjZfCaHfTyYmfnbhbUBW+DlBPG+8UTiSZprsEca+cXZ4r6Rzi6InY5V95sGDB+yyXylVsoi5r/d/qVTB2oP/uSqwPqVIod2CQqECEQVIJWBxSpQodpONL/e/QLNUfbg1qZ5zyhlu7arlpQ418+u3aVPaVSC4b7EP9Kzd+m0cbthgEcLN1hcvlibc1PBy+sZ9unLnMQuOFwtuhmFhAbMOXEb6/3WQ3Z6hDGwZSm/VcLRcwE0NN2ETVsda1nB7i5tBlLY/b6Ntpx2tLXy8uEnFjSrK0eFN2C3kzK3n9NvlN6vlpd+2xuYEEceZNCSankbH7tq/vFWR6hTJEsfqIT4Dq0uNQpmo82+ON3K4/Ss/ciXdx2kv5oZ88b7L1OsP1yx6qFsiR1r6u3sN5moEywQv4u1mnSKZ6Ze3tFvd7rN3u7yJPjCkMbtVFq1z7reXuDX4DTWsCdXHrKI7T2OxahCahZIkSmR6a4sb2Hk7NcIHyAvkZsWhq/TeLM1tkd+qiz2KlhXZsb5WOQ+NbFUyzm0tnh/6bHEa+m9ssmT8bdfAhoxtDFa5TSdu0ohWJWjB7kvsBvb1qnmo60xzt0rjeH57uzJN23SGVgg3m2Vzp6O9F+5QtrTJaU3vmjR/8XIauF07iAx9rgS9EWO1MZsbv33GrfKinhoxCnKSDVioyTVK70ZFCBbEYoM1qm+U6R0qMaZC3Lj2blyUENCOuC+UD/7Yq1uhcbN//e5jOnzlHrUql5MW7nEkMMB7U2fsOvYuGwve1zaV81DpGCseX0/U4xYEPndYdpFsWnxX82RIQedvaZdRZuvuylLFcSmTOx3tuxAbowLL5eqj15iVhvctWkRhZdp4QiMxgDXm6xXHafL6WAswnyMsq3M7V9Xnxv/OMaqULwNFRUfTrnOam9lrlXPTyFal2J72997LzAI2bsVxGvJscfYudJsdKz+Y62dLjtDPG2Nv/UXLapXRq+lWDJmBGS58LONXHtc9Dnb2q0trV6/SLxAgL0djWD1R//myOallmezScgyrD6x/sL42KZGN7aP4f1j8wLhX+8vYvQjti1YePr49gxqyPHe9/9irW7rNZNzsb3zfM/7G1517Doj7nZn84vkXyuVk7wIsSryUzJmGuhS4xSx7X644ySwl3hRYOPJlSunSuoT3HO87SpufwmlHDKU76MU5UQR+2zmgAXP9bDRuPZ29qRFIuCr43sGyV2LoClatUJZUtLRX7TjfKlj+lh28ontMmLUJeRO9CVDHLP6SPyt+Q7OmSUawPsF1kq8TLMcNQrMy10t868VSv1gW+qmdxrg4+O+DNHtbrHsm9jRYtpGEVyyT1p5k7yxKu+r5aFDLUOYZAJmEGzPGKha867AiA2Neftt6lob9e5ialszGiGQQC4cCL44vXtJio7APfjRXi6+DFXXkosNuZTh3hhS0/P0aylLlTmCD5Pf/S6XKytrA6gSFqlKlSvTbb79R4sSONzEgqujfvz8jquA0659//jl9++23DkQVd+/eZb7rvIB2O0OGDEFDVPHpdsTquL5NQTA1qIJLDF7CpimSUHw6by/9vk1TRHDwAJvVikNXGF02aLNRwBrE47TAOseTZOK313/cQptP3mDxR6Bs5fE1HE8jEYFZjEibKnnps5fK0olr96j9z+HMDUcs418rT1tP3WC5Y3gBcxOnCud/Q04juOGZlSwpoun6o1hFgSfHdBdbY2wLGC35oK5DLpMTo1vSb1vOOFDBO5NluDf93rkGi0Xh64E2c6RPQWtimMV4MDba6DxjO/twohgZBfE34CvSplt5h8S6iBvoVr8Ic2erO3opXXoYixViyXCIMStQspF3hRew5iHhJo8F4+uP4OyFey5Q5fyZqNn4dSy2TKbwWBeQhIA45dzNByz/CMaEHDSQzder5nWQDbS7Y2BjFnzN1xcUyD+ZHLbFMYDREHFCIBPhsWm9GxdziOcxjnl7/wa0MGy5fruLOKdzNx+y3lPmwQAAIABJREFU4HXIKGIjxMLHI1Ini5TRqAv3wa9eLU+lBaYyMFPyBN3GMQz8ax/9tkVzcUXOOZALIGYN+ayMyhPybyHWwazgPUSMFiceEXPm8PxnyB3HYx7hvgiF3qyYEZC4ik9w9h7yPhDj1LpCbqaA9mlSTE/c2WFquP7ehA9oxGJoEGNhVpBbaOLqWPIY1OEY1SycmbFqQrZQwO6HvEVmBaQQIIfgBe9/+1+26gx1+DtPOYD/FlMtGHFBfA0IZ9A/XC95/qItfetR2PKVNGync0sJZA0kNIjBQmwh4ucQf8bn4Oz9Ao7ILYSC8SA3YN0vtYS4vOA9BtbAATnj7jyKYHKZP3NqWrzvElMajHFozvrD30HtPrVDFdp74TY9VzYnOzhHREbppEogPsG7LK4dDuBwWzUWWDQQA4jvDS81C2Wi17JfZTTh41edoO9Wu2YGdDVW/AYqblwaGHMBguEOKQxQ2tfIz+JpUUTSBsQsgzyBswKeGtOSzVeMDXPVP+KdEatbdqjmHg8ZBTkLWAllmAbFtrG+xuTmUErOCKRUYn2zb+iKPnWp8dexSjfSTUDh5Djw5xG/OKV9ZSqQJTX1mLWT/jV5D92dBxA7i/cA5DsIP5jyVhV9eGL8rpg/ccr6k4zoAyEE2I+4QiuyXooY4PsKxsCO0xzdW41rAsVtdZ86PqOfdydz4u8qpsoKWnJ1lVLlAifu8geiiRkzZjgoVDlyaLe3MJuGhoZSw4YNmXJ17NgxRqkOynROqY7Yqrp167LcVK1atWKkFiC8CBZK9UWLFtPH25LqNzPOIAN7Udk8GRjdNmI3OPMd6n+9/Kh+yGpSMjslS5yIMZzhI//bO9XYBiV+cEGG0L6GFpchUmwjRwkOvqB6Fgs/3OJvSOoobs68HhiR8LHihznjPHC4AYWuWPCxd0epK9Yvki6ajt+JVRRAFoGbfp5jSe611PK/gHaXK0R4bt/QpvTTupP0rcD256w9HEwmt9PcV5FT6tKth4z8AixkOKghIfPPHWI/JJ2mb2dKLgo+SMbDJ/5mpIWWnYtYjxMP4OA7+Y/F9NuZ1Iw+XqT+hWzAGCwGWSM2BTEqYuG50PA3HChQQESBYG4rBzE854wpEcpp7SJZGMmGmdK3uV9DAiMWx0sckxk+SOj569vV9IBwBInP23me3YiKt87GZ+d3rUabN23UXTnbVstHIEpB4Yq7+AwfD6xc4QMas5+ajltLR6/EXgYgJgl5fzr/GhsbYbzMENsUGTNxmD9x9R6Fn45VdGXlAWuJQ+KbP29lj/C8PfhvTiCDgzyUKhC1QAkB+YpZwe12n6ahLCkrCEhAZiEqVdxqDMuHWfJa3ibvo0DmVIT9CYqxGBAP5j68OygLutWkLr/uYNZMqwW377AmcJp9nkbArJ3tp2/SyzHkLPgdl1Y9Z+90UGBFQgnxnTUeKjmpjlHWEbO3YOla+s6FSzGXTXgDDIs53F+984jenr7NVBkxmwvGY7Yv83cKZA8gyOBEEWIbULp53i4ZvLk1Hvs51hDxa/ziAN8O8R1Ae8Z3D94QIGCByxgvYCHddeY/+rl9RTq6fR1TqiatO82+a94UI0kRb0vcg0Gpz1ni8PurkzczUghcgODSpNbnq9gF5MLutdjjYJYTWf+cja9fi+IscTPPGQmr9I5BTVj+Lk+UKiPJDI8bk8XHyGSL53Cx4QxjUNCDOAKXU8YipnnAHoJcmmIB5fvSA1fY3ovCFVL895dLDzsoy7sHN2HeCC9O2kR7z98mXATgQpbT74PsqXNdLXcaZ0DEd2DnoCYEavq2P2n7nLMCeQ3v10ApVbKCEuD1lFLlYoHg6gcyCbOCgz4vSP7bvXt3lvwXNOldu3ZlShVujXiZO3cuU6TACMiT/7744ovS4mHXjQIOKH/9s1iP5XA14OW967Ks4aDlffA0kiUN5QVMXx2majc2sFYggSi/xcTfcCuIeBVecFjAhoqDzJiwwzqNszMrEQ5FSB6LxLqcodBsrJxyVhp4ixUrZYmiHddjXQnGvVaOmpfK6aAcyTZp/NgjySpujJHHxl0RmRdx4ATLIKfnhhUGFivc1PHSafo25k6H4kypgmWi3pdyQdDOxjeqdWl6o1p+h4Nv+Jnb9MaU2A8PLEI4dIvr6MqVBH3tGdyUWk/aaEoN7w4r/I7D+azws3EYKsHAh5QAzhIXg17+wn8PHSwKzvozo4P+atkRB0p8Z89+2LgI/bPtKB2NidsrlzeDfsiHhRWyUiZPevaezN56lr0zKCAmATagh0ZiUXeWuzUf1Wc3wGYFlid+wIGlCbTcMoc3BHJzFkbeLrd+4N9imoEPft/F0gCAIQsulSKNNKjFcZg0lm0DGhMYE1MlT0LILxUVqSUdbdSkGbWYuIkSh4QwZs/anztaSdCOsc0qBTIyCyjeM1jLRrXW3HpqjFmps/aJY+djkc0Jh8sOWDa5QgwWuLdra2Q+xrL/wm16dkIsMYFZHSioqz6qz+izC/WP9YTAgRmXUvgEgQobB0+wr6GI6wHXvER3LtPSCy4CU2M6hpKCSyaxyFrgsTenSJKYnptoPh9cPuEbYWTag5LbsHh2+mVjXFdLmfcaygYYZnmiX7NnjHsL9j8kgf5HyC8HhQXvnKiwT918VsdUZixmdbYPbMwIgMwusfjfRDlEG7iwhNsazw2H7y0uE7i1WtzLXY0LVvU2VfM5pMfAN9voweFubokThdDxUS0I7nEiIzBcQI1kUO7asvK7uwtPKErwrkACc7MiWtixN+PCr2DW1DRk4QE6KNDX4zcxLQaUXDBvcibGuV1rODAP4vuaLmVS9r0FY2Pr710TSwG/Q0Mbs5Q7UNaTJvVtAm1XmNp1rrSyzsFWVylVQbJidgk/PiK//7WYBu2I6x4CBqp6xbLptz2ukoCC6rdMjJsBKLIXC3Tbni4BDrxisj0cJF6smCfOrRRuWHEL6ipfkCdjwC0okqZytzm0ARKFlRdjDyifvViGmpbK4ZIGXezblaUDihI+pmD5MitfvVKOPvxTs+AZbzfdzW/V4Sv09rTthEPln11rmn7kcTuNZJyuSovSORysTsa6GCOoycXDyf5L9xw+PPygKXtgQx9mLovu5iz+Dur4v3dfpCNX7jo8hhw0cCl6/SdzdjxY/Ny5QfEGzZSqP7afY/l5fFFw6AVd9lwDBTQOSks+qKO/f676guIOin2zApcxWHtQ4K645/wtWhXjxuasTWc38UZ3zr+616LyeTMQt5gC97D9lxxkHbmyJq+Nyz4qKjmwIpXOmYYpVWmLVaW3p2uJxp25V+Idnrwutk3ILxK1Iqca3NfGvVae5VsT1x/WdbB/igUHcSgvz3zrWglC7jFYUX+M6fOLl8rSq1U0RkNjgZuymA/OrA4UAtDrN/9mPbPqiQVuSaAgl7Fsy8gfEre3LKOxIfJi5R119a4goTcU9M+XOHoKwBUViu8kN1TirsZvTDjvbq5Yywkrj9FXghWKXxiK+9bs7RdcppZ4sUJumh/j/uiszwPDmrHUBmZKFc8dBwslMJAt787YztwCUX7pUJnt62YFHhRwD+eJpo11jOyCrvo/OrIFzdh82iEP1ru1CzAGUl5g4YHiN2Ozd3FoxnHgm4nLCtFtH3UODW9O36857nBpBddjHoZgbMfdxR2vD7dEeBx8MEeLdzwysjklT2JOgCR6d4guzca+EUe4ZsUypVTJCnkA11NKVQAvjjg0O5WqqfMW02gTFjO4rkRGkR4LghtjuE44K/hQnbpxn3CQQEwCfNvdFdzi8HwZxrpwXcINJj9MIJahdcXccQ4iuCXFDb2YDd1dv8bfoZhVzJ/RIZ8TLARwTQkdtITdHqK8WCCS5sewDeLfcGNETE6tzxyTIuI3s48WCDxAseuscIseYj94oCyvCx9uflvdrnp+Qi4x2QLLK6jMC2ROzW49zT7yomJs1i4wuvc4Uleyzeogj8qzZXM5KFUnbzxi8U+8zOlcnaoVyhxnDK7mglgPY54wM1cfZ20gOfHyQ1fiWELgDgcrBFxGoUAbCy4WkAxbppgpVWKiY5k2XNWBKxVcncxcd5AfxlkuMrFNMfmxsa85285S33laEDYsSdtP/+c0YS3q4KZ2zxCNltsoT0bcOtYqQB81DaVSMfFdGO/aI9ccDqU/vFlRT9gqjk28iAAhAqjQ4bK84GYOnWrb2WWFsU28N7Bu8GSuyOWDm2uebw39mrmW4iAOa1HooDCXbtJIpAyXLZ4Pi78PZutqlkzVWA+WKMiumNSV1wnNnpbFj8JK7W3BgROyYTw8WlGqYJGBW52xYM9b9H4d2nHmZhyrAhSx0rnT0zdO4vOMbZmtjazs87awlqsPX3WIhdn4aUPmeSEqVfN3X9LfB2f7IXI2msX88Po8rtVsv0UcHKzg8L6wUsT4WDOvA7Nvh1n7sNCLFhvUMVpt+HN4z5H7S8yzBUKakYs1unPuDoeYYHGfRmwULoGcJb6WmTfcIJHOoWOMJwx/BhdEUMb5xSusurgUMMY78vq4gHBnyUddWMh6NylKH/25l8rmTk/v1nWevgBJn+uP1bw7YAmDFUu8COZ9b/i4Lu3YsEopVTILHuB1lFIV4AvEh2enUvX9nMU0br+jpQoHAygrCMzkrkb7hzVjvscyxVV8g8zzqAPlrFKBjPT+7F1MEcGhvnXFPCwgm30AUiShZqVysATEUHpKDVniNi4Mz5nF78DCgiR/YowDAqIbFM9GVUet0OMrOHUynwMOPKiDuCZjwa216GKC3xHPwW8ZXeFg5m4kfkCtKlXGvsSPPP8gigHfqA/rDuLNeN6r7g0K0837T126J056oyK1KJPT4XBy+e5TqvOF5poF1yRYLeA6a3ZgM8PMGU7IJ8ZjfsT/NquPBLQbj1/XrY643YZLKdYOZejfB0w/hs76RlwYckGJxUypwu/48Btv6GXfAbEe4r9uP0Ri4rhK+devlqM+f8TGIeLyw2jZQFvHRrVwcAsV24eswi0KBRZYEMeIsS4r+tSjkYsO6oQOnGwF9d0dvl+plIcd/rlL8M9vVWbEJNyigzZgkalpcjlhxGpxz5q0YvU6+tqwZ5lhuqFvAwe3QFi0CmRJpSug2FOuIcFxTL41szZwSD02Sovpq/35Kj02Dgreu3UKEeKxeEEsHPYXrgRN7ViFJS41K7cePKHyw2OZGXkdo0KKPQaWNWNBrNqtB09dXtLIyhkswa9UjmtRM1tX5Bjil0wy7eMy7KNmoazqsgOX6f6TCD1mFtaewtnSsFhJZwX7MhLoosCVFNZamQJLjdm6cgUZMb48zpHHB1uxVMG9Dvshj9vJmyklta6QR48thqJ6ZGQLNlQzpUpmDmZ13ClVuDQw2yOMbTUukV2Ps+W/Odt/ocDApVVUfpFLj+frKpQ1Na36sD773vE9BG3i0gqWYCRCFousGyJ3b8blAuKr0BbP3QXiC7jowUsFFk/sgUv2X9bPK57iCxIehCbIFHiWcNdTvEPVCmamtlO2xImfxZ51LCZWT7n/ySAbuHWUUhW4a+MwMjuVqq9nhdGkQ7Hm7cntKjFlBWXqxlN6Nnn4VSOZqEz5Yslht9nh3bUD68Sb1fPT5LUn2EaJm/pCWdMwNxJ+oIMFhse21f1iNUug6K50q1+YWdG4stCweDZCYCssEjyoF22AdQ2uQvW+XK1/1DsXj6QfhVwdUDzqFs3KYglypEtBtYtm0d2zwOpkdIUwujQ6GyvGZHS9EpUqkTHK3XzNfhc/8ovfr8MYv1CKDQjTlYVZnaoxpTZ0oMb2+GGTYiw5rNlNHO/j85fK0GtV8jkoVbcfR1HlkVogMeIf6sccMs0ObHAngxuaqz7EvrhlpUahzCyODId2sw82WChheeEHIDC8gfmLl/ErjrI4G9mCmECjm6YzpWr3uVv6RcAPb1aiSWuOx4lBkuk3Q6qkjKHNzHJmTPrsLAbIjE2P9y3e3k94vQKBnU6MgQFmoxcdYjFRKPVDs9K0jlXZf+OiANafhqHZHKw+zuYFlra952/pMStQcHFpY2RJM3setPDrNofTzzH5nFxhhz2ryIAwvQpi/vCevjPd3GVKbAvugdhrxr1anr3XKK/8sEmnf4cL7ju1C1GDmJtq/I73G9h/Ol+z+Lly7XocEam/W2K/RvnFRRasGsaCi6/Ltx/FUe5lZAnvC+LmOHMZYgfBUmcsZu+omey76hNWz051Ym/7YRHmmMGCmSt9yjhKI5dfXB7hMoST2DhTMI394wLomTK5qOW36+MMjb8DomsuLJZwXROVKndEFegDSi1nsYSswVUYJCco8FTYNViz5Bpjb1y9h+7Wr8uv2xkJA4qZpeqZMjkZSZS7AmyN3iTiNwvuuLO2nGVu9as/qk/AS3TTnPVOFZa6BAVKDSxK649do3Y/a4yWUIR2D25KKZImYuQaPG0CrI1IwD5dwk0Q1rTFveqw9vi3nl9swMoJF2Xsh/ys8PWyI167w+Kb3r2BlprFXbn94CmVG66xK4ruswt2nXcg2/rj3ap0af8mZalyB2gQ/K6UqiBYJAzRTqVq5IwwloAPft2wzsAHnBeY/Acs0LKMW/kQjFt+VL/VMiOPMPN9BjsR3Jt44fEaIrMV/w2WiT+61nBYXfHAgx9wcMBtu7EgNgvsX9xVBcHv3AWjxKAlOhPZ2o/rM+rfFt+s12/+hlWMoCECPTEOuc+Xz8Vuy3BDXb1wZj1I3Yx2Gi6N7qwWuEGE7so/nHz84gfUeFCxKua4UcTafvt6BQflouzQpYz2GOXfnrWZaw4/WKFPMKKJ1gVjv1BOEWMmHk4iohPpRB6rPqzHFGMUswMbSBegUHH3KWfzwrifLZNTd4fkLJPX7z+mUYsOxWETgyUSdPqgd0Yx+slP23gqDrWvK0zBUmmMA3GmVKEdUO/iMA85E9mqzKymVtfSrD5iAsBkZSyu3uGtJ2/Qaz9qsWXYB8AWyQ+MHLPPw47opAIgHBnzYlmHLoyHR2cKAQ5gIEbh1jUctDb3a+TW4oXOvn+9PG3atkNPQu4KL8y3zJClerwlLozAIoi4FGMxjhXxW2CuFItIcADykw61CjrEUyKGC+8Mv60HtXOpXOlNhyiynooVZG/xrcoJ5I/Th3MlAmQZdx4+pZpFNKXRWMzeUTPZdzUWeBIgXpSXm/ef6JiBEQ5upEb3Rih8neoUpKxpkjMvgBPXNNdcKC5QGNy5umKval46hyl5CX8HRPZFzg4n7lsL9lx2GQ8Jqydcpqds0Eg20O6WkzeoTcw7hEtAMLLyAtcwxMTCugmPBU+LeGFpplTBBfXirYem3z4HWW5YJA6JTq9GRfXvNub329YzbL8y+4av/7gu1YnJS8YvWMS4Q3H+YroOkJMgZYNZLKDxMgjfwilvaSy3vIjfY/43uICC6fDolbuMRp0XM/dtpLvgKQd4PXF+Vr6t4sUIXB0bC+sKAikwOcLLpm+zYpTrzkGlVHkq9AH0nFKqAmgxXA3FLqVq9tbT1G/BATY0sw3sz+3n6OOYQHsrStXYpUd032YjlTkODW9Uz+fgnw23sYypk+kfJH6gx7iMLgX4m5EyHH+DWyCsAihww3m/YVEHyxPHH7daE1cd1w8YIl07dwNDvA6ULVjBcFOKG92CmVNRt0K3KFupGvT92lNxLBW4VSufL4OuVIGKlTNy8b5hMekXc4ttlAfEl4GmFcplrzm74+TJ4bEAKw9fYf7bzoJnvRH56qNX6rgYSQhALoCPtTOfdRAKAHMw0RlzCY1adJC5ZoJamVsWzQ5ssrm6uCzyNkCLDgY4lF6/74qjVOGjC9cRHsRslGUx/whka92x2OSPaBMHSRAt8FtosJnBHUUssBbtG9rMLfxinBXP4+P2IYsVMFb+LoiPunqHRTY6WFiQR0i0GOJZI5lFr8ZFHUZ2495jqhRjlcQPouuWWBGufsgFx+MgzfK2GadsFhPhLk4CY67zxSqW8wsFylz6lElMUzLA8iNauo3WTDzP82zhv+GejJxkoiUMihYUMW4BcsW2iDbM3gFX+dwsioFDdRx8eQ47kWLaVZtm4xNlH5ZnWDhFqwP2L2DAmSONh03RzRgXT+lSJDFVqvq31BLiNvl6rZ430PjeOxu7MUeT2TsApRZ7MdISgLYfRdy3KFFi5so3wUmKC1yQ4VDNLdwYGxgzuXUMKQ2QNsPXBYd1KKHI0wVl2LhGuLBEvC3SFPAcVWZjMLP6wU16yN/aeQBK1fxd53UvDd4G8j7BklMqR2qqMWoZ3Y9KTDM7VWfWKsRHw2MEDIPwCPmkuZajTcxhhlhAvDc8rEAcG745E1Yd0y+/mpfKQT+00xLY88Ip58W/cVd9/E2kOQcBCfZBfobB74iD/jzssMMFrnhGAQZv1dTSvbgr4sXIjLerEtK6iIXn38TfqmSJolm9miv2P3egBvjvSqkK8AXiw7NLqSo+KEzPFwT3rp6NHA9JIs22FaVKPHzA5anrb5pLBOITlvWuxw7nIs02DjAZUyVjilHqZEloTpfq+uFbpGvneCHv0Pg2FRxWV7zBcvXxxQEbMV/cjQrMRogTQAF9LRid4OsPJY8XHBaThETpDD7jVp6I494IZr1i2dPqt/vYvHnyV96O8TAuUs3jBm/Nxw1YVU49LU7QCv6eij0INzjlLoKTcYuMxM6w+CHYHFYqs6SvuAXf0j/2VtZVglY+NrMDG+a4cPcFtzfRxvUV8/mYKVWwbG0+cV1nkDJiufrIVT0QGvnYYE3keUowXgScw0rH3UPhLtV95k4WW8Jdk0B7vqFvQ7fQi/TYUPBBNjB142nKmCyaqhfNQaXzZHAZY8ItGbDOwbLL8yuJHVfIl4ERK4DqXJQxVzIkBl3DwoJEwCK9P55FzAJ/l82Y7XDIQM4gbnGumC8D7TyrXXSggPkRlhxYxcVbbViVZ3eu7tJSBZZGI5mI2d+M74yYLHXdxw0oX+ZU7OCFA7BoIQFmu2LGCqsV8saJaTPQ7i8bTunxITM7VWP07KIc46Yf68Itfu7Iffiz3EoPOUZ+MLMk2YihQm430KdDEXCVRwsXOnvO3WbWWexzPRsUopCQRLp1QHYv4TkJMXfIHWiq+7UsoSdnh8sm5Kvk4KU67HDt6lCrgJ6/x0hJjYp83sALlxFmliquVDUbt05n7ZRVqhCzh1g2kYaeD9DV3M32LWfxgrjYgovos9+up+alc9Lg50qyvZOTFiHp8L89Nde1+CzG8YnMsHgXzVxHMR7ETXI3VT4+kWEWcUV4341kFtw9DljN/3sxNWzchLKmT6VPEZYt7OGvVcnLcrah4LtaYYQWP4iYL4yRe8CYfeP4nOoVy0pgExaLmHOR/12UMSh2OEfgm/5nlxosQbHooouYXlzGiBYt5ALk1muea1F2zfhYzS5hxNx/LxWIpM/eaaGUKllgA7SeUqoCdGGMw7JLqcIHYX8MG50YWyOO79iVu0zBALuTbBED/w8Ob0Yf/7mX5ZTAbQ5yXRmZ5jgJBs8PJh5mcIh4aZJjLggxTxMf04Zj11nCUfiC92uh3XKafRBxc9r7j916TJXsAUP84H639lScGBy4dODQgcMoCjZnTlHNxwiFDi5PnPEQSuY3bSoQLHsT2lbQXYU++nNPHOps2XHKrpFZvcojl+vKJmeuQj3uz+7MZx0HLjBo8eKNUgVXOXdMjsbDFW4IIVsoJ6/dY7fFcOngN+julCrRbQ3WhWH/HHCgIkZ/uGHHwQCKFCxSOEyCdw23/1DCEHuDXFIypdFXa5hLE/LY4DJh/o6zdPfkbmr3Ykvaee6OfijnbeHQjdxwL1bIwxSTu4+fMrdNBEpzEhCxX1iqcHsLIo/MqZMxAhbI5tb+WqJgs3L17iOqOkqj1AcGoJzmRCs4gCHnjWjNMruZxbOcKhr/LQbDI07wFyEhtUjhD6rzSW9WcnhfccD7d+9FfR3M8liJf0MsCYhH8O6gcKKAdj9v1a3K2IuQKJiXV3/YrJOdiGN1diCG9a7bTM1Cyd2DRUULNOdwO+OEN8b+jLjz3GKwzIM0oUbhzNRi/DpTpQqyAmUP7nM4MGKPxaEXlmEjcQR3Ozx2+RbN+HcdDWzXnK49iGDucCCLWdijtoyY0rbTN9mlyrDnS1OVghkpSaJEzAJSZuhS9j0Ij7lIEZOfg8ADDGo8BxcIBYpkc2S4c6ZUwaUUqQ+W96lHuWLyIIryJKtUzXuvBlXKn8l0/7eqVCHOz4yhdkSrUtSuRgF9bwSg4ncNygOIGuK7GL9xiOsb+nwp1i2+nR//uYcGPlvCgXod+zXqGQlQsE+CGAoFl6y4TDOmF+DucTJ7vP49iIzS8xKCbARun2YunHxtkA8Lrodzu9ZkFjCxdJgarltc+d9FF378DRdKiOnCOUIkkwDB0L5hGssl9rJ3pm+jmoWzEDxIig/SYodhgYRngmxB+1BczWISRZfqEZUiqM0LKk+VLK6BWk8pVYG6MoZx2aVUvT01nFYduUZ5MqSg9X0bxrmZ9RQ+BK3zBJjOPmL4MHOyCLh9wf3NrBj9pFGH32wb6+OWDH7UrlzMECSPQzsSqaLIKiviR2TKxrNxYqPAcIZgZx78C0r6scuOsj54jgxYOHBLVmOMRsGOwxEsZcbSb/7eOHk5ZMfp6ZrhOfEDbdaf6NYp9gPXqXWfaFY2FJkPbtEBi3W2RgT5Ig4oT8ZUzPIiMqqZzcd4uBJJE1Afbjn4gPLDHg4LZXKnZ65EiDn4/GXHWCAwinEGR7hgIkcJiBp44f1xOnOeaNlTrEER/PhplJ6iQMTryNUH+oEU7jAIxm5ROqfT98Ps4gBKFW5keTl8+Q7lTJ9STxBtNm64FXHKc7DmwcrKyVL4/EXGOuQeMlMixTw6YuykeNhD/1BSiw4MI+RZ5/FZRvkTLbZmzGTi33j7vA1O+c7joPDeHRze3GHqvefs1hkJxbgKtAuyDmPh+d5S07PDAAAgAElEQVTwd9HCzfvEPNpUyafLrzs3O9zgg30QFm5exETEYv/O3v+nkVFMuYJ8c3pnrB/eJeN7CEUWMbNi3KwnMoxxJ02SSGeDFdcNrl1wA+ZjMbPW9Zi1kzFxQjFdtPeSbqkCXmDVFF2bPVGqwFSJwzs8LRDTwhVhdxcLZvuWaK0TseJKlfg3Y5ycv/dsjAWshAOeKRlnWcU1QuzqmZv36fmJGx1Sf3zxclk9jgzfL1ipjAyKfN4ye7w4CN4/vhVwAzcji+F4QSm6+eCJ6UVuw7FrdO8A3j6nxDeTZVHRdeWSyccHCx3cUn1RIA9IqJ4ldVLKcH2fiqnyBag2t6GUKpsXQLZ7u5Sqtj9tpk0nbtLYl8vQy5XzyQ7XbT3R0uLsw1L/y9V0OoYq19XHxyyfC25DJ7at6HYcZgdO3AqDrQ+HORTZD5/4EZmx9XwcKxQ+ZiC24Hk6wA713eoTrA+4Bly5/ZgdQkX3LzAjHR4RV6ka+Nc+3eKF58WYIbeT9qICx8uZK5szVke4YYEhiheZDy7cv35ef4r6NC3GDoC8iP73zqZiVKoahGalqTFMdGYfch7IjHgmMM0Z3brE4HnQjrf/OVwP9IY7YNk8GbxA1f2jIl5JkiRhcQ2QJQRVuyvibSivWy5vBlooKFXu2uC/Q8l49DSSMVnBhS381E2HdwSHBCi8N+49oVUf1TON6xOt1OI7AIKYLvUcb4ArjljOLC+4GcYNMZd7uJD92L4y9fljNyOBQYEViJMC8PGKf+MxHG1+3ExbTt7UYzoGL9zPWDiNij/aGP7PQZ14QyRgwLg/bqbFg4gFiieUhSJZ0zB3RV74ewNl7JvXytPb07cxSwviEK0WM6WKJ09219Z3q4+zPGbcdU7mPXTXpszv3EsAdeGaDUsJp4sXlU/eFuQIrozImffTupO6xcRsL275zXrdBU3WUiXGyaJPuI0ij2K3BoXjWM3E+ZnhJZIXiXXh3t2+RtzYm9CBYZYv7GQwdlbn+YkbHEhpYCVEjJCxmF2YId4ob8aUehyk6LIOV3XExYkuwGjTjOFVhiac9w9X8fFtyuvx0+I4Zb7FbX/aEsd65ir/HqyMnFUUlm3Ei5oVPj4xBYA36+JOrnzVtqt27DpX+mNudvWhlCq7kLfYr13C/9L3G2nH2Vs0oU05eq58LEOTxeHHqY6PO8894myjfPH7jXq8havNFIc8bprHYQ8uSQOeKeFwEHc2XjGvDK8D1yZ+i4q/yWzkqCd+cH/fcZHgoiAW+JqD/Qu5nRBAjMMNT1ho7INv4DjgHxrheHuONsWD6dDnSjLXK1jB4rvAlQlEFLPerUbFc2g062KBmxtnvYMSBfdGWDOMt7beHOaAW7lhGk2ts2I8XJkRl+BZjjNXqly1ufLQFZbDCa6EcDeF64wV+fBmbbzBS5wnH4OnSpU4h24zd+i31KL84pCC//E4ROO8cTPL4+5EF1jcgr9qyIXUdNxaOnrlHnGFC+86YigRq4R4jE/m7tGD1uGOBJdEsYhkMCCJAOEAaI7htgR3Q4yRu6wivmt+t1jrHdqZuOqYbk0WLctot3NdcxcgWEGTJkrE3O544XImxrN4Kg9GpcoVq6S7PryVK3ft899FCw3yQ33/RiVacfAKw98YvG9s051S9eyE9bT/gpabTVapspL+QxyPGV78WwZlEQQNTWLY5bAvg/3RWKCodJwazi4JsG/Hd8FFEWIy+fcWrnUfxhBviH278kLgv4HIBZZPzAHfsi+WHonDcjrutXIsH5dV2eJ9IC8iXIe5eygfIzwV/pZwS4V7N5IQtyiTQ3chFF3VzfDmfXM3Y1d1cBECoitfFqtY+apvu86Vvhp/ILajlKpAXBWTMdkl/Dym6qd2FahJqVw+QwuHo6+WHaEmJXOwoHSz0mn6Nlpx6KrDx9LZABDzAipkHBatFNDYIqM7NnLOagR3lCqjtLxJ4ofaXbvu6HZ5rgzeDg4aKw9dpeI508ZRAMUA9QMGlyQ8D7Y80L6jiEyI7sboi9/F3F/G9sTAWxxwsM5HLt9lrkfiIdObj4gzqmk+FpHQg+NoxlyJ+vx3kcpdBiOzg5zMc57W8QYvcZ68f18oVbAQI5gcbnXuDsbivH9cd0JnvcQBBa7AKHM6V6dqhTI7QMTjnZwlnxXdYHFpYUwSi1tznqsM7JMfNI6btJPT5ZsxiYXtu0TvxcRIiQoa8lm9US2/9HIiqS3y+Hz2UllLsadmHYgMnPgd+cmQ78eT4q1cWekz9l3MRlPeqiL9KPKVwQ3N2V4sWmK4UiXS5Jt1JHtRZnzWDC9cIOy7cJvA7golkc8TsY1vO7Eku9pDpYGxUFGkcgdrn5GV07hHGPGBmyQId4yJqnFB+FnYYYeR8HxMVmWL44a4QHzT+MUmCG9A8PF61Xws16CVsuPMTWYtB/mNq8L7hrLkzHoMa+v649foo6ahThOkWxmbWNcqVp72Y3zOrnOlr8YfiO0opSoQV8VkTHYJf+Ov1tDxa/fp146VqU6o57kzPIF5yML9OpGApx9B2X7/3nNRD8A9NLy5njfJ2YfcrF1xY/xz5yX9sMjrTmxbgZ4tK6eY8k3e2S20aBFCsDOCngOhjFl8iCavO+n0AMTH6O1HBFT+Sw9c1pVuce5iolKOozN3LXyswdxo1X3PjHEsPvH3Fi+jm6sVMgJfz0vMbQdqa9x8n7nxgPo2D43jdgma+/k7zzPLc4ZUsWybfEwDFuzT2TTFHDr8d1FpM2MvRT3EWeJgiAOVMegdrrgjFh1klwLI1zT0n4Os6fGvlacXKuT2NTRS7RmVKsSIbh/YROpZYyVv5cpKp1wGRSZO2edBYqSxC8Y9VJvF5x66dIflDzQWWCexbsiD5EmRwYvP0ypLnCfjkX1GzLnlLHmtK0uVs35+Dz8bhyHwhzcrMrZDGazEdnn/IGfa9Gkj/WJz9rvVGUFLfBbet7M9Ij77RttWsfLVeOw6V/pq/IHYjlKqAnFVTMZkl/Bz9zhk/K5a2DHHQnxDh8Nu25+2UuuKuRlbVHwWMQ8RgqFFtipZhU7cGH/ZdDZOng3Q+DYqIaeY8k0eOVr2muQ2Eln2zNiz4hMrV22LFjSrLFqejBnUvJ/M3avHKLxdqyCjLuYFh7Gl+y+zm1mR1c2TvsRnQMHL6btl5cObPr396AaSUiW+ayAI8fSACzwRB8Nd/hAz9f0aLUaRFzGvDhi8cNvtaRGTjINi2ZsErZ6OAc9VG72Crtx5rDfhjlzBVV/eypWVeXAZrFYwE81xErdipT1eF6QuyCsIORItEkhpgETAKCACQoytt2smgxefp5UksZ7M28ozcNcDjTiKM9dVT5QqxFMZ8ypyq7IMVuIcxP6RfJq79PtDqRq3/CgtP3iFfu9SndLF0Lxbwdfbulax8rY//d25c4fSp09Pt2/fpnTpAuNi1ldzs6sdpVTZhbzFfu1SqqqOWsHynSzsVp3K5Yvf2yKLkPi0+rwd51k2exQckj35wIgb453HUSyvBfKUDFqoJUu08nHg/Ttz7UFMCmJTUNwlEPUpUG4ag7vFS5M2s1tlkULd+JgvPyJislBfxKzI4FVzzEqd1joYlCoxmB/zk41PkMHCah0cXnjOF+SoA8W4pwXxIh/+sYe1AcY5bkni7SFWDi6o649dp69fLe80zkumf7gJczp2xBSCatmOYlSqPLH88HH78j10hwXf04zMk+6e8/R3MV+RpzFUnuxb3PXQSOPt6Tx88ZyY6sCZW6In3zwxhQCUNbzbSIuAeEersiX2L15s8nxvvsAhUNuwipWv5mHXudJX4w/EdpRSFYirYjImu4S/7NCldOdRBC19vxaF5rIWrxQk0LJhcnY3JPhc0K0Wy3/Td+5edruJ3DYyxdnGCGsKEomCccnIKuesXTFoFxTexiISfXB6ZJkx+qMOKO7BbAbfeGfF1x8RjterlfPQFy+Xi/dptv5+o54INhiUKsREIN7o373azb2dShUS68ICjYJcWbLvl7tFhfKEhOGcQKRBaBb6qX0VSpJYS9ztbRFdhP3B+OhsvKJSBZZTuEaCDt+T4uv30NUY3MU3ejJ+V8+0/yVcT3vgq3dUBi8Q6cClFJTtgVIQ19ps/Do2HGeshJ4oVbjQGr34MIuLNl6OyGAl4gMFDTmzYL2GRwdIak5ff0A7Bzdx+S0JFIy9GYdVrLzpS3zWrnOlr8YfiO0opSoQV8VkTHYJP6d/XfNhHSqQNWGbh0GHDAY9ng8L8RQiuYI7UfHlxsg/cEjMusNEqRKD/bf2b2Qaa+BuvHb+7kusMA+OFxTX+HYVRX9w/QO7I1zOwOQY38VXeHGc7FSqROIBX99CQ3ms9+Uathy7BjakjGk8UzbM1hO5nrr+toP9JMbtxffaG9vn3gP4u7fKgq/kSgaD1YevMnp6kHXAkh3fRTa+08o4/ImXlXG5q3vi2j1q9NVaVs0Ze50nSpWrfj3BSvzmQmFDTjJfum27w8mu3z3Byhdjtetc6YuxB2obSqkK1JUxjMsO4RdZ1rb0rUc5MgbOzVsgLpsvN0b+gcuSJjltH9g4znSnrD+pJ8Q05lwJRGyMY/IlVmgbbodgUkRSRn9Qy/sbY1/hxeUKxAv/9Kzt72mw/sQD3p9da1CVAubsn54MDkxsrSZuoId3b1PYx00pWbK45BaetItnoBR0nLaNPW7nRUawKlWe4u7pc7gkm7DqOD1TJqdpEmpP2vXVe+hJ3948I+b2M0tdgLYDQanyZo7B/KxdcmXHuTKY10lm7EqpkkEpAOrYIfxi/qedAxpSprTxf7sYAFB7PARfboz8A5ctbXIKHxBXqfp5wyk9ufCeIU0pfcqkHo/bjgd9iZUd4/d3n77CKxCUqit3HlG10SsZhEhAbDUNgjvsHz9+QmFhYfTMMy1JJumou/b478hT9s707eyf+4c1s80lSSlVsivm+3q+eg99PzLXLV689ZBqfraKVeJ5pIxPKKXK36sS259dcmXHudI+lP3Ts1Kq/IOz173YIfxIklluuJZk9eDQxpQqRXKv55GQG/Dlxsg/cM6YvUSl6uDwZkHnIuFLrBKyTPG5+QovLlelc6ejf3vWsQW6e48jqPSQpazvv7rXIhAX+LL4CivjmET3P3fJRH05H2NbyKGHmB2UYHL/i09M/NV2fMlWfI//6t1HVHWUdpEx4fUK9JwJpbxSquJ7FZy3b5dc2XGutA9l//SslCr/4Ox1L3YIP79RTkTRdGREM5/e+noNSAA24MuNkX/gcqZPQZv7NYozW9H97+jIFl6xmtkBpS+xsmP8/u7TV3gFglKFuIlC/RczCH3t/oc2fYWVcY3/2XORes7e5RNlxhv5UUqVN+h592x8yZZ3o3L/NJgxK4xYzip+17YiPVM2Z5yHCvVbRFHR2p+9Vdbj8z10P9vgq2GXXNlxrgy+1bE2YqVUWcPLttp2CD8P+k6WKJoODFNKlbvF9+XGyA+/zqjJRaUK9LOyrILu5uCv332Jlb/GbGc/vsIrEJQq4MjHAdp9X5MW+Aor43ofvnyHmo/XEsr64tDpqTwppcpT5Lx/Lr5ky/uRuW7h7qOnVGao5nXiTKkq0n8xRcRoVb6Q72DFKr7Xwqx9u7Cy41xpB77+7FMpVf5E24u+7BB+UGM3HbeOUieJpt1DlFLlbvl8uTHyQ2eejClpQ9+GcboWlSpffADdzc3Xv/sSK1+PLRDb8xVez0/cQHvP36Yhz5WkjrUK2jZVKChIYxAfuZ58hZUZOOuPXSNYj4tkS2sbdt+sOEbjVhyl2kWy0G+dqnk1jvjEyquBBejDwYqXGB/tTKkqNiCMse356tIgWLGyQ/TswsqOc6Ud+PqzT6VU+RNtL/qyQ/g59XGGZNG0bZBSqtwtny83xme+XU8HLt6hHg2K0EfNQpVS5Q78BP67r2QLN9b7LtymagUz66kDEhp0vsIqUHEB1XT4qZtUPl8Gr2MpEzpWvl7DYMVLTJDuTKlCiohft5yhmoUz06x3q3sNXbBi5fXEPWjALqzsOFd6AE9QPaKUqiBZLjuE/9ClO9R33h6KvH+L/urTXMVUuZEVX26Mtx48oS0nb1DD4tlN46WUpSpIXlwfDdOXsuWjIQVsMwor+aVRWMljhZrBipeYHsWZUgVrFtIG1CqahdKl8J5NNlixsiYRvqltF1Z2nCt9g1jgtqKUqsBdG4eR2SX8dr3sQbIsDsP0J1ZKqQpGCfF8zP6ULc9HGRhPKqzk10FhJY9VMCtVGDt3KXemVFlDwn1tJVvuMeI17MLKrnOlPDLBV1MpVUGyZnYJv10ve5Asi1KqPFwoJVfWgFN4yeOlsFJYySNgrWYwy5ZSqqyttT9r2yVXdp0r/Ymtv/tSSpW/EfewP7uE366X3UOYbH3Mn1gpS5WtS+33zv0pW36fnI87VFjJA6qwkscqoViqJratQM+WzWVt4h7UVrIlD5pdWNl1rpRHJvhqKqUqSNbMLuG362UPkmWxzVK1eN8l6jZzJ+tfsf8Fo7RYG7N6D+XxUlgprOQRsFYzmGWLW6p+71ydqhfKbG3iHtQOZqw8mK5Xj9iFlV3nSq/ACvCHlVIV4AvEh2eX8Nv1sgfJstimVCGB6lfLj1CFvBmpccnsQQeXkitrS6bwksdLYaWwkkfAWs1glq1Fey/Rsat3qVejon7JaxjMWFmTCu9r24WVXedK7xEL3BaUUhW4a+MwMruE366XPUiWxTalKhjxEces5MraCiq85PFSWCms5BGwVlPJljxeCqvAx8quc6U8MsFXUylVQbJmdgm/2hjlBURhpbCSR8BaTSVb8ngprBRW8ghYq6lkSx4vhVXgY2XXuVIemeCrqZSqIFkzu4RfbYzyAqKwUljJI2CtppItebwUVgoreQSs1VSyJY+XwirwsbLrXCmPTPDVVEpVkKyZXcKvNkZ5AVFYKazkEbBWU8mWPF4KK4WVPALWairZksdLYRX4WNl1rpRHJvhqKqUqSNbMLuFXG6O8gCisFFbyCFirqWRLHi+FlcJKHgFrNZVsyeOlsAp8rOw6V8ojE3w1lVIVJGtml/CrjVFeQBRWCit5BKzVVLIlj5fCSmElj4C1mkq25PFSWAU+VnadK+WRCb6aSqkKkjWzS/jVxigvIAorhZU8AtZqKtmSx0thpbCSR8BaTSVb8ngprAIfK7vOlfLIBF9NpVQFyZrZJfxqY5QXEIWVwkoeAWs1lWzJ46WwUljJI2CtppItebwUVoGPlV3nSnlkgq+mUqqCZM3sEn61McoLiMJKYSWPgLWaSrbk8VJYKazkEbBWU8mWPF4Kq8DHyq5zpTwywVdTKVVBsmZ2Cb/aGOUFRGGlsJJHwFpNJVvyeCmsFFbyCFirqWRLHi+FVeBjZde5Uh6Z4KuplKogWTO7hF9tjPICorBSWMkjYK2mki15vBRWCit5BKzVVLIlj5fCKvCxsutcKY9M8NVUSlWQrJldwq82RnkBUVgprOQRsFZTyZY8XgorhZU8AtZqKtmSx0thFfhY2XWulEcm+GoqpSpI1swu4Vcbo7yAKKwUVvIIWKupZEseL4WVwkoeAWs1lWzJ46WwCnys7DpXyiMTfDWVUhUka2aX8KuNUV5AFFYKK3kErNVUsiWPl8JKYSWPgLWaSrbk8VJYBT5Wdp0r5ZEJvppKqQqSNbNL+NXGKC8gCiuFlTwC1moq2ZLHS2GlsJJHwFpNJVvyeCmsAh8ru86V8sgEX02lVAXJmt2+fZsyZMhA586do3Tp0vlt1NgYly1bRk2bNqWkSZP6rd9g7EhhJb9qCit5rFBT4SWPl8JKYSWPgLWaSrbk8VJYBT5WUKry5s1Lt27dovTp08sPWNV0ioBSqoJEOM6fP8+EXxWFgEJAIaAQUAgoBBQCCgGFgC8QwGV9njx5fNHU/30bSqkKEhGIioqiixcvUtq0aSkkJMRvo+Y3Gf62kPltgj7sSGElD6bCSh4r1FR4yeOlsFJYySNgraaSLXm8FFaBj1V0dDTdvXuXcuXKRYkSJZIfsKqpLFVKBjxDQPncyuOmsFJYySNgraaSLXm8FFYKK3kErNVUsiWPl8JKYSWPQMKpqSxVCWct42UmamOUh1VhpbCSR8BaTSVb8ngprBRW8ghYq6lkSx4vhZXCSh6BhFNTKVUJZy3jZSZqY5SHVWGlsJJHwFpNJVvyeCmsFFbyCFirqWRLHi+FlcJKHoGEU1MpVQlnLeNlJo8fP6YxY8ZQv379KHny5PHSR0JpVGElv5IKK3msUFPhJY+XwkphJY+AtZpKtuTxUlgprOQRSDg1lVKVcNZSzUQhoBBQCCgEFAIKAYWAQkAhoBCwAQGlVNkAuupSIaAQUAgoBBQCCgGFgEJAIaAQSDgIKKUq4aylmolCQCGgEFAIKAQUAgoBhYBCQCFgAwJKqbIBdNWlQkAhoBBQCCgEFAIKAYWAQkAhkHAQUEpVwllLNROFgEJAIaAQUAgoBBQCCgGFgELABgSUUmUD6HZ2+f3339OXX35Jly5dolKlStH48eOpTp06Toc0b948GjRoEJ04cYIKFy5Mo0aNotatW+v1kZF72LBh9OOPP9J///1H1apVo++++461nRCKFbx++uknmjFjBu3fv59NvVKlSjR69GiqWrWqDkWHDh1o+vTpDtAAsy1btgQ9XFawmjZtGnXs2DHOnB8+fEgpUqTQ/26lzWAC0Mq86tevT2vXro0zvZYtW9KiRYvY3xOqXK1bt47tVzt27GB71oIFC+iFF15wudTAqk+fPnTgwAHKlSsXffLJJ9S1a1eHZ6zgHyxyZRWr+fPn06RJk2j37t2MXRJ79tChQ6lZs2b6lPFv7O9iyZ49O12+fDlYYHE6Tqt4rVmzhho0aBCnvUOHDlHx4sX1v7v7ZgYjcFaxMtuPMO+SJUuy9xIlocoW2JLxbh0+fJhSpkxJNWvWpM8//5xCQ0NdLr07uUnoZ61gfC/MxqyUqoSykhLzmDNnDrVr145woKhVqxZNnjyZpkyZQgcPHqR8+fLFaWHz5s1M4RoxYgRTpHCgGTx4MG3YsIEpTyjYLKBo4ZBcrFgxGjlyJGEDPnLkCKVNm1ZiVIFbxSpeb7zxBsMVmygUgy+++IJtrviI5M6dWz/8XrlyhaZOnapPPFmyZJQpU6bABUJiZFaxgrz06tWLyYlYcuTIof/TapsSwwyIKlbndfPmTXry5Ik+9hs3blC5cuXYu4vDCwr+PyHKVVhYGG3cuJEqVqxIL730klul6tSpU1S6dGl69913qUuXLuzZbt260ezZs9nzKFbxDwihkRiEVaw++OADpnRCUciQIQPbk8aOHUtbt26lChUq6AffuXPn0ooVK/QRJE6cmLJmzSoxosCuYhUvrlRhz0qXLp0+OWABTFBkvpmBjYr56Kxidfv2bcIFGS8RERFsz+rZsydTplDw/wlRtpo3b05t2rShKlWqEOY9YMAA2rdvHztnpU6d2hRgGblJyGetYHwnnI1ZKVUJaTXdzAWKEA4nuJ3kpUSJEuzmF7crxvLaa68REvhhQ+UFG0bGjBnZIQU3J/go4+Pct29fVgU3nrjJxAaAQ00wF6t4GecaGRnJsJo4cSK1b9+e/YzD761bt+ivv/4KZmjijN0qVlCqIDfAwlmx2mawAOrtvGBdxuUGLDf8I51Q5Upc05CQELdKFfahv//+m2A94AVWqj179rADL4q3+AeDnMlgZTYPWKuw70O++MEXexWsWQm5yODFlSp4ZEAJNSvuvpkJAUMZrIzzhAy9+OKLhEuP/Pnz/1/J1rVr1yhbtmzM26Bu3boeyU1CP2slhPeCz0EpVQlpNV3MBTfdqVKloj///NPBfQ/WAnwwzdyLYL3q3bs3+x8v48aNYy6DZ86coZMnTzKXwJ07d+o3m6jXqlUr9tExurkFE9Se4GWc3927d9lmCsyfffZZ9jMOv/jAwDoFjOrVq8csfagXrMUTrKBUderUiVnwoHyWL1+eWUT5DbknbQYDfr6YV5kyZahGjRrM5ZaXhChXxvWUOczh0AIZ+uabb/THYWF/9dVX6cGDB+wiyOo+GAxy5QlWxmeioqKoQIECzF2yR48e+sEX7pfp06dnyd+hkMKluVChQsEIi9Mxy8gWV6qA0aNHj5gr28CBAx1cAt19MxMCaDJYGef53HPPsQvXZcuW6T/BUvX/IFvHjx+nokWLMmsVrOhmxZ3cJOSzVkJ4J8Q5KKUqoa2ok/lcvHiRHWDhDgP3NF7wgYTyY3TDwu84+OPw27ZtW73+rFmzWCwMNshNmzYxd7cLFy4wixUvnTt3ZkrX0qVLgxZdT/AyTrZ79+4MA8RY8TghuB6lSZOG3dbh1g7xanARQMwIDi3BWDzBCjFk+NhAQYA1FIfgxYsXM4sCPkCetBkM2Hk7r/DwcHawhYuWGKuXEOXKE0UBLshQMPv3768/zvcpYA+lyuo+GAxy5QlWxmdwwP3ss8+YlY9f8sBLAcoocIV7Kdy7ESsCl+bMmTMHIzSmY5ZRFPCNhGs7YmXx/fv111/phx9+IChb3ALh7puZEACTwUqcJyzqefPmJZwdcLnBy/+DbGG/wSUzrJvr1693uvzu5CYhn7USwjuhlKqEtooS8+GHObycuOXmBVYSfBzwoTQWvOhQuF5//XX9p5kzZ9I777zDburEw0rOnDn1OohnOHfuHC1ZskRiZIFZxRO8xJkgngoHFHxwy5Yt63SS+OBAwfr999+Ze0QwFm+xwpxxSw7XVBxOvv32W12psiKvwYCdt1jBpRaY4NbTVUkIcuWJooDDPy59+vXrpz+Oi6TatWszd0nIGZSqhCZXnmAlPgN3bliOFy5cSI0bN3YqWvfv/6+9846t6X/j+ENEa+9dpTYJIWqrvUdsgiDEKpEQm9ASFbOxV6iRpv5AYo/E3rv2aI2iIXZQK9Yv7+f7Oye31Tq9blv3nvt+kob2nqCS69YAABAHSURBVPMZr/O59573ecbno0YnwJuFYiB2MWeFgjFveGBwLkJOYVbfmXbg5SwrpBYsXLhQP9PBJyWz49rCg1UUE0Ieup+fX4pzt1o3dr7XssN7wnEO9FTZ7YqmMJ+/CTvyZpf03/Ay0CPZG090kdwdGBhoucLgmcENjZGXZnmCmx3gCivHqUCMx8fHaw5fWrXpZqhcmhc8Bnh4MXPmTC3yYWWevq7+Rigw/O8/as7c+MLLCSGKMOX27dtbLStp2bKllCtXLlFuruVJbn6AM7wcp4KHkpGRkWYOn9V3pptjSNXwnGEFTw0edCD8HakDVmantYWiHAj1h3czICDgj1O3WjcM/7NaOe7zOkWV+1yLdB8JwoYQuoDqf4YhLhzu6ZQKVSAvCGFZhrVt21ZzgRwLVSDnCk8uYbgZRuiIXQpVOMML80cIDQQVwv7q1q1reU1RyQ1PzpEfYxSzsDzJDQ9wdm0lnQK+fBHOhnDAiIgIfdnVNt0Qk0vzQiguii4g3NYq9Mou68rxGqbmZg4PJnbt2qWVtgwLDg7WvFHHQhXOvq/ddS2lNK7UsMK5+BwfNGiQ/mtVqh7HI+wNniqEeBvFLDyNTXLjTS2vpOd2795dUJ3z8OHD+hIKVfzpO9PbWBl5aH/KJzKY2GVt4bsMggq5nJg/Hm5ZmdW6MQpV2PVey4qPJ71OUeVJV8vFsRqlhBEHbiS6Y28lxMcjBA039bjBNwQWXM548ouncRBeCA1BYm7Skuo4HuV48eGBHC18kNippHpqeSHkDzlSiB1HrplhyKHCT0JCgpaRRWlneBzi4uI09+Px48f6pNOTS9A7u7aw9w1EJ9YMcqoQ8ocwVIRqGblCVm26+Hb4Z6dbzSvp+9AYKLY3wPsToaKOZud1hbkh9w6GAhTh4eFaGABbEODpLsL8IDKxPxzMKKmOMEl4PiGkIESTK6me0vv6ny0MFzt2lhWYYK0hn9Ex9Bh766AwBWzcuHGCEDewfvHihT4wQlEj3CQbVdxcHPY/O91ZXijQhCIVqJCIh4fwUCHEG/sLGfxS8535zybsQsfOsjK6whYusbGxye7DaNe1hS0ccA+A+yXHvanwnsJ7C8Z7LRcWo5ufSlHl5hcorYcHLxVu/pFfgEo0cMkbSbbYZBRfGngibhj2kYCQMtzPEFiOX8DGhnTY88px89+Uqtyk9XzSuz1neIEdCnQktZCQEBVT2LcDT4Ojo6O1lDiEFW4QUfUOibyebs6wwhM37OGFTUTxZYMbZjByzPcDjz+16cm8nGGFecbExOgXNKpnIUTG0ey8rlLacHXAgAH6OYWiFHg4geMMw00/1pex+S+8V8lt/pvS56CnritnWaW0qbTBFhyw3w7Cl169eqV7U+FBCD6vEOHg6eYsL6wXRBRAxOPmGOIKoh6bcDua1XemJ3JzlhXmiL2q8B0H0Y4HHEnNrmsLXs/kDA+ejX0Fea/lie+C1I2Zoip1nHgUCZAACZAACZAACZAACZAACSRLgKKKC4MESIAESIAESIAESIAESIAEXCBAUeUCPJ5KAiRAAiRAAiRAAiRAAiRAAhRVXAMkQAIkQAIkQAIkQAIkQAIk4AIBiioX4PFUEiABEiABEiABEiABEiABEqCo4hogARIgARIgARIgARIgARIgARcIUFS5AI+nkgAJkAAJkAAJkAAJkAAJkABFFdcACZAACZAACZAACZAACZAACbhAgKLKBXg8lQRIgARIgARIgARIgARIgAQoqrgGSIAESIAESIAESIAESIAESMAFAhRVLsDjqSRAAiRAAv8RaNSokZw4cSIRjsyZM8vbt28ld+7cxEQCJEACJEACtiZAUWXry8vJkQAJkED6E/j165fkyZNHQkJCpG/fvmaHEFWFCxf+bQDfv3+XLFmypP/A2AMJkAAJkAAJZBABiqoMAs1uSIAESMCuBGJiYqRixYpy/vx5qVWrVqJpxsXFSUBAgGzZskWWLFki586dk8jISOnRo4c8efJEJk2aJHv37tVz2rZtK8uXL5d8+fKZbdy5c0eCg4PlzJkz4u/vr220a9dOLly4IDVr1pT9+/dLly5d5MOHD6ZQu337tlSpUkVevnwpBQsWtOzn3r17Ur58edm9e7eEh4drXyVLlpRNmzZJnTp1zLGgvalTp8qOHTvk/fv3UqFCBVm6dKn06dNHpkyZIiNGjDCPPX36tLRo0UIwllKlStn10nNeJEACJEAC/ydAUcWlQAIkQAIk4BKBzZs3S//+/SUhIUF8fHwStbV9+3YVPYGBgTJ79mwVWIUKFVLBU79+fRk+fLiKko8fP6ooqVq1qqxdu1bbuHv3roq0YcOG6XE3btyQIUOGyJs3b7QvX19fmTNnjmzdulUuXrxo9ovxjB8/XuLj4wWCyaqfbdu2qchr0qSJTJs2Tfz8/HQs8KgdOXJE23306JHUrVtXGjZsKGPHjpUCBQrIsWPHVNiFhYVJrly5ZP369XosPHcQYxBVmDONBEiABEjA/gQoqux/jTlDEiABEkhXAhAwCxculOzZs5v9QBzB4zNjxgyZP3++CqLSpUubr0NwNGjQQF83DOIGbT148ED/1Lp1aylevLgpVvC3Xr16aVs3b97UY3r37i05cuQwhRj+NmHCBH19z549Kmys+pk+fbp6nOBxg+CDwWO2cuVK7QsG79jnz5/l8OHDkilTpkQ8FyxYIBs2bDCPhYcLY4iNjVWxRSMBEiABErA/AYoq+19jzpAESIAE0pVAs2bNNHdq1qxZZj8QOsWKFVMvVbZs2SQqKsp8DV4fCCz8HXlXhv348UPD7iBuEBqIcL+rV69KtWrVzGP69esnOM5or3LlyupVGjVqlHlMq1at1DMGD5dVPzipU6dOmhMGMWQYvFH3798XeNoeP36sIXyXL1+WGjVq/Mby5MmT0rhxY3n37p3OB2GBoaGhMnjw4HTlzsZJgARIgATchwBFlftcC46EBEiABDySAHKgIKhGjhz52/jLlCmjeVNDhw41X9u5c6cMHDhQ86uSGoRWiRIlNG8JIXmfPn1KVNSievXqGi4ITxA8R/AEIUQvKChIm/r586cKPHia0JZVPzgHwmvixImau2UYhCIqGkIcYSw9e/aUr1+/Jnt9vnz5ohUODx48qD84Pjo6OpFg9MgLy0GTAAmQAAmkmgBFVapR8UASIAESIIGkBBCqV7ZsWUFhhnr16iV6GcUc8ubNq+LJsYDFvn371DuEcuvwaCVnu3btks6dO2uuFXKnYAcOHJA2bdpocQqEBiI0D2GGz58/N6sMom2E6qFAxMOHDy37gXcJY0SoInKmDMufP79EREToGFBIo2PHjloMwzHE0XHcmB/CDNesWSMYe/PmzblYSIAESIAEvIgARZUXXWxOlQRIgATSmgCq+iGvCQIqqeDAvlVNmzY1i0oYfaPQBELk4AlCPlPOnDm1oAQE0eLFi/Wwp0+fCrxc8B4htA+eH3inIOKePXsmRYsW1X/h1YLnq0OHDnL27Fkt6Y6/QwBBMFn1c/z4cYFXCsfDswUzwhMhyuDFev36tVYHhLCC1w2FKHAeCltUqlRJz8EY4R3DODAeGgmQAAmQgHcRoKjyruvN2ZIACZBAmhKYPHmyigijcIRj48uWLZNVq1aZBRwcX0P5dYTcIU8JIqVcuXKCfKkxY8aYh6H0OtqHRwvl1mvXri0oCgHPlGGovIciGRBmEDkobHHo0CEtuQ6z6gcFKlavXp1ojMijQtgg+jXs1KlTWkTj2rVrkjVrVh0Lqgwa5d/XrVunAvD69etaXp5GAiRAAiTgXQQoqrzrenO2JEACJOCxBOCpQuEKhAG6m8HbhYIaixYtcrehcTwkQAIkQAIZQICiKgMgswsSIAESIAHXCSCfCsJl3rx5rjeWBi2gKAb224KXCqF/t27d0iqCNBIgARIgAe8jQFHlfdecMyYBEiABjySA/CkIKuRNuYMdPXpU87GQV4WNf7HhL40ESIAESMA7CVBUeed156xJgARIgARIgARIgARIgATSiABFVRqBZDMkQAIkQAIkQAIkQAIkQALeSYCiyjuvO2dNAiRAAmlCIFOmTGnSjjc0giqHNBIgARIgAXsSoKiy53XlrEiABEiABEiABEiABEiABDKIAEVVBoFmNyRAAiRAAu5HYNiwYbrxb1RUlPsNjiMiARIgARLwGAIUVR5zqThQEiABEvB8Ao0aNZITJ06oiOndu7c5oRUrVkhoaKi8ePEiQyf55s0b8fHxkRw5clj2O3r0aImLixNsDkwjARIgARIgAUcCFFVcDyRAAiRAAhlCADlF2McpZ86cUr9+fdm6davZ7+DBgyU+Pl7279+fIWP5m04aNGgg7du3lylTpvzN6TyHBEiABEjAxgQoqmx8cTk1EiABEnAnAjExMVKxYkXdKHf8+PG6cW727Nl1iDVq1JB27dpJWFiY+Pn5qXAZMWKEOfzTp09LixYt5Pbt21KqVCm5c+eOBAcHy5kzZ8Tf31+WLFmi51+4cEFq1qyp4qxLly4a2pclSxZtB+dWqVJF+y1YsKB6nQICAvRftInNfOfMmaN7Tj158kQFYKtWrSQiIkI9Wd++fTPHU7t2bTl37pw74eVYSIAESIAE/iEBiqp/CJ9dkwAJkIA3Edi8ebMMGjRI3r17pyJm2bJl0q1bN/n69avkypVL8Dp+7969u/4OcQODhwsb60JUzZ49W+7evSu1atUS5EMNHz5cbty4IUOGDBGE8iUkJIivr6+KI3jCLl68aCJG+xBz8IjBEMY3cOBAefv2rf4OQYdjli5dKmXKlNHjIN5wDNrBGK5cuSJFihTRPvLmzetNl49zJQESIAES+AMBiiouDxIgARIggQwhAEFz/Phx9fDACwUxAxED7xI8Pw8fPpTSpUvLggULZMOGDSqWYJs2bZIJEyZIbGysiq3WrVtL8eLFTdGFY3r16qXH37x5U89Bvha8S2vXrjXnhjbw+p49e/RvM2bMkCNHjsjRo0f1d+R71atXT+bOnfsbDwgwhCi+evUqQ1ixExIgARIgAc8iQFHlWdeLoyUBEiABjyXQrFkzDf9buXKlHDx4ULp27aqhePBITZ06VV6/fq1zO3nypDRu3Fg9WpkzZ5YKFSpoEQuIGoTlIdzv6tWrUq1aNZNFv3795MePH2YVv8qVK6twGzVqlHkMQvkCAwPV2wVDeCDaWrx4sf4OMTdx4kRp3ry5jq1nz56SP39+fS0kJETHdejQIY/lz4GTAAmQAAmkHwGKqvRjy5ZJgARIgAQcCOTLl0/mz5+v4uj79+9StGhRzVfavXu3PHjwQIUW7MuXL5I7d279HT87duyQ6OhoFVj4f48ePeTTp09mrhTOqV69uvTp00c9Wp8/f1aPFrxQQUFB2ibypQoXLqz5XPBqwRDiN23aNA3vMwx5X/BKbdy4UZ49eyaXLl3SvKtOnTpJ2bJlJTw8nNeUBEiABEiABH4j8D8ViRpH6PRh0gAAAABJRU5ErkJggg==\" width=\"853\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "FVikpnHZ4z8Q",
"colab_type": "text"
},
"source": [
"After sampling by a factor of N=4, still including the zeros, we get the following spectrum"
]
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "QpT2bWGh4z8Q",
"colab_type": "code",
"colab": {}
},
"source": [
"unit = np.zeros(Fs//32)\n",
"unit[::4]=1\n",
"signal_downsampled = signal*unit"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "my4GeWEr4z8T",
"colab_type": "code",
"colab": {}
},
"source": [
"signal_ds_fft = fft(signal_downsampled)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "txElxJMy4z8W",
"colab_type": "code",
"colab": {},
"outputId": "22f3d247-f8c0-4eac-8add-6a8855a2ef49"
},
"source": [
"from matplotlib.patches import Rectangle\n",
"\n",
"plt.figure(figsize=(12,8))\n",
"plt.plot(freqs/(Fs/2),20*np.log10(np.abs(signal_ds_fft)))\n",
"plt.grid()\n",
"plt.ylabel('Magnitude [dB]')\n",
"plt.xlabel(r'$\\dfrac{Frequency}{Nyquist}$')\n",
"plt.ylim((-270,120))\n",
"\n",
"# Annotations\n",
"plt.annotate(s='', xy=(0,100), xytext=(1,100), arrowprops=dict(arrowstyle='<->'))\n",
"plt.text(0.5, 110, 'Positive Freqs.', horizontalalignment='center', verticalalignment='center')\n",
"\n",
"plt.annotate(s='', xy=(1,100), xytext=(2,100), arrowprops=dict(arrowstyle='<->'))\n",
"plt.text(1.5, 110, 'Negative Freqs.', horizontalalignment='center', verticalalignment='center')\n",
"\n",
"ax = plt.gca()\n",
"rect = Rectangle((0.3,-220),0.15,310,linewidth=1,edgecolor='r',facecolor='none')\n",
"ax.add_patch(rect)\n",
"rect = Rectangle((1.55,-220),0.15,310,linewidth=1,edgecolor='r',facecolor='none')\n",
"ax.add_patch(rect)\n",
"\n",
"plt.annotate(s='', xy=(0.37,-150), xytext=(0.85,-150), arrowprops=dict(arrowstyle='<-'))\n",
"plt.annotate(s='', xy=(0.37,-125), xytext=(1.35,-125), arrowprops=dict(arrowstyle='<-'))\n",
"plt.annotate(s='', xy=(0.37,-100), xytext=(1.85,-100), arrowprops=dict(arrowstyle='<-'))\n",
"\n",
"plt.annotate(s='', xy=(1.63,-50), xytext=(1.15,-50), arrowprops=dict(arrowstyle='<-'))\n",
"plt.annotate(s='', xy=(1.63,-25), xytext=(0.65,-25), arrowprops=dict(arrowstyle='<-'))\n",
"plt.annotate(s='', xy=(1.63,0), xytext=(0.15,0), arrowprops=dict(arrowstyle='<-'))\n",
"\n",
"plt.annotate(s='Original', xy=(0.37,-220), xytext=(0.37,-250), arrowprops=dict(arrowstyle='<-'))\n",
"plt.annotate(s='Original', xy=(1.63,-220), xytext=(1.63,-250), arrowprops=dict(arrowstyle='<-'));"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option);\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
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\" width=\"877\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "cUI3WNfW4z8b",
"colab_type": "text"
},
"source": [
"The picture shows that the spectrum still contains the **original spectrum, plus** the spectral **copies** at frequency shifts of $k\\cdot \\dfrac{ 2 \\cdot \\pi}{N}$ from the originals.\n",
"\n",
"**Observe:** Since we have a real valued signal (the sinusoids), the spectrum of negative and positive frequencies are **symmetric** around frequency zero. This then leads to the **mirrored appearance** between the neighbouring spectral images or aliasing components.\n",
"\n",
"Nyquist tells us to sample in such a way, that the shifted spectra of our signal do not overlap. Otherwise, if they overlap, we cannot separate those parts of the spectrum anymore, and we loose information, which we cannot reconstruct.\n",
"\n",
"**In conclusion:** Sampling a signal by a factor of N, with keeping the zeros between the sample points, leads to N-1 aliasing components or spectral copies."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "16AJqjvN4z8g",
"colab_type": "text"
},
"source": [
"**Example:**\n",
"\n",
"Make a sine wave which at 44100 Hz sampling rate has a frequency of 400 Hz at 1 second duration. Hence we need 44100 samples, and 400 periods of our sinusoid in this second. Hence we can write our signal in Python as:"
]
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "sYUeJNpp4z8h",
"colab_type": "code",
"colab": {},
"outputId": "89c3b039-f17e-49e2-b884-1ddd4250b5df"
},
"source": [
"%%html\n",
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/GpiB5cDa5to\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/GpiB5cDa5to\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "hN1W1Qa64z8k",
"colab_type": "code",
"colab": {}
},
"source": [
"import numpy as np\n",
"fs = 44100\n",
"f = 400.0\n",
"s=np.sin(2*np.pi*f*np.arange(0,1,1.0/fs))\n",
"Omega = 2*np.pi*f/fs\n",
"s1=np.sin(Omega*np.arange(0,fs,1))"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "WTDg9Jvd4z8m",
"colab_type": "code",
"colab": {},
"outputId": "b822f599-2a69-414a-d1dc-4969d48c7c69"
},
"source": [
"import IPython.display as ipd\n",
"display(ipd.Audio(s, rate=fs))"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
" <source 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\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
],
"text/plain": [
"<IPython.lib.display.Audio object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "ehj2axdR4z8o",
"colab_type": "code",
"colab": {},
"outputId": "f56f925b-6e4f-45ea-c3b0-098e2cd42999"
},
"source": [
"# Plot the first 1000 samples\n",
"plt.figure()\n",
"plt.plot(s[0:1000])\n",
"plt.plot(s1[0:1000])\n",
"plt.grid()"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option);\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<img src=\"data:image/png;base64,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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ls64qDie4z8q",
"colab_type": "text"
},
"source": [
"Now we can multiply this sine tone signal with a unit pulse train, with N=8.\n",
"We generate the unit impulse train,"
]
},
{
"cell_type": "code",
"metadata": {
"id": "HTmfqdGQ4z8q",
"colab_type": "code",
"colab": {},
"outputId": "05065278-b5e6-4ca9-c7d2-16168d1a8b9d"
},
"source": [
"unit = np.zeros(44100)\n",
"unit[0::8] = 1\n",
"plt.figure()\n",
"plt.stem(unit[0:100], use_line_collection=True)\n",
"plt.xlabel('n')\n",
"plt.ylabel('unit(n)');"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option);\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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": [
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]
},
"metadata": {
"tags": []
}
},
{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "PtzvEuG24z8t",
"colab_type": "code",
"colab": {},
"outputId": "7c5529a1-f337-49a6-d436-2e9a550766c3"
},
"source": [
"ipd.Audio(unit,rate=44100)"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
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type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
],
"text/plain": [
"<IPython.lib.display.Audio object>"
]
},
"metadata": {
"tags": []
},
"execution_count": 12
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "1nWSDt_l4z8w",
"colab_type": "text"
},
"source": [
" The multiplication with the unit impulse train:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "mxNeViWJ4z8w",
"colab_type": "code",
"colab": {}
},
"source": [
"sdu=s*unit"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "rSiVaufe4z8z",
"colab_type": "text"
},
"source": [
"(This multiplication is also called „frequency mixing“).\n",
"Now plot the result, the first 100 samples:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "MEPU804h4z8z",
"colab_type": "code",
"colab": {},
"outputId": "78599eef-0286-4d36-d416-f4bf88af64a7"
},
"source": [
"plt.figure(figsize=(10,8))\n",
"plt.plot(s[0:100], label='Original Signal')\n",
"plt.stem(sdu[0:100],linefmt='r',markerfmt='r.', use_line_collection=True, label='Downsampled with zeros')\n",
"plt.legend();"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
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" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option);\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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"
],
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}
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uMKFC2Pq1KmpdRYsWGC8mHO2x0L+jXUUWX4sPzKLIKVmzZooU6aMMeMgS5glaZeZCsdsiyszFun7J3/Pbr/9dsTFxRn/tqf34U5f5BmyX0TyB/EvRYSPzLDIMi/Z35ErVy5jj4gINAdLV/IXd2PTH+woLKwbZQoLJ+dAy9pP2USW9o/oihUrjCVPsgZS/hCUKlXKWCLVokWL1JEaPnw4ZsyYgV27dmU6evKHSX4cRYSF/BGMiYlB/vz5rRtxeiYBDQREKOw+eRGr/z2Lf09dwqGzV4yfw+diEZ947a1bdiVXcKAhMEpGhKFURG7UKVUATSoURpVieREYGODMnJ+TgO0J2HXztiTWMlMgb+5d2bztTFjIUig5aWnz5s2pYyozDSJe3BUWIoDkaFhZGuXY67hs2TLj/6sIC2ngSy+9BMkB1q5dm+lSKLN9yUxYyPIuWR4lS6ylyAZvWVYtszIUFnq++hQWejhm5oXCwgVhIesh025UExEhpzjIRm15CyLCQv7QyBsFR5H1oTNnzsTOnTszHT051ULeRqQvFBbWBTs9u09ABPT+05exYt8ZrPz3DFbtO4Mzl+MzdRgUGIBi+XIhJCgQohECAwIQEHBtTfDFqwnGjMb1F3MZ7CPCQ3Bz+UJoUr4QmlcqjFol83Nmw/1ho6UXE7CrsBBBIS/RZLlv+uNm5WVZ2uNmZSmUM2Eh+xirVauG/v37o1evXsZMv+OEqPPnz6NAgQJZngqV1YyF/Lss+ynkpKi3334bhw4dgggYOW3JVWEhvsVWknuZ/ZBjcmWWQlYjyBJpET/pZyzc6UtmwkJWScjMkKyUkJeOcpSvCBl5YUlhoedLTWGhhyOFRToCrkwlWrUUijMW1gU1PSsSiI4G9uwBqlTB8XxF8N36aHy3Lhr/nv5vTbA8QU6SaVy+IGqVLICyhcJTf0pEhBmiIqsiMxqyVOrI+VgcPR+LA2euYP3Bc1h38FyGU3EqFs2DexuUQpcGpVC6YLhix2hOAt5DwK7CQggePHjQuCBPjnSV2YHixYsbS5ckEZdlTY7iirCQuo4jWuXNvLyge/DBB/Hcc89BLsYLCwszLSzE58KFC43ZBdlzIcJl3LhxiIyMdFlYyL6MYcOGGfscREA4Trl6/PHHDRGU1clSZvuSmbCQk7FkWZlsNJeZChEUclJWWpHmSv7iPdHufS2hsLBuTDhj4WTGQt5MyIYtOeHJUeQPnrzNSLt5W46Fk6lLR5E3HLL5jJu3rQteeraAwNSpSHn6aQQkJyM5IBCv3/ECZte9zXhQaFAgGpaLQPOKRdCicmHUKx2B0OCsBYTZ1iUkJWPrkRis2X/W+Fm+7zSuJvy3rKpphUK4r2Fp3FW3BPLmcn6Cjdnnsz4JeJKAnYWF1Zxkxn/SpEnGEiC7F1/qi93HIm37KSysG02/ExaXLl0yjnmTItONcoqFHCEnN4XKmwFZ8iTnV3/11VdGHcdxs3LUrJxuIWJCToXK7LhZ+UMob1s+//xz46IeWYea1cU66YeUm7etC3J6do3Axb37kadaZQReP5lErBIDAtHn/e9wS4dGuKuOZxP6S3GJ+HXLMXy/4Yix/MqxfCp/WDB6tqyAJ1uWR0S4d9zi6xph1iKB/whQWPzHQl7KyU3WMtshS41ffPFFvPDCC8ZSK7sVX+qL3dibaS+FhRla5ur6nbCIiooyhET6ItObcrunbNSWaU+p5yiyrlKmPh0X5MksRmYX5MlFOrLvQk6ekE1WsozK1UJh4Sop1tNNQPY9fLn8ADZ99T2mfjU4o/vFi4HISN2PNeVPlkzN33gE3679b0mWzFp0b14OT1cIQcGjh4ylWyhd2pRfViaBnCJAYfEfefn3Ve6Dkgv45AWf7GuQl3xymZ7dii/1xW7szbSXwsIMLXN1/U5YmMPjudoUFp5jzSddIyCCYsaKA5jy937ExCag+IXTWD7pSQSlpDnVSW6bleMbvSRhl9Ooftt2HOP+2oOdxy/igU1/YMTvnyJIjrYNDETA558DvXpxiEnA6wlQWHj9ELGBPkyAwsK6waWwsI6tKc8UFqZwsbICATnh6bv1RzD8lx04e/1kp0pF86DvrVXRcdn3CHzhhWveRVRMnuyViboIjGVRG9Hq1sYITCOEkgODZP0iAsuWUSBEUxKwngCFhfWM+QQSyIoAhYV1sUFhYR1bU54pLEzhYmU3Cew7dQlvfL8Fq/49a3ioWEQERRV0rFsSckws5DbYvHmveZc7WKpWdfNJHjCTJVrt22d40Jt9x+HhV3oYp1WxkIC3EqCw8NaRYbv8gQCFhXWjTGFhHVtTniksTOFiZZMEriYkYWLUPuMnPikZYSGB6HtLVfRuXeHGo2HTCotLl4A8eUw+yYPV5VjccuXkWu/UhyYFBKLls9NwskARPN6iPAZ0qIp8YSEebBQfRQKuEaCwcI0Ta5GAFQQoLKyges0nhYV1bE15prAwhYuVTRCQo1tf/W5z6j0UbasWxXtdaqNMoUzuhbCTsBAGcsRznz7XaAQFIWbMeLxRuAl+2nzM+NVN+XNhzAP10aJyERPEWJUErCdAYWE9Yz6BBLIiQGFhXWxQWFjH1pRnCgtTuFjZBQJJySmYsHgvxizcjeQUoGi+XHi7U03cXadE1rdZ201YZLF06+89pzBkwTbjtnC59fu5tpXQv0PVbC/ucwEpq5CANgIUFtpQ0hEJmCZAYWEamcsGFBYuo7K2IoWFtXz9zfvJi1fRf85GLN97xuj6vQ1L4e1OtVAgt5NlQXYWFumWbsXGJ+Hdn7bh6zXXLtlqUDYC4x5qkPlMjb8FCPub4wQoLHJ8CNgAPyZAYWHd4FNYWMfWlGcKC1O4WDkbAvK2XkTF6UvxyB0ShGFdaqNbIxfvd/AhYeFA9PPmY3h13mZcvJqIfLmCMfzeOuhUryRjiARylACFRY7i9+jDHfdnnTt3DhEREW4/u3z58ujXr5/xo1pcbZPOZ6q2Wac9hYVOmjf6orCwjq0pzxQWpnCxciYEEpOSMXbhHnwWtde4pbp68XwY/0hDVC52/ZQnV6j5oLCQbkefu4K+szdi3cFzBoXHmpU1ZnBCggJdocI6JKCdgFZhIQcZ7NnjkUsi5RLZGTNmGDzkArtChQqhbt26ePjhh40LZgMD+Z1KHyyuJvHOgkxnkh8fH29cSHjTTTcZS2PlgmARLOfPn7+hGTqf6ax/nvycwsI62hQW1rE15ZnCwhQuVk5H4FJcIl6ctR6Ld50yPnmkaVkM6VgTYSFB5lj5qLAQCCK8PvlrD8Yvvia8WlYujAmPNEKBcJ4aZS5IWFsHAW3CYupU4Omnr52OJkm9xZdEing4ceIEvvzySyQlJRn//7fffsOIESPQunVr/PDDD7a8MVvHmGblwxuFRfq2erOwEBEUGhqqdYgoLLTivMEZhYV1bE15prAwhYuV0xA4FhOLJ6evxY5jF5ArOBAju9VF5/ql3GPkw8LCAWTh9hN4afYGXIlPQsWieTDt8ZtRvogXH6vr3kjSyssJaBEWmRy5bFxseeAAUNrF5Y8mOYmwkLfa8+fPv8Fy0aJFuOWWWzBlyhT07t3b+OzQoUN48cUX8ddffxkzGXfccQc+/fRT4y15TEyMMduxZs0aNGrUCHJxZ+HChVGpUiX8888/hv3XX3+NAQMG4NixYzhw4AAqVKiA7777zvCxevVqVKlSBZMmTULz5s2N+gcPHsQLL7yAZcuWQZJReds+atQo3HXXXYYIevrppyHtPH78OMqWLYvnn38effv2Te2Ho29NmjTBJ598gri4OPTv3x9vvPEGXnvtNUydOhXh4eF499138eSTTxp2jnZJW8eNG4f169cbffjss88QGRlp1MlMWKxYsQKvvvqq0dciRYqga9euhjjLc/2I75MnT6JXr15YuHAhihcvjvfee89oR1ZLobZs2YJ69epB7MSfLLsSnvfddx/mzp1rtEP8i/BbuXLlDW3auHEj2rVrd8N4vv322xg6dKjBULjt3bvX8FOwYEG8+eabxu8yKw4e6T9r27at8Uwpzvouz5QYkmd+//336NKlizFLJn2U8ZL2yzhI3z7++GPkvX73kvh/5ZVXsG3bNoSEhKBWrVqYNWsWysmx5OkKhYXJL76J6hQWJmBZWZXCwkq6vut765EY9JrxD05ciEORvKGY0qMxGpQt6H6H/UBYCJztRy8Y3I7FXEVEeAgmP9YITSsWdp8bLUnAJAEtwiKLSyIhv7+e1JpsltPqWQkLMaxfvz5KliyJX375xRAKIhgkUR47diwSExONRD5fvnypCaZ8/sgjj2DgwIHYtGmTkdxevnwZp06dQv78+fHMM88YAmT27NmpCXz16tUxevRoQ1RIoi2JuSSgsiyrY8eOhqD46KOPjOdu377d8NOmTRskJCQYybnUkcRbkltJjmXm5YEHHjD6LX2bN28eevToYQii5cuXG8n97bffbvi4//77MWfOHENY7Nu3D2XKlEltV+nSpY1+1qxZ00h2pd7+/fuN5D69sJAEuUWLFhg2bBjuvvtuo78iiEQYSHukiBg6fPgwPv/8c+Nt/UsvvYQNGzZg+PDhme6xEN7FihUzhJYk3AsWLDCScxF0MqskRfrRoEEDfPDBBze0SZL0iRMnYsiQIdglF6NC7knNa/xIkn/x4kWjrbfddhu+/fZbg7sk7zIW6YsIOOmPo4iIu/XWW42xF26u9F2eKcLorbfeMkSFFIkrGfNmzZrhnXfeMQSU9E/GRWZbJL5kXJ966ik8++yzRhyIaJWYEhFJYeH0q62tAoWFNpRqjigs1Pj5o/VfO07gxa+vvXmvUiwvpvW8Wf3EIz8RFhIvJy9cxVNfrcWm6BiEBAVgeNc6uL9xGX8MJfY5BwhoERZeNGMhCB966CFs3rzZSOj//PNP3HnnnUZyLQm4FPm9vEWWhO/mm282BMXu3bvx448/GjMEMtPw77//GkmsJNbVqlUzZgwkUXS8Cf/iiy+MZD+tvx07dhhJruz1kKRa3ra7Uvr06WMk3ZIsSxFhISJA2uDYKyJ+JWFfunSpUUcS5wIFCkDaIf11tEuS9cGDBxt1JMmV2RURJ/IGPb2wEOGSO3duTJ48ObWZ0nd5qy/CSmZ6pO+rVq1C06ZNjTo7d+5EjRo1MGbMmCw3b0vfJQGXGR3hFhQUZLzpX7JkCapWrWrMNsisg8wcpW9TdkuhZInbzJkzjXaIgJEZFEnuZVyyKxLjMmtTtGhRQ+gIU2d9DwsLM8SMCCCZrXAUmQkTviK2HLM6ImA7deqEo0ePGjMUDhEnHJ0Vzlg4I+T+5xQW7rPTaklhoRWnzzubufIA3v5hm3E/hbFX4NFGzo+SdYWKHwkLwSFH0g6cuxG/bDlu0Bl0ezX0aVfZFVKsQwJKBLQIC2lBuksiIcnq9cRbqYFZGGc3Y/Hggw9i69atxttsWRYkSbAIi7RFklsREZJgiqDo3r27sYm4W7duxlIqSepl9kES4xIlShhiRBJqRwLvECXiU95qy3IqSZzlzbUk+8899xxkKZO8JZdEW8SGo8jbfKkjS6ZiY2ONt9oyyyI+pUjf5G37zz//nGojSWrt2rWNpU2OIktrRBTJLIKjXY42OOrI0iY5AUpmINIn8SKuZJZFkmFHkYT9ypUrRn9FbAkPiRERB44i7EQ0ZXUqlAgKmeGQWYGGDRsaAm3atGkGC+mnCARh5pg1krf5jpOqshMWIsAGDRqU2g6ZWRG2MsORXXn00Uchy6xEIMkzpTjru4y1CAuZeZCZEUeRJXEyY7NYZuOuF5nNEsYO9k888YSxfK5Dhw5Gn2UmSmIos0JhYcVfh2s+KSysY2vKM4WFKVx+XXlC1F6M/O3adPWDjcvgva619Z1u5GfCQhgmJ6dg9B+7MCFqn8G0T7tKePm2allfIujX0cfO6yKgTVhkcUmkrnam95OdsJAkXpad/PTTT4Z4kB8RCmmLJIKSAIugcOyzkP0SMrshCbgsMZLlPrKWXhJoxzIeRwIvyQXt0gQAACAASURBVKUkyVJkr4ck25JsOvYzyBttEQZ//PGH0Q5ZFiUzB9988w0ef/xx479lT4YkurL/Qp4tya+UzPomfuV5sszJUdKelJSdsJC2SWKfXlhI8izJrwiT9EX4yZt4WXYlezzSnrLlTFg49lmIMJElWadPnzaWCcmyLxEDsi9G+ivFzIxF+n0dwkOWKMkejKyKLDsTYSmiTfacOIqzvsuyr8xOohKhKcvlZI+MoziEhcwmiWiSIvEhhwmIaBUeMnMmy6fSFwoLq/5CUFhYR9akZwoLk8D8sLq80ZJTjeRIWSkv3VIF/W+tojcB9kNh4QilyUv2YcSvO43/fKJleeNULTmGkYUErCBgibBId0mkFe12tnlbEml5c5zdUijZF9G4cWOjebLPok6dOkYyLSJCxIIstZE39rIvQgSBFFeFRdo+y4ZrERmyPEvEhcwGyEZyR5G32pJ86xAWH374obHsSYoshapYsaKxbyKzpVDyJl/2HqRtS9p2yz4HWYIlIkBmX6Q4fpfdUijHPgvZtyGzRsJZknFZ+iSiT8TFyJEjDX/phYVscpY9LbKfIm3JLMl3Jixkg70cP/zrr78as1Bpi7O+S93MnulsKZQcCJC+iICUJXcye5a+UFhY8dfhmk/OWFjH1pRnCgtTuPyusvyDMer3/96qv3JHNTwfacGSHT8WFhJUssTsrQXbjPh6uElZvN+lNgIDKS787gvngQ6nT2zkO54SG2v+yVeuAMWKXbM7eRIIDzftIyB3bpdFdHbHzcrbfXkrLst3HJu3ZQNw2s3b8t+O04GkobKkSGY2ZOmQ4/QiWV8vb5slIZRNv1JcERbyZl1mPmQ/gSzxkWVRkqTKRmp5hizdEaEi+x9kz4D4l/+vQ1jITIP007EPQhJ1WQYmG4rTJ/EidOQtuggwWfIjewZkn4iIMZnNkSL9kL0DsrRJloZJ39atW5fl5m3HoDs2bssbfpmRkXGQNsjbfTkRSvauSEnfJpnVaNmypXEKlQgQ2dAtP2aFhSyFk30hsnRJllA5isxEyLI1V/qe2TNlmVjlypWNTe8yUyJL1mTztsxUyKyMsBZW99xzj7HPRISYiBuZOZE4oLAw/WfBbQMKC7fR6TWksNDL05e8yT8M7/28A1OXXVur/ObdNdC7dUVruujnwkKgfrP2MF79brOxf6Vrg1IY1a0ugnmRnjXx5sde0wuL5CtXsKthoxwhUm39OgS6KEjSX5Any3MkEZXTnWSpUdqlO9kdN+voqCxXkg2448ePT01EJYkWISBJqqzJd1VYyKyEvCWPjo42ToOSN/Xyhl829cqyItlsLBuCZSZSkk7ZhC31dQgLERLSZlmKI0t/pD/t27fPNImXX8psguwhkKNT5W+82Mgelddff92wkRkNSZwl0Ze38ZIgyylJzm7elucKB+EqMxdSZNmS/LfsZREumQkL+Z0k4CLuzpw5Y+zlcBw3a2YplCT5IpjSl7THzTrre1aX8mV33KzMdsn4yiyPtF/2Vkg8Sj8yu7SRMxbW/amhsLCOrSnPFBamcPlNZVn/L5u0Z646aPR5WOda6N68vHX9p7Aw2P6w6Sj6z9mIpOQU3FWnOMY91IDiwrqo80vPdhUWfjlY2XQ6s5kUMvJ+AhQW1o0RhYV1bE15prAwhcsvKstbrCELrokKWeo/omsdPNQk43ncWmFQWKTi/GPbcbwwawPik5Jxb8NSGN2tHpdFaQ02/3ambSmUBoxmlkJpeJxPuaCwsOdwUlhYN24UFtaxNeWZwsIULr+o/PEfuzBu0V5DVEhSe18ja27SvQEmhcUNOERcPPe/9cbMRc8W5fF2J27o9osvnwc6qW3ztgfaykdkTYDCwp7RQWFh3bhRWFjH1pRnCgtTuHy+8rRl+/HuT9uNfg7rUhvdm5XzTJ8pLDJw/n5DNPrP2WT8vq+cxNWhqmfGgk/xaQIUFj49vOyclxOgsLBugCgsrGNryjOFhSlcPl05bSI7sENVvHhLFc/1l8IiU9YzVly7kFDKWx1rolerCp4bEz7JJwlQWPjksLJTNiFAYWHdQFFYWMfWlGcKC1O4fLbyXztO4OmZ64ylN0+2rIC3OtZw+RhILVAoLLLE+Olfe/DRn7uNz0d2q4sHGpfRgpxO/JOAI7GRE3By587tnxDYaxLIIQJy87pjGVtYWNgNrWA+pjYoFBZq/LRZM5C1obStozX7z6L71NWIS0zGvQ1KYfT9ObBZmMIiy/iRzfTv/7wDXyzbD7naYuJjjXB7reK2jTc2PGcJJCUlQW5ILlasmHEcKgsJkIDnCMiRtCdPnjTuPJF7V9IW5mNq40BhocZPmzUDWRtKWzrafeIi7puwAhfjEnFrjWJG0hqSE3cnUFhkGz8iLl79bgvmrD2MsJBAfPNMc9QtHWHLmGOjc57AsWPHjJumRVzIZWS86T3nx4Qt8G0C8jdcLtsTUREREWHcd5G+MB9TiwEKCzV+2qwZyNpQ2s7R6Utx6PLZckSfi0WT8oXwVa8mCAu58Q2KxzpFYeEUdWJSMnp/tRZRu06haL5cWNCnJUpGcCmLU3CskIGAJDlyEZqICxYSIAHPERBRUbx48UzFPPMxtXGgsFDjp82agawNpa0cXU1IwqNfrMa6g+dQvnA4vn++JQrmCc25PlBYuMT+4tUEdJu4ErtOXESNEvkx99nmyJsr2CVbViKB9ARkWVRCQgLBkAAJeIBASEhIhuVPaR/LfExtECgs1Phps2Yga0NpG0fytnLAN5vw/YYjyB8WjHnPt0TlYnlztv0UFi7zjz53BV0+WwGZcWpfvRim9GiMINl8wUICJEACJGBbAszH1IaOwkKNnzZrBrI2lLZx9NnivRj1+y4jGZ3xRBO0qlIk59tOYWFqDDYePo8HJ680NtzLKV5DOtU0Zc/KJEACJEAC3kWA+ZjaeFBYqPHTZs1A1obSFo5+3XLMuNFZyntdauMxT12A54wOhYUzQhk+/3nzMfSZdW0sPXqZoemW0oAESIAESMAZAeZjzghl/zmFhRo/bdYMZG0ovd7RlugY3D95Ba4mJKNni/IYek8t72kzhYVbY5F29mnmk03QorIXzD651RMakQAJkIB/E2A+pjb+FBZq/LRZM5C1ofRqR2cuxaHjp8twLOYq2lYtiqmPN0ZwThwrmxUlCgu34kf2ywz8ZhPmbTiCwnlC8dNLrVCiAE+KcgsmjUiABEggBwkwH1ODT2Ghxk+bNQNZG0qvdSS3afeYthrL955BxaJ5ML9PS+QPC/Gu9lJYuD0ecsLXvRNWYPuxC6hfJgJznmmGXME5dGyw272gIQmQAAn4NwHmY2rjT2Ghxk+bNQNZG0qvdTT6910Yv3gvwkODjLsPqtyUz/vaSmGhNCaHzlxBp/HLEBObgMealcV7Xeoo+aMxCZAACZCAZwkwH1PjTWGhxk+bNQNZG0qvdPTXjhPoNWOt0bZPHqqPzvVLeWU7QWGhPC6Ld53Ek9P/QUoKMPr+eujWqLSyTzogARIgARLwDAHmY2qcKSzU+GmzZiBrQ+l1juQtdsdP/8aFq4net1k7PS0KCy3xM3bhboxduAe5ggMx7/kWqFWygBa/dEICJEACJGAtAeZjanwpLNT4abNmIGtD6VWOru4/iHc+no/FSREoUbsy5jzdHKHBgV7VxhsaQ2GhZWySk1PQa8Y/WLzrFMoUyo2fXmiNAuFetp9GS0/phARIgAR8iwDzMbXxpLBQ46fNmoGsDaX3OJo6FclPPY3AlGQkBQTi4ifjEfHic97TvsxaQmGhbXzOX4k39lscPhtr3MwtJ4AFBPBmbm2A6YgESIAELCDAfEwNKoWFGj9t1gxkbSi9w1F0NFLKlUNAcvJ/7QkKAg4cAEp78Zp7Cgut8bP1SAzunbgC8YnJGNKxJp5sVUGrfzojARIgARLQS4D5mBpPCgs1ftqsGcjaUHqFo6Pf/4KS996dsS2LFwORkV7RxkwbQWGhfWy+WnkAQxZsQ2hQIL7vw/0W2gHTIQmQAAloJMB8TA0mhYUaP23WDGRtKHPckbydfnr4fEwd2g1BcjSQo3DGQv/Y2EAIyeV5T321Dgt3nDDuL/npxVYIDw3Wz4IeSYAESIAElAkwH1NDSGGhxk+bNQNZG8ocdzTi1x2YvORf9NyxEG//MBbGqnoRFZMnA7165Xj7sm2ADRL1G9pvk/aeuxyPOz/5G8cvXMVDN5fBB/fV9e44YOtIgARIwE8JMB9TG3gKCzV+2qwZyNpQ5qijZXtO47Gpq402TLq/Fu5ofH1N/a5dQNWqOdo2lx5uk0Q9tS82au+Kfafx6BerjfstPnukIe6uW8KlIWElEiABEiABzxFgPqbG2i+FxYQJEzBq1CgcO3YMtWrVwtixY9G6detMSUZGRmLJkiUZPrvrrrvw888/G7/v2bMnZsyYcUOdpk2bYtWqVS6PDgPZZVReW/Hs5XjcMXYpTl6MwyNNy2L4bRWBvHmvtffSJSBPHq9tux0TdaPNNhIW0lzH7euV48/h68jCKNqwjndv5vf+iGULSYAESEArAeZjajj9TljMmTMH3bt3h4iLli1bYvLkyfjiiy+wfft2lC1bNgPNs2fPIj4+PvX3Z86cQb169QwbERQOYXHixAl8+eWXqfVCQ0NRqFAhl0eHgewyKq+smHYdfSVjHX1r5E64SmFh9WjZTFgkJCVj8uNv4LlZHxr7b1ICAxHw+efev0TO6nGkfxIgARLwEgLMx9QGwu+EhcwkNGzYEBMnTkwlV6NGDXTp0gUjRoxwSlNmN4YMGWLMduS5/gZaBMb58+cxf/58p/ZZVWAgu43OKwxnrjqIt+ZvvfHkH5slvXacAbDbjAXsegyxV3zL2AgSIAESsJ4A8zE1xn4lLGTmITw8HHPnzkXXrl1TyfXt2xcbN27MdMlTerx16tRB8+bN8bm8ZbxeRFiIqJBZioiICLRt2xbvv/8+ihUr5vLoMJBdRuV1FfeevIS7x/2NuMRkvNWxJno57iqgsLB+rOzGWI4bbt8+IxdvP4bY+pHkE0iABEjAKwgwH1MbBr8SFkePHkWpUqWwfPlytGjRIpXc8OHDjT0Su2SDbTZlzZo1kBmP1atXo0mTJqk1ZXlV3rx5Ua5cOezfvx9vvfUWEhMTsW7dOuTKlStTj3FxcZAfR5FALlOmDGJiYpA/f361UaW1xwgkJiWj26SV2Hj4PFpXKYIZTzRBYOD125XtlvQKNbu12W7tjY4GypUD0lycKLeyJ/77L3KVL+exuOWDSIAESIAEMidAYaEWGX4pLFasWGHMOjiKzC7MnDkTO3fuzJbmM888A7HdsmVLtvVkmZSIjNmzZ+Pee+/NtO7QoUPxzjvvZPiMwkItoD1tPTFqHz78bSfy5QrG7/3boGRE7v+aYLekl8LCM+EzYQLQp4/xLBEVr93+Agr3fQ6D76jumefzKSRAAiRAAlkSoLBQCw6/EhYqS6GuXLmCEiVK4N1334UsnXJWqlSpgt69e2Pw4MGZVuWMhTOC3v/57hMX0XHcMsQnJWNUt7q4v3GZGxtNYWH9INqccdTPK9Bz6VnIJNfcZ1ugUbmC1jPjE0iABEiABCgsLIoBvxIWwlCWMjVq1Mg4FcpRatasic6dO2e7eXv69Ol49tlnceTIERQuXDjb4ZCTo2TJlezD6NGjh0tDR4XsEiavqSSn+9w7YQW2HIlB++rFMPXxxggIuL4EytFKmye9tjgi1wcYD/h5D+atP4IKRfLgl5daI3dokNfEORtCAiRAAv5GgPmY2oj7nbBwHDc7adKk1E3YU6ZMwbZt24zlSyIERBSkPyFK7rmQ38vyprTl0qVLkGVN9913nzGjceDAAbz++us4dOgQduzYgXz58rk0QgxklzB5TaXxi/Zg9B+7USB3CP7o3wY35Q/L2DYfSHq9/u4NH2AcExiK28csNW7lfqJlebzdqZbXxDkbQgIkQAL+RoD5mNqI+52wEFwyWzFy5EjjyNjatWtjzJgxaNOmjUFSLsQrX748ZIbCUXbv3o1q1arhjz/+QIcOHW4gHhsbaxxVu2HDBuPIWREX7dq1w7Bhw4zN2K4WBrKrpHK+3vajF9D5s2VISErB2Afro0uDUpk3ygeSXgoLC+Itk7hYsvsUHp+2xnjYrKeaokWlIhY8mC5JgARIgAScEWA+5oxQ9p/7pbBQQ2aNNQPZGq66vcYnJqPLZ8ux/dgF3FbzJkzu3ijjEijHQyksdOPP6M+HGL/+/RbMWn0IpSJyG7NgeXIFW8+PTyABEiABEriBAPMxtYCgsFDjp82agawNpaWOxi7cjbEL96BguCyBaoui+TI/TthohA8lvZZCVXHuQ4wvxSXijrFLEX0ulkuiVGKCtiRAAiSgQID5mAI8ABQWavy0WTOQtaG0zJGcAiUX4ckSqE8fboBO9Upm/ywfSnotg6rq2McYL919Cj2mrYGcAzDvuRZoUJanRKmGCO1JgARIwAwB5mNmaGWsS2Ghxk+bNQNZG0pLHCUnp+D+ySux7uA53FrjJkzpkc0SKEcLfCzptQSsqlMfZDxgzkbM23AE1Yvnww8vtEJocKAqJdqTAAmQAAm4SID5mIugsqhGYaHGT5s1A1kbSksczVx1EG/N34o8oUH4c0DbGy/Cy+qJPpj0WgJXxakPMj57OR63frwE8r8v31YVL7SvokKItiRAAiRAAiYIMB8zASuTqhQWavy0WTOQtaHU7uh4zFUj0ZM18O/cUwuPtyjv2jN8MOl1reMerOWjjBdsPIK+szciNCgQv/ZrjUpF83oQKh9FAiRAAv5LgPmY2thTWKjx02bNQNaGUrujZ2auxe/bTqB+mQh891wLBMk1ya4UH016Xem6x+r4KOOUlBT0/PIfyDG0TSoUwuynmiHQ1bjzGHw+iARIgAR8jwDzMbUxpbBQ46fNmoGsDaVWR79tPY5n/28dggMD8NNLrVC9eH7X/fto0us6AA/U9GHG0eeu4LYxS3ElPgnDu9bBI03LegAoH0ECJEAC/k2A+Zja+FNYqPHTZs1A1oZSm6MLVxPQ4eMlOHEhDn3aVcKg26ub8+3DSa85EBbW9nHGU5ftx7CftiNfrmAsHNg28xveLcRL1yRAAiTgbwSYj6mNOIWFGj9t1gxkbSi1OXpz/hb836pDKF84HL/1a4OwkCBzvn086TUHw6LaPs44KTkF905Yjk3RMbizdnFMfKyRRSDplgRIgARIQAgwH1OLAwoLNX7arBnI2lBqcSTHyt43cYXha9ZTTdGiUhHzfn086TUPxAILP2C849gFdPx0GURkTH/iZkRWK2YBSLokARIgARKgsFCPAQoLdYZaPFBYaMGoxUliUjLuGb8c249dQLdGpTH6/nru+fWDpNc9MBqt/ISxLIeSZVHlCofjd3dmzzQipysSIAES8GUCzMfURpfCQo2fNmsGsjaUyo6mL9+PoT9uR4HcIVg0sC0K583lnk8/SXrdg6PJyk8YX7yagFs+WoKTF+PQ/9aq6Hsr77bQFEF0QwIkQAI3EGA+phYQFBZq/LRZM5C1oVRydOpiHNqPjsLFuES816U2HmtWzn1/fpL0ug9Ig6UfMf5h01G89PUG5AoOxJ/926Js4XANAOmCBEiABEggLQHmY2rxQGGhxk+bNQNZG0olRwO+2Yh564+gbukC+P75lq7fWZHZU/0o6VWCrmLsR4zlbovHpq7G8r1n0K5aUUzreTMCAly8U0WFMW1JgARIwI8IMB9TG2wKCzV+2qwZyNpQuu1ozf6zeGDySkiuNv/5lqhXJsJtX4ahHyW9aqAUrP2M8b5Tl3DH2KVISErB5O6NcHut4grwaEoCJEACJJCeAPMxtZigsFDjp82agawNpVuOZMO2nLyz8/hFPNykLEbcW8ctPzcY+VnSqw7MDQ9+yHjkbzsxIWofSkXkxp8D2iA8NNgNcDQhARIgARLIjADzMbW4oLBQ46fNmoGsDaVbjhwXkUWEh2DxwEgUzBPqlh8KC3Vspjz4obC4Ep+IDh8vxZHzsXg+shJeucPkxY2mALMyCZAACfgXAeZjauNNYaHGT5s1A1kbStOOTl64ivYfLcGluERjpkJmLLQUP0x6tXAz48RPGf++7TiembkOIUEB+LVvG1QultcMNdYlARIgARLIggDzMbXQoLBQ46fNmoGsDaVpR/1mb8D8jUeNPRXfP9cCgYGaNsT6adJregBUDPyUsWzkfnL6P1i86xQiqxXF9CeaqFCkLQmQAAmQwHUCzMfUQoHCQo2fNmsGsjaUphz9c+As7p90bcP2D31aoU7pAqbss63sp0mvPoAuePJjxvtPX8ZtY5YYG7m/7Hkz2lXnjdwuRAyrkAAJkEC2BJiPqQUIhYUaP23WDGRtKF12lJycgs6fLceWIzF4uEkZjLi3rsu2LlX046TXJT46Kvk54xG/7MDkpf+iYpE8+K1fG4QGB+qgSh8kQAIk4LcEmI+pDT2FhRo/bdYMZG0oXXb0zdrDeOXbzciXKxiLB0WiiLs3bGf1RD9Pel0eCJWKfs5YbuRuNzoKpy/F4827a6B364oqNGlLAiRAAn5PgPmYWghQWKjx02bNQNaG0iVHslFbEjK5afv1u6rj6TaVXLIzVcnPk15TrNytTMb45p/DeOU7CwWyu2NDOxIgARKwIQHmY2qDRmGhxk+bNQNZG0qXHH34205MjNqH8oXD8Uf/ttYsIWHS69JYKFUiY1i+pE9pgGhMAiRAAvYiwHxMbbwoLNT4abNmIGtD6dTRwTOXjXsA4pOS8UWPxri15k1ObdyqwKTXLWymjMjYwLX2wFl0u34IwY8vtELtUhoPITA1IKxMAiRAAvYmwHxMbfwoLNT4abNmIGtD6dTRMzPX4vdtJ9C6ShF89WQTBMiRUFYUJr1WUL3RJxmn8ug7ewMWbDyKJuULYc4zzayLa+tHlU8gARIggRwjwHxMDT2FhRo/bdYMZG0os3W0Yt9pPDJlNYIC5WKx1qh6Uz7rHsyk1zq2Ds9knMr4WEws2o9egtiEJHz6cAN0qlfSev58AgmQAAn4GAHmY2oDSmGhxk+bNQNZG8osHSUmJaPjp8uw8/hF9GheDu92rm3tQ5n0WstXvJPxDYzH/bUHH/+5GyULhGHRy5EICwmyfgz4BBIgARLwIQLMx9QGk8JCjZ82awayNpRZOvrf6oN44/utKJA7BFEvR6JgnlBrH8qk11q+FBYZ+F5NSMItHy3BkfOxeOWOang+srL1Y8AnkAAJkIAPEWA+pjaYFBZq/LRZM5C1oczUkRwvGzlqsXHe/9udauKJlhWsfSCTXuv5knGmjOdvOIJ+czYib65gLBkUicK672fxzMjyKSRAAiSQIwSYj6lhp7BQ46fNmoGsDWWmjj76Yxc+XbQXFYrkwe+euqGYMxbWDiqFRaZ80x4/65Elf9aPMp9AAiRAAh4jwHxMDTWFhRo/bdYMZG0oMzg6HnMVkaMX42pCMiY91hB31C5h3cPSeqawsJ4zGWfKeOW+M3h4yirjkII/+rdBpaJ5rR8LPoEESIAEfIAA8zG1QaSwUOOnzZqBrA1lBkeD5m7C3HXRaFyuIOY+29xzx3Ay6bVuUB2eyThLxr1nrMXCHSfQoeZNmNKjsfVjwSeQAAmQgA8QYD6mNogUFmr8tFkzkLWhvMHRjmMXcNe4v5GSAsx7vgUali1ozYMy88qk13rWZJwl470nL+H2sUuRlJyC2U83Q7OKha0fDz6BBEiABGxOgPmY2gBSWKjx02bNQNaG8gZHPaatwdLdp3B33RL47JGG1jwkK69Meq3nTcbZMn5z/hb836pDqFOqABb0aYnAQIsug7R+pPkEEiABEvAIAeZjapgpLNT4abNmIGtDmepIBIUIi5CgAPw1IBJlC4frf0h2Hpn0Ws+bjLNlfPpSHCJHRUFORRv7YH10aVDK+jHhE0iABEjAxgSYj6kNHoWFGj9t1gxkbSgNR7L84+5xfxuX4T3ZsgKGdKqp9wGueGPS6woltTpk7JTfZ4v3YtTvu1AqIjf+GtiWl+Y5JcYKJEAC/kyA+Zja6FNYqPHTZs1A1obScDR37WEM+nYz8ofJWf7trL8ML7PmM+nVO6hk7BbP2PgktP8oCsdirmLwHdXxXGQlt/zQiARIgAT8gQDzMbVRprBQ46fNmoGsDSUkkWo3OgrHL1zF63dVx9NtciiRorDQN6hZeSJjlxh/uy4aL8/dZAjtv19pjwLhIS7ZsRIJkAAJ+BsB5mNqI05hocZPmzUDWRtKTIzahw9/25nzSz+Y9OobVAoLJZayNPCuT/7GrhMX8UzbinjtzhpK/mhMAiRAAr5KgPmY2shSWKjx02bNQNaDMuZKAlqPXIQLVxMx5sF66NqgtB7H7nihsHCHmjkbMnaZ1187TqDXjLXIFRyIqEGRKFEgt8u2rEgCJEAC/kKA+ZjaSFNYqPHTZs1A1oNSZipkxqJ68Xz4+aXWxs3DOVaY9FqPnoxdZpySkoIHJq/EPwfO4aGby+CD++q6bMuKJEACJOAvBJiPqY00hYUaP23WDGR1lCcuXEXbUYtxNSEZUx9vjFtq3KTuVMUDk14Veq7ZkrFrnK7XWnvgLLpNWgnR23/0b4vKxfKasmdlEiABEvB1AszH1EbYL4XFhAkTMGrUKBw7dgy1atXC2LFj0bp160xJTp8+HU888USGz2JjYxEWFpb6ezM+M3sQA1ktkMX69e+3YNbqQ2hcriDmPtscAQE5OFshDWLSqz6ozjyQsTNCGT7vPeMfLNxxEnfWLo6JjzUybU8DEiABEvBlAszH1EbX74TFnDlz0L17d4gQaNmyJSZPnowvvvgC27dvR9myZTPQFGHRt29f7Nq164bPihcvnvrfZn1SWKgFbWbW+09fxq0fLzHurxBRcXP5QvofYtYjk16zxMzXJ2PTzHYdv4g7PlmKlBRgfp+WqF8mwrQPIWCAjAAAIABJREFUGpAACZCArxKgsFAbWb8TFk2bNkXDhg0xceLEVHI1atRAly5dMGLEiEyFRb9+/XD+/PksSZv1SWGhFrSZWb8waz1+2nwMt1Qvhqk9b9b/AHc8Mul1h5o5GzI2x+t67YHfbMJ366PRvGJhzHqqac7P7rnVCxqRAAmQgH4CFBZqTP1KWMTHxyM8PBxz585F165dU8nJjMTGjRuxZMmSTIVF7969UapUKSQlJaF+/foYNmwYGjRoYNR1xyeFhVrQprfeEh2DTuOXQVY+/fJSa9QokV/vA9z1xqTXXXKu25Gx66zS1Iw+dwXtRy9BfFIyvnqyCdpULeqWHxqRAAmQgK8RoLBQG1G/EhZHjx41BMLy5cvRokWLVHLDhw/HjBkzMix3kgqrVq3C3r17UadOHUiwffLJJ/jll1+wadMmVKlSBe74FL9xcXHGj6OI7zJlyiAmJgb583tJYqwWWx6z7j51Nf7ecxpdG5TCmAfre+y5Th/EpNcpIuUKZOw2wmE/bcfUZftRq2R+/PhCKwTm5AlqbveChiRAAiSglwCFhRpPvxQWK1asQPPmzVPJvf/++5g5cyZ27tzplGZycrKxlKpNmzYYN25cqrAw63Po0KF45513MjyPwsLpENxQYcXe03jki9UICQrAXwMiUbZwuDkHVtZm0msl3Wu+ydhtxmcvx6PtyMW4GJeITx9ugE71Srrti4YkQAIk4CsEKCzURtKvhIWuZUtPPfUUoqOj8euvv7q9FIozFmqBK9ZyLn/XCSuw8fB5PN68HN7pXFvdqU4PTHp10szcFxkrMf5k4R6MWbgbFYvmwR/92iA4KFDJH41JgARIwO4EKCzURtCvhIWgko3WjRo1Mk6FcpSaNWuic+fOmW7eTo9XktkmTZoYS6OmTZtmfKzqU3wwkM0H8sLtJ9D7q7XIHRKEJa9Eoli+/47/Ne/NAgsmvRZATeeSjJUYX7yagDYjF+PclQSMvr8eujXKwZvqlXpCYxIgARLQQ4D5mBpHvxMWjqNhJ02aZCyH+vzzzzFlyhRs27YN5cqVQ48ePYx9GI4TomS5UrNmzYz9FBJssvxJlk3JPg0RGFKc+XRliBjIrlD6r05ycgru/nQZdhy7gOciK2HwHdXNOfBEbSa91lMmY2XGk5fsw4hfd6JModzGcsLQYM5aKEOlAxIgAdsSYD6mNnR+JywEl8xWjBw50rggr3bt2hgzZoyxZ0JKZGQkypcvD7m/Qkr//v0xb948HD9+HAUKFDBOg5L9EWn3aDjz6coQMZBdofRfnZ83H0OfWeuRL1cw/h7cDhHhoeYceKI2k17rKZOxMuPY+CS0HrkYpy/F4f2utfFo03LKPumABEiABOxKgPmY2sj5pbBQQ2aNNQPZda5yCd5tY5Zg36nL6HdrFfS7tarrxp6syaTXetpkrIXx9OX7MfTH7SiePwxRgyIRFhKkxS+dkAAJkIDdCDAfUxsxCgs1ftqsGciuo5y3PhoDvtmEiPAQLH2lHfKHhbhu7MmaTHqtp03GWhjHJSah3agoHI25irc61kSvVhW0+KUTEiABErAbAeZjaiNGYaHGT5s1A9k1lAlJybj14yU4eOaKsa9C9ld4bWHSa/3QkLE2xrPXHMKr87agcJ5QQ7DnyRWszTcdkQAJkIBdCDAfUxspCgs1ftqsGciuoXQkP0XyXkt+wkO9OPlh0uvaoKrUImMVejfYphXtg26vhj7tKmvzTUckQAIkYBcCzMfURorCQo2fNmsGsnOUaZdrDOlYE096+3INJr3OB1W1BhmrErzBfv6GI+g3ZyPyh8mhCO1RILeXLjPU2ms6IwESIIH/CDAfU4sGCgs1ftqsGcjOUc6dvxLz5kThUtkKmPve/d6/wZRJr/NBVa1BxqoEb7CXgxHuGLsUe05ewkvtK2PAbdW0+qczEiABEvB2AszH1EaIwkKNnzZrBnL2KOMnT0HQc88iKCUZyYGBCPz8c6BXL238LXHEpNcSrDc4JWPtjH/begzP/t965JWjnF9ph4J5vPAoZ+29pkMSIAESuEaA+ZhaJFBYqPHTZs1AzgZldDSSy5VDYHLyf5WCgoADB4DSXnxTMJNebd+PLB2RsXbGKSkpuHvcMmw/dgF92lXCoNu98PJJ7b2mQxIgARKgsNARAxQWOihq8EFhkTXEq38sRNjtHTJWWLxYbjTUQN8iF0x6LQKbxi0ZW8L4923H8czMdcgTGmTstSjEWQtLONMpCZCA9xFgPqY2JhQWavy0WTOQs0b5v2+X4aEH2iAoJYUzFtoiLgtHdkvU7dZewW6DNsusRcdPl2Hb0QvGkc5ytDMLCZAACfgDAeZjaqNMYaHGT5s1AzlzlFfiE9H6w8W4ZcVP+OC3cQiUarIMavJk7rHQFn02ngGwQZKeYZhs0uY/t5/AU1+tRXhoEJZx1sKKbxt9kgAJeCEB5mNqg0JhocZPmzUDOXOUk5fsw4hfd6JcwTD89WoHBCMF2LULqFpVG3vLHNkkgbyh/3Zrs93aa5MZC2mmzFp0Gr8MW49cwLNtK+HVOzlrYdnfCjomARLwGgLMx9SGgsJCjZ82awZyRpQyW9Hqw8U4ezkeo++pjm4tr1/YdekSkCePNvaWOWLSaxnaVMdkbCnjhdtPoPf1WQs5Iapw3lyWPo/OSYAESCCnCTAfUxsBCgs1ftqsGcgZUU5asg8fyGxF4XD89WxjBOfPf60ShYW2uMvgyG6Jut3aa6MZC8esxT3jl2PLkRg806YiXrurhnWxR88kQAIk4AUEmI+pDQKFhRo/bdYM5BtRXo5LROuR12cr7q+HbtULAnnzUlhoi7gsHNktUbdbe20mLKS5f+04gV4z1iJ3iJwQ1Q5FOGth9beQ/kmABHKQAPMxNfgUFmr8tFkzkG9E6ZitKF84HAsHtEXw1VgKC23Rlo0juyXqdmuvDYWF7LXo8tlynNi+Dy+WScGj3W/17vtjPPE94TNIgAR8lgDzMbWhpbBQ46fNmoH8H8q0sxUf3V8P9zUqbYsjOjMEA5Nebd+PLB2RsfWMAex8bwyqDBloHPmcEhiIADvcfO8RMnwICZCArxFgPqY2ohQWavy0WTOQ/0M5MWofPvxtJyoUyYM/+7dBcFAghYW2SHPiyG6Jut3aa8MZC0RHI6VcOQTY7eZ7T31n+BwSIAGfIsB8TG04KSzU+GmzZiBfQymzFa0+XIRzVxLw8QP1cG/D0tc/uMylUNqiLRtHdkvU7dZeOwoLueG+ffuMQSO/9+ab7z3xfeEzSIAEfI4A8zG1IaWwUOOnzZqBfA2l496K1L0VMlthx2SMbdb23cjWEYWF9Zyjo4Fy5YA0MxbJgYEIPHiQey2sp88nkAAJeJgA8zE14BQWavy0WTOQgdj4JLQeuQinL8VjVLe6uL9xmf/4MoHUFms+lagzLjwTFxMmAH36GM9KDAjEO3e/hIFzPkREeKhnns+nkAAJkICHCDAfUwNNYaHGT5s1AxmYtmw/3v1pO0oXzI3FL0cixDFbwbf/2uLMqSO7Jep2a6/NYzkFQI8h3+DvuHC81L4yBtxWzWlIsQIJkAAJ2IkA8zG10aKwUOOnzdrfA/lqQhLajlqMExfiMLxrHTzStOyNbJlAaos1zlh4BmWWT7F5LP+y5l88/9125AsLxrLB7VEgd0gOA+XjSYAESEAfAX/Px1RJUlioEtRk7++BPHPlAby1YBtKFAhD1KBI5AoOorDQFFum3Ngt6bVbe20+YyHNT754Ebd/vg57Tl7CgA5V8dItVUyFGCuTAAmQgDcT8Pd8THVsKCxUCWqy9+dAjk9MRuSoxTgacxXvdq6FHs3LZ6TKBFJTpDlxYzfOdmuvDwgLXLqEBXvOo+/sjcZsxfJX2yNvrmDPxCefQgIkQAIWE/DnfEwHWgoLHRQ1+PDnQJ695hBenbcFxfLlwtJX2iEsJN1shY8kY8iTR0OkWOzCbom63drrI7GclDscHT5egn9PX8Yrd1TD85GVLQ5MuicBEiABzxDw53xMB2EKCx0UNfjw10BOSEpG+4+icPhsLN68uwZ6t66YOU0mkBqizAUXduNst/b6iLAQkTxvfTQGfLMJhfKEYtngdggP5ayFC98wViEBEvByAv6aj+kaFgoLXSQV/fhrIH+7Lhovz92EwkZy0h65QzOZrfChZEwxTKw3t1uibrf2+lAsJyYl45aPl+DgmSt4464aeKpNFi8FrI9aPoEESIAEtBHw13xMF0AKC10kFf34YyAnJaekLqd49c7qeLZtpawpMoFUjDAXze3G2W7t9SFhIV355p/DeOW7zSiSN5cxa5HpMkYXQ4/VSIAESMAbCPhjPqaTO4WFTpoKvvwxkBdsPGJsAI0IDzFmK7LdAMoEUiG6TJjajbPd2utjwkKWMkaOisKR87F4555aeLxFJgcvmAg/ViUBEiCBnCbgj/mYTuYUFjppKvjyt0BOTk7BHZ8sxe4TlzCwQ1W86OzISiaQCtFlwtRunO3WXh8TFtIdx1HRJY2jotshNDjQRMCxKgmQAAl4FwF/y8d006ew0E3UTX/+Fsi/bzuOZ2auQ75cwVj2qguXbDGBdDOyTJrZjbPd2uuDwkIut2w9cjFOXYzDyPvq4oGby5gMOlYnARIgAe8h4G/5mG7yFBa6ibrpz58COSUlBZ0/W47N0THo064SBt1e3Tk1JpDOGemoYTfOdmuvDwoL6dLnS/dh+C87UaFIHiwc0BZBgQE6opE+SIAESMDjBPwpH7MCLoWFFVTd8OlPgfz3nlPoPnUNwkICsXxwexTOm8s5MSaQzhnpqGE3znZrr48Ki8txiWj54SKcv5KAcQ83wD31SuqIRvogARIgAY8T8Kd8zAq4FBZWUHXDpz8F8oOTV2L1/rN4omV5vN2plmu0mEC6xkm1lt042629PiospFufLNyDMQt3o3rxfPjlpdYI5KyF6reR9iRAAjlAwJ/yMSvwUlhYQdUNn/4SyGsPnEW3SSsREhRg3LJdokBu12gxgXSNk2otu3G2W3t9WFjEXEkwZi0uxSViSo/G6FDzJtVopD0JkAAJeJyAv+RjVoGlsLCKrEm//hLIT3y5Bot3ncJDN5fBB/fVdZ0SE0jXWanUtBtnu7XXh4WFdO2DX3di0pJ9qFcmAvOfb4GAAO61UPk60pYESMDzBPwlH7OKLIWFVWRN+vWHQN56JAYdP10GWSGxaGAkyhfJ4zolJpCus1KpaTfOdmuvjwuL05fi0OrDRbiakIz/69UUraoUUYlG2pIACZCAxwn4Qz5mJVQKCyvpmvDtD4H8/P/W4Zctx9G5fkl88lADE3QAMIE0x8vd2nbjbLf2+riwkO4N/WEbpq84gGYVC2H2083djUTakQAJkECOEPCHfMxKsBQWVtI14dvXA3nvyYvoMGYpUlKA3/u1QbXi+UzQobAwB0uhtt0Sdbu11w+ExbGYWLQZuRgJSSn47rnmaFSukEJA0pQESIAEPEvA1/Mxq2lSWFhN2EX/vh7IA7/ZhO/WRxsbOmVjp+nCBNI0MrcM7MbZbu31A2EhXXz1u82Y/c9htKtWFF8+0cStUKQRCZAACeQEAV/Px6xmSmFhNWEX/ftyIB8+ewWRo6OQlJyC+X1aon6ZCBeppKnGBNI8M3cs7MbZbu31E2Fx4PRltP8oCskpMI6erVkyvzvRSBsSIAES8DgBX87HPAGTwsITlF14hi8H8pAFW/HVyoNoVbkI/q93UxdoZFKFCaR73Mxa2Y2z3drrJ8JCuvnCrPX4afMxdKpXEp8+bHJPldm4ZX0SIAES0ETAl/MxTYiydUNh4QnKLjzDVwP51MVrp8TEJSZjVu+maFHZzVNimEC6EEUaqtiNs93a60fCYtvRGNw97topcItfjkS5wiZOgdMQynRBAiRAAu4Q8NV8zB0W7tj4pbCYMGECRo0ahWPHjqFWrVoYO3YsWrdunSm/KVOm4KuvvsLWrVuNzxs1aoThw4ejSZP/1g337NkTM2bMuMG+adOmWLVqlctj4quBPPK3nZgQpeFceyaQLseSUkW7cbZbe/1IWEhXe365BlG7TuGRpmUxvGsdpdCkMQmQAAl4goCv5mOeYCfP8DthMWfOHHTv3h0iLlq2bInJkyfjiy++wPbt21G2bNkM3B999FGjXosWLRAWFoaRI0di3rx52LZtG0qVKmXUF2Fx4sQJfPnll6n2oaGhKFTI9dNQfDGQL1xNQMsRi3AxLhGTuzfC7bWKux/XTCDdZ2fG0m6c7dZePxMWa/afxQOTVyI0KBDLBrdDsfxhZqKRdUmABEjA4wR8MR/zJES/ExYyk9CwYUNMnDgxlXONGjXQpUsXjBgxwin7pKQkFCxYEOPHj0ePHj1ShcX58+cxf/58p/ZZVfDFQJ4YtQ8f/rYTlYvlxR/92iBQ1kS4W5hAukvOnJ3dONutvX4mLKS73SauwNqD5/BMm4p47a4a5uKRtUmABEjAwwR8MR/zJEK/Ehbx8fEIDw/H3Llz0bVr11TOffv2xcaNG7FkyRKn7C9evIhixYoZPjp27JgqLERUyCxFREQE2rZti/fff9+o52rxtUC+mpCEVh8uhtzEO/r+eujWqLSrKDKvxwRSjZ+r1nbjbLf2+qGw+GvHCfSasRZ5QoOw4tVbUCA8xNVoZD0SIAES8DgBX8vHPA3Qr4TF0aNHjeVLy5cvN5Y2OYrsmZA9Ert27XLKv0+fPvj999+NPReyNEqKLK/KmzcvypUrh/379+Ott95CYmIi1q1bh1y5cmXqMy4uDvLjKBLIZcqUQUxMDPLnt//RjDNXHcRb87eiVERuRA2KREhQoFO22VZgAqnGz1Vru3G2W3v9UFikpKTgzk/+xs7jFzGwQ1W8eEsVV6OR9UiABEjA4wQoLNSQ+6WwWLFiBZo3b55KTmYXZs6ciZ07d2ZLU/ZXfPDBB4iKikLdunWzrCubwkVkzJ49G/fee2+m9YYOHYp33nknw2e+ICwSk5LR7qMoHD4bi6GdaqJnywpqUeqHyZg6MDc92C1Rt1t7/TSWF2w8gr6zN6JQnlAsH9weuUOD3AxQmpEACZCAtQQoLNT4+pWwUFkKNXr0aLz33ntYuHAhGjd2fnN0lSpV0Lt3bwwePNjvZiwsSSKYQKp90121thtnu7XXT4WFvGxo/9ESHDp7BW93qokndLxscDWmWY8ESIAETBCgsDABK5OqfiUspP+yeVuOjJVToRylZs2a6Ny5c5abt+VoWhEVsgSqWbNmTomfOXPGWHL1+eefp27wdmbkK4Fs2bIHJpDOQkjP53bjbLf2+qmwkG7/36qDeHP+VpQsEIaoQe0QGqy4PFJPxNMLCZAACdxAwFfysZwaVr8TFo7jZidNmmQsh5LkX+6qkONjZfmSnPQkosBxQpQsf5I9E7NmzTKOnXUU2VMhP5cuXYIsa7rvvvtQokQJHDhwAK+//joOHTqEHTt2IF++fC6Nra8E8qKdJ/DkdAs2ajKBdCmOlCvZjbPd2uvHwkIOdGg9cjHk0kwtBzooBzsdkAAJkEBGAr6Sj+XU2PqdsBDQMlshgkH2QtSuXRtjxoxBmzZtjDGIjIxE+fLlMX36dOO/5f8fPHgww/i8/fbbhqCIjY01jqrdsGED5MhZERft2rXDsGHDjM3YrhZfCWTLjpZkAulqKKnVsxtnu7XXj4WFdN1xBHWVYnnxu+oR1GqRTmsSIAESyJSAr+RjOTW8fikscgp2ds/1hUD+58BZ3D/JosuwmEB6Jmztxtlu7fVzYZH20swpPRqjQ82bPBPXfAoJkAAJuEjAF/IxF7tqSTUKC0uwmnfqC4Hca/o/+GvnSTzcpAxG3Jv1qVnm6QBgAukWNtNGduNst/b6ubCQ7n/w605MWrIPjcoVxHfP/Xfst+lYpQEJkAAJWEDAF/IxC7C47JLCwmVU1la0eyDvOn4Rt49dioAA4K8BbVGxaF69wJhA6uWZlTe7cbZbeykscPLCVePyzPikZMx9tjluLl/IM7HNp5AACZCACwTsno+50EVLq1BYWIrXded2D+QB32zEvPVHcGft4pj4WCPXO+5qTSaQrpJSq2c3znZrL4WFEZ+vzduCr9ccQvvqxTCt581qMUtrEiABEtBIwO75mEYUbrmisHALm34jOwfykfOxaDtyMRKTU7CgT0vUKxOhHxATSP1MM/NoN852ay+FhRF1+09fRvuPopCSAmMTd7Xirp2e55kvAZ9CAiTgzwTsnI95w7hRWHjDKACwcyC/++N2TFu+H80rFsbXTzu/58Mt5Ewg3cJm2shunO3WXgqL1JB8/n/r8MuW47i3QSl8/GB906FKAxIgARKwgoCd8zEreJj1SWFhlphF9e0ayOcux6PFB4sQm5CEGU82QduqRa0hxATSGq7pvdqNs93aS2GRGnGbo8/jnvHLERwYgKhBkShdMNwzMc6nkAAJkEA2BOyaj3nLoFJYeMlI2DWQP1m4B2MW7kbNEvnx80utECC7t60oTCCtoJrRp9042629FBY3xNyjX6zC8r1n0LNFeQy9p5ZnYpxPIQESIAEKC8tigMLCMrTmHNtRWMTGJ6Hlh4tw9nI8PnmoPjrXL2Wu02ZqM4E0Q8v9unbjbLf2UljcEJt/7zmF7lPXIHdIEFa82h4F84S6H7u0JAESIAENBOyYj2notjYXFBbaUKo5smMgz1hxAG//sA1lCuXG4oGRCA4KVIOQnTUTSOvYpvVsN852ay+FxQ1xnJKSgo6fLsO2oxfQ79Yq6HdrVc/EOZ9CAiRAAlkQsGM+5k2DSWHhJaNht0BOTEpG5OgoRJ+LxbDOtdC9eXlrSTKBtJavw7vdONutvRQWGeL4p81H8cKsDYgIDzFmLcJDgz0T63wKCZAACWRCwG75mLcNIoWFl4yI3QJ5wcYj6Dt7IwrnCcXyV9sjLCTIWpJMIK3lS2HhGb4UFhk4JyWnGEfPHjxzBe/cUwuPt7D4JYXnRppPIgESsCEBu+Vj3oaYwsJLRsROgSzLF+4atww7jl3AwA5V8eItVaynSGFhPWM7Jr2MC5+Ii5mrDuKt+VtRumBuRL1s8bJKzxDjU0iABGxKwE75mDciprDwklGxUyAv3X0KPaatQXjotQ2XEeEe2HDJBNIzkWo3znZrrx3FmwfafDUhCS0/WIQznjgIwjPfJD6FBEjApgTslI95I2IKCy8ZFTsFsuOIyCdalsfbnTx0RCQTSM9Eqt042629HkjSLQkUD3Ae99cefPynB46utgQQnZIACfgKATvlY97InMLCS0bFLoG8JToGncYvQ1BgAJZ48lIrDyQ22kOBbdaONINDMraesYfEUNrLNmf2aoLWVSy6bNMzxPgUEiABmxKwSz7mrXgpLLxkZOwSyC/MWo+fNh9Dl/olMfahBp6jxwTSM6ztxtlu7fVQkq49WDzEeegP2zB9xQG0qlwE/9e7qfZu0CEJkAAJOCNgl3zMWT9y6nMKi5win+65dgjkQ2euIHL0YiSnAL+81Bo1S+b3HD0PJTZaO8Q2a8WZqTMytp6xB8XQ4bPyNyYKclLUTy+2Qu1SBTzTPz6FBEiABK4TsEM+5s2DRWHhJaNjh0AesmArvlp5EG2qFsVXTzbxLDkmkJ7hbTfOdmuvB5N0rQHjQc59Z2/Ago1H0aleSXz6sAdnRbUCozMSIAG7ErBDPubNbCksvGR0vD2Qz16OR4sP/sLVhGTM6t0ULSoX8Sw5DyY22jrGNmtDmaUjMraesYfF0LajMbh73DIEBgBLBrVDmULhnukjn0ICJEACALw9H/P2QaKw8JIR8vZAHrtwN8Yu3IM6pQrghxdaIiAgwLPkmEB6hrfdONutvR5O0rUFjYc5d5+6Gn/vOY3Hm5fDO51ra+sGHZEACZCAMwLeno85a39Of05hkdMjcP353hzIsfFJxmzFuSsJGP9IA3SsW9Lz1Dyc2GjpINusBWO2TsjYesY5IIZW7D2NR75YjbCQQKx49RYUyuOBu3I8Q5JPIQES8HIC3pyPeTk6o3kUFl4ySt4cyF+tPIAhC7ahbKFwLBrYFsFBgZ6nxgTSM8ztxtlu7c2BJF1L4HiYc0pKCu4ZvxxbjsSg7y1V0L9DVS3doBMSIAEScEbAm/MxZ233hs8pLLxhFLx4TV9iUjLafRSFw2djMaxzLXRvXj5niHk4sdHSSbZZC0bOWFiP0ekTciCWf9x0FC9+vQEFw0OMWYvcoUFOm8kKJEACJKBKgMJCjSCFhRo/bdbeGsiOf9xlKcLywe1z7h/3HEhslAeXbVZG6NQBGTtFpKVCDnCWlxpy9Gz0uRx+qaEFIJ2QAAnYhYC35mN24Udh4SUj5Y2BnHY5Qr9bq6DfrTm4HCEHEhvl0GCblRE6dUDGThFpqZBDnGesOIC3f7i2DHPxy5EIkqOiWEiABEjAQgLemI9Z2F3trikstCN1z6E3BvKKfafxyBQv2UCZQ4mNe6N53YptVsLnkjEZu4RJuVIOcb4Sn4gWHyzC+SsJ+OyRhri7bgnlrtABCZAACWRHwBvzMTuNGIWFl4yWNwZyzy/XIGrXKXRvVg7DuuTwkY85lNgohQfbrITPJWMydgmTcqUc5PzxH7swbtFe1CtdAPP75MBR18rw6IAESMBOBLwxH7MTPwoLLxktbwvknccv4I6xfxuXVMkShHKF8+QsqRxMbNzuONvsNjqXDcnYZVRKFXOQ8+lLcWj5wSLEJSZj9tPN0KxiYaWu0JgESIAEOGNhXQxQWFjH1pRnbxMWA77ZiHnrj+DuOiXw2aMNTfXFkso5mNi43R+22W10LhuSscuolCrmMOc3vt+C/60+hPbVi2Faz5uVukJjEiABEqCwsC4GKCysY2vKszcJi2MxsWj94WIkJqdgQZ+WqFcmwlRfLKmcw4mNW31im93CZsqIjE3hcrtyDnPef/oy2n8UhZQU4I/+bVD1pnxud4WGJEACJEBhYV1StT6IAAAgAElEQVQMUFhYx9aUZ28SFsN/2YHPl/6LphUKYc4zzU31w7LKOZzYuNUvttktbKaMyNgULrcrewHnZ2euw2/bjqNbo9IYfX89t7tCQxIgARKgsLAuBigsrGNryrO3CIsLVxPQYsQiXIpLxLSejdG++k2m+mFZZS9IbEz3jW02jcy0ARmbRuaWgRdwXn/oHO6dsAIhQQH4+5X2KF4gzK2u0IgESIAEKCysiwEKC+vYmvLsLcJi0pJ9+ODXnahSLC9+79cGgd5ybrwXJDamBlQqs82mkZk2IGPTyNwy8BLOD0xaiTUHzuKZthXx2p013OoKjUiABEiAwsK6GKCwsI6tKc/eICziE5PReuQinLgQh1Hd6uL+xmVM9cHSyl6S2JjqI9tsCpdblcnYLWymjbyE88LtJ9D7q7XIlysYK15rj3xhIaa7QgMSIAESoLCwLgYoLKxja8qzNwiLuWsPY9C3m3FT/lzGUoP/b+8+wKsq0j+O/5LQpIMC0gwgIGKjSQeDHXVt+7euDVFQUWyrgmvBsthW0QULKM2CXVewYAMEQRDFhnQRJBTpSC9J/s8cTKSk3HNnzrkl3/M8PssmM++Z85lJ8r73tFIlUn0dQ6CN4ySx8XWMjNkXV1SNMY6KzXenOHHOzs7RyU9O1IKVm/Sv0w7X1Z0b+D4UOiCAAAIUFsGtAQqL4Gx9RY51YZGTk6NTnpyoeb9vUp+uTXTNcYf6Gn/gjeMksfF1nIzZF1dUjTGOis13pzhyfn36b7rj7Z9Us1IZTby9i0qmxdEHIL5h6YAAAvEmEOt8LN48/I6HwsKvWEDtY72Qx89ZqW4jpqv8n5cYVIy3SwziKLGJeAkw5oipom6IcdR0vjrGkfP2XVnq+Mh4rdq4XU+cf4zObVHH16HQGAEEEOCMRXBrgMIiOFtfkWNdWFw45CtNXbhWV3eqr3+d3tTX2ENpHEeJTcTHy5gjpoq6IcZR0/nqGGfOT49foMc+nqsmB1fQRzd2UkpKiq/DoTECCCBQkECs87FEnxkKiziZwVgu5B8z1+vMQZNVIjXFu7SgVuUD4kRlj2HEWWITERBjjojJqhHGVnwRd44z5w1bdqrdw59ry44sjbyytY5rXC3iQ6EhAgggwBmL4NYAhUVwtr4ix7KwuH7UDL3/43Kd07y2BlzQzNe4Q2scZ4lNRMfNmCNismqEsRVfxJ3j0Pm+MT9r+ORF6tDwQL1yVduID4WGCCCAAIVFcGuAwiI4W1+RY1VYLFm7Rcc9Nl7ZOdKHvTupaa2KvsYdWuM4TGyKPHbGXCSRdQOMrQkjChCHzpnrzO+uCcrKztH7N3TUkbUrRXQoNEIAAQQoLIJbAxQWwdn6ihyrwqLf6J81YsoidWp0kF7q3sbXmENtHIeJTZHHz5iLJLJugLE1YUQB4tS596vfafQPy3RWs1p66sLmER0KjRBAAAEKi+DWAIVFcLa+IseisFi3eYfaPzxOW3dm6eXubdSx0UG+xhxq4zhNbAo1YMzBLxGMgzc2e4hT55lLN+iMgV8qLTVFX9yWoTpVyobjwV4QQCBpBWKRjyUTJoVFnMxmLBbywM/n6/FP56lpzYr6oHfH+H6ySpwmNhQWMf4BYl2EMwFx7Hzx81M15Zc1urJDfd3ztzh8ol04M8ReEEDAkUAs8jFHQ4+LMMWysHjmmWf02GOPafny5TriiCP05JNPqlOnTgVOyNtvv627775bv/zyiw499FD9+9//1jnnnJPX3rxc7r777tOQIUO0bt06tWnTRk8//bQXO9It7IW8bad5Fvw4rd60Q09d2ExnNasd6VBj0y6OE5sCQRhz8GsF4+CN4/iMhRnahLkrdcXw6SpbKk1f9TlBlcqWDMeEvSCAQFIKhJ2PJRtisSssXn/9dV166aUyxUWHDh00ePBgvfDCC5o1a5YOOeSQ/eb3q6++8oqOBx54wCsm3n33Xd1zzz368ssvvQLCbI888ohXbIwYMUKNGzfWgw8+qIkTJ2ru3LmqUKFCRGsm7IX8vzHT9PqocdqSXl9v/fv83W+vzcyU5s+XGjWS6uzx0qn8vu6nrRGwjVFQAulnHH7aMmZp0yapXLnd69ePnZ+2ts6FFRZ+xuGnLWP+a13EwdowH+x0fWqS1s/7VX0apuns8zP2/v2V329gP/Ptp63t2ijsr4Wfcfhpm4hjdnF8BVn7iR1U28J+rsJcz36OLxZjjii78t8o7HzM/wjju0exKyxMMdCiRQs9++yzeTNz+OGH6+yzz9ZDDz2032xdcMEFMovso48+yvveqaeeqipVqujVV1+V+aNWq1Yt3XTTTbrjjju8Ntu3b1eNGjW8gqNnz54RrYAwF3LWkOeVfe21SsvJVnZqqlIHDtw9xhtukLKzpdRUyXzt8sulkSP3/7qftq5ibNkiVa++e5wrV0ply+Y/Nlf7c3HcjLnwdeRirs47b/91YdZIfvPnYn8uYjDmon/H+HT+7oGndPSjdyktJ0c5qalKyf39ld9v33heG+a4GXPwf3/CdnbxN5Mxe5drpwwZInXvHlFeFW2jMPOxaMcYz/2KVWGxY8cOlS1bVm+++eZelzLdeOON+v777/XFF1/sN1fmLMbNN9/s/Ze7DRgwwLt8avHixVq4cKF3edSMGTPUvPlfTyU566yzVLlyZY00f8Ty2UzxYf7L3cxCrlu3rjZs2KCKFQN85GtmprLq1dO8ho3ieV0yNgQQQAABBBBAIE/gsHlzlWo++Fy0qOizkhZuFBYWeJKKVWGxbNky1a5dW5MnT1b79u3z5Pr37+8VAObSpX23UqVKeZc4XXzxxXnfGjVqlLp16+YVBlOmTPEuqVq6dKl35iJ369Gjh1d4fPzxx/nOUL9+/bz7MvbdAi8sxo9X9gknaG7jw+xWDr0RQAABBBBAAIGQBLzCIidHGj9eysgIbK8UFna0xbKwMMVAu3bt8uTM/REvvfSS5syZk29hYYqOiy66KO97r7zyirp3765t27blFRamaKlZs2Zem6uvvlpLlizR2LFj852hWJ6xyElP9y7hytvMJwBmM5dB5W5padK48VKXjL2/7qetqxizZkm197m5fOlS6fDDGbOZL5z3/hljbbj/OU6wn8Gc1DSlzPhWatZst0Xu5ZPxvja+ZczefLn6nZbf3zATO0xnF38zGbO3LFJycpRiLDhjYZf5B9y7WBUW8XQp1L7zGmqFPHSoZO79yMra/Qt88ODdw9n3a+Y6Rtu2rmLk94OQ39hc7c/FcTPm3WuroDlxNVc447zHz+uulFS9cMkduubZf0nly+9eHXs+iCCef29ceCFjzv2b5Or3Q37zHbazn7+vBR03Y/4rX+Eei4BLA7vwxaqwMFTm5u2WLVt6T4XK3Zo2bSpzT0RBN29v3LhRH374YV77rl27evdP7HnztrkH4/bbb/famAKmevXqcXvztjdI87SHBQukhg3/ulYxv6+5aOsqRn5rnTHv/wQvm3kt6PcJzjgnwNpY8/3POmvs78osf6De695CxzT+8/LUPQuLgn4fufo9ZfO7tainnO37s11cx+zn91F+RrFwZsz7P03Odj3b5b8F9g71g96AjiGWYYtdYZH7uNnnnnvOuxzKvHvi+eef188//6z09HRddtll3n0YuUWGuWyqc+fO3uNkTfHx3nvv6a677trvcbOm/fDhw9WoUSOZezYmTJgQ14+bjeWiY98IIIBAUAK3vPG93pmxVKcfXk1PX7H7keB7nbEIascu4vJeFheKRcfAuWgjFy0S0VnyngRaqVKl4B+m48I4DmMUu8LCzIE5W/Hoo496L8g78sgjZZ7yZIoHs2VkZKhevXreDdu521tvveUVE7lPgDJFxrnnnpv3/dwX5Jl3Yuz5gjwTO9KNhRypFO0QQACBggXmrPhDpz45Sakp0oRnu+uQDb9TWAS5YBIxeWTMQa6Iv2InojOFhfXaKJaFhbVaAAEoLAJAJSQCCBRLgcuHfa0v5q3S5d+O0X2fDaawCHIVJGLyyJiDXBEUFuHoxu1eKCziZGooLOJkIhgGAggkvMDkBav1jxem6YAd2zTl2W6qsnr53td3x+sRkvCGMzM441yIAPmY3fKgsLDzc9abheyMkkAIIFDMBczlqWc8NVFr5i3S7RNH6tx3npMaN45/FRLecOYIZ5wpLAJbAxQWgdH6C0xh4c+L1ggggEBhAt/962Ed/dCdSsvJUU5qqlKGDNn96ON43kh4w5kdnHGmsAhsDVBYBEbrLzCFhT8vWiOAAAIFCmRmyrwINGXfl34G/GIt6xkh4bUmjCgAzhExWTdKRGdu3raedgoLa0I3ASgs3DgSBQEEEND48dLxx+8PYb6ekRG/QImYiDHmcNYTzuE4U1hYO1NYWBO6CUBh4caRKAgggID3AtD0dGmPMxY5qWlKWbxo7xcdxhsVyWM4M4IzzoUIkI/ZLQ8KCzs/Z71ZyM4oCYQAAghIQ4dKPXtKWVnalZKqwRffrl4vPxTfMiS84cwPzjhTWAS2BigsAqP1F5jCwp8XrRFAAIEiBTIzte7HWTrzo9+1pFxVvXVNO7WqV7XIbjFrQMIbDj3OOFNYBLYGKCwCo/UXmMLCnxetEUAAgUgF+rz9o16bvkQnNa2h5y9rFWm38NuR8IZjjjPOFBaBrQEKi8Bo/QWmsPDnRWsEEEAgUoEFKzfpxCe+UEqK9Nktx+nQauUj7RpuOxLecLxxxpnCIrA1QGERGK2/wBQW/rxojQACCPgRuGrkN/ps9u+6qHVdPXTu0X66hteWhDcca5xxprAIbA1QWARG6y8whYU/L1ojgAACfgSmL1qr8577SqVKpOrLO7qoeoUyfrqH05aEF+eCBFgb4awNHjdr7UxhYU3oJgCFhRtHoiCAAAL5CeTk5OjcZ6fou9/Wq1eXQ3XbKU3iD4rkMZw5wRlnzlgEtgYoLAKj9ReYwsKfF60RQAABvwJjZy7XNS/PUKUDSmpKn+NVrnQJvyGCbU/CG6xvbnSccaawCGwNUFgERusvMIWFPy9aI4AAAn4FsrJzdMLjE7RozRbdc0ZTXdmxvt8QwbYn4Q3Wl8IiHN9EduZSKOs1QmFhTegmAIWFG0eiIIAAAoUJvDx1se7630zVrnyAvrgtQyXSUuMHjMIinLnAGWfOWAS2BigsAqP1F5jCwp8XrRFAAIFoBLbtzFKHh8dpzeYdeurCZjqrWe1owgTTh4Q3GNd9o+KMM4VFYGuAwiIwWn+BKSz8edEaAQQQiFZg4Ofz9fin89S0ZkV90LujUswLLuJhI+ENZxZwxpnCIrA1QGERGK2/wBQW/rxojQACCEQrsG7zDrV/eJy27szSS91bq1OjatGGctuPhNetZ0HRcMaZwiKwNUBhERitv8AUFv68aI0AAgjYCPQb/bNGTFmkjg0P0stXtbEJ5a4vCa87y8Ii4YwzhUVga4DCIjBaf4EpLPx50RoBBBCwEViydosy/jNB5klR79/QUUfWrmQTzk1fEl43jkVFwbkoITffT0RnngplPfcUFtaEbgJQWLhxJAoCCCAQqcCNr32n975fpjOPqaX/XtQ80m7BtUvERIwxB7ce9oyMczjOFBbWzhQW1oRuAlBYuHEkCgIIIBCpwM/LNuj0/36ptNQUTfhnhupWLRtp12DakTwG47pvVJxxLkSAfMxueVBY2Pk5681CdkZJIAQQQCBigUuHTtOk+at1Rft66nfmERH3C6QhCW8grPsFxRlnCovA1gCFRWC0/gJTWPjzojUCCCDgQmDygtX6xwvTVKZkqqb0OUFVy5VyETa6GCS80bn57YWzX7Ho2ieiM5dCRTfXe/SisLAmdBOAwsKNI1EQQAABPwI5OTk6Y+CX+nnZH7r5xMa68cRGfrq7bZuIiRhjdrsGCoqGczjOFBbWzhQW1oRuAlBYuHEkCgIIIOBXYPQPy9T71e+8sxWT7zheB5RK8xvCTXuSRzeORUXBuSghN99PRGcKC+u5p7CwJnQTgMLCjSNREEAAAb8Cu7KyvUfPZq7bqgfOOkKXtqvnN4Sb9omYiDFmN3NfVBScixJy9n3yMTtKCgs7P2e9WcjOKAmEAAII+BYYOWWR7h39sw6pWlbjbj1OJdJSfcew7kDyaE0YUQCcI2KybpSIzpyxsJ52CgtrQjcBKCzcOBIFAQQQiEZgy45d6vDwOK3bslMDL2quvx1TK5owdn0SMRFjzHZzHmlvnCOVsm5HPmZHSGFh5+esNwvZGSWBEEAAgagEnvxsnp78bL6OqFXRext3SkpKVHGi7kTyGDWdr444++KKunEiOnPGIurpzu1IYWFN6CYAhYUbR6IggAAC0Qqs27xD7R8ep607s/RS99bq1KhatKGi65eIiRhjjm6u/fbC2a9Y1O3Jx6Km8zpSWNj5OevNQnZGSSAEEEAgaoF+o3/WiCmL1KHhgXrlqrZRx4mqI8ljVGy+O+HsmyyqDonozBmLqKZ6z04UFtaEbgJQWLhxJAoCCCBgI5C5bouOe2yCsrJzNOb6jjqqTiWbcP76JmIixpj9zXG0rXGOVs53P/Ix32R7daCwsPNz1puF7IySQAgggICVwM2vf693v1uq04+qqaf/0cIqlq/OJI++uKJujHPUdL46JqIzZyx8TXF+jSksrAndBKCwcONIFAQQQMBWYPbyP9T1qUlKTZHG3ZqhegeVsw0ZWf9ETMQYc2Rza9sKZ1vBiPuTj0VMlW9DCgs7P2e9WcjOKAmEAAIIWAtcMfxrTZi7She3OUT9zznKOl5EAUgeI2KyboSzNWFEARLRmTMWEU1tYY0oLKwJ3QSgsHDjSBQEEEDAhcDUhWt04ZCpKlUiVV/e0UXVK5RxEbbwGImYiDHm4NeF2QPO4ThTWFg7U1hYE7oJQGHhxpEoCCCAgAuBnJwcnfPMFH2/ZL2uyzhUt5/axEVYCovgFYveA0l60UYuWiSiM4WF9cxTWFgTuglAYeHGkSgIIICAK4GxM1fompe/VYUyJTSlz/GqUKakq9D5x0nERIwxB7smcqPjHI4zhYW1M4WFNaGbABQWbhyJggACCLgSyM7O0YkDvtDCVZvVt2sT9TzuUFehKSyCleTMUCx9E7kYorCwXjkUFtaEbgJQWLhxJAoCCCDgUuCN6Ut0+9s/qnqF0pp0RxeVLpHmMvzesfhUOjjbPSPjjHMhAuRjdsuDwsLOz1lvFrIzSgIhgAACzgR27MpW50fHa8Uf2/TQuUfpotaHOIu9XyAS3uBsKSzCsU10Z85YWK+TYlVYrFu3Tr1799bo0aM9uDPPPFMDBw5U5cqV84Vcu3at7r33Xn3yySdasmSJDjroIJ199tl64IEHVKnSX29jTUlJ2a//s88+q2uuuSbiCaKwiJiKhggggECoAi9MWqgHP5itegeW1ee3ZijNvOAiiI3CIgjV/WPijHMhAuRjdsujWBUWXbt2VWZmpoYMGeKp9ejRQ/Xq1dOYMWPyVZw5c6ZXWFxxxRVq2rSpFi9e7BULRx99tN566628PqawGD58uE499dS8r5nC44ADDoh4dljIEVPREAEEEAhVYPP2XerwyDit37JTgy5urjOOrhXM/kl4g3HdNyrOOFNYBLYGik1hMXv2bK84mDp1qtq0aeOBmn+3a9dOc+bM0WGHHRYR8ptvvqlLLrlEmzdvVokSJbw+prB49913vbMZ0W4UFtHK0Q8BBBAIXmDAp/P01OfzdUStinr/ho7e733nGwmvc9J8A+KMM4VFYGug2BQWw4YN0y233KL169fvhWkugxowYIC6desWEfILL7ygvn37atWqVXntzR+Y2rVra9u2bapfv766d+/unQ1JTU0tMOb27dtl/svdTGFRt25dbdiwQRUrVoxoLDRCAAEEEAhHYN3mHWr/8Dht3ZmlkVe21nGNq7nfMQmve9P8IuKMM4VFYGug2BQW/fv314gRIzRv3ry9MBs3buwVFaZYKGpbs2aNWrRooUsvvVQPPvhgXnPz7xNOOMG79Onzzz/XPffc48W76667CgzZr18/3Xfffft9n8KiqFng+wgggEBsBO4fM0vDJv+qtg2q6rUe7dwPgoTXvSmFRTimyeLMzdvW6yXhC4uCEvQ9ZaZPn+7dgD1y5EjNnTt3L7RGjRp5Zxj69OlTKKY5o3DyySerSpUq3s3fJUsW/KKkxx9/XPfff7939qGgjTMW1muXAAgggECoAsvWb9Vxj43XzqwcvXNde7U4pIrb/VNYuPUsKBrOOBciwKXpdssj4QuL1atXy/xX2GZu0B41alTUl0Jt3LhRp5xyisqWLav3339fZcqUKXR/kydPVseOHbVixQrVqFEjohliIUfERCMEEEAgpgK3vfmD3vw2Uyc1raHnL2vldiwkvG49KSzC8UwmZ85YWK+ZhC8sIhXIvXl72rRpat26tdfN/Ltt27aF3rxtEn5TVJQuXVoffvihV1wUtQ0aNEi33Xabdz+H6RfJRmERiRJtEEAAgdgKLFi5SScN+EI5OdKnN3dWoxoV3A2IwsKdZWGRcMa5EAHyMbvlUWwKC8NkHje7bNkyDR482FMzN1inp6fnPW526dKl3r0SL774old8mDMVJ510krZs2eI99alcuXJ52tWqVVNaWprX15yZME+XMvdYjB8/Xrfeeqv3iNqnnnoq4tlhIUdMRUMEEEAgpgLXvPStxv68Que2qK0nzm/mbiwkvO4sKSzCsUw2Z85YWK+bYlVYmBfe7fuCPHN2IfcFeYsWLfKe6mSKg4yMDE2YMEFdunTJF/nXX3/13oExduxY70btBQsWKDs7Ww0aNNBVV12lXr165T2ONpJZorCIRIk2CCCAQOwFfliyXmc9Pdl7Ud6Ef2aobtWiz2RHNGoKi4iYrBvhbE0YUYBEdKawiGhqC2tUrAoLa60AA1BYBIhLaAQQQMCxwCUvTNOXC1br0rbpeuDsI91ET8REjDG7mfuiouBclJCz75OP2VFSWNj5OevNQnZGSSAEEEAgcIEpv6zWxc9PU6kSqfryji6qXqHwh3pENCCSx4iYrBvhbE0YUYBEdOaMRURTyxkLa6bgA1BYBG/MHhBAAAFXAjk5Ofr7s1M047f16tm5gfqedrh96ERMxBiz/bxHEgHnSJSctCEfs2PkjIWdn7PeLGRnlARCAAEEQhH4fPbv6j7yG5UrlabJfY5X5bKl7PZL8mjnF2lvnCOVsmuXiM6csbCbc0kUFtaEbgJQWLhxJAoCCCAQloA5a9H1qUmas2KjbjqxkW46sbHdrhMxEWPMdnMeaW+cI5Wybkc+ZkdIYWHn56w3C9kZJYEQQACB0ATG/LBMN7z6nSodUNI7a1G+dIno903yGL2dn544+9GKvm0iOnPGIvr5/rMnhYU1oZsAFBZuHImCAAIIhCmQlZ2jE5/4Qr+u3qw7T2uiHp0PjX73iZiIMebo59tPT5z9aFm1JR+z4uNSKDs+d71ZyO4siYQAAgiEKfDG9CW6/e0fVa1CaU26vYvKlEyLbvckj9G5+e2Fs1+x6NonojNnLKKb6z16ccbCmtBNAAoLN45EQQABBMIW2LErWxmPjdeyDdu8d1qYd1tEtSViIsaYo5pq351w9k0WbQfysWjldvejsLDzc9abheyMkkAIIIBA6AIjJv+qfmNmqU6VAzT+nxkqmZbqfwwkj/7NoumBczRq/vskojNnLPzP8z49KCysCd0EoLBw40gUBBBAIBYCW3dkqeMj47Rm8w49ft4x+nvLOv6HkYiJGGP2P8/R9MA5GrWo+pCPRcWW14nCws7PWW8WsjNKAiGAAAIxEXhmwgI9OnauGlQrp09vPk5pqSn+xkHy6M8r2tY4Ryvnr18iOnPGwt8c59OawsKa0E0ACgs3jkRBAAEEYiWwcdtOdXxkvDZs3amBFzXX346p5W8oiZiIMWZ/cxxta5yjlfPdj3zMN9leHSgs7Pyc9WYhO6MkEAIIIBAzgSc/m6cnP5uvw2pU0Ec3dlKqn7MWJI/hzBvOOBciQD5mtzwoLOz8nPVmITujJBACCCAQM4ENW3aqwyPjtGn7Lj13SUudeuTBkY+FhDdyK5uWONvoRd43EZ25FCry+S2gJYWFNaGbABQWbhyJggACCMRa4LGP5+jp8b/oiFoV9f4NHZWSEuG9FomYiDHmcJYbzuE4U1hYO1NYWBO6CUBh4caRKAgggECsBdZu3uE9IWrLjiwNu6KVjm9SI7IhkTxG5mTbCmdbwcj6J6IzhUVkc1tIKwoLa0I3ASgs3DgSBQEEEIgHgf4fztaQiQvVrG5lvXtd+8jOWiRiIsaYw1luOIfjTGFh7UxhYU3oJgCFhRtHoiCAAALxILBy4zZ1emS8tu/K1kvdW6tTo2pFD4vksWgjFy1wdqFYdIxEdKawKHpei2hBYWFN6CYAhYUbR6IggAAC8SLQb/TPGjFlkVrXr6o3erYreliJmIgx5qLn1UULnF0oRhSDfCwipgIbUVjY+TnrzUJ2RkkgBBBAIC4EVmzYps6PjteOrGy93qOt2jQ4sPBxkTyGM28441yIAPmY3fKgsLDzc9abheyMkkAIIIBA3Aj8692f9Mq039Sx4UF6+ao2FBbxMDMUFuHMQiI6cymU9dqgsLAmdBOAwsKNI1EQQACBeBJYsnaLuvxngnZl5+jta9urZXqVgoeXiIkYYw5nueEcjjOFhbUzhYU1oZsAFBZuHImCAAIIxJvAHW/9qNe/WaLOjavpxStbU1jEeoJI0sOZgUR0prCwXhsUFtaEbgJQWLhxJAoCCCAQbwK/rdmi4x+P4KxFIiZijDmc5YZzOM4UFtbOFBbWhG4CUFi4cSQKAgggEI8CEZ21IHkMZ+pwxrkQAfIxu+VBYWHn56w3C9kZJYEQQACBuBMwZy26PD5BWYXda0HCG8684YwzhUVga4DCIjBaf4EpLPx50RoBBBBINIHb3/pBb3yTWfC9FiS84UwpzjhTWAS2BiIcUDgAACAASURBVCgsAqP1F5jCwp8XrRFAAIFEEyjyrAUJbzhTijPOFBaBrQEKi8Bo/QWmsPDnRWsEEEAgEQUKPWtBwhvOlOKMM4VFYGuAwiIwWn+BKSz8edEaAQQQSESBPc9avHNde7U4ZI/3WpDwhjOlOONMYRHYGqCwCIzWX2AKC39etEYAAQQSVSD3rMVxjatp5J7vtSDhDWdKccaZwiKwNUBhERitv8AUFv68aI0AAggkqkCBZy1IeMOZUpxxprAIbA1QWARG6y8whYU/L1ojgAACiSyQ770WJLzhTCnOOFNYBLYGKCwCo/UXmMLCnxetEUAAgUQW2PNt3G9d006t6lWVSHjDmVKccaawCGwNUFgERusvMIWFPy9aI4AAAoku0PedH/Xq10vUrsGBerVHWwqLsCaUwiIc6UR0lkQ+Zrc8KCzs/Jz1ZiE7oyQQAgggkBACS9dvVZfHJmhHVrZGXdVG7WseIJUvv3vsmzZJ5crF/3EkYvLImMNZV4noTGFhvTYoLKwJ3QSgsHDjSBQEEEAgkQTufW+mRn61WC3Tq+itS49WSoUKFBZBT2AiJryMOehVkReffMyOmsLCzs9ZbxayM0oCIYAAAgkjsPKPber06Hht35Wt4RcdpS7N0iksgp49kvSghXfHT0RnzlhYrw0KC2tCNwEoLNw4EgUBBBBINIF/fzBLz0/6VUfXrKD3bjpOKeYAuBQquGlMxISXMQe3HvaJTD5mR01hYefnrDcL2RklgRBAAIGEElizabt31mLLjiwNefsBnbxgGoVFkDNIkh6k7l+xE9GZMxbWa4PCwprQTQAKCzeOREEAAQQSUeCxj+fo6fG/qMnKX/Xh8N5K3bSRm7eDmshETHgZc1CrYb+45GN21BQWdn7OerOQnVESCAEEEEg4gfVbdqjTI+NUbtXvGvD+f9Tus7elxo3j/zhIeMOZI5zDceaMhbUzhYU1oZsAFBZuHImCAAIIJKrAZzfdry7/7ae0nBzlpKYqZcgQqXv3+D4cEt5w5gfncJwpLKydi1VhsW7dOvXu3VujR4/24M4880wNHDhQlStXLhAyIyNDX3zxxV7fv+CCC/Taa6/lfS2auPvukMLCei0TAAEEEEhcgcxM5aSnKyU7+69jSEuTFi2S6tSJ3+Mi4Q1nbnAOx5nCwtq5WBUWXbt2VWZmpoaYT4Ek9ejRQ/Xq1dOYMWMKLSwaN26s+++/P6/NAQccoEqVKuX9/2jiUlhYr10CIIAAAskjMH68dPzx+x+P+XpGRvweJwlvOHODczjOFBbWzsWmsJg9e7aaNm2qqVOnqk2bNh6c+Xe7du00Z84cHXbYYflimjMWzZo105NPPpnv96ONS2FhvXYJgAACCCSPQGamlJ4u7XHGIjs1TamLOWPhfJJJ0p2T5hswEZ0pLKzXRrEpLIYNG6ZbbrlF69ev3wvNXAY1YMAAdevWrcDC4ueff1ZOTo5q1Kghc3bi3nvvVYU/344abdzt27fL/Je7mUuh6tatqw0bNqhixYrWE0sABBBAAIEEExg6VOrZU8rK0q6UVD101o265bVHVa50ifg9kERMHhlzOOspEZ0pLKzXRrEpLPr3768RI0Zo3rx5e6GZy5xMUdG3b998MZ9//nnVr19fBx98sGbOnOm1a9iwoT799FOvfbRx+/Xrp/vuu2+/fVJYWK9pAiCAAAKJK5CZqV1z5+micas1Paucbj2psW44oVH8Hk8iJo+MOZz1lIjOFBbWayPhC4uCEvQ9ZaZPn65PPvlEI0eO1Ny5c/dCa9Sokbp3764+ffpEhPntt9+qVatWMv/bokULr7CIJi5nLCLiphECCCBQLAVG/7BMvV/9ThVKl9DE27uoSrlS8emQiMkjYw5nLSWiM4WF9dpI+MJi9erVMv8VtpkbtEeNGhXVpVD7xjWXRJUuXVovvfSSzNOhor0Uat+4PBXKei0TAAEEEEgagezsHJ0x8EvNWv6HenRuoDtPOzw+jy0Rk0fGHM5aSkRnCgvrtZHwhUWkArk3WU+bNk2tW7f2upl/t23bttCbt/eNby6HOuqoo7xH0Hbu3Fmu4lJYRDqTtEMAAQSKh8D4uSvVbfh0lSqRqi9uy1DNSgfE34EnYvLImMNZR4noTGFhvTaKTWFhpMyN18uWLdPgwYM9OPO42fT09LzHzS5dulQnnHCCXnzxRa/4+OWXX/TKK6/otNNO00EHHaRZs2bp1ltvlXncrLm8Ks08YzyCuJHMEoVFJEq0QQABBIqPgDlDfsGQqfr617W6qHVdPXTu0fF38ImYPDLmcNZRIjpTWFivjWJVWKxdu3a/F+QNGjQo7wV5ixYt8m7UHj9+vMxjZpcsWaJLLrnEu2l706ZN3lObTj/9dO+pUFWrVs3DLypuJLNEYRGJEm0QQACB4iXw7eK1+vuzXyktNUWf3txZDaqVjy+AREweGXM4aygRnSksrNdGsSosrLUCDEBhESAuoRFAAIEEFrhq5HR9NnulTj+6pp6+uEV8HUkiJo+MOZw1lIjOFBbWa4PCwprQTQAKCzeOREEAAQSSTWDOij/U9alJysmR3uvVQcfUrRw/h5iIySNjDmf9JKIzhYX12qCwsCZ0E4DCwo0jURBAAIFkFLj1jR/09oxMtalfVa/1aKuUlJT4OMxETB4ZczhrJxGdKSys1waFhTWhmwAUFm4ciYIAAggko8Cy9VvV5T8TtH1Xtl64rJVObFojPg4zEZNHxhzO2klEZwoL67VBYWFN6CYAhYUbR6IggAACySrwyNg5enbCL2pYvbzG3thJJdJSY3+oiZg8MuZw1k0iOlNYWK8NCgtrQjcBKCzcOBIFAQQQSFaBP7bt1HGPjte6LTvV/5yjdHGbQ2J/qImYPDLmcNZNIjpTWFivDQoLa0I3ASgs3DgSBQEEEEhmgeGTf9V9Y2bpoPKlvZfmlStdIraHm4jJI2MOZ80kojOFhfXaoLCwJnQTgMLCjSNREEAAgWQW2LErWycN+EKL12zRTSc20k0nNo7t4SZi8siYw1kziehMYWG9NigsrAndBKCwcONIFAQQQCDZBT74cbl6jZqhsqXSNOG2DFWvUCZ2h5yIySNjDme9JKIzhYX12qCwsCZ0E4DCwo0jURBAAIFkF8jJydE5z0zR90vWe/dZmPstYrYlYvLImMNZLonoTGFhvTYoLKwJ3QSgsHDjSBQEEECgOAhMX7RW5z33ldJSU/TxTZ3UsHqF2Bx2IiaPjDmctZKIzhQW1muDwsKa0E0ACgs3jkRBAAEEiotAjxe/0SezftfxTapr2BXHxuawEzF5ZMzhrJVEdKawsF4bFBbWhG4CUFi4cSQKAgggUFwEflm1SacMmKhd2Tl68crW6ty4WviHnojJI2MOZ50kojOFhfXaoLCwJnQTgMLCjSNREEAAgeIkcP+YWRo2+Vc1ql5eH8XipXmJmDwy5nB+RBLRmcLCem1QWFgTuglAYeHGkSgIIIBAcRLYsGWnMv6z+6V59591hC5rVy/cw0/E5JExh7NGHDk/P3GhVm/aruuPb6gKZUoGPnbyMTtiCgs7P2e9WcjOKAmEAAIIFCuBl75apLvf+1mVy5bUF//sokplg0++8oAdJY+hThhjDofbgfOKDdt0/OMTtGVHlp66sJnOalY78LGTj9kRU1jY+TnrzUJ2RkkgBBBAoFgJ7MrK1mn/naR5v2/SlR3q656/NQ3v+B0kj+EN9s89MeZwyB043/z693r3u6VqcUhlvX1te6WkpAQ+dvIxO2IKCzs/Z71ZyM4oCYQAAggUO4FJ81fp0qFfq0Rqisbe1FkNq5cPx8BB8hjOQPfYC2MOh9zS+dvF6/T3Z6fI1BLv9eqgo+tUDmXc5GN2zBQWdn7OerOQnVESCAEEECiWAleNnK7PZq8M9/GzlsljTCaKMYfDbuGcnW1eAjlZP2Ru0Pmt6ujR/zsmnDFz87a1M4WFNaGbABQWbhyJggACCBRXgYXm8bNPTtTOrByNvLK1jgvj8bMWyWPM5okxh0Nv4fzGN0t0+1s/qnzpEhr/zwxVq1A6nDFTWFg7U1hYE7oJQGHhxpEoCCCAQHEWePD9WXrhy1+9S6HGhvH4WYvkMWbzxJjDoY/SeeO2neryny+8J0HdeVoT9eh8aDjj/XMv5GN23BQWdn7OerOQnVESCAEEECi2Ahu2mqRsgtZu3qF7zmiqKzvWD9YiyuQx2EEVEZ0xh8MfpXP/D2dryMSFanBQOe9+oVIlUsMZL4WFE2cKCyeM9kEoLOwNiYAAAgggII2a9pvufPcnVShdQp//8zhVr1AmOJYok8fgBhRBZMYcAZKDJlE473k53/ArjlWXJtUdDMRfCPIxf177tqawsPNz1puF7IySQAgggECxFsjKztG5f974em7z2nrigmbBeUSRPAY3mAgjM+YIoSybReHcbfjXGj93lbocVk3Du7W2HEB03cnHonPL7UVhYefnrDcL2RklgRBAAIFiL/DDkvU6+5nJysmR3ujZTq3rVw3GJIrkMZiB+IjKmH1gWTT16Tx+zkp1GzFdJdNS9PFNndWgWkiPTN7nEMnHLOZcEoWFnZ+z3ixkZ5QEQgABBBCQ1PedH/Xq10vU5OAKev+GjiqRFsC16j6Tx7iYGMYczjT4cN62M0snD5io39ZuUY/ODXTnaYeHM8Z89kI+ZkdPYWHn56w3C9kZJYEQQAABBCTvBu7jH5+g9Vt26t6/NVW3DgHcyO0jeYybSWHM4UyFD+cnPp2n/34+XwdXLKPPbj3Oe8xsrDbyMTt5Cgs7P2e9WcjOKAmEAAIIIPCnwCvTFutf7870buQeF8T7AHwkj3EzKYw5nKmI0PnX1Zt1yoCJ2pGVrWf+0UKnHVUznPEVsBfyMTt+Cgs7P2e9WcjOKAmEAAIIIPCngLmR++ynJ+unpRt0bovaeuJ8xzdyR5g8xtWEMOZwpiMC55ycHF027GtNmr9anRtX08huxyolJSWc8VFYBOJMYREIq/+gFBb+zeiBAAIIIFC0wPdL1uucP2/kfvOadjq2nsMbuSNIHoseYcgtGHM44BE4v//jMl0/6jvvXRWf3NRZ9Q4qF87YCtkL+ZjdFFBY2Pk5681CdkZJIAQQQACBfQT6vP2jXpu++0buMTd0VElXN3JHkDzG3WQw5nCmpAhn84btEx7/Qis3btdNJzbSTSc2DmdcReyFfMxuGigs7Pyc9WYhO6MkEAIIIIDAPgJ73sjdp2sTXXPcoW6MSNLdOBYVJQmdH3h/loZ++avSDyzrPV62TMm0ohRC+T75mB0zhYWdn7PeLGRnlARCAAEEEMhH4M1vlui2t35UmZKp+vTm41S3all7pyRMeO1RAoiQZM6zlv2hvw36UuYeoBHdjlXGYeG/YbugWSIfs1u/FBZ2fs56s5CdURIIAQQQQCAfAXOj7MXPT9NXC9e4u1E2yRLeuF04SeScnZ2j8wZ/pW8Xr9NpRx2sZ/7RMq7YycfspoPCws7PWW8WsjNKAiGAAAIIFCCwcNUmnfrUJO3Yla2nLmyms5rVtrNKooTXDiLg3knk/NLUxbr7fzNVtlSaPr/1ONWsdEDAeP7Ck4/589q3NYWFnZ+z3ixkZ5QEQgABBBAoRGDg5/P1+KfzdGC5Ul5iV7lsqei9kijhjR4hhJ5J4rx8w1ad9MREbdq+K7iXNlpOB/mYHSCFhZ2fs94sZGeUBEIAAQQQKETAnK04/b+TNH/lJl3Qqq4e+b+jo/dKkoQ3eoCQeiaBc07Zsrpq5Df6fM5KNT+kst66pr3SUmP7zor8Zo98zG5NU1jY+TnrzUJ2RkkgBBBAAIEiBL5ZtFb/99xXXqvXerRV2wYHRmeWBAmvysX+3QlF4ieB85gFG3TDq9+pZFqKPujdSY1rVCjysGPRgHzMTp3Cws7PWW8WsjNKAiGAAAIIRCBw57s/adS039SgWjl9dGMnlS4RxeM+kyDhpbCIYLFE02SPtbFu5Tqd+Nx0rdm8I67eWcEZi2gmtvA+FBbuTaOKSGERFRudEEAAAQSiFNiwdadOfOILrdq4XTcc31C3nnyY/0gUFv7NoumR4M63vDJd7/z4uxrXKK/3b+jkvWk7XjfyMbuZobCw83PWm4XsjJJACCCAAAIRCnz003Jd+8oM71r393p10JG1K0XY889mCZ7watMmccbC35RH3PrPtfFDjYbqee5d+r3SQXr72vZqcUiViEPEoiH5mJ06hYWdn7PeLGRnlARCAAEEEPAh0GvUDH3w43I1ObiCRl/f0d+nyRQWPqQtmiai8zPPKKdXL5nbs7NSUvR+r346a+A9FgjhdCUfs3OmsLDzc9abheyMkkAIIIAAAj4E1mzarpMHTPSuf/d9SVQiJryM2cfqiLJpZqaUni5lZ+cFyElLU8qiRVKdOlEGDacb+ZidM4WFnZ+z3ixkZ5QEQgABBBDwKfDhT8t13Z+XRP3vug46qk6El0SRpPuUjrJ5ojmPHy8df/z+B2u+npERJUI43cjH7JyLVWGxbt069e7dW6NHj/bUzjzzTA0cOFCVK1fOV3HRokWqX79+vt974403dN5553nfS0nZ/znMzz77rK655pqIZ4eFHDEVDRFAAAEEAhDIvSTqsBoVNPqGDpE9JSrREl7jxpgDWD17h9y04Fcd0Lih0nL+OmOhtDSJMxaB28d6B8WqsOjatasyMzM1ZMgQz71Hjx6qV6+exowZk+88ZGVladWqVXt9z/R99NFHtWLFCpUvXz6vsBg+fLhOPfXUvLaVKlXSAQdE/pp6CotY/yiwfwQQQKB4C+x5SdT1XRrqn6dE8JQokvRwFk2COd/x1o/KGTpUD308aHdxYYqKwYOl7t3D8bLYC/mYBZ75sD0nJyfHLkRi9J49e7aaNm2qqVOnqk2bNt6gzb/btWunOXPm6LDDIvgFKql58+Zq0aKFhg4dmnfg5ozFu+++q7PPPjtqDBZy1HR0RAABBBBwJLDnU6Leva69jq6T/xn9vN0lWMLrjZsxO1ot+YcZN+d3XTniG5mLOd454xA137lGatgw7u+tyD0a8jG75VFsCothw4bplltu0fr16/cSM5dBDRgwQN26dStS8ttvv1WrVq00efJktW/ffq/Conbt2tq2bZt36VT37t29syGpqQU/p3n79u0y/+25kOvWrasNGzaoYsWKRY6FBggggAACCAQhcP2oGXr/x+XeOwfMU6LKlCzkxXkk6UFMwf4xE8R53eYdOvnJid67Ua7qWF93ndE0HB+He6GwsMMsNoVF//79NWLECM2bN28vscaNG3tFRd++fYuUvO666zRhwgTNmjVrr7YPPvigTjjhBO/Sp88//1z33HOPF++uu+4qMGa/fv1033337fd9Cosip4EGCCCAAAIBCqw1yeGAL7R60w5171hfdxeWHCZIwrsXF2MObPXk3qfTsLp5EV4RRWlgo7ALTGFh55fwhUVBCfqeLNOnT9cnn3yikSNHau7cuXuJNWrUyDvD0KdPn0Ilt27dqpo1a+ruu+/WrbfeWmjbxx9/XPfff7939qGgjTMWdguX3ggggAACwQl8Pvt3dR/5jbeDF69src6Nq+W/M5L04CZhz8gJ4Dz6h2Xq/ep33ssWI7qMLhw533uhsPBNtleHhC8sVq9eLfNfYZu5QXvUqFFWl0K99NJLXgGydOlSVatWwC/YPwdhLpXq2LGjd4N3jRo1IpohFnJETDRCAAEEEAhJ4O7/zdRLUxerWoXSGntjJx1YvvT+e06AhHe/QTNm5yvo9z+2ee9C2bB1p246sZFuOrGx832EFZB8zE464QuLSA8/9+btadOmqXXr1l438++2bdtGdPN2RkaGDjroIL311ltF7nLQoEG67bbbvPs5SpfO5xdxPhFYyEWy0gABBBBAIESBbTuzdMbAL7Vg5SadeHgNPX9Zy/0fr06SHs6MxLFzVnaOLnlhmr5auEZH1a6kd65rr5JpBd9jGg5Y9HshH4vezvQsNoWFOVjzuNlly5ZpsHnk2Z+Pm01PT8973Kw5G2HulXjxxRfzig/TbsGCBTL3Ynz44Yd7PVLWfM88qtacmTBPlzL3WIwfP967VOqKK67QU089FfHssJAjpqIhAggggEBIArOW/aGzn56sHVnZevDsI3VJ2/S99xzHCW+BRIzZ6eoZNG6+/vPJPJUtlebdV9Gg2u5H8SfqRj5mN3PFqrBYu3btfi/IM2cXcl+Ql/tCPFMcmDMUududd94pcynU4sWL93vS09ixY70btU3xkZ2drQYNGuiqq65Sr169VKJEiYhnh4UcMRUNEUAAAQRCFHhh0kI9+MFslSmZ6iWODatX+GvvJOnhzEScOn+zaK0uGDJV5qzFf847Rv/Xsk44HgHuhXzMDrdYFRZ2VMH2ZiEH60t0BBBAAIHoBLKzc3T58K81af5qNa1ZUe/2av/XW7njNOEt9EgZc3QLYZ9eG7bs1Gn/naSl67fq7Ga1NOCCZvtfKudkT+EGIR+z86awsPNz1puF7IySQAgggAACjgVW/rFNpzw5Ueu27Nz7/QQk6Y6lCwgXZ87m3crXvjxDY39eofQDy+qD3p1UvnTkV2mEgxbdXsjHonPL7UVhYefnrDcL2RklgRBAAAEEAhD4dNbvuvrF3Y+gHXxpS51yxMG8xToA53xDxllh8fLUxbrrfzNVMi1Fb18bwRvaw3JysB/yMTtECgs7P2e9WcjOKAmEAAIIIBCQwIPvz9ILX/6qCqVL6P3eHZVeRlL5P2/W3bRJKlcuoD07DBtnSXpERxZHY56z4g+dNWiytu/K1l2nH66rOjWI6BASpRH5mN1MUVjY+TnrzUJ2RkkgBBBAAIGABHZmZevCIVP17eJ13v0W71x+jMpUqbR7bxQWAakrbs4Mbd6+S2c9Pdl7BHHGYdU07PJjlZqaEtxxxyAy+ZgdOoWFnZ+z3ixkZ5QEQgABBBAIUGDFhm06/b+TtGbzDl3YvKYevrAlhUWA3l7oODhjYe6ruH7Ud/rgp+WqXqG0Pryxkw7K76WJQVsEHJ98zA6YwsLOz1lvFrIzSgIhgAACCAQs8OX81bp02DTl5EiPfTBA5838nDMWQZrHQWExZOIv6v/hHO++itd6tFXL9KpBHnHMYpOP2dFTWNj5OevNQnZGSSAEEEAAgRAE/vv5fD3x6Tylr12qF9+4R+lfT5QaNw5hz5a7iIMk3fcRxHjMUxas1iVDpyk7R3rg7CN16b4vSvR9QPHbgXzMbm4oLOz8nPVmITujJBACCCCAQAgC5v0Ww7rdqW4vPaK0nBzlpKYqZcgQqXv3EPZusYsYJ+lRjTyGYzbvqfjbwC+1dvMO7wV4j/3f0UnxvoqC5oF8LKoVmteJwsLOz1lvFrIzSgIhgAACCIQhkJmpnPR0pWRn5+0tJy1NKYsWSXXi+A3MMUzSo56WGI15284snT/4K/2YuUFH1q6ot65przIl06I+jEToSD5mN0sUFnZ+znqzkJ1REggBBBBAIAyB8eOl44/ff0/m6xkZYYwgun3EKEmPbrB/9orBmM3N2ne8/aPe+CZTVcqW1JgbOqpOlbJWh5EIncnH7GaJwsLOz1lvFrIzSgIhgAACCIQhkJkppadLe5yx2JWSqrFjvtIZp7cOYwTR7SMGSXp0A92jVwzG/NLUxbr7fzNlniY78srW6tSomvVhJEIA8jG7WaKwsPNz1puF7IySQAgggAACYQkMHSr17CllZSk7NVV9Tr5e77Y4RaOubqtj68XpU4NikKRbT0fIY54wd6W6j/xGWdk5uuPUJro241DrQ0iUAORjdjNFYWHn56w3C9kZJYEQQAABBMIUMGcuFixQdoND1WviSn00c4Wqliul93p1UN2qcXjpTMhJupOpCHHMs5f/ofOe+0qbtu/S31vU0X/OS+6btfedH/IxuxVLYWHn56w3C9kZJYEQQAABBGIksGXHLi8p/XnZH2pycAW9dW17lS9dIkajKWC3ISbpzg48pDH//sc2nf30ZC3fsE1tG1TVi1e2UakSqc4OIxECkY/ZzRKFhZ2fs94sZGeUBEIAAQQQiKHA8g1bdeagyVq1cbtOPLy6Bl/aSmnmQv142UJK0p0ebghjNkWheQLUzKV/qEG1cnr32g6qVLak08NIhGDkY3azRGFh5+esNwvZGSWBEEAAAQRiLPDdb+t0wZCp2rErWxe1rqv+5xwVP+8+CCFJd84f8JjNvRQ9X/pWn83+XQeWK6V3r+ugQw6Mw8vYnMPuH5B8zA6ZwsLOz1lvFrIzSgIhgAACCMSBwNiZK3TdK996b2u+vktD/fOUw+JgVJICTtIDOciAx3z/mFkaNvlX77KnV69uq5bpVQI5jEQISj5mN0sUFnZ+znqzkJ1REggBBBBAIE4EXv36N/V95ydvNPf+ram6dagf+5EFnKQHcoABjvmZCQv06Ni53rAHXdxcZxxdK5BDSJSg5GN2M0VhYefnrDcL2RklgRBAAAEE4khg0Lj5+s8n87wRPXVhM53VrHZsRxdgkh7YgQU05he/WqR73vvZG/adpzVRj87F57GyBc0V+ZjdKqawsPNz1puF7IySQAgggAACcSRg3uB835hZGjFlkUqkpmjoFcfquMYxfNlaQEl6oOQBjPmtbzP1zzd/8IZ9w/ENdevJcXKpWqCQRQcnHyvaqLAWFBZ2fs56s5CdURIIAQQQQCDOBLKzc3TT699r9A/LVLZUml65qo2aHxKj6/gDSNID53Y85o9+Wq5eo2Z4979061BP95zRNH5urg8cs/AdkI/ZTQCFhZ2fs94sZGeUBEIAAQQQiEMB84So7iOna9L81apQuoRGdm+tFrEoLhwn6aFQOxzz+Lkr1ePFb7QzK0fnt6qjh889Wqnx9DjgUEAL3gn5mN0EUFjY+TnrzUJ2RkkgBBBAAIE4Fdi8fZe6jZiur39d6704b+SVx6pletVwR+swSQ9t4I7GPHXhzz8pHQAAGwlJREFUGl0+7Gtt35Wt04+uqf9e2Dy+3jESGiiFRVDUFBZByfqMS2HhE4zmCCCAAAIJKWBexNZ9xDf6auEalSuVphFXttax9UIsLhwl6aHiOxjzpPmr1OPFb7V1Z5aOb1Jdz13Ssti9VTuSOSMfi0Sp4DYUFnZ+znqzkJ1REggBBBBAIM4Ftu7I0tUvfqMvF6z27rkYdsWxatvgwHBG7SBJD2ege+zFcszmnSK9X/1OO7Ky1blxNQ25tKXKlEwL/TASYYfkY3azRGFh5+esNwvZGSWBEEAAAQQSQGDbzt3FhbnnokzJVA27/Fi1b3hQ8CO3TNKDH2A+e7AY87vfmac//Sjzdu2uRx6spy5szpmKQiaRfMxuhVNY2Pk5681CdkZJIAQQQACBBBEwxUXPl77VF/NWqXSJVA26uIVOaloj2NFbJOnBDqyQ6FGO+aWpi3X3/2Z6gf+vpblR+yiVSEuN2WEkwo7Jx+xmicLCzs9ZbxayM0oCIYAAAggkkMD2XVm67uUZ+nzOSpmHE/U78whd1q5ecEcQZZIe3IAiiBzFmJ+d8IseGTvHC35F+92PlOXpT0Vbk48VbVRYCwoLOz9nvVnIzigJhAACCCCQYAK7srJ193sz9erXS7yRX92pvvp2PTyYRDiKJD3mnD7GbCz//eFsDZ+8yBv29V3My+8a856KCCeRfCxCqAKaUVjY+TnrzUJ2RkkgBBBAAIEEFDBv6H5mwi967OO53uhPP6qmHj//GPc3GftI0uOGMcIx/7Ftp64f9Z0mzlvlDb1P1ya65rhD4+YwEmEg5GN2s0RhYefnrDcL2RklgRBAAAEEEljgf98t1W1v/eC9wK1VehU9f1krVSlXyt0RRZiku9uhg0gRjPnX1Zt11cjp+mXVZh1QMk1PnH+Muh5V08HOi1cI8jG7+aawsPNz1puF7IySQAgggAACCS4w5ZfV3k3dG7ft0iFVy+qZf7TQkbUruTmqCJJ0NztyGKWIMU9ZsFrXvjJDG7buVM1KZbxizJmXw8NIhFDkY3azRGFh5+esNwvZGSWBEEAAAQSSQGD+7xu9t3RnrtuqUmmpuudvTfWPNofY3yuQRIWFuXzs5amL1W/MLO9xss3qVtaQy1qqeoUySbACYnMI5GN27hQWdn7OerOQnVESCAEEEEAgSQQ2bNmpW9/8Xp/NXukd0ZnH1FL/c49S+dIloj/CJCks1m/Zob7v/KSPZq7wLM5pXlsPnXuU+3tSopdOyJ7kY3bTRmFh5+esNwvZGSWBEEAAAQSSSMB8Kv/CpF/18Ng53qfyDQ4qp2cuaaEmB1eM7iiToLCYsnyrbnnjB634Y5tKpqXo9lOa6KpO9e3P5kQnmlS9yMfsppPCws7PWW8WsjNKAiGAAAIIJKHAN4vWek88Msm0eVP3Hac28d53kWZefuFnS+DCYmdKqgY/P1aPL9ihnBx5RZZ5k/ZRdRzdf+LHMUnbko/ZTSyFhZ2fs94sZGeUBEIAAQQQSFKBNZu26+Y3fsh7nKq5p+CRvx+tww6uEPkRJ2Jh8cwzyunVS6aEykpJUd9TblDa1Vfp7jMOV9lSFpeFRa5WbFqSj9lNNYWFnZ+z3ixkZ5QEQgABBBBIYoHs7ByN+vo3PfzRHG3avkslUlN0bcah6tWlYWT3FyRYYbFpwa8q27ihUnOy82Y1JzVNKYsXSXXqJPFMx+bQyMfs3Cks7Pyc9WYhO6MkEAIIIIBAMRBYsWGb97buT2f97h1tg2rl1P+co9S2wYGFH32CFBbm3pL3vl+mjwe9qmeH3bb/MY0fL2VkFIOZDvcQycfsvCks7Pyc9WYhO6MkEAIIIIBAMREwyffYmSt0z+iftWrjdu+oj29SXbee3FhH1CrgvoMEKCxmLftD946eqemL1ungP1Zr8nNXKm2PMxZKS5MWccYiiGVOPmanSmFh5+esNwvZGSWBEEAAAQSKmYB5LO0jH8/R69OXeE+OMtvpR9XUzSc1UsPq+9x/EceFxcylG/TshF/04czl3s3Z5g3a1x/fUD3mj1fJ666VsrLkFRWDB0vduxezWQ7ncMnH7JwpLOz8nPVmITujJBACCCCAQDEVWLhqk578bL7G/LjMS8zNA6PObl5b12U0VMPq5XerxFlhYc66fP3rWj094Ze8m9K9wujomvrXaYerVuUDdo87M1NasEBq2JB7KwJc3+RjdrgUFnZ+znqzkJ1REggBBBBAoJgLzFnxh574ZJ4++fP+C8PRul5VXdSmrrrWr6gyVf68TGruXKlx45hobduZpfFzVuqFL3/Vt4vXeWMwhdDfjqnl3Ywe9Xs6YnI0ybNT8jG7uSxWhcW///1vffDBB/r+++9VqlQprV+/vkg980nCfffdpyFDhmjdunVq06aNnn76aR1xxBF5fc3Xe/furdGjR3tfO/PMMzVw4EBVrly5yPi5DVjIEVPREAEEEEAAgYgEfliyXgPHLdC4Ob/rzyukdPmsz3TvmKeUqhzlpKYqZciQ0C4r2pWVra8Wrtl9U/bMFdq4fZd3HKVKpOq8lnXUs/OhOuTAshEdG42CESAfs3MtVoXFvffe6yX7mZmZGjp0aESFxSOPPCJTkIwYMUKNGzfWgw8+qIkTJ2ru3LmqUGH3dZtdu3b1Ypriw2w9evRQvXr1NGbMmIhnh4UcMRUNEUAAAQQQ8CWwfMNWvflNpsZ9NkNvP3KR0sx1Un9u2ampGj/2a7XscJQqly3lK24kjc27N2b8tl5fzl+lD35artWbduR1q1WpjHep1hXt66l6xTKRhKNNwALkY3bAxaqwyKUyRcJNN91UZGFhzlbUqlXLa3vHHXd43bdv364aNWrIFBw9e/bU7Nmz1bRpU02dOtU7m2E28+927dppzpw5OuywwyKaIRZyREw0QgABBBBAIGqBrM/HKe3EE/brf+FF/TUt/WgdXbuSWqZX9R5da95qXb9aOR1csYxSUop+u7e5aXzN5u0yj8GdufQP7/KmGb+t06+rN++1vyplS3r3T5zVrLZaHlJFqX7fHB710dMxEgHysUiUCm5DYVGI38KFC3XooYdqxowZat68eV7Ls846yzvzMXLkSA0bNky33HLLfkWK+f6AAQPUrVu3fPdgChTzX+5mFnLdunW1YcMGVaxY0W5W6Y0AAggggAAC+wuYG6DT06Xsv142Z85Y/ONfr+mrHflfgmSezJR+YFmVL11CJdNSVbJEqkqlpXj/3pmVo1Ubt+n3P7Zr1abteU+k2nfHjaqXV8v0KjrlyIPVseFBXl+2+BSgsLCbFwqLQvymTJmiDh06aOnSpd6Zi9zNXOq0ePFiffzxx+rfv793mdS8efP2imQumzJFRd++ffPdQ79+/bx7N/bdKCzsFjS9EUAAAQQQKFRg6FCpZ8/9Ht1qzjR8uWC15iz/QwtXb/bONPy2dkuBxUJ++zAnHw4sX1qmkGiVXkUt0quoed0qqlS2JJOSIAIUFnYTlfCFRUEJ+p4s06dPV6tWrfK+FOmlULmFxbJly1SzZs28/ldffbWWLFmisWPHeoWFOXNh7rnYc2vUqJG6d++uPn365DtDnLGwW7j0RgABBBBAIGqBCB/dujMrW0vWbtHitVu0fWeWdmTlaOeubJmvm//MZUzVK5RRjYqlVaNiGR1YrpRKcDYi6mmJh44UFnazkPCFxerVq2X+K2wzN1KXKfPXTVGRFhZBXgq173hZyHYLmd4IIIAAAggggICtAPmYnWDCFxbRHH6khUXuzds333yzbr/9dm9XO3bsUPXq1fe7eXvatGlq3bq118b8u23btty8Hc3k0AcBBBBAAAEEEIiRAIWFHXyxKix+++03rV271nvfxGOPPaZJkyZ5eg0bNlT58rvfyNmkSRM99NBDOuecc7z/b57+ZP7/8OHDZS5vMpc+TZgwYb/HzZrLpQYPHuz1MfdgpKen87hZu7VJbwQQQAABBBBAIFQBCgs77mJVWFxxxRXe/RD7buPHj1dGRob3ZfNIOVNEmLZmy31Bnika9nxB3pFHHpkXxhQr+74gb9CgQbwgz25t0hsBBBBAAAEEEAhVgMLCjrtYFRZ2VMH2ZiEH60t0BBBAAAEEEECgKAHysaKECv8+hYWdn7PeLGRnlARCAAEEEEAAAQSiEiAfi4otrxOFhZ2fs94sZGeUBEIAAQQQQAABBKISIB+Lio3Cwo7NfW8WsntTIiKAAAIIIIAAAn4EyMf8aO3fljMWdn7OerOQnVESCAEEEEAAAQQQiEqAfCwqNs5Y2LG5781Cdm9KRAQQQAABBBBAwI8A+ZgfLc5Y2GkF2JuFHCAuoRFAAAEEEEAAgQgEyMciQCqkCZdC2fk5681CdkZJIAQQQAABBBBAICoB8rGo2PI6UVjY+TnrzUJ2RkkgBBBAAAEEEEAgKgHysajYKCzs2Nz3ZiG7NyUiAggggAACCCDgR4B8zI/W/m05Y2Hn56w3C9kZJYEQQAABBBBAAIGoBMjHomLjjIUdm/veLGT3pkREAAEEEEAAAQT8CJCP+dHijIWdVoC9WcgB4hIaAQQQQAABBBCIQIB8LAKkQppwKZSdn7PeLGRnlARCAAEEEEAAAQSiEiAfi4otrxOFhZ2fs94sZGeUBEIAAQQQQAABBKISIB+Lio3Cwo7Nfe8NGzaocuXKWrJkiSpWrOh+B0REAAEEEEAAAQQQKFTAFBZ169bV+vXrValSJbR8CnDGwidYUM0zMzO9hcyGAAIIIIAAAgggEFsB80FvnTp1YjuIBNw7hUWcTFp2draWLVumChUqKCUlJfBR5VbknCEJnDqQHTB/gbCGFpT5C406sB0xh4HRhhKY+QuFOdCdBDWHOTk52rhxo2rVqqXU1NRAjyEZg1NYJOOsRnBMXEMYAVIcN2H+4nhyIhga8xcBUpw3YQ7jfIKKGB7zl9jzZ0bPHMbnHFJYxOe8BD4qfiADJw50B8xfoLyBB2f+AicOfAfMYeDEge6A+QuUN5TgzGEozL53QmHhmyw5OvADmdjzyPwxf4ktkPij52cwseeQ+Uvs+eOMRfzOH4VF/M5NoCPbvn27HnroIfXt21elS5cOdF8Edy/A/Lk3DTMi8xemdjD7Yg6DcQ0rKvMXlnRw+2EOg7O1iUxhYaNHXwQQQAABBBBAAAEEEPAEKCxYCAgggAACCCCAAAIIIGAtQGFhTUgABBBAAAEEEEAAAQQQoLBgDSCAAAIIIIAAAggggIC1AIWFNSEBEEAAAQQQQAABBBBAgMKiGK6BZ555Ro899piWL1+uI444Qk8++aQ6depUDCXi+5DNU7veeecdzZkzRwcccIDat2+vRx55RIcddljewM1TMf75z3/q1Vdf1datW3XCCSfIzG+dOnXi++CK4ejMfN5555268cYbvZ85szF/8b8Qli5dqjvuuEMfffSR9zPWuHFjDR06VC1btvQGb97Se99992nIkCFat26d2rRpo6efftr73coWe4Fdu3apX79+euWVV7RixQrVrFlTV1xxhe666668tyozh7Gfp9wRTJw40ctPvv32Wy9Heffdd3X22WfnDTCSuTI/h71799bo0aO9fmeeeaYGDhyoypUrx8+BJvFIKCySeHLzO7TXX39dl156qZd8dujQQYMHD9YLL7ygWbNm6ZBDDilmGvF9uKeeeqouvPBCHXvssTJ/HP/1r3/pp59+8uaqXLly3uCvvfZajRkzRiNGjNCBBx6oW2+9VWvXrvV+KaelpcX3ARaj0U2fPl3nn3++KlasqC5duuQVFsxffC8Ck6A0b97cmzMzV9WrV9cvv/yievXq6dBDD/UGb4r9f//7397PoCk6HnzwQZnkaO7cuapQoUJ8H2AxGJ2ZmwEDBmjkyJFesffNN9+oW7du3jyZIp85jK9FYAr4yZMnq0WLFvr73/++X2ERyc9b165dlZmZ6RX7ZuvRo4f3M2v+VrIFL0BhEbxxXO3BfJpmfmCfffbZvHEdfvjh3icC5hNVtvgVWLVqlZfYfPHFF+rcubM2bNigatWq6aWXXtIFF1zgDXzZsmWqW7euPvzwQ51yyinxezDFaGSbNm3yfuZMMW+SmWbNmnmFBfMX/4ugT58+XpIzadKkfAdrPj2tVauWbrrpJu+shtnMWagaNWp4BUfPnj3j/yCTfIRnnHGGNx/mLFPuZhLWsmXLer87mcP4XQApKSl7FRaRzNXs2bPVtGlTTZ061Tt7aDbz73bt2nln//c84x+/R57YI6OwSOz58zX6HTt2eL9M33zzTZ1zzjl5fc2nNt9//72XsLLFr8CCBQvUqFEj76zFkUceqXHjxnmXPpkzFFWqVMkb+DHHHOMViubyDLbYC1x++eWqWrWq96lpRkZGXmHB/MV+booagUlQTIFuPv00vx9r166t6667TldffbXXdeHChd6ZixkzZnhnNnK3s846y7vswnxKzhZbgYcffljPPfecPvnkE++M0g8//KCTTz7ZK+4vuugi5jC201Po3vctLCL5eRs2bJhuueUWrV+/fq/Y5ufR/A42Z6vYghWgsAjWN66im0+zzR9G8wmcuV4/d+vfv7/3B9CcumeLTwHzSY1JVsylGbmfno4aNcr7JWk+Id1zM38069ev713mxhZbgddee807S2EuvyhTpsxehQXzF9u5iWTvZs7MZhKV8847T19//bV3dsL8bF122WWaMmWKd0mpuQ/DnLnI3cylF4sXL9bHH38cyW5oE6CA+d1p7m0yZ5DM5aFZWVnepWt9+/b19socBohvGXrfwiKSuTL5jLkscd68eXvt3RSV5u9l7rxbDo3uhQhQWBSj5ZFbWJgfTnNaMHczv2TNKWFzmpAtPgV69eqlDz74QF9++WXejdkFJaYnnXSS9ymq+ZSOLXYCS5YsUatWrbxPSs1ZJLPtecaC+Yvd3ES651KlSnlzaH5n5m7mplBzz8xXX32Vl5Sa363mpuDczZzRMPM/duzYSHdFu4AETHF/2223eTcEm3sszNl5Uxw+8cQTMmcTc5NV5jCgCbAIW1BhUdhcFfRBqTnb3717d5nLG9mCFaCwCNY3rqJzKVRcTUfEg7nhhhv0v//9z7sh1JyJyN24lCZiwpg0NHNmLjnc8yZ682mp+WOZmprqfZp94okncilbTGYnsp2mp6fLFOrmARe5m7k/zZyFMmcpIrk0I7I90SooAXPPmUkmzYczuZuZv5dfftn7MI05DErePi6XQtkbxiIChUUs1GO4T3Mzk3lMormRNHcz1xGby2y4eTuGE5PPrs0pfFNUmMftTZgwwbu/Ys8t9+Zf8wfSPHHIbObxfOZRs9y8Hfu53Lhxo3c5zJ6bORXfpEkT70Zfk/CYm++Zv9jPVUEjuPjii70zD3vevH3zzTdr2rRp3ifduTeTmq/dfvvtXhjzAY55yAI3b8fHvJqn5ZlCwjzVK3czf+uGDx/uXS7DHMbHPOU3ioJu3i7s5y335m3zM9q6dWsvrPl327ZtuXk7pKmmsAgJOl52k/u4WXOZjLkcyjyO7fnnn9fPP/8s8+kcW/wImJtEzeUy77333l5PsqhUqZL3XguzmT+W77//vndNqblB2LzTYs2aNTxuNn6mca+R7HkpFPMXp5O0x7DMJU/mfjTzIARTvJt7LMxlTub35j/+8Q+vpSkgchNVU/ybSzHMBwE8bjY+5te8s+Kzzz7z7osxl0J999133uNHr7zySm/umMP4mKfcUZin6JkHlZjNPBDBXLJmHvds/r6ZR+JH8vNmHjdrLpfKvc/QzLfJb3jcbDhzTWERjnNc7cWcrXj00Ue9T7fN04XMkxLM40vZ4kvAfFqT32Y+aTN/LM22bds27/phU4Ds+YI882k4W/wJ7FtYMH/xN0f7jsgU7uaGz/nz53uXIpobuXOfCmXa5r6wyyQxe74gz/xuZYu9gDlzePfdd3tnfleuXOndZG+eBnXPPffI3EPDHMZ+jvYcgSnKTSGx72buhzEfoEXy82aelLjvC/IGDRrEC/JCmmoKi5Cg2Q0CCCCAAAIIIIAAAsksQGGRzLPLsSGAAAIIIIAAAgggEJIAhUVI0OwGAQQQQAABBBBAAIFkFqCwSObZ5dgQQAABBBBAAAEEEAhJgMIiJGh2gwACCCCAAAIIIIBAMgtQWCTz7HJsCCCAAAIIIIAAAgiEJEBhERI0u0EAAQQQQAABBBBAIJkFKCySeXY5NgQQQAABBBBAAAEEQhKgsAgJmt0ggAACCCCAAAIIIJDMAhQWyTy7HBsCCCCAAAIIIIAAAiEJUFiEBM1uEEAAAQQQQAABBBBIZgEKi2SeXY4NAQQQQAABBBBAAIGQBCgsQoJmNwgggAACCCCAAAIIJLMAhUUyzy7HhgACCCCAAAIIIIBASAIUFiFBsxsEEEAAAQQQQAABBJJZgMIimWeXY0MAAQQQQAABBBBAICQBCouQoNkNAggggAACCCCAAALJLEBhkcyzy7EhgAACCCCAAAIIIBCSAIVFSNDsBgEEEEAAAQQQQACBZBagsEjm2eXYEEAAAQQQQAABBBAISYDCIiRodoMAAggggAACCCCAQDILUFgk8+xybAgggAACCCCAAAIIhCRAYRESNLtBAAEEEEAAAQQQQCCZBSgsknl2OTYEEEAAAQQQQAABBEISoLAICZrdIIAAAggggAACCCCQzAIUFsk8uxwbAggggAACCCCAAAIhCVBYhATNbhBAAAEEEEAAAQQQSGYBCotknl2ODQEEEEAAAQQQQACBkAQoLEKCZjcIIIAAAggggAACCCSzAIVFMs8ux4YAAggggAACCCCAQEgCFBYhQbMbBBBAAAEEEEAAAQSSWYDCIplnl2NDAAEEEEAAAQQQQCAkAQqLkKDZDQIIIIAAAggggAACySxAYZHMs8uxIYAAAggggAACCCAQkgCFRUjQ7AYBBBBAAAEEEEAAgWQWoLBI5tnl2BBAAAEEEEAAAQQQCEmAwiIkaHaDAAIIIIAAAggggEAyC1BYJPPscmwIIIAAAggggAACCIQkQGEREjS7QQABBBBAAAEEEEAgmQUoLJJ5djk2BBBAAAEEEEAAAQRCEqCwCAma3SCAAAIIIIAAAgggkMwCFBbJPLscGwIIIIAAAggggAACIQlQWIQEzW4QQAABBBBAAAEEEEhmAQqLZJ5djg0BBBBAAAEEEEAAgZAEKCxCgmY3CCCAAAIIIIAAAggkswCFRTLPLseGAAIIIIAAAggggEBIAhQWIUGzGwQQQAABBBBAAAEEklng/wFgdaGtgKwC+QAAAABJRU5ErkJggg==\" width=\"790\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "kbwbnJ_J4z82",
"colab_type": "text"
},
"source": [
"This is our signal still with the zeros in it.\n",
"Now take a look at the magnitude spectrum (in dB) of the original signal s:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "h_Pv5Ehx4z82",
"colab_type": "code",
"colab": {},
"outputId": "3cb23b4d-4d69-410a-8ed7-517677709fd6"
},
"source": [
"from scipy.signal import freqz\n",
"w,H=freqz(s)\n",
"plt.figure(figsize=(10,8))\n",
"plt.plot(w, 20*np.log10(abs(H)+1e-3))\n",
"plt.xlabel('Normalized Frequency')\n",
"plt.ylabel('dB')\n",
"plt.title('Magnitude Frequency Response')\n",
"plt.grid()"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option);\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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": {
"tags": []
}
},
{
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eONbpAmXGXb5JktqXOpeLjrkQlBuA5KLl0yZMlkhpOGXe/P/+eefaCHlmzS5bUdyIRduklO5UJYLuqiLfHMmtxQF8hj1Hv7A7UCB9WM+bxHs8zkZq7tnJu6NAhRQIcCGX4UiY1DAAIGYDb80UoF78qVxlxlNWWI2/J06dbKaSJm1lJnOwBKYOQ40/Lczw6+64X/ppZes+5/llqCoi9w+IbdRBJpXuzP80izK7R/S0Mf1gK7cohL1W4KYpeKk4RfjNGnSRIaQ2WLJh1xIye0psS2FChWyZtHtzvCLgdzaIgZRZ+Pl3+WWEZlJDzy0K7PIcruX3Gce2yIXdtIM22347c7wy77kwlFs5RmQU6dOWZ9VvoGJeTEZ83PFdQ+/jEEe3o56USK33sjzI0OHDrWe44htkW8yYs7ky605UmdysSO33gTewORkhl+eWZBxRV0CM/yBb0qcNPxR48T2+W53rAac+jgECtwTAmz474k0c5AUCC4Qs+GXLaTJl1lGadalcYut4ZdbGOTWDZl9DjQ+MuMqjabMdAYa/kBzKvfgyz3egSW+e/hvp+GXH6uSJjzmfmR/Mosrt0NI4yS3Gcki93DLswXSlAYafif38MuPOMnsqXzTEd+tJHFl4E4afvm88hCuNP3yNpf4Frv38EsMeZg05oPE8pCq3F4lD0MHGn65710aaJmhlvvZ41rsNvwyHnnwN3APf8xGOmb8li1bWm8ukluD5FsMeRYg2BJXwy91ILdHSf1IzcrFjdyeJrf4yPMl8m2X06VJkybWLWxSb7LYvYdfLjDkAlJyKjECi9SvXEQEvuG63YY/EC/q57vTsTq14foUoIC7Amz43fXm3ijgW4HYGv7YPmzMGX65b1reaCMNpdzSI7csyO0S0kDIg4SBhl9iyeyw3O8deEuPXAQE3tIjtz/IaxVlieuz2LmlR7aXJlq+bZAmTX5FVR4yln+TzyKvSpSHO+UecblFR9YJXJgEGn65dUJmZuUtRXL7jtxWFN9beqSRk/vk5V5+2Y80jdLkTpw4MdobhWLzvJOGX+IF3tIjD5bKm3Hkvn/5JkBmy9euXWu9FUkW+e8HHnjA+pwyQyw+cguJXNDJ7TyBW3pkXZntDjwgLPf9S0Mv34DINyMtWrSIbPjlWyBptOX2FbktSGzlYk+cZcZY8im3a9lt+GXfgbf0yMy5vLlGGm7JjzwTEfM+9cCDurKd1IbcohNsiavhl+3kHnqpUXngPPCNltzqIg/VysWF3Fsv32rIazfFU5zFUGpeLobkNqTANypSO/KWJtlOYgQa/sBbeuTCM/CWHrk1SfwCFxWBt/TIuCUP8tzG/Pnzrc8lz4XEfEtP1Df8BMYf9ZYeu5/PzliD+fLvFKCAPwXY8PszL/xUFHBd4HYbfvmg8vYembUP3FIhD2rKfcsyGxy14Q+8h/+HH36wLgjkrS1yC4Xcvy9NVeDB1ztt+OV2CGnopemVfUZ9A9CUKVOsVyJK4yXfWsgtSTJDH/M9/PI+ffmbvClFZn/lIkEaM2noor6lR8Yv45ZbSgLvYJfbbqSxluZMGrv4ljtt+CW2zHLLbVdyD7zcBiIXONIkykObgVeTynoLFiyw3toib6WRCyFxkdc2ysPUURt+MZOLAvn2RZpFuVCQNxbJw8cx38Mvza/cuy4XN3IBIM2/zNLLeuIszzw4afjlc0ojL57yf8Vemld5W43cDx9zkQsC8ZYHZu0s8TX8csEnt+5IPqO+KlQuJmTf8rC4fJsgtS21K99wyIWqXOTIK0Tl88rtMjLzLrfDyQWAXNwGbnULvIdf6lz+XS6kJA+SI6mpqG9ZEnfxi/kefrmIiO09/PHdw2/38wUunOIbqx1jrkMBCvhPgA2//3LCT0SBe0rA7usU7ykUFwcbeMVl1Ibfxd3f0a7kwkXehjNixAjr2yW/L4GGXy7QuFCAAhRwU4ANv5va3BcF7nEBuS1D3oIir/2UmV+5LULuS5b7v+VXR6M+9HuPU7k2/Lux4d++fbs1Cy/3s8ttRvLqUaknvy9s+P2eIX4+CpgrwIbf3NxyZBTwnYDc1xx437rc5y63nsi9z3JvcuChYN99aMM/0N3Y8Mt75+V2I3nIVh4Yl+cI7oaFDf/dkCV+RgqYKcCG38y8clQUoAAFKEABClCAAhSwBNjwsxAoQAEKUIACFKAABShgsAAbfoOTy6FRgAIUoAAFKEABClCADX8cNSCvl5NfmpRX+MkrzQoUKIBvvvnGethQFnl9m7zGT+4flXcxV6xY0XpPtfxYDRcKUIACFKAABShAAQr4RYANfyyZkAa+dOnS1g/vyA/pyDuX5a0Q8r5s+VVLWeSd4/Lea3lfuFwMyHuo582bZ73bW95DbWeRH/eRX2CU9UNCQuxswnUoQAEKUIACFKDAPS0gk67y4gf5ocHQ0NB72sLu4NnwxyIlv7Aov6opv2wY2yKFJkX25ptvWt8CyCI/VJM5c2brQqB9+/a2/Pft22f9iiQXClCAAhSgAAUoQAFnAnfj74c4G6G6tdnwx2Ipv1AprwqUhlx+uTJbtmzWL1HKr4fKsmPHDmumf9WqVdY3AYGladOm1i8+Bn5GPWZouSiQ/wUW+SVP+TXGqL/oqC61/0W6evUqZs+ebX1jkShRIh27uCdj0lVP2ulKVz0CeqKyXumqR0B9VJNqVWb3c+fObf2yuPyOC5fgAmz4YzEK/PhPp06d0Lx5cyxbtsyazZdfc3zqqaesn0+vUqWK9TPyMtMfWOSXHuVn1adOnRqrfM+ePa37/mMuY8eORVhYWPBscQ0KUIACFKAABShwjwtcuHABrVu3hkycpkqV6h7XsDd8NvyxOCVOnBjlypWzGvvA8sYbb2D58uXWr4QGGn65/z7qjwXJNwDy9VJ4eHis+jFn+M+cOWPd0nPs2DGtBStX9fILp/Xq1eMMv73jwtZadLXF5Hglujoms7UBXW0xOV6Jro7JbG1AV1tMjlYyyVT6J/nhRjb89kuADX8sVrly5bKaY/kFysAybNgw68FcmdW/3Vt6Yu5KCla+itJdsHKQT548GY0bN2bDb//YCLomXYMS3dYKdL0ttqAb0TUo0W2tQNfbYgu6EV2DEjlewSRTt/onx8g+3oANfyzJka+JZKY+6kO7HTt2xNKlS63Z/cBDu/Jv77zzjhXhypUr1tt8nDy061bBmnSQ++lYoquebNCVrnoE9ERlvdJVj4D6qCbVqlv9k/oseBeRDX8s9nLrTuXKla377Vu0aGHdwy+368g799u0aWNtIY19//79MWrUKOTPnx/9+vXDnDlzHL2W062CNekg9+5QuXXPdNWTDbrSVY+AnqisV7rqEVAf1aRadat/Up8F7yKy4Y/DftKkSejSpQu2bt1qPQkuD/AG3tIjmwR+eEse5I36w1vFihWznU23Ctakg9w2rgsr0lUPMl3pqkdAT1TWK131CKiPalKtutU/qc+CdxHZ8HtnD7cK1qSD3MN03bJruurJBl3pqkdAT1TWK131CKiPalKtutU/qc+CdxHZ8Htnz4bfQ3sVuzbp5KnCQ1UMuqqSjB6HrnTVI6AnKutVvatJpmz4ndcHG37nZsq2cKtgTTrIleErCERXBYixhKArXfUI6InKeqWrHgH1UU2qVbf6J/VZ8C4iG37v7DnD76G9il2bdPJU4aEqBl1VSXKGX48kXenqhoD6fZh0bmXD77w+2PA7N1O2hVsFa9JBrgxfQSC6KkDkDL8eRLrS1TUBPTvi+VW9q0mmbvVP6rPgXUQ2/N7Zc4bfQ3sVuzbp5KnCQ1UMuqqS5Ey0Hkm60tUNAfX7MOncyobfeX2w4XdupmwLtwrWpINcGb6CQHRVgMiZaD2IdKWrawJ6dsTzq3pXk0zd6p/UZ8G7iGz4vbPnDL+H9ip2bdLJU4WHqhh0VSXJmWg9knSlqxsC6vdh0rmVDb/z+mDD79xM2RZuFaxJB7kyfAWB6KoAkTPRehDpSlfXBPTsiOdX9a4mmbrVP6nPgncR2fB7Z88Zfg/tVezapJOnCg9VMeiqSpIz0Xok6UpXNwTU78Okcysbfuf1wYbfuZmyLdwqWJMOcmX4CgLRVQEiZ6L1INKVrq4J6NkRz6/qXU0ydat/Up8F7yKy4ffOnjP8Htqr2LVJJ08VHqpi0FWVJGei9UjSla5uCKjfh0nnVjb8zuuDDb9zM2VbuFWwJh3kyvAVBKKrAkTOROtBpCtdXRPQsyOeX9W7mmTqVv+kPgveRWTD752972b4/1yzH1lTJ0OF3Ok8VLl7dm3SydNP6nTVkw260lWPgJ6orFf1riaZsuF3Xh9s+J2bKdvCrYK1c5AfOn0JD/Sfiaypk2JxlzrKxmhyIDuuJo9f19joqkeWrnTVI6AnKutVvatJpm71T+qz4F1ENvze2ftqhn/zobNoMHgekiYKRUTvRh6q3D27Nunk6Sd1uurJBl3pqkdAT1TWq3pXk0zZ8DuvDzb8zs2UbeFWwdo5yDfsP42HhixASAiwo19jhMh/cIlXwI4rCZ0L0NW5mZ0t6GpHyfk6dHVuZmcLutpRcraOSaZu9U/OhP29Nht+D/PjVsHaOchX7TmJR4cusjS29m2ERAlCPZS5O3Ztx/XuGIm/PiVd9eSDrnTVI6AnKutVvatJpm71T+qz4F1ENvze2fvqlp5lO0+gxYjFlsaGXg2QIklCD2Xujl2bdPL0kzhd9WSDrnTVI6AnKutVvatJpmz4ndcHG37nZsq2cKtg7RzkC7cdQ5uRS62xrepeD+mSJ1Y2TlMD2XE1dew6x0VXPbp0paseAT1RWa/qXU0ydat/Up8F7yKy4ffO3lcz/LM3H0G7UcstjcVdakNez8klfgGTTp5+yjVd9WSDrnTVI6AnKutVvatJpmz4ndcHG37nZsq2cKtg7Rzk0zcdxgvfr7DGNrdzTeRKn1zZOE0NZMfV1LHrHBdd9ejSla56BPREZb2qdzXJ1K3+SX0WvIvIht87e1/N8E9efxCv/LjK0pjWsToKZE7poczdsWuTTp5+EqernmzQla56BPREZb2qdzXJlA2/8/pgw+/cTNkWbhWsnYNcfmW3w09rrLFNer0qimVLrWycpgay42rq2HWOi656dOlKVz0CeqKyXtW7mmTqVv+kPgveRWTD7529r2b4f125D2//stbS+O3lSiibK52HMnfHrk06efpJnK56skFXuuoR0BOV9are1SRTNvzO64MNv3MzZVu4VbB2DvJxy/agy+/rrbGNfaEiKufNoGycpgay42rq2HWOi656dOlKVz0CeqKyXtW7mmTqVv+kPgveRWTD7529r2b4v1+8Cz3+3GhpjG5XHjULZvJQ5u7YtUknTz+J01VPNuhKVz0CeqKyXtW7mmTKht95fbDhd26mbAu3CtbOQf7Ngp3oPWmTNbYRbcuiQdEsysZpaiA7rqaOXee46KpHl6501SOgJyrrVb2rSaZu9U/qs+BdRDb83tn7aoZ/+NztGDAlwtIY8kRpNCl5n4cyd8euTTp5+kmcrnqyQVe66hHQE5X1qt7VJFM2/M7rgw2/czNlW7hVsHYO8iEzt+Lj6VussX3UvCQeL5td2ThNDWTH1dSx6xwXXfXo0pWuegT0RGW9qnc1ydSt/kl9FryLyIbfO3tfzfB/Mn0LPp+51dLo90hxtK6Y00OZu2PXJp08/SROVz3ZoCtd9Qjoicp6Ve9qkikbfuf1wYbfuZmyLdwqWDsH+YfhERg2Z7s1tvebFEG7KrmVjdPUQHZcTR27znHRVY8uXemqR0BPVNareleTTN3qn9RnwbuIbPi9s/fVDH+fSZswcsFOS6NLo0JoXyOvhzJ3x65NOnn6SZyuerJBV7rqEdATlfWq3tUkUzb8zuuDDb9zM2VbuFWwdg7ynn9txOhFu6yxdapXAG/Uya9snKYGsuNq6th1jouuenTpSlc9Anqisl7Vu5pk6lb/pD4L3kVkw++dva9m+LtOWI+xS/dYGq/Vyoe3GxT0UObu2LVJJ08/ifZAMkEAACAASURBVNNVTzboSlc9Anqisl7Vu5pkyobfeX2w4XdupmwLtwrWzkHe+Ze1+GXlPmtsL1TLjW4PFlE2TlMD2XE1dew6x0VXPbp0paseAT1RWa/qXU0ydat/Up8F7yKy4ffO3lcz/B1/XoMJq/dbGk9XyoVeTYt5KHN37Nqkk6efxOmqJxt0paseAT1RWa/qXU0yZcPvvD7Y8Ds3U7aFWwVr5yB/dewq/L3uoDW2VuVzYMBjJZSN09RAdlxNHbvOcdFVjy5d6apHQE9U1qt6V5NM3eqf1GfBu4hs+L2z99UM/4vfr8C0TYctjUdLZ8MnLUt5KHN37Nqkk6efxOmqJxt0paseAT1RWa/qXU0yZcPvvD7Y8Ds3U7aFWwVr5yB/dvRyzIo4Yo3tweJZ8WWbMsrGaWogO66mjl3nuOiqR5eudNUjoCcq61W9q0mmbvVP6rPgXUQ2/N7Z+2qGv+03SzF/6zFLo27hzBj5dDkPZe6OXZt08vSTOF31ZIOudNUjoCcq61W9q0mmbPid1wcbfudmyrZwq2DtHOStvlqMJTtOWGOrXiAjvn+2grJxmhrIjqupY9c5Lrrq0aUrXfUI6InKelXvapKpW/2T+ix4F5ENv3f2vprhf2zYIqzcfdLSqJg7HX5uX8lDmbtj1yadPP0kTlc92aArXfUI6InKelXvapIpG37n9cGG37mZsi3cKlg7B/nDXyzAun2nrbGVzpkGE16pomycpgay42rq2HWOi656dOlKVz0CeqKyXtW7mmTqVv+kPgveRWTD7529r2b4G302H/8cPGNpFMmaCpM7VPNQ5u7YtUknTz+J01VPNuhKVz0CeqKyXtW7mmTKht95fbDhd26mbAu3CtbOQV73k7nYduScNbZ8mVJgRqcaysZpaiA7rqaOXee46KpHl6501SOgJyrrVb2rSaZu9U/qs+BdRDb83tn7aoa/xqDZ2H38gqWRI10yzH+ntocyd8euTTp5+kmcrnqyQVe66hHQE5X1qt7VJFM2/M7rgw2/czNlW7hVsHYO8ioDZmH/qYvW2DKnSoKlXesqG6epgey4mjp2neOiqx5dutJVj4CeqKxX9a4mmbrVP6nPgncR2fB7Z++rGf7yfWfg6NnLlkaasERY06O+hzJ3x65NOnn6SZyuerJBV7rqEdATlfWq3tUkUzb8zuuDDb9zM2VbuFWwdg7yUh9Mw6kLV62xhSVOgE0fNFQ2TlMD2XE1dew6x0VXPbp0paseAT1RWa/qXU0ydat/Up8F7yKy4ffO3lcz/MXen4pzl69ZGglCQ7C9X2MPZe6OXZt08vSTOF31ZIOudNUjoCcq61W9q0mmbPid1wcbfudmyrZwq2DtHOQF3puCK9duRI5tW99GSJggVNlYTQxkx9XEceseE131CNOVrnoE9ERlvap3NcnUrf5JfRa8i8iG3zt7X83w5+7yN27e/A9j0wcNEJY4oYc6/t+1SSdPP2nTVU826EpXPQJ6orJe1buaZMqG33l9sOF3bqZsC7cKNthBfv3GTeTtOjnauNb0qIc0YYmVjdXEQMFcTRyzG2Oiqx5lutJVj4CeqKxX9a4mmbrVP6nPgncR2fB7Z++bGf5LV6+jUPfwaBJLu9ZB5lRJPdTx/65NOnn6SZuuerJBV7rqEdATlfWq3tUkUzb8zuuDDb9zM2VbuFWwwQ7yM5euokTPada45IFdmfGf/04t5EgXpmysJgYK5mrimN0YE131KNOVrnoE9ERlvap3NcnUrf5JfRa8i8iG3zt738zwnzh/BWV6T7ckUiVNiDOXrmFGpxrIlymFhzr+37VJJ08/adNVTzboSlc9Anqisl7Vu5pkyobfeX2w4XdupmwLtwo22EF++MwlVOw305rdT588MY6cvYy/36iKovelVjZWEwMFczVxzG6Mia56lOlKVz0CeqKyXtW7mmTqVv+kPgveRWTD7529b2b49564gGoDZyNpolBkSJEE+05exIRXKqN0zrQe6vh/1yadPP2kTVc92aArXfUI6InKelXvapIpG37n9cGG37mZsi3cKthgB/nOY+dR66M5SJk0ITKlTILtR8/jpxcfwAN50isbq4mBgrmaOGY3xkRXPcp0paseAT1RWa/qXU0ydat/Up8F7yKy4ffO3jcz/FsOn0X9T+chXfLE1pt5/jl4Bt8/WwHVC2T0UMf/uzbp5OknbbrqyQZd6apHQE9U1qt6V5NM2fA7rw82/M7NlG3hVsEGO8g37D+Nh4YsQOZUSZA1dTKs2XsKXz9VDvWKZFY2VhMDBXM1ccxujImuepTpSlc9Anqisl7Vu5pk6lb/pD4L3kVkw++dvW9m+FfsOoHHhy9GrvRh1gz/sp0n8GXrMniwRFYPdfy/a5NOnn7SpquebNCVrnoE9ERlvap3NcmUDb/z+mDD79xM2RZuFWywg3x2xBG0G70cxbKlQtqwxJi/9Rg+aVESj5bJrmysJgYK5mrimN0YE131KNOVrnoE9ERlvap3NcnUrf5JfRa8i8iG3zt738zw/7lmPzr8tAaV86ZHWOIEmPHPEQx4tDhaVcjpoY7/d23SydNP2nTVkw260lWPgJ6orFf1riaZsuF3Xh9s+J2bKdvCrYINdpCPWbIb3f/YgAZFM1vv4p+8/hB6PVwUT1e+X9lYTQwUzNXEMbsxJrrqUaYrXfUI6InKelXvapKpW/2T+ix4F5ENv3f2vpnhHzpnGwaGb0bzstlx7cZNTFi9H90aF8YL1fN4qOP/XZt08vSTNl31ZIOudNUjoCcq61W9q0mmbPid1wcbfudmyrZwq2CDHeQDpkRg+NzteLZKbpy/fA0/r9iLt+sXwGu18ysbq4mBgrmaOGY3xkRXPcp0paseAT1RWa/qXU0ydat/Up8F7yKy4bdh379/f3Tt2hUdOnTA4MGDrS0uX76Mt99+G+PGjcPFixdRp04dDB06FNmz23/Q1a2CDXaQd5uwHj8u3YMOdfLj5IUr+H7xbrxROx861S9oQ+feXSWY670rc2cjp+ud+cW1NV3pqkdAT1TWq3pXk0zd6p/UZ8G7iGz4g9gvX74cLVq0QKpUqVCrVq3Ihv/ll1/GxIkTMXr0aKRPnx5vvfUWTpw4gZUrVyJBggS2MupWwQY7yN8Ytxp/rT2A7g8VwcFTFzFywU60r5EHXRoVtjWOe3WlYK73qsudjpuudyoY+/Z0paseAT1RWa/qXU0ydat/Up8F7yKy4Y/H/ty5cyhTpow1c9+nTx+UKlXKavhPnz6NjBkzYsyYMWjZsqUV4cCBA8iRIwcmT56MBg0a2MqoWwUb7CB/ZtQyzNl8FAMfL4Hdx8/jy9nb8Uzl+9Hz4aK2xnGvrhTM9V51udNx0/VOBdnw6xGkK13dFFC/L5POrW71T+qz4F1ENvzx2D/99NNIly4dPv30U9SsWTOy4Z81a5Z1C4/M6KdNmzYyQsmSJdGsWTP06tUr1qhyG5D8L7BIwcpFwrFjx6xvEHQtcpBPnz4d9erVQ6JEiW7ZTcuvl2HVnlP48omS2Hz4HD6ftR2tymdH74eL6PpIRsQN5mrEID0YBF31oNOVrnoE9ERlvap3NclU+qcMGTJYE7A6+yf1WfAuIhv+OOx/+ukna1Z/xYoVSJo0abSGf+zYsWjXrl205l3C1K9fH7lz58aIESNijdqzZ89YLwYkXlhYmGdV0H9NAhy6GIJXi1zH3nPAX3sSoELGG2iT74Znn4k7pgAFKEABClCAArEJXLhwAa1bt2bD76A82PDHgrV3716UK1cO06ZNg8zayxJ1hj+uhl9m0PPmzYvhw4fHmgK/zvBXHTQXh89cxoSXHsCKPSfRd/JmPFg8Cwa3KOGglO69VU2aLfFT9uiqJxt0paseAT1RWa/qXU0y5Qy/8/pgwx+L2R9//IFHHnkk2sO3169fR0hICEJDQzF16lTUrVvX8S09MXfl1j1owe7bK9ojHOevXMfczjWxYNsxdJuwAfWLZMZXT5VzXlH30BbBXO8hCqVDpatSzshgdKWrHgE9UVmv6l1NMnWrf1KfBe8isuGPxf7s2bPYvXt3tL/ILTyFChXC//73P+u+e3lo94cffrDe4CPLwYMHrVdy3m0P7V67fgP5uk2xxrCqez3M/OcwOv+6DjULZsTodhW8q8y7YM8mnTz9xE1XPdmgK131COiJynpV72qSKRt+5/XBht+mWdRbemQTeS3npEmTrNdyyoO98k7+48eP33Wv5Tx14QpKfTDdUtjatxGmbDgEeU1npTzpMe7FB2zq3JurmXTy9FMG6aonG3Slqx4BPVFZr+pdTTJlw++8Ptjw2zSL2fBfunQJnTt3htzPH/WHt2T23+7iVsHGd5DvPXEB1QbORrJECfBP74YI33AIL/2wEmVzpcVvL1e2O5R7cj2TTp5+SiBd9WSDrnTVI6AnKutVvatJpm71T+qz4F1ENvze2cOtgo3vIN+w/zQeGrIAmVImwbJudTF78xG0G7UcxbKlwqTXq3mo4/9dm3Ty9JM2XfVkg6501SOgJyrrVb2rSaZu9U/qs+BdRDb83tn7ouFftP0YWn+9FPkypcCMTjWwaNsxtB65FAUyp8C0jjU81PH/rk06efpJm656skFXuuoR0BOV9are1SRTNvzO64MNv3MzZVu4VbDxHeQT1x7A6+NWo0LudBjfvhJW7DqBx4cvRq70YZjbuZaysZoYyKSTp5/yQ1c92aArXfUI6InKelXvapKpW/2T+ix4F5ENv3f2vpjhH7VwJ3pN3IQHi2fFl23KYP2+02jyxQJkTZ0Ui7vU8VDH/7s26eTpJ2266skGXemqR0BPVNareleTTNnwO68PNvzOzZRt4VbBxneQD5oagS9nb8fTlXKhV9Ni2HzoLBoMnod0yRNbr+nkEreASSdPP+WZrnqyQVe66hHQE5X1qt7VJFO3+if1WfAuIht+7+x9McP/v1/X4ecVe/FWvQJ4vU5+7Dp2HjU/moMUSRJiQ68GHur4f9cmnTz9pE1XPdmgK131COiJynpV72qSKRt+5/XBht+5mbIt3CrY+A7y50Yvx8yII+j/aHE8USEnDpy6iMoDZiFxglBs6dtI2VhNDGTSydNP+aGrnmzQla56BPREZb2qdzXJ1K3+SX0WvIvIht87e1/M8Df9YgHW7juNr58qh3pFMuP4ucso22eGpbKjX2OEhoZ4KOTvXZt08vSTNF31ZIOudNUjoCcq61W9q0mmbPid1wcbfudmyrZwq2DjO8irDJiF/acuYsIrlVE6Z1qcvXQVxXtOs8YY0bshkiZKoGy8pgUy6eTpp9zQVU826EpXPQJ6orJe1buaZOpW/6Q+C95FZMPvnb3nM/w3b95Ewe7huHLtBua/Uws50oXh2vUbyNdtiqWypkc9pAlL7KGQv3dt0snTT9J01ZMNutJVj4CeqKxX9a4mmbLhd14fbPidmynbwq2CjesgP3PpKkrEMptfoNsUXLl+A4verY370iRTNl7TApl08vRTbuiqJxt0paseAT1RWa/qXU0ydat/Up8F7yKy4ffO3vMZ/h1Hz6H2x3NveSNPiZ5TcebSNeuXd+UXeLnELmDSydNPOaarnmzQla56BPREZb2qdzXJlA2/8/pgw+/cTNkWbhVsXAf5sp0n0GLEYtyfPgxzovyq7gP9ZuLQmUuY+FpVFM+eWtl4TQtk0snTT7mhq55s0JWuegT0RGW9qnc1ydSt/kl9FryLyIbfO3vPZ/j/XncQr45dhXK50uLXlytHStT+aA52HDuPn198ABXzpPdQyN+7Nunk6SdpuurJBl3pqkdAT1TWq3pXk0zZ8DuvDzb8zs2UbeFWwcZ1kH+zYCd6T9qEB0tkxZety0SO68HP52PjgTMY1a48ahXMpGy8pgUy6eTpp9zQVU826EpXPQJ6orJe1buaZOpW/6Q+C95FZMPvnb3nM/x9/96Er+fvxHNVc6P7Q0UiJZoPX4Tlu05iaJsyaFw8q4dC/t61SSdPP0nTVU826EpXPQJ6orJe1buaZMqG33l9sOF3bqZsC7cKNq6D/PVxqzFx7QF0a1wYL1TPEzmup75dhnlbjuKj5iXxeNnsysZrWiCTTp5+yg1d9WSDrnTVI6AnKutVvatJpm71T+qz4F1ENvze2Xs+w99i+GIs23UCQ54ojSYl74uUeGnMSoRvPITeTYuibaX7PRTy965NOnn6SZquerJBV7rqEdATlfWq3tUkUzb8zuuDDb9zM2VbuFWwcR3k1QfOxp4TF/DLS5VQ/v50kePq9PMa/L56P7o2LoQXq+dVNl7TApl08vRTbuiqJxt0paseAT1RWa/qXU0ydat/Up8F7yKy4ffO3tMZ/th+ZTdA0W3Cevy4dA/erJsfb9Yt4KGQv3dt0snTT9J01ZMNutJVj4CeqKxX9a4mmbLhd14fbPidmynbwq2Cje0gP3n+Ckr3nm6NZXOfhkiSMEHkuAIP87avngddGhdWNl7TApl08vRTbuiqJxt0paseAT1RWa/qXU0ydat/Up8F7yKy4ffO3tMZ/k0HzqDx5/ORLnlirOpeL5rCJ9M24/NZ29D2gVzo3ayYh0L+3rVJJ08/SdNVTzboSlc9Anqisl7Vu5pkyobfeX2w4XdupmwLtwo2toN8dsQRtBu9HIWzpsKUDtWijWnYnO34MDwCj5XJjo9blFQ2XtMCmXTy9FNu6KonG3Slqx4BPVFZr+pdTTJ1q39SnwXvIrLh987e0xn+ccv2oMvv61G7UCZ8+0z5aArfLdqF9//aiMbFs2Bom7IeCvl71yadPP0kTVc92aArXfUI6InKelXvapIpG37n9cGG37mZsi3cKtjYDvJPp2/BZzO34okKOdH/0eLRxjR+xV688+s61CyYEaPbVVA2XtMCmXTy9FNu6KonG3Slqx4BPVFZr+pdTTJ1q39SnwXvIrLh987e0xn+d39bh5+W70XHugXQoW7+aAqT1h3Aa2NXo0LudBjfvpKHQv7etUknTz9J01VPNuhKVz0CeqKyXtW7mmTKht95fbDhd26mbAu3Cja2g/zpb5dh7paj+PCx4mhZPme0Mc2KOIxnR69A8WypMfH1qsrGa1ogk06efsoNXfVkg6501SOgJyrrVb2rSaZu9U/qs+BdRDb83tl7OsPfcPA8RBw6i9HtyqNmwUzRFBZvP44nvl6CfJlSYEanGh4K+XvXJp08/SRNVz3ZoCtd9Qjoicp6Ve9qkikbfuf1wYbfuZmyLdwq2NgO8lIfTMOpC1cx9c3qKJglZbQxrd17Ck2/XIhsaZJh4bu1lY3XtEAmnTz9lBu66skGXemqR0BPVNareleTTN3qn9RnwbuIbPi9s/dshv/S1eso1D3cGvnaHvWROixRNIWth8+i3qfzkDYsEVb3qO+hkL93bdLJ00/SdNWTDbrSVY+AnqisV/WuJpmy4XdeH2z4nZsp28Ktgo15kO8+fh41Bs1B0kSh+OeDhggJCYk2pr0nLqDawNlIkjAUm/s0UjZe0wKZdPL0U27oqicbdKWrHgE9UVmv6l1NMnWrf1KfBe8isuH3zt6zGf6lO46j5VdLcH/6MMzpXOsWgePnLqNsnxnWv2/v1xgJQqNfEHhI5qtdm3Ty9BMsXfVkg6501SOgJyrrVb2rSaZs+J3XBxt+52bKtnCrYGMe5H+u2Y8OP61Bxdzp8HMsr928eOU6Cvf495afDb0aIEWShMrGbFIgk06efsoLXfVkg6501SOgJyrrVb2rSaZu9U/qs+BdRDb83tl7NsP/9bwd6Dv5Hzxc8j58/kTpWwRu3ryJPF0n4+ZNYFm3OsiUMqmHSv7dtUknTz8p01VPNuhKVz0CeqKyXtW7mmTKht95fbDhd26mbAu3CjbmQd5v8j/4at4OPF81N957qEis4ynSIxwXrlzH3M41kSt9cmVjNimQSSdPP+WFrnqyQVe66hHQE5X1qt7VJFO3+if1WfAuIht+7+w9m+Hv+PMaTFi9H10aFUL7GnljFSjXZzqOnbuCKR2qoXDWVB4q+XfXJp08/aRMVz3ZoCtd9Qjoicp6Ve9qkikbfuf1wYbfuZmyLdwq2JgH+ZMjl2LBtmP4pEVJPFome6zjqTZwFvaeuIjfXq6MsrnSKhuzSYFMOnn6KS901ZMNutJVj4CeqKxX9a4mmbrVP6nPgncR2fB7Z+/ZDH+DT+dh8+GzGPNcBVTLnzFWgcA6Pz5fEVXyZfBQyb+7Nunk6SdluurJBl3pqkdAT1TWq3pXk0zZ8DuvDzb8zs2UbeFWwcY8yMv0no4T568g/M1qKJQl9tt1mn25EGv2nsLXT5VDvSKZlY3ZpEAmnTz9lBe66skGXemqR0BPVNareleTTN3qn9RnwbuIbPi9s/dkhh+hCZC/2xRr1Cvfq4v0KZLEKvDEV0uweMdxfNaqFJqWyuahkn93bdLJ00/KdNWTDbrSVY+AnqisV/WuJpmy4XdeH2z4nZsp28Ktgo16kB+/cB0P9J9p/ZjW1j6NEBrHj2o9N3o5ZkYcwYBHi6NVhZzKxmxSIJNOnn7KC131ZIOudNUjoCcq61W9q0mmbvVP6rPgXUQ2/N7ZezLDH3H4App8sQCZUyXB0q514xz9a2NXYdK6g+jxUBE8WzW3h0r+3bVJJ08/KdNVTzboSlc9Anqisl7Vu5pkyobfeX2w4XdupmwLtwo26kE+f/sJPDt6BYplS4VJr1eLcyzv/LoW41fsQ+cGBfFqrXzKxmxSIJNOnn7KC131ZIOudNUjoCcq61W9q0mmbvVP6rPgXUQ2/N7ZezLD//uag/jfb+tRq2BGjGpXIc7R9/xrI0Yv2oVXa+VF5waFPFTy765NOnn6SZmuerJBV7rqEdATlfWq3tUkUzb8zuuDDb9zM2VbuFWwUQ/yrxbsxqCpm9G8bHYMal4yzrF8GB6BYXO2o12V+/F+k6LKxmxSIJNOnn7KC131ZIOudNUjoCcq61W9q0mmbvVP6rPgXUQ2/N7ZezLD/+HUrRi5YCfaV8+DLo0Lxzn6ITO34uPpW9CqfA4MeKyEh0r+3bVJJ08/KdNVTzboSlc9Anqisl7Vu5pkyobfeX2w4XdupmwLtwo26kHe5Y9N+HXlPrzTsCBeqRn3vfkj5+9An7//QdNS9+GzVqWVjdmkQCadPP2UF7rqyQZd6apHQE9U1qt6V5NM3eqf1GfBu4hs+L2z92SG/+WxazDjnyPo90hxtK4Y9+s2xy7dg64T1ls/uiU/vsXlVgGTTp5+yi9d9WSDrnTVI6AnKutVvatJpmz4ndcHG37nZsq2cKtgox7kT4xcjhW7T2JYmzJoVDxrnGOZsHofOv68FlXzZcAPz1dUNmaTApl08vRTXuiqJxt0paseAT1RWa/qXU0ydat/Up8F7yKy4ffO3pMZ/oafL8T2o+cx9oWKqJw3Q5yjD99wCC/9sBJlcqbB769U8VDJv7s26eTpJ2W66skGXemqR0BPVNareleTTNnwO68PNvzOzZRt4VbBRj3IK304B8fOXcGUDtVQOGuqOMcyb8tRPPXtMhTKkhLhb1ZXNmaTApl08vRTXuiqJxt0paseAT1RWa/qXU0ydat/Up8F7yKy4ffO3vUZ/kaNGqFIzxm4duMmFnepjaypk8U5+hW7TuDx4YuRK30Y5nau5aGSf3dt0snTT8p01ZMNutJVj4CeqKxX9a4mmbLhd14fbPidmynbwq2CDRzk1WrXR5m+s6zPH9G7IZImShDnWDYeOI0HP1+AjCmTYHm3usrGbFIgk06efsoLXfVkg6501SOgJyrrVb2rSaZu9U/qs+BdRDb83tm7PsNfolIt1PpkPpIkDMXmPo3iHfnOY+dR66M5SJEkITb0auChkn93bdLJ00/KdNWTDbrSVY+AnqisV/WuJpmy4XdeH2z4nZsp28Ktgg0c5LlKVUWzYUuQJVVSLOlaJ95xHD5zCRX7zURoCLC9X2OEhIQoG7cpgUw6efopJ3TVkw260lWPgJ6orFf1riaZutU/qc+CdxHZ8Htn7/oMf6oCFdHuu5W2HsQ9c+kqSvScZuls7tMQSRLGffuPh4Se7tqkk6enkDF2Tlc92aArXfUI6InKelXvapIpG37n9cGG37mZsi3cKtjAQX4zRxm8OX4dKuZOh5/bV4p3HNeu30C+blOsddb0qIc0YYmVjduUQCadPP2UE7rqyQZd6apHQE9U1qt6V5NM3eqf1GfBu4hs+L2zd32G/2T6Yug5KQINi2bB8LZlg468QLcpuHL9Bha9Wxv3pYn7jT5BAxm6gkknTz+liK56skFXuuoR0BOV9are1SRTNvzO64MNv3MzZVu4VbCBg3xnWCEMnrkNrcrnwIDHSgQdR4meU3Hm0jXM6FQD+TKlCLr+vbaCSSdPP+WOrnqyQVe66hHQE5X1qt7VJFO3+if1WfAuIht+7+xdn+FfF5oX3yzcjRer50HXxoWDjrxC3xk4cvYy/n6jKorelzro+vfaCiadPP2UO7rqyQZd6apHQE9U1qt6V5NM2fA7rw82/M7NlG3hVsEGDvKl1+/H2GX70KFOfnSsVyDoOKoNnIW9Jy7it5cro2yutEHXv9dWMOnk6afc0VVPNuhKVz0CeqKyXtW7mmTqVv+kPgveRWTD75296zP8sy/kwB9rD6JLo0JoXyNv0JHX+2Quth45h7EvVETlvBmCrn+vrWDSydNPuaOrnmzQla56BPREZb2qdzXJlA2/8/pgw+/cTNkWbhVs4CD/+/R9mLbpCHo3K4a2D+QKOo4mQxZg/f7TGPVMedQqlCno+vfaCiadPP2UO7rqyQZd6apHQE9U1qt6V5NM3eqf1GfBu4hs+L2zd32G/9ejmTF/23F83LwkHiubPejIHx+2CCt2n8TwJ8ugYbGsQde/11Yw6eTpp9zRVU826EpXPQJ6orJe1buaZMqG33l9sOF3bqZsC7cKNnCQjzmQASt2n8KwNLVJngAAIABJREFUNmXQqHjwBv7JkUuxYNsxDG5ZCs1KZ1M2blMCmXTy9FNO6KonG3Slqx4BPVFZr+pdTTJ1q39SnwXvIrLh987e9Rn+EbvSYtPBsxjdrjxqFgx+i85zo5djZsQRDHi0OFpVyOmhlD93bdLJ00/CdNWTDbrSVY+AnqisV/WuJpmy4XdeH2z4nZsp28Ktgg0c5J9uSYVdxy9gfPtKqJA7XdBxvPrjKvy9/iB6PVwUT1e+P+j699oKJp08/ZQ7uurJBl3pqkdAT1TWq3pXk0zd6p/UZ8G7iGz4vbN3fYa/34bkOHz2Mia9XhXFsgV/r36n8Wvw+6r9tt/q4yGlJ7s26eTpCWAcO6WrnmzQla56BPREZb2qdzXJlA2/8/pgwx+LWf/+/fH7778jIiICyZIlQ+XKlfHhhx+iYMGCkWtfvnwZb7/9NsaNG4eLFy+iTp06GDp0KLJnD/4wbCCIWwUbOMjfW50UZy9dw6y3aiBPxuC/nNvl9/UYt2wPOtUrgDfq5HdeXYZvYdLJ00+poquebNCVrnoE9ERlvap3NcnUrf5JfRa8i8iGPxb7hg0bolWrVihfvjyuXbuGbt26Yf369di0aROSJ09ubfHyyy9j4sSJGD16NNKnT4+33noLJ06cwMqVK5EgQQJbGXWrYOUg//vvyXh7WSJcu3ETS7rUQZbUSYN+xl4TN2LUwl14pWZevNOwUND177UVTDp5+il3dNWTDbrSVY+AnqisV/WuJpm61T+pz4J3Ednw27A/evQoMmXKhLlz56J69eo4ffo0MmbMiDFjxqBly5ZWhAMHDiBHjhyYPHkyGjRoYCMqXL2l569Jk/HW0oTW51r7fn2kTpYo6GccMCUCw+dux7NVcqNHkyJB17/XVjDp5Omn3NFVTzboSlc9Anqisl7Vu5pkyobfeX2w4bdhtm3bNuTPn9+a5S9WrBhmzZpl3cIjM/pp06aNjFCyZEk0a9YMvXr1shHV3Yb/lz8no+uKfxv+rX0bIVGC0KCfcfCMLRg8YyvaVMyJvo8UD7r+vbaCSSdPP+WOrnqyQVe66hHQE5X1qt7VJFM2/M7rgw1/ELObN2+iadOmOHnyJObPn2+tPXbsWLRr1w5yH3/UpX79+sidOzdGjBgRa1RZP+o2UrDyrcCxY8eQKlUq59mzuYUc5OMnTUfPVQmRKEEINvWsZ2vLr+bvxKBpW/FI6fsw8NFitra5l1YS1+nTp6NevXpIlCj4Nyb3ks2djJWud6IX97Z0paseAT1RWa/qXU0ylf4pQ4YM1h0XOvsn9VnwLiIb/iD2r776Kv7++28sWLAg8oHcuBp+afzy5s2L4cOHxxq1Z8+esc7+S7ywsDCtVXD4ItBvTUKEJbiJ/hWu29rX3IMh+H1XApROfwPPFLhhaxuuRAEKUIACFKAABXQKXLhwAa1bt2bD7wCZDX88WK+//jr++OMPzJs3z5q5Dyy3e0uPlzP8306Yjo/WJ0SWVEkwv3MNWyXy84p9eO/PTahTKCOGtylta5t7aSWTZkv8lDe66skGXemqR0BPVNareleTTDnD77w+2PDHYia38UizP2HCBMyZM8e6fz/qEnho94cffkCLFi2sPx08eND6BsCvD+1+Pm4yhmxKiDwZk2PWWzVtVcrvq/ah0/i1qJY/A8Y8V9HWNvfSSibdD+mnvNFVTzboSlc9Anqisl7Vu5pkynv4ndcHG/5YzF555RXrPv0///wz2rv3U6dObb2XXxZ5LeekSZOs13KmS5fOeif/8ePHfftazkE/TsFXEQlQPFtqTHy9qq1Kmbz+IF75cRUq3J8O41+qZGube2klk06efsobXfVkg6501SOgJyrrVb2rSaZs+J3XBxv+WMxCQkJilRw1ahSeeeYZ62+XLl1C586drQuDqD+8JQ/h2l3cKlg5yPuOmYLRWxKgQu50GN/eXvM+K+Iwnh29AiWyp8Zfr9m7SLA7dhPWM+nk6ad80FVPNuhKVz0CeqKyXtW7mmTqVv+kPgveRWTD7529q+/hf3/0FIzdngA1C2bE6HYVbI164bZjaDNyKQpmTompHatHbnPjxk0Mm7sdYxbvxvPVcuO5qrkR10WSrR3dpSuZdPL0UwroqicbdKWrHgE9UVmv6l1NMmXD77w+2PA7N1O2hVsFKwd5l2+n4NedCdC4eBYMbVPW1hhW7j6Bx4YtRq70YZjbuVbkNsPmbMeH4RGR/3+3xoXxQvU8tmKatJJJJ08/5YWuerJBV7rqEdATlfWq3tUkU7f6J/VZ8C4iG37v7F2d4e/09RRM3JMAj5XJjo9blLQ16g37T+OhIQuQJVVSLOlax9pGHmiu9dEc7Dp+AVXypcfCbceRLnliLPxfbSRLnMBWXFNWMunk6aec0FVPNuhKVz0CeqKyXtW7mmTKht95fbDhd26mbAu3ClYO8teGh2Pq/lA8VSkXPmhq70e0th05i7qfzEOasERY06O+Ne6IQ2fQcPB8JE4YiuXd6qLJkAXYc+ICejYpgmeq/PfqUmVIPg5k0snTT8x01ZMNutJVj4CeqKxX9a4mmbrVP6nPgncR2fB7Z+/qDP8LQ8Mx52Ao2tfIgy6NCtsa9d4TF1Bt4GwkTRSKiN6NrG0Gz9iCwTO2om7hzBj5dDmMXrgTPSduQumcaTDhlSq24pqykkknTz/lhK56skFXuuoR0BOV9are1SRTNvzO64MNv3MzZVu4VbBykD/7RTjmHw7FG7XzoVP9grbGcOTsJVToOxPy0qId/RpbD+a2/WYp5m89hr6PFEObirlw6PQlPND/33Vkxj9DiiS2YpuwkkknTz/lg656skFXuuoR0BOV9are1SRTt/on9VnwLiIbfu/sXZ3hb/dFOBZIw18nPzrVK2Br1GcuXUWJntOsdTf3aYgkCROg+sDZ1i08P7/4ACrmSW/97aEh87Fh/xkMerwEmpez/1pSWx/CxyuZdPL0EzNd9WSDrnTVI6AnKutVvatJpmz4ndcHG37nZsq2cKtg5SB/5otwLDwcig518qOjzYb/8rXrKPheuDXedT3rI2nCBCjUfQpu3ASWdq2DzKmSWn/7dPoWfDZzKx4snhVftimjzMfvgUw6efrJmq56skFXuuoR0BOV9are1SRTt/on9VnwLiIbfu/sXZ3hDzT8b9bNjzfr2pvhlzfy5Ok6GTdvAsu61cH5y9etN/TIPf3/fNAw8t37S3YcR6uvliBr6qRY3OXft/ncC4tJJ08/5YuuerJBV7rqEdATlfWq3tUkUzb8zuuDDb9zM2VbuFWwcpA//UU4Fh0ORce6BdChbn7bY5AZ/UtXb2D+O7Ww7eg5tBu1HIWypET4m//9ENeFK9dQvOc0XL9xE4u71EbW1Mlsx7+bVzTp5OmnPNBVTzboSlc9Anqisl7Vu5pk6lb/pD4L3kVkw++dvasz/E8PCceiI6HW/ftyH7/dpdQH03DqwlXM6FQdC7Yes97I06BoZoxoWy5aiAc/n4+NB85gaJsyaFw8q93wd/V6Jp08/ZQIuurJBl3pqkdAT1TWq3pXk0zZ8DuvDzb8zs2UbeFWwcpB/tSQcCw+Eoq36hXA6w4a/gf6zcShM5cw6fWq+HXlPoxetAvtq+dBl8bRX+353h/r8cOSPXihWm50e7CIMiM/BzLp5OknZ7rqyQZd6apHQE9U1qt6V5NM3eqf1GfBu4hs+L2zd3WGP9Dwv12/AF6rbX+Gv8qAWdh/6iL+eLUKhszcipkRRyJfyRmVTi4G3v5lLSrcnw7jX6rkoap7uzbp5OmeWvA90TW40e2sQdfbUQu+DV2DG93OGnS9HbX4tzHJlA2/8/pgw+/cTNkWbhVs1Bl+pw1/4DWcv79SGX0mbcKqPacw/MmyaFgsSzSHDftP46EhC6xf5V3dvV7kA73KsHwYyKSTp5946aonG3Slqx4BPVFZr+pdTTJ1q39SnwXvIrLh987e1Rn+tkPCseRIKDo3KIhXa+WzPeqag2Zj1/EL+PWlSujy+3psPXIOY5+viMr5MkSLcenqdRTpEW69slPe6JMp5b+v7DR5Menk6ac80VVPNuhKVz0CeqKyXtW7mmTKht95fbDhd26mbAu3ClYO8ic/D8fSo84b/tofz8GOo+cxvn0lvDFutXU//8TXqqJ49tS3OMgrO3ceO48fn6+IKjEuCJSh+SiQSSdPH7GCrnqyQVe66hHQE5X1qt7VJFO3+if1WfAuIht+7+xdneEPNPzvNCyIV2ran+Gv+8lcbDtyDuNeeADPf7cc569cx5y3a+L+DMlvkXvx+xWYtukw3m9SBO2q5PZQ1p1dm3TydEfM3l7oas/J6Vp0dSpmb3262nNyuhZdnYoFX98kUzb8wfMdcw02/M7NlG3hVsHKQd7m83AsOxqK/zUshJdr5rU9hgafzsPmw2cx5rkKaPvNMmu7le/VRfoUSW6J8dHUzfhi9jY8USEn+j9a3PY+7tYVTTp5+ikHdNWTDbrSVY+AnqisV/WuJpm61T+pz4J3Ednwe2fv6gx/oOF/t1EhvFTDfsPfcPA8RBw6iy9al8ZrY1dbWlv6NELihKG3yP25Zj86/LQG5XKlxa8vV/ZQ1p1dm3TydEfM3l7oas/J6Vp0dSpmb3262nNyuhZdnYoFX98kUzb8wfMdcw02/M7NlG3hVsHKQd7683AsPxqKLo0Kob2Dhj/wg1p9mhXDe39sQNJEoYjo3ShWg/X7TqPJFwuQKWUSLOtWV5mTXwOZdPL0kzFd9WSDrnTVI6AnKutVvatJpm71T+qz4F1ENvze2bs6w9/6s3AsPxaKro0L4cXq9mf4mwxZgPX7T1tv9xk0dTMypkyC5XE086cuXEGpD6Zbov980BDJEifwUFf/rk06eerXsr8Hutq3crImXZ1o2V+XrvatnKxJVyda9tY1yZQNv72cR12LDb9zM2VbuFWwcpA/8Vk4VhwLRbfGhfFC9Ty2x9D0y4VYu/cUXqyeB1/N24E8GZNj1ls1Y93+5s2bKNFrGs5euobpHasjf+aUtvdzN65o0snTT/501ZMNutJVj4CeqKxX9a4mmbrVP6nPgncR2fB7Z+/qDP/tNvyPDF2I1XtOoUW57Bi/Yh9K5kiDP1+tEqda48/mY9PBM/j2mXKoXSizh7r6d23SyVO/lv090NW+lZM16epEy/66dLVv5WRNujrRsreuSaZs+O3lnDP8zp20bOFWwcpB3uqzcKw8For3HiyM56vZn+F/fNgirNh9Eg2KZsbUjYdRLX8GjHmuYpweL41ZifCNh9CzSRE8Y/irOU06eWop8NsMStfbhAuyGV3pqkdAT1TWq3pXk0zd6p/UZ8G7iJzh987e1Rn+2234W4xYjGU7T6Bi7nRYuvMEGhfPgqFtysap1vfvTfh6/k48WyU3ejQp4qGu/l2bdPLUr2V/D3S1b+VkTbo60bK/Ll3tWzlZk65OtOyta5IpG357OecMv3MnLVu4VbBykLccHI5Vx0PR/aEieK6q/R/FavXVYizZcQKFsqS0Xs/ZslwOfPh4iTg9xizehe5/bkS9Ipnx9VPltLj5JahJJ0+/mMrnoKuebNCVrnoE9ERlvap3NcnUrf5JfRa8i8gZfu/sXZ3hDzT8PR4qgmcdNPxtRi7Bwm3HkTV1Uhw8fQnPV82N9x6Ke+Z+9uYjaDdquXWBEP5mdQ919e/apJOnfi37e6CrfSsna9LViZb9delq38rJmnR1omVvXZNM2fDbyzln+J07adnCrYKVg7zF4HCsPh6K95sUQTsH99a3/WYp5m89hmSJEuDi1evoWLcAOtTNH6fH5kNn0WDwPKQNS4TVPeprcfNLUJNOnn4x5Qy/vkywXvXY0pWuegTURzWpVt3qn9RnwbuInOH3zt7VGf5Aw+/0Ydqnv12GuVuORioFu2A4ef4KSvf+9138m/s0RJKE5r6L36STp4eHwS27pquebNCVrnoE9ERlvap3NcmUDb/z+mDD79xM2RZuFawc5M0Hh2PN8VD0ergonq58v+0xtBu1DLM3/9fwf9S8JB4vmz3O7eVd/AXfC8eV6zcw/51ayJEuzPa+7rYVTTp5+smernqyQVe66hHQE5X1qt7VJFO3+if1WfAuIht+7+xdneFv/mk41pwIxQdNi+KpSvYb/ue/W44Z/xyJVBr+ZFk0LJYlXrWqH87CvpMX8dvLlVE2V1oPhfXu2qSTp14pZ9Hp6szL7tp0tSvlbD26OvOyuzZd7UrZX88kUzb89vMeWJMNv3MzZVu4VbDWDP9tNvwvfL8C0zcdjhzzN0+XQ53C8f+g1qNDF2LVnlMY1qYMGhXPqszLb4FMOnn6yZauerJBV7rqEdATlfWq3tUkU7f6J/VZ8C4iG37v7F2d4X/803CsPRGK3k2Loq2DGf7AD2kFmEa1K49aBTPFq/byDysxZYP5P75l0snTw8Pgll3TVU826EpXPQJ6orJe1buaZMqG33l9sOF3bqZsC7cKVg7yxz4Nxzpp+JsVQ9sHctkewys/rsTk9Yci1//+2QqoXiBjvNv3/GsjRi/ahVdq5sU7DQvZ3tfdtqJJJ08/2dNVTzboSlc9Anqisl7Vu5pk6lb/pD4L3kVkw++dvasz/IGGv0+zYnjSQcP/2thVmLTuYKTSj89XRJV8GeJV+3L2NgyauhmPlcmOj1uU9FBY765NOnnqlXIWna7OvOyuTVe7Us7Wo6szL7tr09WulP31TDJlw28/74E12fA7N1O2hVsFKwf5o5+EY/3JUPR9pBjaVLQ/w//GuNX4a+2ByDGPe+EBVMqbPl6DX1fuw9u/rEW1/Bkw5rmKyrz8Fsikk6efbOmqJxt0paseAT1RWa/qXU0ydat/Up8F7yKy4ffO3tUZ/kDD3++R4mhdMaftUXf8eQ0mrN4fuf749pVQIXe6eLefv/Uo2n6zDAUyp8C0jjVs7+tuW9Gkk6ef7OmqJxt0paseAT1RWa/qXU0yZcPvvD7Y8Ds3U7aFWwUrB/kjn4Rjw8lQ9H+0OJ6oYL/hf2v8Wvy2al/kmO28ajPi0Bk0HDwf6ZInxqru9ZR5+S2QSSdPP9nSVU826EpXPQJ6orJe1buaZOpW/6Q+C95FZMPvnb2rM/yBhn/Ao8XRykHD3/mXtfhl5X8N/x+vVkGpHGniVTt85hIq9puJ0BBgW9/GCJX/MHAx6eTpp/TQVU826EpXPQJ6orJe1buaZMqG33l9sOF3bqZsC7cKVg7yZp+EY+PJUHz4WHG0LG9/hv/d39bhp+V7I8c88bWqKJ49dbwGl65eR6Hu4dY6a9+vj9TJEikz81Mgk06edPWTgJ7Pwnqlqx4BPVFZr+pdTTJ1q39SnwXvIrLh987e1Rn+ph+HY9Mp5w1/l9/XY9yyPZFKf79RFUXvi7/hl5ULdZ+CS1dvYF7nWsiZPsxDZX27NunkqU/JeWS6OjezswVd7Sg5X4euzs3sbEFXO0rO1jHJlA2/s9zL2mz4nZsp28KtgpWDPNDwD3ysBFqUz2F7DO/9sR4/LPmv4Q9/sxoKZUkVdPtK/Wfi4OlL+PPVKigZ5BagoMF8uoJJJ08/EdNVTzboSlc9Anqisl7Vu5pk6lb/pD4L3kVkw++dvScz/AMfL4EW5ew3/D3+3IDvF++OVJresTryZ04ZVK3h4HmIOHQW3z1bATXi+KGu0xeuYsXuEyiWLTUyp0oaNKbfVjDp5OknW7rqyQZd6apHQE9U1qt6V5NM2fA7rw82/M7NlG3hVsHKQf7wx+H451QoBj1eAs0dNPyBX80NDHrmWzWQN2OKoAZPfLUEi3ccx2etSqFpqWy3rC/3+T82bBE2HjiDRAlC8GXrMqhfNEvQuH5awaSTJ139JKDns7Be6apHQE9U1qt6V5NM3eqf1GfBu4hs+L2zd3WGP9Dwf9S8JB4vm932qD+YuAnfLtwZuf6ct2vi/gzJg27/8g8rMWXDIfR6uCiernz/Lev3nrQJ3yz4L27GlEkwo1ONu+oBX5NOnkET6uIKdNWDTVe66hHQE5X1qt7VJFM2/M7rgw2/czNlW7hVsHKQN/koHBGnQ/Fx85J4zEHD3/fvTfh6/n+N+fx3aiFHuuAP4QYe9u1YtwA61M0fzezq9Rso12cGTl+8ii9al8Yn07Zgx7Hz6FSvAN6oE31dZdgaApl08tTAc9sh6XrbdPFuSFe66hHQE5X1qt7VJFO3+if1WfAuIht+7+xdneEPNPyftCiJR8vYn+HvP/kfjJi3I1Jp4bu1kS1NsqBqH4ZHYNic7Xim8v3o+XDRaOsv2nYMrUcutX6Ya3m3utYv+b79y9q77pd5TTp5Bk2oiyvQVQ82XemqR0BPVNareleTTNnwO68PNvzOzZRt4VbBykH+0Efh2Hw6FJ+2LIlHSttv+AONe2DQS7vWsfWA7VfztqPf5Ag8UjobPm1ZKppZ4LmAFuWyY+DjJa2Z/nJ9puPq9Zuw+1CwsiTcQSCTTp53wKB8U7oqJ7UC0pWuegT0RGW9qnc1ydSt/kl9FryLyIbfO3tXZ/gf/CgcW06HYnDLUmhW+taHaONiGDQ1Al/O3h75Z5mRl/vtgy3jl+/FO7+tQ82CGTG6XYVoq9f9ZC62HTmHr9qWjXxQ99nRyzEr4gjeqlcAr98lt/WYdPIMlk83/05XPdp0paseAT1RWa/qXU0yZcPvvD7Y8Ds3U7aFWwUrB/ntNvyfTNuMz2dtixzzqu71rFtxgi1TNx5C+zErUSpHGvzxapXI1S9fu44iPabi+o2biPptwZjFu9D9z42olj8DxjxXMVh4X/zdpJOnL0D//0PQVU826EpXPQJ6orJe1buaZOpW/6Q+C95FZMPvnb0nM/xxvSYzLobBM7Zg8IytkX9e26M+UoclCqq2bOcJtBixGPenD8OczrUi1//n4Bk0+mw+UiVNiLXv10dISIj1tw37T+OhIQuQUv69R32Ehv77735eTDp5+smZrnqyQVe66hHQE5X1qt7VJFM2/M7rgw2/czNlW7hVsHKQNx4Ujq1nQuN8L35cg/p85lZ8Mn1L5J/X96yPlEmDN/xbDp9F/U/nWa/ZlMY+sPy5Zj86/LQG5XKlxa8vV47892vXb6BEr2m4cOU6pnWsjgI2ftxLWSJuM5BJJ8/bJNCyGV21sPIefj2sdKWrJgH1YU06t7rVP6nPgncR2fB7Z+/qDH+g4f/8idJ4uOR9tkf95extGDR1c+T6mz5ogLDECYNuf/D0RVTqPwsJQ0OwrV/jyPUDzwS0rpgT/R4pHi1Oq68WY8mOExjwaHG0qpAz6D68XsGkk6fXllH3T1c92aArXfUI6InKelXvapIpG37n9cGG37mZsi3cKlg5yBsNCse2M6EY8kRpNHHQ8A+dsw0Dw/9r+CN6N0TSRAmCGpy+cBUlP5hmrbelTyMkThhq/ffz363AjH8Oo2eTInimSu5ocQJvBHqiQk70fzT6xUDQHXqwgkknTw/44twlXfVkg6501SOgJyrrVb2rSaZu9U/qs+BdRDb83tm7OsPfaNBUbDsTYv3Q1UMl7M/wj5i7Hf2nREQqbe3bCIkS/Nu8x7dcuXYDBd6bYq2ypkc9pAn790HfWh/Nwc5j5zH2+YqonC9DtBCB233K358Wv7z03+0+wfbl1d9NOnl6ZRjbfumqJxt0paseAT1RWa/qXU0yZcPvvD7Y8Ds3U7aFWwUrB3nDgVOx/WwIvmxdBg+WyGp7DF/P24G+k/+JXH9Hv8a2H6jN322y9W79Re/Wxn1pkuHmzZvWG3ouXr2OuZ1rIlf65NE+R+DB3bRhibC6x3/3/dv+sC6vaNLJ02W6eHdHVz3ZoCtd9Qjoicp6Ve9qkqlb/ZP6LHgXkQ2/d/auzvAHGv6hbcqgcXH7Df83C3ai96RNkUq7BjxoW6xkr2nWj2rN6FQD+TKlwLnL11Ds/anW9rE9C3DxynUUeT8cN28CK9+ri/Qpgr/v3/aH0bCiSSdPDTy3HZKut03HCyk9dHSlqwcC6ndp0rmVDb/z+mDD79xM2RZuFawc5A0GTsWOsyEY1qYMGjlo+Ect3IleE/9t+GM+gBsMolL/mTh4+hL+eq0KSmRPgx1Hz6H2x3ORIklCbOjVINbNq344C/tOXsTPLz6AinnSB9uFp3836eTpKWSMndNVTzboSlc9Anqisl7Vu5pk6lb/pD4L3kVkw++dvasz/PUHTsXO22j4v1+8Cz3+3GgpyYO38gCu3aXOx3Ow/eh5/PTiA3ggT3os3XEcLb9agtwZkmP22zVjDfPMqGWYs/ko+j5SDG0q5rK7K0/WM+nk6QlgHDulq55s0JWuegT0RGW9qnc1yZQNv/P6YMPv3EzZFm4VrBzkgYZ/+JNl0LCY/Vt6xizZje5/bLDGnCxRAvzTu6Ht8TcZsgDr95/Gt8+UQ+1CmTFx7QG8Pm41KuROh/HtK8Uap8+kTRi5YCfaVbkf7zcpantfXqxo0snTC7+49klXPdmgK131COiJynpV72qSqVv9k/oseBeRDb939p7M8A9/siwaFstie9Rjl+5B1wnrrfXjuxUntoDyS7vyi7uBNwN9u2AnPpi0yXpoWB4ejm35celudJuwAXULZ8LIp8vb/pxerGjSydMLPzb87qqzXvV405WuegTURzWpVtnwO68PNvzOzZRt4VbBykFe78Op2HUuBCPalkWDovYb/p+X78H/fvu34U+VNCHW9Yz93vvYUNqNWobZm49i4GMl0KJ8DgyYEoHhc7fHO3s/e/MRtBu1HIWzpsKUDtWUWesIZNLJU4fP7cak6+3Kxb8dXemqR0BPVNareleTTN3qn9RnwbuIbPi9s3d1hj/Q8H/VtizqO2j4x6/Yi3d+XWcpOX1d5qs/rsLf6w9G/sjWW+PX4rdV+/BOw4J4pWa+WOU3HzqLBoPnIU1YIqzx+as5TTp5engY3LJruurJBl3pqkdAT1TWq3pXk0zZ8DuvDzb8zs0RpYdmAAAgAElEQVSUbeFWwcpBXvfDqdh9LgRfP1UO9Ypktj2G31buw1u/rLXWz5AiMVa8V8/2tp1/WYtfVv7X4Lf9Zinmbz2GQY+XQPNyOWKNc/bSVRTv+e8v9Mb26k7bO3dhRZNOni5w2d4FXW1TOVqRro64bK9MV9tUjlakqyMuWyubZOpW/2QL9i5ZiQ2/h4lyq2CjNvwjnyqHug4a/gmr96Hjz/82/JlSJsGybnVti73/5wZ8t3g3XquVD283KIiGg+ch4tBZfPdsBdQokDHOOMXfn4qzl69Fvr/f9g5dXtGkk6fLdPHujq56skFXuuoR0BOV9are1SRTt/on9VnwLiIbfu/sXb2lp86AqdhzPgTfPF0OdQrbn+H/c81+dPhpjaWUNXVSLO5Sx7bYh+ERGDZnO56tkhs9mhRBuT4zcOzcZfz9RlUUvS91nHEafDoPmw+fxffPVkD1eC4MbH8QTSuadPLURHRbYel6W2xBN6JrUKLbWoGut8UWdCO6BiVyvIJJpmz4HacfbPidmynbwq2ClYO89oCp2Hs+JPIVmXYHEXiVpqyfLU0yLHy3tt1NMWTmVnw8fQtayQO7j5VAoe5TcOnqDcx/pxZypAuLM07gXfwfPlYcLcvntL0/t1c06eTptl18+6OrnmzQla56BPREZb2qdzXJ1K3+SX0WvIvIht87e1dn+G+34Z+8/iBe+XGVpZQrfRjmdq5lW+ybBTvRe9ImPFzyPnzashTydp1sbbuqez2kS544zjjyGlB5HegbdfKjU70Cca63bt8pDJq6GUfPXsbnT5RGgcwpbX82FSuadPJU4aEqBl1VSUaPQ1e66hHQE5X1qt7VJFM2/M7rgw2/c7NoWwwdOhSDBg3CwYMHUbRoUQwePBjVqtl7naRbBRt1hn/UM+VRq1Am26MO33AQL/3wb8OfJ0NyzIrjF3JjCzhu2R50+X299U59afgDD+NG9G6IpIkSxPkZvpi1FR9N24LmZbNjUPOSsa535tJVVB0wC2cuXbP+LhcQcqtQ1tTJbI/tTlc06eR5pxYqt6erSs3/YtGVrnoE9ERlvap3NcnUrf5JfRa8i8iG/w7sf/75Z7Rt2xbS9FepUgUjRozAyJEjsWnTJuTMGfxWFLcKVg7yWgOmYt/5EIxqVx61Ctpv+KdtPIQXx6y0lPJlSmE9SGt3Cdz/Xzlveqvhr9hvJhKEhmBb30YICQmJM8wvK/ai86/rUC1/Box5rmKs6wVuF5I3B127cROnLlxF+xp50KVRYbsf747XM+nkeccYCgPQVSFmlFB0paseAT1RWa/qXU0ydat/Up8F7yKy4b8D+4oVK6JMmTIYNmxYZJTChQujWbNm6N+/f9DIbhVs1IZ/dLvyqOmg4Z+x6TCe/36FNZaCmVNiasfqQccVWGH6psN44fsVKJkjDT5tURK1P56LlEkTYn2QH++aFXEYz45egWLZUmHS67d+W3Ljxk2U7zsDx89fwWetSiEscUJrP/Lu/iVd6sT77YHtD29jRZNOnjaG69oqdNVDTVe66hHQE5X1qt7VJFO3+if1WfAuIhv+27S/cuUKwsLC8Msvv+CRRx6JjNKhQwesWbMGc+fODRrZrYKVg7xm/6nYfyEk6CsxY37o2RFH0G70cuufnf767aJtx9B65FIUyJwCn7QohYeGLECWVEmxpGv8b/pZs/cUmn25EPelTopFsbwVaOOB03jw8wVInjgB1rxfH6EhIag+cDb2n7qIIU+URpOS9wW1V7GCSSdPFR6qYtBVlWT0OHSlqx4BPVFZr+pdTTJ1q39SnwXvIrLhv037AwcOIFu2bFi48P/Yuw6wqI4t/IO9994BRUWwgCIqKBbsMZpoolFjr2lqNLFjb1ETW+yaWBJNTGKMCiqgoKAoIqiIIhasWFBEEZDyvpl1lt1ld++9eO8u7pv5vve9yM6cO/PP2bv/nXvOf06hVatWaisLFy7EL7/8gqtXr+awnJqaCvI/1ojD1qhRA0+ePEHJkiVzORPhYeRL3ukHf0r4t37eDO525YUHve0RGPMEw39VxfA7VC2Bf8a6iR5LiHvfjaGoXrowlnzUCJ9tOQeb8kXh+3UbozbiEpLRYeVJFC5gjYuzcur+bwu+jYWHr6Jt3fLYPLgZtUX+Tf7+iUs1zO/lIHqO79KR4Hr06FF06tQJBQoUeBdTfKwGAhxXZdyB48pxVQYBZaxyf5UfV0vClPCn8uXLIzExUVH+JP8umM8iJ/y5xJ4R/uDgYLi5ZZPgBQsWYMeOHYiOjs5h2dvbG3PmzMnx9927d9O3BUq2JRH5cD/ZCmMbZKB+6SzRl4p+boWfr6gSbGsWy8IkpwzRYx8kA4sj8qNY/iwMtMvEhuh8qFEsC98K2EjJAL4LzU+vs7RFOgrp5PdujrbGxWfW+KBmBjpUU63l8jMrbIzOh/KFsjCzmfg5il4M78gR4AhwBDgCHAGOQJ5AIDk5GQMGDOCEX8JucMIvASzNrrkJ6THnCX+HH/zxINkK24c4o7VtOdGrDrnxFIO3qZJ2m9QohT9G6U+i1Wfw7rPX8FwRRE/ql/ZphK/2RKJ57TLYPby50etnZWXBYc4xvMnIwvFJ7lT/nzXyWfNFAUh8nY4/R7uicXVVAa+klHT694zMnGNEL1ZiR0s6LZG4dEW7c1yVgZfjynFVBgFlrHJ/lR9XS8KUn/BL9w9O+KVjph5BknadnZ2pSg9rDRs2RK9evfJc0q7HQl88eG2FXSNc0VpCSE9I7FP033SaLs+lVhn8OTY7fEkIOlJVl1TXJW3pR06Ysi8SnvYVsG1oC6GhaLnQDw9fpODfL1rDqXppdf+HiSloucgP+a2tcGVeFxTIZ63+rM+6Uzgf9xzL+zbGR87VBa/xrh0sKR7yXbGQczzHVU40s21xXDmuyiCgjFXur/LjakmY8hh+6f7xXhH+V69egUhhvn79Gl5eXqhbt670Fcs4gslyrl+/nob1bNy4EZs2bcLly5dRq1YtwSuZymHJl9x9oS8e5oLwh95MQL8NIXQtLeqUxd7R4mP4E5PfoPHcI3TsjO4NMP/gFXR3qoK1A1Rx98Za15+CcOXBC+iqCgXHPsGATWdQp3wxBOjUBJhz4DK2nbqFEW3qYEaPhkKXeOfPLenm+c5gyGiA4yojmBqmOK4cV2UQUMYq91f5cbUkTE3Fn+TfBfNZzLOEPy4ujmrcnz9/Hi1btsSWLVtocmRMTAxFq0iRIjh8+DA8PMTLRCoBMzndX7p0KS281ahRI6xcuVL0nEzlsJqEf/cIV7SScMJ/7lYCPl6vIvxET3/3yJaiYUxKeaMutkWq5q7yi0E/l+pY+rH+YlqahgduPoOT159gRb/G6NMs+7R+15nbmP73JbSvXxFbh2iHBu05G4fv9l1EG7vy2DlCfOiR6AXpdLSkm2duMVBiHMdVCVQBjivHVRkElLHK/VV+XC0JU1PxJ/l3wXwW8yzh79evH+7cuYPx48dT6ctr167B1taWEn9ra2uMGzcOT58+hb+/v/nQe8crm8phtQj/SFe0shWv0nM+7hn6rAumKzVWCEsfFK/TMtBglg/9aGjr2vT0fUir2vD+QFhF58vfwnEg4j59MzDC3UZtfsHBKGwKuolhretgVk/tU3wm51m+eCGcm5FT3ecdtyvHcEu6ecqNzbvY47i+C3qGx3JcOa7KIKCMVe6v8uNqSZiaij/Jvwvms5hnCX/lypXx77//okWLFkhISKDyS0QCkyniREREoEOHDlTS8n1tpnJY8iVvs9AX8a+t8NvIlnCTkLTLSDTBuG29ClTHX2xLTc+A/QwV4f+oWXXsO38X4z1tMblzfUET3v9exvbgWxjXzhZTumT3H/HLWRy78gjzPmyEQS21w6aS09LhMNsXWVmghJ8QfyWbJd08lcRJqm2Oq1TExPXnuIrDSWovjqtUxMT157iKw0lKL0vC1FT8SQq+eb1vniX8+fLlA5G+rFSpEsWwePHiiIyMhI2N6rQ3Pj4eVatWRUbG+yvBaCqH1ST8v49qiZY24lV6Lt5NRM81Jynm+sJojDl4ekYm7KYfpl28GlbCkah4TO5sj/GedoLfi5+OxWDlsWvo36IGFvVxUvdvv/w4bjx+hZ3DXdGmbs43Fe2WBeDW02TJycmCE9LTwZJunrlZv1JjOK7KIMtx5bgqg4AyVrm/yo+rJWFqKv4k/y6Yz2KeJfwkbOfhw4eoWLEiRadEiRIgp/qc8Et3FvIlb73AF49SrLBnVEu4SiD8l+4l0gq5pHVsUAmbP3cRPQEioVln6iHa382mHIjEp3fPhhjSuo6gjR2nb2PmP5fog8LGwaprkgcIEiJE5DpPfd9eS66TGRy94xx8L8djVo+GGNZG+DqCEzHSwZJunu+Cg9xjOa5yI6qyx3HluCqDgDJWub/Kj6slYcoJv3T/yNOEf9SoUeqCVGvXrsXAgQNRqpRKd50UXSCKOPyEX3jTNQk/UdkhajtiG1HKIYo5pHV2qIQNg8QTfjLGZupBZGYBjaqVxKV7L6g8Z7/mNQQv/1/kfXyxOxwtapfF3jEqZSAmyZnP2gox87vC2toqh51Fh65gQ+ANmjMwu6dwroDgRDjhfxeIcjXWkn6UcgWAQoM4rsoAy3HluCqDgPxWLclXOeGX7h95lvC3a9cOVlY5CZ3uEgMCAqSvOo+MMJXDki95qwW+eJxihT/GuKF5bfGE/+rDJHT+MZAi1s2xMtZ95iwJvXrTDyMtIxO1yhXF7afJWDOgKXo4VRW0EXD1EYZuOwuHqiVx8Ct32p+9bahYohBCp+tPyt0Rcgsz919Gp4aVsOntmwHBi+WygyXdPHMJgSLDOK6KwMpP+JWBlePKcVUIAfnNWtK91VT8Sf5dMJ/FPEv4zQeJ6a5sKoclX3K3Bb54kmKFP8e4wUUC4b/+KAkdV6gIfw+nKlgjQkNfE8H6Mw8j5U0myhQtgGfJb7BtSHN41leFaRlrZ28loO/6ENQuVxTHJ3vSrieuPcbnW0PRoEpJHP5a9RCg2/yj4zFs+zk0rFIShwz00RwTdvsZSOiRFEzYeEu6eQrthyk/57gqgzbHleOqDALKWOX+Kj+uloSpqfiT/LtgPot5kvBPnDhRNCIrVqwQ3TevdTSVw1LCP98XT1KlE/4bj1+i/fITFLpeTarip0+bSoKx0WxfvExNp5Vx0zOzROcQXL6fiO6rTqJCiUI4+/Y0/6/zdzFxb4RRedBr8UnwWhmIkoXzI9K7s9G5bjgRi0WHo9VrW9mvid4wIUNGLOnmKWlTFe7McVUGYI4rx1UZBJSxyv1VflwtCVNT8Sf5d8F8FvMk4ff0VJ3oshYWFkZj9e3t7emfiCY/UfFxdnbmOvwifId8yVvO98XTVCvsG+sG51riQ3puPXmFdj8cp1fp07QaVnzSRMQVs7s4efviRUq6+g//fdkGjaqp8jCMtdtPX6HtsuMoWjAfouZ2oV03Bd7AgkNX8GGTqvjRwIPHq1SVNCdpEbO9UKpIAb2X0cxNYB1IBWBSCVhss6Sbp9g1m6Ifx1UZlDmuHFdlEFDGKvdX+XG1JEw54ZfuH3mS8Gsug5zgHz9+HL/88gvKlClDP3r27BmGDh0Kd3d3TJo0Sfqq88gIUzmsNuFvBedaKhzFtDsJyXBfqsqT6OtcHcv6ClfJ1bTbdO4RGsrDmv+ktrCpUFzw0o+TUtF8wTHa78bCbvTkfdHhK9hw4gaGt6mDmT20i25pGmw27ygSXqXh0FfuaFi1pN5rzfjnInaejkMXh8qwr1wCP/nFoF6l4vD52kP0Kb8l3TwFN8SEHTiuyoDNceW4KoOAMla5v8qPqyVhair+JP8umM9inif81apVw5EjR+DgoK24cunSJXh5eVGt/ve1mcphNQn/X+NaoVlN8YT/7rNktFmiIvyfNq+BxR9la+KLwd1l/jE8eZmq7hoytT2qlCoiOFSzSu+lOZ1RvFB+TNobQYt3Telij3HtDGv5f7DmJCLvJmLjIGd4OVTOcS1SoKvFAj8aarR7hCscqpVC68X+9N9S3oBY0s1TcENM2IHjqgzYHFeOqzIIKGOV+6v8uFoSpqbiT/Lvgvks5nnCT/T39+/fj/bt22uh5O/vj169eiEpKcl86L3jlU3lsORL7jrfFwmpVvh7XCs0lUD4HyS+htsif7rSAa41sbC3o6RVuy48hvgX2YSfxOOTuHyhRhJpbacdopKeodM6oGLJwhiyLRTHrz4WlPYctysMhy4+pG8ByNsA3RZ47TEGbw2lOv4nv/OkalDjd5/HwcgH+LK9HSZ5qULHhJol3TyF1mrKzzmuyqDNceW4KoOAMla5v8qPqyVhair+JP8umM9inif8gwcPxokTJ7B8+XK0bNmSInX69GlMnjwZHh4eNNTnfW2mclhNwv/P+NZoUqO0aMjiX6TAdaEf7T+oZS3M+7CR6LGkIzk5v/f8tXpM+MxOKFOsoCgbjrN9kZSajoBv26FO+WLoufokLt5LxNYhLmhfX1WBWV+beyAKW0/dxOi2NpjatUGOLj8eu4Yfj8Vo5QL8GXYX3/4RAcdqpXDgyzai5mdJN09RCzZRJ46rMkBzXDmuyiCgjFXur/LjakmYmoo/yb8L5rOY5wk/KbD17bffYuvWrVTvmLT8+fNj+PDhWLZsGYoVK2Y+9N7xyqZyWIJbi3m+eJZmhf3jW6OxBMKvGUs/pFVteH8grZiV+1J/3EnIJvyR3l4oWVh/Iq0unOztAEv0bbXID/cTUwTXsDbgOpb5XsXHztXxg56cA3K6T0755/ZywGC32vSymusU+xbCkm6e7+jKsg7nuMoKp9oYx5XjqgwCyljl/io/rpaEqan4k/y7YD6LeZ7wM2hevXqF2NhYqpluZ2f3XhN9tiZTOSz5kjef54vnaVb494vWcKou/oT/6ctUOM9XJc/mpnqt5w/HcfPJK7WHR83tjKIF84vy+PbLj+PG41dUypNUB7af6YO09EwahlO9TFGDNvacjcN3+y7C074Ctg1todUvMzMLjeceQVJKOnQVgzqvDMTV+CRsHuyCjg0Nv0FgBi3p5ilqQ0zUieOqDNAcV46rMggoY5X7q/y4WhKmpuJP8u+C+Sy+N4TffBApd2VTOawm4T/wRRs4VheWxWSrfp6chiZzj9J/DmtdB7N6GlbH0YdUh+XHEfs4m/Bfnd8FhfLnEwWqZggPqQ7s6H2EjrsytwuKFDRs41hUPEb8eg5O1Uvh3y+0w3NYIbEiBfLhorcX8uezVs9l4p4L+Cv8HiZ0rIevO9YVnKMl3TwFF2vCDhxXZcDmuHJclUFAGavcX+XH1ZIwNRV/kn8XzGeRE37zYQ9TOSz5krvM80VimhWkEv7E12/QeI6KaAvJYeqD0mvlCVyLf6n+iElsioH9040hOH0jAav7N6V5B0QetHABa0TP62p0eHjcM/ReF0yTck99r53s7XPpIcbsDEPj6qWwX+dhYHPQDcw/eAWdHSphwyAXwSla0s1TcLEm7MBxVQZsjivHVRkElLHK/VV+XC0JU1PxJ/l3wXwWOeE3H/amJfxzfZH4xipHGIvQ8olUJamWm1vC3/WnIJAiV6RZWQE3F3UXuqT68+Hbz8Iv+hEW93FEk5ql0eXHIJQrVhBhMzsZtcFqB5CHA/I2gKjwsLYxMBYLD0WjZ+Oq9EFCs4XEPkX/TadRvQxR79F+UNB3QUu6eYreFBN05LgqAzLHleOqDALKWOX+Kj+uloQpJ/zS/YMTfumYyTbCVA5LT/hzSfiJZn3DWbkn/D1WB+HSPRXhL5DPCjELuonG76vfwvFvxH0qr9msZml6ai+GjGtW2708pzOKFcrOGZj+90XsOhOH8Z62mNy5vtZcNN9mRMzyQqmixpOLLenmKXpTTNCR46oMyBxXjqsyCChjlfur/LhaEqam4k/y74L5LHLCbz7sTXrC7zzXFy/eWOHgV23gUFV8DH/KmwzUn+lDURrRpg5mGKlwqw/KXmtPIeLOc/qRmHAcTRtT/4rEb6F3MLFTPbjUKoMBm8/QarhHJrQ1umsksbvBLB+kvMlE4GRP1CyXneA7aMsZBMU8Majl32aJP+4+e00ThV1tyhm9jiXdPM34NchxaY6rMrvBceW4KoOAMla5v8qPqyVhygm/dP/ghF86ZrKNMJXDki85I/yHvnJHw6olRa/hTUYm6k4/TPuPdK+D6d2lJe32WXcK5+NUhJ9UyyVVc8W2ef9FYctJlZ5+81plaSIukRQl0qJCjen/6xYa81gagLiEZPw+qiVa6iH07IFg2cdO6OtSw+hlkpJTMHHLUTRuaI9PWtQSVVBMaN78c1D53UOHDqFbt24oUECchCvHTRgBjqswRrnpwXHNDWrCYziuwhhJ7WFJmJqKP0nFOC/354TfjLtjKoclX/Jmc32R9MYKh792R4Mq4gl/Rqaq4i1pozxsMK1bzkJWxiDstz4EobcSaJdSRQogYraXaMRXHL2GVX4xtOBX8zplQUJ83GzK4bdRqgJsxlqvNScRcTdRS2IzPSOTSnuSNYVMbY8qpYrkMDHt74vYfSYOX7W3w0QjFXeJjTE7zuHolUfURs2yRXFkggcKFxCnQCQ0///nzy3pRykv7SPHVZnd4LhyXJVBQH6rluSrpuJP8u+C+Sxywm8+7E0a0tN0ri9evrGCzzfuqF9ZPOEn4TF1puae8DOlHQKzmIRbze3YcCIWiw5Ho0/TanC1KUu19TvUr4gtQ5oL7tqw7WfhH/0ISz5yxCfNa9L+cU+T4bEsAAXzWyN6bhdYW2cn8zKD60/EYvHhaK0qvPou9l/kfXyxO1zrIxJ69FUHYTlPwcn/n3ewpB+lvLSVHFdldoPjynFVBgH5rVqSr3LCL90/OOGXjplsI0zlsORL3nSOL16mW8H3Gw/YVy4haQ21vz9I+4/2sMFUiSf8n20+jVPXn9LxFUsUQuj0jqKvvfP0bcz45xKVySThN3MORKG7UxWsHdBM0Ma3f0Tgz7C7mNzZHuM97Wj/U9ef4LPNZ2BboRj8JrXTa+PQxQcYt+s8TRL+a5zh0KGh20IRcPUxOlXLRPfWTfDN3kiUKJQf52Z2FF1nQHAR/6cdLOlHKS9tIcdVmd3guHJclUFAfquW5Kum4k/y74L5LHLCbz7sTXrC32SOL16lW9Gwk3qVTEf4B28NReC1xxRlfbr4xuD/O/wuJuyJQBu78nCzLYdlvlfR17k6lvVtLLhriw5dwYbAG1q1A/ZfuIevf7+AljZl8fsoN702Lt1LRI/VJ2k8/lkDDydPXqbCdaEfDQ2a1iQdn/fuCvcfAvEoKRXbhzZHO/uKgvPjHQwjYEk/SnlpnzmuyuwGx5XjqgwC8lu1JF/lhF+6f3DCLx0z2UaYymHJl1wWwt/WBlO7SovhZyfhBDQS5x44xVM0fkcuP8SoHWFoWrM0WtuWx5qA6/jcrRbm9GokaGO1XwyWH72GT5vXwOKPnGj/baduqt4SOFbB2s/0vyVITH6DxnONV/Tde+4OpvwZCcdqJTGiZgJNLvX+L5rKfQ5wrYmFvR0F58c7cMJvah+wpB97U2Nn7HocV2V2g+MqP66WhKmp+JP8u2A+i5zwmw97k57wN57ji+R0Kxyd4IG6uT3hzwXhH/HLORy7Ek9RtilfDP7f6g+l0bcN5M0AeUNAkoxb2Zajij1j2tri+67a+vn6xm49eRNz/4tCD6cqWPM2BGj5katY7X+dJgHP+9DwQ4OTty9epKQbfBvCEntHtKkNx4zrlPAH33yOz7eG0rClM9M6aBX7MqOLvZeXtqQfpby0ARxXZXaD48pxVQYB+a1akq9ywi/dPzjhl46ZbCNM5bDkS84I/7GJHrCrmLuQHrFkWxOg0TvOwfeyivDXrVgcRyca19DXHBt8/Ylae9+5Vln8FhpHNfnFJMayU3hP+wrYNrQFNcuKbpHxxI6h1n1VEC7ff4Etn7ugQ4NKObqxYmKrPnFCVtx5SvgzraxpReI3GVkImuKJGmWztf9lc5j/E0OW9KOUl7aM46rMbnBcOa7KICC/VUvyVVPxJ/l3wXwWOeE3H/amPeH39kVyhhWOTWwLu4rFJa2aJe3mhvCP33UeBy8+oNerX7kEfL7xEH3tMzee4pONp2FToRicqpXCPxfuY0b3BhjhbiNogyXfNq9dBn+MaUX7j90ZhsOXHmLOBw74vFVtgzZYGJKmwg/rTAqREWKfnpmF45PcEREcoNaLZw8C6z5rhm6OVQTnyDvoR8CSfpTy0h5zXJXZDY4rx1UZBOS3akm+ygm/dP/ghF86ZrKNMJXDki85CVN5nWEFv0ltYVshd4R/bDtbfNdFOJxGE6AvfwvHgYj79E+NqpXEf1+6i8Yv7HYCPvo5BLXKFYV9pRI4EhWPBb0b4TPXWoI2Tlx7TENsSDgQqT1AWr8NIQi9mYDV/ZuiZ+OqBm1M/iMCf+go/LDO4XHP0HtdMJUYDfmuLQ4fPqwm/FP/ukjfQuQGJ8EF/R91sKQfpby0bRxXZXaD48pxVQYB+a1akq+aij/Jvwvms8gJv/mwN+kJPyP8/pPawiaXhH9cO1tMkUj4v/k9nJ7Mkya2Si7bkog7z9Fr7Smq7kNO+YNinmBFv8bo06y64K6xhwXNROGOK07g+qOX2D3CFa3syhu0scQnGj8fj8WQVrXh/YGDVj8mFdrOvgI2DWyqVRGWFOwi8f1EVWjnCFfBOfIO+hGwpB+lvLTHHFdldoPjynFVBgH5rVqSr3LCL90/OOGXjplsI0zlsORL7ujti5QMKwR82w51yheTtAYW0pMbwj9pbwT2nb9Lr+dcqwz2jVWF14hpTCKzcsnCqFamCMJuP8P6gc3QpZFwuEz0wxfo8mOQVrEv53lH8fRVmmC1YZIcPE8n4ZfNd+GhK9gYeAPDWtfB1C51tQg/my+pKHxhVifBxN3MzCycvP4ExQrlQ7OaZY7MFDUAACAASURBVAT7i8HMEvpY0o9SXtoPjqsyu8Fx5bgqg4D8Vi3JV03Fn+TfBfNZ5ITffNib9IS/kbcvUjOscPzbdqidS8I/3tMWkztLC+mZ8mcE9p5TEf4Wdcpi72j9+vf6toGR9vLFC1Fd/CsPXuCXYS3Qtl4FwV27+ywZbZaoqupem98VhFzbTT+EzCwgdFoHVCxZ2KANY3r9Y3aEwefyQ8zu2RADW1TXIvxp6ZloMMuH6vMTpZ5KRq5BLj7/vyhsPnmTzuODxlXx06dNOOkHYEk/SoKOasIOHFdlwOa4clyVQUB+q5bkq5zwS/cPTvilYybbCFM5LPmSk0TT1EwrnJjcDrXK5e6EPzeEn8W1E9Ba25XDrhEtReN3/VESOq4IRJmiBUBOzW89TcYfY9zQvHZZQRvPk9PQZO5R2i9mQVckpaSj2bzsfxfIZ23QBqvIq09ViCn4bB7sgrZ1y2oRfmLQfak/7iS8pg825AHHUAuKeYxBW0K1PhbKLRBctIV0sKQfpby0JRxXZXaD48pxVQYB+a1akq+aij/Jvwvms8gJv/mwN+kJv8NsX6S9I+H/wtMO33a2l4TYjH8uYufpODrGo14F/DpMJZEppt188gqePxxHicL5UbRgPsS/SMV/X7ZBo2qlBIe/ychE3emHaT8SXvPkZRpIDH/JwvkR6d3Z6PirD5PQ+UfVg0b4LC+tvkyj3/cbD9iUK5yD8A/acobmGiz92An9XGoYvM7IX8/haFQ8PnOtiXLFC2GVX4xkFSNBEN7TDpb0o5SXtoDjqsxucFw5rsogIL9VS/JVTvil+wcn/NIxk22EqRyWfMkZ4Q+c7Ima5aRpxLMY/twQfu9/L2N78C2KWfv6FbF1SHPR+N1JSIb70gAUKZAP+fNZ0VN6KUnH9WYcBgmzOfmdJ+4/T6EqPSR/geQxGGtPX6bCef4x2oW8HWBvAxJfk3oGqiq8l+d0RkHrrByEn2n9G8MqKeUNtU/m5vONO6qULAKXBUephn9uZFNFA/qedLSkH6W8BDnHVZnd4LhyXJVBQH6rluSrpuJP8u+C+Sxywm8+7E16wt+QFIXKtMpVUShG+L9sb4dJXtJO+OceiMLWU6o49U4NK2HTYBfRiN9//hqtFvujYD5rZGZlUe3701M7oHIpw/H3msZJCE/CqzRKqm8/TcboHWFoWrM0/h7X2ugcNOP9NWPxWVIukeQMm9lJb6z5xsBYLDwUTWU/SYiOvvZP+D18s+cCVR7ym9iWxu0P2RaK41cfiy4sJhrE97CjJf0o5SX4Oa7K7AbHleOqDALyW7UkX+WEX7p/cMIvHTPZRpjKYcmX3FyEf8HBKGwKUhH+ro0q4+eBzqLxe/QiBS0W+mn1j5jtReP5xTSPpQGIS0jGvrFu9P8n7ImAe93y2DFcWDLTZf4xPHmpHULkc+kBxuw8r5YX1Xfz9L38kD5YOFUvhX+/aKN3mt/+EYE/w+5CU/WIVQY2Nk7Mmi2hjyX9KOWl/eC4KrMbHFeOqzIIyG/VknzVVPxJ/l0wn0VO+M2HvWlP+Gf54k2WFQ1vqV4mdyE9X7W3w0SJJ/yLD0dj/YlYinIPpypYM6CZaMTJ6TxLtGWDiOIOUd4R07r+FKRW9rn37DXVyBf7lqHLj4GIfpikpQq0OegG5h+8gu5OVbB2QDO9J/xMWYg8lJCHE32N2SZvO8h8SGOqQvmtrXBpTmcULpBPzBItso8l/SjlpQ3iuCqzGxxXjqsyCMhv1ZJ8lRN+6f7BCb90zGQbYSqHJV/yBrN8kZ5lhVPft6eFrKQ0FtKzqI8j+reoKWUolvlGY22AivB/2KQqfvxUf5iLPqOaMfPkc0KGry/sJvr6fdcH4+ytZ1j3WTM8SEyh2vq9mhD5S+E5DNx8hmrkr/ykMXo3VRX6Yg8vQ1vXxuyeDnoJf3JaOhrO8qX9I2Z5oVRR7bcRKW8yaD4Fke4MmdoeVUqp9iIrKwvNF5C3Cmm0VgGpWfD/2izpRykv7SHHVZnd4LhyXJVBQH6rluSrpuJP8u+C+Sxywm8+7E16wl9/li8ysqwQ/H17VJVI+P2j43Hq+lNM7Vof+Y3IWeqDcsXRa1SBhrSPmlXH8n6NRSP+KjWdkmPWiFrPRQGFHU3jLC5+6UdOePwyFct8r+LT5jWw+CMnwTmM3RmGw5ceYl4vBwxyq037f78vEr+fvYNJnerhyw51DerFN5l7BM+T3+DIBA/Uq1RC61oX7jzHh2tP0YJg52Z01NLdH779LPyiH2FWj4YY1qaO4BwttYMl/SjlpT3iuCqzGxxXjqsyCMhv1ZJ8lRN+6f7BCb90zGQbYSqHJV9yRvg1T5VlW4gRQz8di8HKY9doD7Fkm5kjp+H1Z/qorZPiW2endxQ97fG7z+Ng5ANKoEl40JqA6xjSqja8P3AQtMHi7Kd0sce4dna0/6hfz+FIVDzmf9gIA1vWMkj4O604gZhHL7FrhCta25XXutbO07cx459LtHgYKSKm2ciDEXlAEvsW4uytBCw/chWv0zLomprWtIy3Apb0oyToaCbswHFVBmyOK8dVGQTkt2pJvmoq/iT/LpjPIif85sPepCf89rN8kZllJUnlRg5o1gZcpyfrpBHN+QW9HUWbTc/IhN1bLX0yqGqpwgie2kH0eM0T+eev32DLyZsY284W33URrhbM5EQ1i41phgh1c6xikPAP2HQawbFP8eMnTfBh02pa8yV5BLvPxGkl7LIOJ649xudbQ2FTvhj8RUiHdloZSB9kSKtcsjAOfe2OssUKisYnr3a0pB+lvIQxx1WZ3eC4clyVQUB+q5bkq5zwS/cPTvilYybbCFM5LPmS28/0RSZMT/h/Ph6LJT7RFLPP3WphTq9GovEjce11ph5S969VrihOTPYUPZ7E7BOSP7qtDV68TsdvoXGiZS/Jyflq/+tac+6w/DhiH7/C7pGuaGVb3iDh/+q3cPwbcR8zujfACHcbrfmywlzLPnZCX53CXPeev0brxf40VyF6Xhej4VOsgjEJcyKN1CgY1roOZvVsKBqfvNrRkn6U8hLGHFdldoPjynFVBgH5rVqSr5qKP8m/C+azyAm/+bA36Ql/vZm+yIIVNHXlTbF0pktPrpUbQmo77RBNcCXNlujWTzJeNEtzTSx/gLxZSE7LwN/h9zC9WwOM9NAm4fpw2HAiFosOR6NPs2pY0a8J7eI87yievtX1r1+5pEHCr37Q8LDB1G4NtMyTysGkgvBvI1vCzbac1mdE/7/BLB+kpmfixOR2qFWumN4tIlWEiWwoSWomYUMk9Gn4L+dQvnghnJ7aXnKehSn8QMo1LOlHScq6le7LcVUGYY4rx1UZBOS3akm+ygm/dP/ghF86ZrKNMJXDki85I/yh0zqgYklxhavkWCg5YScEmLRRHjaYpkOAha7BquWSfvUrl4DPNx5CQ9Sfs3Civs7V6Qm4z+WHmPdhIwxqWUvQxq4ztzH970vwalgJGwe7QLMYF8PQ0M2TyJASRZ8+TathxSeqhwXSiI36s3xohd2gKZ6oUTanPKrXyhO4Fv9SSw5Ud7LB159gwOYzNHyH5DSQomQtFhzDs+Q3+HVYC3jUqyC4vrzcwZJ+lPISzhxXZXaD48pxVQYB+a1akq+aij/Jvwvms8gJv/mwN8sJf+j0DqhYwnSEf/upm/A+oCL8YuPnNbfEYZYPXqVl0D85ViuFA1/qL2albxvZ24XeTavRWHcSI/9D38b42Fkls2ms7b9wD1//fgGtbMth98iWeJ6chiZzj9IhrBaAoZvnvrC7mPRHziJfrJCYtRVwdX5XFNCjeMQSg+d84IDPW6nUgXTb7P2X8EvIbfRzqY6lH6tUj2b8cxE7T8dR2VQin/o+N0v6UcpL+8BxVWY3OK4cV2UQkN+qJfkqJ/zS/YMTfumYyTbCVA5LvuR1Zx6h8yYnwkTtxlRtx+nbmPnPJXq5L9vbYZLEwl1O3r54kZJOxzetWRp/j2steupbT97E3P+iaMGvR0mpCL2ZQDX5ScKtUCNSpMO2n1NXzCVhOCQcp0Sh/Lg4pzMdbujmyZJvdd9InI97hj7rgmkdBFIPQV9bdOgKNgTeMKomxAp3rR/ojC6NKlMzPpceYszOMNhXKgHfCeLfggjhYI7PLelHyRz4Gbomx1WZ3eC4clyVQUB+q5bkq6biT/LvgvkscsJvPuxNesLPCD/Rfiex3qZqRJGGKNOQ9k3HuvimYz1JlyaVdpkSTYs6ZbF3tJvo8b+G3MKs/ZfRtVFlkITYyLuJ2DakOTzrVxS0QR4O+m0IUSvmhN1+ho9+DkaNskUQNEVF1g3dPKPuv0C3VUEoX5xo7XdSX4sk8pKE3ha1y2LvGP3rYHh52lfAtqHasp3EkKHCXeztgZUVEDnbCyUKaxf8ElxwHupgST9KeQhWg/6al+b4Ps6F+6syu8ZxlR9XS8KUE37p/sEJv3TMZBthKodNS0tDvVmqcJSwGR1RzoSEf+/ZO5iyL5Jee3Jne4z3VGnai22k+uzjpFTavbVdOewa0VLsUCp/SR42OjaohFtPX+H6o5d6k2X1GWSknWn/H4uKx4hfz6Fx9VLY/4UqrMjQzZPMl8ybkO+Y+V3VSbTrjl/HUp+rOWL7Na8fHPsEAzadQZ3yxRCgR5rz4t1E9FxzEmWKFsD5mZ20CncRhR/yYLNzuCva1NXW/9e3xqsPk/BLyC36EEFqFZQumjckPS3pR0m0s5qgI8dVGZA5rhxXZRCQ36ol+aqp+JP8u2A+i5zwmw97k53wp6amwX62ivATkmhKrfY/w+6CFLEi7fuu9TGmra0kxN0W+eFBYgod086+ArbrOfU2ZHDvuTuY8mckHRcT/5KS4X/Gt0aTGqUF5xD3NBkeywJQpEA+XJnXBZq22BwM3TyJqlDd6YdAxIU0k6Sn/30Ru87EGQ1tYtctXMAaV+Z20SL0ZNJ7zsbhu30X9T78fPlbOA5E3FdXAja2yGev0tB++XGa6Euaa52y2DHcFQXzWwtio3QHS/pRUhorKfY5rlLQEt+X4yoeKyk9Oa5S0BLX15Iw5YRf3J5r9uKEXzpmso0wlcOmpKah/lvCHz6zE8qYsDjT3+F3MWGPivDr06UXArPNEn/cffaadiMn9Zs/dxEaov6cXbuNXXlcefCCSmr6fuMB+8olBG2QMCISTkRa7MJu2HLyBhYe0lbeMXbzZKFIPt+4g0h4kjbil7M4duURFvRuhM9c9SsFkaq5RJqTtEhvL5TUCc1hCbsj3etgendtzX2miNTZoRI2DDKOE8mrIPkVmm1xH0d82qKmIDZKd7CkHyWlsZJin+MqBS3xfTmu4rGS0pPjKgUtcX0tCVNT8SdxyL4fvTjhN+M+mcphX6ekooH3MbpSUxN+FrdOrj27Z0MMbV1HEuLtlgXg1tNkOobE4v880Fn0eHbtljZlafw+0eIPnOyJmuVyymHqGk1Nz4D9DBXxjpjtBaLLv+54rFYyrbGbZ9tlAbj9NBl/jnGDS+2y1A7JASC5AD9/1gxdjSQOO872RVJqOo5NbAu7isW1psaq/a78pDF6N9VWG2LJwvUqFceRCW0N4kQeKprMPUL1/nePcEXkvUQqI+pcqwz2jW0lGl+lOlrSj5JSGOXGLsc1N6gJj+G4CmOUmx4c19ygZnyMJWFqKv4k/y6YzyIn/ObD3mQhPckpqWj4lvBfmNXJpLHaByMfYPzu8xTleb0cMMhNv9SkoW1g1W3J5x80ropV/ZuK3rHDFx9g7K7zcKlVBmFxz5BFQmwkyJKyGgBEUWdz0A1sO3UL49rZYkqX+nQOxm6ePVYH4dK9F1pJwiSE5sZj/UW3NBdlrB/R2yeKQ/vHt0ZjndCkOwnJcF8aQMNySDhQPqL/qaf5XYmnhbqIWtDJ7zxpjkTLRX40BMlvUlvYVtB+yBANuEwdLelHSSZIZDHDcZUFxhxGOK4cV2UQkN+qJfkqJ/zS/YMTfumYyTbCVA776nUqHOaoTvgjZnmhVFHTKbgwuUhy7YW9HTHAVVrICJOgJOM1q96K2YSjUfEY+es5WrAr+mESHXJpTmcUL5RfzHB1ZV0SBrQ9+BZ+C43Tio83dvP8dGMITt9IoA8o5EGFNN1KvYYmwcb+9GkT9GpSTd1N862DPrUlkjvQYKYP0jIMF/YixkgiM0loJgXISCEy0j7fGkrrFEztWh+jJeZZiAJTQidL+lGSsGzFu3JclYGY48pxVQYB+a1akq+aij/Jvwvms8gJv/mwN9kJvxbhn+2FUkVMR/gZ6SYwL/3ICf2a15CEePdVQbh8/wUd84lLDSz52En0+ICrjzB021l6kk0Sdkm7viBbNUfIEAvL2TfWjRa1+jv8HqZ3a4CRHjZ0qLGbJ3nQIGtn8fpZWVmwm34YhJSfmdYBlYxUOybSnSQcSTfngSX0Fspvjeh5ORN6yZw6rTiBmEfGK/W2WuSH+4kp2Da0OTztVRKlrEhZp4aVsGmw+DwJIQxz87kl/SjlZv1KjeG4KoMsx5XjqgwC8lu1JF/lhF+6f3DCLx0z2UaYymFfvk5Fo7cn/PoSQWVbkB5DAdGPMHT7WfrJ8r6N8ZGIKreaZnqtOYmIu4n0TwNb1sT8D8VXkT0Z8wQDt5xBycL5afGugvmscW1BV9HLZQ8b24c2x++hd+Bz+SE9EScn40KEf+KeC/gr/J76xDzx9Rs0nqMqfnZ1fhcUyp/P4Dzm/RcFkoA7ysMG07o1UPdjkp025YvBX49kJ+nIKvV692yIIXryJTQlQy95d0axt287WJ0BouBEpFutiKaoQCMPUX+eu4siBa0xoo0NrA2EEAnZ0f3ckn6UpK5dyf4cV2XQ5bhyXJVBQH6rluSrpuJP8u+C+Sxywm8+7E12wv8yOQWN5vrRlV70Nm1RJpZISq6tG6IiBvo+607hfNxz2nVIq9rw/sBBzDDaJyT2KfpvOk318En8PiH+kd6qKrli2icbQnDmZgLWDGgKIi96/OpjLPvYCX1dVG8pjN08mZrOF552+LazPW4/fYW2y46jaMF8iJrbxejlSYLwosPR6N20GlZ+0kTdl0mcEtWhnSNc9dogybfrT8Tic7damNNLFa6j2YJiHmPQltAcOv8kXMjR+wjS0jNFxfGTB4dOK0/g+VtZz8FutTBXz/XE4Kzbx5J+lHKzfqXGcFyVQZbjynFVBgH5rVqSr3LCL90/OOGXjplsI0zlsEnJKXB8S/ilxLDLsVB2yk5srR3QDN2dqkgy2299CEJvJdAxuifeQobO3UrAx+tD1N0qlSyEM9M6Cg1Tfz58+1n4RT8Ckask4TyM/PdwUsXkG7t5LvONxtqAbFWfC3ee48O1p2h4EUkCNtaYnKhuobFVfjFYcfSa0dCm30Pj8P1fFw3WLNgUeAMLDl3Rq3jEFICWfuyEfm8fagzNc8Y/F2mYk2b7a1wrNKtZRjS+hjpa0o/SO4MhowGOq4xgapjiuHJclUFAfquW5Kum4k/y74L5LHLCbz7sTXbC/+JVCpzmqU74L8/JDuMwxdLZKTu51vqBzujSqLKky/bfeBohN57SMZoKOWKMMJLN+tYuVxTHJ3uKGaq63q4wHLr4EHN7OWDf+XuIuPMcWz53QYcGlQQJPzllJ6ftLNGY5RM4VC2Jg1+5G50De0iqW7E4jk7Mltf87s9I7Dl3BxM61sPXHevqtXH86iMM2XYWDaqUxOGvc15n4t4L+Ov8PUzsVA9fddC2MfdAFLaeuokRbepgRg9tjX/Niz15mYqWC/2QnpmF30e1pEXJiM2Pnavjh76NRePLCf87QyXJgCX92EtauMKdOa7KAMxxlR9XS8KUE37p/sEJv3TMZBthKodNfPUajef503lHze2MogXFqdTIsdDQmwnot0F1yr55sAs6NlSRZbFt0JYzCIp5QrsTgkqIqth26V4ieqw+qe5O1Hp8vvEQOxwseXZmj4bYe/YOrsYnYdcIV7S2Ky9I+HeduY3pf1+CV8NK2DjYBZpFwAyF47CJXYtPgtfKQJpcTWoAsMaw0Awr0l1M1P0X6LYqCOVILP7MTjnW2u2nIEQ9eIGNg5zh5aD98LXz9G3M+OcS2teviK1DmhvE6a/zdzFxbwTYw0vY7QR89HMISHXg0OkdcxQLEw34246W9KMkde1K9ue4KoMux5XjqgwC8lu1JF81FX+SfxfMZ5ETfvNhb7IT/ucvX6PJfPMQfpYMSmDWVIURC/uQbaE0dp60b73q4Yv2+k+29dmLfvgCXX4MUn/UrGZp/DWutdhLY9LeCOw7fxffd61PJTlJIS1SmIoUqCLN2M1z/4V7+Pr3C3CzKYffRrXE1pM3Mfe/KBrSREKbjLVHSSloscCP5h7ELuimToZl+vykWFartw8dunaevkyF83yVBGvMgq4okM9a3UVTtlNfATL2NqZWuaI4YeRNCHsQGu9pi8md64MoELVffgI3n7zS+yAhGnBO+KVCJam/Jf3YS1q4wp05rsoAzHGVH1dLwpQTfun+wQm/dMxkG2Eqh3328jWaviX8pCBTkYKGFWJkW9xbQ5phNTuGt4B73QqSLjHil3M4diWejiHEe4wEjfjrj16i44oT6uvpxsQLTeT7fZH4/ewd+qDxa8htWvDq4Fdt4FC1lCDhZ+pEjtVK4cCXbbDiyFWs8r8uSmko5U0G6s9UVfnVTLJuOvcIniW/wZEJHqhXqYTe6WdmZoEUDCPhNsHft0fV0kXU/R4kvobbIn/kt7bC1fldcxTmevQiBS0W+oGI7VyZp19JiDw0uMw/Suexd7QbWtRRVRFm2v5C4UCakyYPCmdvPUPV0oVRvUx29WNL+lES8jFTfs5xVQZtjivHVRkE5LdqSb5qKv4k/y6YzyIn/ObD3mQn/AlJr9FsgeqEn+i3Fy5gOsKvGVaze6QrWtmqwmHEtjE7wqgcJmm6uvRCNpgyDusnFKqia2/mP5ew4/RtGkq07dRNJKWkw39SW9i8rURr7OZ59lYC+q4PAcsbYLa+bG+HSV72RqdOiDAh7W8yskk7IfJ20w/RarhC1YKZzv4/41ujiUY1XhZ6YyhxmFzXyfsIklLTDT5UXHnwAl1/CqLFy8JndVK/Qfgn/B6+2XMBjauXwv4v2ghtDRKT32DI9lCExz1HiUL5selzF7S0KSf4ICVomHcwiIAl/djnpW3muCqzGxxX+XG1JEw54ZfuH5zwS8dMthGmclhzEn4WU05A0zwRFgvi+N3ncTDyAe1OkmcHu9UWO5QW22q9WPWgQ1oXh8pYP8hZ9Pg5By5j26lbNFl4c9BNWsFW89Tc2M2ThROxWPovfwvHgYj7IPkAw9vUEZxDs3lHkfAqDaTKr33lEpQgN54rTsefqAGRNysbBjmjs0acPrk+mUfz2mXwx5hWeufA6h6sH9gMXRrlVFRixF7Xxv3nr9FqsT99axA520ut729ooUt9orHueKz64zJFCyD4+w707ZMl/SgJbrQJO3BclQGb48pxVQYB+a1akq+aij/Jvwvms8gJv/mwN+EJfzKaLQigKxUq+iQ3HFcfJqHzj4HUrGb8u9jrfP17OPZfuE+7L+ztiAGuNcUOBQtRYQN6NamKnz5tKnr8wkNXsDHwBoa1rkPVa0gLn9kJZYoVpP9t7OZ591ky2iwJQMH81rg2vysGbw1F4LXHoouPsSq/f4xxQ/PaZSXp+LPiW/N6OWCQxgMSq6ZrDIcJey5QCdLJne0x3tMuB1ZM519fETTycEUesoTe5JAHmTZL/JGcloHV/Ztime9VxCUkU/nTT1vU5IRftIdK62hJP/bSVq5sb46rMvhyXOXH1ZIw5YRfun9wwi8dM9lGmMphn75IhvNCFeEn5JOQUFM1zTj6f79oDafqpSVdmslIkkHG1Gn0GdVMYCWf93WujmUSZCOZln4/l+rYe+4uvYRmDoSxm6duZd1Bm0NpPYF1nzVDN0fhWgQ9V5/ExXuJ2DrEBe3rV6KSoL3WnkLVUoURPLWDUQwNhQ95/3sZ24Nv0TwIkg+hry0/chWr/a/TasKkqrBuG7b9LPyjH2lVHGZ9RvxyFseuPILug4aujd1n4mjMP5EOPfRVG/r2hNQGYFKilvSjJMnZFe7McVUGYI4rx1UZBOS3akm+air+JP8umM8iJ/zmw95kJ/xPXiTD5S3h11VuUXr5RLnF84fj9DKaCa9irzvlzwg12f7xkyb4sGk1sUOhSbrJoM9ca2JBb0fR41cevYaf/GJokarDl1R5BDcWZqvmGLt5kuRW22mH6JiwGR0xdPtZRN7NJvBCkxiw6TSCY5+qqxOzisWG9PU17a32i8Hyo9dAHlSWfpyti89O/o2FRpGcBfLA0KlhJWwa7JJjmuwUX1941qLDV7DhxA2DVX6ZMVbfgNUTeJ6cRpWFCGYnv/NEpeIFcOjQIXTr1g0FChQQgop/LhIBS/qxF7lkk3TjuCoDM8dVflwtCVNO+KX7Byf80jGTbYSpHPZxYjKaL1Kd8F9f0BX5NaQaZVuMAUN3EpLhvlR1bRaPLuWaU/+6SCUxSVszoClYlVsxNpLT0tFwlq+669DWtTG7p4OYobTP2oDrNNykjV15nLz+BIXyW1N1G9aEbp4Os3zwKi0Dx79th1E7zuFa/EsYk9TUnNjoHefgezlefZLOZD5b2ZbD7pEtja6B1AyYsi8SbetVwC/DWqj7srcGxuohHI2Kx8hfz+lNvn2R8oYm9ZIWMcsLpYpqk3FSgGvKn5EwpoZESD3JTyAPY5qVeVnewfK+jfGBUyVRhJ9IvpJkalLMTYpfiHYAC+so5K8WtlyTLYfjqgzUHFf5cbUkTE3Fn+TfBfNZ5IRfB/tbt25h3rx58Pf3x8OHD1G1alUMHDgQ06dPR8GCqtht0i5evIgvvvgCoaGhKFu2LEaPHo2ZM2fCioini2ymcthHia/QYpHqlD12Ybcccowip5urbpqJs8cmtoVdxeKSPtjHaAAAIABJREFU7LDwFDJINwlVyFBaeiZVu2FtdFsbTO3aQGiY+vMNJ2Kx6HA0Jb8RdxNRumgBXJiVXQhL6ObpuvAY4l+k4r8v22DcrvM0Tl1sHsO3f0Tgz7C7mNLFHuPa2eGX4FuY/e9ldHOsjHWfGU88PhYVjxF6SDuR03zyMs3om5bIu8/xwZpTqFSyEM5M66iFVXjcM/ReF6z3M9LxfNwz9DHyOenDZFpLFM5P8yHYwyd7O0DCrhZ+2FCQ8PtdicfwX86p5zetW32M8rAVvbf/jx2F/PX/ERM51sxxlQPFnDY4rvLjakmYmoo/yb8L5rPICb8O9j4+PtizZw/69+8POzs7XLp0CSNHjsSgQYPwww8/0N7E0erVqwdPT0/6IHDt2jUMGTIEs2fPxqRJk0TvpqkcNv75K7guNg/hj3+RAteFfhQTctJdu3wx0fiQjizunPw3i2cXa4BIWdq8DashY75qb4eJApKYmra3nLyJef9FwaZ8Mdx48gpVShVGiEb8vNDN02NpgJrkj90ZlkPH39g6mEIQi7f/6VgMVh67hv4tamJRH+NhSay6cZ3yxRDwbTt6GU1tf83EY905aGrxxyzQfjg8dPEBfXAhhcfIg4tu03wDEOntpbfi7vZTN+F9IAod6lfEFo1qvgFXH2HotrOoWbYo/Ca0MUr4iXwokQaNfpiknkKxgvkQMq3DO1f5Fetb72M/IX99H9eUF+bMcVVmFziu8uNqSZiaij/Jvwvms8gJvwjsly1bhp9//hk3btygvcl/T506FfHx8ShUqBD92+LFi7F69WrcvXtX9Cm/qRz24fNXaPmW8GvGoItY+jt3eZyUiuYLVJVfg6Z4okbZ7AJLYowvOBiFTUEqhZxfh7WARz1phbtsph6k2vWkSa3UuyPkFmbuv4zyxQvhyctUaBJoYk/o5tlh+XHEPn6F30e1BImff5GSDr9JbWH7Vsff2PpZ/gDLO2APAGPb2eK7LvoTbpk9JglavnhBnJvRif5Zs+gWyeMw9CaKhNzUfav3f2ZaB1QqWVg9zc1BNzD/4BX0cKqCNQaqBbdYcIw+2Pw9rhWa1lRVJNZsrEAXq9LLPnuZmg5Hb19kZQGnv2uLM4F+BmP4/aPjMWz7ORCSf+r79rTeQcyjl+Cn/Ma/UUL+Kub7yPvkRIDjqoxXcFzlx9WSMDUVf5J/F8xnkRN+EdjPmDED5OT/3DlVCMHgwYORmJiI/fv3q0eHh4ejWbNm9KGgTh39Ouupqakg/2ONOGyNGjXw5MkTlCxZUsRMcteFEH735afo4GtzO4l+IMnd1bRHEQlG9nbhxCR3rcqvYuwvO3ING4Nu0a47h7nA9W1lVzFjSR+HOcdAQntI+65zPYxoI17Hf8+5u5ixP4rG7qemZ6J+5RI4MN5NfWly8zx69Cg6deqkN7m055pgRMe/xLbPnTF6Vzidh1gMtgXfxsLDV9HDsTJW9nPCt39exP6IB5jSuS5GCuj4E038tsuDUCCfFS7P7kj3m8ij9lgbAlIX4PT3qlN/Q63N0hOIT0rFX2NcQSoFs7bo8FVsDb6N4a1r4fsu+ouHDdhyllbPXdHXET2dcqoR9d8cinO3n2P5x474oLH25+1XBOHOs9fYPrgJEmPOGcR1yl+X8Hf4fXzuVhMzutWnSd3T90fBrkIxHP6qtVjX+L/rJ+Sv/3eAyLRgjqtMQOqY4bjKj6slYUr4U/ny5SkXU5I/yb8L5rPICb8A9rGxsZTIL1++HCNGjKC9vby8ULt2bWzcuFE9+v79+6hWrRqCg4Ph5pZNCjXNe3t7Y86cOTmuuHv3bhQtKu3kW4rLvEgDZoblp0N+ckuXMvSd+yanA1PPqq49u1k6yqpeiIhuB+OsceSeSkb0a4d02Eh8LppyJh9SM1V5FR/VzoBHlbfH/SJmcOaRFXbHZlclrl08CxMcM0SMVHX5ITIf7ryywkj7DGy6qrKzwCUdxUUIz5x+ZIXfYvOhYelMjG6QiQ1XrBH13Br9bTPQsqLxNaSkA9+9xXxZi3QUzAdcTwRWR+VHxcJZmN7U+BqWR+ZD3CsrjLDPgGPZ7Gttv2aN8KfW6F07A+0M4PhrjDXCnlijV60MtK+qPU9yej/1bD68zrDCFKd0VNOJ7toYbY3Lz6zxcZ0MuFfWv0Ziw/t8PjxPs8LYBhmoXzoLr94A08/lQxasMNc5HaWyU22M7lVMohXOPbFCq0qZqCUttUS0D/COHAGOAEeAIyA/AsnJyRgwYAAn/BKg/b8h/IbItiZWZ8+ehYtLthQhIfFt27al/9u8ebO6KyH85BR/w4YN6r/du3cP1atXR0hICFq21K+iYq4T/gfPXsFjheqEP2ZedtKpBD/JddeklDfqol+B33rQOHgpbZX/dawOUIVS7RvtCqfq2SfOYuy4LPRH4mvVQ868Dxri0+bVxQyjff6NeIBJf15U93ezKYtfh2b7h9BpySebQnE+7jl++NiRntCTdmFGe8EqtKSfz+V4fPl7BJxrlsbvI1ug78YzuHAnEev6N0GnhhWNroHkLjTwPkpDmU5NaYuKJQrhSFQ8xv8WgaY1SmHvKFej48fuCsex6Mfw7tkAn7Wooe7bb+MZhN9JxOpPG6OLQyW9Npb4XsPmk7cwxK0mpnfTDj0i+RxtlgXSpPGIGe1RqED2wxQxttT3GjadvIUBzavBNf9tvSf8t56+QqcfT9G3F2HT2tPKvKT1WheCqAdJet8c6JsoeUPw3d+XaAgRmc+qT5zg1VD/mkQ7TB7vKOSveXz6eXZ6HFdltobjKj+uloQpP+GX7h//N4SfhM2Q/xlr5NS+cGEVISVknyTlurq6Yvv27bC2zi5WlduQHt1rmyoG7X7CS7RaegJEQOjmou7SveQdRhDC7/hWyvH01A6oLJHwM015MoXc6Pg7zzuKp6/S6Ap+6NsYHzuLJ/wHIx9g/O7z6tW3r18RWzUSTYXiIT/dGILTNxJoISqSC0CaWJWkkzFPMHDLGdSrVBxHJrRF+x+O08ThPaNawtWmnOCONJ5zhEpfHpvoAbuKJcCkOj3tK2Db0GypTn2GmDLSF552+LZzduhOq0V+uJ+Ygn/Gt0aTGvoLqG09eRNz/4vSqyYUFPMYg7aEwqZCMfhPyhlWRFSJiDpRyzpl0L/yY70x/LvO3Mb0vy/R0K49o7PfpLGqyLq1B/Stj4RWuS/1pwpKrJH8DKIiRci/pTYhf7XUdSu9Lo6rMghzXOXH1ZIwNRV/kn8XzGfx/4bwS4GYnNYTsu/s7IydO3ciXz7tk0iStDtt2jSatMukOpcsWYJVq1blyaTdewkv0XrpCRAuc8PEhJ8oqozeEYa0jExsG9Jccv7AuuPXsdTnKt2+IxM8UK9SCSlbCSaNSQat6t8UHzSuKnr8kcsPMWpHmLp/d8cqWPtZM/W/hW6eg7acQVDME0zubE/1/MmpNFG+EdOYPCZTBmIPLj7fuKN+ZeG4JkJo7yS8VsuAbgyMxcJD0ejdtBpWftLE6BRYwvAA15pY+LZQGUnmJRKn5P91k3k1jR2++ABjd51Hs5ql8dc47Xh6Ji1KTtI36inqxaoJk2TjmY7Jegn/5D8i8EfY3RyKS0zlp3a5ojg+2dPo+vaF3cWkPyKovCipDdHuh+N4nvxGcp0HMfuYl/oI+Wtemuv7NBeOqzK7xXGVH1dLwpQTfun+wQm/DmYsjKdmzZr49ddftch+5cqVaW+SJGJvb4/27dtT4h8TE0NlOWfNmpUnZTnvPk1Sh1KQE+b3qTGiSuZMJCbJSayUxirDkjHrBzrTIk1iW0D0I1ohl7U+zaphRb9ssix08xy+/Sz8oh+BSGuuPxGL4oXy49KczqIuzyoUszENZ/kgOS0DgZM9UbOccL5H91VBuHz/BbYPbY529hWxzDcaawNiMaRVbXh/YLz4GDul11TjeZiYgpaL/JDf2ooWHzN0Es60+KuVLkIVdDTb4sPRFAdDBdBepabDYbaqUNpCl3T07ZWz0i4r0LV2QDN010gKZmpQ5C1W1Jwu6lAffWCzKsbkQWy8px2WH7mK1f7X0bFBJWz+PGd1YUMbRh5myZ4UK6TKUcnrTchf8/r88+r8OK7K7AzHVX5cLQlTTvil+wcn/DqYkfCdoUOH6kWS/MCzRgpvjR8/nhbeKlOmDMaMGUMJf14svHXnaRLclwVSsnb9PSP8TAuf4J4bWc92ywJw62ky3TbyhsGzvvH4d82NZyEo7G9MIpP9W+jmOWZHGHwuPwQZt+tMHDRlMoW+qppypkRKta6I03VNm/03nkbIjafqtxrT/75I5/B1h7qY0Kme0cuz0Br3uuWxY7gq3p8V3dJH5DWNEYWgVov9qa9dm98V1hohMt/8Ho5/LtzH1K71Mbqt/iJZrDjYZKd0jOqrTfjJ94+EhxEJT923PeQzUsH3WfIbWuiskYa6kOb8SD0CEu5EVJdYIbiLdxPRc81J+kAWPqsTCoioRP0oKQVjd56nhcQGtayF6d0biBontO9Kfi7kr0pe25Jtc1yV2V2Oq/y4WhKmnPBL9w9O+KVjJtsIUzls3JMkePzwfhL+X0NuYdbb+Pfc5AAwLXyyabtGuKK1XXnR+3f6xlN8uvG0uv/wNnUws0dD9b+Fbp5f/haOAxH3aRjRvxH3IUSWNSemWcTq8pzO6pPviFleKFVUWOaH6P6TRN35HzbCwJa18MXu8/gv8gFm9WiIYQKynkej4jGSVOqtURr7x6vCcgxV79UF801GJuxnHKYJw6HTO6BiiewkbZbT8NOnTdCrSTW9+9Bz9UlcvJdIlY2mDOyqJXfK3jKQtwtX5nZBwfzZeTXE2CcbQnDmZgJW9GuMPs3052qcufEUn2w8jQolCiF0Wgf6gE6SnJ3nqx4W/hzjBpfaZY36CHm4+HBdMEgIEmvfd61P3+Tk5Sbkr3l57nl5bhxXZXaH4yo/rpaEqan4k/y7YD6LnPCbD3tasbdUqVKKy0oxwi8lhtyMsGhdeufp25jxzyX6t7AZHVGuuDRdzy4/Bqorsv4xxg3NBcic5sXDbifgo59D1H/STWIVunlO3HsBf52/B5IoG3D1MWwrFIOfnmRVfVhrVsYlDzoknIa06HldUFhH3UbfeJL8Sk7qp3Sxx7h2dmD5BMbIMLPDSLFmoTEW96556m/IR1jxrQNftIGjhqoSe9tiLPGYPGiQB46+dTKwcJg24WdvXAzhyJKNR7e1wdSuDfRO78dj1/DjsRj0bFwVq/s3VfchydkkSVvMG5CztxJosa/CBawxoEUtbD11E2WLFaRvoPJyeI+Qv+aV7/z7Ng+OqzI7xnGVH1dLwtRU/En+XTCfRU74zYe9yQj/7ccv1IWYxCaNmhEWrUvvOH0bhMiRFjHbC6WKCJ9uaxrosToIl+69oH8ip9Xk1FpsY4mzrD+L+Wb/Frp5fr8vEr+fvQOXWmVw7vYzOFQtiYNfuYu6PDl1tpl2iPY9OsEDnVYG0v8WWyl57oEoSkTJqTM5fWYn51s+d0GHBsblJ1mlXlKkK2ymqlKvvrh+Qwv5YM1JRN5NxMZBzvByUOVMkFPxBrN8kPIm02gewqz9l/BryG10qpaJdWO6aJ3wszl0caiM9YOcc1ye+YqumpJmx882n8ap60/Vbz7YZ+zBklRyJhWdjTX2cPBp8xrUDtkbknOxoHcjfOZaS9T+mqOTkL+aY06WcE2OqzK7yHGVH1dLwpQTfun+wQm/dMxkG2Eqh731+AXaLQ+iIRAkrvp9ajtCbqklLUkYB9NdF7sGluRJ+h/+2h0Nqggr3DDbUfdfoNuqIPWlZnRvgBHuNup/C9082YmzfaUSuBqfBOdaZahqjthmN+0Q0jOz6JiPfg6WtH/sJJsp7XgsDUBcQjL2jXWDcy3jISuacfgxC7rSsBem3KObx6BvLcO2n4V/9CMs7uOIT1vUpF2eJ6ehydyj9L+NvaVgqkzNK2Ri91fahJ/lIei+aWFzYG8mapQtgqAp2gnDrE/zBcdA8iN0pUXDbj+jGBPlnjPTOhrcIiLp6ejtS3MAWK7AGv8Y/HDkGjo1rIRNetSH9BkjFajH7gzD45epGNvWFn1dsusdiPUPqf2E/FWqPd5fhQDHVRlP4LjKj6slYWoq/iT/LpjPIif85sPeZCf8jPAXym9NFVbep8akHMmcCfkUk1Cpub6Pfw6mp+uk+U1qC9sK4kuqxsQnqU/WyXjdE1yhmyc7Za9aqjDVr29tVw67RugvyqZvT5gyD1HaGbLtLEoUzo+L3uJUfthpOAtdcfL2xYuUdLUuvzEf0FTLiZrbGUUL5of3v5exPfgWxrWzxZQu2gW1dG1N2HMBf4ff00rOZW8NSOjL+bdvDfTN4e/wu5iwJwJ1S2bi0GRtwq/vQULThmaMP3mw1VUSInUJSMIuaRe9vVCicPbbIs16ERdmdULpovrL9bIwL/L249yMjvRhSDPpl6xNN7dAd53pGZn4YM0pRD1QvXkiTWp+SW6+w0L+mhubfAwn/Er5APdX+ZG1JEw54ZfuH5zwS8dMthGmctibj17Ac0UQjTmOnvd+Ef7tp27C+0AUxfzmom6SVJDIGJYoSv775HeeqF5GWNKSbfCtJ6+oRjtry/s2xkcahbuEbp6LDl/BhhM3KFFPSklHh/oVsUWjcJeQI7HiWSTWnCQAk0TTs9MNnz5r2mNKO23rVaDFwuymH6JVZcl4YsdYI+E3dtNVmvssUXringv4S4fEG7Kh7+GA6eSTNyzkTYuhFhL7FP03nUaFwlkInt5ZK6Sn209BlCRvG9ocnvY51ZbIfEnCMHkroi/Bm0mGVi5ZGKendcgxBSbhaizHgL2B6NqoMn4eqAorIuFX5M0BKfD2+6iWaClQGI3VdyAP4AQPovRDKkiTkDMpKl9C/qP7uZC/SrXH+6sQ4Lgq4wkcV/lxtSRMTcWf5N8F81nkhN982JvshP/Go0S0X3ESRQpY48p7RvjZSTXZpluLpVcJZsmqZLyuaozQ1t99low2SwLU3dZ91gzdHKuo/y1082T67myAbuEuoeuz8BNS/Gra3xdRvUwRnPxOf6iKri3fyw9pwTNSEZe8IWDhNOTkW+gEmtgiEpck7IQUprKvXAKspoBmmI6h+esr3PV7aBy+/+sijMXXE3u3n75C22XHUcA6C5e9vdSF7chnrPjYoa/c0bCq/tAsRtr/GtcKzWqW0Zri3nN3MOXPSINvWtga5/ZywGC32nqXN2RbKI5ffYzZPRtiaOs66j5f/RZOlZgmdqqHrzrUNbq1n28NxYlrj0GSi0e626Dt0gC8SsvA3tFuaFHHeLiVpuH4FykonD+fKNUmTkyFvm25/1zoPpB7y//fIzmu8u+/JWHKCb90/+CEXzpmso0wlcPGxieiw8qTKFowH6LmdpFt/qYwJCfhFytpydZFCJXrQpU6Dmlbh7igff3shFehm+cqvxisOHpNPV63cJcQfoy8Et36RYejYVexONWOF9NOxjzBwC1nUL9yCRpX7r40QNIbHqaow5SNWGiU7kOPvrmwPSOFsUiBLNJW+8Vg+dFr+MSlBpZ87GRwCZrqRGeneqJCKdUbmdT0DNjP8KH/TcJmSGiQvsbmqVuYi/RddOgKNgTewOdutTCnV6Mcw5f6RGPd8VhoVhjW7ETefDjNOULf1uhq/W8KvIEFh66gm2NlrPssZ0Ixs0P0+4lPkbctJya3Q61yxfD17+HYf+E+xrazxXcC4VLMjt+VeIzZGUbtkEJm07tny8UaAlfIX8X4Fe+TEwGOqzJewXGVH1dLwtRU/En+XTCfRU74zYe9yU74r8cnouPKkyhWMB8uv2eEX7PwVm5O+JkqC9lmqUm/5ISbnHSztnukK1rZZuv4C908fz4eiyU+0erxhoikIRf0/OE4VX8hSaprAq5LUvkJvZmAfhtCYFO+GDYOdkbHFYEoXbQALszyEuXxvdacRMTdRGwe7IKODSuh04oTiHn0UlSsuT4JzwUHo7Ap6CZGe9hgajf9kplsYk3mHMHz129w8As3OFRXnXizty0F85E8lC4GQ19Y7QPdBGtiY8QvZ3HsyiPM6+WAQXpO8Fn+QEubsvh9lFsOnNgDoL46AEwyVFPKVB/Qhy4+wLhd52koDwtt+if8Hr7Zc4E+nPl84yG4PyTUzOvHQJAEYtZ+GdYCJHzLWBPyV8EL8w56EeC4KuMYHFf5cbUkTDnhl+4fnPBLx0y2EaZy2OsPE9Hxx/eT8G8OuoH5B69QzHND+FnFWTI+dmG3HImcxjZTs/gV6acbJiJ089ScOxk/rHUdzOopfBLL5uS18gSuxb/EkFa1acJss5ql8dc4VSEsoUbiwolCESn2RQh/91UnUZEUmxKZA6Cr28+09Y1VsWVzYkW6SFz6v1+0oX/+7s9I7Dl3B7rSpvrWwd4u7B7eHK3qqmL1WbKsUFgTO8XXh3XHFSdw/dFL7BzuijZ1cxZgYw9JtcoVxYnJnjmmFnz9CQZsPgN9pJ5VRrayAkihNJLorK/NOXAZ207dwmC3Wpj79i3DM/JgOf8oPa0P/r49qpYuYnR7Fx66go2BN2j4T4PKJfBLyG0QJSifb9yN5gAI+auQT/HP9SPAcVXGMziu8uNqSZiaij/Jvwvms8gJv/mwN9kJf8zD5+j04ykUK5QPl+e8XyE9LFQit4SfVV/NzXjN8BIyXlfWU+jmqVklmIwXo3Cj6Y6shgAJBSIFvFrZlsPukeJUfpikaPnihSjh77MuGMbkKnW/BkxrnsWqk2RYIkVJikvVKGs88ZkVptIkzmN2hMHn8kODp+ua12dvF34e0ARdnVQVeUlRLDInUtPgTyPSpizJW59WP5HTJOE4JCyKhEfpNs23CEQ61NraSqsL0/nv2KAiNn/ePMd4l/lH8eRlWg7JT82OrB7Cqv5NaQVm1ljtgjUDmqKHU/bfdS9CTvVbLfaj1yF1DlzrlIPromO0voGQ7Kymv95LTMPc/6LoQ+Dotrb0IYa33CEgdB/InVU+iuMqvw9YEqac8Ev3D074pWMm2whTOey1B8/h9dMpFC+UH5fmiJN1lG2R72hoY2AsFh5ShcXk5oS/3/oQhN5KyNV4Ip9I1GpYC/i2nRYxErp5/hYah6l/XVSPF5PQqQlXn3WncD7uOTo2qIRjV+Jpxd5tQ40XhWLjyUk2OdEuWTg/Ngxyoco3UnIAyLzJ/Cd0rEeTS+vPVMXPiyl+di0+CV4rtUOIBmw6jeDYp/jp0ybo1URF4g21wVtOIzDmKRb1dkB/V1XyLAvt0swL0DeeJSs3Jqo3b98ukH7JaeloOMuXDtGV5GR23mRkUpWfzCz9Cd5MfWiUhw2m6QlLYm9FDCU2v0xNB5FHJfZDprZHlVLZJ/kMb6GHQqZ2RB7kiA0iU8uSjb/1qocv2htOGGb+6tauI/ptDMWtp8l06eQtEHkIklrj4h2/2hYzXOg+YDELNfFCOK7yA25JmJqKP8m/C+azyAm/+bA32Qn/1fvP0XnVKUk67maERevS4XHP0HtdMP1bbgg/KaZEiirlZjxJ0qwzVVXtljRdqUehmyeTxmTjp3Wrj1EetqKhZW8nXOuUxZmbCdCUghQycichWZ2ou36gM9Xxl1Lpd/HhaKw/EUvDkMa0tUGLhX4g4SqxC7rlOPnWncujFym0Pzkgv/62f/dVQbh837CkpqaNL3eH4UDkQ3zfpR7GtFMRWBbGMrxNHczsYTgsimni60qYMolVkrhOQm4MyV+6LfLDg8QUvaf0jNAv+cgRnzRXFRTTbKzuwkj3OnqTaI0V92IF5oQe6pb5RmNtQCz6OlfHsr6N6eV3n4mjKk5EkYkUFDPUmL9GF6iLnwNv0v0hDx+kfdXeDhO97IXcin+uBwGh+wAHLXcIcFxzh5uxUZaEKSf80v2DE37pmMk2wlQOywg/Oe2NFFm4SbZFymCIhIjUKFMUlUsVlmyt97pTCI97Tsfl5oGh3vTDSMtQJUfqFmQSunnuv3APX/9+QT1nY3KP+hbGCGbDKiWp/vyHTarix0+bisJAk3QTvXgi0SklB2BtwHUs872Kfi7VQU60SdJvqSIF6Am/UNMMhYr09kLJwgXgvtQfdxJe06rBpOKwsTbz70jsOHMHY9vWwXddVeSeKdkIPTSxxFrNhw0ynlXhFUqqZQ+I+tSImGoSUy7SXQN7C2FIqYc9AOoLzWI5CkKVflldCc23CJpqUsaUqIi//nfwEJZEFcPDF6lqBSUSKkUKiZH8Dt1iZYb2ibzF2XbqJq1rQfIRNIuYCfmHpX0udB+wtPWaaj0cV/mRtiRMTcWf5N8F81nkhN982JvshD/6/nN0WXUKpYrkR8Ts9yuk5123p9faU4i4k3vCz6rdknmQuO7CBfKppyR08zx88QHG7jqv7r/0Iyf0a15D9JJYqEbNskURl5CMT5vXwOKPDEtaahp+npym1t5f+UljWr3WzaYcfhslLgeAJRyTh4xBbrXw0c8hIPMInJIzmVXfgnRj/lkRMUPx85o2fvC5gjXHb2BAi+pY2Ed1is2065d97IS+LoYx1HzY0Aw/Ihr5RCufvC3ZMzqnAg+7viGVH01ZUFJhl4TU6DafSw+pVKZuOBHrx2Q/P3OtiQW9HbWGk3CfRrNVIUdhMzqinB77JOSI5CGQeP2jEzxQt1IJtY02S/xx99lr6CpJaV6E+OuK3Yfx85V89OGN1KWwtrKi9Q1IFWZDDzK663zyMhUfrD5Jq0eT1o6Emg1prmjRMNFfGjN0FLoPmGFKFnFJjqv822hJmHLCL90/OOGXjplsI0zlsFfuPUPX1cEoXaQALog4oZVtgXnAEEuSJFPJzQk/I6oknOXGQu1Kv0I3T6ZWw2AQE7+uCdnYnWE4fOkhyhQtgGfJbwzqx+uDWTNmnbxZmLX/MiVm20XmALAQExJG1NelOoZtPwfHaqVw4EuV6o5Q01T1IW8obN9W+hVT/GznaPZRAAAgAElEQVRT4HUsOHQV3RtVxtq31WzZm5oNg5zR2aGy0cs3mOmD128yEDjZEzXLqRKM2QMMSZQlCbOGGquOTLTtZ/d0UHcTIwt66V4ieqw+SR8GyEOBbmP7SUKSSGiSbmPqRIZUhCLvPscHa8iDewGEz+ykFVo1esc5+F6Ohz45UnYd4q/D1/og8KE1+reoiUV9VA8dE/ZcwN/h92AoFEl3npP/iMAfYXe1/izVt4X85336XOg+8D6tJS/NleMq/25YEqam4k/y74L5LHLCbz7sTXbCH3XvGbqtDqbEMVykDrsZYZH10ix2nBjNDeFnyitFCuTDlXnaCkdCN09STZWcTLMmhqxqLp5Vb81vbYX0zCwaWqMvWVQfYJoJx0QKk4TndHaoRBN4xbS9Z+9gyr5IWhmXqAR9sVv4dFzTrqZuv2P1UnDyPkI/1n1Lom8ue0NvY8pfl9Dathx2vVUlYpKaxk6wma1Wi/zo6fP+8a3RuEZp+mdWB0CI1DJlJV2szsc9o0pHJMH11Pf6qx0Tec2mb+s26Ftnlx8DEf0wiZ6Ge9ZXyY1qtmHbz8I/+hFIZWVSs0G3sVh997rlsWO4q9bHrMhb76bVsPKTJnq3mPhrxyW+uP3SSit5mr2Jsq1QDH6T2hl1D/Ig6TL/GJLTMrBnVEtVIrZfDJUIJZWCxTZSeXnf+bu08BgpLKfvjYZYW+buJ3QfMPf83tfrc1zl3zlLwpQT/v+xdx3QVRRr+CehI7333kLvofduByuCoICIqDRBem8igohKFZAiVeABSeidhCQQkkAIBEILvVfpvPNN8t9MNltmMdwA3jnnnSe5O7OzM3P3/vPPV+yvD1fAb3/MEqyGsxZsWNQ1ajHlvxnwc5CFSXuWgN9z9CY6f/OecHaFw6tcrF6eu49dpo9n7HFUWdixGtUoEl//3WhB9V4aTMB9c7FLrCzUb60gZUJlZ9q2SCEDaZbdlvvB/IOaRTLTuxXyUK+lwaQXaBr1XXbmhR5/rXFbKEVSmGY1t/z+rDtwlr6YH0Slc6WjNd/UFtfb8QFo/vMOOnTuJslmVLx5MsuA4z6s8qMlwDJcp0K+DLTCwAsBJO9SQ9aJYHhzr7pUKGus9OeTJ0+p5GAfIW3KDrvagRi86gD96XvSUL6Vicva0we0szn8gjiFKZb9NVrfQ9+N+fbde1RuxEZ6/DRJHHnVK7fvU6WRG0V3jBSMuK+8LiDxihMUbKzAbcAJ2J7+DSlbWmueDfwOwEVgwjA2lbM+rfzSQoKs3gOWC951geEG1cvLi1q0aEHJkiVzjVICjMCrtFadFT8lwLC/ME24Av5EnApnLdiDUVep5RTf/2SGv+nE7XT4wi0xy88S8DPZNFf6lLS7X0NbAX/giavUeqqvo87/utWksnmiM84qBcoryOpyUTGtktstMchb4L2RLUY7rSvloR9jlF2s7s9Z3yoFMtK7FfMIeVHIg878VO2EgPkHgI0g4Ifxl1Y5x6gPe45dog9m+FPejKloR9/obDo/i4oPgJ4EKCseafXvtX1g860CmVPTVsl8yyjzr63PJxvzPq9KtYvGOt8yJCiZexLh+JzU3S3e40/bdozGeIcbbsw6zg0U8qx65G/ZBRgqRDLXhG/E45rlteQUMKBRnACbT0WQta9WKLPh8mA/ha8bFKFeMao+zJMZ+XZp+sQzv+nSwqao6aTtwlAOJ443/nkoAv+pn1SkZqVzWi1Lx+fgVERcuC3gU89C5le+kcKFr1IQpfC4TrvENa4JP9Sv0pg6K35K+FlIvBZdAX/ijb3TID0HTl+l13/1pUxpktG+QdYqK4k4JAl+aw7A0PCzBPwNftxKkZfvUKGsaWizBu5g9fIEWRjBEBdt1tfqYVn3na+zyk5r24PmO8iYb5TLRauDz5IeWdSoD5wxRrDeqmIeGvK/g9SyTE76tU1Fq26Lz7st3EdrQs7R4Nc9qGTOdMIHQAUygrpMMmdVKZhNFRsY7YdgpkLDHeu6YC95hZ6nYW+Wok9rROv48zwu6uxJniYBbcSFW9R4YnxFoh/XHaYpW45SW8/8NOLt0oZj0H62P209fIm0Wvx+kVfow+l+ui693Bibi0HFCGpG2sKwpj8/q0p1isVuJnAdAunywzeIAHpd9zpUPEcsoZfbmbo1gsb6HKHGJbPRDI1xWOc/A2l92AUhearHL+B7QG4VrsLLulSnygUyiaZ/33qMxvmEK20I2RAueVI3sen4betRcfrUxCM7TW+ntpm8cfchgdOB7yVOjTBWpXOnV1qXz+Miq/fA87jnf6FN17gm/Cy/SmPqCvjtrw9XwG9/zBKshrMWbOjpq/TGr75Cem+vBpaSYA/zgjbUcMJWOnbpjujdswT8TSZuE9lIEE+9vo2Gl3CxenlycMPXqxBW5fYZwsF/Q6CJgFO1VBm1UQRnIOsiCIWm/uA3jDXs5XZ3Hb1MbWbuoeLZ01KrSrmF+ZkZPlzbJ4Yj9W1WQmyW7MiCnr92mzzHbRNNHhvdgqA4xJAT/NtKOpJPRro3KkrdGxUT7VQcsYGu3nlAPt1rU4kc6QyHEOOFcQNEBR4CfK8+y4JpSWAUWZlbDVgRSgv2nCI5A46bsUqQGdadN4h60pyPAQka5CMkYo1OOdiZeWa7ytTII3u8Z+yxOIhWBJ2lbxsUph5NSsT5XIUDcOb6PwK+A04JDPz4FIGdla0kRXFDbAywQWAnZECvAMHCBgDqRCrynt0XBdHK/Wcd/cdpjPe3dRLNOMzqPaD6fXVdF3cEXOOa8CviVRpTZ8VPCT8LideiK+BPvLF3WoY/5NRVevM3X8JRfuDAuDj0RHx8p9y6/o9b6fjlZw/4mfSrl3W1enkevXhL6NdzAZTDjpspmyxxfStJSu2Asm48+g7Tpy/rFSYE4CqF4UjQrW9VMTf9uP6ILVlQDnwRdOfKkIr6LAtRVgm6e+8+eQyNxpRDjeb6Pw8J86jqFM3yl+1rFKChb5YS2W+cEDx8/JR2f99A9MeoQPqyaIy7Mjgb4G6gsCyolbQqB84fVc1LY96NlVBllaDXy+akKR/rn5LIWPrDI5tRiqSxErBspJbc3U2Qx/U2PQy3GfqGB7WvGV8FqNVvu2jvqes06f2y9HbFuNKmW8IvUoc5AaZuzHwCUTp3Olrzdezm9879R0IuFNAc4PizpzPG8fP3ccrHFej1srnE3ODkApvySR+Up7crmLswn7pyl+qM3yJMw/5oX4X6Lg+hCzfvK9XlOf/nwWMatOoA7T56mSrkyygIzHoQK5XvCa6xeg+otuO6zhXwP+818CqtVVfAb3+1uAJ++2OWYDWctWA54M8K7O5/LODnoFkPkqMykYxPBnl1Qce4GvZWL8+TV+5Q3fFbxW0QoB0d1dwWMfHnjRE0ceMRRzet8Ofa52EYC4icOKWQM95Wz84SkOAuAPs/efNRYbA0/C1jOIvcJrvOYpOBk6WRaw8pk4YxrtCkv/8kCW3tXU/AVDAPejwKveeYsT2SRnkdchiVydr8VqRUtIfg9da9RyR7BjAReHaHKlS/eHyFHe7HPL+TNGjlgXiKSEZyn3L/Efx6DF4nJEW39K4n4D9cth+5RO3+8Kei2V6jDT31SbmsRGTkRgy9/St3HtCKLp5UoUBcnD5n78ExCB/RXHdDwSdOetAwPgkzOl3Ac8gbGtkjwaxd7fwyfIi/jz9tOELYZFk5FMvt8Djx36zcm62+K1bvAav6rs/1R8A1rgm/Ml6lMXVW/JTws5B4LboC/sQbe6dl+INPXaG3fvOjbGlTCDfN/1IBuQ/65JB4fBbpv/em7qaAE9eoUclsNFODe7Z6eZ69/g/VGLtZDLeqS608N8A3/+Bz2PEnu7KerFCUM31KOnfjnsjuIwBXKYfP3xLkSgTrCPinbY9U1mlH+5xlh6IMYBoIyj7xzEcj345rOKXXF4xrlRHr6PqDJEJa8+a9h9R2lj+VyJGWfLrXsez+ksDT4kShbrGsQqnn4q17VHXUJgHTOTaqRRz9er3G6vywRRidyTh1lmdd+00tKpXLGC++JuSskDCtWiATLekSK1PZc/F++jvojOUcGJF+eSNhRpxmYrEeHv7WvYdUJkYadd+A+pQpbbQ/ARdAhkCMxikIZEchP6ot7PL7Q+uy9L7G/IwhXN80LEo9G0fDqLRly+GL1GF2QDw+jFfoOeq6YB9pTw702nhzyk4KibpBo94pTW2q5aejF2+LEwJsqP37N7T8jh+7dJswxjiNgBGdb+QVsS5w8pMzvfHJj9wXjOWE9UcIBG9I1n7qmZdcajKWX0vbF1i9X2036KrwSp1GuQJ++wvaFfDbH7MEq+GsBbv/5BV6+3c/yp42Be35jwX8/3ayPpruJ4KClmVz0q8aKIbVDxLjwdEHM/12oz4yDIQ/l2UmVZ6LgyNAYeDkCgLtZzqGT3ptnbh8h+rFwGgQ8M/ZfYK+ql+YvmuqBgni0wkoBKVNkdTWhgHjWnPUOrp4LwmBZAvsPQJCKAYt7RKfzKrt/4awC9Tpz0ChwY8NA4K8hhO2UdqUSSl0qLXT9FtTdlJw1A2a0a4yNfbIToD5ABL09CkJQy09l13uA2AiH8/cEy8T33bWHtoRcZkmvFeOWlXKYzh9yOIjm68Nqn9af1icsphtmphoDZK0t4ZvwqZgryV9SkFDmurKHLLxlxGxmSVqV3StIaAwcpm7+4QgdjeExGb7KrrPN2njEZq0MSIeF8SIG6BthJWIAOdB4oLngTe2DBMy+27wugTpGeTn96f5isDdzmaY+Rx8n/GtSlPys/td8pEqLyUb11i9X2005bo0ZgRepTF1Vvz0Ki0eV8CfiLPprAXrCPjTpaA9/f9bGf5/O70cqOlJWlq9PKEmUm54tOGUqkKN3F/O2PLfrBRmtM/KWvj8d86KqowJn04AM44A9S//U9SjUTH6tlFRleo0ddsxGusdLhR+EGjb2TBgXOuNWUdn7iahOR2q0Pkb9+j7v0NNg0m5U0wizZ85NW37rj4FnbpG71iYZsn1HXj9mEy2vHGzIg0zCVXLl2F5WD2FHfne7HoLM6ov6saexvT7O4T+8j9tOgesMIQNVsjQJnHgY3zyUDDtU1rfRz/g57Wul8GXYVHgVWSM4TZw33dGXKZPZu0xXedsLKblGADKBKL05dsPhOIOOCd6Zf3B89R53t54Jz2AUOEEpGOtgjTwdXNSOkOz+BkXB5yivstDxQZtfY86lpC7/aev09sxyls50qUUHh2Y6/6l7tIbr6vpxYNTBAUurMvvmpWwRcRX+vK9IhdZvV9fkcd06mO8SmPqrPjJqRP0nG/mCvif8wCbNe+sBRt04gq9M9WPcqRLQX6ugN/WjLOevJ4co9XLE66kwGSj6Kn8WHUEbqQIdLms/KomwRBKtbAePV9vh/Qr463frZBbwFG+b16CukhBqFk/5uw6TkNXh4mTEcCZ4AOgumHAuDYet45O3E5CgDGBC2FHJUgrrcn4d1VIEKvA9G9RgjrXKSxI36qkYVkPP2Jkcwd8qMLw9XTt7kNLlaARa8Jo1s7j9EWdQtSvRUnHEHecG0AbDxm78OJCkFFh7oWilS+dsjlCEK+rZH1CC79pppvhN1IYQntHLtyiJhO3i81byJC4mwl87iAVJ3Wj8OHNdGFTcOi9fPs+/d21BlXUnBDw98zsFIpPOd6rlIfGS34Sy/dGCWM4IzlTHkTuI+A/kAQFIRtwMXAbAGVS8XhgBai3yucSnhY49QAvolPxx9Tnk+aWBlGATuHk7eDZm465/a1NRWpRRt2DABUxjngevA+SAJP0Char9+sr+MjP/ZFepTF1Vvz03CfFiTdwBfxOHGztrZy1YPeduEzvTt3jCvifYa6/mBcoOACdahekAS3jZg+tXp6y4ouZQ6tRt/7eF0U9lwQ7PgZMA3AN1dJhtj9tOXzJcbkd0i8gQCDOogDWApiMHUgQTgTYrCtD6mTCMVgVNoFxbTHehyJuugkFFeC0f9l8lD6tnp+GKZCGZWlNYPa9D5ynrxbui4erNxpH9j9gVSMmMIML4asxX9O2Ac5I8YFxg27ZR0BW/tG7/69bjtL4dYdJG9RqYUZGfWf5Ua9vapNHrti1wjCU5nke0+Qv9ANTPpVBMPvzhxXi3IKz62Vyp6fVX9eKd/tHj59QiUE+9OjJU/LtFx8Pj8C6bAyHAJKegJnJhX0OzLwi2ONgxFulqG31aH8FlMhLt6nBhG1Ckx9tJ9MxNcN1zO3Q8it4bLHW3ipvrBIEt2TPMZvo4q374uSpXvFsNHJNGM3ceZzKZnpCy3vob6Tk58T3AHyH1MndxXcZ6lnYiOK7rRq4/7HzuDg9g0QrlKjwvXQDzukVK1bv11fscZ3yOK/SmDorfnLKxDjpJq6A30kDrXcbZy3YvccvU6tpe0glYEnE4Xghb80GUt80KEI9Y5xFuaNWL09AFQr28xKXexbKRIs6x5I4VR4WZllf/xXkuFSr3GLVBm9W+Do7pF95s4K++0VeJRUnVb4Xb1ZqF81CGVMnFzr0qsZhGNe3JvhQ2HU3ggzmwbM3aK7vSepWvwj1blrc6rEJMpGlYjYrYcOb0v/2n7UFCWKc94dV8tLYVmWJPQmgdrS+h75CjtypUoN96M6DWKUdhkdBv/6IlPXXexDeKGmx8OyEa3XKw6Tf+Z9Xo1pFszhuwZu/Dws9phEd9AN+Js/qbU6ZT6LHZeGb1B2/hU5euSt4F1pzM+YQGEkDLw08Td8tC6FaRbLQ/I7V4g0Nvks4IUA2XTsGsumYmZv14FUH6E/fk/E277zBYxlXowXG0DBsVvYOaiRkU/m5krs9peDBjSlVyhSm65Nhdn2aFac2VfNT1dEb6f6jJ6THi9BrCLKkDX/aKk4kuNg5uUMdcCambD4qvieQrWXpWcsvlpMvsHq/Ork7r8TtXqUxdVb89EpMfMxDuAL+RJxNZy3YwOOXqfW0Pcqyhok4JC/crVld5bumxemr+kXi9E/l5Vng+7WiDivG2HnAdQfPC8MqLlYa8tq2sVnApoELZyVV+oAgqlB/L0FULZUrnYAg2AksWLMd2VQEFD4Hz5M2M2vUD4xr64k+FHzVjYa/VYqCTl2nFUFniCE2Vv0HbKJw/+iNFjLqgHzIMp1W9ef5nqBBqw46pDV9DpynLvP3UsV8GejvrjWtqlOtcZsp6to/Djw6475VNtx8Lznoln0EjBR0uFMfTPOlPcevipMROVv9xi87KfTMDepU4jH1aaMf8JsF5QNXhtJ8v1OmxG0HB6BVWXq/Slydf7PNBPrOvIs8GVPRzr4N4o2xvGmSTb/4wjYz/WjX0Suma/Td33bRvlPX440Nm6IZnV7wPZh0LDtOY62VG7ZekOJXfulJ5fPHlTuVHwTkc6g9QSGIv8s9l+ynv/edIZDbR79jrWDFHA9spKsUyESQJQVcEOpRKicEUBgCgR2nFCiQfl3VrSalS5nMcl3zBTjpgCtz1rTJqVL+aLfl51FU3q/P476vcpuv0pg6K356ldaDK+BPxNl01oINiLxE7033p9wZUtKu7xsm4hO/fLcGlOHH9Ydp0gcV4kAk8CQqL08O+PWkEq1Gg82Q+LrwEc0c7qZWdfF5ryXBtHxflOPSvzp5UvXCxgGJtk3INN57+ITyZUotZCqtIA9y/U2HLtDncwOpXJ70Qipxc/hFGteqDH1QJZ9l1zGuH/3sQ4GX3USQvyfyKm0Kv0hj3i1DH1W1ro8bQFUHUBoEyOBCABKkx8PQ6wyfrLArLmefVTdtrI7EmvQsR4mN09pv4ro1a++vJRzjczgNlx++QVyqNeTS1v9qwT5aG3qOhrzhQR0k863qYzYJadaeZR7Rl+/rk0uBC0cWHQWeEbIZlRmhl/vAmwK9kxjWz3+7fC6apIELoT5LpwKZAh8AOO/KhdWPjPw0mH9gdAoEyFHpoevEet7Uqy4Vzvqao/moa3ep1rgtQtrzwNCmhuZ4zKPQjm27WX60PeIKDWpZgj6vbSx7y1wDWUWJvyeFsqShzb3rmX43QJzG5gInAjjlyJ8ptYAY4d9mZGe5UTaGwzhj44EyoEVJ6lSnkOX3EheAJ/LpbH+hbATqABIhXevFTYRYNYQN7KFztyhf5tTxoF1yXZX3q9W9XJ/HHYFXaUydFT+9SmvIFfAn4mw6a8H6R16i96f7U54MKWmnK+BPsBlXeXlywP9GuVz0y0dxcdFWHWEoCa5LB7KkgqSk3CYw9ICIcNEjS5r1AcEFTK8ypk4mCKdTP6lEzUrnsOq2+JxVW4BPhnzizqOXaeIH5eidCsaSlNwwxrXdLz7ke9FNaLrvOX5FZG/tbDjKDl1HN2PMs+b7nbSlEqQl+QIzPXxNGJm55MqDwio/fCLCGwgVWBfryssSoloSstkEsGLN1w2KUK8YCJp8QjCk4iP65B39gB/Z6iIDok91/Ac0pGxpYx1zG07YKtxwF3asRjWKxEKF5L5M335MkKv11jqrDBnp9KOPgGHdffCYNveqS4WkgBz3YAJ7veJZaU6HqvGGwApyxL4SgOOAdCxj3nFvcB+wxs18FnjTtOSL6oTNIJdJGw7TpE1HqWXpHPTrJ5UMp4dP3OS5gZJX+RHrxZiDSJw1rTEkiDeOOCnCCQEy+pzx71ynEPWXSN56ncCGoeqojeJ7AT7P3fuPBNQNpypQs9Jzb9a2o5UKxucbetShotnTKr0X0AcQrHECmD1dCvrlo4pxxlIl4Mc6jbh4i4pkfe1fOSQrdfgVu0jlN+tleWRnxU8vy3io9NMV8KuM0nO6xlkL1hHwGxyXP6fHe+WbVXl5csCvJ+tpNUDIokEnHKVItteE86udwthkrmNlGqVtG8EBjv6BPQcZc3b7KlS/hLHLrFyfM9UFMqcWgaP/iavCxwAYcKuCcf38Vx/aft6NutYrTIEnron6dtRMqo3eSBdu3qc1X9eiP3YdF7AJVZWhwBNXqfVUX0Lft35XX5iGATrxUdW8NObdslbddwRhDEGSCcwzP61sWv/anQdUYUR0Nh94f2S6dx+7TB/P2KO0BiZuOEI/b4qIAxGRTwgmVHtEb5rIR7Ibr5Ygzps/s+DOO/QcfblgH+lxAFgxCso2+C7oFdbT11tnbORmdEqzMewCdfwzUMDP9E5RVgadoe6L9xt6ObT6fbcg0Bpp+QOOg00BitatecfhC9R2dqAlZBJKT1B8mvd5VapdNKtjCPi5f29TkZqbqPUMWXVAcFlwyoXTLpQVQVHUY3Gww3PCbHHtiLgkDOwQaPt+31CQfrGJwUZHy/nQawfBeu0fthBI8WPfLSNO7QDt+aByXhrX2vp7gTYZFsXtY4MDdaSUydzj3VLv/YoNEgj4SCAUz56Wfm1TgYpkU9ts8A1wkgUifs0iWQQP479UVH6zXpbxcFb89LKMh0o/XQG/yig9p2uctWD9j12i92f4U96MqWiHDj72OT3eK9+sysuTA34z9RGjgZI1v+EK+ldnT1tjOsbrkDC84oINAzYOqoWx6Hz9go7VxI+kSgmNukFvTNkpiOLZ06UkPAsbWVnVx7h2+d2HNp11o89qFqS9p65R8OnrxBAZq/r4nE2k4JaLMYDKkKoPAWPZERjBt2LU2jCaseM4qWRRce/hq8PEJgMSpthkcOb7nQq5aeIH5U27D3w0suyAW+zp31CM3ar9Z+jbRfuFM6zVGmDvhqalstO0ttGbi6MXb1Gjn7aLU6IRFe6ZGkQ1mbiNjly4HScAlFWG9DT4+YF4owQI2PY+9eM8J6+lpV2qC+y5Xukyb6/gemghM7iWs+NG8BM+GUmT3F0o9Wjx7Lxpe79yHvqhdbl4t2en4F6Ni9HXDeN7TXCwDMw7yPNyuXTjLlUZs0X8CSTx1MnjKhDh78D4lxm6TmTy9w5sFMcRmE9l4Eo95I1ShuuDNwzT21aiJqWiT9rYtAzZ+eAhTUwhMqwoJCtAMYcAG+s+zcxN9ZhThO80TgRCz1ynVr/7Erw6QGKGo7ZZgUwxnMev330oNiy/bIqgszfuGX4v9d6vWpgieDWAM6nwF9C38PM3CSdwSAbADBGbL+1pktX7BUpLMPPDxlWGhlnV48/xHQccSrXPqu2qXKfym6XSzotwjbPipxfhWROqD66AP6FG8hnacdaC3XPsEn0ww5/yZUpF2/vEJ8Q9Q9ddVWxi+BG4Dn7D3BRIO6hhZ29Si8k7xJ/fLJdLHMPbKRPWHxbYdS4qOuNy+wzj4L8heK5sEKxp+8W67SDswqAo7NxNUnUKxo/S19O8ySfKnbBRAmnXTn30hbOm+EGH1CVUhlRlSdmZl2FU3y8PoUUBp8koGNQ+OwKZCRuOEKv8sH68KodAm2VnGIUKLIwNtmRXYt9jV+ijGX5UKEtq+rboTdOAn52lZfgUjM+AFUdQKXsLaJ+b3ZkhORk2vJnjY+DnwanAJsavX0PKkT4WKiS3wRtUvcD3rV93iU2fEawMcqglB/mIe+hBY75bGkxLoddvENCzHCo8J37S2ZQxB8HIcbv8sHV051EScaJUOnf6eF/TvSeviuAY3wW//nF5VHz6UDl/Rlr2pb6TNMi2ZWJkTbWbLt5MWX2/WMFJPsVgfooKIZ05GrI8Liszzfq0MjUsmd309cQnXTDE29yrHmFzOmx1WDxXam5EG5xiHeJZcdqI7zLmFPwFKzM7bg/QraaTtosNLZcGJbLRHwbO0HoPw+sEn0EGdkXXmvG4XWaDAAnZT2buoQePn9JntQrY5j9AWQkJDJjrwRDRrsLSvfsP6Pcl3vRGk3pUJHv8dWr1+4IxxIkQvuN6pzJW9RPyc2fFTwnZ58RuyxXwJ+IMOGvB+h29SB/ODBAkr22azFsiPv5Lf2uVbAln+CHDZ5fcxplZDNTntQrSIAsXUaPAk//u378hZUunH2zpTUaLn3eIQJuLmeShtj7MsuqO3yp+GHJlSCW09Bd2qkY1Cs3j3VwAACAASURBVFufEGBce83wpv+dchdOvcFR10V9O6RjuKHiVAHZUEBcoDI0u0MVql/cGpIkuwwfGdVcQAiAOdbLPOuNG4yzYKDFAfqw1Qdp9q4TxLr+VgufAzM+UQGcCBnqTzzz0ci3zZVcHMF91jQiqEJhFZqqBTJSm5yXTAN+lqGVPRf4xCNb2hTkP8DYqVv2bpAz3bIvAjYMMhlYHgve2OhxJYz8BeT6ZqcIH073FZu+SR+Up7crxNfat1IRYh8DcErAQ5AL1muTH9bR8VtJDDeVfPKiF2Dy+CJ4g6qUXmGInN6GgbP0etLB3JY8B9gwZEidXHzEZmSA7eGEII3GH0HuCwf38kkb84RUEhp8gsObLvCDYEgnqxZpx9XLy8uxXjmBwWR6PklrVDI7WUHl0C7zinAKNK9jNXpvqi+BD7D8y+pKakM4Tak9brOD7Iw2ISOLpIJKth6btmaTdohTGS5WmzR5PLBx7vRnoMNbBQR2+G2oBt4I1nsv3U/L90Urt33bsCj1aFzM6nXk+Bz1ccICE0YkQ6Z8XJHqFIuFpik3lEAXOit+SqDuvhDNuAL+RJwGZy1Y36MX6SNXwJ/gM60S8IMwCjjJ759U1D3qN+sUNLfrjI+GCvRrXoK+UHS55TanbTtGY7zDHbfQuq9aDcg7v+0S2XUuPt1rU4kcasZfsuMsjs6h8qP6w4px7TvLm/4+4S4w/wiIoO+uWh/95Uw1MoHj14XT6auxMplWzy3j6KFW89ncQAKR1wx/LrcJV2E4snIgwtll1U0feBvgb4DkjU2DFiJk1n8+WYHZ2f7BTcSlTDpuUTo7NU17xjTgZ97HV/UL03dNoyEeTBa1cotGQADzLWRd5dMkwCgQ6JgFtLgPQ5e05GY5u63Fz8tjgcwpsN0T3isnsp9yqTl2swi0jE6pDp27Sc1/3kHyuMn1eT3pEc+xXj+Z7EN7LrkZuknzKZE8rty+7MhtZMzGUrH1i2el2RrSMm+UmpfOQb8bkIaZiK6ncsQbJbNMubwx2C9Bh/hEycrFGoE1Nm0I8mXxAH7HwG9DK+Wqfb9yAoI3bbxRQgAfNLhJPGUn7fcEwTLexXxCwTAuVbglm8MBWvdD67JC3hQ8CFWFJN70YdNWPEda2nbkEhXOmoY29KirZJymdV7H83VvVJS6N1IL2tn0jccFSk04UdK6Xhu9X/i9xp/DU8Onex0hypAYxVnxU2I82/O6pyvgf14jq9Cusxbs7oiL9PGsAAcJUaFrrksURkAl4FdoxvCSczf+oepjNovPf3q/HL1b0VrhRm5s9q7j4sici11ZT9Z05/p2jL9koih+EECUW92tFpXJY32MjHEdONubFke6U6OS2QjQJmB97ZwwsNEUAomxPuEE0uW67nXED61VATkRgSsKAsx2f/iLjY+qcRlDNGoWyUwLOnrSl/P3CrdfVR8CNkzj6/suC6HFMKbS8YLQPossrRkxqrlwnY0lvOajykkiTQN+LRwJ7XOgAO33eZ/HN8XSC6zloI7Vpopme402mBDPWXpTS1C3Csb5/pzp1pKzYSJXPAZSxLwI7bhBbrLk4Og51+Mp1P5hs9g06nEQsF57zvCm1afcSc+lGG2yBwBv4rT3t9qQcCZdD2u/9fBFaj87wBAag3sxj0T2EOA+dF2wl7xCz5vKc/Ka1kJ/rty+T5VipFzN+B3sVg0oStDgxo5THoa76cHV5Pfr7QdPHWR2hmwBCw/jssu3H1ie/gHyBeI5ZFmZkL45/AJ9NidQYPl39q1vmqXHhqXa6E3iPcbiAd/8FSROz5irY/ZewWYYG8rw87fESSE2pDXHbKZb9x8pbxj41BKO5bkzpiLcH5n2vYMaG7pLy33iDVOLvI8peaY8tDL4HBmpXmmfBc9fY+wmwX3ACQ2eO+LibVNfDqv37L/93Fnx07/t54tU3xXwJ+JsOGvB7oq4QG1mBVLBzKlpy3dxyXSJ+Pgv/a2fd8Av/5iq4lTlQV2w5yQNWHHA8afI0S2UMklcAYEuMoNcrEyf5HvLARSwrsj6qgbcGNdhc71p/lF3cWSODDF+1O2cMHAQM+zNUoTMHH5Yt/auRwWypLFcd7JDMuQp28zYI37czCQp5UaZ3MhqNaxhrypLqg1cWVt/6Bse1F7S1td7ED1pTT5h6NmoCOW/E24a8GtPJ3CPqduO0VjvcDLCt8v9eGvKTgqOuhGHoK1KOubTifSpkgl4CRetTKrRBI7xPkTTtkXGg7/xSRkUj8KHNzP8DrCyk3ZjCigFNoDAjvv2a0A506eK0wWs17HzvWnWYXcyMu9ixatVX9UUijrawmvEyKuCgz09Hgr7CCRzT0KHhjfThUyxgaAeJImVnYwIzejrOJ9wAo9BD1ZW54ct4gTPDHLHGw4t/IaVyKDWg0BeLvL7ddPhy9Rl/r54mxqWJbWCyzEkKnOa5BQ4sJEI7vGOKjd8vfDrsJIW5dMEbFj2DY4OsHldqzhwwy285eSd4hQC0EpAqpiIbtV3jAnDO8GjwRrMnCaFkFiF87SKwhJvmrFGhlV4SJVq1KWmk3cR/h04oDGlT21OuGalMGwwAgY2onUHL4gNBwj6276rpwRpsnzx2rzAWfGTzW690Je7Av5EnB5nLdidRy7QJ38ECtLe5t6ugD+hpvx5B/w37z2ksjFEPdXsuPxsTMjD36CkATy6ncJH4FzHSidcbhvZNzj1ykX1hADjOnqeN80+4k4gMiIQhHa41jDJ7Fk4aAYUChh4bDiQxcuTMbXSEIAA+s/Dx7T9u/pCGvX8zXvKJxTaAJWDNVWVIiZHsmY9b7xUIUWMd+cNEs/j8DdLUvpLoaYBv3azgsFidRcVlaLP5wTEM0lT9THQkyTF/Vl6kk9MjCaQoS1agjufMBiZdnF77EasJaCyEg6Co8MjmsfbMGC9/rHMi8YEJxUqOVAJkguyy8UHRp8eaBV6+DqGUumNMTagpYesozsPHusGpviuwcMA69XoO8LZXVnhh+/NsBw9OVW+5rM5AUKGU++Uig3J4IrdrnoB3enhwFx7SgU4E/qup14kv19HeB2mP31POuA4fBM+fTIjPOPaKZsj6Mf1R6hFmRz0W5tYrwTeaA1sWZI61jY2H2NejgypgkRoxZEbBA/AShBBrz5za1Qkl7n/DUtko1kxJGOGiamIAfBmuIlHNmqZ/qx4B7w+xZcOX7ilC4HTTiKfMrIQAcjDlUZuECcmdk5elV6+ihc5K35S7M5LcZkr4E/EaXLWgo0N+K3dHBNxOF66Wz/vgF8OFMzUTYwGjn9Q8DkyU6GaQMRqwJmsyteFDG1C6Syk9+Q2iw3wFhhXLqonBBjX8Qu8aXq4O5XOnU4QdvHDYvWjKt8bGHpkq4FxBeEVxEA7pGVWysGpBOAYCLZUTwhYnhJqJJAvbPTTNluk49Feh2j69kjqVLsgDWjpQawRr2p8xvKNbBDFGvgTWpehpGeCTAN+PWlNDtbYV8Bs3TC5tXeTYtStQTS5FRyKX7cco/Y1CtDQN41lJxG4Qs1Hm0lXVSky4gAsDjhFfZeHkpVTMge1Wkdnv8gr9OF0P0NIJNbritVe1Mc/Wo4TAT8Cfy7Q3secpEzmJjLwegTPeX4nCfKcckDH9eWNkBEs7/VfdtCBMzd1YWeANJUavE58F/W+Q2xKhncEvuN6/WPIkdZ0DH1kyJgZFp43HHqbXiYDa0n98vsVstKA1WlPOJgfYtZ39JH5HdpNCavuWKmgMeEYcBpk5Lm0/n03BZ68Zsnv4foyjwd8BrxnsN6t3o3tZ/vT1sOX4ggHMLcmF4zY+sVVftJ+R/nk7cfWZShZzDvg123HadLGCJIlfPW+29hwAs4ETxb5NIFPHmUjOavflIT83FnxU0L2ObHbcgX8iTgDzlqwHPCDILQpRrkjER/7lbn18w74MVDIjj568oQ614n9kVEdQJ8D56nL/L3icmhn+1r8KGjb5Sw5/90uB6DMkHUCSsNF9YQA4/rzX940Jcxd+AYgYEIWzQh/rTceUMlBVg1BMzT0Ucwwxto2OMABIQ8BNwqgACoENT6+Z5iCbAKmJ9movTdDLDiAajpxu8jEqRzdo62Wk3cIVaI5HapQveLZiH/sp7YpT/cjA00Dfg5OQYQ8GCOtyVlQPTKstu8c/MnBvR1ZUz1YDcNJrDYMDDvQvuc4qJP15/XWDPdTC3vhLDLgZfM7xucw8Hug/74UdOd+fKdgVocxy+SCwAl9eD3yK8NJsPawBvVK90VBtHL/WV2eB8vMQjHrwNCm8U4okFjwGLxOfMf0EgsyaVqP+M/4/qoFMtGSLtXjdQ/tegyOJnMD/pE/c1xYHZ9AaVWweFybN29OlUZtEe8SLSwQcBy0jaDZ6AQPAStOSlEfqjYeuWKFBxjHb8YvQX3wFMAD0hJ0WYHLTKUI9auMiuYaaEnjvBEy4wdhI1x++Hpxyimf9CLLDm8HkczQOGPLkwBOEk6IMEabe9aiUN+t4h0QfOaWMBhkvxGj3xVWLQOcCOsnVfJoszKGjKpwe1R/s+xc56z4yU6fXvRrXQF/Is6QsxYsO0EWyZqGNroC/gSbcWcE/P+ms1vCL1KHOQGiCchbTng/vuGQWftMFORrjo9pYQurWXnkBvEjxwW4bOCzrQrG9bfFXjTxQFJBqGMZOyMFE732WFEDR9DQ0EfRZl7N+sFZefwQfzEvetN0eGQzJWdOaG03mLDNcapSarCPrRMCrVEXbz5WflWTyuvgv7XP8d7U3RRw4pqDXMh+CvM/q0xXDvmZBvyAKQDXjMJOv+xpoCIhqAff6Tg3kDYeukCj3ykjHIDNCmeq/2hfmRqUiNZ1ZziBlQ+CbDAWMjQWVsMqR1/ULUT9mpc0vD0TSLU4dXaHZTiDtgF+D/wckY4iL8fHsqucMHCWPWPqZEJxRi68cS+XJz2t6lZLt/8/b4ygiRtjvR/kixhiBmfadT3q6NbnNaLHFYIDMTa9epKgaIw3uFA4wqZae0Ign3CEDYvPoWC5Ta2TNY9rhZoNqM6P24UPBORete64vD6NvABkHwltfRZGQNsHhzXVlbhkhSLAIvEOAQ6fC28GqxXMRIu/iL/ZwXX8/KgHEQC5/8yvMZNUZW5LqmTu4gQG/AEuLOErf1+0E8yndtgw7u5Th7y9vcU74OHTJGIjIJv86S0OSBLjtFfrYs0bUeD6oQjmBtkfJxZnxU9OfKTnfitXwP/ch9j4Bs5asNsPn6d2s/dS0WxpaEPPuC6Rifj4L/2tX/SAnzOLGGhV/Lg8KYwrxt+ehQPAgSq3CTgDZ4fMJh/jOmOpF/0QkpTSpkxKt+5FnxKYSTJq2+OsLlRJ1oaeEx+rBuy4lvHccOcF8Rn47YhRLZTWrBxgIGguHMNlMMJvaxtleAcftUNdBMf/qk7JyBQjYzy+dVl6r3Je8hy9SXAQVn7pSSf37zQN+AH/KDrAW3Rp/+BovfYaYzYpqyTpwWpYelFF5YihC7JMo+qGQd6syKdRnP22giTxuDfxyE7T20W7FKOYafDjc34PLDyflfYcv0ayaRk+54DWDPIiq1pp16lDVlWDP5fXDW8q9FRXWM5RT9KT2+AxHvF2aQImXC7MBTI64UAGGVl2I9gcb1iMCM2rg88KAquWQ8DjmrZYVfps7j4hYal3Qm12uoHn4PdgoSzxIa3IvlcYsUG4/xrxpDhxonf6wuaIeE+FDNGHQzG0Uo8jMXf3CRryv4O6UC6eAzYs03PaZjJ2j0bF6NtG8R2i0QYnELCuf/2oHMneBnx6aPb7wE7j2o0w3hXYMODkZnOvurYdi5VepiYXOSt++rf9fJHquwL+RJwNZy3YbeHn6dM5e6lYttdovYksXiIOxUt56xc94N8RcYnazvIXY2sXjoM67HyK/9YjI1pNWoMJWyny0h3HZcdGtxBZOquCcZ2z3ItG7Y/FQaOOnYCdcd84bt4RcVnc0o5K0ftTfcn/xFUCZheQEhniYtV/BOcI0lEQ5LNsoWr/l8MRdmkwoe/IuBYZ4G0It9Dri6xQ9GmNAuJHGaZYG7rXpLA920wDfrQHHD2gEgyRKDt0nTJpmoMrOZvMKi4qPgqsjS6TO3nDYMVhQPAGciyw6jK8gyFJVqRnDkxxioLTlNhgOIA2HrpoeELB74GNd/LQ6pD48pYclJn5MIi+D/IR467F2cvwNHA69ApLc+oFpXxyYbbhGLzqgCDF6vkEmJ0ecF9Yy19vjlnq9d2Kuemn98vH637EhVvUeOJ28Y7Bpp5PCHhcL2QoRaO9D1OzUjloattYwi03xCpSeoZtuGbOruM0dHUYNfbILhIf2sIeC3peALiW3yV6kqaYr1JDfOjhY2PiLp8Q6akgcfbdDFYzZNUBmut7kr6oU4j6tYh7QsWbQTPzMcba413WsWa+OAE/nzCY4fDNeArML1JVILN6d9r53Fnxk50+vejXugL+RJwhZy3YreHnqb0r4E/wmX7RA378GPVdHkJVCmSyhFLoDQ4HCvgMcnbQe7ZToDsNOTgUBPoI+FUKxnX+Ci8ati9uwG8nYGd8KWAQkImEk+hRxfujj6yMA4Ie5AiNDJn0ngfjjqAZBZrfGAc7JyTeoefoywX7hEIRMOPsCaAKSeKgGQHml3ULC7UkqKDs7lOXAnZssgz4WeVnfY86QgbRzoYj6NQ1eue33QKKBSIiCrK/dxVJz5D/RAAn4/WZ1GlkmiXPAZ8qrehagyrkyyg+Yk6DGewB1+07dY3e1fQdf2cN/amfVKRmpXPGm3J+D4S4FaZZu05Sx1oFaaDkis2bRz1JTbkx3hhpn5MJn2ayrExe1VuncEddvi/K1MeBT8T0oH/MbTDLIvMz6vkM8AmJESRL9r2QOQI8rrse5Kcle8+QEexl06EL9PncQDIyhhuwIpQW7DlFeh4GGH+GfBnh8Pv9HUJ/+Z82vD/j8I02pCy/qfWHwL2Bwy89NFqlyIjjxBtWvQ2JmQMzry2GPMFpvFahjHECfjZ0MyK0YyNaZuh6kTDQk1VmDkOHmgVoyBvGhHyV977da5wVP9nt14t8vSvgT8TZcdaC3XLoPHWYu5eKZ3+N1vWom4hP/Grd+kUP+P/taHMQgHaehfQrO/UCf3poRDOlLmFcl6zyogGBsQG/HUgNbvL3vijquSSYcIwfefkO2bk/6rP5FY6x5/udEmRdI8Kk3kMV6e8lSHLAvQNiY+UyK7fBBM6SOdOJDD8If0mSEB0bpeajwBlBZO1gCgTZQ5TgQQ1o68b1lgE/Z2thnoUgSjYhS2uh0sTZWg48ZT8GFZUnLX8B/eYTChXYAEugyvKTDEmy4kCwnj02ZziN4UyzVvVIO9/8Hjif3oPG+BwhreJLgx+3ijW4qLMneRbKbPgdYO7FlI8r0Otlczmue3PKTgqJukF6kpp8kQwJ0p7mcQabHWr1OsDfFz3pU978wl32/cp5dfv/7aIgWrX/LOnBplROWHiTKZNqeVznnc1CgSevx4NKcUfMNju4hg0EjcwLGVajhXJx+zwvWqgWf84GXEaQMd5wGsFm2NRNTwEJ9+Dvo57pmyzdDA5CGkkdCnVB+IWhHGA3UBnLnT55nIB/T+QV+mC6n9DT394nvmT3pVv3He8fQDJTJosm7HLhxEqDEtnojxi5UKWXfAJc5Kz4KQG6+sI04Qr4E3EqnLVgNx86JzCQJbK/Rj6ugD/BZvxVD/j5KBsDxhKTdgbvw+m+5Bd5VVTRmimZtaOVOcS1UBgJi1GNUemDV+g56rpgH8H+HcRhEMtkIqdVG4wLRvAGDK6K9J3cJtQzwD0AjAQZd6MfVL1+cNauQObUNLtDVSHpaAdSxVlyZCy71C1EVUdvIiCpwoc1dhD2kiUzJk9zRhCqQCVzpnVAklQgWazowRu0i7fuUdVRm8SGBSc0epKP8hiw8RfDL+JkfxVI34xFB/eiTbX8hAwlNiwIeKxkXWUZXFnRiSFNG3vWoSLZ4js183vgcZ4K1HNpKGkJnFBYAUbcytyJZXAHve4hzMO4sETs2m9qUalc+k7V8nNqlXDqjd9CJ67cJaOAEvdhhSM9rwImsJupRLHOu16mlwnBCzpWo5pFsuh+9ZisLRNveVzHh6elqGv/xFO44YZkFSG9oLfySCjk3DfUi+cTAi0pldvnzciar2uRnsoWK1O1q56fhr9VOs7zYV6w4cYJl5FHgkM2971ywoFXLlj/CNhxAmCkEsbrS8+YkL+POOHERvDpk8dxAn6Zb4TPZUIw+sGQI/nETu6fgx+RNQ1tdrIgiLPiJ6vfipfpc1fAn4iz5awFuznsHH325z5dybdEfPyX/tavesDPChSYKBU3Se2EMnkUf9dz0jRaABjXNWu9qIdfbIbfzoYB7TLRDsoYgNjYhSTxMT6IjlsOX7IVsOP+7KwKWM0PPocN4QZ6Y8DqF9nSphBZs9d/2WmokKJXnzHTUJWBkRMrBu0b2CDOj73R+DOEBSTbkjnSUZ3xW5RPSGT+ArLk567fo3o2NixMcGSCoryBAAHaasPA8BWGTwAywSccesGgdgw4eGL4gkxiNiJd83sgc0nPGIPDWHIoXHqLDvQ2Ddi4Dw41IQmrLcPDrFSqOLBf3NmTqsWcJCDDW2KwPjdAfnZWksHGGuPE4yybfpkZ33GWXIuzlwNesxMaluaUjb34PdAnIJnAyJsZ5/EGW7upkjeMTELXzrnZCYHsgQCFn9TJ48IM0RZvUvWy3KwChIAbJ5zagBr1WYUKniHdGxWL0z1Wb0LCAipneuufBQb0ThB2H71MH8/cI046N/eu5yCYQ6UHm375BEBPMpV/A4xM72QFIzyfCkcroX74nRU/JVR/X4R2XAF/Is6CsxbsprBz9Pmf+6hkjrTk3V1fli0Rh+GlvfWrHvCfvHKH6o7fKuZHxQ1SO5Gd/wyk9WEXxJ+NMkR6k8/j2ts/+ofe7oYB1/seu0IfzfBzNG8kKWi0+BibChw9jHWsXFq17XDwhUwt/ACsnEDl+rKsJ9Ri8Bx2xp9dPd8ol4s61y5Eb0yJ3jDs+K6OUsDPEAxAIAArAgdBFdKEABeYfxQEqAh4Wk7eSdi8+A/Q15CXn5110VnRhTc/Vlrh3AYrS3WrX4R6Ny1OHJCkSOomMpxWGwaG33DQLEMajo7SJ53zei1ZtS41+XlXHIL3ldv3HSckR0c1p6SSpKJ2zTCc6a3yuejnDyuIjy/evOc4ocH9zaQPGboiQ0/k/mPDpBdw4j4y9EqWz5U3cGYqW+sPnqfO8/aSVjpUtT7PGzgzIJeiYFwXr/KigYFJxQkRXI5lSUx5/PhUir0n+LNTV+6KDavZ/MsnBFqeTGjUDfH9MVu/LHuqlxRRyYCzi64ef8LnwDnqMn8flcubgVZJRHL52ZmUqz0ZwjXz/U7SwJUHiDcjer9ZfIIz7/OqVLto1jjLkuWNIacLWV1tgcdCiUHe4j1tZR6W0D/0zoqfErrfidmeK+BPxNF31oLlgN8jZ1ry+tYV8CfUlL/qAT+ycwX7eTmG68TYlraGjrGtqFQwSxra0ltNEpbHdcC+lIIshmJnw4DrmTzKHc6bKRXt6BNNIlUpfEyPH/EjF27bPh1jwjLMnpbujSLPQploUWd9nW5tfy7cvCecLZEtAxEQ2U+zH3xtfZZhhGtrx9qFHBsG769rKAX8TBKFRCOSBDDnsQPpQgDAzsjnbtyj96f5OjKMVmPvf/xqnOs5YNJTn9FriwOUT6vnp2Fvlab9p68TcP2qkCw2KZvZrjI18shOrIGup4/P9+f1WrtBY6o4aov4M+PojbwB9PquJ2lqps+vbUMPRx8SdZ3enLLL0lwJbWlPN8RznL9JzSbtILPnx3UcGGtP8rj/VqT3aduO0RjvcJI3OxjXaUu86MfQpJYnhJ/PCaBN4fGVlHg9Wa1fhm1piakbwi6I71/ZPOnpfwYeCLxB156OYFxUJFF53qsWzCRgV3L5betRcUL4ToXcNPGD+ApHuFaP6M5tjFwTRjN3HhcQMWwI9H6zeOxGvl2aPtFIsnZbuI/WhJyjAS1KUqc6hXS/vrxJXtixGtUwgGxZfe+f5XNnxU/P0rcXtY4r4E/EmXHWgt148Cx1nBdEpXKlpbXfuAL+hJryVz3gxzhBQx5ZHBS7AT/DYlDXzPRHOx88riNCUzuMu4Bn3/pdfFKZ0VxyoMKf283QMywGZGUEraVzp6M1X9dWXjoMiwHEwefgeSGxOe/z+C6teg3KRLxxrcpQ3+WhZKSBrlefYTHYZHxeq5Bjw7Csc1WlgJ8dlgGLQaDdfnaALUgSG65BoQj6/x1mByiPn9aleN3B88L4rFL+jMLl1KqwRCNLQPKJger8fTJzD+08eplYZpBPisxcynm9NmvWnEoM3SDgO+x8KvMxrNYvwy/k0xy/yCv04XQ/pQ0Ty+jKOHqZAI75MCt6WXKGxhkp4HB7wMgDK6/NxG85fFHMv9WGjbX4ZbdejOu4+d4087A7GWn48/0HrTxA8FHQyoryd0EvmJbHgjfoWiUnzpAbSXqiDRk2pIVdqUiasrGZ3qa0/4pQARn6pmFRggO0XjEjznacGy0py/4Ker9ZfLoC+F9/jewncyvMCOPsnTHm3TL0UVVzYz2r76+dz50VP9np04t+rSvgT8QZctaC3XDwLHWaF0Slc6WjNd+oBy2JODQvxa3/CwH/+HXh9OuWY5Y/2HoTxtlWfGb1gy3Xd5D1Dr1GUdfviY/scghkOBLqWwUc2v4zYRlkWZwyaLXZrRYoB47Avu46eoXMTI+0bcmwmN5NitGP648Qm3BZ3Refbwy7QB1xKpAnPXWoWZC6L95P6MecTyspBfysyQ4ZxBI50wnysxyIWfVBltG8cPO+cOm0Cri4TYZgMEl7RVAU9Vgc7UmgsmHi4IcVV9g0qk6xrELxyKp8OX8veR84T8PfKkXtqhcgJn9XKZCRlnbR33DI74FKozYLzwI2SeMNRuJ5DgAAIABJREFUi57pkrYvevAlhnSobHhmbI+kUV6H4mTJOXtco3BmWtjJ0/TxO8z2F3yVse+WoQ9jAjfGp+O0aJaJCovsgSCTo83w7XJn9p68Sq1+941zkodx7f+HNy097m6ooc9tQDoXfhnaTDjDpLTKSdqB0OMQ4Bo2TdOaTmnrM2fnf91qUtk8GRwfsySoWcAuE9u1sCUmoetl3/km7LeiB/tjhaDZ7atQ/RLZdDP8s3cdp2Grw3R9DpgbAYneYtnjE9bRB94wWDlZW3337H7urPjJbr9e5OtdAX8izo6zFuz6A2ep8/wgKpM7Ha22kaVMxKF5KW79Xwj4EXwuCYwSAVfeTKltzQsb3qCSSsDCjfO4Tj6ano7FGHcZKWgYdYhhMfy5nQ0H6nBmj+vbCXhRhwMIQAEgqWiWIdR7hmIDvIWBFJQ/YIikh+81enZWXEEAAD17YHj1XDaN6ssqPyVypqU+y0JIz8HVqD7rkgNPffHWfVFfdcNz9c4DgioKClSB4DKK/qtueLQBLgfBb5fPRZNicPFmi5g149n4i9eBkWQj2pLfA/Um7KAz1/8h9gFgSIeKbCHzDVImA9+guegmB8yNSmajmZ9WMf3+LQk4TX2Wx50r/g62MHHp5UaZ8CwbhLE0L6Bp498rZ3p/lpeUzbfYy8MIA84NyuRWcA3AVcC4dp3qQxvOuInvgVYBR+6MI5NfIBMt6RILi2EitF72Wq5vFLRaeQhwG3yi91ubitSiTKxXg1Y1Sm8AsVmCEg9gcJDOLJAljeMyhpiZZdhPXL4jiPF6PAVI+oLHwQpDer9ZRj4G8smFmaQuJ0fAGYIPg7OKs+InZz2PM+7jCvidMcoG93DWgl134Cx94Qr4E3ym/wsB/78ZtDUhZ6nbwiDRhJ4tvFHbPK6zTmWikDPRxl0qGVK5PZksiL9XzJeB/u4a655q9VysS87XqWRI5TaZvwAoEiQRVQIuuT7jqZuXziEyzlYBj1w3+PR1eisGtw6nXWCj362Qm8a9W0opwy+r/BTPkVZk/1qWzUm/flzRatjE52zChOsv3bonXE5V68vSmCCPLg44RaO9ovv/kwGGWe6UlvQ7ccMR+nlTBFllaLkNh1JO3ULUr3lJmrwpgn7acIQ+qpqXxrxbVvf55ffAm7/5CbM5+C/AzIgx2Cobtht3H1K54dEOzezKzAF360p5hMSrWWGnYPm7wi6vVgE32tU+O/422usQTd8eSZ1qFyQjl1/uE/sFyNKarEADOAqy3EZFViNiNR2M68eTfSjgkhuZuRSjTdaT13KFzAitcl/4JEC7MVTxIEA7jHUf2LKk4M1ox8RIg5+vYxz8X508qXrhWK+G6mM2CUihmYdEnO/M4CaUPnW05C6gmEUHeBEQmQwx0/vNklXBZGK9Q4EnqRsdNiG88ybbzjte6UVicZGz4qeE6OuL0oYr4E/EmXDWgvUJPUNdFuynsrnT0f9cGf4Em3FXwG8+lIw/xlVGTo56LfC4Lr6QjXbH6PirQkK4PTmAwN+02uhWi4Ddbvk6O/1HHXYnheEWstZWkAJtf9gsChuN3ceuOEh3Vv3G50wUhZQpyKuTNx+ltp75aXDL4koB/x87j9PwNWH0etmcQqVn/LrD9EHlvDSutX7Aq+0TQ0PgDHrp9n1R//3KeeiH1uYBK7fDpxu7v29ASwJP06SNEdSmWj4apaMSor03kzQ58OOA1SrDy+3wBoEDZM78Grm0op78HmjzRyChD2yeNWptGM3YcVwpYEaABs4MCmuu26mvxzfg/mux7XrrSG9zoz3xMFt/rO40QdKTZwM7xpCb1S812IfuPHgsyP2YP4xri/E+FHHTjYxMs7g9JldrycGtft9NwMhj84lNp1Exgn4xr4E3cEb12exOO86eozcJHosW6qNth8295H5CMhOO3TDww3chV4ZUhv0vM2Qd3br/KI7WP0OF4MEREaMwpfebxacrEAmIiDldwY2MnKe1ndh19DK1mblHuHJv6Ok8Y09nxU8q79yX5RpXwJ+IM+WsBesTcoa6LNxPZfOko/91c2H4E2rKXQG/+UgevXibIPmGYgfSwuO65nou2nDooqhvh7SK63FMjuAphm+sjAHnJ2KyIf9bBVIhjwbLesKACpJ1TCJVXXtsVgQoUuiZG2QHHytr17f1LEB/7DouHHd7NSqsFPAjqw6iMGAoyPADH61nqGT0LJztHPy6hzA8+s1mfTY6Am4YOuDIMKsG7MiuyzKiA1eGCqfkbxsWpR4GpEf5ORiewBs0Vr4xUymR3wNfLtwvSJJMYITpGp7BKkPNfeDAjTXruT5DjMzWDxOeZQlVlf5zm6ylj1Ol3z+pJP7M0rpmGHKu//VfQQTyrSwPyVKhkz+qIDa9ZqXm2M1x4FAY19qj19H5f5KQnmSk3JaRfCq3KcOM9PrAsBYt9K/C8PV07e5D0qr3aNtgci5Iq5h7FGzgELDj//f0b0jZ06U0fHzHxuitUtS2egFxnSzpCpiTkSQprtUzV9NbD3q/WXJyRDacY/6JFX/JjpKU6vtP5TpnxU8qfXlZrnEF/Ik4U85asN4hZwg/RFqN5ER89Ffi1q6A33waZYhCo5LZaeanlZXmncd16718tCLorKijgoHWNs4ZQ/xdFUPObcinE/ib1lDI6kFY1pOvs5PhRh0202FIkEqGlu91/e4DKj88GgcPKMzfQWcIAWPnWvmVAn6GYuFUBWRncAi+blCEejUpbvXY4nM+3ejVuBhdufOA5uw+QayLr9JALBa8BgFatWDPKdIzJdJrS4uDZ8Whfs1L0Bd1C1vennHwvF4Yg22mQCK/B/r+fVCMN9+PJQ9lIqxZJzhAZQgHq6yoKKBEXbtLtcZtoeTubgISBM8BNr8b37osvVc5r+nzrww6IwjeMnwNkqo4sbDKkKNhVsoB2btnzFrhDDkI0yBOmxU9gmnl4evoxsMktLpbLSqTR99lGG3KBmmslINNPwJuK9Mu1Odsdp6MqWhn32j5XhXTLn6eeb4naNCqg3G4JjIZF5lzMw+Gfn+HCr6KvM5584pTQjyTWeGTjN/bVKTmMRyCrYcvxlPYMvrNYllS2biMCfBW7255YxIxytjrwfLLZ/MCZ8VPNrv1Ql/uCvgTcXqctWC9gs9Q17/2U/m86WnlV7US8YlfrVu7An7z+ZR1/O1AcnhcA58Wonl+p8RNVEmbco9YHhJ/MyNd6j0F67fzZ3YJaWymw/VVMNRyPzgzypAgM5UPbf/ljB1ORiAzOfQND2pTNY9SwM9SjJCyLJ49HS3fF0XsXKvyDR6xJkyYjeFU4urtB8KHQDXDjfZZIhFBIoJQBND9W5SgznWsA3Z5s4Pg4+uFQUIWVXZwNXsGhnKxUVqbmX5CZUk2s9LWl98DI70O01zfk44Nzju/7aKgU9eFn0Kz0jksh08bIDMZdOonFalZaWNIChqWDaTYB4BJn1YYctTnUy2ZIN904nY6fOEWLehYjWpaaKyzoo3MN2EMOkyj4CVhVrSSqBhXjyHr6OGTJLT9u/qUL7O5aIAW1gJ1rdJD1olbmpmG4XMmvqaB0/DwZqKOKoYd164NORetRiWRhhkbr+Iyzopm8tixpKqKwpjeSQzgcCDMy3BEo9+sBhO2UuSlOyRzCJj/IZ9a6M0foEdwk1Y5ybD8Ati4wFnxk40uvfCXugL+RJwiZy1YDvgr5E1PK1wBf4LNuCvgtx7KAt+vFRep/Ghxazyu4cmL0u/bjos/A08+RZE0yu3UGreZoq79I/6pShrlumFnb1KLyTscD6hKGuUK7HbL/2YjKOsRi76CcfAMCUK2/GsT0qO2XZD1kNnEuIefv0U/tC5L75TLoRTwMwGyUJY0QorPTsCMfoDkCjw4iLLX7jyktaHnaNibpQgEYpXCeGYonoAQuO7gBVKBlKBtOdMLeMK3i/cTnFBlXLlZH9joi30jOGA3U0mR3wOTt0TSL5uPOkjW9X/cSscv3yF27rV6fs6oMweAyZyLOnuSZ6FYMqdeOzKMjSEkdX7YQqeu3qVlXapT5QKZTG+vh9lmuUlWeTFrQAuHwrUeg33o7oPHtO27epQ/c6z6jF47MhTss1oF6fY/96n0sI3i0mCJjGrUB61KENSScGKC7xAgMWYuyzLJnzdLqhh29IeVsWS/BjseEMybkd9TzCtQkaRlz5MejYrRt42iydF6hG+j3ywm2vO6Q30VSVGeC60akNU6T4jPnRU/JURfX5Q2XAF/Is6Esxbs2uAo+uqvYNtKJYk4NC/FrV0Bv/U0ccBvxymXxzUqbUkavz5C3MQuBh512DIe/23mVKn3FMcu3aaGE6L5Byh2ITlaWU92urQesegrWF2Er7eTIUedcsPWE4IYNg6b9EF5alk6m1LAL6t2AMO/I+KyJWlSfi5WPMGYX7v7gLYevkQqkBJuw0H6bV1WYMJxfzbCUhk/2ekXkJ6AE9dIhjqYtSErHO3u15A4426GIZffA7N9o1WFeL1VG72R4EWgEjCjXwwhGv1OGcKpkCqGnJ+J1Z1YN52hGuwLYPbsvObTpkhKocOaCh5M8UE+hBOjnX3rU56M5hl2cBXAOWDPA1k9hpV3zO7PfAuGBJ29eptq/LBNmHkdG9VCSHWaFa1LciyfIzkFDjSHxOBZiwyIzlL79WtIOdKnJD1IjNH9Gccuw29UXHa5PT2lGw7YVRSe9E4I9AjnRr9ZXRfsJa/Q8+IksH3NgqJberwCo+fnU7nZHapQ/eLZVL6m//oaZ8VP/7qjL1ADroA/ESfDWQt2zf4o6rYomCrly0DLbUgTJuLQvBS3dgX81tPEAT8HEdY1YlVPrmcpQ0NWHxJVPqySl8a2UlOJ4XswDh7/thuw83E+t6WqEsPXMxac/22HdIs6TNbk+qqQFr6eVX4AUYDyCfSxm3lkVQr4kZFGZhqmYzA823fqOk1rW4malrKGpOD+jP0FURs8Dv8TV0mrT262Dpj8CdIvTgegsqIKiUG7nG30+qY2fbcsmA6evUnwBKinEIhog142ETMjfcrvgeVB5+j7v0OJjarYuGhTr7pUOOtrlstfdjnuVLtQrKxi/4aUzYT0yQ3LpmcgWyKIRWHVH7MOsFsuroEHAgJ96MOjHBjWVKwHsyIbvq3qVotkDPvRGJUYs/paSNChM9eo+S+7KV3KpBQytKnl2DFfAadZ71fOS3ZcitE4nIIxBlg3HrnSkexYvahzrLa/Xkf0nnXatmMOSVwrSVk2z5IdyTlg/7JeYerbrITp87N5VssyOenXNtHyuZw0GPKGhzDgQzH6zWL+hczVsQMnY4UmOxt7ywm1uMBZ8dO/7eeLVN8V8CfibDhrwa7eH0VfLwqmyvkz0LIv1bXIE3FoXopbuwJ+62nigB8SkdBVVyk8ro9yV6Bey0JFFchKQtrPTuFjatSxG7DzDzjfDwZWQ98spXx7dojlCnZIq6jDR/RcH8EvYA6qhVV++HoE3I1LZFEK+OXgBVJ7Ry7cpvmfV6NaRbMo3V42v7p+9yGFSbr0Kg3ws0O7HU63gCRZqbTI7TIMZskX1anv8hABqcF/g0diVeRnR1a52phNwriIg0C9+vJ7YP2hy3Gw3Ayt8u3XgHKmN5ZV5HblrCxIxjipQWFdfqv+y1r4CPgrjYyGxBwdZU4axTVaONS9R4+p+pjNlBRyjaPMITGoH3jiKrWe6kv5M6embd/VjyMPq/Ld1xo47Tl2iT6Y4U8ykdbs+bsvCqKV+886+B7rD56nzvP2KrtkN/5pG0VcvO3gK6iYrnF/9EjDnHVXgfMxhFBWWOLnMVOI4vvrbU70YDpGv1l6KkN6RmpG488bVWxMsEFxRnFW/OSMZ3HWPVwBv7NGWuc+zlqw/ws6Td8sDnEF/Ak8166A33pAIXc3eNVBYRokG8qY1eRxTVm4ijCMQ7ELiUEdzjrhv+0G7FrjLhXjIfmZZNMx/F1VZYbb4Iwb/3v4W6WoXYxcn/WoxxJf+Vpk6BsUy6wU8N+5/4hKxZAdmTTMzrEq95YzvRhHGI+pYMi5bdae/6JOIWE6Bgz68i9rCLdmlSIHvf1XhNqC1MjKLKFDm4iAF+RPrQOq3A/5PeB34jq1neUvuBOrv65FRWMy7CqQFrQpG4V93aAoVRu9iaCPjoDdDIPO/WHiK3Try+bJIGBtaVMmpVCFDDnakLXwMRbREqfWkBjUlf0fEODzBiBfptS0vU99y6lbvjeKei0NdkjoskN8qVxpae03dSzrazPiRtr6Rg0xfwKnYSDps2maiukZ2tTCpwavOqCscMXO4LIWvh2Fp91HL9PHGi187QYGfTT6zeLNjSyfXHKQD/3zUI1/McbrEE3bHvlM72nLiTW4wFnx07P270Ws5wr4E3FWnLVgXQH/85lkV8D/fMc1i4cntZkVKG4CHXkoxdgprFyBOqo67ty+HPjhbyrH6nLfWMOa/9a7STHq1sDYaVT7XKzj7wiC3ylNbarlV358Gc6ESnA/rVMkk1LA/+jxEwcUBAEIcM0+3WtTiRzplO4vG0DdvPfIMkOubVR2h11/8IKAWXh/W1uYgKmUj2f4CbMyKOsMXHmAbt17RKxrb1VflnKE2RGI3/ByMNNRl98DB8/fobd/3UXgrGDMygyNztAzEdTq/kz2hmY9TjjqxUCrAKlRKTKMo2ye9NTqd1/KmykV7egTLTVpVRgKBlnQfx48po9m+JFMRDWrr9XCBwb+87mBhH78r5u1OpzWJXlZwEnqvfwA1SiUiRZaQGrQL61xGI+lqsJWl3l7BUGdN9djvcNp6rZj9FnNgjT4DQ+roRMwOPk0qcfi/bRCUWFKTwtfL0Nv1Inw8zep2aQdJHMIWCFJNv0y+s3yOXCOuszf5+D5aR2vcUJrVmZsj6RRXoforfK56OcPK1iOVUJc4Kz4KSH6+qK04Qr4E3EmnLVgV+07Td8uCaEqBTLS0i41EvGJX61buwL+5zOfPK4FKtSit37zEzexI0vJvWLTIfzbjo49rofUXKEY11Nxf0lbXOWpWdqSr7Uja4k67BDL9eFa+34Vcx11uV8IOiEtygUY9pqFMioF/LKcKtdXIX3ytUGnrtE7v+0WUIxrdx4IDoGKSgvXl9VeNh66IFReVGQZuT6TDaHsg6wvnEqZiKkyd2z8Be33N6bsFFVChjahdCn1gx75PXD6+n1qMCE6q76pZ12qOnqTIJ1Gjm6hlKHnrHS94lkFbls2EVPpO+u5Q62lfL4MQocfGyVsmFQKky/hLHv3/iP6csE+cbKCExarIgetONHYdOhinIy9VX1wNaAnzxCeWTuO0Yi14dSsVHaa2tbaw0Orhc+nJapwPq0WPk6HFtrwgIjFvEdLsHKGXsVDAWPDfA/+rqm6/KKunvEYy5SyczGuM/rN0sKxZG198Dmw8TcrWv8Kq7lOiM+dFT8lRF9flDZcAX8izoSzFuzKfaep+5IQqlogIy1xBfwJNuOugD/BhjJOQzyupT3rUcOJ0QGX3Qw56vRdFkKLA0+L+qpOq3JHGH+Nv9mVxWR5R25vYMuS1LF2IeUBG+cTLhxuuajKSvL1rX/fTYEnrznqAwPvWSCDUsCPSgX7raWnT2O7KwcNVg8RGnVDBMrZ06Wgi7fui3YCBjQi6JGrlHl+J4WJE7wXIMmJokI65bYZT4w5m7DhiPgzICZWWUquz8RXnIogQ41iZigkvweu33siSMMI8jf3qieyvrK2u9Xz88lQxXwZaODrHvRuzMaJzaCs6o/xPkTTtkWKrDQ4C13m77WlzvbhdF/yi7wqTkew0UIQbMdlmiFBgEBtDr9Iw9eEKUvqRl66Hb1ZilEJ+ml9OE3efIw+qJybxrUub/XoQtEJhG/2/NBTqTFrZPy6cPp1yzEH/E8mj6vwZ7QKS5yhVzEtQ7+0brksK/x31xpUMZ85nE0+lYNJV4ZUyajwAK943z2j3yxWGcqcJjntHdSYTl65Q3XHb6XUyd0pLMaXwGzswLXpuiCuD4HlhP3LC5wVP/3Lbr5Q1V0BfyJOh7MW7Iq9p6jH0lCqVjAjLf7COlOTiEPyUt3aFfA/n+nicfWs24iqjd0qbmJXlhJ1+Acf/w2n2a/qF7HVYZj2AL+NYpeMxlr2fEM7OvSo89P6wzR581FHf82Mn/Qeio27+LOFnapRlXzplQP+Iv29RGaci50MOxMQoerC4xc2vCmlTm6u8sL3YjlDOL4CmoNiZZwkjwGTfjvWKkgzd0b7ONhxAOUs97hWZajv8lCh4x4xqoXh2pHfA4/JjUoMila2WdqlOr031VcZA486MhwKJPWPZ+whEKc39KyrtHYZdw4pxzrFstC3i+I651o1IksxIuAf4x0u3JqtVGa4XdkpGAE/YDaqGfardx4QTld4vkatOUhzfE9R59oFqH9La8I8b7KhLLW+R12SFY8ACbQqWtIwq/6AfwQcv1X5bmmwMJnjd40dl2G0zbKi2Gg2LJndIa27sWcdKpItrdXtSZajzZA6mS6czOg3i1XJUiSFS3NzOnj2BrWcvJOypU1B/gMaWd6bTcLsnCZZNmpxgbPip3/bzxepvivgN5mN+/fvU7Vq1Sg4OJiCgoKofPnYLENoaCh169aN/P39KVOmTPTFF1/QoEGDlI5t+ZbOWrB/7z1FPZeGkmfBjLTIFfAn2PfPFfAn2FDGaYjHtWGTZg7jHdlQRvWujMHF9XZlLVGHoR34b7sZejbt4b6OsonBZzwy11fNEvL17BDL/4ZKTYU8aZUD/mIDvYUsIxcVHXa+9siFW9Rk4nZHXTuQFlRiWAucfg+cuWkLEoP6THh+r1IeEYBZBeza9cSBF9YMNPWtZCHl90DSpEmpYD8v0STcbTv9GaisMoM6sg/AyHdK02dz1DHwqC+fjjQokU1sWFgiVOV7IwetUJ6ZtDFC+AHAF0ClyEEuAv45u08ow+nAFSkcA6PbO7ARjVwbRiuCzlLvxkWpW8NilrcPibpOb07ZRTnSpSS//g2p49wA2njoIqlCahYHnIozXiqma3KnOMHAilzy5geKSVblo+l+5Bt5RUjowmiQfQHM+CNym+wsvq57HUqXKqkgnGtNx4x+swC9qxCz2QJBHPCqD6b7UaGsacRJlVXZe/Kq4IuoErSt2lP53Fnxk0pfXpZrXAG/yUx9++23FBERQd7e3nECfiy0YsWKUf369WnAgAF05MgRat++PQ0ZMoR69eqlPPfOWrAc8FcvlIn+UiA/KT/Af/xCV8D/fBaAPK5FB0WTHrvWK0x9LLSotb1h8if+LmtRq/aaSW+43m6Gns2r+F52MficqeX6dnToUafdH/7CYZYLMNhlc72mHPCzQgfXV5WVxPVa07KUydwofERz1WGnlUFnqPvi/YJsevrqP7YgMWKuVh+k2btOOCBBdiRhUZ/hUAjcpmw56gggjR5A+x4oNsCbHjx+IpSp4KfAGWeVAZDNooa9WTpa4rNgJiErqlKWBJ6mPstCqH7xrFS3WFYaujqMZG12qzZ4swTOyoPHT22RVtG2HCQD5iHLZFrdG5/z2O36vgENXhlKm8Iv0Yg3PahtDWtJWlYJQnZ7/+AmZBdSozW/YmlbFZdj9J1heB1qFqAhb5RyYPJVPRgY84+TpdfL5nIoZamejrGrMr7r2KQ2nridMqZORkGDY+WQjX6zZP4FKywBzlYuT3qCp4JVYdIwQ4Ksrk+Iz50VPyVEX1+UNlwBv8FMIMjv2bMnLV++nEqVKhUn4P/999+pX79+dOHCBUqRIhqXOnbsWPrll18oKipKOcvvrAW7PPCU0DNXVTt4URbni94PV8D/fGZIL+B/FllONr5BL0Hg/MRTXeUGdRhTi/+2m6FnTCyPEGQS361oDQvg61n1gv89s11lauSRXXnAP5sTIDDUXKC6UipHGuWAX4YzoQ1/ReMnXMv4X743oD2qKjOow5KmCNQh6wnsPzgAqoUlAj0LZRJ4dLgN+/ZrqFqdONParnp+IatYKEsa2tzbOMupfQ/w2A163YNGrAlTDprQQQeOPWVSETRiw4DAHSRalSJ7IMDxFqdcdlyqZUnU+4+eiAy9nc02cwAmf1SB1oacFRwMO9892ais77JgCjx5nSZ/UJberGBNWI+6dpdqjdtCDEtpOnE7Hb5wS9lDYkPYBXEig2w8vi+ygRuMuKzKL5siBGcEJoE4EWEMvf+AhpQtbUqr6oJ/AB4CPDdalMlJnmPsSbLKrtCAz4EArVVoMvvN4s0W1KkCTly1BQfjsU+e1I2OjFTf3FsOiskFzoqf/k0fX7S6roBfZ0YQyFeqVIlWrlxJWbJkoYIFC8YJ+Nu1a0c3btygVatWOWoD8lOxYkWKjIwU16sUZy3YZYGnqDcC/sKZaGEntUyRSv//69e4Av7nswL0Av5nMd760/eE8ABAsZthR50mE7cJ0ylRP8a9U/WJOXDj6+1i8Nk5k+urOsXy9QhcEMBwWfN1LSqeLbVywM+a4lzfDmmWf/y5rt0MO0sEAgoEwi8bOamOPZMvPXKmE6ZfqrAEbp9PRyAxuGr/WUI7XiYqN9r3QIXh6+na3YeCKP7zpgiqVjATLVbM0MtBK0i7yLg3K5WDpratpPT4PHaV82cURmmA5Khi6HEDNouCbwUC/r/8Twl5UKhkqZT2s/1p6+FL4vuyNuQcAdttx3216qiNgui99pta1GPRfjpy8TbNaV+J6pWwdnmWlWWgilRz3GY6d+MeybKUZs/AHAB2uy0+0FuMgSqcTVaXAhyrrE1JVhYZAAegiUd2kaHn0wqVsUeAz67UqZK7C4Um7do1+80qP3w9wShvQ486tOf4VSFpi35Mb2etkHT97gMqPzyWf5HM3U2ly//qGmfFT/+qky9YZVfAr5kQSNK1aNGCatasSQMHDqQTJ07EC/ibNGlCBQoUoOnTpztqnz17lnLnzk27d++m6tX1g2pwAvA/LliwefPmpcuXL1O6dNb1YPcoAAAgAElEQVQZhGddO8v3nqbvVx6i6gUz0p+fVXnWZlz1NCOAl+eGDRuocePGlCyZuU6xa/DUR0AeV4/hW0TF9yrlptFvWxP35Lss3XuG+q+MDvh/bFVaaETbKe/87kcHzt58pvpR1/6h+j/tcNwOWcrmpa2DFq6wwP80DV19yFEfQU/NwpmVu9/tr/20Liw2w7/6q+pUOHNK5fVadcwWEbRy8e9XjzKmTq50//M371Ht8bEY/kxpktGe762Nl7jxTeEXqcuC/Y57CROrr9QTFSA7/7IlknJnSElnrt8jGDet/FK9PszeNh++RHWLZqFtEZepUr4MtKiTcYZd+x6o9cM2unDrPrXzzEd/+p0S7cxsV1Fp7CCvWOOHbYK30LdpMRrrc4TeLJuTJrynhqHfeuQSdZoXRKVzpSNAOGfsPEEdauSn/s2LK93/162RNGnTUaGMc//hE1oZfE70o2OtAkr1v/prP60Pu0hDXy9B3gcv0J7j12jS+2WpZRm1td/gpx10+to/tLhTVeq5NETM31+fVaTKBa1dnu8+eETlRmwW/Qwe1ICqj9smlIY29qhF+TOltux/0Knr9P4Mf8qbMRV5f12DSg/fJOrs7V+f0lno0OO6RQFRNOh/YdSwRFYa3LIE1Z2wQ2Dow4Y2trw3LhjpFU5zfU9RlzoFqUHxrKIveTKkpC29rE3HUL/D3L208+gVGt+qtDjlgNkmpLgXfh77m2/2m1VvwnYx3ks7V6WAk9foh3UR9E75nPRDK+u1B76Hx9BoV+eAfvXFRuV5F8RPSMgi+fo846fn/RzObP8/E/APHTqUhg0bZjq2AQEBImBfvHgxbd++ndzd3Q0DfmTxp02b5mjvzJkzlCdPHvL19SVPT0/d+xj1YeHChZQ6tfUL6VkXRsClJDT/qDsVT/+EunrEEvGetT1XPdcIOGsEZoa7Ueg1N+pd5hHlfc3eXfddTkJzI9xFpfZFH1OFLJLOpEJTkw640/Fb0frTnxZ9TBVt1L/xgGjw3lhVmo7FH1OZTOr3330hCS2OjO47SjePx1Q0vXr9OUfcKOhKbJatX7lHlMPGK2ZgoDvdehirvT2myiNKrSayQzcfEA2Snj1dsqc0ovJjhRGPviTsWhKaFh777AVee0o9yqjXXx+VhNaedqdU7k/pn8dJqHDap/RNafX6fxx2o+CrboT7nridhEqkf0Jf2nhvDtvnTlfvJ6EqWZ5QwGU3Kp/pCXUorvbevfuIqF9A9EA3zfOE1kW5UfVsT+jDwmr1j9xIQr+GuVOOVE+pWPqntP28GzXO/YRez6dWf/PZJLTqpDtVzvKEwNnef9WNWhV4THVyqq29PyPcaO9lN3or/2MKvuImxs/O2h+7353O/ZOEuno8pvkRbnTzYRLqU/YR5U5jvXwgKtXDL3rshld65Pj+ja78iNIoxJ9n7hD9EJKU0iZ7Sn3KPhZrOAk9pZ88H5OFDL24Z+ClJDTvqDsVS/+E3s7/RLT1WrKnNEpx7a895Ubrz7hRnRxPyCPjU5p6yJ1yp35Kfcqprd1Zh90o5KobvVfwMbknIVoU6U6lMj6hziXU5l4e+6M3koi+1M7xhFoXVKvf28+dHj5NQkMqPqJMagq81pNqcsXdu3fp448/dgX8NkbxPxPwI4uO/5kVZO0//PBDWr16dRwc/uPHj0Xw36ZNG5o7dy49K6QnsTL8ywJPU79Vh4TxDqABrpIwI+DK8CfMOGpbkcfV3T0p3bj3UDm7LLcF458uC6Mzxb99VJ4ae2Sz1eF2swPJN/KqqPPrR+XE8bZqgcQgS4qizoy2Fahesayq1Wn5vjP0/Yro0wmURR2rCAMk1YLs6OqQ847L131Tk/JmSK6c4ecsNTewf2ADSpNCLeK/dvcBVR0TLaeKAgz99t5qWUpcv+vYFWo/Z6+jPvxDFkhZSqsxmLHzuMhOcrGTYUedHktCaE3oeYHdj7x8hxqXzEa/fWysA699DzT9eSdFXr5L9YtnoS2HLytnSXFvuNuWHRGdWW5bLS/N23OaPq2ejwa2UHOZBqTjw5kBIqMNGeYle89Qj4ZFqGs9NQ+I+XtO0bA10WZXcJveeuQyjX7bg6B4pFIGrDzouCcy/OHnb9Ef7SpS7aLWGXq032qqH4WcuUlT25SnPssPEJya13atRsVyple5vVD1AgxnVVdPh2nfwSGNCNhyq3Lyyl1qNGknpUnhTn9/4UlNJ+8SBmr7Bqi5FG8Iu0hd/9pP5fOmpz5NitHHswKoQObUtKG7NekVfZu6LZImbDxKrSvmptpFMjvMMuUMvdkz9Pn7gFA1+q5JUUrqloTG6JwOmf1mvTd9D+0/fUO8K/2OXxWnU1/WKUg9G6vBuaqN3UJX7zykNV9Vp+I5rGVErebD6nNXht9qhOJ//p8J+FWH5tSpU4SFxAVQnaZNm9KyZcuERCey+CDt9u/fX5B2kyePPuYeN24cTZ48+YUk7S72P0F9/z4oXiLzOuqfPqiOj+u62BFwYfifz2pIqHHdEXGJ2s7yF538o31lalBCPWBHHcYj479ZG1v1iW/de+jQwUYdGF/VLqoe8LNSDd9vRdcaVMHCfEfuG2uQ89/gdJsrXXJlDH+NMZvo7I17jibDRzSjlMlis+5m4wCibblh0epKKFrioNUY+kVeoQ+nRzsso9QqkoXmd6xmVc3x+aydxwVZlkuLMjnotzZqGHjU4bHL8loKunz7Pr1dPhdN+rCC4f2165XJk4BTBJy4ZgtDL0tTvlMhN60IOmOLNMumZ9hkgTsAlRw7krKyNOU/Dx8LHwQ7/BNZmtLrwDmKvHSHFnf2pGqF1OBo70/zJf/jV2nKxxWo15JgEbxv7VWbCmRVg7wyDh2+E/AwsCMJe/HmPeGMjGz+si9rCNOz3BlSERSDVApzAABB692kOHX8U13lBu3P2XU8WlWpbE6x5u2ang1edUCQzKGwlCRJEsEf+cQzH418OxaSY/ZubTtrD+2IuEwQGMC8L9sbZcv/JFYlqDpVyp9JZcj+1TUuDL/94XMF/BZjpofhB2asePHi1KBBAxH4Q7oTspyDBw9+IWU5F+05IbKFdYpmpj8/dwX89r8m+jUSKjBNqP68Ku0k1LiyXTzGxW7AjTpsQoT//vOzqgTVE9WC7CgbMKHOX508qboNDD4r1fD9VnerRWXyqGU5UafPsmBaEhjl6C6Ih9lfS6Yc8LPLJzcA5Q2VLCmuv3P/kUNSEP+2UrnRjqk8b/gMEpOzO6ip1Ii5ksja+DdMqCa8X0516uj75SG0KOA0JXd3E/KaH1XNJ7TcjYp2vb45ZSeFRN0QcpwgfXeqXZAGtPRQvj+06BH4Q0cfSkt2XJ7ZAyFTmuQCvw2VHBh4gfSuUnijiYATAT+TQJsp8k/Y6RemZ94HztOZ6/8IxRsVHXr0j82uQPTtszxEkLZ9+9alnBnV8HwspTv1k4rUZf4+h2KPyrPfvPfQQbRFggAeCEzgVamPsQJxFlr0PRoXpR6Lg21tVpcEnBbPjPWOdwU8ILDpm/iBtcsw+se+I1A0w7j9ses4wXDs++axp0Nm79Yu8/aSz8HzNOKtUiLgx/zhv9tWV+NvsGEdFKWgLPW8iyvgtz/CroDfYsz0An5UgfHWV199JYy3MmbMSF26dBEBP3bWqsVZC/avPSeo34qDgjw293P1TJnqc/xXr0uowPS/On6qAdSzjo+sha+qpS3fi2Xy8DdkDGsUVoMl4Ho5U4t/L+tSnSoXUM96+Rw4T13mx8JavL+tTXCxVC3IDkJhhYtfv4aUObW7csBfd/wWAsSBy7HRLchdBchMJKAg8mbHjlMs7rf/9HV6+9ddjns39sguTKxUC54bz8/FrsITa9FzfStJWO174P/tnQV0FUcXxy9QoLh7cHcnuAaHosUpULRYkRY+3KE4xSkUh0IpUCy4u7sECRbcS6FYwnfuvEzYLCG7s29233ubO+f0HJrs2G9mJ/+duXMv95aCAaDwAjPuuPaopO/SLNbJYyCgCReKyH7VskPb0vpMcm48fgVlx+0CdIWK+dFLjt5IsVi30ssPCv7zd/9hZqBls+ozh5uw9TKLros7yziHH//7DjZ1KwXZkuubu/wjG11TDg0+pcFLs4ni6ruAUn7cLmaGxaMkawVNU84pvHiaud9G9qOJDfMywZ47VTxY10WfSc6nGArRoWuFTMxDGF7Un9FM3+kS/8jHkxmMvTBlx1VA17BDa+XSNfW5W9DGRVKz9Qc/+NURxsP7m4UnKitPBLAPhP1XH7PdfuRQJ78+cy4e92B60wLMrajZySr9ZHY/rCyfBL+VtFV1WTVhQwR/lsSw4HsS/LKGnAS/LJKhy5HFVRkACoPRiNjAY4vQBzoea2Na0aEYFBYQ7JiH79Tiv0VNcrZffAAY+IYndJWXOZl+u1i1aEVf4Am+1i/4uXDi9V8fVU33ZsaHwCAWJZQnNHHY1E2/Db86aJmoSQ6P1Mvrx91mdHGpNw1dd4HtjvLEI6d+Kb96vnI//jGiRmG75L2qZIWOZTPprR64WUqmpLHh6sN/hXbo7734LyTCaoE0CZh7RTSPwUBOetLOSw+h1fyjTOii15trj16ByMcyDxhXv6AXbD53H16+/QA7fyoL6RPruHULAN2WnWRmSNylKbb53MAKEDumth97fLbar3uZK1YeJRnNstClrN6UuZ8vvA/8CINr5mDmNbhm4NqhJ/H4E7GiRYHO5TOzQFwip0tK9livSJRibB83Zfsmb0r4EBQEvmfvw9BaOeE7xQ59eGsrNwnqUj4TE/v44Y0f2vjBrSe1mncEdqJL1np5oEFh7bgJesoM7xmr9JOz7XSn/CT4XTgaVk3YpYduMPeEZbMkhvkk+KWNuCxhKq1BNilIFlc0J8Dw9phETWIwT7/VZ2HJYccuuYhZQojQHbAR3rx3eLhAP/i5Uuk3ydnl9xBazjsaMqI7epaBDEn0mTVgJm5LzQs4MaAixIkWSfcOv8+E3UxsYsKNff9R1XXPLnRtnL6Pb8jzuVLFhfVdSunOz6N28gwoYDCQk96kvv/wQ9mM0FsgSjM3S+H1qXdJ1e1Qz1d1lGPRKM/cF33SONGZT3qRHXq8LF5gmMMfOor2s3degEjQtgNXH0OTOYeZOdKrt4HCJjlz911nO/M18qSAzefvM/GMgZxSxo+ha/i4ORXGAUDBi+ny0Iohd+W0CuGnKxgsbPqua0I2+Fg2jz/R3ScLTNx2GYplSAR/tNNnBvvw5RsoMmI7uzfQrYIjv5Y5mLI//O5KxiSxIG/q+LAKL+5XzcbMcvSkZUduwf9WnQWf7EnZ3Qduj68M+Bfe2qqMFIx58f0XMUXsvPQErD9zjwUO+76kvlhEevr1pWes0k/OtNHd8pLgd+GIWDVhlx66Dn3/vsC8RsxrRTv8soZcljCV1R67lCOLq1L8iJgVcI5D1p2HefsdokNUsDPBNXgzvHzzgeUXrR+P1JvOORwypHt7lYPUOnyJ8wzD11+AOfs+7VKfHlSJudX09fVlcUa04kbwKKVYHvoSvzKimtD0Up5uoHhZ06mE7vwoNPCDgyeRXVI2VmfuQuelJ0Py425x94pZdNc/fosfM6fgSUuwq+drmwXHYNvFT0HP0LykYeE0uuvn9yfQlzoKt2lNCrCLnHqS8v4EBixDs6wlbbyhRCZ95mhKO3Tc4UeTHBFzsqWHb0Hf1WehQrakgPEUMOHHJt4p0JP4hyq/sPxVpI9wcWhlzfnKy2425zDsw3fHOw37WBe9P+I9chs8+OcttCqRjr37IlGO/337ATDKMia8tzF773VoUSwtDNFpkqO8cI2nMxvO3mMnDS1L6BPPGKUXzRAxwjRuNIS1Qx/e2jpt51UYu9kPGhZKzUzB0BxNZKOEf6yJ3DnRMye+9IxV+smZNrpbXhL8LhwRqybskoPXod8aEvyyh1qWMJXdLk8vTxZXdHGYfeAmhmN7zzKQUWCHHPPwS3D4783dSgu7mis4bCs8efWO1b+tRxlAEw296bD/E2io8FQjskuKdah3qc8PqQzRIn/ULfj5BTwsC4Wn3/CqepvOnsvSfyO8Q0fuAEJmEfg8t0PnFTYqnBp+qZdHd/24s9x+0af7D1o79OqC0QYdbdF5+qVubmhU5MuCXT1fOy45zswpeBLxcoN5yo/fxbzb8CTiYUpph47BjzBy6sof9HtN4eZUyeJGZzv8KGJFTHJWnQiAHn+eZheG0UMRJpx7el268neOX1jGWApnBusX/PxjCz+QMNKvqDlZuXG74PrjV1C3QCq2wy5yf0R5bwfdmK44HiB0YZubIOK9A/RqhJGyR9bJDU289X0s7rj0gF00zuOF5liBbIdeffcovLWVR/dGdnv8HgmbY/FNhvalM0Cfatl1v69GH7RKPxltnzvmI8HvwlGxasIuPngd+q+5wKL3zRXwduFCNB5RtSxh6hGdtbCRsrgGBX2EDH0dpiWiO+SYh19AxH+LmtRgnqIjt7NdMkzoFjNtIn12zPg832nl2I/0rQBJ4+qzY8Y8Yzdfgmk7r4WMGrrVjAJBugV/zSn7mDkIJrRJPj+0itAMyDFwExMdmPAS4vL2+iPdBjx7DSVHOyIsY1K7FtRqCBc+/DkRt5SYZ8aua8z+mictwa6er9wOnef/rXlBqJRTX6RZzMPdevL8S9t4Q3GdO/RoToWnKxiEiieR06mrD1+Cz4Q9LFIqnhagSc7BPuUhRTx9Jjm+Z+9BxyUnQjwUYRuujqgKX0XR9oOPz07adhkmbbsCBdLEhxO3nrMgWCcG6hf8/KI9+v1Hs5S8XvFgTWd9l26xfv6hy08oqudOAdOa6ouSjPmz9t/ITmXwQwEFO5oW9dJpTqa8f4EnMrv8HgF6K/q2kD57eKVJEHqXuv30P1jVsTjgaQFP4a2tfx67Db3+OsNONfZcecQ8/Rzt5wNJ4uiLojVx62XmChRPV0bU0Y7Oq/Uea/3eKv2k1Q5P+j0JfheOllUTdtGB6yEhv39vqd+9nQvReETVsoSpR3TWwkbK5Io2/OhLHS/uxflaR7hNRT/5ETf+yMgHQ6kxO9gfXUzoyxt9eutNZwKewzdTP3mqETGLwDqUHyv4/1dGVAUICtQt+GtN2w+nbz9nzcXgQ2cHV9bbdPac0pypRKZEsEQg/seDf96A90hH8ClMaF4xqGZO3fXvufwI0I6epyHf5IQWxfW5FsQ8c/b6w/ANF0Pyz2xWEMJzS6merz+vOM12d3la3NobSuoMPIV5ak3dB6cDHB9bmNSiTQsE9/LDnxM53br99DWUGrOTuWDlJzQnB1SEBDpNcvjHFr9/gAGgro7Ubw42a/c1GLXxEqAdO14YThj9Ixzur1/wc3e0uMuNrlHxpGFFB32XbpEXvwNQKG0COHbzmZBbTMyff+gWePb6PfOyg/EERMzJlPEreH6tj03lXFCaBOHP77343CQnvLWVf6zlTBmXeWfCdGFoZYgZTV/Avdl7/GGE70XNuBVa81fv763ST3rb4wnPkeB34ShZNWEXHvCHgWsvgk+2JDCHBL+0EZcpTKU1ygYFyeR69/l/bKdSxMMNR6gUfujWMnk8/TvsWIbSNEN0h/7C3X+g2uS9IaOJNvjxYuj/YFGbpfiPrAaBgR90C/660/ezHVZMuNt7amAloZnFhQ9mwvgFGMdAb8IPtELDt4U83q50BugrYCJw8NoTaDz7U+Au9KGPlyf1JrUf/3mtCkO5cNxSquer8rI31iliUoPPfzvzQIg5DP6/iA09Po9Bz1A88iTysckvnipZXRxaBWJE0xd0jd894fcPRE+HFhy4AYPWngce9Czp1x9hfz/9gn/QmnOw4OBN5gv/1tPXQn7wsc/8DgD3kIT27KPr6zcnww0GdBaApkQYZVjEnExpjoX+//0evAQRF5dKkyD8YAvr/kV4ayva7WMcBNyYwD5gEjmd4fc3fLIngzkt9LvR1fteqp+zSj8ZbZ875iPB78JRsWrCLtjvD4PWXWQh4me3KOzCHturapnC1F5knOuNu3BVCj88IUARIpIqTdzNAi9hEt2hv/LgJVScuCekOhE7aMykPJ3gXnZEuCpFZ6JY0eD4gIoiXWeCHYU7JrTHnttS/7rz4vV7yDv0U6ReEbMIrE8duGv8t3mhXkF9vsQxPxcuvMNankrUXNUekjZ0LQk5U+r30NR0ziHYf/VJCO9dP5WFdDrdWmIm7uWHF3C8vw8k0jl31VGSsQz8WIysMwbD8ZtPod6MgyFtF507PPgUD3qWKuZH2NVHv+Af5XsRZu3xZx/H2BfRudd24TFmioNmLI9evmUByzBwmd7EvVvxGAwiMRSwjiz9NrJgbzy/iFvM+y/eQNFR2wFPVfDOBPZffXcovDWAvzcYwwHvbmAScce79vRd6Bp8aXhZO/0mfHrZkuA3SupTPhL8zjM0XIJVgn/+fn8YTILf8Dh9KaOIgJJeuY0LdBeuSw7fhH6rzzHSpwdWgngx9e+wYx6lLbboDr3/o3+h/PhPnmr8hleB6F/p22XFurlpBP6be9kR4dpw1kHmwx0Tih+05RVJ3NsJ5hG5+IjPK72d4P+LmEXg8+rAXVMa54eaefX5ocf8aj/+WjEU1Fy56OS8RC69Yh7uz5znP9y3AiQTuL+hNCXDMkTMMtRB03CnGKMs603qGAop430NB/pU0Jsd1py6Az8uOxXyfNrYH2Fbb/2Cn9uR8wKq5EwOM5vrC3zF5tqyk7Dm1N0QkyatoGvqjvEoyzwGg6g5GY/B8HXUyMzTjtbpkrL+l2/eQ+7Bjg9lfOfx/oX67lB4awAPHMbLFDXHwg8k3KjA9cLIiaruSRL8oFX6SbRd7vw8CX4Xjo5VE5YL/ko5ksJv3+nfaXMhGo+oWkRAeUSH3KSR7sJVGbFVRDSFiI1Je9ixvqjowue5LTUvSyTSLeZRmiOheLg0rCqIcG0y+xAcuObYZcbdxkN99Ys2zMNNG/DfItFG8Xm16PypUhYWyEhvUotOLRt8dblq0enbtRTkSPnlSLFqruM2+8HUnZ/ceoqac3VYdBw2nf/k5Uf0Y7PC+F3M/p0nkR16dQwF0fsbapeqGHALP3j0JrWHpYxxPsKmXvoF/8zd15h3LZ5q5UsJvzbSH8OBu5bk+UVjOCg/lLEMES87+HzxUdvh7gvHRX9MIi5V1dG9Mb/anCu8NUC9ycDXDb1jZ/VzVuknq/tlZn0k+M2kq1G2VRN2/r5rMHj9JaicIynMIsEvbcRFBJS0SiNAQe7CdfnRW9B75VlGHHc5cbdTJCldW4rm5x47eH0iR+uYh7vYw3/jEf25IZWFBH/z3w8zLyeY0KYXhYNIKj1mJ7OhxoRBmKY20e/pRC1cRIIPsbF68BIqKcyh5rUsDOWyJdXdfH55kWfQ8tCknq/q+xNnB1cSujCOZhFoHsGT6OkOjzaL+dE05jJe2BZI3NMMZhE93VF7WBJ1i6m+cJ0tXhCs+6mKbj/8/A4A7y66xxz7bV7dvVfG3sBMoqdL6tMZES87WJ8y4B3+/5/ti7ELwHqTcuwwD0bYThrn092j8NZW9SZDnOhfwdkhYpf19bZTxnNW6ScZbXWXMkjwu3AkrJqw8/ZdgyHrL0GVnMlgZnPzL9O4EKmlVbuLMLW00xZU5i5cuZs67LKo4MY8SuElmh+PxwuPcFxcFT1axzyLDt6AAWvOs/xoz4wmRSJc8fIeXuLDlDphDNjbS0zwlx+3C/wfO3aZMYjSxIb5dM8c9S6zqFtN9U6lyC4pNhJtuNGWmyetGAhqrmq3nqKnMz+tOA1/BXv5QdN5zB8Jw7fqTHWm74eTwReuRXfosQoebdbI2KsvXIsGXUPPNg1mfboDkCtBEKzuoV/w8zsAHJWoS9cxmy6xCL08iVy6xTydlpxgAbN4EvGyg3m4SRDPr2VOpp4SSu9Y+Du1h6Xw1gD1JoORy/o6p6iUx6zST1Ia6yaFkOB34UBYNWHn7r0GQzeQ4Jc91CICSnbddi7PXbii6ELxhenGL9WFkVefvDfEvZ1o/uev30G+oVtZnUYi3SovnmKUU7w0LML1+/lHYUdwpFRRswxsc8UJu+HKQ8eF5foFvWCcwC4r5sncz5fZIGMaWisnfFdMv1tN9U6l6C7pLr+H0HLe0ZDx1rr0qub6+77rMGz9BZbfiFkERqrF8cOEQZgw8JRIavTbQTjk77h/ge4xjwjev8APTfzgZOOQNDZs7VFGd/Xq+xe4O4389SbuWpI/nz9REPzZTb/g5xdHef7vS6SHgTVz6K0epu64AuO2fAq6JvqxqfxYw0pnNC0AVXPri5KMz6tNgkRiKGB+ZbA//H/16VJ4a4BykwHzopMCdFbgrskq/eSu/TfSLhL8RqhJymPVhP197zUYtuESVM2ZDGbQDr+k0QMhASWt0ghQkIgwNRPH6pMB0H25ccFfY8peOHfH4c9aVPArhZMRwa/c6eRmGSJcecRSbDv6RN/eU78dNuZRXlgWjZSL+bMN2MguLWIStYNW71T+3akE5EsdX/dUOXD1MTSZczjkeS0PSWquytMV/rGlu3IAUHr58UoQA/b1FjtdwRgEaBqDCd1T7ulVTqR6UF76zZ0qHqzroj9wldK1JFYq6pJV7Z2qcJIgWNpVv+BXn850KJMR0CRMb1LHYBC9dMvdgvL65nxXCHxyJNNbPShN6TDTlu6lIUuyOLrzK4P9YSYMuPd11E+X/cNbA5SbDJg3Rbyv4aDAhWvdjZT0oFX6SVJz3aIYEvwuHAarJuycPVdhuK8fVMuVDKY3I5MeWUMuIqBk1RkRynEXrsrLm6KCHcdJGa1WNL/y4qoRk56VxwOgZ/DpBP/DLcJVeXE0S7LYsKW7/l1e7LvyY8dI5M3cgzbDy2DXgGPq54EGOqONYt1qsxKtS7fqd+rojafw7cxPZiVavsjVXJV3P4wIdqWXHwyCtKFrKaHXnruWxGN2WN4AACAASURBVExGxk5pRy4auArrxEi/eA8Dk6iHJvXpTPGkQbCgi37Bv+/KY2j2+6ePNVEbfLVLVtEYDqM2XoRZu/1DxgvjT+BHj96k/NDGPFr3R9TlKu/O4O/U5mThrQHq0xkjc1dvP2U8Z5V+ktFWdymDBL8LR8KqCTt7z1UY4esH1XMlh2nN9LsocyEaj6haREB5RIfcpJHuwlV5gVBUsCNKZcRU0fwfAoMgU7+NbESMCH7lxwr/wy3CVWmLLHrxkvVdEam3RbG0MKSWfl/mmF8ZuGtSw3xQO38q3bNT7cdf7YtcqyClW0897NVclSdDRgT3+C1+MGWHw8tP8YyJYGnbolpNDvX7zktPwPozDjtyjDi7trP+HXrMozRFK5U5MSxq7S1Uf86Bm+DVu0CWB92holtUvUltVlI6eRD83km/4FfHARC1wf/75B3otvyTW1DRGA5qt6BaMRzUXNR3AEQjfCs9NOG1j+ujQpsihrcGqL1jGTHl0zvOMp6zSj/JaKu7lEGC34UjYdWE/W33VRi50Q+q504O05qS4Jc15CICSladEaEcd+GKl0eHrr/AomY2LKw/UisfI6XoFRX8yourUSJHYjt1Imn9mbvQeelJliVtopiw++dyQiZoXf44CeuCPcUY2WWuN+MAHL/5jNUvakeNeZSBu6Y2yQ818uj3o4+RlXMO2hyCa8/P5SBNopi68Z2/+wKqT97HnucejsLLrJ6vSvZoSoQmRSJpyvYrMH6rw45c1KUp5unx5ylYdeIOy18mSxJYIBDlGPMox84ne1KYIxisUWlHLnp/Q+lLHttSIWUQzPxBv+BXjh3mF7XB33L+PrRbdDxkuERjOKgvbK/8oTgUTJtA9/D3WH4KVp10jB0m0RgMSlO6sDw0hbe2qr1jid7f0N1JSQ9apZ8kNdctiiHB78JhsGrCcsFfI3dymEqCX9qIu4swldYhNynILlxrT9vPgkBhEhX8mCfd/zawvEYE/6Zz96DD4hMsf4YksWBHz7JCgr/bspPw9ymHa0gju8ToaQU9rmBqVzoD9K2WXWh2FRu1He4F+yMX9aP/7kMQZOnvOB3BdKhPBUge75NrQq2GKO3IE8eOBsf6hx9lWD1flaLRyA79b3uuwUhfhy95I/cf+qw6CxhDAlPjIqlhVN08Wl0O9XtlDIbqeVLANAGXqliQMgaDqDmX+g5A5VRBMLWDfsF/4/ErKDtuV0h/htXKCc0FLnzvv/oYmirub8xqXhAq50yum9/8/ddh8DrHhW1M6zqXhNxe+qMsq+MAiEboVnr5iRUtCpwfWiVU27XW1vR9NsBHhzUWZE8RFzb+KGZOphuUhAet0k8Smuo2RZDgd+FQWDVhueCvmSc5TGlCO/yyhlxr8ZRVT0Qrxy5cle4RnRH86JrRX3U0rzUnlJcXuVmJCFflLrGRXWqlaOxYNiP0qqL/4iT2TXlxdG7LQlA+m/6Lj2q3nqKi6frjV1AuWDTqiUGg5rrT7yG0Cvby45M9GcxpIXZvSikajXwsKS/99qiYBbpW0B+0DNkrfcnXK+AF4xvo92OP+cuP3wX+wYG/RCPVYv5MfX3hQ/AdgOqpA2FSu6q6/fCrL56Orpdb6HTu5K1nUGf6gZDXSyTSLWZaduQW/G+VI3YHpk3dSkG25F8O2qZ+j9WXfkVjOChPZ7g7XmUdWmtAln4b4V2g47K86IVtrTVJ9u+t0k+y2+3K8kjwu5C+VRN21q4rMGrTZfgmTwqYLLhb40I8bl+11uLp9h1w0wbahWvd6fvhRLA/dGcEf1i2uFpDt/PSQ2g13+Faku/UiXD9ecVpWBHsCx5NEtA0QSQpvY10LZ8JelTKKpKdCW4U3phELz5iHn46gv/GoGNomqM3KYNH8dOR8PKquSq9/IhGesV6lBdHRW3QMb/y4qho4CfMr7ywLbpDj/mV8SeMfOwpzblqpw2EsW30C361WYro/Q+1l6ClbbyheKbEeqcOqKM0i166HbHhAszeez2kPrWXHa2GKF2yhnU6pbUG5Bi4CV4H37/InyY+rO4oZo6m1T6Zv7dKP8lss6vLIsHvwhGwasLO3HUFftl0GWrlTQG/NtYf8dKFaDyiaq3F0yM64YaNtAtX5W6b1YJfeeGY79SJcFWaFhRJlxD+7KDflzpOqZbzjsAuP4dryO4+WeBHH7FdZqUf/6VtvaF4Rv2iSy34RSPVPvznDRQZuZ21PUeKuOCrYdag5qr08mPEpEYZ/2FY7VzQvGhaobd0whY/mBx86Xdxa28omVmMndKca2CNHPB9yfRC9Ss/dI2cMCjNUuqnD4RR3+sX/NhQZfCp6U0LQDUBP/h3nv/HTJJ4+qtDMSiUTn+k203n7kOHxZ/uAIheuh232Q+m7nRc2MYkGrRN+aEdlltNrTVAGXTNyHsvNFGcfNgq/eRkM90qOwl+Fw6HVRN2xs4rMHozCX7ZQ621eMquL6KUZxeu9WccgGPBF1etFvzKXWYe7VSEqzL4U7EMieCPdmKeYtosOArbLj5kU9bILrXy8uGKDsWgsIDoUgt+0SjHz169g/zDHEHP9ESKVXM9ffs581KEyYhJizJ41OTG+eGbvPovLGOd03ZehbGb/Vj923uWgYxJYgstHc3mHIZ9Vx+zPKKXRjFP77/OwPJjt1n+PlWzQfsyGYXqb7/oGGw+/4DlaZwxEIa2FBP8SnMwUT/4apOgtZ1LQB4v/TEcMDo1RqnmSZTf5O1XYELwhW0jpnyt5x+F7cEB88KKkK21BigvXBu5fyI00E4+bJV+crKZbpWdBL8Lh8OqCTt952UYs/kK1M6bAibRDr+0EddaPKVVFMEKsgvXb2cegKM3HJ5qnBH8RvIf9n8CDX87xOrmJjkiXAf8fQ4WHbrJ8pfMlBgWtxFzzagUbRj4CAMgiSRlDAPRwFlYj9KkR5S90h95gTTxYZWGWYOa64W7/0C1yXtZd7uUzwQ9Bc2ZlLvE81sVhrJZk4qgY4IRhSOmC0MrQ8xo+s2ZMI/SBl+UHeZXit4BNXKwjx6RpLyD0DxTIAxsISb4lTEgFrUuAqUy6/eDr77wjZdW0SROb1K+d5jn5ICKkCBWNL3ZYdbuazBqo+PCdvSvIoPf8Kq68+KDSnOsDIljwY6fQgfM01oDvEdugwf/OKIsG3HJKtRYJx+2Sj852Uy3yk6C34XDYdWEnbbjMozdcgXq5EsBExuRSY+sIddaPGXVE9HKsQtXpacaI8LJGdGq9EdeJH1C+LN9MSEvPUrRJRotFeer0p+4qGtEzK+88Ly+S0nIlUq/pxNnBf/bD4GQtf8m9trpCTylnq9XH/4LGLwKU+8q2eCHsmIfO8r7F6s7Fof8afS7dcQ6+/99FhYfcnjpMTLvULCjSdfY+nmFzYGwTqWnHSOXjpVeir7PEgh9mosJfuUJxfJ2RcE7QyKhJVR5cVX0hER5uoOVit4fmbf/OgwJ9vITJ/pXcHZIZaG2d/3jJOAJEaawYkBora1KD0vlsyWFuS0LC9Vv5cNW6Scr+2R2XST4zSYcTvlWTdip2y/DuK1XoE7+lDCxof4gKC5E4xFVay2eHtEJN2ykXbg2nHUQDge7pjQivJwR/EpvI/xoXoTrsPUX4Pd9jsuD5bImgXmtigjNFKXwGFQzB7QqIbbLqzwd2dytNGRNHkeofmfYBQV9hAx9fVl93ukTwvL24d9fUHO99eQ1lB67k+UfWisnfCfgFhLzKF1Dil76xPw/LD4OG8/dNyz4hUB/4eHpu64C+qTH0xlRkyKM/4BxIDC1yxYIPzcVE/zKj00jp0P5hm6B56/fs/pFbfAvP3gJlSbuCaFyeXhViPZVZN1IlRe2E8aKBuhhSiT1/PM0rDwRwLKEFT9Daw0oO3Yn3HjymuWvlCMZ/PadmIcpkbY6+6xV+snZdrpTfhL8LhwNqyYsF/x186eECST4pY241uIpraIIVpBduCo9Zlgt+M8GvICaUx3Bo/jRvAjXkb4X4bc9/iy/keBLygBCRi6eNv7tEBz0f8LqNyJ6nRH8WCfPr+f+gprr/RdvoOgox6VfI15yDvk/gUbB5ljH+/tAotjRhVYA37P3oOOSE2EKPqGCnHgYXaNiioQupgST8nSqU45A6NZYTPAr4xD4di0FOVLqN8nBpip3uY/0rQBJ4+qP4aD82MOyRO+PKC9sJ4sbHQ739RGi12fVGfjjiOP+RFj3T7TWADyZwhMqTNVyJ4fpbhy3xyr9JDQAbv4wCX4XDpBVE3bKNj8Yv+0q1CuQEsY3oB1+WUOutXjKqieilWMXrkrXllYLfqUdedmsSWB+qyJCJj2/bLwEM3dfY1PPyE6fsu+j6uaGxkXEIhUrvY2I7rIqBTv+2xn2eu4vqOfrk3/fQsHh2xg70SjBmEdpA39lRFWIGkX/DjHmR7GNAd8yJY0Ncb6O6nHLx93n/0HxYE85XXN+gC6Nqun2w4+dHb3pEjtdwLStRxnGQSQp7zCcGlgR4sfUb4P/8OUbKDLC8bEXNUokuDJCLEK28nTDK0EM2Ne7vEjTYeCac7DwoOPuTaG0CeAvlTtdrbVVeVkeL4vjpXF3TVbpJ3ftv5F2keA3Qk1SHqsm7ORtfjBh21WoXyAVjGuQT1LrqRitxZMIGSNgF67o7WXg2vPQoJCX0MVBTs2ZXWqlaQHfoRfhOnbzJZi20yGaquZKDjOaiQXsU+40jqmfBxoUSi00GZTBnw72KQ8p4sUQyu8MO6yI59dzf0HN9eWb95B78BbWXtFIrZhnx6UH8P38Yyy/kY8VIVBu+PCHwCDI1M8RKblt1kDo1Uxshx8/VPGDFZORj8XKE/eA34OXLL/oped/3ryHPMFjb0Twbz5/H9ovcrj1TJ84FuxUXbrVGi6lKV5Yp1Naa4DysnzdAqlgghvrBav0kxZzT/o9CX4XjpZVE5YL/m8LpoKx35LglzXkWounrHoiWjnE1THizojWa4/+hQrjHRdHK+dMBrOaFxLa4Vf6cq+eJwVMEwzYp7w4OqFBXqhbwEtoGrdZcAy2XXS4ZjzazweSxBEza3GGnZI9Px0Jr/Hq+frmfSBkG+C49CsaJRjz4KXhOtMOQB6vePBLvTxC3OzyMI+2O6TAB2hSR2yH/48jtwDNejCJmuRgnuqT98L5u/+w/FdHVIWvBE5YlF5+jATM2+X3EFoGR2kO69Kt1vgqT+bC8rKjtbYqL8s3LJQaRtd33/lnlX7SYu5JvyfB78LRsmrC/rrVDyZuvwoNCqaCMST4pY241uIpraIIVhBxdV7w33zyCsqM3cUK4ra4IlwnbbsMk7Y5XDsaiRar9PLza6N8UCtfKqFZ3HbhMdh6wSH4Tw+sBPFiipmmyBL8FbIlhd81PJWouSov/RqJEiwEyqYP4+nYk5f/wfnDu6BaNTHBrzSLMTJ3ak/bz0yiMImesKA5Vfo+jgvfRvIfuPYYmsw+zPKGdelWa7iVH+phednRWgMazDwIR248ZdU08U4DI+vk1qrSZb+3Sj+5rIMmVEyC3wSoeou0asJO2uoHk0jw6x0W3c9pLZ66C6IHQxEgrg4czojWgGevoeRoh6eYmnlTwpTG+YV2+KdsvwLjgwMA1c2fCiY0FDsZHLruAszd7/Dyg6cDeEogkpSC//yQyhArupgveWfYKdlXzJEMZmt4KglrvvL6jUQJFuFk52eNrgPbLjyANgsdJlEXh1aBGNGiCGFyZfyM4zefAUboxpQvdXzm5UgkKd9bfrKnzK/FtMnsQ3DgmuOyfItiaWFIrVwi1Vv6rFX6ydJOmVwZCX6TAYdXvFUTduKWS/DrjmvQsFAqGF1f7A+3C/G4fdVai6fbd8BNG0hcnRf8Sk8xdfKngokN8wkJfmW01voFvWDct3mFZovSy8/MZgWhSq7kQvmVJj1+w6tA9K/ERJsswR+WaFJ3JKz5+s3UfXDzyWs41KeCsOAUAmXjh42uA0q3ptdGVoMoGLJWICk9RInu8Cs/FvHfovnP3XkBNaY4vGsVSZcQ/uwQvktYdbeU9xfCMsXTYvrd3COw5/IjVqyRKNECmJ1+1Cr95HRD3agAEvwuHAyrJuyELZdgMhP8XjC6vtgfbhficfuqtRZPt++AmzaQuDov+B+9fAuFRzg8xXDBLsJVKRyM2PIqPaX83qIQVMieTGi2tVlwFLZdfMjy+I+sBpEFRZsswV89dwqY1jT8YIVhcQ0M+ggfgoKEP1SEINn8YZH5qkShvLAuKrixHKWHKCP5nZl7Vx68hIrBfvxLZEoES9oUFRpljJ2BF3cx1c6XEiY1Cu1lR4tp6/lHYfslx3vXvnQG6FMtu1D9Vj5slX6ysk9m10WC32zC4ZRv1YSdsPkSTN55DRoV9oJf6pHglzXkWounrHoiWjnE1XnBjzbQ+YdtZQV9W9ALxn6bV2iHf85efxi+4SLLjy410bWmSBq/xQ+m7LjKssxvVRjKZk0qkh2UwsNq0YUN5aKNm0OF13iar0JDq/thZ7hO3n4FEsWOBk290+qujz/oyrmnvHuj58K4unOLDt2EAX+fYz8O62ROi2n7Rcdg83nH3ZlO5TLCz5WzCfOzKoNV+smq/lhRDwl+Kyh/oQ6rJuz4zRdhyk5/aFzYC0aR4Jc24lqLp7SKIlhBxNV5wa90D2hE8M/ddx2GBu8UNiuaBobXFhP8yku/i1t7Q8nMiYVm8ffzj8KO4J1GVwr+RoVTa3rKofkqNLS6H3YV1w6LjsOm88YjFTuzw680xfPJngzmtBCLdLv86C3ovdLhoSisD3Utpp2WnoANZ+6x/D9WyAzdK2bRPV5WP2iVfrK6X2bWR4LfTLoaZVs1YcdtughTd/lDkyJeMLIu7fDLGnKtxVNWPRGtHOLqvOB//e4D5Bi4mRVkRPAvOHADBq09z/Ibubw3dccVGLflMsv/R9uiUCxjIqFp7GrBj/1H944LWxeBpHHCj7RK81VoaHU/7CqunZeegPXBotfqj82nr95BgeCTOT33R9QwV50IgB5/nmY//q5YWhiqunSrxbTbspPw96m7LP9PlbJA5/KZdY+X1Q9apZ+s7peZ9ZHgN5Oumwj+sZsuwrRd/tC0SGoYUdd9/eq6cCgMVa21eBoqlDIJmZ7YGZczO4Xoyz1rf4cveCOCX2ka0KpEOhhUM6cQaox0inb8mFZ0KAaF0yUUyq8MvGW16BJqKADNV1FgOp931fraffkpWH3yDmul1XPv1dsPkHOQ40PdSIRrpUvS70ukh4E1c4SircX0pxWn4a/jASxP7yrZ4IeyGXWOlvWPkeAXZ06CX5yZtBxWTVgu+Jt5p4bhdUjwyxpArcVTVj0RrRzi6hhxZwQ/XhrN2NfhD9zIpd2lh29B39UO04C2pdJDv+qhhYPWnJy9xx9G+DruAKzqWBwKpEmglSXU70nwC+Gy5cOuWgfQpAVNW2JH/wrODakszNaZ9/Z9YBBkDo4yrMclrLpxm87dhw6LHZF625fJAH2qhr50q8UUA5bhyRam/tWzQ5tSGYT7b1UGq/STVf2xoh4S/FZQ/kIdVk3YMRsvwvTd/tDcOzUMI8EvbcS1Fk9pFUWwgoir84JfGQDIiOBX2gKHJRy0pqTyDsC6ziUht1c8rSyhft9y3hHY5edwD2j1LqtQQ2mHXxSX7uddtQ7gu7Pr8iPIkSIuJIsbvjlXWJ1xRvAr31uf7ElhTovCunnhgzsuPYDv5ztiEHQulwl+qpw1VH4tpgPXnIOFB2+yPINr5oCWJdIL1W/lw1bpJyv7ZHZdJPjNJhxO+VZN2NEbL8CM3ddJ8Esea63FU3J1EaY44uoYavzj3W/1ORjfIC8Uzyh26RXzc+FhRPCvOHYbfv7rDGtHx7IZoVcVMW8dCw/egIFrHHcAfLuWghwp4wrN3xZzj8DuYH/gRgR/5n6+8D7wIySJEx2O9vMRqlv0YZqvosT0Pe+pXJ0R/Mr3Vk+UZzXJvVceQfPfj7Afd/PJDN18Ql+61WKqDJg3vHYuaFZU3MuRvtF1/imr9JPzLXWfEkjwu3AsrJqwo30vwIw916F50TQwTNDbhgvxuH3VWoun23fATRtIXOUMjDOCX3n5r0v5TNCzUuidQq0WLjl8k32sYNrSvTRkSRZHK0uo3zsr+M8EPIcJWy/D/6pmg2zJxT42hBpKO/yiuHQ/76nrgCzBXy5rEpjXqohuXvjgIf8n0Oi3QyzPz5WzQqdymULl12I6yvcizNrjz/L8Ujc3NCqSRqh+Kx+2Sj9Z2Sez6yLBbzbhcMq3asL+4nsBZu65Dt8VTQNDSfBLG3GtxVNaRRGsIOIqZ8C58KhXwIudEohwXXPqDvy47BRriBH3fMuO3IL/rXLcAdjeswxkTBJbqFPKiJ9GdviFKnPyYRGuTlYVobJ7KldZgr9MliSw4HsxwX/85jOoN+MAmyd9q2WDdqVDX7rVYjp28yWYtvMay4/RtfF00F2TVfrJXftvpF0k+I1Qk5THqgk7asMFmLX3OrQolgaG1BLzpy2pq7YsRmvxtGWnLegUcZUD2RnBv/7MXei89CRrSI+KWaBrBTH3fEqToN0/l4W0iWIJdcrZaKdClTn5MM1XJwF+IbuncuXBq/KniQ+rO5YQhsPf29JZksBCQcF/NuAF1Jy6j9U5sEYO+L5kaBt8LaYTt16GX7dfYfl/bZQPauVLJdx+qzJYpZ+s6o8V9ZDgt4LyF+qwasKO3HAeftt7A1oWSwODSfBLG3GtxVNaRRGsIOIqZ8CdEfwbz96DH5acYA0JyzRAq4WrTwZA9+UOf+D7epcDrwQxtbKE+j0JfiFctnzYU9eBF/+9h7Wn7kDV3CkgcezowmPD39tSmRPDotbeQvn97r+EypP2sDzDauWE5sXShcqvxVQZP2Nqk/xQI09KofqtfNgq/WRln8yuiwS/2YTDKd+qCTti/XmYve8GtCqeFgZ9k8uFPbZX1VqLp716a11viKsc1s7Y8G8+fx/aL3K49zPij3vt6bvQ9Q/HCcGhPhUgeTwxbyck+OXMAU8uJaKuA/y9LZkpMSxuIyb4/R/9C+XH72bDHpYNvhbTmbuvwS8bHfEzZjYrCFVyJXfbKWSVfnJbAAYaRoLfADRZWayasMPXn4c5+27A98XTwkAS/LKGT8gmWlqlEaAgrT9KEQCBlC46s8O/7cIDaLPQ4d6vX7Xs0La0mD9u7ssc8x/r7yO809lszmHYd/Uxq59s+KVMB48rJKKuA/y9LZ4xESxtW1Ro3G4/fQ2lxuxkecKywddiOmevPwzf4Iif8XuLQlAhezKh+q182Cr9ZGWfzK6LBL/ZhMMp36oJywV/6xJpYUBN2uGXNeRai6eseiJaOcRVzog7I/h3XnoIreYfZQ0ZUCMHtFbZAmu1UGkSdGpgRYgfM5pWllC/515+UsWPAfv/V14or9UP03w1h3hE5crf26IZEsKydsWE4D745w14j9zO8oRlg6/FdMGBGzBorcOdLl4YxovD7pqs0k/u2n8j7SLBb4SapDxWTdhh687B7/tvAgl+SQMXXIzW4im3tohTGnGVM9bOCH70gY+uMTEZCcCjFPxnB1eCOF9HFepUUNBH2H3lEeT1ig8JY4l9LAhVJOFhmq8SIIZRRETlyt/bIukTwp/txQT/01fvoMCwrYxmWDb4WkyV7nSXtPGGEpnE43+YMxs+L9Uq/WRVf6yohwS/FZS/UIdVE5YEvzmDrLV4mlOr/UslrnLG2BnBv+/KY2j2+2HWkLAu/2m1UCn4Lw6tAjGiRdHK4rG/p/lqztBFVK4dlxwH37P3YW7LQlA+m5hJzcs37yH34C2GBf+fR29Dr5WOgHvL2xUF7wyJzBlcCaVapZ8kNNVtiiDB78KhsGrCDl17DuYeuAltSqaD/jVyurDH9qo6ov5BMnsUiascwlzw1y2QCiY0yCd05+TAtcfQZLZD8I+okwuaeotF3FQK/svDq0K0ryLL6ZQblkLz1ZxBiahcA4M+wsOXbyBFvBjCYN+8D4RsAzaxfJMb54dv8ob2sqPFVBlwb+UPxaFg2gTCbbAqg1X6yar+WFEPCX4rKH+hDqsm7JC152DegZvQtmQ66EeCX9qIay2e0iqKYAURVzkD7ozgP+z/BBoGR+w0EnHT9+w96Bjs1tN/ZDWIHDmSnE65YSk0X80ZFOIqzhU/FjL29WUZjdjwK71rrelUAvKmji/eCItyWKWfLOqOJdWQ4LcEc9iVWDVhB685C/MP3oJ2pdJB3+q0wy9ryOkPkiySocshrnK4OiP4j998CvVmHGQNGVM/DzQolFqoUUrB7+5edoQ6FsbDNF+dJRh2fuJqjCt/740IfuXJ3IauJSFnynjGGmFBLqv0kwVdsawKEvyWof68Iqsm7KA1Z2HBwVvQvlR66FM9hwt7bK+q6Q+SOeNJXOVwdUbwn7z1DOpMP8AaMv7bvFCvoJdQo5RuOUnwC6Gjh4MJ0DpgbCo4I/i3XngAbYPd8W7pXhqyJItjrBEW5LJKP1nQFcuqIMFvGWrXCf6Bf5+FhYduQYfS6eF/1Ujwyxpy+oMki2TocoirHK78Dz+3wRfheibgOXwzdT9ryKSG+aB2/lRCjSLBL4SLHg6DgMh8JYCfCPD3Pqz3VovpTr+H0Gqewx3vjp5lIEOS2G6LlgS/+NCQ4BdnJi2HVRN2wN9nYdGhW/BD6fTQmwS/tPHTWjylVRTBCiKucgYco24euf4Uvi2UGqJEjiR0affcnRdQY8o+1pApjfNDTdXlP60WkuDXIkS/1yJA64AWobB/zwX/nO8KgU+O0F5+tJgqvXPt+bkcpEkU01gjLMhllX6yoCuWVUGC3zLUn1dk1YQNEfxl0kPvqrTDL2vItRZPWfVEtHKIqzkjLsL14r1/oOqve1lDpjctANVypxBqFAl+IVz0cBgEROYrAfxEAINnnQl4AWPr5/nssrwW00P+T6BR8GX9A/8rDynji3sKsmosrNJPgcfUPAAAIABJREFUVvXHinpI8FtB+Qt1WDVhB6w+A4sO34aOZTJAr6rZXdhje1WttXjaq7fW9Ya4msNahOvlBy+h0sQ9rCEzmxWEKrmSCzUK/YEXHbkd8njFhz/aFRXK62kPi3D1tL65sr3EVT59LabKy/pH+lWApHG+lt8ISSVapZ8kNdctiiHB78JhsGrC9l99BhaT4Jc+0lqLp/QKI0iBxNWcgRbhevXhv+AzYTdryOzvCkFFlWmAnha++xAEUaNEgkiR7OuSEzmIcNXDjZ5xECCu8meCFlPlZf2TAypCAjeOcm2VfpI/Cq4rkQS/69iDVRO236ozsOTIbehUNgP8XIV2+GUNudbiKaueiFYOcTVnxEW4Xn/8CsqN28UaYiTipzk9cM9SRbi6Zw/cs1XEVf64aDE9dfs51J7muKx/ZnAliPt1VPmNkFSiVfpJUnPdohgS/C4cBqsmbN9Vp2HpkQDoXDYD/ESCX9qIay2e0iqKYAURV3MGXITrrSevofTYnawh81sVhrJZk5rTKBuUKsLVBt21rAvEVT5qLaZKwX9xaBWIES2K/EZIKtEq/SSpuW5RDAl+Fw6DVRO2z8rT8MfRAOhSLgP0rEw7/LKGXGvxlFVPRCuHuJoz4iJcA569hpKjHYJ/UesiUCpzEnMaZYNSRbjaoLuWdYG4yketxVQp+K+MqApRo0SW3whJJVqlnyQ11y2KIcHvwmGwasL+b+VpWHY0ALqWywg9KmdzYY/tVbXW4mmv3lrXG+JqDmsRrvdfvIGio7azhixt4w3FMyU2p1E2KFWEqw26a1kXiKt81FpMlYL/+qhqbn3/xir9JH8UXFciCX7XsbfMhr/3X6dh+bEA6Fo+I/SoRIJf1pBrLZ6y6olo5RBXc0ZchOvDl2+gyAiH4F/erih4Z0hkTqNsUKoIVxt017IuEFf5qLWYKi/ru3uEbBL84vODBL84M2k5rJqwvf86BcuP3YEfy2eE7iT4pY2f1uIpraIIVhBxNWfARbg++fctFBy+jTXkrw7FoFC6hOY0ygalinC1QXct6wJxlY9aD9MJW/wgUezo0KJ4OvkNkFiiVfpJYpNdXhQJfhcOgVUTtteKU/Dn8TvQrUIm6FYxqwt7bK+q9Sye9uqxNb0hruZwFuH6/PU7yDd0K2vIqo7FoUCaBOY0ygalinC1QXct6wJxlY/aTkyt0k/yR8F1JZLgdx17y0x6uODvXiET/EiCX9qI22nxlAZFQkHEVQLEMIoQ4frPm/eQZ/AWVsqaTiUgb+r45jTKBqWKcLVBdy3rAnGVj9pOTEnwi88PEvzizKTlsGrC/rziFKw4fgdI8EsbOlaQnRZPuWScK424OsfvS7lFuL56+wFyDtrMilrfpSTkShXPnEbZoFQRrjbormVdIK7yUduJqVX6Sf4ouK5EEvyuY2/ZDv9Pf56Cv07cgR4+maCrD5n0yBpyOy2espjIKIe4yqD4eRkiXN+8D4RsAzaxQny7loIcKeOa0ygblCrC1QbdtawLxFU+ajsxJcEvPj9I8H+B2YYNG2Do0KFw5swZiBUrFpQuXRpWrVoV8vStW7egU6dOsGPHDogRIwY0adIExo0bB9GiRdM9ClZN2J5/noSVJ+5CT59M0IUEv+7x0XrQTounVl+t/D1xNYe2CNd3H4IgS/+NrCGbu5WGrMnjmNMoG5QqwtUG3bWsC8RVPmo7MbVKP8kfBdeVSII/DPYrV66Etm3bwsiRI6F8+fLw8eNHOHv2LNSvX589HRgYCPny5YMkSZLA+PHj4cmTJ9CiRQuoW7cuTJkyRfdoWjVheyw/CatO3oWfKmaGzhWy6G4fPRg+ATstnu401sTVnNEQ4RoY9BEy9vVlDdnWozRkSkqC/0ujIsLVnJG1Z6nEVf642ompVfpJ/ii4rkQS/Cr2Hz58gHTp0sGQIUOgdevWYY7Mxo0boUaNGnD79m1ImTIle2bZsmXQsmVLePjwIcSNq+/426oJ2335SVhNgl/6W2anxVM6HCcKJK5OwAsnqwhX3ORI38ch+Hf+VBbSJ45lTqNsUKoIVxt017IuEFf5qO3E1Cr9JH8UXFciCX4V+yNHjoC3tzfMnTsXJk+eDPfv32e7+WiukzNnTvb0wIEDYc2aNXD69OmQ3M+ePYOECRMyE59y5crpGlGrJmz3ZSdg9al78HOlzNCpPO3w6xocHQ/ZafHU0V3LHiGu5qAW5Yo7/LjTv+fncpAmUUxzGmWDUkW52qDLlnSBuMrHbCemVukn+aPguhJJ8KvY405948aNIU2aNDBhwgS2249mO1u2bIHLly8zUd+uXTu4ceMG+5kyRY8eHebPn8/yh5Xevn0L+B9POGFTp04Njx8/1n0qYGSq9FxxGtaeeQA9fTJChzIZjRRBecIggIvn1q1boWLFihA1alRiJIkAcZUEUlWMKNccg7fC+8CPsKtnKUgVP4Y5jbJBqaJcbdBlS7pAXOVjthNT1E+JEyeGFy9emKqf5I+C60qMMIJ/8ODBzEwnvHT06FEm6ps2bQqzZs1iwh4TinQvLy8YPnw4tG/fnv385s2bsHmzw20dT3hhd+HChdCoUaMwq/lSG5YuXQoxY5q3g7bsWmQ4/jgSVE8TBGVTfHTdbKOaiQAR8BgCf1yLDE/eAHTMEQSRI3lMs6mhRIAIRAACr1+/Zs5SSPDrH+wII/hxFx3/Cy/hbv7BgwfZRd29e/dCyZIlQx5HMx8fHx8YMWKEYZMeV+3w2+mrXv/UNv9J4moOY+JKXM0hYE6pNF+JqzkE5Jdqp7lKO/zi8yPCCH69aHASJU2aFKZNmxZyaRdfEtzhHzZsGNvd55d2AwICIEWKFKzo5cuXM0897nhp1052e3rH0YrniKs5lIkrcTWHgDml0nwlruYQkF+qneYq2fCLzw8S/GEw69atG/z111/s4m7atGlh7NixsG7dOrh06RIkSJAgxC1nsmTJ2O+ePn3KPPTUrl3bLd1y2uklF5/i5uUgruawJa7E1RwC5pRK85W4mkNAfql2mqsk+MXnBwn+MJjhS9GnTx9YtGgR/Pfff8xrz6RJk0K89GAWDLzVsWPHzwJv4cVdvcmqCWunl1wvWyueI67mUCauxNUcAuaUSvOVuJpDQH6pdpqrVukn+aPguhJJ8LuOPVg1Ye30krtwuD6rmriaMxrElbiaQ8CcUmm+EldzCMgv1U5z1Sr9JH8UXFciCX7XsSfB70L2Mqq20+Ipg4esMoirLJKhyyGuxNUcAuaUSvNVPlc7MSXBLz4/SPCLM5OWw6oJa6eXXBp8CQURVwkQwyiCuBJXcwiYUyrNV+JqDgH5pdpprlqln+SPgutKJMHvOva0w+9C9jKqttPiKYOHrDKIqyyStMNvDkniSlytICC/DjutrST4xecHCX5xZtJyWDVh7fSSS4MvoSDiKgEi7fCbA5G4ElfLCJhTEa2v8rnaialV+kn+KLiuRBL8rmNPO/wuZC+jajstnjJ4yCqDuMoiSTvR5pAkrsTVCgLy67DT2kqCX3x+kOAXZyYth1UT1k4vuTT4EgoirhIg0k60ORCJK3G1jIA5FdH6Kp+rnZhapZ/kj4LrSiTB7zr2tMPvQvYyqrbT4imDh6wyiKsskrQTbQ5J4kpcrSAgvw47ra0k+MXnBwl+cWbSclg1Ye30kkuDL6Eg4ioBIu1EmwORuBJXywiYUxGtr/K52ompVfpJ/ii4rkQS/K5jTzv8LmQvo2o7LZ4yeMgqg7jKIkk70eaQJK7E1QoC8uuw09pKgl98fpDgF2cmLYdVE9ZOL7k0+BIKIq4SINJOtDkQiStxtYyAORXR+iqfq52YWqWf5I+C60okwe869rTD70L2Mqq20+Ipg4esMoirLJK0E20OSeJKXK0gIL8OO62tJPjF5wcJfnFm0nJYNWHt9JJLgy+hIOIqASLtRJsDkbgSV8sImFMRra/yudqJqVX6Sf4ouK5EEvyuY087/C5kL6NqOy2eMnjIKoO4yiJJO9HmkCSuxNUKAvLrsNPaSoJffH6Q4BdnJi2HVRPWTi+5NPgSCiKuEiDSTrQ5EIkrcbWMgDkV0foqn6udmFqln+SPgutKJMHvOva0w+9C9jKqttPiKYOHrDKIqyyStBNtDkniSlytICC/DjutrST4xecHCX5xZtJyvHjxAuLHjw+3b9+GuHHjSitXXRC+5Fu2bIFKlSpB1KhRTasnohVMXM0ZceJKXM0hYE6pNF+JqzkE5Jdqp7mKgj916tTw/PlziBcvnnxYNiyRBL8LBzUgIIBNWEpEgAgQASJABIgAESACYgRww9TLy0ssUwR9mgS/Cwc+KCgI7t69C3HixIFIkSKZ1hL+JWz2SYJpHXDTgomrOQNDXImrOQTMKZXmK3E1h4D8Uu00Vz9+/AgvX76ElClTQuTIkeXDsmGJJPhtOKjqLpGtmzmDTFyJqzkEzCmV5itxNYeAOaXSfJXPlZjKZ+pJJZLg96TRMthWeskNgtPIRlyJqzkEzCmV5itxNYeAOaXSfJXPlZjKZ+pJJZLg96TRMthWeskNgiPBbw444kpcXULAnEppfSWu5hCQXyrNVflMPalEEvyeNFoG2/r27VsYNWoU9OnTB6JHj26wFMqmJkBczZkTxJW4mkPAnFJpvhJXcwjIL5XmqnymnlQiCX5PGi1qKxEgAkSACBABIkAEiAARECRAgl8QGD1OBIgAESACRIAIEAEiQAQ8iQAJfk8aLWorESACRIAIEAEiQASIABEQJECCXxAYPU4EiAARIAJEgAgQASJABDyJAAl+TxotaisRIAJEgAgQASJABIgAERAkQIJfEJi7Pj59+nQYO3Ys3Lt3D3LmzAmTJk2CUqVKfbG5K1euhAEDBsC1a9cgY8aMMGLECKhTp467ds9l7RLhOn/+fGjVqtVnbf3vv//g66+/dlkf3K3iPXv2sLl6/PhxNl9Xr14NtWvXDreZu3fvhh49esD58+dZZMVevXpBhw4d3K1rLmuPKNNdu3ZBuXLlPmvvxYsXIVu2bC7rh7tVjN7NVq1aBZcuXYIYMWJA8eLFYfTo0ZA1a9Zwm0rra/gjaYQrra/ab8eMGTMA/7tx4wZ7GLXAwIEDoWrVqqQFtPHZ/gkS/DYY4uXLl0Pz5s0BxWmJEiVg1qxZMGfOHLhw4QKkSZPmsx4ePHiQfQwMGzaMiXwUXLgo7Nu3D7y9vW1ARE4XRLniH6Qff/wR/Pz8QjUgefLkchpkk1I2btwI+/fvhwIFCkC9evU0Bf/169chV65c0LZtW2jfvj3L27FjR/jjjz9YfkoAoky54Me5Gjdu3BCESZIkgShRohDSYAJVqlSBRo0aQeHCheHDhw/Qr18/OHv2LFtbY8WKFSYnWl+1p48RrrS+anNdt24de38zZcrEHl6wYAHbXDl58iQT/+pEc1WbqZ2eIMFvg9FEkY7iCb/secqePTvbNcWdFHVq2LAhYAAOFAk84QKcIEECJqIoOQiIcsU/SN26dYPnz58TQp0EIkWKpCn4e/fuDWvXrgXcfeYJd/dPnz4N+AeLUmgCephywf/s2TOIHz8+IdRJ4NGjR5A0aVLAE6fSpUuHmYvWV50wFY/p4UrrqzhXzJEwYUIm+lu3bk1awBhC2+Qiwe/hQ/nu3TuIGTMmrFixIpRJDu40nzp1iv1hUifc9e/evTv7j6eJEycyM6CbN296OBE5zTfCFf8gtWnTBlKlSgWBgYGQL18+doqSP39+OY2yYSl6xCkKK2T466+/hhDAU6kGDRrA69evIWrUqDYkY7xLephywZ8uXTp48+YN5MiRA/r37x+mmY/xltgv59WrVyFz5sxslx9PncJKtL6Kj7serrS+inHFv0GoC1q0aMF2+PEdJy0gxtBuT5Pg9/ARvXv3LhOYaOaA9qU8jRw5kh3nqc1L8PfRokUDXDybNGkS8vzSpUuZ/TlG4qMEYITroUOHAP9w5c6dm52goED19fVlO9EoEih9TkCPOM2SJQu0bNkS+vbtG1LAgQMHmPkajlOKFCkIrYKAHqa4LqDdf8GCBdk7v2jRIpg5cybgh8CXdq4jOuSPHz9CrVq1AE9F9u7d+0UctL6KzRS9XGl91ccVP0aLFSvGPuRjx44N+Le9WrVqYWamuaqPqV2eIsHv4SPJhSkKIHzJecJLuPhHHC+bqRO+5Pgx0Lhx45BfLVmyhB354SJB6ZPgF+Gq5hYUFMRMrVBATZ48mbCGQUCPOEXBjx+jffr0CSkBP3BLlizJLv3SHYnQYPUwDWsy1qxZEzAvmk9R+pxAp06dYMOGDeyuk5eXV7iCn9ZX/TNIL1daX/UxxdPpW7duMdNSvDyO9/nwpD+sHX7SAvqY2uUpEvwePpJGTE/oyFl70I1wDatUvGgaEBAQ6r6Edu0R5wk94pRMesTmgx6mYZWImwSLFy8OdVdCrGb7Pt2lSxf4+++/2alI+vTpw+0ora/654EIV1pf9XNVPunj48M88aEzD3WiuWqMqafmIsHvqSOnaDdeLsWjefTSwxN+zePx85cu7b58+ZKZm/CEbrvw8h5d2v0EVpSreirhUXWRIkWYic/cuXNtMNPkd0GPOMVLu+h9Aj2j8PTDDz+wOyp0affzMdHDNKyRrF+/Pjx9+hR27Nghf6A9tER8h1GU4p0RNHfSY5qHl3ZpfQ1/wI1wpfXV2EtUoUIFSJ06NTPjVSeaq8aYemouEvyeOnKKdnP3kWiDi2Y9v/32G8yePZv5LE+bNi189913zM6fi380U8FdU9zRw4+CNWvWsAt75JYz9GQQ5TpkyBAoWrQoEwVow49mPGhWheYnKPwpOQj8+++/7K4DJryMO2HCBHZZFL1J4I4Tmu7cuXMHFi5cyJ7hbjnRJSeemKDIRy895Jbz04wSZYoX9PHCLrrqw9Ms3Nn/5ZdfmAlA3bp1aaoGE0D3r2gDjWuk0vd+vHjxmF9+TLS+ik8XI1xpfdXmjPeccPMOBT5+dC5btoy915s2bYKKFSvSXNVGaOsnSPDbZHhxd3/MmDHMphm9R6DXHX75rmzZsuyPu/IL/6+//mIi39/fPyTwFv2h/3wyiHBFr0cYpOf+/fuAggDF7ODBg0PdrbDJdHOqG18K+oTeJHCO4gVdDByDz/GENqjIlwfewl1/Crz1aRhEmeJagRsD+GGFwhWFP35ofelyn1MD7sGZ8bQkrDRv3jw2TzHR+io+wEa40vqqzRnv4W3fvp3pAPwblCdPHsC1EsU+zVVtfnZ/ggS/3UeY+kcEiAARIAJEgAgQASIQoQmQ4I/Qw0+dJwJEgAgQASJABIgAEbA7ARL8dh9h6h8RIAJEgAgQASJABIhAhCZAgj9CDz91nggQASJABIgAESACRMDuBEjw232EqX9EgAgQASJABIgAESACEZoACf4IPfzUeSJABIgAESACRIAIEAG7EyDBb/cRpv4RASJABIgAESACRIAIRGgCJPgj9PBT54kAESACRIAIEAEiQATsToAEv91HmPpHBIgAESACRIAIEAEiEKEJkOCP0MNPnScCRMDdCWBU0tWrV0Pt2rVZBOL06dPDyZMnIV++fKY0HaMdd+vWDZ4/f25K+VQoESACRIAIWE+ABL/1zKlGIkAELCbQsmVLWLBgAYwaNQr+97//hdT+999/Q506deDjx48Wt0h/dUrBHxgYCI8ePYLEiRPDV199pb8QgSf1CH5skzqVKFEC9u3bJ1ATPUoEiAARIAJWESDBbxVpqocIEAGXEUDBv3z5cvj666/B398fEiRIwNoiQ/C/e/cOokWLZlrflILftEoUBesV/PPmzYMqVaqE5EQGCRMmDLOJ79+/h6hRo1rRfKqDCBABIkAEwiBAgp+mBREgArYngIL/yZMncPXqVahZsyaMGTPmi4J/5cqVMHDgQPZsihQpoEuXLtCzZ88QRunSpYM2bdqw33NTmyFDhjBTG/yomDJlChw7dgxy5coFS5YsgRcvXsAPP/wAly5dgpIlS8KiRYsgSZIkrLyjR49C3759mYkOimI005k4cSIUKFAgpL7wTHr4yYV6AHfu3Ally5YF/Bjp378/awea6GCbRo8ezX7HEwp87O/jx4+hcuXKrI3Dhg0L16QnvI8Q5JI5c2ZYsWIFY3H48GGYPXs2NG/enJ0A9OnTh/FBBvXq1YMRI0ZAzJgxWXPu37/P2G7fvp2xHzlyJPz000/sVKZz586MOZZ99uxZ1hdM2G4sa+/evaztmM6dOwc///wz+1ns2LFZvyZMmACJEiViv8fnChcuDJEjR4a5c+eyD8GOHTvCgAEDQrg8ffoUevXqBevWrYN//vkHMmXKxOYN5sW2LV68mJlZ8YRz4bvvvmN9iBUrlu3fKeogESACnkWABL9njRe1lggQAQMEUBij4G3RogU0adIErly5Al5eXp/t8B8/fhyKFCkCgwcPhoYNG8KBAweYEJw+fTpgGZhQ8D979oyJQy740LwGBX+2bNlg0qRJkCZNGvj++++Z4I4bNy4MHz6cidoGDRqAj48PzJgxg5W1Y8cOuHv3LhQsWJD9//jx42H9+vWsfXHixGE/C0/w48fEf//9F0Lkl19+gT/++ANOnz4NyZMnh6ZNmzK7f/x5ypQp2QcKfgCgYEbhjGK8WLFiTFjXrVsXNm3aBIMGDWImTuHZ8OsR/BkyZGD9yZs3LxPUDx48YGIZ66pWrRr7/06dOjHhjR8EmCpVqgQPHz6EWbNmMTHetWtXOHXqFIwdO1a34L9z5w7kyZOHjVuzZs3g1atXTPxHiRIFtmzZEiL4kQH+HMcZP0RwvHA8ypUrB0FBQVC0aFF4+/Yt6wOO7YULF9hJDn484LP4AblmzZoQ9t988w378Pj9998NzFDKQgSIABEwlwAJfnP5UulEgAi4AQEu+NGEBwVujhw5mDBTm/SgQEYbeS4Msem4y7thwwY4f/58iODPnz8/E8888cu0c+bMgdatW7MfL1u2DBo3bsx2q8uXL89+hsIbd9Rxtz+shDb6aG60dOlSqFGjhqbgV5axatUq9jGzbds2JqyvXbvGRH1AQAAT+zzhBwd+1KDwxufx42Xjxo0hv2/UqBET/lqCH0U8imie+I4334WfOnUqE/Q8YV3Yt2nTpoX8bNeuXewD6PXr12z3PmfOnGz3n38A4U597ty52UmB3h1+PDHBDx4cM/X4IBP8EEE+aGKEJyE84akKfojgx5mvry+ggPfz84OMGTN+NlT4IVimTBnGNlmyZOzjBT8gsT94l4ESESACRMDdCJDgd7cRofYQASIgnYBS8O/Zs4cJ8DNnzsDly5dDXdpF0VerVi22y80T7uJ+++23bCcdBS7u8Ldt2xb69ev3maA8cuQI27HGhGIS68Eda27Cg3bvaB6E5iKY8HdoToM7yygaUfCj+EWxjDvUmPR46UGToFKlSsGvv/4a8sGBJjV4oqA2L8Fda9zNR/Mj/HDBS8vYBp6wDOy/luDHUwoU6zyhmQvWxQX/oUOHwNvbO+T3WbNmZacNSlt+PEnA/uI44HjgR8GbN29Yn3nCExL8ONEr+HEHHtmr71XgTj9+yFWsWJEJfvyowL7yVL16dUiVKhX89ttvrD78IMQPhC8lNCnCeYUmR3gCgc9/6UNO+oSmAokAESACggRI8AsCo8eJABHwPAJKwY+tR3GHwhN/rvTSE5YAxlMAFM5KwY9uK/E/nsJyl4m7vWgegjvo8ePHZ4+qL8TijjKeKOAdgLRp00L06NHZCQR+TPDytQQ/2ozjRwaKeKWARUGPJxZ4MqHcicd2oF07mvzgnQHMZ0Tw8/sL6tkQlp09PoOnDXh/gn/IKPOhCdTatWuZCQ5yVgp+NG1C70oo+PHCNe6448cB7vxjunfvHjvB4Db8KOjxJAFFuzrhc2hahYIfTXbGjRsX8gieqCATPKXBexT40RWe4Mdn8FnkiycTaL/fu3dvz3s5qMVEgAhECAIk+CPEMFMniUDEJqAW/CgYUdzjbjvuznK3nF8y6UETDzQvwYQ7/LIEP4pZvB+AF1ox3b59m9n/o5jUI/hxNxxNS3AXHM1wlMIed81xVx1PNHD3P6yEO+q4k4/94wnNkNDER2uHX1Two608lrl58+Yw24I28iic8R4Fv7SMYhp30rlJz7///svuNmAZaO+PCduKH05c8KPoxnsQOMbqDx1esZbgRzMsPCn4kkkPloM2/PgBgfOnR48ebOzwlIMSESACRMAdCZDgd8dRoTYRASIglYBa8GPhuCOLZi8omrngP3HiBNst55d2Dx48yDzsqC/tyhL8+NGB5j64M4+eYPASKdqw4+60HsGPl5C3bt3K7glwV6PYN3SPiSYtuGO+f/9+dvEU60KPNmg+hLvjKJLR7KZ48eLsbgFeQEaTF7yMLOPSrtKTDrYJL9/irnq7du2Y2RHutKPIx/bwkwncnUchPXPmTHZp98cffwQcE35pF8vB8cETChwTNIPizLjgR7t6PLmoUKECM7dBFnjqgJeZ8YQFk5bgx2dKly7NPCwhOzxVuHjxIot9wD808Bn8iMETIPwZevOhRASIABFwVwIk+N11ZKhdRIAISCMQluC/efMm2wFHm3Zl4C3ulhM95XC3nCgceZK5w4+29yiAURzjzj53Q6n8oAjPpAfbgv1QJ+6WE1194iXUhQsXAnqvQbeUaDKEJkTcJAbdUqLNPgpttMnHEwMZbjnVgh/biF6B0EsQfkhhv1BI44kCN4VB8xz8GMCPADSvQR54aZq75cQycNcfn8EdfPSKhOY+GA9A6ZYTd+YxD3JAT0loLlW1alXmmlOv4MePIxx3FPJ4zwBNktAtpzL2AH4g4UkAXphG0zBKRIAIEAF3JUCC311HhtpFBIgAESACzPuNUvC7ExKM3owfJHiqQIHF3GlkqC1EgAioCZDgpzlBBIgAESACbkvAHQU/7vjjBWL03oQXuvHEhBIRIAJEwJ0JkOBEmmV+AAACpklEQVR359GhthEBIkAEIjgBdxT8aJbEIxajDT9F1o3gk5S6TwQ8gAAJfg8YJGoiESACRIAIEAEiQASIABEwSoAEv1FylI8IEAEiQASIABEgAkSACHgAARL8HjBI1EQiQASIABEgAkSACBABImCUAAl+o+QoHxEgAkSACBABIkAEiAAR8AACJPg9YJCoiUSACBABIkAEiAARIAJEwCgBEvxGyVE+IkAEiAARIAJEgAgQASLgAQRI8HvAIFETiQARIAJEgAgQASJABIiAUQIk+I2So3xEgAgQASJABIgAESACRMADCJDg94BBoiYSASJABIgAESACRIAIEAGjBEjwGyVH+YgAESACRIAIEAEiQASIgAcQIMHvAYNETSQCRIAIEAEiQASIABEgAkYJkOA3So7yEQEiQASIABEgAkSACBABDyBAgt8DBomaSASIABEgAkSACBABIkAEjBIgwW+UHOUjAkSACBABIkAEiAARIAIeQIAEvwcMEjWRCBABIkAEiAARIAJEgAgYJUCC3yg5ykcEiAARIAJEgAgQASJABDyAAAl+DxgkaiIRIAJEgAgQASJABIgAETBKgAS/UXKUjwgQASJABIgAESACRIAIeAABEvweMEjURCJABIgAESACRIAIEAEiYJQACX6j5CgfESACRIAIEAEiQASIABHwAAIk+D1gkKiJRIAIEAEiQASIABEgAkTAKAES/EbJUT4iQASIABEgAkSACBABIuABBEjwe8AgUROJABEgAkSACBABIkAEiIBRAiT4jZKjfESACBABIkAEiAARIAJEwAMIkOD3gEGiJhIBIkAEiAARIAJEgAgQAaMESPAbJUf5iAARIAJEgAgQASJABIiABxAgwe8Bg0RNJAJEgAgQASJABIgAESACRgn8H1bh32ymfsZJAAAAAElFTkSuQmCC\" width=\"764\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "L2Dozqlb4z84",
"colab_type": "text"
},
"source": [
"The plot shows the magnitude of the frequency spectrum of our signal. Observe that the frequency axis (horizontal) is a *normalized* frequency, normalized to the Nyquist frequency as $\\pi$, in our case 22050 Hz. Hence our sinusoid should appear as a peak at normalized frequency 400.0/22050*pi=0.05699, which we indeed see.\n",
" \n",
"Now we can compare this to our signal with the zeros, sdu:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "GdYhcqQg4z85",
"colab_type": "code",
"colab": {},
"outputId": "31850d5b-76da-423b-99b9-85858add49c4"
},
"source": [
"plt.figure(figsize=(10,8))\n",
"w,H=freqz(s)\n",
"plt.plot(w, 20*np.log10(abs(H)+1e-3))\n",
"plt.xlabel('Normalized Frequency')\n",
"plt.ylabel('dB')\n",
"plt.title('Magnitude Frequency Response')\n",
"\n",
"w,H=freqz(sdu)\n",
"plt.plot(w, 20*np.log10(abs(H)+1e-3))\n",
"plt.legend(('Original Sinusoid','Sampled Sinusoid with Zeros'))\n",
"plt.grid();"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option);\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"text/html": [
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width=\"858\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "M5421xO_4z87",
"colab_type": "text"
},
"source": [
"Here we can see the original line of our 400 Hz tone, and now also the 7 new aliasing components. Observe that always 2 aliasing components are close together. This is because the original 400 Hz tone also has a spectral peak at the negative frequencies, at -400 Hz, or at normalized frequency -0.05699.\n",
"\n",
"Now also listen to the signal with the zeros:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "1fCrD2P24z88",
"colab_type": "code",
"colab": {},
"outputId": "297033ca-49c1-4665-8a91-eadea7466bb8"
},
"source": [
"ipd.Audio(sdu,rate=44100)"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"\n",
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type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
],
"text/plain": [
"<IPython.lib.display.Audio object>"
]
},
"metadata": {
"tags": []
},
"execution_count": 26
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "9v-z5w-s4z8_",
"colab_type": "text"
},
"source": [
"### Real-Time Python Example"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "D-LaGr_94z9A",
"colab_type": "text"
},
"source": [
"Here you can hear that it sounds quite different from the original, because of the strong aliasing components!\n",
" \n",
"**Python** real time audio **example**: This example takes the microphone input and samples it, without removing the zeros, and plays it back the the speaker in real time.\n",
"\n",
"It constructs a unit pulse train, with a 1 at every N'th sample, using the modulus function „%“, \n",
"\n",
"```s=(np.arange(0,CHUNK)%N)==0```"
]
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "onmXvGph4z9A",
"colab_type": "code",
"colab": {},
"outputId": "b0723d44-adc5-49a9-fd4b-7087e914afdf"
},
"source": [
"%%html\n",
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/hbIQOeD4N2k\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/hbIQOeD4N2k\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "nruLk4L_4z9D",
"colab_type": "code",
"colab": {
"referenced_widgets": [
"58af0e2b243b46b8beb32885f671b62b",
"85e6d70dffce42e6a4aa4b78d1ea1b06"
]
},
"outputId": "af09f9a3-c46e-4909-b75b-22a72a040dfd"
},
"source": [
"\"\"\"\n",
"PyAudio Example: Make a sampling between input and output \n",
"(i.e., record a few samples, multiply them with a unit pulse train,\n",
"and play them back immediately).\n",
"Using block-wise processing instead of a for loop\n",
"Gerald Schuller, Octtober 2014\n",
"\n",
"Updated and Ported to Jupyter Notebooks by: Renato Profeta, November 2019\n",
"Using PyAudio Callback Mode, Matplolib\n",
"\"\"\"\n",
"\n",
"import time\n",
"import numpy as np\n",
"from pyaudio import PyAudio, paFloat32, paContinue, paInt16, paComplete\n",
"from ipywidgets import ToggleButton, Checkbox\n",
"import threading\n",
"\n",
"sampling_on=False\n",
"\n",
"button_stop= ToggleButton(description='Stop')\n",
"box_sampling = Checkbox(False, description='Downsampling with Zeros')\n",
"\n",
"def on_button_stop(change):\n",
" if change['new']==True:\n",
" stream.stop_stream()\n",
" stream.close()\n",
" pa.terminate()\n",
" button_stop.disabled=True\n",
" print('PyAudio terminated...')\n",
"button_stop.observe(on_button_stop, 'value')\n",
"display(button_stop)\n",
"\n",
"def box_sampling_changed(box_sampling):\n",
" global SamplingOn\n",
" if box_sampling['new']: \n",
" SamplingOn=True\n",
" else:\n",
" SamplingOn=False \n",
"box_sampling.observe(box_sampling_changed, names='value')\n",
"display(box_sampling)\n",
"\n",
"N=8\n",
"s=(np.arange(0,1024)%N)==0\n",
"SamplingOn=False\n",
"\n",
"\n",
"def callback(in_data, frame_count, time_info, flag):\n",
" global SamplingOn\n",
" audio_data = np.frombuffer(in_data, dtype=np.int16)\n",
" audio_data_s = audio_data\n",
" if SamplingOn:\n",
" audio_data_s=audio_data*s\n",
" if button_stop.value==True:\n",
" return (audio_data_s, paComplete)\n",
" return (audio_data_s, paContinue)\n",
"\n",
"pa = PyAudio()\n",
"\n",
"stream = pa.open(format = paInt16,\n",
" channels = 1,\n",
" rate = 44100,\n",
" output = True,\n",
" input = True,\n",
" frames_per_buffer = 1024,\n",
" stream_callback = callback)\n",
"\n",
"\n",
"def keep_alive(button_stop):\n",
" while stream.is_active():\n",
" if button_stop.value==True:\n",
" break\n",
" time.sleep(0.1)\n",
"\n",
"# Create a Thread for run_spectrogram function\n",
"thread = threading.Thread(target=keep_alive, args=(button_stop,))\n",
"stream.start_stream()\n",
"thread.start()"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "58af0e2b243b46b8beb32885f671b62b",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"ToggleButton(value=False, description='Stop')"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "85e6d70dffce42e6a4aa4b78d1ea1b06",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Checkbox(value=False, description='Downsampling with Zeros')"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"PyAudio terminated...\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "sLmiWjaZ4z9F",
"colab_type": "text"
},
"source": [
"## Removing the Zeros"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "scKzsUxO4z9F",
"colab_type": "text"
},
"source": [
"The final step of downsampling is now to omit the zeros between the samples, to obtain the lower sampling rate. Let's call the signal without the zeros $y(m)$ where the time index m denotes the **lower sampling rate** (as opposed to n, which denotes the higher sampling rate). \n",
"\n",
"In our Python example this is:"
]
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "RFSgMQ4A4z9F",
"colab_type": "code",
"colab": {},
"outputId": "32537ffa-36bc-4833-abbd-a25df6b787ce"
},
"source": [
"%%html\n",
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/XGKfAm1-Mek\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/XGKfAm1-Mek\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "__4hUY1W4z9H",
"colab_type": "code",
"colab": {},
"outputId": "00b4d27f-b302-479d-df0e-8cde95be28ed"
},
"source": [
"sd = sdu[0:44100:8]\n",
"plt.figure(figsize=(10,8))\n",
"plt.stem(sd[0:int(100/8)],linefmt='r',markerfmt='r.', use_line_collection=True, label='Downsampled without zeros')\n",
"plt.legend()\n",
"plt.grid();"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option);\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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": {
"tags": []
}
},
{
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\" width=\"762\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ytABmewr4z9J",
"colab_type": "text"
},
"source": [
"We can now take a look at the spectrum with :"
]
},
{
"cell_type": "code",
"metadata": {
"id": "yPdaSA2W4z9K",
"colab_type": "code",
"colab": {},
"outputId": "a1be4b74-b937-44b3-d692-99514bb78705"
},
"source": [
"w,H=freqz(sd)\n",
"plt.figure(figsize=(10,8))\n",
"plt.plot(w, 20*np.log10(abs(H)+1e-3))\n",
"plt.xlabel('Frequency')\n",
"plt.ylabel('dB')\n",
"plt.title('Magnitude Frequency Response')\n",
"plt.grid()"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option);\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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": [
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}
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\" width=\"773\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Fbrl0xV84z9L",
"colab_type": "text"
},
"source": [
"Observe that the sine signal now appear at normalized frequency of 0.455, a **factor of 8 higher** than before, with the zeros in it, because we **reduced the sampling rate by 8**. \n",
"\n",
"This is because we now have a new Nyquist frequency of 22050/8 now, hence our normalized frequency becomes $400*3.14 / 22050 * 8 \\approx 0.455$. This means removing the zeros scales or stretches our frequency axis.\n",
"\n",
" \n",
"Observe that in our time-domain plot, we only have $100/8 \\approx12$ samples left."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "MqyDFEi74z9M",
"colab_type": "text"
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"source": [
"How are the frequency responses or spectra of $y(m)$ and $x^d(n)$ connected? \n",
"\n",
"We can simply take the Fourier transforms of them,\n",
"\n",
"$$ \\large\n",
"X^d (\\Omega)=\\sum _ {n=- \\infty}^ \\infty x^d (n) \\cdot e^{-j \\Omega n} \n",
"$$\n",
"\n",
"still with the zeros in it. Hence most of the sum contains only zeros. Now we only need to let the sum run over the non-zeros entries (only every Nth entry), by replacing n by mN, and we get\n",
"\n",
"$$ \\large\n",
"X^d (\\Omega)=\\sum _ {n=mN} x^d (n) \\cdot e^{-j \\Omega n} \n",
"$$\n",
"\n",
"for all integer m, now without the zeros. Now we can make the connection to the Fourier transform of y(m), by making the index substitution m for n in the sum,\n",
"\n",
"\n",
"$$ \\large\n",
"X^d (\\Omega)= \\sum _{m=- \\infty} ^ \\infty y(m) \\cdot e^{-j \\Omega \\cdot N m} = Y(\\Omega \\cdot N) \n",
"$$\n",
"\n",
"This is now our result. It shows that the downsampled version (with the removal of the zeros), has the same frequency response, but the frequency variable $\\Omega$ is scaled by the factor N. \n",
"\n",
"For instance, the normalized frequency $\\pi /N$ before downsampling becomes $\\pi$ after removing the zeros! It shows that a small part of the spectrum before downsampling becomes the full usable spectrum after downsampling.\n",
"\n",
"Observe that we don't loose any frequencies this way, because by looking at eq. (1) we see that we obtain multiple copies of the spectrum in steps of $2\\pi /N$, and hence the spectrum already has a periodicity of $2\\pi /N$. This means that the spectrum between $-\\pi/N$ and $\\pi/N$ for instance (we could take any period of length $2\\pi /N$) contains a unique and full part of the spectrum, because the rest is just a periodic continuation. "
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "-qEMAodW4z9M",
"colab_type": "text"
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"source": [
"This can be seen in following pictures,\n",
"\n",
"<center>\n",
" <img src='https://github.com/GuitarsAI/ADSP_Tutorials/blob/master/images/Lecture6-6.PNG?raw=1' width=\"600\" ><br>\n",
" <cite>Figure: The magnitude spectrum of a signal. The 2 boxes symbolize the passband of an ideal bandpass, here a high pass.</cite>\n",
"</center>\n",
"<center>\n",
" <img src='https://github.com/GuitarsAI/ADSP_Tutorials/blob/master/images/Lecture6-8.PNG?raw=1' width=\"600\"><br>\n",
" <cite>Figure: The signal spectrum after passing through the high pass.\n",
" </cite>\n",
"</center>\n",
"<center>\n",
" <img src='https://github.com/GuitarsAI/ADSP_Tutorials/blob/master/images/Lecture6-7.PNG?raw=1' width=\"600\"><br>\n",
" <cite>Figure: Signal spectrum after multiplication with the unit pulse train, for N=2, hence setting every second value to zero (the zeros still in the sequence). Observe that we shift and add the signal by multiples of $2\\pi /2=\\pi$, and in effect we obtain „mirrored“ images of the high frequencies to the low frequencies (since we assume a real valued signal). Observe that the mirrored spectra and the original spectrum don't overlap, which makes reconstruction easy.</cite>\n",
"</center>\n",
"<center>\n",
" <img src='https://github.com/GuitarsAI/ADSP_Tutorials/blob/master/images/Lecture6-9.PNG?raw=1' width=\"600\" ><br>\n",
" <cite>Figure: Signal spectrum after downsampling (removing the zeros) by N (2 in this example). Observe the stretching of the spectrum by a factor of 2. </cite>\n",
"</center>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "PW3kLqwc4z9M",
"colab_type": "text"
},
"source": [
"## Upsampling"
]
},
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"metadata": {
"hide_input": true,
"id": "weiOkO4p4z9N",
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"source": [
"%%html\n",
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/Ow_FOJS82gc\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/Ow_FOJS82gc\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
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"text/plain": [
"<IPython.core.display.HTML object>"
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"metadata": {
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"metadata": {
"id": "y04ZGema4z9P",
"colab_type": "text"
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"source": [
"What is still missing in our system is the upsampling, as the opposite operation of downsampling, for the case where we would like to increase our sampling rate. One of the first (**wrong!**) approaches to upsampling that often comes to mind if we want to do upsampling by a factor of N, is to simply repeat every sample N-1 times. \n",
"\n",
"**But** this is equivalent to first inserting N-1 zeros after each sample, and then filter the resulting sequence by a **low pass** filter with an impulse response of N ones. This is a very special case, and we would like to have a more general case. \n",
"\n",
"In our case, we actually a high pass filter, not a low pass. Hence we assume that we upsample by always first inserting N-1 **zeros** after each sample, and then have some interpolation filter for it (can also be a **high or band pass**, as needed to reconstruct a signal).\n",
"\n",
"Again we take the signal at the lower sampling rate as $y(m)$, with index m for the lower sampling rate, and the signal at the higher sampling rate, with the zeros in it, as $x^d(n)$ with index n for the higher sampling rate. Here we can see that this is simply the reverse operation of the final step of removing the zeros for the downsampling.\n",
"\n",
"Hence we can take our result from downsampling and apply it here:\n",
"\n",
"$$X^d(\\Omega)=Y(\\Omega \\cdot N)$$\n",
"$$or$$\n",
"$$X^d(\\Omega /N)=Y(\\Omega )$$\n",
"\n",
"We are now just coming from y(m), going to the now upsampled signal $x^d(n)$.\n",
"\n",
"For instance if we had the frequency $\\pi$ before upsampling, it becomes $\\pi /2$ for the upsampled signal, if we have N=2. In this way we now get an „extended“ frequency range.\n",
"\n",
"Since we now have again the signal including the zeros, $x^d(n)$, we again have the periodic spectrum, as before, as we progress through the same steps backwards now. We can also see that the result of upsampling is periodic in frequency, because the signal was $2\\pi$ periodic before upsampling anyway, and after upsampling the frequency scale replaces $2\\pi \\cdot N$ by $2\\pi$. "
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "d0s3T4v44z9P",
"colab_type": "text"
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"source": [
"## Reconstruction"
]
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "m-LfxHvp4z9P",
"colab_type": "code",
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"outputId": "6c43a142-c19c-40ad-d359-6527e9508369"
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"source": [
"%%html\n",
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/bIYXoAUISNs\" frameborder=\"0\" allow=\"accelerometer; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/bIYXoAUISNs\" frameborder=\"0\" allow=\"accelerometer; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
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"metadata": {
"tags": []
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{
"cell_type": "markdown",
"metadata": {
"id": "VGuJFU6M4z9U",
"colab_type": "text"
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"source": [
"Observe that if the **aliasing components don't overlap**, we can **perfectly reconstruct** the signal by using a suitable filter. We can make sure that they don't overlap by **filtering** the signal at the **higher sampling rate**, before they can overlap (as we did in our high pass example). If they already overlap at the lower sampling rate, it would be too late to separate the different components, the signal would already be „destroyed“.\n",
"\n",
"We can perfectly reconstruct the high pass signal in our example if we use ideal filters, using upsampling and ideal high pass filtering.\n",
"\n",
"In this way we have for the analysis and synthesis the following picture:\n",
"\n",
"<center>\n",
" <br>\n",
" <img src='https://github.com/GuitarsAI/ADSP_Tutorials/blob/master/images/Lecture6-10.PNG?raw=1'>\n",
"</center>\n",
"\n",
"Observe that we violate the conventional Nyquist criterium, because our high pass passes the high frequencies. But then the sampling mirrors those frequencies to the lower range, such that we can apply the traditional Nyquist sampling theorem. This method is also known as bandpass Nyquist. This is an important principle for filter banks and wavelets. It says that we can perfectly reconstruct a bandpass signal in a filter bank, if we sample with twice the rate as the **bandwidth** of our bandpass signal (assuming ideal filters, to avoid spectral overlap of aliasing components).\n",
"\n",
"In genereal this is true for **complex** filters.<br>\n",
"For **real** valued filters observe that this simple assumption only works if we have bandpass filters which start at frequencies $\\pi/N\\cdot k$(integer k) . Otherwise we could have overlap to the aliased components!\n",
"\n",
"**Example:** We have a real valued bandpass filter which starts its passband at $\\epsilon$ and ends at $\\epsilon+\\pi /N$(since it is real values the the passband also appears at the same negative frequencies, $-\\epsilon$ to $-\\epsilon-\\pi /N$). After multiplication with the unit pulse train, we get one (out of N) aliasing component by shifting the negative passband by $2\\pi /N$ to the positive frequencies, which results in the range of $\\pi / N-\\epsilon$ to $2\\pi /N-\\epsilon$. Hence we have an overlap from $\\pi / N-\\epsilon$ to $\\pi/N+\\epsilon$ and we could not perfectly reconstruct our signal!\n",
"\n",
"Hence, sampling of twice the bandwidth for real valued signals and filters only works if the bandwidth are aligned with $\\pi /N \\cdot k$. What could we do otherwise to avoid overlapping aliasing components? We could simply increase the sampling rate, for instance to twice the usual sampling rate (4 times the bandwidth), to have a \"safety margin\".\n",
"\n",
"Another possibility would be to shift the bandpass signals in frequency, such that they are now aligned with the above mentioned grid.\n",
"\n",
"Observe that this restriction is not needed for complex signals or filter banks. That is also why complex filter banks are used for instance in acoustic echo cancellation, because there the sampling rate can be increased by a certain fraction (less than a factor of 2) to reduce aliasing artifacts, and still have a lower complexity.\n",
"\n",
"<center>\n",
" <br>\n",
" <img src='https://github.com/GuitarsAI/ADSP_Tutorials/blob/master/images/Lecture6-11.PNG?raw=1'>\n",
"</center>\n",
"\n",
"**Summary:** if our band boarders are alligned with multiples of $\\pi/N$ then we can donwsample by N, otherwise we are on the safe side by using N/2 as downsampling rate for real valued signals. For complex signals we can always downsample by N, regardles of the exact placement of the bandpass filter.\n",
"\n",
"Compare with the standard Nyquist case: here we have a lowpass signal which we downsample and reconstruct:\n",
"<center>\n",
" <img src='https://github.com/GuitarsAI/ADSP_Tutorials/blob/master/images/Lecture6-12.PNG?raw=1'>\n",
"</center>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "WQsCQLI94z9V",
"colab_type": "text"
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"source": [
"## Python Example: Live Spectrogram: Sampling, LP Filtering"
]
},
{
"cell_type": "code",
"metadata": {
"hide_input": true,
"id": "SN6hProM4z9W",
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"source": [
"%%html\n",
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/6WJQ3KCBN7w\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
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"outputs": [
{
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"text/html": [
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/6WJQ3KCBN7w\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
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"text/plain": [
"<IPython.core.display.HTML object>"
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{
"cell_type": "code",
"metadata": {
"id": "EuBXv0rf4z9Z",
"colab_type": "code",
"colab": {}
},
"source": [
"# Imports and Configuration\n",
"\n",
"import pyaudio\n",
"import numpy as np\n",
"import scipy.signal as signal\n",
"import struct\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.mlab import window_hanning,specgram\n",
"from matplotlib.colors import LogNorm\n",
"from matplotlib.ticker import FuncFormatter, MultipleLocator\n",
"from ipywidgets import ToggleButton, Checkbox, Button\n",
"from ipywidgets import HBox, interact\n",
"import threading"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "x43cNPTu4z9e",
"colab_type": "code",
"colab": {}
},
"source": [
"CHUNK_SIZE = 2048 #Blocksize\n",
"CHANNELS = 1 # Audio Channes\n",
"RATE = 32000 #Sampling Rate in Hz\n",
"N=8.0 #Downsampling/Upsampling Rate\n",
"FORMAT = pyaudio.paInt16 #conversion format for PyAudio stream\n",
"NFFT = 1024 #NFFT value for spectrogram\n",
"OVERLAP = 512 #overlap value for spectrogram"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "nGIljmRP4z9g",
"colab_type": "code",
"colab": {}
},
"source": [
"# LP Filter\n",
"[b,a]=signal.iirfilter(8, 1900.0/16000,rp=60,btype='lowpass')\n",
"#Memory for the filter:\n",
"zd=np.zeros(8)\n",
"zu=np.zeros(8)\n",
"LPFilterOn=False"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "9sAiqYjY4z9k",
"colab_type": "code",
"colab": {}
},
"source": [
"# Function to Plot Spetrogram\n",
"SamplingOn=False # Turn Donwsampling/Upsampling On/Off\n",
"ctr=0 # Control for plotting\n",
"def run_spectrogram(toggle_run):\n",
" global zd, zu, ctr, SamplingOn, LPFilterOn\n",
" while(True):\n",
" if toggle_run.value==True:\n",
" break\n",
" \n",
" #Reading from audio input stream into data with block length \"CHUNK\":\n",
" data_stream = stream.read(CHUNK_SIZE)\n",
" shorts = (struct.unpack( 'h' * CHUNK_SIZE, data_stream ));\n",
" samples=np.array(list(shorts),dtype=float);\n",
"\n",
" #start block-wise signal processing:\n",
" #Low pass filter *before downsampling*:\n",
" if LPFilterOn==True:\n",
" [samples,zd]=signal.lfilter(b, a, samples, zi=zd)\n",
"\n",
" #Compute a block/an array of a unit pulse train corresponding a downsampling rate of N:\n",
" #make unit pulse train with modulus function \"%\": \n",
" s=(np.arange(0,CHUNK_SIZE)%N)==0\n",
" #The sampling:\n",
" #multiply the signal with the unit pulse train:\n",
" if SamplingOn == True:\n",
" samples=samples*s;\n",
"\n",
"\n",
" #Lowpass filtering *after upsampling*:\n",
" #filter function:\n",
" if LPFilterOn==True:\n",
" [samples,zu]=signal.lfilter(b, a, samples, zi=zu)\n",
"\n",
" #end signal processing\n",
"\n",
" #play out samples:\n",
" samples=np.clip(samples, -32000,32000)\n",
" samples=samples.astype(int)\n",
" #converting from short integers to a stream of bytes in \"data\":\n",
" data=struct.pack('h' * len(samples), *samples);\n",
" #Writing data back to audio output stream: \n",
" stream.write(data, CHUNK_SIZE)\n",
"\n",
" # Update Plot\n",
" if (ctr%4 ==0):\n",
" arr2D,freqs,bins = specgram(samples,window=window_hanning,\n",
" Fs = RATE,NFFT=NFFT,noverlap=OVERLAP)\n",
" im_data = im.get_array()\n",
" if ctr < 16:\n",
" im_data = np.hstack((im_data,arr2D))\n",
" im.set_array(im_data)\n",
" else:\n",
" keep_block = arr2D.shape[1]*(16 - 1)\n",
" im_data = np.delete(im_data,np.s_[:-keep_block],1)\n",
" im_data = np.hstack((im_data,arr2D))\n",
" im.set_array(im_data)\n",
" fig.canvas.draw()\n",
" ctr+=1"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "kFDJ_Tqz4z9n",
"colab_type": "code",
"colab": {}
},
"source": [
"# GUI\n",
"toggle_run = ToggleButton(description='Stop')\n",
"button_start= Button(description='Start')\n",
"box_sampling = Checkbox(False, description='Downsampling/Upsampling')\n",
"box_LPFilter = Checkbox(False, description='LP Filters')\n",
"\n",
"def start_button(button_start):\n",
" thread.start()\n",
" button_start.disabled=True\n",
"button_start.on_click(start_button)\n",
"\n",
"\n",
"def on_click_toggle_run(change):\n",
" if change['new']==False:\n",
" stream.stop_stream()\n",
" stream.close()\n",
" p.terminate()\n",
" plt.close()\n",
"toggle_run.observe(on_click_toggle_run, 'value')\n",
"\n",
"def box_samping_changed(box_sampling):\n",
" global SamplingOn\n",
" if box_sampling['new']: \n",
" SamplingOn=True\n",
" else:\n",
" SamplingOn=False \n",
"box_sampling.observe(box_samping_changed, names='value')\n",
"\n",
"def box_LPFilter_changed(box_LPFilter):\n",
" global LPFilterOn\n",
" if box_LPFilter['new']: \n",
" LPFilterOn=True\n",
" else:\n",
" LPFilterOn=False \n",
"box_LPFilter.observe(box_LPFilter_changed, names='value')\n",
"\n",
"box_buttons = HBox([button_start,toggle_run])\n",
"box_checkbox = HBox([box_sampling,box_LPFilter])"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "voRW9wbz4z9o",
"colab_type": "code",
"colab": {}
},
"source": [
"# Create a Thread for run_spectrogram function\n",
"thread = threading.Thread(target=run_spectrogram, args=(toggle_run,))"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "4F1vJTAQ4z9q",
"colab_type": "code",
"colab": {}
},
"source": [
"# Start Audio Stream\n",
"# Create \n",
"p = pyaudio.PyAudio()\n",
" \n",
"stream = p.open(format=FORMAT,\n",
" channels=CHANNELS,\n",
" rate=RATE,\n",
" input=True,\n",
" output=True,\n",
" frames_per_buffer=CHUNK_SIZE)\n",
"\n",
"\n",
"\n",
"input_data = stream.read(CHUNK_SIZE)\n",
"samples = np.frombuffer(input_data,np.int16)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "AM46-UOj4z9s",
"colab_type": "code",
"colab": {
"referenced_widgets": [
"e1e25ba72c6a4321bcef7f3aecc60a29",
"621d72d9ceb64f6b9f572825a27fda66"
]
},
"outputId": "bf53c828-1f1b-42fe-9e6b-9a3c136750fd"
},
"source": [
"# Initialize Plot and Display GUI\n",
"\n",
"display(box_buttons)\n",
"display(box_checkbox)\n",
"\n",
"fig, ax = plt.subplots()\n",
"arr2D,freqs,bins = specgram(samples,window=window_hanning,\n",
" Fs = RATE,NFFT=NFFT,noverlap=OVERLAP)\n",
"\n",
"\n",
"extent = (bins[0],bins[-1]*32,freqs[-1],freqs[0])\n",
"im = plt.imshow(arr2D,aspect='auto',extent = extent,interpolation=\"none\",\n",
" norm = LogNorm(vmin=.01,vmax=1))\n",
"plt.xlabel('Time')\n",
"plt.ylabel('Frequency (Hz)')\n",
"plt.title('Live Spectogram')\n",
"plt.gca().invert_yaxis()\n",
"plt.xticks([])\n",
"\n",
"def handle_close(evt):\n",
" # When everything done, release the capture\n",
" stream.stop_stream()\n",
" stream.close()\n",
" p.terminate()\n",
" plt.close()\n",
"plt.connect('close_event', handle_close);"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "e1e25ba72c6a4321bcef7f3aecc60a29",
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"text/plain": [
"HBox(children=(Button(description='Start', style=ButtonStyle()), ToggleButton(value=False, description='Stop')…"
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"HBox(children=(Checkbox(value=False, description='Downsampling/Upsampling'), Checkbox(value=False, description…"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option);\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>');\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" 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": {
"tags": []
}
},
{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "mTAIrsGQ4z9v",
"colab_type": "code",
"colab": {}
},
"source": [
""
],
"execution_count": null,
"outputs": []
}
]
}