{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Dependencies\n",
"==============="
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[nltk_data] Downloading package timit to /home/boisgera/nltk_data...\n",
"[nltk_data] Package timit is already up-to-date!\n"
]
}
],
"source": [
"from __future__ import division\n",
"\n",
"from IPython.display import *\n",
"\n",
"from numpy import *; seterr(all=\"ignore\")\n",
"from numpy import linalg\n",
"from numpy import random\n",
"\n",
"%matplotlib notebook\n",
"from matplotlib.pyplot import *\n",
"\n",
"import wish\n",
"\n",
"import audio.wave as wave\n",
"from audio.filters import FIR, AR\n",
"import audio.frames\n",
"import audio.index; import nltk; nltk.download(\"timit\")\n",
"from audio.lp import lp\n",
"from audio.quantizers import Quantizer"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"df = 16000\n",
"dt = 1.0 / df"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sandbox\n",
"========"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"FIR\n",
"---"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2.0\n",
"1.0\n",
"[ 0. 7. -3.]\n",
"0.0\n",
"2.0\n",
"[1. 0. 7.]\n",
"[0. 1.]\n"
]
}
],
"source": [
"fir = FIR([1.0])\n",
"print fir(2.0)\n",
"print fir(1.0)\n",
"print fir([0.0, 7.0, -3.0])\n",
"delay = FIR([0.0, 1.0])\n",
"fir = delay\n",
"print fir(2.0)\n",
"print fir(1.0)\n",
"print fir([0.0, 7.0, -3.0])\n",
"print fir.a"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Audio Source (NLTK)\n",
"============="
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"a crab challenged me but a quick stab vanquished him"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"utterances = audio.index.search(type=audio.index.Utterance)\n",
"utterance = utterances[0]\n",
"display(utterance)\n",
"data = utterance.audio\n",
"audio.wave.write(data, \"voice.wav\", df=16000)\n",
"Audio(\"voice.wav\")"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"phone: h# (a crab challenged me but a quick stab vanquished him).\n",
"word: a [q-ey]\n",
"word: crab [kcl-k-r-ae-bcl]\n",
"word: challenged [ch-ae-l-ax-n-dcl-jh-dcl-d]\n",
"phone: epi (a crab challenged me but a quick stab vanquished him).\n",
"word: me [m-iy]\n",
"phone: pau (a crab challenged me but a quick stab vanquished him).\n",
"word: but [b-eh-dx]\n",
"word: a [ix]\n",
"word: quick [kcl-k-w-ih-kcl-k]\n",
"word: stab [s-tcl-t-ae-bcl-b]\n",
"word: vanquished [v-ae-ng-kcl-k-w-ix-sh-tcl-t]\n",
"word: him [hh-ih-m]\n",
"phone: h# (a crab challenged me but a quick stab vanquished him).\n"
]
}
],
"source": [
"for item in utterance:\n",
" print type(item).__name__.lower() + \": \" + str(item)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" 0. bcl (black [bcl-b-l-ae-kcl]).\n",
" 1. bcl (betide [bcl-b-iy-tcl-t-ay-dcl]).\n",
" 2. bcl (be [bcl-b-iy]).\n",
" 3. bcl (both [bcl-b-ow-th]).\n",
" 4. bcl (blues [bcl-b-l-ux-z]).\n",
" 5. bcl (be [bcl-b-ix]).\n",
" 6. bcl (bowl [bcl-b-ow-l]).\n",
" 7. bcl (publicity [p-ax-bcl-b-l-ih-s-ix-dx-iy]).\n",
" 8. bcl (be [bcl-b-iy]).\n",
" 9. bcl (rhubarb [r-uw-bcl-b-aa-r-bcl]).\n",
" 10. bcl (rhubarb [r-uw-bcl-b-aa-r-bcl]).\n",
" 11. bcl (biblical [b-ih-bcl-b-l-ih-kcl-k-el]).\n",
" 12. bcl (maybe [m-ey-bcl-b-iy]).\n",
" 13. bcl (blistered [bcl-b-l-ih-s-tcl-t-axr-dcl]).\n",
" 14. bcl (underbrush [ah-n-axr-bcl-b-r-ah-sh]).\n",
" 15. bcl (arbitrate [q-aa-r-bcl-b-ix-tcl-t-r-ey-tcl-t]).\n",
" 16. bcl (tomboy [tcl-t-aa-m-bcl-b-oy]).\n",
" 17. bcl (brother [bcl-b-r-ah-dh-er]).\n",
" 18. bcl (battery [bcl-b-ae-dx-er-iy]).\n",
" 19. bcl (built [bcl-b-ih-l-tcl]).\n",
" 20. bcl (books [bcl-b-uh-kcl-s]).\n",
" 21. bcl (be [bcl-b-iy]).\n",
" 22. bcl (buy [bcl-b-ay]).\n",
" 23. bcl (about [ax-h-bcl-b-aw-tcl]).\n",
" 24. bcl (honeybees [hv-ah-n-iy-bcl-b-iy-z]).\n",
" 25. bcl (be [bcl-b-iy]).\n",
" 26. bcl (birth [bcl-b-axr-th]).\n",
" 27. bcl (becoming [bcl-b-iy-kcl-k-ah-m-ix-ng]).\n",
" 28. bcl (available [ax-v-ey-l-ax-bcl-b-el]).\n",
" 29. bcl (bequests [bcl-b-iy-kcl-k-w-eh-s]).\n",
" 30. bcl (obstacles [q-aa-bcl-s-tcl-t-ix-kcl-k-el-z]).\n",
" 31. bcl (bluejay [bcl-b-l-ux-dcl-jh-ey]).\n",
" 32. bcl (building [bcl-b-ih-l-dcl-ix-ng]).\n",
" 33. bcl (both [bcl-b-ow-th]).\n",
" 34. bcl (interchangeably [q-ih-n-tcl-t-axr-tcl-ch-ey-n-dcl-jh-ix-bcl-b-l-iy]).\n",
" 35. bcl (able [q-ey-bcl-el]).\n",
" 36. bcl (suburbanites [s-axr-bcl-b-er-bcl-axr-n-ay-tcl-s]).\n",
" 37. bcl (suburbanites [s-axr-bcl-b-er-bcl-axr-n-ay-tcl-s]).\n",
" 38. bcl (valuables [v-ae-y-ix-bcl-b-el-s]).\n",
" 39. bcl (bank [bcl-b-ae-ng-kcl]).\n",
" 40. bcl (impossible [ih-m-pcl-p-aa-s-bcl-b-el]).\n",
" 41. bcl (bureaucracy [bcl-b-y-er-aa-kcl-k-axr-s-iy]).\n",
" 42. bcl (subdued [s-ah-bcl-d-ux-dcl-d]).\n",
" 43. bcl (by [bcl-b-ay]).\n",
" 44. bcl (big [bcl-b-ih-gcl]).\n",
" 45. bcl (bizarre [bcl-b-ix-z-aa-r]).\n",
" 46. bcl (boy [bcl-b-oy]).\n",
" 47. bcl (bought [bcl-b-ao-tcl]).\n",
" 48. bcl (breakfast [bcl-b-r-eh-kcl-k-f-ax-h-s-tcl-t]).\n",
" 49. bcl (you're [y-er-bcl]).\n",
" 50. bcl (crab [kcl-k-r-ae-bcl]).\n",
" 51. bcl (stab [s-tcl-t-ae-bcl-b]).\n",
" 52. bcl (both [bcl-b-ow-th]).\n",
" 53. bcl (be [bcl-b-iy]).\n",
" 54. bcl (blowing [bcl-b-l-ow-ih-ng]).\n",
" 55. bcl (by [bcl-b-ay]).\n",
" 56. bcl (be [bcl-b-iy]).\n",
" 57. bcl (problem [pcl-p-r-aa-bcl-b-l-ax-m]).\n",
" 58. bcl (be [bcl-b-iy]).\n",
" 59. bcl (suburban [s-ix-bcl-b-er-v-ih-n]).\n",
" 60. bcl (gab [gcl-g-ae-bcl]).\n",
" 61. bcl (habit [hv-ae-bcl-b-ih-tcl]).\n",
" 62. bcl (big [bcl-b-ih-gcl]).\n",
" 63. bcl (biology [bcl-b-ay-ax-l-ax-dcl-jh-iy]).\n",
" 64. bcl (celebrates [s-eh-l-ax-bcl-b-r-ey-tcl-s]).\n",
" 65. bcl (born [bcl-b-ao-r-n]).\n"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"audio.index.search(\"bcl\", type=audio.index.Phone)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Short-Term Prediction\n",
"======================"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [],
"source": [
"class STP(Quantizer):\n",
" \"Short-Term Predictor\"\n",
" def __init__(self, order=16, method=\"autocorrelation\"):\n",
" self.fir = FIR(a=r_[1.0, zeros(order)]) \n",
" self.ar = AR(a=zeros(order))\n",
" self.order = order\n",
" self.method = method\n",
" def encode(self, data):\n",
" if self.method == \"covariance\" and self.order >= len(data):\n",
" raise ValueError(\"not enough data samples\")\n",
" a = lp(data, order=self.order, method=self.method)\n",
" self.fir.a[:] = r_[1.0, -a]\n",
" error = self.fir(data)\n",
" return (a, error) \n",
" def decode(self, data):\n",
" a, error = data\n",
" self.ar.a[:] = a\n",
" return self.ar(error)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
"def stp_error(data, T=0.02, order=16, method=\"autocorrelation\"):\n",
" length = len(data)\n",
" n = int(T * df) # number of samples for T s at the given frequency.\n",
" frames = audio.frames.split(data, n, pad=True)\n",
" stp = STP(order=order, method=method)\n",
" error = zeros(n*len(frames))\n",
" for i, frame in enumerate(frames):\n",
" a, error_frame = stp.encode(frame)\n",
" error[i*n:(i+1)*n] = error_frame\n",
" return error[:length]"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('');\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",
" '');\n",
" var titletext = $(\n",
" '');\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 = $('');\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 = $('');\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 = $('');\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 = $('')\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 = $('');\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 = $('');\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 = $('');\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 = $('');\n",
"\n",
" var fmt_picker = $('');\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",
" '', {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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"\");\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('![](\"')
');\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'] = '';\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 = $('')\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 = $('');\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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('');\n",
" var 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= 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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\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"figure() \n",
"n = len(data)\n",
"t = r_[0:n] / df\n",
"plot(t,data, \"k\", alpha=0.1); axis(\"tight\")\n",
"error = stp_error(data)\n",
"plot(t,error, \"r\")\n",
"xlabel(\"time [s]\")\n",
"ylabel(\"amplitude\")\n",
"axis(\"tight\")\n",
"grid()"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SNR 15.446422432113586 dB\n"
]
},
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('');\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",
" '');\n",
" var titletext = $(\n",
" '');\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 = $('');\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 = $('');\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 = $('');\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 = $('')\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 = $('');\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 = $('');\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 = $('');\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 = $('');\n",
"\n",
" var fmt_picker = $('');\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",
" '', {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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"\");\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('');\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'] = '';\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 = $('')\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 = $('');\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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('');\n",
" var 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= 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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RCAXQB2wLbScdZJr+awDLHCwfQKkA1rrOa/PLFUVbW5u0t7czDDFr1iyZPn26knj66aeb8h3mzJlTKMOMGTNk9uzZTc8ro/Q4475hGOO5556T9957T7q6uqSvr4/RwtHV1SXvvfeePPfccyXHSVtbGwXQB+iydqBp+m8ALHWwfAD2AljtOlkD6DBU1gDG4/GG53FwcFBWr15dVI6urq6m57WZ4cVj0q/7xou59GuwBpA1gKwBHL146RGwGbYBtEFlG8BkMllzOWrJ4/DwsGU5Ojs7ay7HaMCLx6S+b6LRaLOLUhVezKVfMeeSbQBrZ2SktjaATl4Dd8YZZ8hxxx3npnglPPLII0WvozPDNoCjg7cB3G+atgTuO4HUuk4dCqANkUjEtwJYrw4pfseLx6Rf940Xc+lXWkEA6yFPVtQqgPF4vOJrOymApFb0IVt+Am3IljugDdkyOf/5TBSL28YAvpqPELQhYb4K4EtVrNMJFEAbVMmf1wRwaGio5rL4HS8ek8Z9k8vlml0cx3gxl36FAuiOVCpV+H+tAugECiBxw/nQavNS0AZtPtTw2TwAMwx/7wiLzhr5+Zyu0wkUQBv8KoCpVKquw9L4GS8ekxRAMloE8Omnn5Y99thDNtlkE5k4caIcccQRMjg4KNdcc03JvezVV1+VVatWCQCZNWuWHHjggTJmzBjZfffd5dVXXy27ncmTJ8v1118vZ5xxhowbN05OP/10ERHp6OiQH/zgBzJ+/HiZOHGiHHvssbJq1arCcq+++qp87Wtfk8985jMyfvx4OeiggyQQCIhI6SPgbDYrv/jFLwrruuyyy+T0008vEsDJkyfLHXfcUVS2vfbaS6655prC37fffrvsscce8pnPfEa22247Oe+88yQejxc+pwCSZkIBtMGvAhiLxSiANnjxmKQAkooCmMuJDA42Jxwek6FQSDbccEOZNm2arFq1ShYuXCj33XefxONxicfjctJJJ8l3vvMdCYfDEg6HJZVKFQRwu+22k2eeeUaWLFkiZ511lmy++eZlH8dOnjxZxo0bJ7feeqssX75cli9fLolEQnbeeWc588wz5fXXX5ePPvpITjnlFNl1110llUpJJpOR8ePHy6WXXiorVqyQJUuWyIwZM2T16tUiUiqAN998s4wfP75Qrp/+9Key+eabVy2Ad9xxh7zyyiuycuVKefnll2XXXXeV8847r/A5BZA0EwqgDRTA0YcXj0kKIKkogIODIkBzYnDQ0XdYsGCBACjUqJmxenyqC+BNN91UmJbJZGS77baTm2++2XZbkydPlilTphRNe/jhh2XXXXct9AIeGRmRVColm266qbz44osSjUYFgMybN89ynWYB3GabbSzLVa0Amnnqqadkiy22KPxNASTNhAJoAwVw9OHFY9K4X4yPhryOF3PpV0aDAGazWTniiCNk8803lxNPPFEeeugh6e3tLXxeTgDnz59fNH3KlCkydepU221NnjxZbrjhhqJp559/vmywwQay2WabFcV6660n999/v4iITJ06VcaMGSNHH3203HnnnRIKhQrLGwWwv7/ftlzVCuArr7wi3/zmN2XbbbeVsWPHyiabbCIAZDCfVwogaSYUQBsogKMPrx2TmUzGt/vGa7n0M6PhEbBWzJy8/vrrcvXVV8tXvvIV2XLLLWXlypUiUr0AnnnmmbbbsRKvc889V/bbbz9ZtmyZLFiwQJYtW1Z4PNzf31+Y77///a/8/ve/lwMPPFDGjh0rb775pojUJoBf+MIXZNq0aUXz7L777gUBDAQCsskmm8jFF18sb775pixbtkwefvhhASB9fX0iQgEkzYUCaINfBdBJeVoVrx2TPT09vt03XsulnxktnUCMZLNZmTRpktx+++0iInL22WfL0UcfXTSPLoDGx72ZTEa23377io+AzQL40EMPyYQJEwpv0HDSC/iAAw6QCy+8UESsHwFblcsogPvtt59cdtllhb9jsZhsuummBQF85plnZMMNNywqy/XXX08BJJ6BAmgDBXD04bVjsrOz07f7xmu59DOjQQDfeustufHGG+Xdd9+V1atXy1NPPSUbb7yxzJ07V0REbrzxRtlhhx1k6dKl0tPTI+l0uiCAO+ywg8yZM0c+/vhjOeecc2Ts2LHS09Njuy0rAdQ7gRx++OHy/PPPy4oVK2TevHny85//XNauXSsrV66UK6+8Uv7zn/9IIBCQF198USZOnFh4PGwWwJtuukkmTJhQKNfZZ59d0gnkyiuvlK233lpee+01WbRokUyZMkXGjh1bEMD3339fAMidd94pn376qcycOVMmTZpEASSegQJoAwVw9OG1Y9JKAOsxflk98Fou/cxoEMAlS5bIkUceKVtuuaWMGTNGdtllF7nnnnsKn3d3d8u3vvUtGTt2bMkwMG1tbbL//vvLxhtvLLvttpu8/PLLZbdlJYAiIuFwWH784x/LFltsIWPGjJGddtpJzj77bInFYtLZ2SlTpkyRbbbZRjbeeGOZPHmyXH311YXzzSyAmUxGLrroIhk3bpx89rOflV/+8pclw8DEYjE56aSTZNy4cbL99tvLjBkzStoATps2TbbZZhvZdNNN5cgjj5SZM2dSAIlnoADaMJoF0C+SoRqvHZNWAuiXV8J5LZe5XE4ymUyzi1ETo0EAa0EXwPfff1/ZOus5EHQzoACSekIBtCAej/tSAEdGRhyVR//12Wp47Zi0EkC/1NB6LZf6qxv9KE0UQAqgHRRAUk8ogBaEQiFfCqDT9xdTAL1xTNoJYFdXV7OLVhGv5dJvAm2EAkgBtIMCSOqJ7wQwHo8XjS9VD/wqgOFwmAJYBq9Ji50ABoPeHxPQS7nMZrO+buLQqgJYDyiAhDjHdwKoQqoqQQEcnXhJWkTKC6DXa7K8lMtoNDoqBTCRSPjq7TBegAJIiHN8JYC5XK5wka/nr2PVAuimNocCqA4vSYsIBVAV5qYP5d4j60WhshLAjz76SGKxmCfy6ycogIQ4xzcCaL45+kkA3dzM6yGAXpeLeuElaRHxnwAa5clLubRq+2pFb2+vBINByWazhWmxWEx6enqaKoZWArho0SKJxWKSSqWaVi4/MtoEcGhoiAJI6oYvBDCdTpdc4AcdvqOyFvwqgI0oj5/xkrSIVN5fXhrWpL+/X4LBdcPUeCmXVgKYSCSK5jH2kB8YGChM16cNDQ01utgFzLnMZrOyaNEi6ezslFQqNWpkphGMNgGMRCKyZMmSoh8tOhRA4hbfCmA9JcaPAmh8PE4BtMZL0mJ3TBujmVJixnzseCmXVgJo7ihmfO3ewMCARKPRoraDoVDI8ibbCKxyuXz58oIExmIxGR4eZjiIRCIhXV1dkkgkml4WNzE0NFSQv1AoZHncUACJWyiAFvhRAJ2OAahHZ2enDAwMNO2m1wy8JC2pVIoCqIhKAmj+caTXZpqjWcPvWOWyq6tLli5dKgsXLpSFCxfK4sWLZcmSJYwKsXjxYnnvvfdGTb5CoZBt8wQKIHELBdCCVhBAPbq7u2sum9/wkrRQANVRSQCtjnm7nDejg5RVLvUay7Vr18rq1aslGo02vVbKDzEwMCDPPfecDAwMNL0sbqPSj3MKIHELBdAC1fLnZQGsZx69hpekxU8CaD62RLyVSzsB7O/vr+nHXKMpJ4CteJ66wUvHZb2hABK3UAAdbosC6H+8dHPwiwBatS0V8VYurXJnHhvQy+eDVS6tailJZbx0XNYbCiBxiy8E0O5mGQ6HlQ/fQAEcvXjp5uAXATS/ZYMCqB6nAtjV1eWL1wQ2Ey8dl/WGAkjc4msBrMcF268CaHWjdhpeEI1G4KWbg18EMJPJ+FIA3URPT09DhxFx+ghYDy/k3Kt46bisNxRA4pZRIYAqawH9KoBdXV01l627u9uTb0hQjZduDn4RQKvBxbPZrGdyOTw8XJfztZGdQZzWABrD6++KbhZeOS4bAQXQX5wPYBWAJIAFAP5fhflPALAEQCr/7/dNn8+AtvON8VaVZaIAmvCrADazjH7BSzcHvwigVbl6e3s9kct6yV8wqNUCNopaBDAY9NZA4V7BC8dlo6AA+oeTAaQBnAVgNwB3AhgEsIPN/AcCyAL4FYAv5//NANjfMM8MAC8A2NoQE6ssFwXQRCwWa1kBTCaTNZfTD3jp5pBIJHwrgJFIxBO5HBgYaGkB9MLx4TW8cFw2Cgqgf3gbwAOmaR8D+IPN/E9Ckzsj/wAwy/D3DADtLstFATRRrxtKrTRSACORSM3l9ANeujk42R/NvsHbdSxqBQF0c85WCwVQHV44LhsFBdAfbAytNs/8CPcuAPNtllkD4Bemab8AsNrw9wwA/QC6AXwC4E8APl+hLGOgHSx6TAJQuKCrjEQiIe3t7ZJIJFyva3BwUAKBgG2kUill5S63HTdRzzx2dnY2vZx+CJXHZCOOs1gs1tQyhkIhy3KFw2FP5DIajdbtfA0EAtLR0SGBQKAu18dKx2UwGPT88eHF8MJx2aiIRCIUQB+wLbSddJBp+q8BLLNZJg3gFNO0U6C1B9Q5GcD3AOwB4BgAHwD4CJrk2XEtStsNSltbm7S3t3s2nn76aZk+fbptPPvss8q2VW47bqJeuXnyySd9UU5G9fvsySefbGo57co1c+bMpuewvb1dZs2aVbfz1RyNvkY++uijnj8+GM2NtrY2CqAP0AXwQNP03wBYarNMGsCPTNNOhdaBxI5t8ssdX2Ye1gBWCL/VAPb09HiinH4Ir9QOhMNhz9cA9vb22parVWoAG3VuWOXSSXnqXTPpx/DCcdmoYA2gP6jXI2ArlgO4ooqysQ2gAau3HjS7PVGlPNq92L7WSCQSNZfV66g8Jt1g9eoyr7Xxshr+pdXaADaqTaA5l056iDe6nWI1mMdQbOQQU144LhsF2wD6h7cB3G+atgTlO4HMNU17AcWdQMxsAa2G8PQqyuULAUwmkw0RwHg87rmbR6MFMBQK1VxWr+OVm4NbAUylUnXtsV1JQLwigI2UPwqgMwYHByUYDMrAwICIrLt2Dw4ONmT7XjguGwUF0D/ow8D8BNowMHdAGwZmcv7zmSiWwYOg1RpeAW0YmCtQPAzMWAC3QXusvCOAwwH8B0AHgM2rKNeoEEBVg6K6lanIY4/J0DHHSOijjyS4cqUEOzoKn6VSqZrKVMjjwIBIb6/yMvvhpqIKr9wc3Aig8UdKf39/XcpX8ThvUQGs17h7o0kAzWULhUJ1K2smkym5rnrhuGwUFEB/cT6AALSOHAsAHGr4bB60Xr1GToTWRjANbcgYY9u+TQG8CK0HcBrao+EZALavskyjQgBVXVzcyFTXyy+LAIXIbbihDB96aOHzXgt5c4Kex9znPqet2zRUSz0EcLQ+BvbKzaHc49VK+6HeAuDkXGtVAaxXLZYbAfTaUDCNFEArOffCcdkoKIDELb4QQCeD5qrAjUwlv/a1IgHUI7hmjRIBLKzzueeUlbne+fQaXrk5uBHxeu8nJ+caBVAtbgQwGFQ7DqpbjOVKp4vfqlTPbXV1dYmId87xRkABJG7xhQA2SljcyFRq330tBXDgZz9TKoDZv/5VWZnLhddqFlTglZtDrQLY19fnCQHs6enxRC6tytb5n/9I7733SnDt2pYRQC+9F7je12gdq9cAinjnHG8EFEDiFgqggXoIoABKBTD2xBPKylwpvFSzoAKv3Byc5t/4Zha7Huq17KNcLme7nBMBDAaDnsil5XUgf5703n57ywigarmqRDabtf2sUWW0Wn82m/XEcdkoKIDELRRAA/UUwGg0WlOZzALY//jjyspcKWqV1mpo5A3MKzeHWm7sdgJYS0cQvV2WlQSOFgFMnHSSbwVwaGiopnO1ET/Y9KF37GodmymAwWBQYrFY04/LRkEBJG5pKQHM5XLS2dlpK2MUwNLIZDJ1vbHU6wZhhRekRUStAHZ2dla1beN6rHqmUwCbL4C1lq+vr68u5TNS6Xx1e412Qrka0kAg0PTjslFQAIlbWkoAje1GrHDyAna7GP4JrFQAACAASURBVK0CqEd3d7fSAbf1dRm3oXKYjWw2K8PDw0XHnxekRaQ2ARwZGbH8vFoBzGQy645ZDwlgLceWZb50ATzxRAkvXChdL78swRUrlJwDXhdAvYz1+sFm7iFuhdtrtBPKbSMQCMicOXOafo43AgogcYtvBLD33nulZ/ZsVxcX46MVu+3UGvUUwLa2tsK6oo8+WvR5owRQD7c3F70GSh9w2rhuVQJolhj9zQSjUQCrvbEaBdBqMOlmCKBRLHK5nOPjwDIXFudf6itfUXLs16uzhUoBDAYbNz6k1b53ciyrLocxAoGATJ8+vebrrZ+gABK3+EIAu/71ryKZqvXiUml+Nxfdegrg9OnTC+uKzJhR9HmJAHZ0SPdf/yqhRYuU3PTMoQ+3UCvGoSHMOVclgJ2dnUXrDYVCMjIyMmoFsJq8GQXQqo2nWQCjDz8syYMPluif/yzBQKDo5l+PGv6enh4JBp31QrfMl905aBiU3U3UA9UCWK9yOtlOuTLFYjEltZPltqELYCAQcL0dr0MBJG7xhQBGZszwvADa3XhUC2D0gQeKPjcLYGTmTBFARjbfXMLvv6/duFevls633pKBiy+Wztdea+rNpRkCaAz95jA8PKxkW7VQS67LCWA1r4UzCqDVMWkWQONxPHj66YXpbs9v4762+k4R04DnVlRzHvZfdZVnxaoeAliup24t2B1/OrlcznJoFnPor4hzQ7n1GwVwtI1iYIYCSNxCAbT5vJoIf/BBwwQwM2lS0edmARz88Y8L84589rMlZRnZZBPXNxc376FthAA6uTkEg1otk+obpZvylTuu9d6XbveHUfCsjklzD1S7mrRaz2/j/tcfqVp9p3ICmEqlbB9VlzsPQ4sXS2jFCgmuXl3zsV8PKgpgR4d0vv66pPbZp0jCy0W1bUMrYbcdvXmF0/bTbkcWsOsMZXeOj2YogMQt/hDARx+tKIBO5KHShbzWm0L0gQfK3nh677vPUY2GFWYB1HOgY36tWGrvvcuWpVwO63Uj7O/vl3A4LNlstkgwzI3KVQhguZoy881Bj76+vrq959WKavNcaVy4agTQuJzVMVlJALvb2yUYrCyA2WxWOjs7SzpOdHV1lZTd6juVO1/s8hBavLjscR/9059EAEl/8YsNOe6dUkkABy68sOh7dP3znw0vq902uru7y35uDrcCWO6HkNU53uzmHvWEAkjc4g8BzD/WLCcvlb6DWQysqPZmEFq+XGKXXFJRuMzSVg12Aqi3kSq56Dssi9uo5vFKo24OIsWPOCvdHKqRDpVUKxyVxoWrZviPSt+3kgD2PPVU4cZa7vyORqOW51q5x/NO94XdMkPHHuvo+HdzDtSDSgJoVf7YpZdKuEI7X5VU2o6SczwaFalwXbF6G06lc7we9zcvQAEkbhk1Alip51t/f790zZ8vkUcekWBw3aMLnUqPFoqio0OGjjzS8c3GjQAODw9bCqDeGcPJzaIeAqj/8neC03WGw+GSZasdh9CNANbrBm8km81WLRxOBgZ2inGZegpgJBKxLJtTAezp6XH0HYyR3XrrmgQwvGCBDFxwgXS++aayPFdDLQIogOTGjGlYWSttx+nx3NPTI/39/aU17m+8oX2vk06yLYOTN6TYnePRaHTUtQmkABK3+EMAH3+8cNELf/hhoQ1P7JJLpO+WWyQYrCyAXV1d625is2eXtP2KxWKOLmChZcskcfLJVcmfANL52mtVf2/9gmcWwOFvfEP6r7tORGoUQBdtoIxhlmg7nK5PHxpGR29UXk4GzLgVQD3ctHMsh+13X7xY0rvtVtLGS6R+Ami1nHFbna+9VnLsDB1zjASDlQXQahvVDllkd13qbm+XvltvLZk/t/HG1QvgmjWSGzNGBFr72sjMmTL07W9L+IMPXOW5GiwF8NNPJfrHP0ryoINq/jGnosOFTqVjr9prR8mPvSlT1n0vG5y0M6x0jluNfelXKIDELf4QwCeeKLropb/0pZKhYSoJYDC4To76f/c7yWazEovFCm3T9OEnKkX8pz+tWv4E0DpnVIHeWF6/oFmt00oMnJSl7/e/r/qC7egiXib3TqNov9vUIpXDuEy1N4dG3OzttjUyfnzxjxxDGZz0rqx1++ZakcHBwcJng6eeaisdqVTKsQBaDfpdy/FQQP8h9/TThfkqtf8zR/fzz0ukrU1yG2xg+XliypSGHRNWAuj0OtOoY7jSNlzv2xoFsP/aayW9884Sfv99x+f4aKkJpAASt/hSAPWaCLcCWLiI9Pc7EsCe2bNrkj8BZPC006r6znovx0AgII/adDKxvKg6KcvUqcrGRSvXi3ZoaKiskFW6KdQigOXW7UkB7OiQgV/8omj/hBcsKCpDIwXQybEUDASkq6vLmQB2dBTeU+taEnT0HzL52v9gMCgjY8fWfG5aReYLX5Duv/2t0GSknseElQBmJ070jQCWbdawenVBzsqVLWO4ntthJYAFYT/hBMfneKPa+tYbCiBxiz8E0PAmDLuLYL0EMHbFFTJ4yinSd+ONrm4otQpgx8svV3Xxd1qe7DbbSGjx4ppuysYo96g0uHKlhN97r3iZtWulZ/ZsCS1bJsFgUPpuuEFS++5buNEW7fcmC2A93qhgXH/PX/5iuW965swp+t7NEECrx7+F8+f66yu+czUYDMrQkUdqPW4//bTm48sSCwFUKX/m6HzjjcJ26tFb3I0AhpYsUXJcVKLcNsr9eE5+7WsigHTPnVvymfERdfrrXy98J7umJWYBDC1bVnxcXnedBFatcnSOjwYogMQtLSmA6d12K7qpWgrgmjXS/9vfKruJVCuAennSO+3kWABDy5dXVabYlVe6FsByF9PM5MkigHTNm7cu19ddJwJIas89Jbh2bfHN7OOPi/d7UHvE0zV/vuPx+lQKYD1uFL133y2x3/ymorQ0SgDNA2IXRKfMcTd4xhkVBdA4NFL04Yety+2gLarl4zpdAA3tAOspgHrHl2DQebOHarASwGrKN3TssdLT3i6d//53Sf6cvFGlEpU6LpXr2FM4Zn78Y9vjNpvNlhz7Vj8szQJolYv4SSc5OsdHw2NgCiBxiz8EcNYs1wJolshgMKg9Bg0EJBqNlghg77RpSm8ig6edVlUDZCc3tqIbaEdH1WVSJYC2cmaxnfTuuxemmweqDr/3XtGFOXHFFevyZxpPrlLeVAmgyob0xpxUqlGOPvjgOgEcGpLB004riKNKAezv75dUKlWodSncINdf35UAjmy2WWH+3rvukmAwKLHf/Eb6r7uu8P/cBhtI91//Wr3cNlgABSiSK9WYr5Vd8+fXXM7gmjVFuUskEq7L19vbW3Ef9d14oyQPOUS6Xn7ZUtJSe+1lu2/N+y/8zjuWA1k7EUAB5JE//7niOV7N0ElehQJI3OILARz69rddC+DwYYeVLJM47jgR5F8TZbpgxM89V60AnnpqVTePUCgk3XPnll1nz+zZhfIm99+/pnL1zJnjuj2gbZsalApgubLoj4t1UocfXrS/yr2+LZ1OV2zHWRDApUur+n5Kew5WsW/C77wjIiKDDz9cmDZ0zDHS8+yzygTQ6mZcSQAFqCiA5ZY1dnDI7LijDFx8cWGA6WoFsPPtt5Wep3ZhHDy6VnKplAzeeqsMvf9+0XTztbL3rrtqLmdw5cqi3Dm9tuudf6yGdzKO6WgVXS+9VHxNefJJy/M9ceKJjgRQAIk88kjJ43ajAIbfe69sHvr/7/+k+/nnbcus+k0pzYACSNziCwGseNFzcGEeNrQx0ZcpumD89reF9bjp7FGpnE7pfvXViuvreeYZCa5Y4VpW7Xo8VhPlHtXFrrxSgp9+Kj0VanL1zg/6MZMySHv6i1+U/hUrSverg8ejRgGce/nl2nc+/ngJdnRIaPlyR8sqo4r90tPebrvM8Le+VVQ+/bVqlQgGgxIMBLQetCZZMA6WXk8BLBeZ7bYraZtqJJ1O1+XcdBKxX/1Kk48aHwMPG2t9Td9Jz2Uul5PeO++suYy9995b07FrnN/82LiSAA4ddVRJOYaOPloy225bMl1v+1tJAJP7719S628UwPSXvuQoH/r8oSVLLLftZyiAxC2eF8BMJlPxJNdrD8piWia1777FN9Qjjqh6KIlqo5qLTt8NN1RcX3qXXZSVTX80V2t0dnZKPB4vromtsgyd8+cXXZzNr7WLn3NOSZ5sy7RqlfTddJOk9t5bMjvuKENHHSUpw+Pnou2+807F76esFrCKfPQ8/XTZZWq50RubNiSmTJHgmjUSXrhQgkFDb04HzQnqJYBW381IJByu6znqtFzVjE2pk/zudwvryeVyMjw8LNlstuhaGY/HKz7xcBKRWbNqFkDz05SCAK5eLYnjjiu5VlQz/mJ2q62k8803CzKWSqWk89//tpx3cPVqyzJGH3zQ+fYmTJCYoSmJ8WmH39sBUgCJW0aFAA6cf37VAtjMm4cTsltu2fDyDVxwQdEFMrR8ucQuu0wSJ5wg8fPOk9DHHzsWwpGRkaq3n9p336LlzW0EEyecUJInq20njj++uu3+7/9KdPp0Cf/3v/WtBTQ1dq9Yrr331m5SNp/rzQqqKp9pHXovza4XX9T2ualnpV3UWwCNPaGNvUIHr7mm4eeFMUIffWRZLickDWIXWrFCBn7+c+mZO7foWhmLxZSV1XhsVHoThvlYz2QyhSYXugD23nNPYd3Dhx5aeHOK2/Kld97Zdp7uNWsKQhpetEgGLrrIXU5MTX38LIEUQP9xPoBVAJIAFgD4fxXmPwHAEgCp/L/fN32+HoBrAYQADAOYB+B/qiiP5wXQ6SOfrnnzyq+oiTcNPTpff73wC7u7u7tsm7ZmlTG9yy4S/eMfLcdeFED6r7lGE0EH7QZrLUPv3XdLeNWqkum5MWMkmUwWXbRLaiJdNKAXaI+eRsaN0wbLNj0idU0iUX0u3nmn4jzdf/tbzQJojNillzru+R5YtUrmzJlTNwEUQAYuvFCCHR1FNVKpb3yjaeeGAJI85JAiqaoGYwcoo8jUSwB777mn5PxwMnC3XQyedlrJNnra212da5WuE+kvf1nC77wj4XBYhgw1qLVGau+9K/7QCwbr9yYglVAA/cXJANIAzgKwG4A7AQwC2MFm/gMBZAH8CsCX8/9mAOxvmOcKAAMAjgewB4C/QJPBzR2WadQIoAAiIta/6MrUojQysp/7XMmFxvYXqAfK6ySGjjlGetrbS3ofhhcscLXewVNOsZxuvPHqb0tRIZ12obcVVHFTyA0P120/BD/91FkhFG0vetVV8vjjj9dVAAWQkc031x5J5zF2DGpWGMe21Nvtucm98VrZ39+v9riwkBu9jV8ulyuUPXr//ZLZaSfpu+027fx9912tacDatZqE16nmtdY3K9UjL3Wp9a8jFEB/8TaAB0zTPgbwB5v5nwTwgmnaPwDMyv9/PQBhaBKoMwZAP4D/c1imughgrq9PUgsXyt8ff1yGli6VbCAguUhEcqGQ5Lq6JLdypeRWr5bsJ59I8q23ZPiTTyS5eLEkP/5YhpYskeRHH0ly5Urpq6Kth0Ab3y+7zTaS/PhjyfX2ysjAgIy4FJF6xcgmm8jQt78t3S+8IF1Ll0o6kZCRri4ZnjGjpH0iwzoyO+wg6S9/uWHb67vlFpGODhlZuVJGenq0YzoalVw8LhKJyEgsJunubsmuWCEj/f2S6+iQXCwm2XBYkgsWSPaCC+pavoGnnpLsxx+LhMOSXbVK0qGQpHt6JBMMykg4LNloVPk2hz76SLJr1shIOCzJNWsk1dUlua98Rfl2st/+tmTXri1pFtDMGDzlFOmcP1+TpQ8+kM433pDQRx/JcDwumd5eyaxcKenOThnp7ZXc1Vc3vbzZbbYpqUUbOvpopeOdjpbQO0ENXHCB9N53n0QfflhiL78swy+9JOl33pH0Bx9I6q23ZHjlSkmtWiWpVaskHY1KcvVqSS1bJqnlyyUVCkl2zRrJLVhQl0fNFED/sDG02jzzI9y7AMy3WWYNgF+Ypv0CwOr8/3eCtvP3Ns3zVwCP2qxzDLSDRY9JACQSiUg6nVYWiVtvbfoJzGAwGAyGF2LoySeV3mPT6bREIhHJOwAF0ONsC21HHWSa/msAy2yWSQM4xTTtFGjtAZFfl+TXbeQhAC/arPPa/DJF0dbWJu3t7cpiydFHN/2EYzAYDAbDC/HalVcqvce2t7dLW1ub5O/hFECPowvggabpvwGw1GaZNIAfmaadCq0DCbBOALcxzfMnaI+KrWhIDWA6nZbBNWtk0emny/C0aZJ+9FHJPPaYZG69VTIPPyyZu++WzIwZkrn8ckl+4xuSvPpqSf3615L6+c8lff75MnzxxZI5+mhJmoYBcRqJa66R1IsvSnrOHEm98YbkPPTYyBzxKVMk+vDDMrhwoSQ/+EAydXh8xlATQ9ddJ6nrr5fkdddJ8plnJP3ss5KePVvS06dL+u67JfXuu5L6+98l3dYmmenTtXjsMcn84Q+S/c1v6l6+5AknaOV66CFJ33efZG65RdL33CPpv/xFMs88I5kKr1SsKScXXyzJK6+U5J/+JMmXXpLUP/4hI4ceqn47DzwgGQ88RjVG/PjjpfeyyyR67bUSuekm6bn9dul96ikZfPNNSc+cKcPTp0vq0Ucl9Z//SNpFZ4l6x/B++zW9DF6OzFZbSezMMyV5+ukyfNFFEr/xRhm8+mpJn3eeJKdNk+RVV0nq1lsl8dJLkrr7bkk98ICk/vY37dpw332SCoeV319ZA+gvvPII2IznO4EMDg46P1HLvajdAxeS4IoV1sOleLC86d13L3qdlzmyW28tw4cfbtsb2Dj2VrWRnTBBgmvWWOcwuG4U/5JOIGvXSnbrrZXlILf++hIMBApDfyihDvuq//rrlfQCFmhv5nCyzZ5p02TOU0/VvROIANo7o/Mkf/Sjhp8Lxgh/+OG6jk5VDgg9YvH6v/i55xZdK4PBoIyMHaukrL3Tplmem8YxLfWOIEXzdHRI17/+VdQLPrR4sfTefXfT8p79/Oel/9prXa9n+IgjHL2DOhgMSigU8vQwMWwD6C/eBnC/adoSlO8EMtc07QWUdgK53PD5xvBAJxARdQJYbhw0Y4QWLy5/sjbxpqGHcYytSujjszXsArv11o7fiuEkahkHUAAZ/sY3JBgMSm9vr+XniUSiIM2ZTKZ0259+Wrhx9f/ud462ObLppiKARNrapPv55yW0aFH9egRWmY/wwoWOj6tqtx/+739Lxkws9BT9znfKbrPe4wDqMfTd7xa9tit50kkNPS/06H7uOec9+G3IJZMSu+QS6X7hBclkMpJMJksGgk6n064GpI9deql2DlQ5vInT87pr3jwJf/CBkl73uY02ksgjj1Scb/jwwwvbczJ/yfmxalVZyctms4VrirFntNehAPoLfRiYn0AbBuYOaMPATM5/PhPFMngQtFrDK6ANA3MFrIeB6YdWs7gHgDaMsmFgRKTyTeKooyreAMMVxlMbbsDwEk7lT0Sk8803Ha0zfs45NZdHxSvgbOXPwX4rd7HO5XKS2mOPos/6HnywKEclNRdWN6wXX5TIjBnSe8cd0vXww/LEXXdJ9KqrpOvVV0teXF+pNkAJVeQi+uCDMjIyUvatMN1z50ow6PzNFJFZs4oG8Q0GgxL66COJn3OOdL30UtG0ctusJIDZCROUnTPZbLaw3uSJJ9b1HE3vvLOMbLaZDB11lPZKOpsa7lrfDGMlj+ZrZa2iIygd6FiP/v7+qgaC7u7ulqGhoaLXA1qeF8uXu9q3wWBQYr/6VclnyYMOkr7bbpPIY49JaPlyy3KUGxcwsHSpVtNXYbxSP0MB9B/nAwhA68ixAMChhs/mAZhhmv9EaG0E09CGjDne9Lk+EHQYWtvA+dBE0CmjQgD1savKYfy1Grv00pLHGcFgUOnjQ3NEnniiqgtOMFj6knVzdP7nPxJcubK2G93uuysXP/NNsZbhbILBYOEdoEnTGGG9FgPvGt8PWikCgYBMnz5dAjY3yWq+W81UkYue2bMll8tJ+h//KEzLbbCBRB98UHrvuUe65s0rlK+vr8/R5qv5zlZlSn3lK4Vclju/o/ffX9NxmdlpJ8mNGSOxSy+Vrn/+s+ScSZlqLAd+8QtX52VwzRpJnHyyZHbYwfEPgmoHgDYyMjJS0uzDSgDL7YPCNaWtTQYuuED6br5ZwgsWSPj992s+bsuJUS3HSblIffWr0vPss5pAhkISXL3a8jrQ398vweC6HzdW2+568UWJXXqpdL71lgyeeqoMHXSQPHbvvY7Ocb/U9NlBASRuGRUCqNcalcN4oeq79VYJBoPSPXeuDB15ZOFdwuEPP5T4uedKau+9JXnIISLQRqvvmTXL1U1Gv6BVLYD/+lfZdYbz77CNPvSQ43IMfe972o3OwZs83ApScM0aCX30UVVtd4w5ihs6LSROOMFScirVUKgQwIGBAcf7rSK66Gy/fcVchBYtEhGRnKGWxa6M+uC+lSh7Izd9njj5ZNtzrZIA9jzzjKvzxE5GUscdt07+fvazqgUk/P77En3gAen+61+l8403ajrWVVNOAEOLFll+j8RJJzk6h421p+UwLmNu2zg0NFR2G5nttqt5H8fjca2t3Xrrlcyjvy9ZFzWV57gbifcKFEDiFl8IYOL737e9mEQeecTRhblIAG++ufLFZM0a7RVbhobQfbfcUtNNLXH88RIMBsu/+s1EKBQq+xhOUNypJPLYYzXfYN1GV1eXbc4LF9w//rFi2Tpff72odiRh6ADU9c9/2tZyjYyMSF9fn7Kbgzni8bjj/VYR/bh9/HGJ/vnPtrnomTWr6JgeePBBieSnuZESq2U7OzsLktvV1VW8bw210MbG85UE0Gk7tuCnn0q3oYdspe+WMgwxpX8+fMQRjrYVffhhJce7asoJoPG6pUd6t92Ul9W4jLmZSsWmFmvXSvidd6TrlVfK5j87cWJJLWsul5N4PC65DTcszNc7bZrlceXk+zo9x53+YPIyFEDiFl8IYDm5cXqxCwaDMnTssZKdMEFCS5a4ugF0vvmm9PzlL4UyDP7wh+VvcmvXVn3jiMVilhd/W5nr6JDkwQfbi/Kjjyrt5GEMu1qGSCSybr7Vq2Xou9+VoaOPlsgTT5S0Eet5+mnLHCWOP17rGNLR4ag2Q8XNwRxKHxXlv2/3Cy8U9pvVfjYf05YdXlze6K2WLdpn+fINnnqqDPzyl0XTu7q6yp7fwWBQwgsXSuiTT4raag3+6EeSnThRho46at07WTs6JH7WWdJ3440Vj62EYTgdfZ7whx/K4Bln2DaZCHZ0lLyq0E2oppIApr76Ve2H5MknS88zz0ho6VJH5azm1YX6MpFIpOQzJ21tC/vi3Xdl+Fvfkp5Zs0qE0C6X8XhcRjbZZN0P5kTCsozJZLLi9p2e46MBCiBxiz8EsMz4ZU5P6sJ8+RuBuaajlgi/95703nWXBFetKinX4NSpmtjkHy9Xe9HRL3adTzxh+b1T++5rfWGzy5OhJlN1lGNgYKD8svny2Q21YicCFfezi5tDXW8UM2dqPTUtjqX0LrvYCmCl7+YU83LmziM9PT2O8pJMJisKYFHU0O7S6nul43Hpv+oqbZgSh8d/I4/3WqgkgKFFi6T37rslZDGMlF3YSZQdQ0ND0t3dbXmeVSOAJWVfvFjiZ55p2Yta71gVj8elZ84cyW61lUT/9CfbMjopBwWQEOf4QgBDn3xieWE3vpS9v7+/7DrMF4B4PC4jIyMSjUZleHjY9U3B2F4vedBBri86epnWvPuu5XfvfOsty21kJ07UavwM4pjbYAPlN0E99A4bdsTj8bLLh997Tzpff12CQet2OYlEoqpHsCpuDnrUq5G47c1y+XKJXXJJofOD+ZixW844TEq12zafn04FsNL5XXRuuPixVU3+gsGgJA88cNQJYLWhtM1qHtU5DAbXtRsutOPt6KjYTKbSOp2c41a1nH6EAkjc4gsBDAaDEpk5s+yFvVJvN3MbMXNPvJJHXzVEbqONRACJXX656xuHLoCBQEAWmsZk09sUBoPazb9kW6bHisOHHVbT9+nt7a0ocJVIJBINvXG5vTnU8ybqpIzl8ms3j+1g4g62bT4/nZ4H1QhgLpcrNGmoNqwYGhqyL+fq1SVDPrk9r42hrDe4ARUCGI/HJZVKSSwWq8sPl0rHgqp966YcTs9xp08TvA4FkLjFFwIYCoWk58knywpgpfYu5t6i5ptmNb1J7aLzrbe0IWlsBh6tBqMATp8+vbj2L9/7d3h4uGztSu+0aZLeeeeaezuabyRDQ0MSj8clFotpDbcd3GiqeXzkdIzEcri5OQwODhbd1OpFrTdJp/upmm2bv2dvb6+jclU6v401iSK1n1+15rFeAlgP3ApgPa7fZspdZ2opc60dqyqtt9I5XulJkZ+gABK3+EIAg8GgawEUKR7OwCyAbtq51OPmYRbAkc98Zt33zrdjFCl/YXYTKmsRnG5ThQCWq3G0ujnE43Hp7+8vPHpKp9NV9dauhVqPGRX7yrxsvQRQ791prG1Rfc6UXa6FBLAR2I23qZ8rTss6ODjo6p5Q6XpXTgAbIcqNhAJI3EIBzON1Acx+9rNF31tv5F3NQMjNuqEkk0nrR9WmaLQANota94WK/VUp506G0wkGKwugFbU8KqzmuxQtRwFUilUvdGMHokaVtVYBHA3DvpihABK3+EcADcOu1EMA9e3UM6rBLICxM87Qev/uuWfRulQLYL0GSHUi2CoEsNxQEYFAQGbPnl3V8Bj1oNZjxmpAXqevgNMxd3gy4/RRba3nt1kCw+Gw7TbcdAgIv/uuDJ52mnTNn9+0c7ianNQqgCrOGaeYt228hjYqf9UKoN/f9lEOCiBxiy8EsKenp+RtHOZXmY02AdTLWrigLV0q0fvvLxkuRbUA1vOC2aibmV1OAoGAPPvss3Vt3+cEN8eM+QZYxPVHgAAAIABJREFUrbCbRbyW8vX29ro6v43fwfx99BpcJz2b632+mqNePxzcCGAjMdaum+U8Go1WLKuK+4yxna7dOT59+nTpcDhuqJ+hABK3+EIAE4mEREwCGP3Tn6q+OFcSQKdDYNQa1ZBKpYouaMZHGsabo0oBtHujhyoqPQJUecE2rjccDks4HJZ4PK7u9YSKylbtMZPNZl1JiRMBrDTg7vDwsKvz21jLaBZAEe3Yd9KzuZ7nqlXU68dRrQJYz57q5bDaN/pr2xpRXqtrXigUkmAwKGvWrPHEj7xGQAEkbhk1Auik9sh4gbK6mJtvriqjlt5ng4ODEo/HSwTQOPaeWwHM5XKSTCZlZGSkIY9L9KEqdNkzlkWlAA4ODkpvb2/RNKXvp3aBk/aQwWDpO1l1KglcOVQIoIj7XBoF0DikSy3raERUO7ByNfhNAMvRiPKa2/kah+bxyjneCCiAxC3+EUDT20Cif/5z1TdCvVat3Pz1uoHUmuN0Ol0igMacVjPOnt3NvJk0sixeuTlUejuKHnYD1uqCVstQGkYBNAuyef31FMBEIiHhcFjS6XTR9qqhkQJYTyiA1WE8hs3XVa+c442AAkjc4h8BNL0Szfxid6f09PTY3vhE/CGAqsrshTGx3OanGrxyc3ArgCJSc22t8eZpJ5CNEEAjTn6YWaHiDT5u94MKzLm06uxDASxGf3JhPg+8co43AgogcYsvBHBwcFC6X3ihSAB7nnyycGFR2Tjb6TAYjRTAp556SrkA9vX1uU2VEiiAjRUPLwqgselFNVQqp6qod9MIq1yORgGs9NpIFXjlHG8EFEDiFt8IYDAYlNiVV0pqn31k8NRTC687q/am4XRbXhLA9vb2ggBaddSotizVDh1ST1rx5uB1AbQa862eAiiiyVwt69Ib/9crGkGtAujFse2aKdIi3jnHGwEFkLjFVwLYiIu02zZ19RZAq2E/qi2Ll2oO9DI14oLtlZuD02OsWQIoUv4xpIh3cml8fKw6GjVeZC0CWK4ZSzPxokyPViiAxC2+EMBKN0yVeF0ArdrtVVtrSQFs/s3B6wIoYl+7JuKdXNoJoD70j9flT6R6AWzk4M/VYi4nBbB+UACJW3whgJXeIqGSeg0F41YABwYGJBqN2o6PVk2DeC/dQCKRSN3HH9Tx0s3BCwJY6RGi3Xkn4p1clhPAeDxe07na3d3d0O/gVADT6bSj8RGbifk4oQDWDwogcYuvBbCnp6cu7WC8KICV8uhUAEOhUE3lGA146ebQLAE0bttJmyyvC6DdD7ZkMlm1AA4MDEgmk2n468OcCKCXau3LQQFsHBRA4hbfCmA928DUQwBrHeRYtQB6vQahnnjp5uDksX29BDCbzTo+Hu3K5KVc2kmq0/caN1JQrLDKpXmAdwqgM7x0XNYbCqA/mADgMQCxfDwG4LMVlhkD4B4AEQAJAH8DsJ1pHrGIc6ssmy8EUKT8i8hVUw8BrBXVAtjKeOnm0EwBrAa7HzJeymW547yaN+U0C6tc9vf3jwoBNL71phF46bisNxRAf/ACgEUADszHIgB/r7DMAwA6AHwTwN4AXgHwAYANDPMIgKkAtjbEplWWzZcCWG8ogKMTL90cnAz260UB1PFSLssd59ls1vE7vpvFaBZA47ueG4GXjst6QwH0PrtB20H7G6YdkJ+2q80y4wGkAZxsmLYtgBEARxqmCYApLstHAaywLQrg6MFLN4dKHZsogM6xEjwj5QaMHhoaknQ63dSOUU4EcHh4uGnlqwbzPkin09LV1dWw8nvpuKw3FEDv8xMA/RbT+wGcabPMN6Dt1Amm6R8C+J3hb4FWSxgB8C60x7/rV1k+CmCFbflFAJ0IRTgcrrkcowGv3RwogGowdwQxH+flevZ7YTBlJwLoF5LJpHR2djZ0GB0jXjou6w0F0Pv8GsAnFtM/AfArm2VOAZCymP4SgAcNf18F7ZHyVwFcAq2t4FUVyjMG2sGixyQAEolEJJ1OK41EIiHt7e2SSCSUrC8QCBRCdVnLbUtVNCKPlcqwZs2auufOy6H6mKz3cRYOhz1XRj/kMh6Pl3w+NDQkw8PDkk6nJZlMSjgcljVr1kgqlWp62a1yGY1GG3rNGy3hteOynhGJRCiATeJaWHfCMMa+0ARwmcXyywFcabNuOwH8J4A/linTJdA6mVRd7ra2Nmlvb/d0TJ8+vRCN3JaqaHSOrOKRRx5p+n5kON9fM2fObHoZn376aXn88cfl0UcflSeffLLp5XGSy9mzZze9PG7j2Wefbfj1g+GvaGtrowA2ic8B+HKF2AT1fQRs5uD8cluVmYc1gFVuizWAoye8VjtQaX91dXU1vYx+yeXAwIAEAgHp6elpellU5XLt2rUSCASko6Oj6WX0S3jtuKxnsAbQ++idQPYzTNsfzjqBnGSYtg1KO4GY+RmAYWiS5xS2AaywLb+0AXRSbrYB9Fb7oEr7y8tjNnotl37GLpfZbFb6+/trHkO0FWml45JtAP3BC9Bq7w7Ix0IUDwMzCcBSFEviAwDWAjgC2jAwL6N4GJhjAJwNYA8AXwRwFrTHv3dVWTbfCODAwIAEg5XfX6qCSCRCARyFeO3mUK9jphF4LZd+hrlURyvlkgLoDyYCeBzAQD4eR/FA0DtC24mHG6ZtAm0g6CiAIWjCuL3h8+8AeB9AHFrnj0UALgKwYZVl840AikjDfglX+wYBvwhgPfazn/DazYECSESYS5W0Ui4pgMQtvhLARjIaBbDV8dox6ef95bVc+hnmUh2tlEsKIHELBdAGPwqgeewwPwlFI/DaMRmNRkv2USgU8sXjeq/l0s8wl+popVxSAIlbKIA2+FEAK5W71fHaMdnb21uyj0ZGRiQWizX1zRRO8Fou/QxzqY5WyiUFkLiFAmjDaBNAL7zxoNl47ZiMxWK+lXSv5dLPMJfqaKVcUgCJWyiANow2AfTLu0TrideOSavORn7Ba7n0M8ylOloplxRA4hYKoA0UwNGHF49JCiBhLtXRSrmkABK3UABt8KsA9vX1UQBt8OIxSQEkzKU6WimXFEDiFgqgDX4VwOHhYcvtJ5PJmsswWvDiMWncR729vc0ujmO8mEu/wlyqo5VySQEkbqEA2lBpSBU/CWBfX1/N2x9NePGY9KukezGXfoW5VEcr5ZICSNxCAbQhmUyOCgEcHBysedujDS8ekxRAwlyqo5VySQEkbqEA2qBSAHt6emouh1sB9Pp4co3Ei8ekPvCz3/aVF3PpV5hLdbRSLimAxC0UQBtUCqCbtl1uBZCsw4vHZCaTkUgk4ruaWi/m0q8wl+popVxSAIlbKIA2UABHH34/Jr0Ec6kO5lIdrZRLCiBxCwXQBgrg6MPvx6SXYC7VwVyqo5VySQEkbqEA2pBKpZQJoJv8VpvHTCZT2C5f/1aM349JL8FcqoO5VEcr5ZICSNxCASxDX19fUSP9WmNgYKDmMtSSx2Qy6asOBY1iNByTXoG5VAdzqY5WyiUFkLiFAugAt7WBjRZAYg1zqQ7mUh3MpTpaKZcUQOIWCqBD3LQJdPModrTlsZkwl+pgLtXBXKqjlXJJASRuoQBWQSUJzGQylu/idcNozGOzYC7VwVyqg7lURyvlkgJI3EIBrJJyj4N1stksBdCDMJfqYC7VwVyqo5VySQEkbqEA1ogud+FwWDo7O4sG8qUAehPmUh3MpTqYS3W0Ui4pgMQtFMAaGRoasu3cQQH0JsylOphLdTCX6milXFIAiVsogHWAAuhNmEt1MJfqYC7V0Uq5pAD6gwkAHgMQy8djAD5bYZlzAMwDMABtB1vNX8t6zVAA6wAF0Jswl+pgLtXBXKqjlXJJAfQHLwBYBODAfCwC8PcKy1wM4Mp82AlgLes1QwGsA7lcjgLoQZhLdTCX6mAu1dFKuaQAep/doO2g/Q3TDshP29XB8ofDWgDdrleHAlgnUqmUhMNh169ja/U8qoS5VAdzqQ7mUh2tlEsKoPf5CYB+i+n9AM50sPzhsBZAt+vVoQB6HOZRHcylOphLdTCX6milXFIAvc+vAXxiMf0TAL9ysPzhsBbAWtc7BtrBosckABKJRCSdTiuNRCIh7e3tkkgklK+7lYJ5ZC69GMwlc+nFaKVcRiIRCmCTuBZa4svFvtBEbZnF8suhte+rxOGwF8Ba1mtZ7ra2Nmlvb2cwGAwGg+GDaGtrowA2ic8B+HKF2ATeewTMGkCfBfPIXHoxmEvm0ovRSrlkDaD30Ttr7GeYtj/UdQKpdb06bAPocZhHdTCX6mAu1cFcqqOVcsk2gP7gBQAfQuulewCAhSgermUSgKUolrmtAXwVwFnQdvD/y/89sYr1OoEC6HGYR3Uwl+pgLtXBXKqjlXJJAfQHEwE8Dm1Q54H8/401ejtC24mHG6ZdC+t2hVOrWK8TxgGQtWvXSiwWUxqRSETa2tokEokoX3crBfPIXHoxmEvm0ovRSrlcu3YtBZC4YhIqd2ZhMBgMBoPhzZgEQmpgPWgHz7g6hC6X9Vp/qwTzyFx6MZhL5tKL0Wq5nATtPk6IpxgH7UQc1+yC+BzmUR3MpTqYS3Uwl+pgLgnxADwR1cA8qoO5VAdzqQ7mUh3MJSEegCeiGphHdTCX6mAu1cFcqoO5JMQDjIHWm3lMk8vhd5hHdTCX6mAu1cFcqoO5JIQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIcQ5+wN4FsAaACkAXQDeBHC7ab55+fAK8+C8PL8GMKVO5dBfDH+lxWdT85/tW8N69WV3rLFctaBvU48sgDCAvwDY2cV6j4I2RpwVAQAzXKybEEIIIVXyPQAjAF4G8EMAh+X/vQ1Ah2ne3fPhFebBuQAOon6SoctSP4CJps+monYB3BLAAWjswLpToZV3an7bhwP4DYAhaD8MJtS43nvz67VibwBfrHG9hBBCCKmB+QBWANjQ4rP1G1yWapkH7wjgPwFkUFprOhW1C2AzmArr8l6dn35mjestJ4CEEEIIaTAfAXjL4bzzUCpc2wF4BkAcWg3YEwC+hnW1SDozoEnYlwDMzf9/LTRhMtdwXQPgbQC9AAYA/BfATwGs56A8VohFGJfbA8BfAfQBSAL4AMAZDtZrXP+9AP6YX36y4bOpsBaqY6E9Zh+Clrt/AjjQNI++7I6GaXsDeA5AN7TH9SEAz0PbDzrrATg//z2G89/rGQA7OfguduU9CtaPuU8G8BK0x8TDAD4GcBOAzQzzzID1PtC/VwClcr4DgMex7nt+DOASeP9HCSGEEOIL/gTtZnw3tLaAG5WZdx6KxWkzAMsBRKEJx7cBTAOwEtYCmAKwBNqN/AgAvwOQg1a7ZOQRAD8B8M18XAVNlMzzmctjxwH55Z/P//8ArHuUvSs0yVwB4MfQRKctX/7LHawbWCeAWwNIAJhp+GwqSoXqlPy0FwEcB+AkAO9By88hFsvumP97MwARAO8C+AGAQ/PLPgBgN8NyDwFIQ3uMfySAH0ETqE4AW1X4LlblBYAL8tOPN02/CsDF0PJ2GID/g7b/XzHM80UAT+eXP8AQuvgHUCyAW0JrftCdX9+RAO7JL39/hfITQgghxAFbAPg31tXKpAG8Aa2mZ6xp3nkoFq7z88t8xzTfH2EtgAJNXIw8D2BpmfKtD+3x9G+hyY+xFtBcnnLYPQKeBa3WbnvT9LnQZG68g3XrAggAN0BrU7ln/u+pKBaq9QEEASxEcW3WWGht7N4wTNOX3TH/9z75v48rU5YD8vP80jR9O2gSfHOF76Jvc39oeR8LTcDC0JoLWDUV0Fkv//mh+XXsafis3CPgAIr3zR/y8+5nmu9+aD8YdqnwHQghhBDikH0BXAGtpqYH2g14FYDPGeaZh2LhehJa7ZmZw2AtgDkAm5jm/QO0R4dGvgHgXwBiKH1saKzBMpdnA2gCoodRsOwEsAuahJo5CcVyW27dRgEcBy1/L+T/nopiAdwt//dlFtu8H5o8fsa07I75v8dDeyy+FMC5sO6QcwO0PH/eVN4NoT1yfttiGSP6Ns2xBMBnLebfCVqNaWd+u8ZlTjbMV40Avg1gscV8++XXcW6F70AIIYSQGtgI2qNcAXCLYfo8FAvXv6A9AjbzZdi3ATRzLYrFYD9oQ4/8C5qEHQRNnm5AaXs4c3nmoVhAZhg+sxPALIA/W0w/JL+OU/N/B0zrvtYwr1EAAeCi/LSvo1QA9fWeZrHNq/KfTcr/rS+7o2Ger0AbkqU3/1kI2qN0/dG9/kjfLj612K4RfZs/zpf561hXo/uCad6x0GozPwVwFrSav30BfB+l+78aAVwBbf+b2S6/jt9U+A6EEEIIqZHx0G62cw3T5sFZDeDhqF0Ap0GrETTXFDoRwF2hCYgexnlrrQE8Mv/3V0zr3tYwr1kAN4bWDu4daL1mVdUAGlkPwF4A7kBx54w/QKuJO9hUXj2+YrEuI/o2zW0AdbE80TDt2Py0w0zzfhPuBLBSDeD/2ayHEEIIIQ7Zxma63pbMWDs2D9ZtAL9rWtauDaATAbwdWq9YY2eUTQGsRmUBLEcUmrCaaYMmnNuapj+H2toA6ugdPeaitA1gB4D3UdyecTNoMvq6YdpU2AugkT4AT+X/f3B+mZMclNsKfZtmAZwArdZxCdY9/j4G6zp2GNE7fEw1TLs9P21Ti20GUCyAv8/P+7+m+e4F2wASQgghSlgITVLOg/a47whovXRD0ETMWGM0D/a9gM8D8C1oNXiroN3ATzfMOwPOBPAb+b+fzq/vh9B6yH4CdwI4D5pgHQNNbnbNT9d7AS+D9rj3u9CGH7GrpbPCSgDXgzZ8jf7o1aoX8PPQatF+AK22sFIv4KOh7atzoNWyfQtaD2ABcLZhuQehyest+WW+nt/m/dD2Uzn0bVqNW3gZih9fbwFNCj+A9tj3aGidavR9NdVivddC62CyL7SaUsC+F3A4/72+DeAuaPJ3X4XyE0IIIcQBJ0Ebu+8TaMKXhlbbNhPFQ4sA1sK1PYDZ+WUHoI03911oN/tjDfPNgDMBBLTHpkuh9c79FNrjzZ/AnQDuBa12LZFfj3G5PQD8Ddo4hiloQjPV4XoBawEENEGzEkBA68n7FrTax0Fobd4OMs0zFcXfeVdoNZYroPXo7Yf2uPQMi22fmV//YH7eFQAehdaTuBz6Nq0EcBNox8Yn0DrFANrYhf+BltduaI+K90apAG6c/6wb6zqL6N8rAOtxAJ+A1vM7De14uBQcB5AQQgjxLL+GdpPfrtKMhBBCCCHEf/wsH9+EVvN3K7RatJnlFiKEEEIIIf7lJwAWYd3j4xUArsO69l2EEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCiO9ZD9o7P8cxGAwGg8HwVUxC8dt8CHHMJJR/aTuDwWAwGAzvxiQQUgPjAMjatWslFospjUgkIm1tbRKJRJSvu5WCeWQuvRjMJXPpxWilXK5du1YXwHFN9gjiU8YBkFgsJqpJp9PS3t4u6XRa+bpbCeZRHcylOphLdTCX6milXMZiMQogcQUF0OMwj+pgLtXBXKqDuVRHK+WSAkjcQgH0OMyjOphLdTCX6mAu1dFKuaQAErdQAD0O86gO5lIdzKU6mEt1tFIuKYDELRRAj8M82pPLiQSDzudnLtXBXKqDuVRHK+WSAkjcQgH0OMyjPb/9rQggMneus/mZS3Uwl+pgLtXRSrmkABK3UAA9DvNozwknaAJ4443O5mcu1cFcqoO5VEcr5ZICSNxCAfQ4zKM9xx6rCeAllzibn7lUB3OpDuZSHa2USwrg6OZXAN4FEAfQDaAdwK6meeahdFTwv1SxDQqgx2Ee7fnudzUBnDrV2fzMpTqYS3Uwl+popVxSAEc3/wAwFcD/ANgLwHMAVgPYzDDPPAAPAdjaEOOr2AYF0OMwj/Z885uaAB57rLP5mUt1MJfqYC7V0Uq5pAC2FltC29mHGqbNA3Cni3VSAD0O82jPYYdpAnjIIc7mZy7VwVyqg7lURyvlkgLYWnwJ2s7ewzBtHoAeABEAiwHcBmDzKtZJAfQ4zKM9Bx+sCeDuuzubn7lUB3OpDuZSHa2USwpg67AegL8B+Ldp+tkAvglNCn8IYBWAf5ZZzxhoB4sekwBIJBKRdDqtNBKJhLS3t0sikVC+7lYK5tE+vva1EQFEttoqx1w2OJhL5tKL0Uq5jEQiFMAW4T4AAQDbVZhvn//P3nWHWU187QMsXUCkN2kCClhQsIIogvwEUVARsQCKDQt8KHaaBVFAEQtdRISlCHKlKFXEgtJRkS5FkOYKCLvAZnfv+f449+xMclPvTe7NunmfJ89uJpOZuSeT5M2ZU4AmxOUGxwdDtNMIpqamYigUCrZgy1NbnTrHEQAxJSUH585N/niCLdiCLdgStaWmpgYEMB/gAwDYDwC1bdQtAAAKAHQxOB5oAPPYFsjReGvUKIwAtAx87Fggy0RugSwDWfpxy0+yDDSA/20UAIAPAeAvAKhn85zGEO0oYobABtDnCORojAYNMJcA7ttnXT+QpXsIZOkeAlm6h/wky8AG8L+N0QBwAgBagjrMS/HI8boAMBAAmgJALQBoBwBbAWADABSy2UdAAH2OQI7GqFNHEMCNG63rB7J0D4Es3UMgS/eQn2QZEMD/NqJs9SJbj8jxGgCwEgD+AYBMANgFAKMA4DwHfQQE0OcI5GiMGjUEAVy2zLp+IEv3EMjSPQSydA/5SZYBAQwQLwIC6HMEcjRGlSqCAM6aZV0/kKV7CGTpHgJZuof8JMuAAAaIFwEB9DkCORqjfHlBAMeOta4fyNI9BLJ0D4Es3UN+kmVAAAPEi4AA+hyBHI1RpowggG++aV0/kKV7CGTpHgJZuof8JMuAAAaIFwEB9DkCORqjRAlBAJ991rp+IEv3EMjSPfhZljk5iD16IL77brJHYg9+lqXbCAhggHgREECfI5CjMQoXFgTwwQet6weydA+BLN2Dn2X5++90fxUvjhgOJ3s01vCzLN1GQAADxIuAAPocgRz1EQ4L8geAePvt1ucEsnQPgSzdg59luWaNuMcOH072aKzhZ1m6jYAABogXAQH0OQI56iM7W00AW7SwPieQpXsIZOkevJblL78gbtkS27krV4p77Kef3B2XF8hP8zIggAHiRUAAfY5Ajvo4c0ZNABs2tD4nkKV7CGTpHryU5bFjZCtbrhzZ8znF4sXiHktNdX14riM/zcuAAAaIFwEB1MFbbyHWrIm4a1eyR5K35eglTp5UE8DKla3PCWTpHgJZugcvZTl/vrhHMjKcnx8KifOHDHF9eK4jP83LgAAGiBcBAdRBkyb0wBs4MNkjydty9BL//KMmgEWKWBupB7J0D/ldlmvXIl59NeK338bflpeyfPFFcY+kpTk/f8YMcf7DD7s+PNeRn+ZlQAADxIuAAOqgalV64F19dbJHkjg5jhqFeNFFiO+8Q8urfsfhw2oCCICYnm5+Tl6ek35Dfpfl00/TnOvaNf62vJRlixbi/ti/3/n5n3wizm/d2vXhuY78NC8DAhggXgQEUIOcHMRCheiBV7Ag2dAkE4mQY1YW2Qjxg/788xG/+MKz7lzB/v001sKFRTiYffvMz8mrc9KPyO+yvOUW+7anVvBKlmfPIhYtKu7r7dudtzF6tDi/bl1Xh+cJ8tO8DAhggHgREEAN/v5brVX6/PPkjicRclyxgn5r6dKI1arR/8WKETH0K3bvpnGWKEH2fwCIGzean5NX56Qfkd9lecEFNOcKFYpfY+6VLFetUj/LNm1y3sa774rzCxcm73s/Iz/Ny4AABogXAQHUYPNm9UMz2XYviZBj7970W7t3J0PxYsVo/48/POsybuzYIUhrw4b0//Ll5ufk1TnpR+RnWSoKYkqKeEasWxdve97Icvhw9bMsljAuQ4ao27DSsicb+WleBgQwQLwICKAGy5erH3jnn5/cCPheyzEcpt8IQB5/iIiNGtH+4sWedOkKOENBuXKIzZvb09bm1TnpR+RnWe7apX5GfPxxfO15Jcvbb1eP85tvnLfRv7+6jZUrXR2i68hP8zIggAHiRUAANUhNpQfdlVcK+5mtW93tIz0d8cgRe3W9luP69WIp9fRpKuMXx0cfedKlK9i0SYR/4fGOG2d+Tl6dk4lEdjbi0aPW9fKzLL/+Wk2KeveOrz0vZBkOI1aoIJZuARAXLHDeTr9+6t86ebJrQ/QE+WleBgQwQLwICKAGI0fSg65LF/J6AyAPWURaHv3kE8RrrkGsXh3xu++ct5+Tg9isGeXWPHTIur7XcuQv/DvuEGXPPENlfft60qUrWLuWxlijBuUBBkB8803zc/LqnEwkuncn5yerzBH5WZYffCDs/wAQW7aMrz0vZLl9O42taFH6mI3VnvnJJ9UEcNAg14boCfLTvAwIYIB4ERBADThuVu/eiMOG0f/16iG2aoVYqpT6YVi8uPNl0rlznS3JeC1HXu797DNRxp5/HTp40qUrYAP3OnUQn32W/u/Xz/ycvDonEwmOgTljhnm9/CzLPn1EWBQAxHPPjc9MxAtZTppEY2veHPHmm+n/KVOct9OzJ53Lz75u3VwboifIT/MyIIAB4kVAADVgbdKQIZRDUxtrrk4dxKFDRRiIIkUQ582z13Y4TLEFua3Zs63P8VKO7EiRkqIOd7NkCZVfdJHrXboGzlHaoAFp/gAQH3rI/Jy8OicTiQYNSJbjx5vXy8+ybNeOZPT++8IZJB7nCC9k+dBDNK4XXrBvIqGHe+8VJjEA9nJuJxP5aV4GBDBAvAgIoAZM7CZOpP1hwxB79UKcMAFxwwaRTzMzE/HOO6lu1ar22v7uOzWZtPNA9lKOb79N42jTRl3OIVaKFLEf9uH554kw/vOP68PUBTvrNG6MOHYs/d+xo/k5eXVOJhLsEDR8uHm9/CzL+vWF13njxvS/3Y9APXghy+uuo3HNnIl4zz30/8jsyZBSAAAgAElEQVSR+nV37kQ8eFD/WKdOIkIAm1z4GflpXgYE8L+NlwBgLQCcAoCjABACgAaaOkUB4AMASAOADACYBwDVHfQREEANLr+cHnTz51vXPXFCkDk7eTbbt1cTwKFDrc/xUo6sjRw9Wl2elWU/uDIiObWww8zSpa4PUxeLFlF/l12GOGuWPe1EXp2TiQQ7DgwYYF4vv8pSe2/cdx/9//rrsbfphSzr1RNeu6wN1LOR/fdfcgAzCvLMH8T8sVigAH38+hX5aV4GBPC/jUUA0AMAGgHApQCwAAD2AUBJqc4YADgAAK0BoAkAfAMAmwCgkM0+AgKoAQdCXrvWum44TA9PAAoNYYbffhMP0A4d7NmsIXonx7/+EkT0r7+ij8taDivMmyfaisXTMBZwkvtmzRCXLaP/GzUyPyevzslEomRJkmWfPub18qss//hDOFfk5Ag74c6dY2/TC1mWLk3j2rZNOHLokXoOpwQgVjdk3HADHZs+XTzrdu50bZiuw6ksMzPpmXXypMcD8wABAcxfqAB0sa+P7JcBAAUAukh1qgJADgC0tdlmQAAlhMPi6/7PP+2dwxkBvv/evN7LL1O9Tp1EcFUrmzVE7+TIjh5G+Y7ZzsnOMvVjjzmza3QDX3xB/V17LWUAAUCsUsX8nLw4JxOJcJg8gAEQe/Qwr5tfZbl4McmHU8Dxfv36sbfptizPnBH347FjIpSL3gennC3k1Kno41ddRcdCIRFwfckSV4bpCZzIMidHmPFceWXeyIEuIyCA+QsXAF3sxpH9VpH9spp6vwDAqzbbDAighH/+EQ/Ds2ftnXP99cLWxgw9eohlmDFj6P/bb7du3ys5tmkjlnb0wNlBnnvOvJ1wmELisNymTXN1mIaYOVOE4Ni3T2hlzLwx8+Kc9AJGdp2ZmeI6ymGB9JBfZfnRRySf226j/cOHhWY/PT22Nt2W5Z9/CueucJg0fwCITzwRXferr8Q1P3w4+vill9KxxYuFCUssziSJghNZPv+82iTnwQeTG/TfKQICmH9QAMi+73up7F4AyNSpuwQAxhm0UxRosvBWDQAwLS0NFUVxdcvIyMBQKIQZGRmut+3V9ssvCgIgnntu2PY5nTvnIADiiBHZpvVuuSUn8vDMwtTULARAbN48JylyPHJEwZSUMAIgbt6sX2fkyOwISY0eY2am+H/dOkX1EB0/Pish12ryZJLhTTfl4LFjYgzHjuWdOfn99zQXEtnnwIHZWKZMGH/9NfrY0aNCjjfdZD43/SbLRG29e9N98X//J+73ihXpXvr559jadFuWP/+sRJzT6Dn2xhvZEUeO6Gv62WdZudd869boturVo9/2zTdZ2KtXduSj0PxZl8zNrizHjBG/+6mnsrFgQfqdo0b597dpt7S0tIAA5hN8BAB7Qe3gYUQAlwLAWIN2BgNNGNWWmpqKoVAo32+vv/49AiBWq3bS9jm33bYTARA7dtxhWq9evWMIgPjyyz/jq6/+gACINWr8m5Tf+X//t86y/wEDViEAYs2aJ1Tlkyd/hbVqncArrjiEM2fOxwce+F1FAB99dFNCfsPTT69HAMTLLz+Mc+eGsGzZMwiAOHDgqqTPIzvblCkLsVgxegl98MGymNqYPPlrnDBhkaNzGjb8O2Ljtz7q2KRJX+dex3r1jiVdRn7cmjY9hACIjz++Kbfs/PP/jTiC/JD08YVCIezfn+7dOnWOYygUwp49f0UAxBYt9kfV7dVrY+41f++9b6KOly+fgQCIw4d/iw899GvE7OJA0n9jPNvgwT9iwYL0QX7PPVsxFAphjx6/IQBioUI5OHr00qSP0c6WmpoaEMB8gA8AYD8A1NaUx7IEHGgATTb+Gm7Rwlozx9tbb9FX8b33mp9Ts2Y4YiuYhWvW0Bd65crWmkYv5NipEz38XnzR+Gv3999pjMWLh1UavzvuyMl9YXTsmIPXXJMTeXCGIy+KxHxBjx1L16p9e5L7Y49lR+wqja+Dn+bkK69k58rx00+dawEzMhSsWjWMpUuH8d9/7Z/XtCldr48+ir5O27YJDWD9+uZz00+yTORWvz7N86+/FtfsiityInZysWlz3ZblxIl0b9x8M90Lo0fTfocO0ffGm2+KebhyZfT4K1Sg37thg4Jz51I7l15qf4Uk0ZuVLDdsULB06XDuM5ufbZmZCl51VU5CVzHi3QIN4H8bBQDgQwD4CwDq6RxnJ5C7pbIqEDiBxIz33nPu0Td1Kp3TqpV5PdlbmG3WChe2tjlxW45nz4qxrFtnXC8zU6S6Yi9hDreSkkIxAmXNH2dFsErH5hbYiYVt1dgTuHx5Yxs3v8zJkycpewTL7uWXnbfx44/i/AMH7J938cV0zrvvRh9jT3WAwKFGD9nZwklszx5RznbAs2bF1q4sS7txN83AIVseeID2p0zBCCGMrsvOaWznp8U55wjP323b6P+SJf1rK2c2Lw8dQqxZk37D9ddH23k/9ZT96Ax+QGAD+N/GaAA4AQAtAaCytBWX6owB0g7eBBQGZjkEYWBixksv0QPg6aftn/PNN3TOhRca10lPFw/ZkyfV+3qedzKcyjEcJoeTO++kmGVaMHGoUMH6IV6njogldvQokSsAMipn4gtAwXB79cLIEqytYcaNUaOovy5daD8rC/G886hsxQr9c/wyJzl0CG92nIG0eO01cf4ff9g/j+PDDRkSfWzNGtFmiRLm7fhFlonErl0kG22A9P/9jzW5sbXLsty5U8GyZckBKx5oUyPOnk37zZtH15Vz/X7xRfRxznRy4ID+R6HfYDYv77qLzRsQ09Kiz+WPyvbtEzBQFxAQwP82omz1IlsPqU4xoCXifwDgNADMB4AaDvoICKAEDpj6xhv2z+Gv4jJljOvs2aP2Ug2HhQbNKtCyUzlu3Soe6HPnRh8fPpyXb63b4hyivXohXnEF/X/xxSIQLJOQt99G7NuX/n/hBVvDjBsjRlB/998vyjiN31NP6Z/jhzl55gxipUpCQwNAoYScguOzASBu2WL/vBo16Jz+/aOPffutmpjqfUAwki3L48cR27a1zlnsJsaNI7loQydxtowxY2Jrl2U5ezYtsZYqhRiPWO+/n8YzbBjtL1xI+1dcYVwXIDpXcFaWOMYZfurWpf1vv419fF7CaF7m5NAzGoBC3+hhxQo6XqeO9+N0AwEBDBAvAgIogcMcTJhg/5x//xUPSaMwEKtX0/Hq1UVZlSoYsa0xb9+pHEeOFOPRpnhDFC8rfjmY4Ykn1ITgnHMQ169X1zlyhAgta0+tAgi7haFDRegGxoIFVFatmn5QWz/MyfHjaYznn4+4fz/9X6CAvUwyjIwM9RL8xo32z+VMH888E33s66/V11vOD61FsmU5fbrQZCcqMwUHcNdqTzkbyDvvxNYuy3LaNOGZ+uOPsY+TP9wmT6Z9XqXg2IUy+DfpEdiTJ8Uxnp+s7XTyjEwkjOblli007uLFjT9s5JA+p08nYLBxIiCAAeJFQAAlNG1KDwAneT3DYZE9wShCPhOTyy8XZY0aUdmyZebtO5Vj27bql/j27eqxsvbphx+s2+IlkZQU0gKaLfsMHkx1H3vM1jDjBmsfH31UlJ09S9oTAMSffoo+xw9zkkn1iy/S9ShXjvZlYq1HXmUsXaq+xqtX2++f5dOrV/QxDq7Nm2znpkWyZTlpkhjnnDne93f6NJEHAMRfflEfe+QRKo81HRzLctIkQQBffTX2sV52GbXx1Ve0/9NPtF+7dnRdtl8EiM7/fPSoOMZz8umnad8qPmiyYDQveb5cf73xueEwYtmyzj+qkoWAAAaIFwEBlMDLY05eqIjCruq77/SP88OnbVtRZjeAtBM5nj6NWKyY+NoHoKVZhmzDZCfq/ZkztCxkx8bsrbeobasMEm5h4EDq78kn1eVdu6rtn2T4YU5q87LyPODlt/HjydHAyI4RkcijTNSM5p0e2IlB7zrJdp16REdGsmXJwdQBEmOzxcuoNWpE285y0PRYnHkQhSzHjRME0CqvtRmqVlV/VGzaRPuVKkXX5UDPAPQRJ0MOsM54/337JiTJgNG8fPRRGvfzz5uff+21VC811cNBuoSAAAaIFwEBjEC2y9u719m5/BI3skfSeuUh0gPUjt2QEznyEl6NGkLreO65YvmGvQGvucbmD3MA9qC+5x7329aD0ZLztGn6dlqI/piT995L42MvXHaeYdvJCy+k/ddeM27jyivVRG3pUnt9Z2eLc9h5RsaECep2zdIbJluWPN8AKH2dE0/oWMDXSU9zyoT8//4vtrZZlu+/L0KypKRYO4jpISdHOG7s309lO3bQfunS0fVr1RJy1H406dk3L1pEZVZ5t5MFo3l5ySU0bj27aBk9e1I9vbzJfkNAAAPEi4AARnDsmHgQOs0Jec896pe6FpyLU7a74geNlcOJEzn26UNtPvIIvexr16b9SZPo+OOP0/6zz9r8YQ4wdmxiNQNG+U1Z21GuXPQ5fpiTbIM5ejTtc2qxW28Vdkpm2qTjx0W+3sqV6e+CBfb6zsgQ7XfoEH2ctTu8mbWbbFmyxpk3Pa9mtxAOi9WBhQujj+uZIzgBy3LEiGzVb9Lrywp66SzZ1rRw4ej6vOQJQM8HGXwvVa4syv74Q2gFrUwVkgG9eXnypLhnDh40P5+dy+66y+OBuoCAAPoD78awnZeUkUYjIIARsPesmTevEZ55xnjZERGxWzc6/tZbouy556JJoR6cyLF+fbVNFGsea9cmbQLHgNML9xAvPvmE2r7lFvfb1gOT3ZdeUpfLIXbYc5Hhhzl5yy1qUs6et7Vr08cAj91oXnz5JR2vV08sV9m1gZPJQevW0ce1pMpsGSzZsnz1VaHhBiDvVK9i0/3yC/VRvLi+cwB71ssafidgWQ4ZoiaAsvmGXeg9x9LSRJuyA0Q4LMK66I1fz3YwK0uYEThdKUkE9Obl8uU03po1rc/npX6/ajhlBATQHwgDwI8AsMLmlgUAdZIy0mgEBDACfhHXr+/8XH4B3Hef/nF+6X/8sSjjl2337uZt25Ujf5kXKoR44gSVnTxJ3qb8cC9QgP4/dMj+b7ML9sq88Ub329YDO1PoxR2sVo2O/fyzutwPc/LGG9Xk6u+/xQuYl38B6PfpgYnv44+LtqZPt9f3X3+J9q+7Lvr4oEFqAmhmnpBsWXIA4549RbBiJ7aQTjBkiLHWFFFoce+8M7b2WZaDBmXnaq8B6IPNKVaujH6OyZrfkydF+alT6uvdqZO6LQ6LctFF6vIGDZyZHiQSevOSr5+e2YMWu3cLbalZGCQ/ICCA/kAYACo6qH8KAgLoO8ycSTd+LMbXbHdmRH44ht78+aKMw4EYvVQYduXIHrva8Ws9Rr2KcTV3LrXvhX2hHsw8LzlG3mefqcutZJmI7AbXXBOtha1YUX2NAMhZRA8cqmj8eBGSg8N9WIGdgAAQmzSJPv788+oxvP22cVvJvr852PFzz4ll9fffd7cPRaGA46xlHDdOv1682m+W5YsvEgFkR6ZYPtY4W48c9DknR7R35Igo56Vh3rSZQr76isrl6AWIZK4AIMwY/AS9ecmhbkaOtD4/J0d4e8sRFPyIgAD6A92Bcuzaxb0AUNKjsThFQAAj4K94Ti3mBPyl3KCB/nHWwskaqTlzqOzaa83btivHzp2pPT2bwsceM17mcQtGLwuv0KNH9LI6g8mhVjtoJMvMTMRmzciZx6n9p1M0aUJj+/prUdaqVTQBvPde/fM5VNGXX1IGETNiosXmzWptoxacCou3V14xbivZ9zePtX9/4eEZT+gULfbtEyYVABRahTXrWsyYQXVuuCG2vliWzzxDBPDZZ8U8ceqN+uGH+s8xjg4gL9vK80HvWcTPKK22mE1eYlmi9hraeRkOi9iXeqGh9MCyD4U8HKgLCAhggHiRJwng2bOUt9RNcHqubt2cn8vecnpeduGwePju3i3KmTSapZBDtC/Hiy6i9hYtij528qTIgelVAFezYLNegDMY6AXf5Wup9Ug2kqWcV9cLBxkZfJ3kMC8cW42X28w+ROSPCSb9djVf69aJfvTsodgxie3CjDKqICafAMoaYPbCdTMIOV+TihXJwclsOXDePKp75ZWx9cWyfOopIoAvvSR+n1NSy+GRtN7K7Oyxdasok+c9AHnKyuCVjZtuUpdzCB4/pkzTzks2jSlSJDr3rxHYU3/oUA8H6gICAuh/1AGARgBQMNkDMUCeJIAcdNjNWE1s/6QX5sEKcsR8begG2c5GPvbrr1RWoYJ523bkmJkpQj/8+ad+nR07yMPNq6wJq1Z5u8SsRZcu1N+oUdHHQiE6pk19ZSRL9vwDIDtJL9NcsWe2rI1gD2p+4QMgtmsXfa72Y4JJsDaArxF++EH0ozfv+MXHWWrMPoaSTQDZsWrYMOHsFMvHmxFY+2cVNgSRgrkDUE7sWMCyfOQRIoCDB1MYklieR6ztHzRIXa6NDYgotPa81a2rPmfiRCq/9VZ1Of/eWOylvYZ2Xn72GY1VLyyUEV5/3f355AUCAugfFAaAV4Fy8b4CAIUAYDoA5ES2LQBQK1mDM0GeJIBs+9S5s3ttGoUVsQs2RN+xQ13OX6DFi6ttzA4cENoWM9szO3LkpZxSpRJjx6aH9etpDFWrJqa/O+4wtkP6/XehkZXlYSRLbqt8efpbqxal+PMCTK7kTANbthCBb9OGPmoAaFlYC23aQbuhhBj84gag+aoFx6bkJTCzkD7JJoDyBwDHL9QSFT2sX08fX2bgezYlxd48YE2alkDZBcuye/ecXM2T0VKuFdge8qOP1OUXXEDlcgYgdtw67zz6qw0U/cEH+s9ZDhCdkpJYR4m9e+l3mWnytPOS821bBYCWMXs2ndOsWZwD9hgBAfQP3gGAowAwEQD+AIAvAWAbAHQBgM4A8CsATEva6IyRJwkghzOpUsU9wsOBXrVfznbB2UBWriQtGxtb//wzlZ9/vrr+6dPiZWwmfjtyZMPvq66KbexugEmXXvw9L8CG3XpL2mfOCI/nw4dFuZ4sw2ERT2/hQhEYN9aYblbQW4pDJNJx8qRIx6ZnG7pzJx0rWZL2zTyh9cDBwY0+PDiNIHutm3l0J5sAMlkdO1a8sPU8m2UcO0Ya1EKFSLtlBHaoMksbJmPjRvE8igUsy3vuIQL4zjuIn39u7zdpcd11dN7nn6vL+Zkpe+6y5pmPaT8KjMLb5OQITbRR+ksvwGTO7NrJ8zInR9j/mWXW0eK33+icsmXjHrKnCAigf7APANpF/q8P5Bl8i3S8JQAcSPSgbCBPEkA5eOmuXe60KS8pxYKWLcXL+IILKIzAzp3CPqhp0+hz2NtMtg3Uwo4cefnayHM0EWCtCZMTr2HlAcs2j3I2Cz1Z7tkjtBmnTwvbTABvloL5mhvl2eVlOe3yNaLQNHFctr59aZ+ziFiBiRJvWnOAFi2o/MEHjcfASDYBZJL6ySfC/lQbrkSLxYvVv/+VV/Q/INm5htP1WWH7dqofSwxRRCHLO+4gAvjhhxTSJhatolFaSs4eI+c556VzJv4FCqjlYRbgWv7gTRRat6Y+jUIkIarn5Zo1YmXEyTQ9fFjIw4/BrhkBAfQPsgCgmrR/BgDqSftVACA7oSOyhzxHAOVAv/wCcAN33qm/dGIXcugG3t59l2L/sVZFi+rV6di6dcbt2pEjOwOMGBHb2N2AvKSdCNx0E/U3bZr+8TZt6DgHXEbUlyUbussG/OxVWr++u17B4bB1LEYmM3qBaDnUDmt6naYg0+b61Xq1socxt1uvnnFbySaA7DmdmqqfsUIPHA+uUiUhgxdfVNfJzBTmHLK9nBn+/JPq62XasAOWZfv2RADHjxfp2/SW6s1QujSdt22bupw/UOV0lRxLkfNTA4i0kYgi3WLv3tH9XH45HfvqK2fjiwdXX019tmxpXEeel2xP63QZ/exZIY/jx+MasqcICKB/oI0FqI31VwnIFtBvyHMEkL+2eevZ0512ncZU04JDI/DSAQDZJJkFfOb8lIsXG7drR44NG1I7cmiRRMMo24BX4BfarFn6x3l5VH7B68nyySepnuxBevy4sNUzC4XiFJmZ1i8WdqbR0/zwkt1tt9G+kcenEdionzctCW3UiMo5z27FisZtJZsA8lLnnDnCJq1IEXOTELb1HDFC2A0WKkQ2tAwOCF+xon3tT7xzn2V5881EAD/9NNre0w7OnBHnHDumPsbPN/mDmef+K6+I8+Q4gWYaZtYWa5eavQTPz3LljK+zPC+vuorqxxL5wEpT7wcEBNA/CAPAAwBwW2TLAIBHpP1uEBBAV8BpfXhzyxMt3gfa11/TQ6NXL2H3V6oUfT0D6DuX2MnkYCVHRREewPv2xTZ2NyBrZu2+sOIBp0EzSms3ciQdl7Mz6MmSNRkzZ6rPZ1u8lBRa3nYD8kvdSLO4YQMdr1Yt+hgvyT38MO2zRsvu0j87FvCmNT1gD2WOa1esmHFbySaArK1csEDtaW829ziEDi/tsx1hq1aCULD28/777Y9FtueVM23YBcuyZcucXPnLHt9255+sidQSJD2nKdmLvESJ6L44d/jgwdF9xfvBHAv4+gGobXtlsCwPHlRyte0HDjjviz8AN2yIb8xeIiCA/kHYxhYQQBfw6ad0Y/ILQPvVGivcWNLgr/+cHKEFZFsZPdtCXnb+8EPjNq3kyM4X55yTPA9gRPrtfD3S0rzvr1kz6kvOriKDc3rKsc20sjx1SsS8278/ug2eE3Zz7VqBbYsAjK+VmTMNBz9++WXa5/A1dsmKHO4GQK35QhTOMLIdpFHYoGQTQNmpIRwWH0F61xER8ehR8Zv4cbd7tyBZs2YhZmdTwGcAWi63i3DYmpiYgWV59dU5qo8adkhatcpeOxznUe/j4b776JgcN5MdqcaPF9loZA9ps2Drdp5dboO9lQFIEaAHluXkyVlR978T8KrKN9/EPl6vERDAAPEizxHAN9+kG7NHD4q75dYLmvNbumXUzF/cvOnZKrKt2WuvGbdjJUf2Fow1CK2bYDL111/e98Uvar3A14jChqp4cbGUp5Ul29tVr67fxs030/EpU9wZ89691F7RosZ1zJxp2NaTYx8ahekwwhtvqOfk2rXq42XKUPmWLaLO33+r62zZQnZ3mZnJJYAcp4+dHZjA/PKLfv2vv6bj2mw9HFO0TBnx+2P5qIxnyZDn5eWXEwFcuJDKeQnTTixCRPHRo5fm7+GH6ZicOvH664X2u06daLJpFmuTnebM0gW6jcKFxfUxCn7OsuzalWSptfG0C15hcOvjzwsEBDBAvMhzBJBtu/r3F6Fb7BrBm8GOQ4YTaJfbFiyIrmMng4GVHPkF9uCD7ow7HpQs6WzJKh6wPZCxJiBau6eVJS+h3n23fhtmsQZjAWeMMfMW/esvqqPnTMN2j2wywPmk2SbQCv37q+ek1lOUX7D79+tfy3CYMtcAIP74Y1ZSCSB7ea9eTfv8AWfkuc3Bfe+7T11++rTQtAGQ2cZzzzkfT7lydP7vvzs/l+dlo0bhXK0mIl1XAMq8YQccvqZt2+hjnNmEtceIiJdeKj6i9MLEcP/jx0e35zQEUbyQHTMAjMM0KYqCc+aEsFy5cFwf9Jxz++OPYx+z1wgIoD9wm4PNCa4HCix9EOgid9Qcnxwpl7efHfbhKQGcMWMGHj9+HNPT06O2MxojKL06vJ0+fTq3Hj2U0nHUqHScNCkdAdKxSRP9uoiIGRkZhu1mSC5vtGSbgevXW9dFRDx9+rTpmGUtCsBpXLkyus4bb9D45ThbZ86cUdU5fvy4So4yzpw5g3fcQW0MGRLdflhaZzx79qzpeJ3UzZGs4zMzM3PLy5alsaxda11Xb8vOzrZdt1697FwSoyiKbp06dWg8S5Zk5c7J2bNn4/Hjx/Ho0XRs3JiOv/WWOCdLsuK/774sQ9mmp6eryE9WVpbpeBVFyfVWrVQp27Den3+mI0AmAtCyena2qNugAY13wQLaHzeO6vILPycnx3QMfftmSnMyB0Mhcezff6ltgHTcty8dK1c+iwAU4y4cDmN6ejquWSPqzJhxIndenpUi83Jdo83JfW9Wt2JFGsdPP9H+lVeeRnn5VNtW+/ZUf+jQ6GfEL79k4KhR6fj99+l44oT5fW/0PKlWLR0BMlRaVatnBENRFJw5cybWrXsKAdJx8WI6/uCDNOaXX46+7/Xau/VWqi/b7HHdvn3p2FNPifrnn5+OAGH86SfEa65BBDiL06eL461a0TkTJkQ/I/r2PYsA6di7t7NnRKx19+3juUf3/XXX6dc9fvw4DhnyNQKkY6lS2bnhX4yeEXr3vaIo2KWL8XNVrmvnvvcKAQH0B/Rs/bT7vDnBLQDwBgDcAcYE8GsAqCxt5znsw1MCCNEENXdrp8l1VaJECcO6LSW/f7LLKm9Yt6km4F7NmjUN6zaUEtcWKYII0NCwbk1N8tSmTZsa1i1fvrwqwDBASxNZlFCl/WrXrp2p3GTcddddpnXll0z37t1N6x49ejS37hNPPGFad4+0ztWvXz/TupslQ7NBgwaZ1l2zZk1u3WHDhpnWrVx5BQJQSrUPP/zQtG6jRgswI4Pm5NNPP21ad5bkVnzzzbNM634iresvWLDAtO6HH36Y6xxUqdIK07oAwxCAbBTXrFljUXcQ3nADjWHz5s2mdZs06ReZj4gAe0zrnnvuEwgRjdrRo0dN63aXXNzT09NN6951112qOWxW18kz4rzzWiJIGpvy5d1/RiAiNmxo/IwAqKnSqlo9IxiKomCjRo0M66aklFCNweoZIa9iWD0jAOhjlWLs2X9GNGuWnGcEwBoEQDz3XMS33zZ/RjRvviK3XatnxAJpieaTTz4xrSs/I2bNsv+McBsBAfQfWgPAegBoC3RRSkX+XwsAbeJoF0GfAIbiaBMgDxJAsvVx9+EuHBjcI4CIIreqFQGU81Q6IYB33JF/CWCFCkQA162zflCriZ8AACAASURBVLgDLMB27RAzMhTs1auP7Yd7hw7uEkAOMVKjhj0C+Pff9gjgNdfQGKwI4MUX2yeAFSsSAZw3L28QwIoViQByXuRkEUDZJtUtAliokDMCKIevsUMA//qLPaLtPyOuuSY5z4iSJddgwYJsBmT+jOjbd0VuuwEBDJAIbAaA5jrlLQBgaxztIugTwBNAKeh2AMAEUMcitIM8tQQs7EDSce9eOsbLjuvWqesy7CwBnzjB7WbgP/+Y12XYWd7hWGPFi+vXXbSIxi6HsnGyBLxp0xkESMeSJdPx1Kno9hO9BHzhhfR7Fi6MbSnIyRJwpUq0FLRpk/nyztKl6VisGHkEVq4cxgIFMpGXMadMMV/eGTCAloB79rRe3rGzFLRoEc2HSy81XgJOT0/HlBRaqt2/XywB79pFYy5QgJZr09PTcc4cWgLmjB1WS8Bdu6qXgD/6SBzbsoXaL1qU9lu1oiXgzz6jZd1t28TyL5lgJHcJuGBBGsfOnbT/xBO0BPzSS9F1Z8+mug0axP6MsKp71VW0BCyHJXK6BFy27CnVs2zqVBr3VVdZLwH36kV1u3XTrzt8OB3v1InqHzrE1zKM6ensJXxWteTZsCHVmT8/+hkxahQtAXfo4OwZEWvd5ctpLLVrZ+c6AC1cGF33zz+PY8GCJxEgHbdvF88Tp0vAb75J/XXpYl43WAIOIOMMAFysU35J5Fis0COAXQCgPQA0BoAOALAJiIAWNWmnKNBk4a0aAGBaWhoqiuLqlpGRgaFQCDMyMlxrc8cOBQEQixYNY2YmlVWrRsa+q1fH3u7evdRuoUKiXTe2PXsULFkyjC1a5OgeX72a+q1WLRyTHOfMIWJz+eX67Sd6u+wyuhbz52d53hcbeW/aZF13/vwsLFw4nEt+ypcP4+jR1mN86y0imffd5458Z8+m63XVVebtlSpFY92yRZStXUtzpWJFMVcWLaL2GjUynj/yxqnGeHvvvezcY7/+Su2XLUttdepEdd9/n+qMGpWtOveddzJdv7/tbmfOKLnjOHSIyvr3p/E9+mh2VP2BA929jnpbq1YcxNn53Od7vGRJuu5bt1L5ihV0fevWNb++mZkK1qlD586apd//2LHUVrt2JIPdu9XPvEceIRkNHCjkV7cuO1JEtzlpErXXpk1inj0LF3JYlzDefjvJevjw6Gv9+ef04VK7dnzjGj+e+rvlFn88W/W2tLS0gAD6DN8BwHKg1G+MygCwFABWxtGuHgHUogoAKEA2g0YYDDpq6tTUVAyFQr7f3nzzu4gm51RuWeXKpxAA8a23Vsbc7ujRSxEAsUQJxfUxT5nyFc6aNU/32EcfLUMAxJIlM2Nq++mnNyAA4hVXHEr6tQmFQtigwT8IgPjiiz973leJEvQCGz16qa367733DQ4cuAonTVqEc+fa6+PxxzchAOLVV//lypj79SP7pcaNj5rWK1PmbIR8Lc8tGzToRwRArFnzRG7ZkCF0P1StespW/02bHlKRuO7dN+cee+cdWlIvV+40hkIhvOmmvQiA+MADv2MoFMJLLjmKAIgFCxIp6NHjt6TNs5kz5+f+hunT52MoFMKHH/4VARCvu+5AVP0rrqDf3bPnr56NqVmzgwiA+OSTG2JuIyWFiM3EiYswFBLPpWLFskzP+/BDeo6kpGTj9OkLdOv07bs2QqBo7r3//nIEQCxVip49t9++EwEQO3bckXtOuXKkVX333RVR7b3wwmoEQLzoorSEXHO5v7vv3oYAiK1b742q1779HwiA+L//7Y6rvxdfpP4uvDAxvy+WLTU1NSCAPsMFAPAbEBHbFdkUIM3cBXG0a4cAAgDsBIAXTI7naQ3gZ5/RV9n114uvsoYN6YW0eHHsWqc1a4hMVKliT5Pi1sZf4UWKxKYBHD6cvtrvuccfX6k33JATWTb0XgNYvDhd9x077J/jdE66reWYOJHaa9vWvL0aNei3/fyzKPvkEzq3VStx7o8/Utn559ubtzfdlBN56VP7AwYIDcq331JbF1xAbT39NM2t557LxiNHFCxUiM658cacyLnJ0wAeOSI0gBkZ6mvVurVatseOKVi0KI193TrvxtS5c06ELEVrpezMyy++COX+pgMHqDwtTfzO48fV5xw7Rhrg48cVfPvtbN3fLm+zZmVFPmaozsqVWRFNGV3vV16hNh5/XIz/vPNIbr/8Et3eggV0/qWXJuaZKd87U6caa9Lr18+JfBicjau/JUuyIgQwse8EJ1ugAfQnCgDAzQDQGwD6ADl/FIizTTsEsBwAnAVKO2cXeSoO4PDh0bG85JRQseKHHzDy8ot/jE7wzz9CG2OUQ9RMjpwL9oknPB6oTSQyPRRnfnCS5snpnOR0cNddF+MgNeBcvh07mtfj7DE//CDK3nmHyrp2FWUirIy9/ps3xwhhpL9yjtclS6js4otpX55bnH2ncWOR2vCFF7Jdv7/t4tAhGkOBAiKjyoIFGNGGq+vOnCnubS8z5XDWjKFDnZ+rKAp+/vm83GfBiRNUHg6LANNyPMbMTA7bQincKlSg//UCNjM4EPZll9H+V1+p94cNo/1u3cQ5ZsGtv/8+sc9MOej5b7/R/6VLq68pB1ovWDAHjx6Nb15u3IgRpUCcA/cQgQ3gfxvnAMBlkQ0BoG/k//Mjx0YAwDUAUAsAbgCAVQBwAMjz2C7yFAHs0yf6xcUvtdmzY2938WI2zo9/jE4gBzc1ugRmcuSXsRzcNZng3Kpjx3rbj5x6y0nGBqdz0u158d57GNHYmtfjDDfLlomyF16gMjno+datVFa2rL3+r7hC/B4Amj+ML7/EiFaF9uU0c0w2Xn0V8fnneRzJI4D8opdzFf/4I5XVqaOuy9ks5GeGF4gnMLKiKJiauiB3Tss+Khyk+scfRRnf99pt1y7jPtgDnTOhTJ9O+xxg4aOPaP+OO2g/HMbcXLp66e04Z3WiCNLQodTfgw8SAeYUfnLqOna6u/DCtLjn5Z490XPMbwgIoD/QGwCKOaj/ONgjaTcA6LqWTwaA4gCwGMgDWAGAfZHyGg7GAZDHCCDnn5TTALVpQ2VOcndqwZqea6+Nf4xOEA5jbkiDgwf165jJkdMx6eUZTgbuuYedC7ztR847/M8/9s9zOifd1gy/9Ra116OHeT09rTZrmN58U5Tt3i20QHbA2VNuuIH+PvKIODZjhjiGKLKMsLawcGHSvA0aRPuPPZY8Arh9O41BzqjCZPjcc0XZmTOUIxtAZAzxCv36UT/9+jk/V1EUnDLlq9w5LYdx4XRw7F2cmirm/rx5iGvWELm1ylazZo24nohCG3377bTPWl4OKi5/nLJGUganWixd2vnvjQUvv6z+aLnlFtqXU9Hx++Gee7bGPS9FZAiaR35EQAD9gRwAqOCg/kkAqOPRWJwiTxFA7cMQUSQ0nzAh9nY/+4zaaN06/jE6RalS5l/vZnKUk7n7Ad2703j0kse7idOnxcP55En75zmdk7zEWrlyjAPVgNP2Pf64eT09rXa7dlQ2caIoM0sbp4e6dYWWB0BtSjFpEpXdcgvt89Ipb/ffT+WsienePSdpBPDXX2kMFSuKssOHxbIwRxOaN4/KqldXkyovMGCAWDJ3CkVR8OOPFyEAmTbIuP12anfMGFoGLlEiNq0/L5tWqED7b7+tXvKdPZv22dzh+HFx7TMzo9uT556XS+sMTmX3yiu0z6k2WYN58qTQCo4YsSLueZmTIzSghw7FN3avEBBAfyAMAL8CwAabWxYEBDAmcL5eKV4wdu5MZR98EHu72q/hRKJSJerbKIm9mRxbtKBzpbikScVjj4mlQi/x77+xfZ07nZM7d1IfpUrFOFAN9JZx9UBZGdRabdYKzp8vyv7+W8hBCqFoiGrVqG7PnurlPkSxBHjnnbTPNmO8cYqzkSNpv0uX5BHAtWtpDDVqiLLMzGitMGtN5aVuryAvUTqFoig4btwSXW3uo49Su4MGIT77LP3fvLm96y1j1y46t2RJ2meN2tNP0z7HqGSbQD07SxmyhkwKA+kZHnyQ+mIbyz/+EAT0xAnEKVNov169MM6d6868pPSgpF32IwIC6A8MimE7NykjjUaeIYBZWXSza5dL3VgGZQP7e++Nf5xOUacO9b1qlf5xMznqJXBPJthGk4PxeoW0NGfEh+F0Tlq9BJ2C5fPii+b1br01WttXo0b0UubJk0IOmnjFuihXTixTyto+RLXNHyLNR25bNo0QH0vJI4BGS/MlS1L5zp2IioJ43nm0/+233o9p1Cgmxs7PVRQlN5SL1p6TNYs9e3IWJLLXdArW2BUsSHP5ySdpv39/Oq6VqZV5gWyGkZbmfDxOcddd1NeHH4qyCy+kss8/Fw5oAwa4Z5pQu7b5sznZCAhggHjhewIYCiE+84xYokpJUb/0+Qv5tddi7+O116gN2SYqUdAz+JdhJkcmBXIC+mSCHQT69vW2H5mYOYHTOSkTLE3yiJhgV0OqfdmFw4hFi1KZ7JEpa72OHbPunwnSm2+ql88QxT3w6KO0v3mzaHvGDFFv8mQqa9s2eQRw2TIaQ6NG6nK+H9asEXUqVHCuLYsFbDPZoYPzcxVFwZEjv0GAaI9u1syWKYO5x2MRuXZJ9/776X9Onaf1et2yhfbLlTNuk/KnI+7b53w8TtG2LfX16aei7JlnqKx9e6Ec2LzZPcUD5Z0nj2k/IiCAAeKF7wkghzjgTV72QXRH62R3ac4LsF2j0Ve9mRzZfnDnTo8HaROJCkvz55/UT5Eizs5zOiezs8W8k9Kgxgy2kZQN1/XAL+cRI2hfXvKWNX2yN7Sep6YW/JIcM4b+XnmlOPbSS1TWpw/tnzpFL/9GjdSEg51FWrZMHgFcuJDGcPnl6nL2bl60SCxxymFNvMTUqdRfLHbEiqLg8OHfIoBw0mCwbR5vsTiZIEY7dWjth7XmDuvX0361asZtsoZ1y5bYxuQE111Hfc2ZI8qY5PPWtKm7K0+tWlG706bF3ZQnCAhggHjhawIoe8my/RIvUTGYvMWjdXrqKWqDDYwTiRtvpL6nT9c/biRHeQnm778TMFAbYM3SQw952w8vT7E9k13EMifNYqE5BYckMYvXhoj48MNU7403aJ9fzuecE12XNYNWWhh5vjCJ45h/iPTxo12e/vdfIoIyRLiY5BFA9tq/5hp1OXs3T58u7qtEOUjFE0lAUZTcLEfaZW2Ot8fb77/HNj45rMvBg8J+eOZMOn7woNCqh8P2POATuQJxySXU15IlouzsWeHlDUCmPG4SQPYq/uijuJvyBAEBDBAvfE0A09PFzX3qFC39aQMmc1iKXr1iHysbGMshNhIFPXsvGUZylINIJ+EdrItE2VLqhQGxg1jmJGugf/vN4SB1wB6d48aZ1+MPEq19ljbGHaLQAu/YYd7mqVNivnDQ57p1xXG7phQcG/GSS8JJI4Acw45D1jDYu3nUKOEtu3lzYsakDbTsBIqi4Guv/aC7rM3kn0h3fGNkmfzxB3m2AyD+9BMd05o7sHZN/kjQgm3wEmFjaWSPx7FHCxSgoPBuEkB2luIPMb8hIIAB4oWvCaAdI3y7sdXMcPfd9jQzXoD7lmMbyjCSI3vBOdWCeQmtJ6lXYPu08uWdnRfLnORAvD//7HCQOtCzY9KDNqZcKGRMAMqXt0dQZY9h9qKtWlUcf+ABKmObMCOsXEn16tdPHgEUdojqctm7mT8QvA7/whBycX6uoig4YMAq3WVtmZhZfThYgZ2AeKwAIoyS1txh/nz6v1kz4/Y4sHg8WZjswuhDjOdCmza07yYBjCe2YyIQEMC8hWbJHoAOfE0AOdioWRgOu9kVzNC+vbkWzktowxtoYSTHdeusbXQSjY8/pjG1b+9tP7GmaYplTlo56ThBy5bqZTcj9O9P9ThEB4e44JecDDaNWLfOvM39+6leSop+BhFe7pK9LPWwejXVq1kzeQRw3Dgaw223qcufe04slQOQZ2iioBeaxi4URcGXXvoZARCvvlp9LBwm27ZatfQDMjsBL9myx3etWurjsrnDrFn0//XXG7d3/fX25rMb4Bh/e/eqy8Nh6p9j9blJAN94g/rs2TPupjxBQAD9h3OAsnTIuAwA5gMFjPYbfE0A2RBZ1lRowS+DeGL4ybZDiQaHYxgwQP+4kRyNPCGTCTaEv+kmb/vRZjWwi1jmpJWTjhPYbYtfPOyVbqZZ5TBCcqowPch2hPv20f9Fi4rjHGh60iTzdkQQ5uQRwPffpzF07qwuZxtU3uKJDOAUrJU285o1gqIo2K/fGgRQe2YzsrPd8UKvX5/GyKsOt96qPi5r2fijQ6tllcHZOKzmTLxwEnLGTQKYqBWNWBEQQP+gOgD8CETyFAB4FwBKAMAUoMDPs4Hy9voNviaA2vyVetCmMIoFV15JbcybF3sbsYJDpzzzjP5xIzlqI/f7ATym5s297Yfzvso2bHYQy5x00xOQvVQXLzavN3w41XvgAdrnIMN6Zg4XXUTHVqwwb5MzQZQvT0t8/ELlJVIrZySGSAGWPALI8tE6hHGMQt7c0NraBTsmFS/u/FxFUbBPn3WGWl63wPOP7em08Shlcwc7H9ZuBOG3A6usJDLcJIDTplGfrVrF3ZQnCAigfzAVAH4BgKcAYAUQEVwPAJMAoHYSx2UFXxNAtkNp2tS4Dqes0vtytgvOkbp8eextxIpXX6W+jdKDGclx4kT9r/hkYsEC6+vlBtiG6cILnZ0Xy5y87Tbqyw1v0gYNhA2WGT74QK3h0mZtkCGHPjGDvEQpO4RwWBnWToZC5u2IEDzJI4BGS3Ny+rqCBZ2lCYwXnIoOwHnQcEVR8MknN3h+P199tZogaz9qZHMHO6Y1nGnF69SPTsI+uUkAv/qK+tXaZfoFAQH0D/4CgOsi/1cGSg/3YvKGYxu+JoCc+PzGG43rcL5POaaZU7hp6O8UWm2PFkZy1GZu8AN4Wbpx48T0Y+ahqIdY5mTXrtTXyJEOB6mDmjWpLTmbhx4mTKB6HFSY86Dq5X9l7bXVsjKHE6lXT23wz0tqemE29CA7k8yZkxwCaJR3d+lSMbZYvHHjgRyr0elyraIo+OijmxBAnZ7PbbA2mzdt+kn5I4Cd68xS22mziXgFDkp93nnWdd0kgJwNp3btuJvyBAEB9A9ygIgfIwMALkrSWJzA1wTQyNhbBoe0uOSSmLtxNdSHU4webW5nYiRHdhR46qkEDNImZJLhJTjkRpMmzs6LZU4+8gj19frrDgepA6u8z4zPPkPVcqCZpsVuPmgmR0yaOYvDn3/Sfr16tP/99+btyNrDmTPnJ4UAGmWcYZthACIniYSi2LdTiz5XwYce+hUB6IPDK7CzGwAFBdfm8L3pJqEZtBNeK1GZf4TjkXVdNwmgnrOUnxAQQP8gBwAqSPunwN9LvwxfE0DWct13n3EdN0gHx8favTv2NmIFhzEw8lg0kqM2VpwfEI8npBPEqvWNZU7qBUiOFaVLU1vbt5vX+/xzqteiBe2bBaRt3ZqOffaZeZvasB6cWozHYtebWDbI/+yzhUkhgEY5ldkOT295MxEoXJj63r/f2XmKomC3bpsRIL5wVlbgFIMAZDuqhRynkgPsG9kmIwrzFU4f6BWcrCy4SQDlMGSJCifkBAEB9A/CAPArAGyIbNkAsFna581v8DUB5K9QI/s4xPhJR06OeCgeORJbG/FA+7LXwkiO2nRhfgA7GlSo4G0/c+ZQP04dYGKZk25qWrVaNyNoyVqbNrQ/ZUp0XdbqfPyxeZvaeValCu1v2kT7TtJ6paRQ3UmTFiWFAD7+OPU/aJC6XF6GTcbHnF2Cr4WiKNi16xbPyRTHegQgT2At7r2Xjr37LmLv3vS/WXYkDvyu94EeDkcH7Y8VHAdTGyJHD24SwDNnhLziDcHjBQIC6B8Msrn5Db4mgH370s333HPGdeIlHXK2kfT02NqIB5zX9Ior9I8byTGZsQuNIDxEve2HU5lpM0FYIZY5yR64ZrZQdiB/aFjlFdYu17Lx/ty50XU7daJjo0ebt6ldVubwMZxZwUnKO46zN2bMkqQQQLPMPc8/T5tTRww3wNk1Nm50dp6iKNi58zYE0Hf0cQuPPSbmoF6IHDkbjB3TB/a67thRXb57NzmCValCGYvihXbumsFNAogo4g+6kQrSbQQEMEC88DUB5JyoZvG8du2iOnp5Uu3gyBHxUEyGmp9D3Rh5tBrJkZOjz56dgEHahBNvvXjg5IUgI5Y5qfXIjRWnT4t5ZuWdqjVrMPNSv+ceOmblpKJ1LJHbDIfF2A4ftv4tnH3k/feXJ4UAsqbqnXcS3rUptKTaLhRFwY4ddyAA4rPPejM2RGHOAEC5i7XgD+7nnxfaQrMVBr4PW7cWZUuWCG0ygLVXuR2wnXSnTtZ13SaArCl3SuoTgYAABogXviaAXbpYv9wOHKA6KSmx9cF2QyVKxHZ+vLAKamwkR36BJzLWmRX04st5gU8+oT7atXN2XixzctKk2PrS4tgxIRur7rVmDeefT/tr1kTX7d6djlmF4tAS2WbNaH/BAmfkFFHOKLHCdQJ48CB91JnBbtaSRCPWrDGKouCtt+5CAH1Pb7fw0kviOu/cGX1c9q5me0EzGX/xBdW55hraX7KEwu8AiL/aZfpYMGwYtdWtm3Vdtwkgx9n85htXmnMVAQH0D1YAwDcW2/Kkjc4YviaAnJ3AbJnzn3/EQy0Wm5NE2a0Z4fffqX+jDAJGcrRrtJ9IxBMKwwnGj6c+zLzD9RDLnOTYcmYpsezg4EHxYrRantTOyXPPpf2tW6Pr8rLdq6+at6kNN8RpvGbNcn4Pscfwm29+5yoBzM6mkBslS5o7Utx6q//MHxAFqXYaUF5RFGzbdjcCIA4e7M3YEGklBYCW+7Ozo4+PGUPHK1USv8XMtnTxYqrDERh42fi220QYGaf3qB6YmNrx7HabAF57rbHGNNkICKB/MNJk+xgAToPzVHDXA6WQOwh0kTtqjhcAgMGR42cA4FsAaOSwD18TQA5xYZZrMiNDvLxOnXLex88/07navJiJwp494qGsByM5lixJ51lpSxKJzExxLY4f966fWFM0xTInrWw07cKJppnTtpUqRWSxUCHaP3Aguq5ZjEAZ/PLn9HJt29L+p5+q8wTbwcUXM+n80VUCyEvfAObZJdgpxsrzOdHgXM8zZjg7T1EUvOmmvQhgnBPcDfBHgNFczsgQWkzeUlON29Nm5JE/2DlYuxsRAXjp+oUXrOu6TQD5N1k5WSUDAQH0N1IAoA8AHAWAnQBwj8PzbwGANwDgDtAngC8AwMnI8cYAMAOIDJZy0IevCeBll9HN99VXxnVk4/q//3bex/LldG6ycupaLZvqyVGOOeaGkbVbCIcpZAKASM7uBexkKdBDLHPSTjpCO3ASzFa2pZSXZ/Vu03796Fi/fuZtarOJdOxI+2PHOnfe4eDTr7zyk6sEkOPKAZjnk5a1l34C58b95BNn5ymKgtdf/ycCkAeuV+CPGTOnum3bhJOPleZr0yaqU7ky7XMw8a+/Vq8GxPJclsG24G+8YV3XbQJ4333Ut9/sTREDAuhn3AcAfwARsieAyGA80BLAAgBwCIgEMooCwAkAeMxBu74mgHXr0s1nFZzWbngNPbiRSSQeWHkh68lRzsbgVqgFt+CV19ypU8J71ip7ihFimZPr1lFf1as760uLDRuonapVrevKHwUci8zoA8EsTZyMZ55Rv/zZkWLkSPEir1TJ3m9hAvbcc2tcJYAXXih+a6FCZDepB85YYZX9JNG44w4al168RjMoioLXXnsAAby3a9yzR3/5V4acUs8sxSBrqtkBr1w52ueA+vz8tsouYwW2BR81yrqu2wQwUdlOYkFAAP2H/wHAJgD4FwAGAEBJl9rVEsA6kbImmnpfAsCnDtr1NQGsWJFuPo5VZgSOv7Vjh/M+pk+nc83SzXkJqziEenKUlwj9BrZX27bN3XYbN6bgxadOUfgPAMSHHnLWRixzkrMBnHuuwwFrwGml6tSxrnvypJgTv/6qfslqYTcY7xNPUL0BA2i/Z0/aHzIE8aefnJlB3Hwz1e/TZ51rL1rWQqakCOJgtMTLKwNW+Y8TDY7NOXy4s/MURcFmzQ4iAHlr+wFvv01aWDOzGrZrLVBAralm4t65M+2//XZ8Y3GyDOs2AfRjxiVGQAD9gyuBHEHOANn9lXe5fS0BvDZSVlVTbzwALDZppyjQZOGtGgBgWloaKori6paRkYGhUAgzMjJibqN48TACIG7fbl6vUiWqt26d8z7GjctCAMR27XJcl4HT37ljhz05rlqVFbGvCSdtzEZb5cr0W9auda/N06eV3JfLpk0KDhqUjQCIjzyS7aidWObk7t3Ud+HC8cl6yRK6ZhddZN1ORob4vYsX03lVquifN2RIdkQbaj5/e/TIQQDE114jmT3xBJ330kvZjsamKAp26EBtPfHExrjub3kbNozG06pVDr70Ev3fqZP+b7rwQppjS5dmeTaPY9kefpjGPWiQ83nZpMnhCMnx128y29LSxDzduJH+L148jJmZdPz110ked98d37O1RQuab6mp1rJx470jb0OH0m+4777kvR+M5Z8WEECfIAyU//ddAOhtssUKIwJYRVNvAgAsMmlncOQ81ZaamoqhUMhX25w5X+Y+XKZM+cq0boUKGQiAOGzYt477efhhysHZvPn+pP3W0qXPIgDFVbNTf/DgHxEAsWbNE0m/TsbXYqVrbU6ZsjB3Lrz11kq8++5tEdL+h+e/Z+pU0ffnn38ZczsDBqyKaACPW9adOzeEBQsSyenXb01k6fiUbl3OIduihfn8ZRuzBx/8DUOhEHbqRHHnbr99J/bv/xMCINataz22UCiEzZvvRwDEhx/+1TU5N2r0d26bI0asQADEYsWycObMeVF1K1VKz50LXl9/JxuHcrnzzu2Oz23c+Gju9U7277C7zZkTyr03XnhhddQ8FF9uiAAAIABJREFUHTiQ5ny1aifj6qdOneMIgDhw4KqE/8ZevTYiAOKVVx5Mury1W2pqakAAfYK9ALDHYtsdR/tuLQHnGQ3g0aPi6/LUKfO69evTy3LZMudfz/yV2qNH8r7watak8a9aFT1+PTmmpmZFSKv/vkr5Wixf7p4mY+tWMRfmzcvC556ja9a7t/cawPR00feRI7H/hlmz6Jpdc429a1aiBMnxvffot15xhf55H3xAxzt2NG+3Y8ecyEcGyax/fzrvsceycfp0Gtt119kb2wMPUFvdum12RdNy+LCChQoJbX9mpoLVq9P+F19Ez6Nq1ejY6tXJn+/y9vzz2ZHlQufzskGDfxAAcdasvKMBVBQFixWja8HP0ZYtxRzav1+JLBGH8dix2Pu44ALqY8WKxGsAP/ssK+p3+WULNID5B1oCyE4gz0tlReA/5ATCnpCFC1vXjccm6JVX7BnRewkONrpiRfQxPTlyHDzO6uAnXHopL1261yY7YtAyEGVLADD3ZtRDrHOycGHqzyw2nRWmTbP2bpXB2RQGDjS3UZ04kY63b2/entaOiuO09ehBOYYByLbPDjilWNeuW2K+v2VMnUrtNW4syp56ytjOkzORbN4cd9eu4vXXMWKa4Ow8RVGwbl3Sci1c6M3YvAI7fvToQX/vv199vGpVKv/hB7JxnjzZecpNTrFnZQuO6L4N4FdfUd+XX+5Kc64isAH8b+McALgssiEA9I38f37k+AtAhK8TUBiYVPgPhYHhAMl2wmZwrtSQSdqhnBwiJdqQBBxj6sUXYxqmK2jaFA0f/npy5Mj4Tr1gEwEOEfLllxT65O67yZEhHixbJgjgmDEiUb3TrAmxzsmyZak/vUDMdvHxx/aIGoNfnI8/Tn+NAurqpePSQ6tWVG/aNNp//33a79JF5HS9/XZ7Y+N75s47t8f9os3OFkGH5es5fz6VcT5kGaVK0TG9bBbJxIgRNK777nN2nqIoeP75/0ZWMbwZm1fgLDXXXMNLwerjnLP84YdF8Hqz/MJ6cBLz1G0C+MMPGDGPcKU5VxEQQP/gKqC4fTK6AS39HgVyzijqsM0bAKLt9QBgcuQ4B4I+BABnAWAlEBF0At8SQA7QXLOmdd0bb6S606frHw+HhdZCGzvOTtJzr2EW10xPjnZDfyQD8m9hovbgg/G1OXu2IIBvvYXYqxf97zTNVKxzsnp16i+erCtOg1dzXllOe2ZEKmbNouMtWpi3xxkN5syhfTk3MHs62km1hUgfS3TurrhftCyX0qXJq5TB3s/ly0efE0/YJy/hJGetDEVRsGrVUwiA+N133ozNK/DqBWsC339ffZznlrxde6399q2iJGjhNgFMdqYoMwQE0D/4GtQx+S4GgCwgp4xngEja4MQPyxK+JYBLl0YvCxnBKgDroEHiIaIN+Mzx0LwMwGoFs/HryZFDegwcmLgx2gWHCJkyRSw76mlxnICXOVlT6yQwrIxY52SDBtTft98660/GO+840w41bEj1mVD36qVf78sv6bhVHMvLL1drmXnZtXVrkdnj00/tjW3wYKr/v//tjutFe+iQCOGkjX8nx7rMzBTl4bAzQpBITJ7McnF2nqIouc5Tq1d7MzavwNpb3rSBozlfMIDIlFKoEOKJE/bal0Mi2Ukv6TYB3LeP+i5SxJXmXEVAAP2DQwDQVNofAgA/SPudAWBLQkdkD74lgNpE42bo1Inqjh4dfYzzW/J2zjnqXKy3307l48bFNExXwFoevQCyenL0A2k1wm230djGj0esX5/+L1iQ0kzFCl5aYyLE9kZO44vFOievuMJ4id4uhgyhNnr2tFefCRtrWJ5/Xr/eokV0/NJLzdtjQrl8Oe3z/cVLzYUK2c8q8/bbdE6rVvvietF27UrtNG0aHZw4HBa2l/v2ifKzZ8VcsEsiEoVY80YrioJly55BAMSNG70Zm1e44Qb181VLYDMyKED2a6/RNb7gAmEiYgd//SWeIVY5tBHdJ4AnTojfdvasK026hoAA+gdnAaCGtP8DAPSX9msBwKlEDsgmfEsAP/2Ubjo7hulGhCgrS9iPPPecuJHlDAOtW1PZ1KkxDdMVdOtGYxg2LPqYnhxZszZpUgIHaRMc/PW998QLHIDyhsYKeRmpa9fY0zPFOidZC2eWk9oKThLaIwqbKl5aMzJR+OYbQRTNwEvKq1bR/tdfq1/cdp1TECkjAwCFTor1/l67VrzY16/Xr8P2ZT//LMrkF/KZMzF17RnYbrFpU2fnKYqCpUplIgDZzeYlsI0fb3r5qmWw+YZd85Xt26l+mTL26rtNALOz/atxDgigf7APAK6P/F8EAE4DwE3S8YsB4FiiB2UDviWAH35o32bqoYeo7ptvqsu1KdMqVMCor2x+0c6dG9MwXQEb+g8eHH1MT448ZrM8ncnCAw/Q2NiLk7f33tOvb+erWm6rXTtyLAGItjeyQqxz0g3CzR8gzz5rrz7btXJuZSP5/fgjHbfKMMKavg0baJ9zHPPmJAXZuHG87Hww5vub5dGli3EdTvkm35tHjogx66XGSyY4r3jDhs7OUxQFixWjcCN2HB38BL4XWYtslWZuzhyqe+GF9tp3morRbQKI6F+no4AA+gfjAGAVALQAgHcAIA2ICDLuA4C1SRiXFXxLAIcOpZuuRw/rupyvkdNcMbQp03gpT15+4ATm8earjAdmYU305MjLgt98k8BB2gQ71TCB4U0bHgKRHBEKFCDHnLQ04zY5xRYA4nXXiSX/MWOcjS3WOclaTaeEU8bTT1Mbr7xirz7bhfJmlAaLX5DVqpm3x2FlWMO0Zo26fSchbjhsTJMmh6Nk+dtv5LRjhnBYpHv7/HPjeh07RptGOAkPlWhwSj07jmsyFEXBlJQcx9fBD3jwQTGHrOYgIq2+FCxof86tWOGMMHpBANl7OR4nMC8QEED/oAIAfA+UEeQkUGgWGcuB7AL9Bt8SQCeerkYEil9yNWrQPidrl1/k/CKKZ4kyXpgtD+rJsUoVtTbHT2BtHedxLlFC/wGek4NYu7Z4eVSubGxjd+utol6jRmJ/4kRnY4t1TvJLbuhQZ/3JcOptziSXNyOixF6Ket6yMvg67N6tPg+ADPmdgD2PGzX6O0qWjRrRMbPQP7/8QnWKFTPPNcvOTv37izL+qDPKjZxM/PEHja1oUXv2aoyzZ0Ww8aNHvRufF+APGwDS2NoBh4qaPNm6Li+r252jXhBAtp/12wd3QAD9hzIAUEin/DxQawT9At8SQH6w2In1xsGctQm7lyyh8ksuoX2OXyYvwzkJMuoV5KC8WmjlGA7Ti1N+mfsJ/fqpics994ilTHma8Zd9qVJEDgHI005PK9C8uWivenXEtm3pf7teq4xY5ySTWrvaOz3w0vjw4fbqs4MEb0ZBznfsUGu59RAOC60Lh1rZtUu0rTWdsMK8eXRevXrHVLJUFFoGBDA3T2AvYqPYhgwOrCw7zmzeTGXlyjkbcyIgO6g4IXKnTgkC6DfHFitwSCAA+sC2A/64t+MRz3Eu7dqoekEAOc5sMs2E9BAQwADxwrcEkD097Whd3niD6j78sLpc65U3ciTtd+4s6vjBvoOD8t59d/QxrRxlI3inEfUTAW3cr1GjhDG/HEaFHV8efpiM+ZkE6gXzbtxYtHfOOfQyAKCsIE4Q65zkl9z//Z+z/mTwMvIHH9irLy+tmWmoOUxF0aLGbSmKaIcdoA4eFGVOA1xziKZatU6oZMnaOe2yrRZsdmGlAeLwP7fcIsrWr6eyqlWdjTlRYM23E+18WpoggH5zbLECk3S7qzWIwnGpUiVrTSlHALj3Xntte0EAY/3g9BoBAQwQL3xLADk0ih3jdH5IaO3M2FidMxywATLHTNPTjCQDZlkitHLcupXqli6d4EHahPxCAEBcsEAsvY8YQXVOnhRLkkxs2LNXTxvFgZh5u+4682VRI8Q6J/k3aT8wnKBDB2pjwgR79dlbkjejJdVDh0Qdo5epXiy1cJicp2IJJv7990zCTqlkySFptMu2Mpgk2gk7w2m4LrtMlK1aRWW1azsfdyKgZ2dshYMHBQH0m2OLFd59V1xzu2GZzp4VqxhWTi/sLNS3r722vSCAbtgAe4GAAAaIF74lgBxQ2M5Xl1GWBV5a7d6d9tlgvnJl2j9zRjy8PBCBbUyfTmPQy/eqlSN/PTdokOBB2sTw4WrisnUrkTpeDkYUmp0GDQRp4Th5es4i55yjbpO1hU6XZGKdk6w57trVWX8y2rShNuyGG+rbV/2b9+7Vr3fsmKgjB0yWcfSoqOMGweAQLuXLZ6hkyfehdtlWBqcxtLOkt3Ej1a1YUZQ5dQpINPQcV6ywZw8RwJQUB4aDPgF/ZDuZ24iI9erROStXmtfjlYK33rLXrhcEMNbA814jIIAB4oVvCaCTUCdGGjTt0p38IjxzRsSYKlbMOnyBl2CbKr1sDlo5TptGdW+4IcGDtIkPPhAyLlCAvvbZFvOCC4jwsQZPXt4PhaisSRN1e1lZaiJExENoF50g1jk5fjz116GDs/5ktGhBbVh5yDJeekn9m420ZRkZos7Jk/p12HPWrWwGbIdXpsxZlSyfeUaMpV07/XP5vrZDkA4fFvMoK4vK7Aa+ThbYXtRJbvFt24gAliiR9wggP48AiJzbBcfWnDHDvN7//kf17IZg8oIA8rzWi9KQTAQEMEC88C0BZLuvpUut6/JDqFUrdTnn/+X4euEwYvHiVLZzJ6VeA7DOo+o1li2jcXDauw0bBLnRypE1bHZtYhINJksAZPuHSOSFyzj1V8GCFOWfwc4MWjIux3Jk4sex8RYvdja2WOek0fxygqZNnZHWV19VE0CjIcuBav/+W78Oy9YtswF2ICleXFHJkrPq6BF5RLUD044d1v3k5AinEg4wbDf1XbLAWVLspvxDRPz1VyKAZcvmPQLIH278TLWLLl3onJEjzes1aUL17Gbh8YIA8r342GOuNekKAgIYIF74lgDWrEk3nZwFwAic1kqbZJwfMqNGiTJePly2TKj2X3ghpiG6Bo4fVrs2vSQ5aO/evdFy5K9RuwGFEw2OEadd0r70UlFesCBi797q87KyyJEBgMJpMOSwH5yTlzenYRlinZNMOuyGudADf9AsW2avPhMJAHMHD8RokqQFh12Rl1LjwYED1F6hQjkqWcrOOmxmIYMdTwoWNCa0WnAMtjVraJ9D0CT7o80Iqak0vpYt7Z+zdq0SkVneI4DsEARgL1cvgyMyGKU4ZPCz0G4MPi8IIJuAsAmLXxAQwADxwrcEkAPX/v67dV02FtdqHfTsCLls0iQR38mJwbYX+PVX8YLm3JcAtHSqlSOHB2GHCr+BX9AAFPuOsX8/yXnzZuPsH+wdOn++KGN7s+rVRWYI3r7/3tnYYp2TrKFt1MhZf19/TTZv4bDIgfrDD/bO5XRrAJTBxgys1TYKC7R6tVojGy/S0uSXvghPxI49TPK0ZhXswOFkHKw55XuUw4K0bu3Ob3Eb331H47PKzCJj1aqsiFzyHgHkj9eyZZ2dxx84DzxgXCcnBzElherZDZDtBQGcNMncrCFZCAhggHjhWwLIeWT//NO6LhuGa/OhcsBRmeBxQN7evcXLKtnBV3lJ7ZxzaFmTx/Xxx9Fy5OTr06Yld8xGYG0ZgH3DbQbHDJS9CVnD0LixIO+82dEOy4h1Tv78M/VXq5b9c3bvFsudy5cLT2a7moyxY8XvtCIT555L9YzCuaxcScfr17c/fjPIdofHj5Ms2Ru5YEFjz3peSneiHbvtNjpn7FjaZwciPY95P2DPHhpfkSL2g0GvWEEE8IIL8h4BPH2a7DpfesnZebxSYEbk5Q8NOykjEb0hgLNn0xiuu861Jl1BQAADxAtfEkA5oOrx49b15SVUGexp9t13ooxDenA2jXr1HA/PdfDLs0ABxHfeEb990KBoOdavH9vyZ6IgE1inYVpee43OY69tRGoDgIJBy3lHASgmnBPEOiftZtuQwcQFgEKisP3i5s32zp88WZxv5fBQqRLVMwpmzteEA6LHC9nu8OBBkuUPP9B+zZoiuLr2+rCnt3x9rcB2vAMH0j57GtsNOpxoZGYKG9UjR+yds3gxEcCGDfMeAYwV/GFnplXfsoXqnHuu/Xa9IIA81osvdq1JVxAQwADxwpcEUPbWZe8/M3C4CK3dUYUKVC7HUJNt1ADs5Rr2Gv/+K8Zz773i/4ceipYjB67eti3JgzYAa5sA6Lo4AX9py2mfJkygsltvFdpb3n75xVn7sc7J/fupv5QUe97iCxeqx9mihQhlYxX3jDFjhji/eXPzuhxoe/Vq/eNeOE4ULhyOLDuTLD/9lPpo1UoY7stL+YjC5padsuyAs4awOQHHnYsnJI/XMCLARpg3jwhgkyb5hwCyJ/l55xnX4ZUdJyGvvCCATk0o/vmHbBunTHFtCLoICGCAeOFLAsg5NYsXt1d/27boL8VwWN9+5Ntv1S/n8eMdD891yKFOODcxAMWOk+WYni6OJTNuoRl4uRTAOCyJEfiLv2RJsXzGXs/33y+CwvK2ZYuz9mOdk9nZYi5ZmSScOSOuIefzLVJELIsaOWpoIXtXypkw9KCn6ZahzYjjBkqXDkeuAcly4EBB1Nq317+3Wremcjs5YBnsVX7rrbQ/dKh/PtyM0KwZjVEvq40ePv+cCOBVV+WxKNBxQI4MYLS8yx9BTuatFwRQ7/1iBv4I9jpYeUAAA8QLXxLATZvoBrLrtbh3L9WXvSVlsiQnnGcbHd7sLsl5jSJF1OMCII9lWY7sEVuihLNk84kEj7F6defnKoqw/dy3j8rkPM+c8o83p+n74pmTdeqYkyzGe+9RvapViQCzqQFvaWn2+pOzanTpYl63USOqt2wZac/nz1fPD9bO3Xyzvb7toGLFcETLRbLkTC5DhwpN36uvqs9hYmwV/FfG/Pl0zuWX0z5rBP0WkkMGE3+7af+mTcuKEJ38QwDDYeH1bxTknB2h7rrLfrteEEDZe93Oc3fMGKrvtdNIQAADxAtfEkBONXXBBfbqHzkiXpZ8g8rLdvJNqyhCG1OmjH9SL5UtG00AS5ZEzMwUcuQvy7p1kz1ac0yebN/bVQsmM199RftPPkn7/furg0ybvTiMEM+c5PzDVplpOOAzp41ixxbe7OZvljXVVinoLr+c6i1cSJpSAPXyE2dikXNgx4vzzycCuGoV2WhcfTX1MWsW4oAB9P/jj4v62dnR5N4OOHtPlSq0zwGytWGE/AR2MLMbXmrSpKyIxt8nD6MEgUN9/fST/nH++HvySfttekEAZacnWZlgBL7+/fq5NgRdBAQwf2Mw0MWXt8MO2/AlATQK62IE2YaOk6mbGe6zR+b//ud4aJ6B450BCEcPAMQjR4QceUnErzHQ3ADn3eQwN6xZGjFChADhTQ4kbQfxzMmePfW1WjKOHRMx+fbsoTLWBvBmN+OMvJRulQdVzprDc0d2krjxRiqzk1fbLurXJwL4zTdEANnedv16xNGj6X/OwY0ospHYtaNkyNqX7Gz/ZmWQ4TRY+7hxWRGNUf4igPzRYJTtiTXJr71mv00vCGA4bB1rUwabOnz8sWtD0EVAAPM3BgPAZgCoLG0VHLbhSwLo1GYpM1O8LI8dozKOx6Xn5cupyJw8WLyGTPruvVd4ja5dK+TIAUnvvjvZo/UOgwbRb3zoIdpne7KJE0XKPN6chu+JZ06y9/iDDxrXYYLesKEoY7tGANKA2QWbQQAID1gjcGigTz8VL6rSpUnbnZ4uNG92sm/YxSWXhCNaxyw8eVKM9cQJytEMoHY6iSU+HiKRPjmsjKwR9is4t7fd59f772cjAGKnTvmLAPJSuVFawA4d6Pi4cfbb9IIAIoq4tHbsjvljftUqV4cQhYAA5m8MBoBNcbbhSwLoNNZXOBwde4zJguxRypg6lcqdLEV5jcsuEy/RN98UnpRz52blyvH556msT59kj9Y7MPnnrBtM1mfPFiRCS/btIp45OXUq9WmWg/mBB6K1U+Ew2bICkAe3XbDhuawNNULbtlSP5wdv330ntOm1arlrN3rllTkIgDhnTlauF365cnSMtZc1aoj6spewU7Ad5fr1Qiv0+uvu/A4vwCFx7DoBjBhBBLBLl/xFAJ94wpzMcxzXuXPtt+kVAaxVy3y5mnHihLj/7IQwiwcBAczfGAwAGQBwEAD2AMAMAKjjsA1fEsBYUu9wFgJOI+aF4buXYKIDQOSV86p+8EF2rhzZvstpgOW8hK1b6TcWL07e0WwTuHy5SGnGmx17HBnxzEl+qRsFg87OFlrbb79VH+NlbauMHjLYscmOBoRjDmoDZb/8ski59eij9vu2g5YtiQBOm5aVG76HNX779gmNJ5NOzqfas6fzvtjGccECQbKHDXPvt7gN/v1FitizMR4yhAhgt275iwCyVt1oTjDpcqJJ84oAcipLq/zj/PHDNqteIiCA+Ru3AMCdAHAxALQGgG+BbADLmZxTFGiy8FYNADAtLQ0VRXF1y8jIwFAohBkZGY7PHTQoO/JgyLF9TrlytCS1aRPtv/sutXHXXfbbSObWunVO7ot7+3YFn3iCxt+vn5Irx1atqM6kSVlJH69X29mzCp5zDl3LDRsUrFaN/l+9WsGdOxUNAUzcnNy7l/ouVCiMp09HH//+e7LjKlMmjBkZ6mOjRmVHNGJh2/3t3y9+65Qp5tf7jjtoXlSqFI4s/9LfJk3CeNFF9P+MGe7OmTZt6DeNH38Whw4VGixFUTA9XYz94EGq3707jXHw4GzHfbVrR+eOHp2Fd91F/7/7rvN2ErVlZChYoADJff9+6/oDBmQiAOJDDyV/7Inc2Pbxlluin9GZmQoWL04y3LbNiexjv8fNtubNad6lpprfRxMmZEU03d6/d9LS0gICGCAXJYEI4DMmdQYDRDmOYGpqKoZCId9sHTvuQADE227bafuccuVOIwDiO++swFAohF27bkEAxLZtdyf999jZrrrqIAIgFiuWhV98EcJu3TYjAGLLln/m1qlR418EQHz11R+TPl4vt0aN/kYAxKefXo/FitEDdezYJTht2gIVAfzii8SN6YsvQpiSkh3RyC2OOt658zYEQLz22gNRx8aNW4KFC2fjZZcdsd3f1Knit77yyk+mdVu2/FMllw4ddqn2CxYM49SpCz2Zr716bcTWrfdGCODW3OOlSp1FAMT33luOoVAIGzc+igCIffuuc9wX/5527f7AK68U/SZ7nppt5513OrJ8/61lXZ477dv/kfRxJ3Lr338VAiDWqXM86tj06WL+z5gxP+ljbdr0EAIgPvnkBlX5hAmL8dZbd+HEiYswFBLvrnbtvL+WqampAQEMoMJSABhjcjxPaADvvtu5tqBu3XBk+Y2+0Hr3Zg2afzUF8nbPPfSbmzWjL8cpU4j4tGiRnSvHsmXpN27cmPzxern16ZMdWbbMzn0JHD5M2kHWrBQsaF+bxlu82oELLqC+ly6N1gJcdhkdmzhRX0Owb5+CJ0/a7+vkSaFFW77cXOvQo0eOivDNnp2VOx4ACjDs9jXq3DkrshSbiVdfTf1PnSrG2aiRcBJRFAVr1VLfn042jpPXpEkY27bNMZWzXza2kfz8c+tx9ulD17pPn+SPO5Hb6tX0uytXjr6Xt2yhYyVKOLvPvdIA8vN52DD1+4S101275qj2P/jA+/dOoAEMIKMoABwAgIEOzvGdDWBWloiJ9/339s9r3JjOWbaM9nv0oP2hQx11nzRwmjP2fuVYiLVrhzEUCuG//wpC8M8/yR2r12CHC85wASBSApYpQ/ty0G+7iHVOMtjG7pNP1OVs81WggP38r1YIh8Vv37DBvG6vXmrbv+3bRbw8AGsv4ljAS7pvvJGde03klItt2lDZ5Ml07dg72WnoHkQRQqZQIXIOoqU4936LF7jzThonx4M0w1NP0YfOCy84iI/zHwDnQOcQPzKcOtIw4r3HjcD32KBBooztlQEoZmtGhggYv2KFq93rIrABzN8YAQAtAaA2AFwFAPMB4CQA1HTQhmcE8PRpBWfP/tLxjcjBjs87z1m8sKZN6TzOP8pOFGPHOuo+aZgyhYzGQ5H0UewEULhwGL/44v/bO/coqYo7j38IBnRFjKxBRQEf+CCKEVfDwwQwhCgma8AYHxg1YVXQrAZcjyieZMesRokbAYkKxg2jMROVEAc1SlRYcE+ChI1CHiqYKJuJojDRgKBOw8zdP35V3uo7M8x09+2Z7unv55w607du3brVv7m36tv1+FVttH595kPhU6q7gKRFWLFC9upZv+9tr16551to43DZZS0LqiuvtPhTT80r21bZa6/shU2t4Rd62PNigivckzlfp9y7Y8qUeJ6ub8TDLb0uvjhe0e533+nZM3/H6953p3dps3hxGt+ieEyf3vKK/Xffbb6/+aWX7nLPVWUJwKSLn5Cf/9zihw/PLc9iCcAZM6w806bFccm9yRcutB+BNmKR6u1bRAKwsnkQWwGcAV4HFgOfyDGPogjABQtswvtVV/025xfxmmvsBfrqV3O7p9+BYdEiOx492s8fyS2fzqShIf6cCXYsWbjwyWjlShsGa20ValeisdEEnq9YQ3ciQ4ZYXHv35QwptHHwO2pcdFEct2lTFO25Z+SGhvPKtlVmzbItz9oS/KH7F++DMJMxWw0ZYp/TZto0Ey0nnmgC8Kijss9fd52V58oro2j58qjFNLngV1L78PjjhZW/2FRXR24KRxz36qv2Y+b887PThr2plUbo4ifEO1APnYm3h2IJQP/u+xGat96Kt7LzjtZ971+fPh3zI10CUBRKUQSg37D9iCPeiRoacnsRjznGrn3oodzu6Yec/BZYxx/fvmX7pYx3KHrbbSuiBx80AThiRGeXqmMYNSpu7IcMieO90M/FpYqn0MahJQe//gfL8OGd1zPrt14DG3r0NDYWr0wzZpgA7NHD5vZNmJB9PtzIsvcbAAAUE0lEQVTH9Uc/it3U5Mvtt2cLwLTFdtr88Y/x0KAfyfBbGXp/iR4/v+y22ypPAIYufkL8ns+XXppbfsUSgD/4Qfb79e1v2/GnPhXvOuXDKaekeutWkQAUhVIUAbh5cxT17Nnkhp92NjtfV2dzlMI5Q1EURa+8Yi/QHnuYQ81c8F7j77nHjv1Q4erVeX6JEsBvlTRjxupo9mxrcMMtvroyfggt2YvyxS9aXL9+uedZaOOwalV2j+SWLdbAd3aP1E03xba64YaOuad31eTDzJnZ5x9+2OL33z9+F6dMyf9+4dZ4YE6uS5ldu+Jn4w9/sLhwX+ht2+K03o3P3LmVJwD9Tj8//GF2vJ9zl+uOL8USgH4bynHjoui992Kfnw8/bOd9h0M+ojVfJABFoRRtDuCFF1qlNmlS9qSfnTvj+Xo9ekTR978fzwvyv/LHjs39fueckz3pep997DjN7a86Gj/sNXny76Jrr7UGN5eN0csZvxAETNx7vDPsgQNzz7PQxuHNN+NJ6w0N8Wb1Q4d27rxMv/csmN06Au/7r7X7erHsQ/fuue3okKShIR5yK5cfdr632i8a6t8/Lv+6dXG6L3zB6sr585v/WO7qtLbfr19EM29ebvkVSwAuWRL3+C1aZJ8HDIjnc956a/y/vf32VG/dKhKAolCKJgBXrdr54RBROCHWe3/389v8kFptbTxvb/bs3O930UV27axZ9lL6vHPdL7aU8Bvfn3jim9FBB1mPainvgJAm4VZoF14Yx/u9YAcNyj3PQhuHpqZ4vt9jj8WCpLMXJNxxR2yr5FyqYjFnTrYATK5UbmqyYbKrrzbht2VL4fccOTK+39q1hedXbPz7+41vxCuZfViyJE43blzs4L3S8NMXLr88O/7Tn87uYWsvxRKAK1ZYeY45Ju7JDbd8DHfuefLJVG/dKhKAolCK6gbmqKP+FoENUUWRVdp+Fd8DD9gKXb/SMQx/+lPu95syxa698cYoqq+P8yrGBPiOwm+J58Oxx6bTkJYDjY1xL+6VV8bxM2da3ODBueeZRuPg56h+7GP294wzOn9V9vz58TOyfXtH3XPnh/fs1s1cYBQbP98SbKV4qVNTY2UdNswWo4Xv8pw5cTq/rd4DD1SeALzrLrNHcg6pdwG1cmVu+RVLAD7/fDx/0y9Qe+657DSXXWZzGnPdojJfJABFoRRVAE6b9r8RRFHfvrZ66rDD7MWZODFuNF991X5J9e1r5046Kb/7ffObdv1115mABJuDU84sXhw3GJ//fGPO8yLLHb8Q5FvfiuO+9z2LO/743PNLo3EYPz7+n/Tp09x9RWewcGE8JNVx94wF4OGHd8w9w/fhtdc65p6FsGGDlbVnzyiaOjVbAIbuYbwj7UWLKk8A1taaPY4+Om4Twh9/uQr9YgnAP/85+/93yCH5uzRKCwlAUShFFYCLFj0a9e3blPXi7L9/yz6SMhmb2L1pU373C/00rVkTv6TlzDvvRNEppzRGEyZsiN57r4y7MvNk7lybO/aLX8RxCxb4YfHc80ujcQidLue6Ur1YPP20lefsszvunn5VOtjCnI7gjTdi2+dbT3QkTU2x4/Leve2vn+Zy5plxOu9KZ8mSyhOAb78dL5bxQ6d+jl3v3rbgIheKJQC3bGldwHcWEoCiUIq+E8izz+6Mrr/e/CjdeWd+OwG0B+82YOrUuEE87rji3KsjKVaFVi4khxYfeigeVsuVNGzp/btdcEHeWaROY2MULVtmUx86itraWABee23H3feqq6Jo0qTOH3ZvL2PHZguHe+6xv6FrI79t3tKllScAoyieKzl6tD3LflencNeN9lKs+rKhIfv/WAqr0CUARaGU3FZw+eJXYV18ceyCInQfUq5UugBMsnlzFJ18ss0dypU0bNnYGEUvvJDbLjVdkaVLYwFYXd3ZpSld/MgE2Cpgv8tNr16xiD3ySBOAy5dXpgCsq4vnhnsxuO++NgKSK8WsL/0CsAMOKI33XwJQFEqXEYDe8ey558a/skP3IeWKBGB6yJbp4XemgSj6zW86uzSly89+FgvA886zIU1/7HtsBw40AfirX1WmAIwimyMe9rBVVeWXTzHf8QMOiEeZSgEJQFEoXUYA+rlhZ55prmAg231IuSLRkh6yZXqsXp35sLEOnRqLbEL3IN5H6YEH2vGaNf64yR1X7nP50kvxPrr59v5FUXHf8WHDrHwrVqSedV5IAIpC6TIC8L77/GpZ22UEbL5QuSPRkh6yZXq8/nom2mOPXdEJJ5TJZLxOoqkpdgDtdz4aMSLbx12fPiYA162r7OfSO75POoXOhWK+4+vXR9ETT6Sebd5IAIpC6TIC0K8c++hHbZswMEe05Y5ES3rIlumRyWSiBQt+Gb31lmzZFmvXZq9knzTJ6qdZs6ynq3v3JufaprJtuW1bFD36aGHz6yrpHZcAFIXSZQTg5s22TU84jySfHUVKjUqq0IqNbJkesmX++C0Ep06Novvv9wtEtsqWKVBJz6UEoCiULiMAo8iGW9asMY/sw4eX9z7Ankqq0IqNbJkesmX+3Huvib7TT4+iL33JPp9zzsuyZQpU0nMpASgKpUsJwK6I7JgesmV6yJb5s2xZ7BbGuxaZPXu5bJkClfRcSgCKQpEALHFkx/SQLdNDtsyf5LZigwY1RY88IlumQSU9lxKAolAkAEsc2TE9ZMv0kC3zJ5OJoo98JBaA11yzS7ZMiUp6LiUARaFIAJY4smN6yJbpIVsWxsCBsQD89a93ypYpUUnPpQSgKBQJwBJHdkwP2TI9ZMvCGDPGxN+AAVHU0CBbpkUlPZcSgALgCuA14APgt8BncrhWArDEkR3TQ7ZMD9myMKZMMQE4fbpsmSaVZEsJQHEukAEuAQYDc4DtwIB2Xi8BWOLIjukhW6aHbFkYf/lLFN14YxRt3Spbpkkl2VICUKwG7k7EvQTc0s7rJQBLHNkxPWTL9JAt00O2TI9KsqUEYGXTA9gFTEzEzwVWtjMPCcASR3ZMD9kyPWTL9JAt06OSbCkBWNn0w/75IxPxM4H1rVzTE3tYfDgYiOrr66NMJpNq2LFjR1RbWxvt2LEj9bwrKciOsmUpBtlStizFUEm2rK+vlwCsYLwAHJGIvwF4uZVrqtw1WaGmpiaqra1VUFBQUFBQKINQU1MjAVjB5DMErB7AMguyo2xZikG2lC1LMVSSLdUDKFYDdyXiXiTHRSB1dXXR1q1bUw319fVRTU1NVF9fn3relRRkR9myFINsKVuWYqgkW9bV1UkAVjjeDcxkzA3MbMwNzMB2Xn8wLQwJKygoKCgoKJRFOBhRsVwBbAQaMEfQo3K4thv28PQuQvDislj5V0qQHWXLUgyypWxZiqHSbHkw1o4LUVL0xl7E3p1dkDJHdkwP2TI9ZMv0kC3TQ7YUogTQi5gOsmN6yJbpIVumh2yZHrKlECWAXsR0kB3TQ7ZMD9kyPWTL9JAthSgBemJ+B3t2cjnKHdkxPWTL9JAt00O2TA/ZUgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQggh2uIK4DXgA2x3ks90bnE6nFHAY8AbmEuCCYnz3bCVam8A7wMrgGMTafYDfgxsdeHHwMcSaYYAK10erwPfprlX+C9j+0M3uL8T8/pGncP1wBrgXWAzUAscnUjTE5gH1AM7gEeBQxJpBmD/jx0u3R1Aj0Sa0diz+gHwKjC1hfKU83N9OfA7YJsLq4DxwXnZMX+ux97zOUGc7Nk+qmi+tdmbwXnVlUKUEX5/4kuw/YnnYPsTD+jMQnUw44GbgLNoWQDOwBrhs4DjgAexCm6fIM2TwO+BES78HmssPL2xivKnLo+zXJ7/FqQZAezCGqhj3N+dwLACv19HsRT4GlbhfxJ4HPg/YO8gzd3AX4HPAUOB5cBaoLs73x2z3XJ3/nNYAzAvyOMwrBGegz2zl2DP8JeDNOX+XP8zcAZwlAs3Y9/HN6ayY36cjImvdWQLQNmzfVQBfwAODMLHg/OqK4UoI1ZjlV/IS8AtnVCWUiApALsBm7CKzdMT+DswxR0PdteFlc9wF+d7wC5314T+rq7DGhH/y/YhrHIMWYpVhOXIxzEb+P2u98Uav3ODNP2ARuA0dzzeHfcL0pyH9ZZ4Z7GzsGc0ZD7WS+bpis/128C/IDvmSy9gAybeVhALQNmz/VRhwrglVFcKUUb0wH5FJbvO52Ld75VIUgAe7uKGJtItAe5znydjFVaSvwNfd5/vd9eEDHV5H+aO/wJMT6SZjvWilSODsO93nDv+rDveL5FuHXCj+/wddxyyn7vuVHf8LPaMhkzEegA+Std7rrtjYqMB+ASyY77cB8x2n1cQC0DZs/1UYb2cb2A9qQ9idSSorhSirOiHvVQjE/EzgfUdX5ySICkAR7q4fol09wC/dJ9nYj0LSTZgQxMAT7lrQrz9R7jjDDApkWYS1vCXG92weVT/E8S19l2eAha4z/e44yQNwPnu8wbM5iH+/3QQXee5HoIND+7CGsgzXLzsmDvnYUONe7rjFcQCUPZsP+OxIe0hxD2pbwL/iOpKIcqK5EvluQF4ueOLUxK0JgAPSqT7ITbkAK1X4K9gQxeQ3Zh4DnZ5D3fHGeLGxHMBNsxUbtwJbCR7In1rFfTT2FAZZDcWIRmsEYfsxsJzCmbLA+k6z3UPrBf1JGyIcAvWAyg75kZ/4C1sXqpnBW0LQNmzbfbGBODVqK4UoqzoCkMSaaMh4MKZB9QRfy+PhtoK4xmsYZQdc2MC9r13BSECmtznsciehfA0Nq9RdaUQZcZq4K5E3IuUz6TktGltEci1QVwPWp7Y/KkgzTCaT2x+h2y3ETNoPrH5iUR5nqR8JjZ3A36AfacjWzjvJ9ufE8QdRMuT7cNehHNpPtn+xUTed9N8sn1Xe66XAdXIjrmyDzYPNQxrMPcjxyF7FkJPbPW0d9OiulKIMsK7JZiMvZyzsXlHAzuzUB1ML+AEFyLsl+QJxK4ZZmCV2ESswaihZdcG67AhiuGYD7fQtcG+2FBJjctjIuYDK3RtMBLrIZiBuTaYQXm5NrgLs9Nost1E7BWkuRvrHRyL/apfRsvuNp5x58e69C2527gde2Yn07q7jXJ9rr+L+Yc7FJtvdTMmQMa587JjYayguRsY2bNt/hN7vw/D6qXHMBctvvyqK4UoM67A5ms1YI5JR+02dddjDM2dm0ZYbwvEzk03Yb/4VxKvbPX0AR4gdtz7AC07N33W5bEJ+HeaOzc9G5sPlMHcQ5yV/9fqcFqyYYT5BvTsiTWafwPewyr+/ol8BmA+BN9z6eaR7RICrBF6HntmX6N1h7sbKc/n+r+Iy74ZEx7jgvOyY2GsIFsAyp7tw/v1y2A9couxeake1ZVCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIITqVaqC2wDw2AtMKzGMM5qQ76YBXCCGEEEKkTDWFC8CPA/9QYB5jkAAUQgghhOgQqilcAKbBGCQAhRBCCNHFOBv4PfA+tm/rM8De7tzJwNNAPbbJ/ErgxMT1ETCFeO/Xl4ARwCBsH9kdwCrgiOCaKmCtu67OXbeIbJFVTbYA7AZcC7zqyrrOlX13bCR7CDgCLgEecfd8BTgzcc0ZwAZ3j//G9mdOCsCR2P6r77vy30Fss2Nc3pOC9Gdhe7UOaaO8QgghhBBF5yBgJzAdOBQTKFcAvdz5zwJfBQa7cC/wJrBPkEcE/BU4BzgKE1evAcuA09x1q4Ang2uqgO0uzQnAKEyM/SRIU022ALwZE5enAYdjwuwDYPRuvt9GmgvAOuB8TKDOBd4F+rjz/V2ec4CjgQvc9w0F4BB3zTTgSEwMPg8sDO5zBfB3YCDQDxPWhc5FFEIIIYRIhRMxcTOwnem7A9uALwZxEfAfwfFwFzc5iDsP6y3zVAG7gEOCuNOBRuBAd1xNLAD3dtePSJTnXqBmN+XdSHMBGJZ1b6DJ3Rvgu8CLWG+j51ayBeD9wILEfT7tyr5nEPc41kv4DPBUIk8hhBBCiE6jOyZQtmFDsJcC+wXn+wLzsSHRrVivXRPWw+WJgK8Ex4e5uJODuFNdXG93XIUN5Ybs69L4Hr1qYgF4sju3PREywOrdfL+NNBeAX0mk2Qpc5D4/Avwocf5LZAvAPwINiXLscGkGB9f1xXoB38Z6AYUQQgghSoZuwCnAjcDvgM2YiAN4AliDzYs7Fhs23UJzUTUhOD7UxZ0QxI0hW0RV0VwA9nZpRrnjamIBOIxYHA5KhP67+W4b2ygrmEj7mvtcS9sC8CVszl+yHIOAHsF147Dh9Qaaz5sUQgghhCgZumPz+a52x+8CFwbn+2NiKA0BuIvsnrHTaH0IeB9sbl5YlvawsY2yQrYA9EPAIbckyv4TbO7i7ugDvI59z/mYaNyr3aUWQgghhCgiw4CZwEnAAGx4tAEY786/gM1fG+zSPoutcE1DAG7HVhh/EvgMsB74aXBNNdmLQG7CViNfjK0oHgp8wx23xsY2ygrZAnAA9v1vxxaBTAI2Jcp+PGaDO913PBJbSTwvyPNh4DlgD8wP4csuvRBCCCFEpzMYWIoN+36AibB/Dc4PxYaAP8DmAZ5N26LqUNonANcCl2M9Ze8Di8mef1hNczcwV2FiKuPKvJR4yLgl2iorZAtAsAUur2Df+Vng64myg81JfArrId2OuaSZ6c5d5OKODNL/EyYsz9hNWYUQQgghujRVmAAUQgghhBAVQhUSgEIIIYQQFUUVEoBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEKBr/D2wStrzxcfTfAAAAAElFTkSuQmCC\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"error = stp_error(data)\n",
"SNR2 = mean(data*data) / mean(error*error)\n",
"print \"SNR\", 10*log10(SNR2), \"dB\"\n",
"\n",
"T = 20.0 / 1000 # 20 ms\n",
"n = int(df * T)\n",
"data_frames = audio.frames.split(data, n, pad=True)\n",
"error_frames = audio.frames.split(error, n, pad=True)\n",
"\n",
"fig, (ax1, ax2) = subplots(2,1, sharex=True)\n",
"SNRs = [10.0 * log10(mean(d*d) / mean(e*e)) for d,e in zip(data_frames, error_frames)]\n",
"ax1.plot(data, \"k\", alpha=0.1, label=\"original\")\n",
"ax1.plot(error, \"r\", label=\"stp residual\")\n",
"ax1.set_title(\"Waveforms\")\n",
"ax1.axis(\"tight\")\n",
"ax1.legend()\n",
"ax1.grid()\n",
"ax2.plot(r_[0:len(SNRs)] * n, SNRs, \"b\")\n",
"ax2.plot([0,len(data_frames)*n], [10*log10(SNR2), 10*log10(SNR2)], \"k--\")\n",
"ax2.set_xlabel(\"sample index\")\n",
"ax2.set_ylabel(\"SNR [dB]\")\n",
"ax2.set_title(\"Signal-to-Noise Ratio\")\n",
"ax2.grid()"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"wave.write(error, \"voice-error-stp.wav\", df=df)\n",
"display(Audio(\"voice.wav\"))\n",
"display(Audio(\"voice-error-stp.wav\"))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Pitch Estimation\n",
"=========="
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"def ltp_parameters(history, frame,\n",
" offset_min=1, offset_max=None,\n",
" gain_min=0.0, gain_max=inf,\n",
" SNR_min=1.0, SNR_max=inf,\n",
" select=argmax,\n",
" returns=\"offset, gain\"):\n",
" p = len(history)\n",
" data = r_[history, frame] # full data\n",
" m = len(frame)\n",
" n = len(data)\n",
" nxcorrs = zeros(p+1)\n",
" gains = zeros(p+1)\n",
" SNRs = zeros(p+1)\n",
" valids = zeros(p+1, dtype=bool)\n",
" frame_norm = linalg.norm(frame)\n",
" normed_frame = frame / frame_norm\n",
" for i in range(p + 1):\n",
" windowed_data = data[n-i-m:n-i]\n",
" windowed_data_norm = linalg.norm(windowed_data)\n",
" normed_windowed_data = windowed_data / windowed_data_norm\n",
" nxcorr = nxcorrs[i] = dot(normed_frame, normed_windowed_data)\n",
" SNR = SNRs[i] = 1.0 / sqrt(1 - nxcorr*nxcorr)\n",
" #print \">\", SNR\n",
" gain = gains[i] = nxcorr / windowed_data_norm * frame_norm\n",
" valid = True\n",
" if offset_min is not None:\n",
" valid = valid and (offset_min <= i)\n",
" if offset_max is not None:\n",
" valid = valid and (i <= offset_max)\n",
" valid = valid and (gain_min <= gain <= gain_max)\n",
" valid = valid and (SNR_min <= SNR <= SNR_max)\n",
" valids[i] = valid\n",
"\n",
" criteria = SNRs.copy() \n",
" criteria[logical_not(valids)] = -inf\n",
" offset = select(criteria)\n",
" if not valids[offset]: # everything is invalid!\n",
" raise ValueError(\"no valid set of parameters\")\n",
" else:\n",
" gain = gains[offset]\n",
" nxcorr = nxcorrs[offset]\n",
" SNR = SNRs[offset]\n",
"\n",
" return wish.grant(returns)"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"offset: 75 gain: 1.1689857342477985\n"
]
},
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('');\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",
" '');\n",
" var titletext = $(\n",
" '');\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 = $('');\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 = $('');\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 = $('');\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 = $('')\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 = $('');\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 = $('');\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 = $('');\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 = $('');\n",
"\n",
" var fmt_picker = $('');\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",
" '', {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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"\");\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('');\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'] = '';\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 = $('')\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 = $('');\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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('');\n",
" var 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= 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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"output_type": "display_data"
},
{
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\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
""
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"N = 100\n",
"data_ = (0.7 * sin(r_[0:N]/N * 2*pi*4) + 0.05 * random.uniform(-1,1,N)) * (1.0 + 0.2*r_[0:1:1.0/N])\n",
"#history[::7] = 1.0\n",
"history, frame = data_[:-25], data_[-25:]\n",
"m = len(history)\n",
"n = len(frame)\n",
"offset_min = 5\n",
"def select(factor):\n",
" def _select(SNRs):\n",
" i = argmax(SNRs)\n",
" is_ = r_[0:len(SNRs)]\n",
" SNRi = max(SNRs)\n",
" js = [int(ceil(i/2.0)), int(floor(i/2.0)), int(ceil(i/3.0)), int(floor(i/3.0)), int(ceil(i/4.0)), int(floor(i/4.0))]\n",
" ij = argmax(SNRs[js])\n",
" if SNRs[js[ij]] >= factor * SNRi:\n",
" return js[ij]\n",
" else:\n",
" return i\n",
" return _select\n",
"offset, gain, nxcorrs, SNRs, valids = ltp_parameters(history, frame, \n",
" offset_min=offset_min, SNR_min=1.0, select=argmax, #select(0.5),\n",
" returns=\"offset, gain, nxcorrs, SNRs, valids\")\n",
"print \"offset:\", offset, \"gain:\", gain\n",
"\n",
"figure()\n",
"plot(data_, \"k\", alpha=0.5, label=\"data\")\n",
"plot(arange(0,n)+m, frame, \"b\", label=\"reference\")\n",
"plot(arange(m-offset, m-offset+n), frame/gain, \"r\", label=\"matched\")\n",
"axis(\"tight\")\n",
"legend(loc=0)"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('');\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",
" '');\n",
" var titletext = $(\n",
" '');\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 = $('');\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 = $('');\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 = $('');\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 = $('')\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 = $('');\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 = $('');\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 = $('');\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 = $('');\n",
"\n",
" var fmt_picker = $('');\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",
" '', {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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"\");\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('');\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'] = '';\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 = $('')\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 = $('');\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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('');\n",
" var 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= 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": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
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\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
""
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"figure()\n",
"m = arange(len(SNRs))\n",
"plot(m[offset_min:],SNRs[offset_min:], \"r\", alpha=0.25, label=\"SNR\")\n",
"n = arange(len(SNRs))\n",
"plot(n[valids],SNRs[valids], \"bx\", linewidth=1.0,label=\"valid\")\n",
"xlabel(\"offset\")\n",
"ylabel(\"SNR (linear scale)\")\n",
"axis(\"tight\")\n",
"legend(loc=0)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Long-Term Prediction\n",
"===================="
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [],
"source": [
"class LTP(Quantizer):\n",
" def __init__(self, order, **options):\n",
" self.fir = FIR(a=r_[1.0, zeros(order)])\n",
" self.history = zeros(order)\n",
" self.ar = AR(a=zeros(order))\n",
" self.order = order\n",
" self.options = options\n",
" def encode(self, frame):\n",
" a = zeros_like(self.fir.a)\n",
" a[0] = 1.0\n",
" try:\n",
" offset, gain = ltp_parameters(self.history, frame, **self.options)\n",
" a[offset] = - gain\n",
" except ValueError:\n",
" offset, gain = 0, 0.0\n",
" self.fir.a[:] = a \n",
" error = self.fir(frame)\n",
" self.history = r_[self.history[len(frame):], frame]\n",
" return (offset, gain), error\n",
" def decode(self, data):\n",
" (offset, gain), error = data\n",
" a = zeros_like(self.ar.a)\n",
" a[offset-1] = gain\n",
" self.ar.a[:] = a\n",
" return self.ar(error)"
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"320\n",
"40\n"
]
}
],
"source": [
"f_min = 50.0\n",
"f_max = 400.0\n",
"order_ltp = int(df/f_min)\n",
"print order_ltp\n",
"offset_min = int(df/f_max)\n",
"print offset_min"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [],
"source": [
"def ltp_error(data, T=0.005, order=order_ltp, **options):\n",
" length = len(data)\n",
" n = int(T * df) # number of samples for T s at the given sampling frequency.\n",
" frames = audio.frames.split(data, n, pad=True)\n",
" ltp = LTP(order=order, **options)\n",
" error = zeros(n*len(frames))\n",
" offset = zeros_like(error)\n",
" gain = zeros_like(error)\n",
" for i, frame in enumerate(frames):\n",
" (offset_, gain_), error_frame = ltp.encode(frame)\n",
" error[i*n:(i+1)*n] = error_frame\n",
" offset[i*n:(i+1)*n] = ones_like(error_frame) * offset_\n",
" gain[i*n:(i+1)*n] = ones_like(error_frame) * gain_\n",
" error = error[:length]\n",
" offset = offset[:length]\n",
" gain = gain[:length]\n",
" return error, offset, gain"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('');\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",
" '');\n",
" var titletext = $(\n",
" '');\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 = $('');\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 = $('');\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 = $('');\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 = $('')\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 = $('');\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 = $('');\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 = $('');\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 = $('');\n",
"\n",
" var fmt_picker = $('');\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",
" '', {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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"\");\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('');\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'] = '';\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 = $('')\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 = $('');\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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('');\n",
" var 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= 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": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"stp_error_ = stp_error(data)\n",
"ltp_error_, offset, gain = ltp_error(stp_error_, offset_min=offset_min, SNR_min=1.1, select=select(0.5))\n",
"stp_SNR2 = mean(data*data) / mean(stp_error_*stp_error_)\n",
"ltp_SNR2 = mean(data*data) / mean(ltp_error_*ltp_error_)\n",
"\n",
"T = 20.0 / 1000 # 20 ms\n",
"n = int(df * T)\n",
"data_frames = audio.frames.split(data, n, pad=True)\n",
"stp_error_frames = audio.frames.split(stp_error_, n, pad=True)\n",
"ltp_error_frames = audio.frames.split(ltp_error_, n, pad=True)\n",
"\n",
"\n",
"fig, (ax1, ax2, ax3) = subplots(3,1, sharex=True)\n",
"stp_SNRs = [10.0 * log10(mean(d*d) / mean(e*e)) for d,e in zip(data_frames, stp_error_frames)]\n",
"ltp_SNRs = [10.0 * log10(mean(d*d) / mean(e*e)) for d,e in zip(data_frames, ltp_error_frames)]\n",
"ax1.plot(data, \"k\", alpha=0.1, label=\"original\")\n",
"ax1.plot(stp_error_, \"r\", alpha=0.5, label=\"stp residual\")\n",
"ax1.plot(ltp_error_, \"g\", alpha=1.0, label=\"stp+ltp residual\")\n",
"ax1.set_title(\"Waveforms\")\n",
"ax1.axis(\"tight\")\n",
"ax1.legend()\n",
"ax1.grid()\n",
"ax2.plot(r_[0:len(stp_SNRs)] * n, stp_SNRs, \"r\", alpha=0.5, label=\"stp SNR\")\n",
"ax2.plot([0,len(data_frames)*n], [10*log10(stp_SNR2), 10*log10(stp_SNR2)], \"r--\", alpha=0.5)\n",
"ax2.plot(r_[0:len(ltp_SNRs)] * n, ltp_SNRs, \"g\", label=\"stp+ltp SNR\")\n",
"ax2.plot([0,len(data_frames)*n], [10*log10(ltp_SNR2), 10*log10(ltp_SNR2)], \"g--\")\n",
"ax2.set_xlabel(\"sample index\")\n",
"ax2.set_ylabel(\"SNR [dB]\")\n",
"ax2.set_title(\"Signal-to-Noise Ratio\")\n",
"ax2.legend()\n",
"ax2.grid()\n",
"#n = len(data)\n",
"#t = r_[0:n] / df\n",
"ax3.plot(df / offset)\n",
"ax3.plot(2*df / offset, \"k.\", alpha=0.5, ms=0.25)\n",
"ax3.plot(3*df / offset, \"k.\", alpha=0.25, ms=0.25)\n",
"ax3.axis([0, len(data), 0, 400.0])\n",
"ax3.set_ylabel(\"frequency [Hz]\")\n",
"ax3.set_yticks(r_[0:400:100])\n",
"ax3.grid()"
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" \n",
" "
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"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"wave.write(ltp_error_, \"voice-error-stp-ltp.wav\", df=df)\n",
"display(Audio(\"voice.wav\"))\n",
"display(Audio(\"voice-error-stp.wav\"))\n",
"display(Audio(\"voice-error-stp-ltp.wav\"))"
]
}
],
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