{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Dependencies\n",
"==============="
]
},
{
"cell_type": "code",
"execution_count": 1,
"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": 2,
"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": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0., 1., 2., 3., 4.])"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fir = FIR([0.0, 1.0])\n",
"fir([1,2,3,4,5])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Linear Prediction"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/boisgera/miniconda2/envs/audio/lib/python2.7/site-packages/audio/lp.py:244: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.\n",
"To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.\n",
" a_, _, _ ,_ = np.linalg.lstsq(A, b) # can't trust the residues (may be [])\n"
]
},
{
"data": {
"text/plain": [
"array([0., 1.])"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x = 4*[-1.0, 1.0]\n",
"#figure()\n",
"#plot(x, \"k+\"); grid()\n",
"lp(x,order=2)#, method=\"autocorrelation\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Audio Source (NLTK)\n",
"============="
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"brush fires are common in the dry underbrush of nevada"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"utterances = audio.index.search(type=audio.index.Utterance)\n",
"utterance = utterances[16]\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": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"phone: h# (brush fires are common in the dry underbrush of nevada).\n",
"word: brush [b-r-ah-sh]\n",
"word: fires [f-ay-axr-z]\n",
"word: are [axr]\n",
"word: common [kcl-k-aa-m-ix-n]\n",
"word: in [ix-n]\n",
"word: the [dh-ix]\n",
"word: dry [dcl-d-r-ay]\n",
"phone: q (brush fires are common in the dry underbrush of nevada).\n",
"word: underbrush [ah-n-axr-bcl-b-r-ah-sh]\n",
"word: of [ax-v]\n",
"word: nevada [n-ax-v-aa-dx-ax]\n",
"phone: h# (brush fires are common in the dry underbrush of nevada).\n"
]
}
],
"source": [
"for item in utterance:\n",
" print type(item).__name__.lower() + \": \" + str(item)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" 0. ey (away [ix-w-ey]).\n",
" 1. ey (taken [tcl-t-ey-kcl-k-ix-nx]).\n",
" 2. ey (spray [s-pcl-p-r-ey]).\n",
" 3. ey (exchanged [ix-kcl-s-sh-ey-n-zh]).\n",
" 4. ey (vaguely [v-ey-gcl-g-l-iy]).\n",
" 5. ey (make [m-ey-kcl-k]).\n",
" 6. ey (occasionally [ow-kcl-k-ey-zh-l-ix]).\n",
" 7. ey (monday [m-ah-n-d-ey]).\n",
" 8. ey (always [ao-l-w-ey-z]).\n",
" 9. ey (situation [s-ix-tcl-ch-uw-ey-sh-en]).\n",
" 10. ey (clay [kcl-k-l-ey]).\n",
" 11. ey (straightforward [s-tcl-t-r-ey-q-f-ao-w-axr-dx]).\n",
" 12. ey (rachel's [r-ey-tcl-ch-el-z]).\n",
" 13. ey (maybe [m-ey-bcl-b-iy]).\n",
" 14. ey (they [dh-ey]).\n",
" 15. ey (take [tcl-t-ey-kcl-k]).\n",
" 16. ey (traits [tcl-t-r-ey-tcl-s]).\n",
" 17. ey (today's [tcl-t-ix-dx-ey-z]).\n",
" 18. ey (made [m-ey-dx]).\n",
" 19. ey (arbitrate [q-aa-r-bcl-b-ix-tcl-t-r-ey-tcl-t]).\n",
" 20. ey (cases [kcl-k-ey-s-ix-z]).\n",
" 21. ey (straight [s-tcl-t-r-ey-tcl]).\n",
" 22. ey (play [pcl-p-l-ey]).\n",
" 23. ey (repainted [r-iy-pcl-p-ey-nx-ix-dcl]).\n",
" 24. ey (waste [w-ey-s-tcl-t]).\n",
" 25. ey (masquerade [m-ae-s-kcl-k-axr-r-ey-dcl]).\n",
" 26. ey (imagination [ix-m-ae-dcl-jh-ix-n-ey-sh-ix-n]).\n",
" 27. ey (grade [gcl-g-r-ey-dx]).\n",
" 28. ey (a [ey]).\n",
" 29. ey (birthday [b-er-th-dcl-dh-ey]).\n",
" 30. ey (cupcakes [kcl-k-ah-pcl-k-ey-kcl-k-s]).\n",
" 31. ey (pays [pcl-p-ey-z]).\n",
" 32. ey (instantaneous [ih-n-s-tcl-t-ix-n-tcl-t-ey-n-iy-ix-s]).\n",
" 33. ey (contained [kcl-k-ix-n-tcl-t-ey-n-dcl]).\n",
" 34. ey (that [dh-ey-eh-tcl-t]).\n",
" 35. ey (slavery [s-l-ey-v-r-iy]).\n",
" 36. ey (change [ch-ey-n-dcl-jh]).\n",
" 37. ey (that [dh-ey-eh-tcl-t]).\n",
" 38. ey (unappreciated [ah-n-ax-pcl-p-r-iy-sh-iy-ey-dx-ix-dcl]).\n",
" 39. ey (today [t-ax-h-dcl-d-ey]).\n",
" 40. ey (coeducational [kcl-k-ow-eh-dcl-jh-ax-h-kcl-k-ey-sh-epi-n-el]).\n",
" 41. ey (holiday [hv-aa-l-eh-dcl-d-ey]).\n",
" 42. ey (aprons [ey-pcl-p-r-ix-n-z]).\n",
" 43. ey (available [ax-v-ey-l-ax-bcl-b-el]).\n",
" 44. ey (data [dcl-d-ey-dx-ix]).\n",
" 45. ey (famous [f-ey-m-ax-s]).\n",
" 46. ey (names [n-ey-m-z]).\n",
" 47. ey (a [ey]).\n",
" 48. ey (made [m-ey-dcl]).\n",
" 49. ey (agency [ey-dcl-jh-ix-n-s-iy]).\n",
" 50. ey (a [ey]).\n",
" 51. ey (great [gcl-g-r-ey-tcl]).\n",
" 52. ey (bluejay [bcl-b-l-ux-dcl-jh-ey]).\n",
" 53. ey (makes [m-ey-kcl-k-s]).\n",
" 54. ey (names [n-ey-m-z]).\n",
" 55. ey (interchangeably [q-ih-n-tcl-t-axr-tcl-ch-ey-n-dcl-jh-ix-bcl-b-l-iy]).\n",
" 56. ey (able [q-ey-bcl-el]).\n",
" 57. ey (hesitate [hv-eh-z-ix-tcl-t-ey-tcl]).\n",
" 58. ey (they [dh-ey]).\n",
" 59. ey (remained [r-iy-m-ey-n-dcl-d]).\n",
" 60. ey (may [m-ey]).\n",
" 61. ey (overweight [ow-v-ax-w-ey-tcl]).\n",
" 62. ey (display [dcl-d-ih-s-pcl-p-l-ey]).\n",
" 63. ey (misplaced [m-ix-s-pcl-p-l-ey-s-tcl-t]).\n",
" 64. ey (ate [ey-tcl]).\n",
" 65. ey (face [f-ey-s]).\n",
" 66. ey (they [dh-ey]).\n",
" 67. ey (paper [pcl-p-ey-pcl-p-ax]).\n",
" 68. ey (place [pcl-p-l-ey-s]).\n",
" 69. ey (they [dh-ey]).\n",
" 70. ey (eyestrain [ay-s-tcl-t-r-ey-n]).\n",
" 71. ey (a [q-ey]).\n",
" 72. ey (upgrade [q-ah-pcl-g-r-ey-dcl-jh]).\n",
" 73. ey (status [tcl-t-ey-dcl-d-ix-s]).\n",
" 74. ey (may [m-ey]).\n",
" 75. ey (cooperated [kcl-k-ow-ao-pcl-p-er-ey-dx-ix-dcl]).\n",
" 76. ey (make [m-ey-kcl]).\n",
" 77. ey (operates [aa-pcl-p-axr-r-ey-tcl-s]).\n",
" 78. ey (daytime [dcl-d-ey-tcl-t-ay-m]).\n",
" 79. ey (save [s-ey-v]).\n",
" 80. ey (they've [dh-ey-v]).\n",
" 81. ey (agency [ey-dcl-jh-ih-n-s-iy]).\n",
" 82. ey (alien [ey-l-iy-ix-n]).\n",
" 83. ey (interpretation [ix-n-tcl-t-er-v-axr-tcl-t-ey-sh-en]).\n",
" 84. ey (hatred [hv-ey-tcl-t-r-ix-dcl]).\n",
" 85. ey (celebrates [s-eh-l-ax-bcl-b-r-ey-tcl-s]).\n"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"audio.index.search(\"ey\", type=audio.index.Phone)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = wave.read(\"sounds/whisper.wav\")[0]\n",
"Audio(\"sounds/whisper.wav\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"audio.wave.write(data, \"voice.wav\", df=16000)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Short-Term Prediction\n",
"======================"
]
},
{
"cell_type": "code",
"execution_count": 10,
"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": 11,
"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": 12,
"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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""
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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": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"fires [f-ay-axr-z]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"ay (fires [f-ay-axr-z])."
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"6781"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"9315"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"display(utterance[2])\n",
"phone = utterance[2][1]\n",
"display(phone)\n",
"start, end = phone.span\n",
"display(start, end)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SNR 20.299399909750694 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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],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[]"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"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()\n",
"ax1.plot(r_[start:end-1],data[start:end-1], alpha=0.2,color=\"g\")\n"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
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""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"error = error / amax(abs(error))\n",
"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": 16,
"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": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"offset: 25 gain: 1.061276723494138\n"
]
},
{
"data": {
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" 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",
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" 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",
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" 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",
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"\n",
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"\n",
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" var titlebar = $(\n",
" '');\n",
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" '');\n",
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"\n",
"\n",
"\n",
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"\n",
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"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
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"\n",
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"\n",
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"\n",
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"\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"
},
{
"data": {
"text/plain": [
""
]
},
"execution_count": 17,
"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=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": 18,
"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"
},
{
"data": {
"text/plain": [
""
]
},
"execution_count": 18,
"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": 19,
"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": 20,
"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": 21,
"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": 22,
"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": 23,
"metadata": {},
"outputs": [
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"source": [
"ltp_error_ = ltp_error_ / amax(abs(ltp_error_))\n",
"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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