CARFAC input reconstruction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2542f1f9",
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   "source": [
    "# Generating the original audio signal given the output of CAR FAC\n",
    "\n",
    "In this code the original input is reconstructed from the output of CAR FAC model using the inverse of BM transfer function measured by this model. for this purpose a class is defined with all the synthesizing parameters and processes defined as its properties.\n",
    "Synthesis class consists of an initialization function with all the BM parameters as its input so each object of this class can be customized for different conditions with different cochlear characteristics for example various number of channels and frequecy ranges, hearing disorders or other specific condition. for instance:\n",
    "\n",
    "object = synthesis(200) \n",
    "\n",
    "gives us an object of this class in which the BM model has 200 sections. Notice that all the parameters are set with default values from CAR FAC model. There are other variables defined with static initial values as class properties. Also this class has 3 ohter functions as below:\n",
    " - transfer_function : cochlear transfer function measurement\n",
    " - input_reconstructor: estimating the original input sound\n",
    " - BM model: calculating the output of CAR FAC for selected input\n",
    " - wavPlayer: playing sounds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "840e635d",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "from pylab import *\n",
    "from scipy import signal\n",
    "import colorsys\n",
    "import scipy.constants as const\n",
    "import scipy\n",
    "from scipy.io import wavfile\n",
    "from IPython.core.display import HTML\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from __future__ import division\n",
    "\n",
    "class Synthesis:\n",
    "\n",
    "    f0 = 0.001                    # sweep start frequency\n",
    "    f1 = 20000                    # sweep end frequency\n",
    "    gain = 0.1                    # input gain\n",
    "    tau_in = 10e-3                # p329 transmitter creation time constant   \n",
    "    tau_out = 0.5e-3              # p329 transmitter depletion time constant\n",
    "    tau_IHC = 80e-6               # p329 ~8kHz LPF for IHC output\n",
    "    scale = 0.1                   # p313 NLF parameter\n",
    "    offset = 0.04                 # p313 NLF parameter \n",
    "    b = 1.0                       # automatic gain loop feedback (1=no undamping).\n",
    "    \n",
    "    def __init__(self,sec_number = 100,srate = 32000,npt = 64000,low_freq = 0.10,high_freq = 0.90,damping = 0.2,f_hpf = 20):\n",
    "        \n",
    "        self.fs = srate                                     # sample frequency\n",
    "        self.npoints = npt\n",
    "        self.dur = self.npoints/self.fs                     # stimulus length\n",
    "        self.t1 = arange(self.npoints)/self.fs              # sample times\n",
    "        self.stimulus = 0.9*signal.chirp(self.t1, self.f0, self.t1[-1], self.f1, method='logarithmic', phi=-90)  # create input tone\n",
    "        self.c_in = 1/(self.fs*self.tau_in)                                # p329 corresponding IIR coefficient\n",
    "        self.c_out = 1/(self.fs*self.tau_out)                              # p329 corresponding IIR coefficient\n",
    "        self.c_IHC = 1/(self.fs*self.tau_IHC)                              # corresponding IIR coefficient\n",
    "        self.nsec = sec_number                              # number of sections in the cochlea between\n",
    "        xlow = low_freq                                     # lowest frequency position along the cochlea and\n",
    "        xhigh = high_freq                                   # highest frequency position along the cochlea\n",
    "        x = linspace(xhigh,xlow,self.nsec)                  # position along the cochlea 1 = base, 0 = apex\n",
    "        f = 165.4*(10**(2.1*x)-1)                           # Greenwood for humans\n",
    "        self.a0 = cos(2*pi*f/self.fs)                       # a0 and c0 control the poles and zeros\n",
    "        self.c0 = sin(2*pi*f/self.fs)\n",
    "        self.r = 1 - damping*2*pi*f/self.fs                 # pole & zero radius actual\n",
    "        self.r1 = 1 - damping*2*pi*f/self.fs                # pole & zero radius minimum (set point)\n",
    "        self.h = self.c0                                         # p302 h=c0 puts the zeros 1/2 octave above poles\n",
    "        self.g = (1-2*self.a0*self.r+self.r*self.r)/(1-(2*self.a0-self.h*self.c0)*self.r+self.r*self.r)  # p303 this gives 0dB DC gain for BM\n",
    "        self.q = 1/(1+(2*pi*f_hpf/self.fs))                 # corresponding IIR coefficient\n",
    "        self.d_rz = 0.7*(1 - self.r1)                            # p310 relative undamping\n",
    "        self.W0 = zeros(self.nsec)                          # BM filter internal state\n",
    "        self.W1 = zeros(self.nsec)                          # BM filter internal state\n",
    "        self.W1old = zeros(self.nsec)                       # BM filter internal state at t-1\n",
    "        self.BM = zeros((self.nsec,self.npoints))           # BM displacement\n",
    "        self.BM_hpf = zeros((self.nsec,self.npoints))       # BM displacement high-pass filtered at 20Hz\n",
    "        self.trans = ones(self.nsec)                        # transmitter available\n",
    "        self.IHC = zeros((self.nsec,self.npoints))          # IHC output\n",
    "        self.IHCa = zeros((self.nsec,self.npoints))         # IHC filter internal state\n",
    "        self.BM_transfer_func = fft(zeros((self.nsec,self.npoints)))   # Basilar membrane transfer function\n",
    "\n",
    "\n",
    "\n",
    "    def transfer_function(self):\n",
    "        \n",
    "        self.BM[-1] = self.stimulus             # put stimulus at BM[-1] to provide input to BM[0]\n",
    "        self.BM[-1,-1] = 0                      # hack to make BM_hpf[nsec-1,0] work\n",
    "        for t in range(self.npoints):\n",
    "            for s in range(self.nsec):\n",
    "                self.W0new = self.BM[s-1,t] + self.r[s]*(self.a0[s]*self.W0[s] - self.c0[s]*self.W1[s])\n",
    "                self.W1[s] = self.r[s]*(self.a0[s]*self.W1[s] + self.c0[s]*self.W0[s])\n",
    "                self.W0[s] = self.W0new\n",
    "                self.BM[s,t] = self.g[s]*(self.BM[s-1,t] + self.h[s]*self.W1[s])\n",
    "            self.BM_hpf[:,t] = self.q*(self.BM_hpf[:,t-1] + self.BM[:,t] - self.BM[:,t-1])\n",
    "            self.z = (self.BM_hpf[:,t]+0.175).clip(0)   # p328\n",
    "            self.v_mem = self.z**3/(self.z**3+self.z**2+0.1)      # p328\n",
    "            self.IHC_new = self.v_mem*self.trans    \n",
    "            self.trans += self.c_in*(1-self.trans) - self.c_out*self.IHC_new   \n",
    "            self.IHCa[:,t] = (1-self.c_IHC)*self.IHCa[:,t-1] + self.c_IHC*self.IHC_new\n",
    "            self.IHC[:,t] = (1-self.c_IHC)*self.IHC[:,t-1] + self.c_IHC*self.IHCa[:,t]\n",
    "            self.v_OHC = self.W1 - self.W1old\n",
    "            self.W1old = self.W1.copy()\n",
    "            self.sqr=(self.v_OHC*self.scale+self.offset)**2\n",
    "            self.NLF= 1/(1 + (self.scale*self.v_OHC + self.offset)**2)\n",
    "            self.r = self.r1 + self.d_rz*(1-self.b)*self.NLF\n",
    "            self.g = (1-2*self.a0*self.r+self.r*self.r)/(1-(2*self.a0-self.h*self.c0)*self.r+self.r*self.r)\n",
    "        output = self.BM_hpf               # use this signal as the output signal\n",
    "        self.BM_transfer_func = fft(zeros((self.nsec,self.npoints)))\n",
    "        for s in range(self.nsec):\n",
    "            self.BM_transfer_func[s] = fft(output[s])/fft(self.stimulus)\n",
    "        return self.BM_transfer_func+10e-100\n",
    "    \n",
    "    def BM_model(self,stimulus):\n",
    "        \n",
    "        self.BM[-1] = stimulus             # put stimulus at BM[-1] to provide input to BM[0]\n",
    "        self.BM[-1,-1] = 0                 # hack to make BM_hpf[nsec-1,0] work\n",
    "        for t in range(self.npoints):\n",
    "            for s in range(self.nsec):\n",
    "                self.W0new = self.BM[s-1,t] + self.r[s]*(self.a0[s]*self.W0[s] - self.c0[s]*self.W1[s])\n",
    "                self.W1[s] = self.r[s]*(self.a0[s]*self.W1[s] + self.c0[s]*self.W0[s])\n",
    "                self.W0[s] = self.W0new\n",
    "                self.BM[s,t] = self.g[s]*(self.BM[s-1,t] + self.h[s]*self.W1[s])\n",
    "            self.BM_hpf[:,t] = self.q*(self.BM_hpf[:,t-1] + self.BM[:,t] - self.BM[:,t-1])\n",
    "            self.z = (self.BM_hpf[:,t]+0.175).clip(0)   # p328\n",
    "            self.v_mem = self.z**3/(self.z**3+self.z**2+0.1)      # p328\n",
    "            self.IHC_new = self.v_mem*self.trans    \n",
    "            self.trans += self.c_in*(1-self.trans) - self.c_out*self.IHC_new   \n",
    "            self.IHCa[:,t] = (1-self.c_IHC)*self.IHCa[:,t-1] + self.c_IHC*self.IHC_new\n",
    "            self.IHC[:,t] = (1-self.c_IHC)*self.IHC[:,t-1] + self.c_IHC*self.IHCa[:,t]\n",
    "            self.v_OHC = self.W1 - self.W1old\n",
    "            self.W1old = self.W1.copy()\n",
    "            self.sqr=(self.v_OHC*self.scale+self.offset)**2\n",
    "            self.NLF= 1/(1 + (self.scale*self.v_OHC + self.offset)**2)\n",
    "            self.r = self.r1 + self.d_rz*(1-self.b)*self.NLF\n",
    "            self.g = (1-2*self.a0*self.r+self.r*self.r)/(1-(2*self.a0-self.h*self.c0)*self.r+self.r*self.r)\n",
    "        return self.BM_hpf               # use this signal as the output signal\n",
    "        \n",
    "    \n",
    "    def input_reconstructor(self,BM_output,BM_trans_func):\n",
    "        \n",
    "        frequency_domain_input = fft(zeros(self.npoints))                              #Initializing frequancy-domain input array\n",
    "        for s in range(10,self.nsec):                                                     #Summing up the output of\n",
    "            frequency_domain_input += 1/self.nsec*(fft(BM_output[s])/BM_trans_func[s])                #all the synthesis filterbank channels\n",
    "        time_domain_input = real(ifft(frequency_domain_input))                         #Time-domain original input estimation\n",
    "        return time_domain_input\n",
    "    \n",
    "    def wavPlayer(self,filepath):\n",
    "        \"\"\" will display html 5 player for compatible browser\n",
    "\n",
    "        Parameters :\n",
    "        ------------\n",
    "        filepath : relative filepath with respect to the notebook directory ( where the .ipynb are not cwd)\n",
    "                   of the file to play\n",
    "\n",
    "        \"\"\"\n",
    "\n",
    "        src = \"\"\"\n",
    "        <head>\n",
    "        <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n",
    "        <title>Listen To The Sound</title>\n",
    "        </head>\n",
    "\n",
    "        <body>\n",
    "        <audio controls=\"controls\" style=\"width:600px\" >\n",
    "          <source src=\"files/%s\" type=\"audio/mp3\" />\n",
    "          Your browser does not support the audio element.\n",
    "        </audio>\n",
    "        </body>\n",
    "        \"\"\"%(filepath)\n",
    "        display(HTML(src))\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0349ae8a",
   "metadata": {},
   "source": [
    "At this step we can choose a random speech signal (VCV) to test the process with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "586e252f",
   "metadata": {},
   "outputs": [],
   "source": [
    "Audio_file_path = 'audios/S10M_L014_V2_M1_N1_CS0.wav'   #ALA\n",
    "# Audio_file_path = 'audios/S10M_L014_V2_M1_N2_CS0.wav'   #ALA\n",
    "# Audio_file_path = 'audios/S10M_L014_V2_M1_N3_CS0.wav'   #ALA\n",
    "# Audio_file_path = 'audios/S10M_L014_V3_M1_N1_CS0.wav'   #ALA\n",
    "# Audio_file_path = 'audios/sp15.wav'   #ALA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "0bd39180",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <head>\n",
       "        <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n",
       "        <title>Listen To The Sound</title>\n",
       "        </head>\n",
       "\n",
       "        <body>\n",
       "        <audio controls=\"controls\" style=\"width:600px\" >\n",
       "          <source src=\"files/audios/S10M_L014_V2_M1_N1_CS0.wav\" type=\"audio/mp3\" />\n",
       "          Your browser does not support the audio element.\n",
       "        </audio>\n",
       "        </body>\n",
       "        "
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      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The original audio fs: 16000\n",
      "The original audio number of samples: 23616\n"
     ]
    }
   ],
   "source": [
    "sample_rate , input_audio = wavfile.read(Audio_file_path, mmap = False)    #Reading the audio file\n",
    "original_npoints = size(input_audio)\n",
    "Analyser = Synthesis(100,sample_rate,original_npoints)                     #An object for BM analysis with original audio features\n",
    "Analyser.wavPlayer(Audio_file_path)                                        #Passing the original audio to player\n",
    "BM_output = Analyser.BM_model(input_audio)                                 #Output of BM model analysis (based on CAR) for original audio\n",
    "print(\"The original audio fs:\", sample_rate)\n",
    "print(\"The original audio number of samples:\", original_npoints)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "4fa281bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100\n",
      "23616\n"
     ]
    }
   ],
   "source": [
    "print(size(BM_output,0))\n",
    "print(size(BM_output,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "4572653d",
   "metadata": {},
   "outputs": [],
   "source": [
    "Synthesizer = Synthesis(100,sample_rate,original_npoints)                  #An object for synthesizing original audio from BM model output\n",
    "BM_tf = Synthesizer.transfer_function()                                    #Measuring the transfer function based on CAR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "81fe42d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100\n",
      "23616\n"
     ]
    }
   ],
   "source": [
    "print(size(BM_tf,0))\n",
    "print(size(BM_tf,1))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e88ed031",
   "metadata": {},
   "source": [
    "Syntesizing original input using transfer function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "49d7bddb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <head>\n",
       "        <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n",
       "        <title>Listen To The Sound</title>\n",
       "        </head>\n",
       "\n",
       "        <body>\n",
       "        <audio controls=\"controls\" style=\"width:600px\" >\n",
       "          <source src=\"files/estimated.wav\" type=\"audio/mp3\" />\n",
       "          Your browser does not support the audio element.\n",
       "        </audio>\n",
       "        </body>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "synt_audio = Synthesizer.input_reconstructor(BM_output,BM_tf)              #Synthesizing the etimasted input signal using output and TF\n",
    "\n",
    "estimated_audio = synt_audio[0:original_npoints]\n",
    "\n",
    "wavfile.write('estimated.wav', sample_rate, estimated_audio.astype(np.int16))   #Saving the synthesized input as a file\n",
    "Synthesizer.wavPlayer(\"estimated.wav\")                                          #Passing the synthesized estimated input to player\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de321541",
   "metadata": {},
   "source": [
    "Calculating RMSE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "db54976f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Root Mean Square Error: 5.6091774832605905\n"
     ]
    }
   ],
   "source": [
    "\n",
    "sample_Diff = input_audio - estimated_audio\n",
    "RMSE = 1/original_npoints*sqrt(sum((sample_Diff)**2))\n",
    "print(\"Root Mean Square Error:\",RMSE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "d6932a7a",
   "metadata": {},
   "outputs": [
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       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"1200\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "estimated_t = arange(original_npoints)/sample_rate\n",
    "figure(2, figsize=(12,4))                                                                                                                    #with the original input signal\n",
    "# ---------------------------------Plot of estimated input ---------------------------------------------\n",
    "estimated_input = subplot(1,2,1)\n",
    "plot(estimated_audio)\n",
    "# plot(estimated_t,synt_audio,'g')                         #Difference between original and estimated signals (in samples)\n",
    "xlabel('t (ms)')\n",
    "title('estimated input')\n",
    "# ---------------------------------Plot of original input ---------------------------------------------\n",
    "orignal_input = subplot(1,2,2,sharex=estimated_input)\n",
    "plot(input_audio)\n",
    "xlabel('t (ms)')\n",
    "title('original input')\n",
    "tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "e6b1db80",
   "metadata": {
    "scrolled": true
   },
   "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1200\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "estimated_t = arange(original_npoints)/sample_rate\n",
    "figure(4, figsize=(12,4))                                                                                                                    #with the original input signal\n",
    "# ---------------------------------Plot of estimated input ---------------------------------------------\n",
    "estimated_input = subplot(1,2,1)\n",
    "f, t, Sxx = signal.spectrogram(estimated_audio,sample_rate)\n",
    "plt.pcolormesh(t, f, Sxx, shading='gouraud')                        \n",
    "xlabel('t (seconds)')\n",
    "ylim([0, 2000])\n",
    "title('estimated input')\n",
    "# ---------------------------------Plot of original input ---------------------------------------------\n",
    "orignal_input = subplot(1,2,2)\n",
    "f, t, Sxx = signal.spectrogram(input_audio,sample_rate)\n",
    "plt.pcolormesh(t, f, Sxx, shading='gouraud')\n",
    "xlabel('t (seconds)')\n",
    "title('original input')\n",
    "ylim([0, 2000])\n",
    "tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "4be13bd1",
   "metadata": {},
   "outputs": [],
   "source": [
    "b=Synthesis(100,32000,64000)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "dca236d2",
   "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"1200\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(6, figsize=(12,4))                                                                                                                    #with the original input signal\n",
    "# ---------------------------------Plot of estimated input ---------------------------------------------\n",
    "estimated_input = subplot(1,2,1)\n",
    "f, t, Sxx = signal.spectrogram(Synthesizer.stimulus,Synthesizer.fs)\n",
    "plt.pcolormesh(t, f, Sxx, shading='gouraud')                        \n",
    "xlabel('t (seconds)')\n",
    "ylim([0, 3000])\n",
    "title('estimated input')\n",
    "# ---------------------------------Plot of original input ---------------------------------------------\n",
    "orignal_input = subplot(1,2,2)\n",
    "f, t, Sxx = signal.spectrogram(b.stimulus,32000)\n",
    "plt.pcolormesh(t, f, Sxx, shading='gouraud')\n",
    "xlabel('t (seconds)')\n",
    "title('original input')\n",
    "ylim([0, 3000])\n",
    "tight_layout()"
   ]
  }
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