{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis of spectral compression for narrowband photons with a cavity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import parmap\n",
    "import pyfftw\n",
    "import tqdm\n",
    "\n",
    "from scipy.optimize import minimize_scalar\n",
    "\n",
    "from numpy import pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fract(pw_spectrum, fraction):\n",
    "#     the vectorial form time is independent of the output, while the loop form is faster if the result is close to zero\n",
    "#     return np.nonzero(np.cumsum(pw_spectrum) > fraction * pw_spectrum.sum())[0][0]\n",
    "    s = np.sum(pw_spectrum)\n",
    "    j = 0\n",
    "    for idx, k in enumerate(pw_spectrum):\n",
    "        j += k\n",
    "        if j > (s * fraction):\n",
    "            break\n",
    "    return idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cavity_f(omega_v, omega_c, R1, R2, Gamma_c, separated=False):\n",
    "    Domega = omega_v - omega_c\n",
    "    num = np.sqrt(R1) - np.sqrt(R2) * np.exp(\n",
    "        -1j * Domega * np.log(R1 * R2) / (2 * pi * Gamma_c)\n",
    "    )\n",
    "    den = 1 - np.sqrt(R1 * R2) * np.exp(\n",
    "        -1j * Domega * np.log(R1 * R2) / (2 * pi * Gamma_c)\n",
    "    )\n",
    "    retval = num / den\n",
    "    if separated:\n",
    "        return [np.abs(retval), np.angle(retval)]\n",
    "    return retval\n",
    "\n",
    "\n",
    "def decay_state_f(omega_v, omega_0, Gamma_p, separated=False):\n",
    "    Domega = omega_v - omega_0\n",
    "    num = np.sqrt(Gamma_p)\n",
    "    den = np.pi * Gamma_p - 1j * Domega\n",
    "    retval = num / den\n",
    "    if separated:\n",
    "        return [np.abs(retval), np.angle(retval)]\n",
    "    return retval\n",
    "\n",
    "\n",
    "def decay_state_t(time_v, t_0, tau_p):\n",
    "    time_n = time_v - t_0\n",
    "    retval = (time_n > 0) * np.exp(-time_n / (2 * tau_p))\n",
    "    return retval / np.sqrt(np.power(retval, 2).sum())\n",
    "\n",
    "\n",
    "def psi_compressed_t(t, Gamma_p, Gamma_c, DeltaOmega):\n",
    "    state = (t > 0) * (\n",
    "        2 * pi * Gamma_c * np.exp(-t * pi * Gamma_c)\n",
    "        - (pi * (Gamma_c + Gamma_p) + 1j * DeltaOmega)\n",
    "        * np.exp(-t * (pi * Gamma_p + 1j * DeltaOmega))\n",
    "    )\n",
    "    state = state / (pi * (Gamma_p - Gamma_c) + 1j * DeltaOmega)\n",
    "    return state / np.sqrt(np.power(np.abs(state), 2).sum())\n",
    "\n",
    "\n",
    "def psi_compressed_f(Omega, Gamma, Gammac, norm=False):\n",
    "    retval = (\n",
    "        (\n",
    "            Gamma\n",
    "            * (\n",
    "                1\n",
    "                - 2\n",
    "                ** (\n",
    "                    (2 * Gamma * pi - Gammac * pi + 1j * Omega)\n",
    "                    / (Gamma * pi - Gammac * pi)\n",
    "                )\n",
    "                * (Gammac / (Gamma + Gammac))\n",
    "                ** ((Gamma * pi + 1j * Omega) / (Gamma * pi - Gammac * pi))\n",
    "            )\n",
    "        )\n",
    "        / ((Gamma - Gammac) * (Gamma * pi + 1j * Omega))\n",
    "        + (\n",
    "            Gammac\n",
    "            * (\n",
    "                1\n",
    "                - 2\n",
    "                ** (\n",
    "                    (2 * Gamma * pi - Gammac * pi + 1j * Omega)\n",
    "                    / (Gamma * pi - Gammac * pi)\n",
    "                )\n",
    "                * (Gammac / (Gamma + Gammac))\n",
    "                ** ((Gamma * pi + 1j * Omega) / (Gamma * pi - Gammac * pi))\n",
    "            )\n",
    "        )\n",
    "        / ((Gamma - Gammac) * (Gamma * pi + 1j * Omega))\n",
    "        - (\n",
    "            2\n",
    "            * Gammac\n",
    "            * (\n",
    "                1\n",
    "                - 2 ** ((Gamma * pi + 1j * Omega) / (Gamma * pi - Gammac * pi))\n",
    "                * (Gammac / (Gamma + Gammac))\n",
    "                ** ((Gammac * pi + 1j * Omega) / (Gamma * pi - Gammac * pi))\n",
    "            )\n",
    "        )\n",
    "        / ((Gamma - Gammac) * (Gammac * pi + 1j * Omega))\n",
    "    )\n",
    "    if norm:\n",
    "        retval /= np.max(retval)\n",
    "    return retval"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Test of the functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "omega_max = 10000\n",
    "n_points = int(1e5) + 1\n",
    "omega_v, omega_step = np.linspace(-omega_max, omega_max, n_points, retstep=True)\n",
    "spec = decay_state_f(omega_v, 0, 26.54, True)\n",
    "\n",
    "fig, (ax0, ax1, ax3) = plt.subplots(3, 1, sharex=True, figsize=(14, 10))\n",
    "\n",
    "ax0.set_title('Phase of the cavity transformation')\n",
    "ax0.set_yticks([-1, 0, 1])\n",
    "ax0.set_yticklabels([r'-$\\pi$', '0', r'$\\pi$'])\n",
    "ax0.plot(omega_v, cavity_f(omega_v, 0, .99, 1, 3, True)[1] / np.pi)\n",
    "\n",
    "ax1.set_title('Frequency features of exponentially decaying state')\n",
    "ax1.set_yticklabels([r'-$\\frac{\\pi}{2}$', '0', r'$\\frac{\\pi}{2}$'])\n",
    "ax1.set_ylabel('Phase')\n",
    "ax1.set_yticks([-.5, 0, .5])\n",
    "ax1.plot(omega_v, spec[1] / np.pi)\n",
    "\n",
    "ax1b = ax1.twinx()\n",
    "ax1b.set_ylabel('Power spectrum')\n",
    "ax1b.plot(omega_v, (spec[0])**2, 'r');\n",
    "\n",
    "ax3.set_title('Frequency features of compressed state (from analytical solution)')\n",
    "ax3.set_xlabel('Detuning from central frequency (MHz)')\n",
    "\n",
    "[ax3.plot(omega_v, np.abs(psi_compressed_f(omega_v, 26.54, k, norm=True))**2 , label='{} MHz'.format(k))\n",
    "  for k in [1e-2, 1, 7, 30]]\n",
    "ax3.plot(omega_v, (spec[0])**2 /np.max((spec[0])**2), label='Original')\n",
    "ax3.legend(title='$\\Gamma_c$')\n",
    "plt.xlim(-500, 500);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26.292396598781227"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idx_50 = fract((spec[0][n_points//2:])**2, .5)\n",
    "omega_v[idx_50 + n_points//2] / pi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analytic approach"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the analytical approach is limited to the case of $\\Delta\\omega=0$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.116983267519338"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def analytical_bw(Gamma_c, Gamma_p, freq_v):\n",
    "    idx_50 = fract(np.abs(psi_compressed_f(freq_v, Gamma_p, Gamma_c, True))**2, .5)\n",
    "    return freq_v[idx_50] / pi\n",
    "\n",
    "# test\n",
    "freq_v = np.linspace(0, 1e4, int(1e5))\n",
    "analytical_bw(7, 26.54, freq_v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "512it [00:08, 58.68it/s]                         \n"
     ]
    }
   ],
   "source": [
    "Gamma_p = 26.54\n",
    "# gammas = np.linspace(.01, 20, 500) * Gamma_p\n",
    "gammas = np.logspace(-2, 2, 500) * Gamma_p\n",
    "\n",
    "bws = parmap.map(analytical_bw, gammas, Gamma_p, freq_v, pm_pbar=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14, 7))\n",
    "plt.plot(gammas, bws)\n",
    "gammas[np.argmin(bws)]\n",
    "plt.xlabel('$\\Gamma_c$ (MHz)')\n",
    "plt.ylabel('Resulting BW (MHz)')\n",
    "plt.semilogx();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "gamma_min = gammas[np.argmin(bws)]\n",
    "res = minimize_scalar(\n",
    "    analytical_bw,\n",
    "    args=(Gamma_p, freq_v),\n",
    "    bounds=(gamma_min - 3, gamma_min + 3),\n",
    "    method=\"bounded\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimal bandwidth 7.295 MHz\n"
     ]
    }
   ],
   "source": [
    "if res.status == 0:\n",
    "    print('Optimal bandwidth {:.3f} MHz'.format(res.x))\n",
    "Gamma_c_opt = res.x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Applying dispersion directly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frequency resolution 0.2 MHz\n"
     ]
    }
   ],
   "source": [
    "omega_max = 10000\n",
    "n_points = int(1e5) + 1\n",
    "omega_v, omega_step = np.linspace(-omega_max, omega_max, n_points, retstep=True)\n",
    "Gamma_p = 26.54\n",
    "dispersed_state_f = cavity_f(omega_v, 0, .99, 1, 7) * decay_state_f(omega_v, 0, Gamma_p)\n",
    "print('Frequency resolution {} MHz'.format(omega_step))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14, 7))\n",
    "ax1 = plt.gca()\n",
    "ax1.plot(\n",
    "    omega_v, decay_state_f(omega_v, 0, 26.54, separated=True)[1] / pi, label=\"Original\"\n",
    ")\n",
    "ax1.plot(omega_v, np.angle(dispersed_state_f) / pi, label=\"After cavity\")\n",
    "plt.yticks([-1, 0, 1], [\"$-\\pi$\", \"0\", \"$\\pi$\"])\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(omega_v, np.abs(dispersed_state_f) ** 2, \"r\", label='Power spectrum')\n",
    "\n",
    "lines1, labels1 = ax1.get_legend_handles_labels()\n",
    "lines2, labels2 = ax2.get_legend_handles_labels()\n",
    "ax2.legend(lines1 + lines2, labels1 + labels2);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7.830423200121366, 26.292396598781227)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "a = pyfftw.empty_aligned(n_points, dtype='complex128')\n",
    "b = pyfftw.empty_aligned(n_points, dtype='complex128')\n",
    "c = pyfftw.empty_aligned(n_points, dtype='float64')\n",
    "d = pyfftw.empty_aligned(n_points//2 + 1, dtype='complex128')\n",
    "\n",
    "fft_object = pyfftw.FFTW(a, b, direction='FFTW_BACKWARD')\n",
    "fft_object2 = pyfftw.FFTW(c, d)\n",
    "\n",
    "a[:] = dispersed_state_f\n",
    "b = fft_object()\n",
    "\n",
    "c[:] = np.abs(b)\n",
    "d = fft_object2()\n",
    "\n",
    "d_ps = np.abs(np.r_[d[::-1], d[1:]])**2\n",
    "d_ps = d_ps / np.sum(d_ps)\n",
    "\n",
    "plt.figure(figsize=(14, 7))\n",
    "plt.plot(omega_v, d_ps)\n",
    "plt.plot(omega_v, np.abs(dispersed_state_f)**2 / np.sum(np.abs(dispersed_state_f)**2) )\n",
    "plt.xlim(-500, 500);\n",
    "\n",
    "fract(np.abs(d)**2, .5)\n",
    "omega_v[n_points //2 + fract(np.abs(d)**2, .5)] / pi, omega_v[n_points //2 + fract(np.abs(a[n_points//2:])**2, .5)] / pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frequency resolution 0.02\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "3183.098861837907"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "omega_max = 10000\n",
    "n_points = int(1e6) + 1\n",
    "omega_v, omega_step = np.linspace(-omega_max, omega_max, n_points, retstep=True)\n",
    "print('Frequency resolution {}'.format(omega_step))\n",
    "\n",
    "Gamma_p = 26.54\n",
    "dispersed_state_f = cavity_f(omega_v, 0, .99, 1, 7) * decay_state_f(omega_v, 0, Gamma_p)\n",
    "\n",
    "a = pyfftw.empty_aligned(n_points, dtype='complex128')\n",
    "b = pyfftw.empty_aligned(n_points, dtype='complex128')\n",
    "c = pyfftw.empty_aligned(n_points, dtype='complex128')\n",
    "d = pyfftw.empty_aligned(n_points, dtype='complex128')\n",
    "\n",
    "fft_object = pyfftw.FFTW(a, b, direction='FFTW_BACKWARD')\n",
    "fft_object2 = pyfftw.FFTW(c, d)\n",
    "\n",
    "\n",
    "def psi_compressed_fft(omega_v, Gamma_p, Gamma_c, DeltaOmega, phase_switch_time=0, mirrored=True):\n",
    "    dispersed_state_f = cavity_f(omega_v, DeltaOmega, .99, 1, Gamma_c) * decay_state_f(omega_v, 0, Gamma_p)\n",
    "    phase_v = np.ones(n_points)\n",
    "    phase_v[phase_v > phase_switch_time] = -1\n",
    "    a[:] = dispersed_state_f\n",
    "    b = fft_object()\n",
    "\n",
    "#     c[:] = np.abs(b) # removes phase\n",
    "    \n",
    "    c[:] = b * phase_v\n",
    "    d = fft_object2()\n",
    "    if mirrored:\n",
    "        return np.r_[d[::-1], d[1:]]\n",
    "    return d\n",
    "\n",
    "\n",
    "def fft_bw(Gamma_p, Gamma_c, omega_v, DeltaOmega):\n",
    "    psi_compressed_fft(omega_v, Gamma_p, Gamma_c, DeltaOmega, mirrored=False)\n",
    "    return omega_v[len(omega_v) //2 + fract(np.abs(d)**2, .5)] / pi\n",
    "\n",
    "fft_bw(Gamma_p, Gamma_c_opt, omega_v, DeltaOmega=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Checking the effects of the cavity bandwidth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "time bin 0.050 ns\n",
      "frequency bin 0.020 MHz\n"
     ]
    }
   ],
   "source": [
    "DeltaOmega = 0\n",
    "Gamma_p = 26.53\n",
    "gammas = np.array([0.1, 0.3, 1, 3]) * (Gamma_p + 1e-11)\n",
    "\n",
    "time_v = np.fft.fftshift(np.fft.fftfreq(n_points, omega_step))\n",
    "time_v_lim = time_v[time_v>-1]\n",
    "time_step = time_v[1] - time_v[0]\n",
    "\n",
    "psi_start = decay_state_t(time_v_lim, 0, 1 / (2 * pi * Gamma_p))\n",
    "psi_start_f = decay_state_f(omega_v, 0, Gamma_p)\n",
    "psi_start_fft = np.fft.rfft(np.abs(psi_start), norm='ortho')\n",
    "\n",
    "psi_final = [psi_compressed_t(time_v_lim, Gamma_p, k, DeltaOmega) for k in gammas]\n",
    "psi_final_fft = [psi_compressed_fft(omega_v, Gamma_p, k, DeltaOmega) for k in gammas]\n",
    "# # psi_final_fft /= psi_final_fft.max()\n",
    "\n",
    "print(('time bin {:.3f} ns\\n'\n",
    "       'frequency bin {:.3f} MHz').format(time_step*1e3, omega_step))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"1296\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(18, 6))\n",
    "\n",
    "ax1.set_title('Time')\n",
    "ax1.plot(time_v_lim * 1e3, np.abs(psi_start) ** 2, label = 'Original')\n",
    "\n",
    "[ax1.plot(time_v_lim * 1e3, np.abs(k) ** 2, label='{:.1f} MHz'.format(j)) for k, j in zip(psi_final, gammas)]\n",
    "ax1.set_xlim(-3, 100)\n",
    "ax1.legend()\n",
    "ax1.set_xlabel(\"$\\Delta t$ (ns)\")\n",
    "\n",
    "\n",
    "ax2.set_title('Frequency')\n",
    "ax2.plot(omega_v, np.abs(psi_start_f) ** 2, label = 'Original')\n",
    "[ax2.plot(omega_v, np.abs(k) ** 2, label='{:.1f} MHz'.format(j)) for k, j in zip(psi_final_fft, gammas)]\n",
    "\n",
    "ax2.set_xlim(-300, 300)\n",
    "ax2.set_xlabel(\"$\\Delta \\omega$ (MHz)\")\n",
    "ax2.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scan parameters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sanity check, compare with the analytic one for the case of $\\Delta\\omega=0$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "512it [00:59,  7.42it/s]                         \n"
     ]
    }
   ],
   "source": [
    "gammas_v = np.logspace(-2, 2, 500) * Gamma_p\n",
    "Gamma_p = 26.54\n",
    "\n",
    "\n",
    "def u_func(Gamma_c, Gamma_p, omega_v):\n",
    "    return fft_bw(Gamma_p, Gamma_c, omega_v, DeltaOmega=0)\n",
    "\n",
    "bws = parmap.map(u_func, gammas_v, Gamma_p, omega_v, pm_pbar=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14, 7))\n",
    "plt.plot(gammas_v, bws)\n",
    "plt.xlabel('$\\Gamma_c$ (MHz)')\n",
    "plt.ylabel('Resulting BW (MHz)')\n",
    "plt.semilogx();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "105it [00:13,  8.51it/s]                        \n",
      "105it [00:14,  7.42it/s]                        \n",
      "105it [00:13,  8.24it/s]                        \n",
      "105it [00:13,  8.45it/s]                        \n",
      "105it [00:13,  7.93it/s]                        \n"
     ]
    }
   ],
   "source": [
    "Gamma_p = 26.54\n",
    "deltas_v = np.linspace(-15, 15, 101) * Gamma_p\n",
    "gammas = np.array([.1, .3, 1, 3, 10]) * Gamma_c_opt\n",
    "\n",
    "def u_func(DeltaOmega, Gamma_c, Gamma_p, omega_v):\n",
    "    return fft_bw(Gamma_p, Gamma_c, omega_v, DeltaOmega)\n",
    "\n",
    "bws = [parmap.map(u_func, deltas_v, k, Gamma_p, omega_v, pm_pbar=True) for k in gammas]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18, 6))\n",
    "[plt.plot(deltas_v, k, label='{:.2f}'.format(j)) for k, j in zip(bws, gammas)]\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "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, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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+lhg8Sn9zd9aP1r+YpN2FDoJ/f//+KPzuAUWmD4WWPypr62QTmOS5Cy5TTsKnaTgFnR16gw52tOtHYdOAlhg+lhg8Sfr2bul25ggdVXF2lHoFOR+8p41rP69NO0odBLAAtPHAosvxRmfcNh8gugLBCR/0U3SZkyWhgN7teNQmMAC08cCix8Bv1/K0q6Ug2aydLa3asehCNhblic9xnjJXP4j7SgUJrDA9LHA4odv/TIR0yNZm1dpR6EISl/1kIjpkeKsT7WjUBjAAtPHAosPjfW10mpOkaIF13FG8wTTfrhZDprJUpZ2pfh7e7Xj0CiBBaaPBRYfMp+7R3qM8VJTkqsdhaIga/Mq60fp6xZrR6FRAgtMHwvM+Qq/3GwN3Fj9iHYUipK+QEAKF14vbcZkOVRXrR2HRgEsMH0sMGfr7uqUPakXy76UC6Srs107DkXR3vIC6TYmSM7S27Wj0CiABaaPBeZs6WseFzE9kv/5Bu0oFAPBGTpyP31fOwqdAFhg+lhgzlVbXijdxgTJXnqndhSKkZ7uLqlOvVQOmOdJR1uLdhwaAVhg+lhgzhTw+6VowXU8JuJCwR+re1ferx2FRgCXF9gsAKUAKgA8McT9pwFYZ9+fASA55L659vJSALfYy84BsBXAbgC7ADw8mhAsMGfyrVssYnok44Pl2lFIge/Fn4jfSLJOWEqOBBcX2FgAlQDOBfBVAPkALhm0zkMAVtnX74VVZrDXy4dVcNPtxxkLYAqAK+11/gFA2RCPeRwWmPPsrymRDuMsKVh4A3/z5VKtzQ1y0EyWqtTLpLurUzsODQEuLrBrAGwJuT3XvoTaYq8HAOMANAIYM8S6oeuF2gTgX04UhAXmLH2BgBQsvEE6jLNkf02JdhxSlPfZ+/a8l7/SjkJDgIsL7B4Ar4fcvg/AikHrFAGYGnK7EsBEe705IcvfsB8vVDKAvQA8JwrCAnOWjA+W8wet1C9j+b3iN5KkNGerdhQaBCywfpEssK8ByAFw9wjPfz+sFz972rRp2u8Dsh3cVyVtxmQpWnCdBPx+7TjkAIdbGqXenC41qZdI15EO7TgUAi4usGjtQvyKffux0QbhFpgzBPx+KVh4g3Qak2RfZZF2HHKQgm1/sEYlvvKgdhQKARcX2DgAVbAGYQQHccwYtM4vMHAQx3r7+gwMHMRRBWsQxxgA7wB4PpwgLDBn8L6XZu06XL9MOwo5kO+FORIwkqwh9uQIcHGBAcBsWCMFKwHMs5elAbjTvn46gA2whstnwhqxGDTP/rtSALfay64DIAAKAOTZl9knCsEC01dV5JNuY4LsXDyLow5pSO2Hm6Uu5XypS7lADrc0aschYYE5AgtMV9eRDqlKvVwazGnSdHCfdhxysOKMT6TXOEOynr1bOwoJC8wRWGC6vCsfEDE9kvfZOu0oFAeCc2NmbnxZO4rrgQWmjwWmp2D7h9Zxr5d+qh2F4oS/t1d2Pf3P0mGcxcE+ysAC08cC03GorlqazKlSnXqpHOlo045DceTAnjI5bE6R0vlXydGebu04rgUWmD4WWOz1Hu2RXQuulU5jktQU52jHoTiU8+c1HFqvDCwwfSyw2Et/7Vc8jkGnzPfiT0RMj+zcslY7iiuBBaaPBRZb+Z9vsGaZf/7H2lEoznV3dUrZ/JnSZkyW2vJC7TiuAxaYPhZY7BzYWy7N5lSpSr1cujrbteNQAqirLpEW82ypTL2cx1JjDCwwfSyw2OjqbJeytCul3Zgse0pzteNQAsn/fIMEjCTJfO6H/CF8DIEFpo8FFn19gYBkPfsDEdMjuZ+8px2HElD66/9pn8VgiXYU1wALTB8LLPq876ZY53Va87h2FEpQ/t5eyVt0kxw1xkvhl5u147gCWGD6WGDRVbD9Q/EbSZKz5DaeIoWi6nBLo9SkzpAW82wO6ogBsMD0scCiZ295gbSaU6Qq9TLpaGvRjkMusK+ySFrMs6UmdQYn/Y0ysMD0scCio/nQfqlNuVCazamc8odiqujLj+SoMV7yF90k/t5e7TgJCywwfSywyOvqbJfi+d+WbmOCFGf+VTsOuZBv/TJ7ns1/48jEKAELTB8LLLICfr/kLL1DAkaSNd0PkZLgmQ7S335SO0pCAgtMHwsssryvPGjNUbfW1I5CLhfw+yV72fc5bVmUgAWmjwUWOd53U/tPj8LdNuQE3V2dUrjweuuY2NYPtOMkFLDA9LHAIiPzD8+LmB7JWXo7D5yTo7S1NklF2jel05gkZTu3a8dJGGCB6WOBnbqcP68Rv5Ek+YtulO6uTu04RMdpqKuRupTzpdn8hlTtytSOkxDAAtPHAjs1+Vs/kB5jvBQ/fbV0trdqxyEa1r7KIjloJkujeQ7n44wAsMD0scBO3q70P0unMUkq0r4lrc0N2nGITqimJFcazXPkoJks+yp3a8eJa2CB6WOBnZyiLz+yzqicOkMaDuzVjkM0alVFPmkxz5b95nlyYE+Zdpy4BRaYPhZY+Aq/2CRHjIlSzfKiOFWWu0MOm1+XupQLpK6qWDtOXAILTB8LLDwF2zdKlzFBqlIvk8b6Wu04RCetNGebtJpTpN6cLnvL8rTjxB2wwPSxwEYv77N1dnldLk0H92nHITplFQVeaTKnSoM5jaMTwwQWmD4W2OhkbXpFjhrjpTztCmk+tF87DlHE1BTnyEEzWZrNb0hZ7g7tOHEDLDB9LLAT8743X8T0SNGC70hba5N2HKKI21dZJPvN86TdmCyFOzZqx4kLYIHpY4ENry8QkPTXHrZm2Fhym3Qd6dCORBQ19bUVUpV6mfQY4yVr0yvacRwPLDB9LLCh9XR3Scbye0VMj2Q8/384PRS5QmtzgxQtuK5/FnvO6Tk8sMD0scCO19pY3/8h9q5+lB9icpXurk7JXva9/ompe4/2aEdyJLDA9LHABtpblid7Uy6SHuNM7kYh1wr4/f3nE8tfdKO0Nh3SjuQ4YIHpY4EdU/jlZmk1p0izOVWKfVu04xCpy/jgOekxxsvelIukpoTzJ4YCC0wfC8warOFda0qvcYbUpM7gHHFEIXb7PpZG8xxpMyZL3ufrteM4Blhg+txeYO2HmyVn6R0ipkd2LpnNYfJEQziwp0zK066QgJEk6W/+VgJ+v3YkdWCB6XNzgdWU5EpN6gzxG0nifecpDtYgGsGRjjbJevZu+7jYd10/Gw1YYPrcWmBZm1ZKh3GWNJlTpfCLTdpxiOJCXyAgvvXLpNuYIAfNZNnt+1g7khqwwPS5rcDaWpv6/xW5++lrpL62QjsSUdypyP+b1KZcKL3GGZL+9pOu/J0kWGD63FRgxVmfSl3KBdaHbs3j/H0L0Sloa23qP368a8G1Ulddoh0ppuDyApsFoBRABYAnhrj/NADr7PszACSH3DfXXl4K4JaQ5WsAHAJQNNoQbiiwoz3dkv7Gb6TXOEP2m+dJccYn2pGIEkJfICCZf3xJ2o3J0m5MlowPX3TNsWS4uMDGAqgEcC6ArwLIB3DJoHUeArDKvn4vrDKDvV4+rIKbbj/OWPu+6wFcCRZYv4r8v0lF2rdETI9kLbtLWpsbtCMRJZy66hLZteDa/tG8bjhXHlxcYNcA2BJye659CbXFXg8AxgFoBDBmiHVD1wOsLTXXF1hPd5ekv/6YHDXGS4M5TXI+fkc7ElFC8/f2inetIT3GmdJini2Zf3wpobfG4OICuwfA6yG37wOwYtA6RQCmhtyuBDDRXm9OyPI37McLSobLC6w0Z6tUpV4uYnok87l7pLWxXjsSkWvU7M6W4qevFjE9UrDwfyXsxABggfWLdYHdD+vFz542bZr2+yBiWhoOiO+FORIwkuSgmSy5n76vHYnIlQJ+v/h+/4y0G5PliDFRvO88JUd7urVjRRRcXGDchRhBAb9fMj5YLs3mN6TXOEO8Kx+Q9sPN2rGIXK++tkJ2Lp4lYnqkOnWGFGxPnJNlwsUFNg5AFaxBGMFBHDMGrfMLDBzEsd6+PgMDB3FU4dggDsBlBVaas02K53+7/3ddVUU+7UhEFKIvEJCdW9bKvpQLrEEei29NiN2KcHGBAcBsAGWwdg3Os5elAbjTvn46gA2whstnwhqxGDTP/rtSALeGLH8fwAEAvQD2AfjZiULEa4HVVZdI1rK7REyPNJrnSOYfVyT0AWOieNd1pEPS35orncYk6TYmSPprD8f1nhK4vMAcId4KrLXpkHhfeVB6jDPliDFR0lc/EtcfAiK3Obivqn82nCZzqnh/97R0d3VqxwobWGD64qXAOttbxfvOU9Jini0BI0kyl/+I00ARxbHSnK1StOA7IqZH6lLOl8yNL8fVlFRggelzeoEd6WgT77sp0mie03922Ir8v2nHIqII6AsEpGDbH6Q87QoR0yNVqZfLzo/fiovTtYAFps+pBdbV2S7e9+ZLgzlNxPRI4cLreZZkogQV8Psl+6PVsjflInvE4qWS9adXHb1FBhaYPqcVWGvTIUl/a25/cRUtuE52pf9ZOxYRxYC/t1eyNq+S6tQZIqZH9qZcJBkfvujI35CBBabPKQV2YE+ZeFfeLx3GWf27Cgu/3Kwdi4gUBPx+yfnLm/3zmB4wzxXvWsNRc5mCBaZPu8DKcndI5nP3yFFjvPQaZ0jWs3dLRYFXNRMROUNfICC5n74vRfZEwR3GWeJd8TPZV1mkHY0F5gQaBdZ1pEMyN74sJfP/ScT0SKcxSbwv/1z217jrfEJENHrleV9I1rM/kKPGeAkYSbJzyWwp3LFRbcAHWGD6YllgddUlkr7ql9JsThUxPbIn9WLx/u5pR+0WICJnO1RXLemv/UpazLNFTI/Uplwo3neekqaD+2KaAywwfdEusK7Odsn606uSv+hGCRhJ4g/5lxNnziCik9V1pEOyNq2U3U9fI2J6pMc4U7KXfV8Kv9wck60ysMD0RaPA+gIBKcn6THwv3ieHza/bB2HPk/TXH5MDe8sj/nxE5G7Vu7PE+/L/k8PmlP4fRqevfkT2luVF7TnBAtMXyQKrLS+U9Dd/KzX2ENgjxkTJevYHUvjFprj4YSIRxbeuznbJ2rRS8hfdKH4jScT0SOn8q8T3/kJpPrQ/os8FFpi+Uy2wuuoS8b79ZP8v6a1Z4a+WjA+ek7bWpgi9VYiIwnOorlq8aw2ptE9ue9QYL3nP3CwZH74QkZPcggWm72QKbF/lbvG+myKl86/qL63S+VeJd60pB/aUnfIbg4gokioLfeJ95UGpSzm/v8zyF90ovvXLpLG+9qQeEywwfaMpsIDfL8VZn0r6q/8h1amX9pdWedoVkv72kwlxbh8iSnx9gYCU5e6Q9Fd/KbUpF4qYHvEbSVK04Drxvpsa1jEzsMD0DVdgHW0tkvvJe5Lx/I/7p3XqNc6QogXfEe97aY74ISER0cnqCwSsLbPVjw74h/nelIvE+/LPpWD7Runp7hr278EC0xcsMH9vr5TmbJP0N38ruxZcKz3GeBHTI23GZMle9j3J2rxKWpsOxeq9RUQUU3XVJeL7/SLJW3STdBsT+mf+2LlktvjWLz1uTxNYYPouOneqZC+9s/9Hgf27Blf9Ugp3jPwvECKiRNTZ3iq5f/2d+F68T+rN6f3fjXUpF4jvhTmS/d9rWGBOMHPK38lBM1kyl/9Isv706kkf0CQiSkR9gYDsKc0V3/sLZefiWdJuTBYxPSwwJ7hsxsWcEYOIaJR6j/ZIccYnLDAn0J6NnogoHoEFpo8FRkQUPrDA9LHAiIjCBxaYPhYYEVH4wALTxwIjIgofWGD6WGBEROEDC0wfC4yIKHxggeljgRERhQ8sMH0sMCKi8IEFpo8FRkQUPrDA9LHAiIjCBxaYPhYYEVH4wALTxwIjIgofWGD6WGBEROEDC0wfC4yIKHxggeljgRERhQ8sMH0sMCKi8IEFpo8FRkQUPrDA9LHAiIjCB5cX2CwApQAqADwxxP2nAVhn358BIDnkvrn28lIAt4TxmMdhgRERhQ8uLrCxACoBnAvgqwDyAVwyaJ2HAKyyr98Lq8xgr5cPq+RxFOkAAAWeSURBVOCm248zdpSPeRwWGBFR+ODiArsGwJaQ23PtS6gt9noAMA5AI4AxQ6wbXG80j3kcFhgRUfjg4gK7B8DrIbfvA7Bi0DpFAKaG3K4EMNFeb07I8jfsxxvNYx6HBUZEFD6wwPrFusDuh/XiZ0+bNk37fUBEFHfg4gLjLkQiojgGFxfYOABVsAZhBAdczBi0zi8wcBDHevv6DAwcxFEFawDHaB7zOCwwIqLwwcUFBgCzAZTB2jU4z16WBuBO+/rpADbAGhKfCWt0YdA8++9KAdx6gsccEQuMiCh8cHmBOQILjIgofGCB6WOBERGFDywwfSwwIqLwgQWmjwVGRBQ+sMD0scCIiMIHFpg+FhgRUfjAAnOEdtizcjj8UuOADMzJjMzJnMFLO0hdtnaAUWLOyIqHnPGQEWDOSGNOGrV4+Z/AnJEVDznjISPAnJHGnDRq8fI/gTkjKx5yxkNGgDkjjTlp1O7XDjBKzBlZ8ZAzHjICzBlpzElERERERESkZimAEgAFAP4I4IyQ++bCmvW+FMAtIctn2csqADwRm5j4IYBdAPoAXBWyPBlAF4A8+7Iq5L6ZAAph5XwR1nnTtHICzno9Q6UAqMOx13B2yH3DZdai/VqNpAbW+y0Px46DnAngrwDK7f+OV8i1BsAhWCfDDRou1xhYn5UKWN8JV8Yu5pA5U+Cs9+Y5ALYC2A3rc/6wvdyJr6cr/Cusc4YBwGL7AgCXYOD5xSphnV9srH39XBw7v9glMch5MYALAWzD8QVWNMT6gHW6mathvYn+goGnmImW4XI67fUMlQLg10MsHy6zFie8ViOpgXV29FBLcKxon8Cxz1csXQ/rizP0czJcrtmwPitjYH12MmKUERg6Zwqc9d6cgmMl9A+wTlN1CZz5errOXQDes69H9AzPEbQNoyuwKbC2LIN+DODVqKU63jYMzOnU1xMY/ktiuMxanPBajaQGxxdYKaz3Iuz/lsYyUIhkDPycDJfrVViflaHWi4VkjK7AnPLe3ATgX+Dc19NV/gRgjn19Rch1AHgDwD325fWQ5ffZ68bKNhxfYJ0AcgFsB/Ade/lVAD4NWe87AD6Kfrx+2zAwp1NfT8D6kqiBtYtjDY7t/hgusxYnvFYjqQawE0AOjo1Eaw25f8yg27GUjIHFMFyujwBcF3LfZzh+V3g0JeP4AquBM9+byQD2AvDAua9nQvgU1pti8OV7IevMg3UMLHicSOMLdzQ5t2HgG+A0ABPs6zMB1MJ6Q0WzwE4mp3aBjZR5MqzdL38HYAGsL4qRMmtxeoF9w/7vWbB2b12P4wurJaaJjknG8AUGHMul/YWbjIE5nfre/Bqsf6jcbd926uvpCj8F4AXw9yHLnLrLaxtGfgME7+cuxJOTjGNfIE7ZTRPktNdqJCmwdn1xF2J4kjH8Me3Q+zTfm1+xn++xkGVOfT0T3ixYI2omDVo+AwMPklbB+pfQOPv6dBw7kD4jVmFxfDFMwrGDt+fCGrF0pn178CCO0BFM0bYNA3M69fUEBn6gHgXwe/v6cJm1OOG1Gs7/hHVQP3g9HdZnaykGHtxfEvtoAI4vhuFy3YaBgw4yY5QvKBkDczrtvTkGwDsAnh+03KmvZ8KrgLXbbahh6PNgje4pxcARfLNhjb6ptNeJhbsA7APQA+Agjv1L/AewhrPmwTr+cEfI31wF68NQCWuXQyyG0Q+XE3DW6xlqLazh3wUANmPgl8ZwmbVov1bDORfWF2o+rPdjMNsEWLuNymHtxj1zyL+OrvcBHADQC+u9+bMRco0B8DKs17cQsd3dNVROp703rwMgdp7Qof1OfD2JiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIEtv/B2JispJb7TYMAAAAAElFTkSuQmCC\" width=\"432\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x15634ce10>]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "np.arange(0, 50e-3, 1e-3)\n",
    "plt.figure()\n",
    "new_a = psi_compressed_fft(omega_v, 24, 2.7, 10, phase_switch_time=-5e-3, mirrored=False)\n",
    "plt.plot(omega_v, np.abs(new_a)**2)\n",
    "plt.xlim(-200, 200)\n",
    "new_b = decay_state_f(omega_v, 0, 24)\n",
    "plt.plot(omega_v, np.abs(new_b)**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}