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   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# QuTiP development notebook for testing functions qutip.ipynbtools\n",
      "\n",
      "Copyright (C) 2011 and later, Paul D. Nation & Robert J. Johansson"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 28
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from qutip import *\n",
      "import qutip.ipynbtools"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import time"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 30
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Software versions"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "qutip.ipynbtools.version_table()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<table><tr><th>Software</th><th>Version</th></tr><tr><td>Cython</td><td>0.19-dev</td></tr><tr><td>SciPy</td><td>0.13.0.dev-38ad5d2</td></tr><tr><td>QuTiP</td><td>2.3.0.dev-71d6e0c</td></tr><tr><td>Python</td><td>2.7.3 (default, Sep 26 2012, 21:51:14) \n",
        "[GCC 4.7.2]</td></tr><tr><td>IPython</td><td>0.13</td></tr><tr><td>OS</td><td>posix [linux2]</td></tr><tr><td>Numpy</td><td>1.8.0.dev-bd7104c</td></tr><tr><td>matplotlib</td><td>1.3.x</td></tr><tr><td colspan='2'>Tue Apr 23 16:06:27 2013 JST</td></tr></table>"
       ],
       "output_type": "pyout",
       "prompt_number": 31,
       "text": [
        "<IPython.core.display.HTML at 0x2638950>"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## IPython.parallel based parfor\n",
      "\n",
      "To run the following examples you first need to start an IPython cluster. Easy to do from the \"Clusters\" tab on the IPython notebook dashboard page, or from the command-line using\n",
      "\n",
      "    $ ipcluster start -n 4\n",
      "\n",
      "### Simple example"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "delay_times = numpy.random.rand(10)\n",
      "\n",
      "delay_times"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 32,
       "text": [
        "array([ 0.85397305,  0.6850936 ,  0.99509335,  0.85106784,  0.65212566,\n",
        "        0.47303261,  0.18808245,  0.13273333,  0.72033813,  0.53014309])"
       ]
      }
     ],
     "prompt_number": 32
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def task(delay):\n",
      "    import os, time\n",
      "\n",
      "    t0 = time.time()\n",
      "    pid = os.getpid()\n",
      "    time.sleep(delay)\n",
      "    t1 = time.time()\n",
      "    \n",
      "    return (t1-t0)  # return the actual delay"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 33
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result = map(task, delay_times)\n",
      "\n",
      "result"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 34,
       "text": [
        "[0.8548479080200195,\n",
        " 0.6857919692993164,\n",
        " 0.9961011409759521,\n",
        " 0.8519401550292969,\n",
        " 0.6527969837188721,\n",
        " 0.4735140800476074,\n",
        " 0.1882779598236084,\n",
        " 0.1328730583190918,\n",
        " 0.7210910320281982,\n",
        " 0.530709981918335]"
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result = parfor(task, delay_times)\n",
      "\n",
      "result"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 35,
       "text": [
        "[0.8548691272735596,\n",
        " 0.685809850692749,\n",
        " 0.996117115020752,\n",
        " 0.8517839908599854,\n",
        " 0.6528029441833496,\n",
        " 0.47353196144104004,\n",
        " 0.18828606605529785,\n",
        " 0.13289308547973633,\n",
        " 0.7210750579833984,\n",
        " 0.5306930541992188]"
       ]
      }
     ],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result = qutip.ipynbtools.parfor(task, delay_times, show_scheduling=True, show_progressbar=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
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KBQAAqJ4qXKEqKSnRzZs3dfPmTRUXF7s/L3vsySuvvKKsrKxKLRYAAKA6suySX2pqqurX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\n"
      }
     ],
     "prompt_number": 36
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 37,
       "text": [
        "[0.8548541069030762,\n",
        " 0.6857941150665283,\n",
        " 0.9953198432922363,\n",
        " 0.8512799739837646,\n",
        " 0.6527988910675049,\n",
        " 0.4735231399536133,\n",
        " 0.18829107284545898,\n",
        " 0.13288402557373047,\n",
        " 0.7210788726806641,\n",
        " 0.5306930541992188]"
       ]
      }
     ],
     "prompt_number": 37
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### QuTiP example 1: steady state of a qubit-cavity system"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def visualize_results(g_vec, n_vec):\n",
      "    \n",
      "    fig, ax = subplots()\n",
      "    ax.plot(g_vec, n_vec, lw=2)\n",
      "    ax.set_xlabel('Coupling strength (g)')\n",
      "    ax.set_ylabel('Photon Number')\n",
      "    ax.set_title('# of photons in the steady state')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 38
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def compute_task(g, args):\n",
      "    wc, wa, N, kappa, n_th = args['wc'], args['wa'], args['N'], args['kappa'], args['n_th']\n",
      "    \n",
      "    a = tensor(destroy(N), qeye(2))\n",
      "    sm = tensor(qeye(N), destroy(2))\n",
      "    nc = a.dag() * a\n",
      "    na = sm.dag() * sm\n",
      "\n",
      "    c_ops = [sqrt(kappa * (1 + n_th)) * a, sqrt(kappa * n_th) * a.dag()]\n",
      "\n",
      "    H0 = wc * nc + wa * na\n",
      "    H1 = (a.dag() + a) * (sm + sm.dag())\n",
      "    H = H0 + g * H1\n",
      "    \n",
      "    rho_ss = steadystate(H, c_ops)\n",
      "    return expect(nc, rho_ss)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 39
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# problem parameters\n",
      "args = {'wc': 1.0 * 2 * pi,  # cavity frequency\n",
      "        'wa': 1.0 * 2 * pi,  # atom frequency\n",
      "        'N':  25,            # number of cavity fock states\n",
      "        'kappa': 0.05,\n",
      "        'n_th':  0.5,\n",
      "        }\n",
      "\n",
      "g_vec = linspace(0, 2.5, 50) * 2 * pi"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 40
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# serial calculation\n",
      "t0 = time.time()\n",
      "n_vec = array([compute_task(g, args) for g in g_vec])\n",
      "t1 = time.time()\n",
      "\n",
      "print \"elapsed =\", (t1-t0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "elapsed = 4.68055295944\n"
       ]
      }
     ],
     "prompt_number": 41
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "visualize_results(g_vec / (2 * pi), n_vec)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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GDVI6KtJWaXJnkYnez88Pp06dKtHO822QiZ6ozEVGAv37A3fvAh4e8krXJk2U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\n"
      }
     ],
     "prompt_number": 42
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# parallel calculation using qutip parfor\n",
      "t0 = time.time()\n",
      "n_vec = parfor(compute_task, g_vec, args=args)\n",
      "t1 = time.time()\n",
      "\n",
      "print \"elapsed =\", (t1-t0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "elapsed = 1.57517004013\n"
       ]
      }
     ],
     "prompt_number": 43
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "visualize_results(g_vec / (2 * pi), n_vec)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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GDVI6KtJWaXJnkYnez88Pp06dKtHO822QiZ6ozEVGAv37A3fvAh4e8krXJk2U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\n"
      }
     ],
     "prompt_number": 44
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# parallel calculation using qutip IPython.parallel parfor\n",
      "t0 = time.time()\n",
      "n_vec = qutip.ipynbtools.parfor(compute_task, g_vec, args=args, show_scheduling=True, show_progressbar=True)\n",
      "t1 = time.time()\n",
      "\n",
      "print \"elapsed =\", (t1-t0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"border: 1px solid grey; width: 600px\">\n",
        "  <div id=\"f394088a-aff0-47ac-93f5-36e71b5d47db\" style=\"background-color: rgba(0,200,0,0.35); width:0%\">&nbsp;</div>\n",
        "</div>\n",
        "<p id=\"75fd46c8-e9c4-4afd-a836-d11417a65d53\"></p>\n"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x4867f10>"
       ]
      },
      {
       "javascript": [
        "$('div#f394088a-aff0-47ac-93f5-36e71b5d47db').width('0%');$('p#75fd46c8-e9c4-4afd-a836-d11417a65d53').text('Elapsed time:   0.00s. Est. remaining time:   0.00s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x4867290>"
       ]
      },
      {
       "javascript": [
        "$('div#f394088a-aff0-47ac-93f5-36e71b5d47db').width('28%');$('p#75fd46c8-e9c4-4afd-a836-d11417a65d53').text('Elapsed time:   0.51s. Est. remaining time:   1.31s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x468d410>"
       ]
      },
      {
       "javascript": [
        "$('div#f394088a-aff0-47ac-93f5-36e71b5d47db').width('52%');$('p#75fd46c8-e9c4-4afd-a836-d11417a65d53').text('Elapsed time:   1.01s. Est. remaining time:   0.93s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x468d410>"
       ]
      },
      {
       "javascript": [
        "$('div#f394088a-aff0-47ac-93f5-36e71b5d47db').width('82%');$('p#75fd46c8-e9c4-4afd-a836-d11417a65d53').text('Elapsed time:   1.51s. Est. remaining time:   0.33s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x468d410>"
       ]
      },
      {
       "javascript": [
        "$('div#f394088a-aff0-47ac-93f5-36e71b5d47db').width('100%');$('p#75fd46c8-e9c4-4afd-a836-d11417a65d53').text('Elapsed time:   1.81s. Est. remaining time:   0.00s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x468d410>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "elapsed = 1.96851205826\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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      }
     ],
     "prompt_number": 45
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "visualize_results(g_vec / (2 * pi), n_vec)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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GDVI6KtJWaXJnkYnez88Pp06dKtHO822QiZ6ozEVGAv37A3fvAh4e8krXJk2U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\n"
      }
     ],
     "prompt_number": 46
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### QuTiP example 2: steady state of a qubit-cavity system with pre-allocated Qobjs"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def compute_task(g, args):\n",
      "    H0, H1, c_ops, nc = args['H0'], args['H1'], args['c_ops'], args['nc']\n",
      "    H = H0 + g * H1\n",
      "    rho_ss = steadystate(H, c_ops)\n",
      "    return expect(nc, rho_ss)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 47
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# problem parameters\n",
      "wc = 1.0 * 2 * pi\n",
      "wa = 1.0 * 2 * pi\n",
      "N = 75\n",
      "kappa = 0.05\n",
      "n_th = 0.5\n",
      "\n",
      "a = tensor(destroy(N), qeye(2))\n",
      "sm = tensor(qeye(N), destroy(2))\n",
      "nc = a.dag() * a\n",
      "na = sm.dag() * sm\n",
      "\n",
      "c_ops = [sqrt(kappa * (1 + n_th)) * a, sqrt(kappa * n_th) * a.dag()]\n",
      "\n",
      "H0 = wc * nc + wa * na\n",
      "H1 = (a.dag() + a) * (sm + sm.dag())\n",
      "\n",
      "args = {'H0': H0,\n",
      "        'H1': H1,\n",
      "        'c_ops': c_ops,\n",
      "        'nc': nc\n",
      "        }\n",
      "\n",
      "g_vec = linspace(0, 2.5, 50) * 2 * pi"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 48
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# serial calculation\n",
      "t0 = time.time()\n",
      "n_vec = array([compute_task(g, args) for g in g_vec])\n",
      "t1 = time.time()\n",
      "\n",
      "print \"elapsed =\", (t1-t0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "elapsed = 30.7636711597\n"
       ]
      }
     ],
     "prompt_number": 49
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "visualize_results(g_vec / (2 * pi), n_vec)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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dDSqVCj4+PsUrkDdjiRRx6xbQvz9w5oycp2bZMmDYMKWjIm2VJHcWmuh9fHxw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\nTkSuQmCC\n"
      }
     ],
     "prompt_number": 50
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# parallel calculation using qutip parfor\n",
      "t0 = time.time()\n",
      "n_vec = parfor(compute_task, g_vec, args=args)\n",
      "t1 = time.time()\n",
      "\n",
      "print \"elapsed =\", (t1-t0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "elapsed = 13.2212700844\n"
       ]
      }
     ],
     "prompt_number": 51
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "visualize_results(g_vec / (2 * pi), n_vec)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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dDSqVCj4+PsUrkDdjiRRx6xbQvz9w5oycp2bZMmDYMKWjIm2VJHcWmuh9fHxw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\nTkSuQmCC\n"
      }
     ],
     "prompt_number": 52
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# parallel calculation\n",
      "t0 = time.time()\n",
      "n_vec = qutip.ipynbtools.parfor(compute_task, g_vec, args=args, show_scheduling=True, show_progressbar=True)\n",
      "t1 = time.time()\n",
      "\n",
      "print \"elapsed =\", (t1-t0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"border: 1px solid grey; width: 600px\">\n",
        "  <div id=\"f71ddb01-5d66-4354-8e2d-3bdf210395a5\" style=\"background-color: rgba(0,200,0,0.35); width:0%\">&nbsp;</div>\n",
        "</div>\n",
        "<p id=\"466ca3c0-51b8-429f-9a14-759e39657916\"></p>\n"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x4767350>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('0%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   0.01s. Est. remaining time:   0.00s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('2%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   0.52s. Est. remaining time:  25.25s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('4%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   1.02s. Est. remaining time:  24.52s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('10%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   1.53s. Est. remaining time:  13.75s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('10%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   2.03s. Est. remaining time:  18.29s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('18%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   2.54s. Est. remaining time:  11.56s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('18%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   3.04s. Est. remaining time:  13.86s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('26%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   3.55s. Est. remaining time:  10.10s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('26%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   4.05s. Est. remaining time:  11.54s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('34%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   4.56s. Est. remaining time:   8.85s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('34%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   5.06s. Est. remaining time:   9.82s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('40%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   5.57s. Est. remaining time:   8.35s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('42%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   6.07s. Est. remaining time:   8.38s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('46%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   6.57s. Est. remaining time:   7.72s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('50%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   7.08s. Est. remaining time:   7.08s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('54%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   7.58s. Est. remaining time:   6.46s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('57%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   8.09s. Est. remaining time:   5.85s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('62%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   8.59s. Est. remaining time:   5.26s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('66%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   9.09s. Est. remaining time:   4.68s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('66%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:   9.60s. Est. remaining time:   4.94s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('74%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:  10.10s. Est. remaining time:   3.55s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('74%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:  10.60s. Est. remaining time:   3.72s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('82%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:  11.10s. Est. remaining time:   2.44s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('82%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:  11.61s. Est. remaining time:   2.55s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('90%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:  12.11s. Est. remaining time:   1.35s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d150>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('90%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:  12.61s. Est. remaining time:   1.40s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('98%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:  13.11s. Est. remaining time:   0.27s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "javascript": [
        "$('div#f71ddb01-5d66-4354-8e2d-3bdf210395a5').width('100%');$('p#466ca3c0-51b8-429f-9a14-759e39657916').text('Elapsed time:  13.44s. Est. remaining time:   0.00s.');"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x476d050>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "elapsed = 13.6379978657\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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J2U3KTFb7mJTXpKySeXkvxZTPYEpOSXJHuyVJhf5Ch5OEVh3nNWShWrBggVwul2bPnl3u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\nAAAAiyhUAAAAFlGoAAAALPo/iK2AzqMezJkAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 53
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "visualize_results(g_vec / (2 * pi), n_vec)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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dDSqVCj4+PsUrkDdjiRRx6xbQvz9w5oycp2bZMmDYMKWjIm2VJHcWmuh9fHxw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\nJPqrV2WtWYjcP9VqOS96Zqb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      }
     ],
     "prompt_number": 54
    }
   ],
   "metadata": {}
  }
 ]
}