{
 "metadata": {
  "name": "Brian tutorial CNS July 2013"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Ignore this, just a few imports needed for the tutorial."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from brian import *\n",
      "import time\n",
      "import pickle\n",
      "import joblib\n",
      "import gc\n",
      "\n",
      "def brianreset():\n",
      "    clear(True,True)\n",
      "    gc.collect()\n",
      "    defaultclock.t = 0*second"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Python data structures"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Python has some great datatypes, it's worth understanding and using them.\n",
      "\n",
      "* List\n",
      "  - Appending is fast, inserting anywhere else is slow\n",
      "  - Indexing x[i] is fast\n",
      "  - Uses a 'dynamic array' structure\n",
      "* Dictionary\n",
      "  - `X[key] = value`\n",
      "  - Key can be (almost) anything\n",
      "  - Fast!\n",
      "* Set\n",
      "  - Fast to add or subtract elements\n",
      "  - Fast for testing if an item is in the set or not"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Python iteration"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Don't do this:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit\n",
      "for i in range(1000):\n",
      "    for j in range(1000):\n",
      "        i*j"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10 loops, best of 3: 42.6 ms per loop\n"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Do this instead:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit\n",
      "for i in xrange(1000):\n",
      "    for j in xrange(1000):\n",
      "        i*j"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10 loops, best of 3: 38.3 ms per loop\n"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Similarly, don't do this:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "A = rand(100000)\n",
      "B = rand(100000)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 33
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit\n",
      "for a, b in zip(A, B):\n",
      "    a*b"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10 loops, best of 3: 63.9 ms per loop\n"
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Do this instead:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import itertools"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 36
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%timeit\n",
      "for a, b in itertools.izip(A, B):\n",
      "    a*b"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10 loops, best of 3: 51.5 ms per loop\n"
       ]
      }
     ],
     "prompt_number": 35
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "* `range` creates a list, whereas `xrange` can only be used for iteration.\n",
      "* There are many other nice tools for iteration in the `itertools` module of Python\n",
      "* Best of all is to use numpy vectorisation instead of loops"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Saving and loading data in Python"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Saving and loading is easy in Python with pickle"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pickle\n",
      "obj = ['a', 'list', 'of', 'words']\n",
      "pickle.dump(obj, open('alistofwords.pkl', 'wb'), -1)\n",
      "newobj = pickle.load(open('alistofwords.pkl', 'rb'))\n",
      "print ' '.join(newobj)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "a list of words\n"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Shelves are a dict-like database"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import shelve\n",
      "shelf = shelve.open('test.shelf')\n",
      "shelf['meaning'] = 42\n",
      "shelf.close()\n",
      "newshelf = shelve.open('test.shelf')\n",
      "print newshelf['meaning']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "42\n"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "There are many other databases in Python"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "A Python example"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Compute firing rates for a two parameter family of experimental data recorded in random order with an unknown number of trials per condition.\n",
      "\n",
      "First we generate some fake data - ignore this."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from collections import namedtuple\n",
      "paramA = linspace(0, 1, 10)\n",
      "paramB = linspace(0, 1, 10)\n",
      "trials = []\n",
      "Trial = namedtuple(\"Trial\", ['a', 'b', 'spikes'])\n",
      "for i in xrange(100):\n",
      "    a = paramA[randint(len(paramA))]\n",
      "    b = paramB[randint(len(paramB))]\n",
      "    r = (a-0.5)**2+(b-0.5)**2\n",
      "    spikes = rand(int(r*100))\n",
      "    trials.append(Trial(a=a, b=b, spikes=spikes))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 40
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now we compute the firing rates and plot them. Using a dictionary means that we don't need to precompute the set of which parameters exist and which don't, etc., but just immediately start computing what we need."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from collections import defaultdict\n",
      "\n",
      "counts = defaultdict(int)\n",
      "numtrials = defaultdict(int)\n",
      "\n",
      "for trial in trials:\n",
      "    counts[trial.a, trial.b] += len(trial.spikes)\n",
      "    numtrials[trial.a, trial.b] += 1\n",
      "    \n",
      "rates = dict()\n",
      "\n",
      "for a, b in counts.keys():\n",
      "    rate = counts[a,b]*1.0/numtrials[a,b]\n",
      "    plot([a], [b], 'o', ms=rate, c='k')\n",
      "    rates[a, b] = rates\n",
      "\n",
      "pickle.dump(rates, open('rates.pkl', 'wb'), -1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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Al3PH03XOeyaIyarD3RwNDQ2St9HU1GTW63K4dOkSjh49ipycHCxatEjpcogJ\neDl3lnCdG0OOTBAThXsP5PiSp0+fPma9LgdnZ2cAbXPbZmZmKlwNMQUv584SrnNjWFoHB6sOd1dX\nV8HbSjF34qPGjBlj8PXRo0dLXkNvtm/fjmeffRaHDh2Cu7u70uUQE/By7ni6znnPBFGJ+MVuj2Rq\npgtzvhnXarWS16fT6bjpRUCIVHi6znnPhEeZk53Uz/0RcvdpbWhowKpVq3DmzJmO/r+jR4/GqlWr\nLO7PQEJ6wst1bgmZ8DBzstOqwx148DTahQsXel03NDQUmZmZlvfnFyHEaJaUCRTuvdBoNJg3bx6u\nXr3a4zq+vr7YuXMnBTshNsBSMkHSsWVyc3MRFBSEgIAAfPTRRz2ud/LkSahUKuzdu1dQIVKKiorC\nxo0bERwc3O3rwcHB2LRpEwU7ITbCFjLB4Cf3lpYWBAYGIj8/Hz4+PggPD8eOHTu6HJCWlhbExcXB\n2dkZCxYswJw5czo3wsk0e1qtFhkZGdBoNGhoaICTkxOioqKQnJwMFxcXpcsjhMiM90yQ7LZMUVER\nUlNTkZubCwBYu3YtAGDFihWd1svIyMDvfvc7nDx5ErNmzeI23AkhxJKYk50GJ+uorKyEr69vx8+D\nBg3C8ePHu6zz/fff44cffsDJkydhZ2fX7b4eHj9i4sSJmDhxoqCCCSHEWv3444/48ccfRdmXwXDv\nKagflpycjLVr13a8w/T0LlNQUAAXFxd4enri/PnzCAwMxMCBA4VVTQghVujRD76pqamC92Uw3H18\nfHDt2rWOn69du4ZBgwZ1WqekpAQvvPACgLY+pDk5OXB0dMQzzzzTab0jR450/P+vvvoKa9aswdCh\nQzFjxgwsX74cffv2FfxLEEII6czgPXe9Xo/AwEAcPnwY3t7eGDduXLdfqLZbsGABEhISMHv27M6N\nGPgLwN7eHkFBQXj++efx/vvvw8HBQeCvQggh1kWyrpAqlQobNmzA9OnTERISgueffx7BwcHYvHkz\nNm/eLKjBR7W2tqK0tBQffPABpkyZAr1eL8p+CSHElsn2EJMxVCoV3nrrLaxfv17iigghhH8W8YSq\nsby9vZGXl4eQkBBRazh37hy+/vprlJWV4d69ex3/3cXFBUFBQUhMTMSoUaNEbZMQwi9LyASrCncA\nmDlzJg4cOCBK2/X19Zg/fz4KCgpQXV3d43qenp6YMGECvvrqK7OGBSWE8M2SMsHqwt3LywtHjhwx\n+9N7fX2cIj0UAAAZfElEQVQ94uLiuvTNNyQiIgJ5eXkU8IRYIUvLBEnHllHCzZs3uzwFK8T8+fNN\nOokAcPz4cSQkJOD+/ftmt08I4YstZQKX4Q4Ap06dMvgnU2/Onj2LgoICQdseO3YM69atE9w2IYQ/\ntpYJ3IZ7VVUVcnJyBG+/ZcsWwW8Ora2t2LFjh8W9UxNCemZrmcBtuDPGkJWVJXh7U2Za6c7Fixct\n7p1abIsWLep4HHrixIlITExUuiRiJDp3XdlaJhgcfkBpt2/fFrztw12bhGhtbUVhYaFZ+7B0ly5d\nwtGjRzt+9vT0xKZNm/D6668rWFVbcF26dAnOzs7Yvn07FxN381YTr+dOSbaWCdx+cgfaxolXUmNj\no6Lt86a6uhp79uxRuoyO4MrJycGiRYuULgcAnzU9jJdzZ+ksKRO4Dnelx5mhwcw68/T07DJWvxKc\nnZ0BAOHh4cjMzFS4mjY81vQwXs6dpbOkTOA63Pv37y9428cee8ystu3t7REdHW3WPizdkCFD4Onp\nCaAtHOLi4rj4s3779u149tlncejQIcVvf7TjrSZez52SbC4TmAwAmLzY2dmxLVu2CG7z7bffFtRu\n+xIaGsqamppEPAqWaePGjWzq1Kls48aNSpdCTETnrjNLzARzIprLJ1SBtrHkz5w50/Hpw1Tnzp3D\nlClTBHV9sre3R1paGt5//31BbRNC+GOJmWB1T6gCwJNPPik42AFg1KhRmDBhgqBtx48fj+XLlwtu\nmxDCH1vLBC4/udPYMoQQKVhaJljdJ/fw8HBRhvx1dXVFXl4eYmNjYW9v+Fe1t7dHbGwsBTshVsyW\nMoG7cPf29sbHH38s2v5cXV1x6NAhpKWlITQ0tMsJtbe3R2hoKNLS0nDo0CGLPImEEOPZSiZwdVtG\npVIhOTlZskd8m5qasH79ehQWFqKxsRF9+/ZFdHQ03nnnHfTp00eSNgkh/OItE6qqqpCVlYW8vDzc\nuXMH+fn5lj+eu0qlQnR0NPLz86FScT0qAiGEiIYxhr///e/4y1/+gvLycty8ebPL60JwkaL9+/fH\nggULkJ6eTsFOCLEZhw8fxnvvvYfS0lI0NDSIum8ukrS1tdWixmwghBBz6PV6LF26FLt27cKtW7ck\naYOb2zIODg6IiorCgQMH8Pvf/17qkgghRBF1dXWYNWsWNBqNUYMjWvw993bjxo1DXl4eBTwhRFJX\nrlzB1q1bcf78edTU1KClpQUODg7w8PDAyJEj8fLLL8PPz0/UNuvq6hAXF4cTJ04YvY3VhDvQ9jTY\nDz/8QPffCSGi++677/DJJ5/g0qVLXb68fJiXlxeGDx+OZcuW4Y9//KPZ7er1ekyaNAk//fSTSdtZ\nVbg7ODjgT3/6Ez777DOJKiKE2Jr6+nq89NJLKCgowN27d43ezs3NDRMmTMC2bdvM6vO+ZMkSbNy4\n0eR5Kqwq3IG2d80dO3Zg8uTJElRECLElQoYdeJQ5wxAcPnwY8+bNE/TlqdWFOwCo1WqcPHlS8Pa8\nq66uxoYNG1BSUoL6+vqO/+7q6gq1Wo2kpCSzBk8jhAc8XOcJCQk4cOCAKPvZv3+/SdswxhAeHo6S\nkhJBbQqOaMGDBZsAAsdPdnJyYrt27ZKjRNkVFxezwMBAg79/YGAgKy4uVrpUQgTj4Trfu3cvc3Nz\nM2ss9/bFzc2N7du3z6T2d+7cyZycnAS3KRTX4Q6ARUdHy1GirIqLi1loaKjREwQUFhYqXTIhJuPl\nOo+JiREl2NuXmJgYk9qPjo42qz2huL4tAwADBgzA6dOnMXDgQBErUk51dTViYmJQVlZm9Da+vr7Y\ntGkT4uPjJayMfzqdDmlpaTh9+jSamprQp08fjBkzBikpKXBycqKaOMLLdX7lyhVEREQY7BVjKi8v\nL5w4cQJDhgzpdd2qqiqMGTPGrPYFR7TgtwUTwMx3yr/+9a9ylCmLlJQUQccgJCSE3bt3T+nyFaPV\nallkZGS3xyYyMpLpdDqqiSO8XOdpaWmifmpvX9LS0oxqf/PmzWa3JRR3Q/525+DBg0qXIBqhX6qU\nlpYiIyND5GosR1paGoqKirp9raioCKtWrZK3IPBZEy94uc7Pnz8v2r6E7Dc/P1+S9o1hEeFeW1ur\ndAmiebi3gKk0Go2IlViW06dPG3z9zJkzMlXyAI818YKX67ympka0fQnZ7507dyRp3xgWEe6mdvq3\nVmKPGmdJmpqazHpdCjzWZA3EvM6lyg5j96tkdllEuDs4OChdAhds+Qu63iZOUGJiBR5rsgZiXudS\nZYex+1Uyu3oN99zcXAQFBSEgIAAfffRRl9e3bduGsLAwjBo1CtHR0Th37pzoRbq7u4u+T6WY8/hy\nVFSUiJVYljFjxhh8ffTo0TJV8gCPNfGCl+vcw8NDtH0J2W+/fv0kad8ohr5t1ev1bNiwYezy5cvs\n/v37LCwsjJWWlnZaR6PRsNraWsYYYzk5OSwiIqLLfkC9ZTqY04tAq9UqXb5idDoddz1TeKyJF7xc\n57bcW8bglhqNhk2fPr3j5/T0dJaent7j+jU1NczHx6drI2b8YgMGDGBVVVWCf0He3Lp1q9cn9h5d\nfH19WVZWltKlK06n07F3332XTZs2jcXGxrJp06axd999V9EQ5bEmHvBynV++fJl5eXmJGuxeXl7s\nypUrRrVfWVlpdvtCGdzy22+/ZQsXLuz4eevWrSwpKanH9detW8dee+21ro2Y8YvRE6r0hCqxTLxc\n57b6hKrBe+6mPFl65MgRfPHFF93elxfKyckJb775pmj744VarUZmZiYGDx5scD1fX19kZmba9L12\nYrl4uc6XLVsGNzc3Ufbl7u6OZcuWmbTNkiVLlOkMYSj5i4qKOt2WWbNmDVu7dm2X9c6ePcuGDRvG\nysvLu90PBL5jqdVq1traKvidi3dZWVksODi42989ODiYbsUQq8DDdZ6QkCDKp/aEhAST225tbWVq\ntVr2T+4Gx5bR6/UIDAzE4cOH4e3tjXHjxmHHjh0IDg7uWOfq1auYPHkyvvnmGzz11FPd7ofGc++Z\nVqtFRkYGNBoNGhoa4OTkhKioKCQnJ8PFxUXp8ggRhdLXOQ/jub/44ouCxpgxENG9bmhQdnY2Gz58\nOBs2bBhbs2YNY4yxTZs2sU2bNjHGGHv11VeZh4cHGz16NBs9ejQLDw/vsg+Y+E5lZ2fH3njjDcHv\nWIQQ8qi6ujqWkJBg8vC/bm5uLCEhgdXV1ZnVflJSEnNwcODjk7tYhHxyj46ORnZ2tigTZTPG8Msv\nvyA7OxvHjh1DbW1tx2S47u7uGD9+POLj4zFs2DCrnRiEENLmu+++w/r163Hx4kWDwwh4eHggODgY\n77zzjmhzqE6ePBnHjh0zaTuhEc3tDNSFhYWIi4tDXl6e4IDX6XT49NNPsXfvXvzzn//s8UTu3r0b\nqampeOKJJzBnzhy8+eabcHZ2Nqd8QgiHdDodLl68iKamJrS2thpct7W1FU1NTfjHP/4BnU5ndiao\nVCocOHAAcXFxOHHihFn7MopZf2cYCWZ8gREdHW1yn+Hr16+zV155hQUEBDA7OzuTbwkFBASwV155\nhV2/fl2iI0IIkRNPmXD37l02fvx4o2/RCMV9uANgiYmJRrWj1+vZf/3Xf7EhQ4aY3SYANmTIELZy\n5Uqm1+ulPUCEEEnwmgnNzc1syZIl7PHHH7e9e+4P69+/P7755hs8/fTTPa7T0tKCqVOn4qeffoJe\nrzervYepVCrExMQgPz+fBjAjRIArV65g69atOH/+PGpqajq+7/Lw8MDIkSPx8ssvw8/PT/R2LSET\nfvjhB7z77rsoLS3tcTRMwRFt1tuPkSDCO+aIESNYfX19j22sXLmSqVQqUdp6dHF0dGQrV66U41AR\nYjX27dvHYmJien383svLi8XExJg88XRvLCUTWltb2a5du1h0dDQbMGCAaJ/cLSbcAbDFixd3u//r\n16+L9mdXT8uQIUPoHjwhRlC6yyFjlpsJlZWV7K9//St79tln2dSpU20n3IOCglhjY2OX/b/yyiuS\nnsT2Zf78+XIcLkIsVl1dHYuIiDDr31lERITZAW8tmWBOuHPbFbI75eXlyMzMxJIlSzr+m06n63Ee\nS7FpNBpRukQR01VXV2PDhg0oKSnpNIWbq6sr1Go1kpKS4OnpafM1Ke3FF1806ylQADh+/Dheeukl\n7N+/X9D2lAn/JuKbTI8g4jtlZGRkp32np6eb3LVJ6GJnZ9ft2DpEWsXFxb0OHxsYGMiKi4ttuial\n7d271+RbMT0tbm5ugu/BW1MmmBPRFhfuPj4+rKamhjHW9kXE2LFjZTmJ7cvYsWOtejAz3vAybCzv\nNfFA6aF1GbO+TLCpcFepVCwnJ4cxxlh5eTnz8PCQ9UR6eHiwiooKOQ6bzeNlwgfea+KB0pNitLO2\nTDAn3C1iguyH6fV6ZGVlAQCys7MNjg0hhZqaGmRnZ8vapq3asGEDysrKTNrm2rVrWL58ObRarc3U\nxIOtW7cKGvHQkJs3b2LLli0mbUOZ8IDFhTsAXL58GQBMHoBHLAUFBYq0a2tKSkoEbVdaWoqMjAyR\nq2nDY008OH/+PBf7pUx4wCLDvampCQBQW1urSPtKtWtrHu6BYiqNRiNiJQ/wWBMPpPq0bOp+KRMe\nsMhwb2lp6fS/SrVP+NXTo9xK4rEmsUj1b8LU/VImPGCR4d4+noNSY73QGDP8U2TOyl7wWJNYpPo3\nYep+KRMesMhw79OnD4C2yWqVINZku8QwIdOZtZNqsmUea+KBh4cHF/ulTHjAIsN96NChAIDx48cr\n0n5sbKwi7doatVotaLuQkBAsXbpU5Gra8FgTD0aOHMnFfikTHiJil8wegfq5EwF47FPOY008oH7u\n/PVzt7hwpydUbQuPT4PyWBMP6AlV8ZkT7hZ3W2bw4MHo168fgLZJQObMmSPbpNZ2dnaYO3cuTaIt\nI7VajczMTAwePNjger6+vsjMzJTlvjaPNfFg2bJlot17dnd3x7Jly0zejjLhISK+yfQIIr5L/vd/\n/3enfWu1WhYQECDLO/Tw4cOZVquV45CRR2RlZbHg4OBuz0twcLAitz14rElpCQkJovxbS0hIEFyD\nNWWCORFtUUP+AsDPP//c6WdnZ2dERkaivLxc8rajoqL4HNrTBsTHxyM2NhYZGRnQaDRoaGiAk5MT\noqKikJycDBcXF6qJA9u2bUNcXJxZw/5GRERg27ZtgrenTPg3Ed9kegQR3yldXV3ZF1980Wn/5eXl\nzMXFRdJ3aBcXF1ZeXi7H4SLEovEwE1NFRYUsmSB15wpzItriwh0ACwkJ6ZhP9e7du6J/kdPTEhMT\nw+7evSvHISPEorW2trJly5YxV1fXXsdWt7OzY66urmzZsmWifDFpTZlgc+EOgC1YsIDdvXuXjRs3\nTpaT2L6MGzeOAp4QA/Lz85larWZOTk4m/dtycnJiarWaHT58WHDb1pYJ5oS73b93ICkpvkn28vLC\nwIEDcfbsWdH33Zvo6Gjk5eVZ5ePkVVVV2LNnD06dOoXq6mpotVowxmBnZwcXFxd4enriySefxNy5\nczFw4EClyyUc0ev1WLp0KXbt2oVbt24J3o+Xlxeee+45/M///A9UKuO/FmxoaEBcXBwKCwsFty2U\nVJlgZ2cHoRFtseGutMTERHz11VdKlyGKxsZGfPzxx8jNzcXly5fx22+/9brNH/7wBwwdOhQzZszA\n8uXL0bdvX0lrrK6uxt/+9jdoNBo0NjaiubkZjo6O6Nu3L6KiorBw4UKbm6+UJ3V1dZg1axY0Go0o\ng2g5ODggKioKBw4cwO9//3ujtpk/fz6+/vprs9sWSopMMCfcLfa2jNJL//79O56UtVR6vZ6lpqay\nkJAQwXNO2tvbs5CQEJaamsr0er2o9d2+fZulp6ezSZMmsUGDBhmsY9CgQWzSpEksPT2d3b59W9Q6\niGFS3gox9pZHdnY269+/v9VlgjkRTeFuxjJixIiOL3YtjV6vZxMnTmQqlUqUY6FSqVhsbCxrbm4W\npbYPPviADRs2TFAt/v7+bPXq1aK/2ZCumpubJf/ycvz48Qavq/r6eqOfGLa0TAAo3BVbFi9eLMch\nFF1qaqpowd6+qFQqtmzZMrPqan/TcXR0NKsWR0dH0d5sSM+SkpKYg4ODpP/GHBwc2JIlS3qsYfHi\nxYrngFSZAFC4K7YEBQWxxsZGOQ6jaBoaGlhISIgkx8Pb25tduHBBcG2rV682O9jbF5VKxd555x0R\njxx5WH5+Pnv88cdl+Xfm5eXVbS+ahoYGFhQUpHgOSJUJAIW7YouDgwP77LPP5DiMoklNTRV8j92Y\nZebMmYLqun37NvP39xe1Fm9vb3b+/HmRjyBpbW1larVa1n9rarW6Sz/4Tz/9VPK/HJTMBMCGBg7j\nTUtLC3bs2KF0GSbJzc0V/g28EU6ePInS0lKTt8vMzERFRYWotVRVVQkagIoY9ve//13QOTZHaWkp\nvv32207/befOndxNccdLJlC4i+Dq1au4c+eO0mUYpaqqCpcvX5a0jZs3b2LFihUmb3fo0CEJqml7\nszl27Jgk+7ZVf/nLX2SfE7ahoQGfffZZx8937tzB1atXZa3BWDxkAoW7CG7cuGH0QEk//vijtMX0\nYs+ePUb1YzdX+0NQhjx8LKqrqyUb6OnOnTt4//33Jdm3WJS+LkxRVVUly6Bc3amoqMCvv/4KoG0Q\nQTmuZSFMyQSp9Bruubm5CAoKQkBAAD766KNu13nzzTcREBCAsLAwnD59WvQieafX65GVlWXUukr/\nI5br/FRVVSEnJ8fgOg8fi7/97W+4fv26ZPVcuHABly5dkmz/5lL6ujDFgQMHcPPmTUXavnHjRse/\ntezsbO5uybQzJROkYjDcW1pakJSUhNzcXJSWlmLHjh24ePFip3Wys7NRUVGB8vJyZGZm4o033pC0\nYF5JfatDLOY8Fm4KxphJF7dGo5GwGqCmpgaff/65pG3Yivz8fEXbP3jwIAD+/80pXZ/BcD9x4gT8\n/f3h5+cHR0dHvPDCC/j+++87rbN//34kJiYCaBuHuba2Fjdu3JCuYk41NTUpXYJRtFqtbG3dvn3b\n6HUbGxslrKSNEuMQWSOl7yXX1tYCkOeaMYfimWCoK823337LFi5c2PHz1q1bWVJSUqd1Zs2a1WmO\nyClTprDi4uIu3XlooYUWWmgxfRHK4JBrxg749Wi3uke3k7LbHSGEkK4M3pbx8fHBtWvXOn6+du0a\nBg0aZHCd69evw8fHR+QyCSGEmMJguI8dOxbl5eW4cuUK7t+/j127duGZZ57ptM4zzzyDLVu2AGjr\nmuTu7o4BAwZIVzEhhJBeGbwto1KpsGHDBkyfPh0tLS149dVXERwcjM2bNwMAFi9ejPj4eGRnZ8Pf\n3x8uLi748ssvZSmcEEKIAYLv1ncjJyeHBQYGMn9/f7Z27dpu11myZAnz9/dno0aNYqdOnRKzea70\ndiy++eYbNmrUKDZy5EgWFRXFzp49q0CV8jDmumCMsRMnTjAHBwe2Z88eGauTlzHH4siRI2z06NEs\nNDSUxcbGylugjHo7Frdu3WLTp09nYWFhLDQ0lH355ZfyFymDBQsWMC8vLzZixIge1xGSm6KFu16v\nZ8OGDWOXL19m9+/fZ2FhYay0tLTTOllZWWzGjBmMMcZ+/vlnFhERIVbzXDHmWGg0GlZbW8sYa7vI\nbflYtK83adIkNnPmTLZ7924FKpWeMcfizp07LCQkhF27do0x1hZw1siYY5GSksJWrFjBGGs7Dh4e\nHlY5hHNBQQE7depUj+EuNDdFG36A+sQ/YMyxiIyMhJubG4C2YyHl05lKMuZYAG1jlcydOxePP/64\nAlXKw5hjsX37dsyZM6ej44K1Th1ozLEYOHAg6urqALRN49e/f3+T5lS1FOPHj0e/fv16fF1obooW\n7pWVlfD19e34edCgQaisrOx1HWsMNWOOxcM+//xzxMfHy1Ga7Iy9Lr7//vuOp5utcc5dwLhjUV5e\njpqaGkyaNAljx47F1q1b5S5TFsYci9deew0XLlyAt7c3wsLC8Omnn8pdJheE5qZob4Ni9Ym3Bqb8\nTkeOHMEXX3yhyIztcjDmWCQnJ2Pt2rUdkwE/eo1YC2OORXNzM06dOoXDhw9Dp9MhMjISTz31FAIC\nAmSoUD7GHIs1a9Zg9OjR+PHHH/HLL78gLi4OZ8+ehaurqwwV8kVIbooW7tQn/gFjjgUAnDt3Dq+9\n9hpyc3MN/llmyYw5FiUlJXjhhRcAtI0OmZOTA0dHxy7dbi2dMcfC19cXnp6ecHJygpOTEyZMmICz\nZ89aXbgbcyw0Gk3HaJ7Dhg3D0KFDUVZWhrFjx8paq9IE56Yo3wiwtolyn3jiCXb58mXW1NTU6xeq\nRUVFVvslojHH4l//+hcbNmwYKyoqUqhKeRhzLB42f/58q+0tY8yxuHjxIpsyZQrT6/VMq9WyESNG\nmDVtIa+MORZLly5lq1atYowx9ttvvzEfHx92+/ZtJcqV3OXLl436QtWU3BTtkzv1iX/AmGORlpaG\nO3fudNxndnR0xIkTJ5QsWxLGHAtbYcyxCAoKwtNPP41Ro0bB3t4er732GkJCQhSuXHzGHIs///nP\nWLBgAcLCwtDa2oqPP/4YHh4eClcuvnnz5uHo0aOorq6Gr68vUlNT0dzcDMC83LRjzEpvcBJCiA2j\nmZgIIcQKUbgTQogVonAnhBArROFOCCFWiMKdEEKsEIU7IYRYof8HOzi1iTE9XLcAAAAASUVORK5C\nYII=\n"
      }
     ],
     "prompt_number": 42
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Python: final thoughts"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There are several other useful toolboxes that are worth finding out about.\n",
      "\n",
      "* **Multiprocessing** for running simulations simultaneously on multiple CPUs or computers (including over the internet). There are also other, simpler solutions for this.\n",
      "* **GUI toolboxes** are surprisingly easy to use and can be useful for interactively exploring your data/simulations."
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Vectorising with numpy"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Don't do this:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a = linspace(0, 1, 100)\n",
      "b = linspace(0, 1, 100)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 47
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def getimg():\n",
      "    img = zeros((100, 100))\n",
      "    for i in xrange(100):\n",
      "        for j in xrange(100):\n",
      "            img[i, j] = (a[i]-0.5)**2+(b[j]-0.5)**2\n",
      "    return img"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 54
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Do this:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def getimg_vectorised():\n",
      "    return (a[:, newaxis]-0.5)**2+(b[newaxis, :]-0.5)**2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 56
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "They're equivalent:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "subplot(121)\n",
      "imshow(getimg())\n",
      "subplot(122)\n",
      "imshow(getimg_vectorised())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 58,
       "text": [
        "<matplotlib.image.AxesImage at 0x4b8f590>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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8u8T3EQ9bYppniWgZIyNqXE8oKpsw3mNN3j2yVdLlgW0hGKTgECaPMD9SovMj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\nJhl7wd6P/diP/bhJxv8Hs1i9ofvC/bsAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 58
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And the vectorised version is much faster!"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit getimg()\n",
      "%timeit getimg_vectorised()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10 loops, best of 3: 39.3 ms per loop\n",
        "10000 loops, best of 3: 40.9 us per loop"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      }
     ],
     "prompt_number": 59
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Advanced vectorisation"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "With a bit of ingenuity, almost everything can be vectorised, and numpy includes some nice functions to help with this. For the cases that can't, we'll come back to that later.\n",
      "\n",
      "Here's a more complicated example, computing the coincidence factor between two spike trains."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "delta = 0.005\n",
      "train1 = sort(rand(50))\n",
      "train2 = sort(rand(55))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 61
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Don't do this:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def cf_loop():\n",
      "    num_coinc = 0\n",
      "    for t1 in train1:\n",
      "        for t2 in train2:\n",
      "            if abs(t1-t2)<delta:\n",
      "                num_coinc += 1\n",
      "                break\n",
      "    return num_coinc"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 62
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Do this:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def cf_vectorised():\n",
      "    ends = 0.5*(train2[1:]+train2[:-1])\n",
      "    i = digitize(train1, ends)\n",
      "    return sum(abs(train1-train2[i])<delta)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 63
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "As before, they're equivalent but the vectorised version is an order of magnitude faster."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print cf_loop(), cf_vectorised()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "19 19\n"
       ]
      }
     ],
     "prompt_number": 64
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit cf_loop()\n",
      "%timeit cf_vectorised()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "100 loops, best of 3: 2.22 ms per loop\n",
        "100000 loops, best of 3: 18.5 us per loop"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      }
     ],
     "prompt_number": 65
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "It can be a little difficult to understand the vectorised algorithms sometimes. Talk to me later if you want to know how this one works."
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "When vectorisation doesn't work"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can run C++ code inline in various simple ways:\n",
      "\n",
      "Scipy has a package weave which allows inline C++ code:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from scipy import weave\n",
      "N = 100\n",
      "x = zeros(N)\n",
      "code = '''\n",
      "for(int i=0; i<N; i++)\n",
      "{\n",
      "    x[i] = i;\n",
      "}\n",
      "'''\n",
      "namespace = {'x': x, 'N': N}\n",
      "weave.inline(code, namespace.keys(), namespace, compiler='gcc')\n",
      "print x[3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "3.0\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There are also other options:\n",
      "\n",
      "* **Cython** allows you to write code in a Python-like syntax with a few extra keywords to define types, and then generates C++ code.\n",
      "* **Swig** makes it straightforward to write a separate C++ library and link it to Python\n",
      "* **numba** is a very new option, not yet complete, by the people who designed numpy. It allows you to write 'naive' Python code with loops, and it JIT compiles to LLVM and then machine code behind the scenes. In principle, this may turn out to be the best solution, and something we are considering for Brian 2."
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Numpy, scipy and other packages"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Don't forget to investigate features in numpy, scipy and other third party Python packages. Check out the list of related software on the scipy website. No need to reinvent the wheel!"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "joblib"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "One of my favourite packages is joblib which I use in every project for cacheing computations to disk rather than managing this manually."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import joblib\n",
      "\n",
      "cache_mem = joblib.Memory(cachedir='.', verbose=0)\n",
      "cache_mem.clear() # don't do this normally, it's just for the example\n",
      "\n",
      "@cache_mem.cache\n",
      "def f(x):\n",
      "    print \"--- I am currently computing x*x for x =\", str(x)\n",
      "    return x*x\n",
      "\n",
      "print \"Computing f(2.3)\"\n",
      "print f(2.3)\n",
      "print \"Computing f(3.5)\"\n",
      "print f(3.5)\n",
      "print \"Computing f(2.3) again\"\n",
      "print f(2.3)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "WARNING:root:[Memory(cachedir='.\\\\joblib')]: Flushing completely the cache\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Computing f(2.3)\n",
        "--- I am currently computing x*x for x = 2.3\n",
        "5.29\n",
        "Computing f(3.5)\n",
        "--- I am currently computing x*x for x = 3.5\n",
        "12.25\n",
        "Computing f(2.3) again\n",
        "5.29\n"
       ]
      }
     ],
     "prompt_number": 69
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The same thing works with arbitrarily complicated arguments including lists, dicts, complex objects, etc.\n",
      "\n",
      "You can use this to write your code as if everything was being computed from scratch each time, but on subsequent runs it will complete fast."
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Efficient Brian code"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There are several key elements to writing efficient Brian code:\n",
      "\n",
      "* Using the C++ extensions\n",
      "* Using code generation\n",
      "* Knowing when to use `Connection` and `Synapses`\n",
      "* Handling looping over several simulation runs correctly"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Brian's C++ extensions"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Brian is designed to run in pure Python. However, if you do have a C++ compiler (if you are running on Linux, or Windows with MinGW installed) then you can build several extensions which replace their pure Python equivalents. These can make a big difference to speed. The latest release of Brian (1.4.1) will try to detect if you have a compiler installed and build these automatically, but if it fails or if you're running an older version of Brian you can do it manually (see the docs for details).\n",
      "\n",
      "* `ccircular` package\n",
      "* `cspikequeue` package"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Using code generation"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Brian has support for automatically generating C++ code in the background, compiling it and then using this rather than working in pure Python. Sometimes this can make a big speed difference.\n",
      "\n",
      "Brian has a preference mechanism, you can create a file `brian_global_config.py` anywhere on your Python path, and set preference values in it. The following is the recommended settings for most computers if you have `gcc` installed (on linux or Windows):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from brian.globalprefs import *\n",
      "set_global_preferences(\n",
      "    useweave=True,\n",
      "    weavecompiler='gcc',\n",
      "    gcc_options=['-ffast-math', '-march=native'],\n",
      "    usecodegen=True,\n",
      "    usecodegenweave=True,\n",
      "    usenewpropagate=True,\n",
      "    usecstdp=True,\n",
      "    )"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "C:\\Users\\goodmad\\programming\\brian\\brian\\synapses\\spikequeue.py:490: UserWarning: Using C++ SpikeQueue\n",
        "  warnings.warn('Using C++ SpikeQueue')\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "In Brian 1.x code generation doesn't work for all models, so you might need to disable it for some simulations (which you can do in the script rather than the preferences).\n",
      "\n",
      "Here's an example of the speed difference:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from brian import *\n",
      "import time\n",
      "def runsim(N, duration=1*second, codegen=False):\n",
      "    set_global_preferences(usecodegen=codegen)\n",
      "    clk = Clock(dt=0.1*ms)\n",
      "    G = NeuronGroup(N, 'dv/dt=(2-v**2)/(10*ms):1', reset=0, threshold=1, clock=clk)\n",
      "    G.v = rand(len(G))\n",
      "    net = Network(G)\n",
      "    start = time.time()\n",
      "    net.run(duration)\n",
      "    end = time.time()\n",
      "    return end-start"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "N = 10\n",
      "runsim(N, codegen=True, duration=1*ms)\n",
      "t_without = runsim(N, codegen=False)\n",
      "t_with = runsim(N, codegen=True)\n",
      "print 'N =', N\n",
      "print 'Without code generation:', t_without \n",
      "print 'With code generation:   ', t_with\n",
      "print 'Speedup:                ', t_without/t_with"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "brian.stateupdater: WARNING  Using codegen CStateUpdater\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "brian.stateupdater: WARNING  Using codegen CStateUpdater\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "N = 10\n",
        "Without code generation: 0.461999893188\n",
        "With code generation:    0.175000190735\n",
        "Speedup:                 2.63999651228\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Connection and Synapses"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Brian 1.4 introduced the `Synapses` object, which is much more flexible than the older `Connection` object.\n",
      "\n",
      "However, `Synapses` is currently much slower than `Connection` (we're working on this for Brian 2).\n",
      "\n",
      "Conclusion: only use `Synapses` if you cannot do what you need with `Connection` (e.g. nonlinear synapses)."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Working with large Connections"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Some users have run out of memory when working with very large numbers of synapses in `Connection` objects. This is because:\n",
      "\n",
      "* The underlying matrix object uses two data structures and converting between them is expensive.\n",
      "* When building the network we use a data structure optimised for inserting elements.\n",
      "* When running the simulation we use a data structure optimised for fast extraction of rows and columns.\n",
      "* When converting between them a large amount of memory is used.\n",
      "\n",
      "To solve this problem, break your `Connection` into multiple sub-connections:\n",
      "\n",
      "* Instead of one connection from neurons `[0, ..., N-1]` to `[0, ..., N-1]`\n",
      "* Use two connections:\n",
      "   - from `[0, ..., N/2-1]` to `[0, ..., N-1]`\n",
      "   - from `[N/2-1, ..., N-1]` to `[0, ..., N-1]`"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Looping over simulation runs"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here's how to do a loop over several parameters:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import gc\n",
      "for params in []:\n",
      "    clear(True, True)\n",
      "    gc.collect()\n",
      "    defaultclock.t = 0*second\n",
      "    # your code here"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Explanation:\n",
      "\n",
      "* Each time you call `run()` it collects all existing Brian objects\n",
      "* Because Python doesn't always immediately deallocate objects, sometimes objects from the previous run still exist for the next run\n",
      "* This means the second time you call `run()` you might be doing twice as much work as the first time.\n",
      "* Calling `clear(True, True)` deletes all memory from currently existing Brian objects.\n",
      "* Calling `gc.collect()` forces Python to deallocate these objects.\n",
      "* Don't forget to reset the global clock time to 0!\n",
      "\n",
      "All of this will work much better in Brian 2, the above is a workaround for Brian 1.x. For now we use the following function to abbreviate this:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def brianreset():\n",
      "    clear(True,True)\n",
      "    gc.collect()\n",
      "    defaultclock.t = 0*second"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Another way to run a simulation for several parameters is in parallel..."
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Running simulations in parallel"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There are many options. Most of them rely on you being able to pickle your Brian objects. This usually works, but sometimes objects cannot be pickled and you need to find workarounds. For example `f = lambda x: x**2` is a definition of the function f(x)=x**2, but lambda functions cannot be pickled. Simply use a `def` instead of `lambda`.\n",
      "\n",
      "We'll use this I-F curve function as an example:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def IF(v0):\n",
      "    brianreset()\n",
      "    \n",
      "    eqs = '''\n",
      "    dv/dt=(v0-v)/(10*ms) : volt\n",
      "    '''\n",
      "    group = NeuronGroup(1, eqs, threshold='v>10*mV', reset='v = 0*mV')   \n",
      "    monitor = SpikeMonitor(group)\n",
      "    duration = 1*second\n",
      "    run(duration)\n",
      "    return monitor.nspikes/duration\n",
      "\n",
      "V0 = [v0*mV for v0 in range(20)]\n",
      "\n",
      "log_level_error() # suppress a few warning messages"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Using a loop:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%time plot(V0, [IF(v0) for v0 in V0])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "CPU times: user 102.20 s, sys: 0.00 s, total: 102.20 s\n",
        "Wall time: 102.18 s\n"
       ]
      },
      {
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "[<matplotlib.lines.Line2D at 0x8083130>]"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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fX+R0WgtIJEy1tMAdd8C0abBkidXRSE9oMTgR6bLWVnOWz8SJ2sQ9HCgBiEiXnDhhTvVM\nSICXXlLnHw6UAETkogwD/uVfzM3bV6/WJu7hQstBi8hFOZ3mlM+KCnX+cnFKACJh4t13YcUK2LUL\nLrvM6mgkFCgBiISBTz+FefOgpEQbukjX6TkAkRB37Ji5tMPSpXDrrVZHI6FEg8AiIayjA3JyYNgw\n+NWvrI5GAkWDwCJyjqefNh/4+t//tToSCUVKACIhat06ePNN+OMfoV8/q6ORUKQSkEgI+vhjc5mH\n8nIYP97qaCTQAtV3+jwI3NLSwuzZsxk5ciQpKSns3LmT5uZmHA4HSUlJZGVl0dLS4s9YRQRobjbr\n/s8/r85fesbnBPDII48wbdo09u/fz5///GeSk5NxOp04HA4OHDhAZmYmTqfTn7GKRLyTJ80nfe+6\nC+65x+poJNT5VAI6duwY48aN429/+9sZrycnJ1NRUYHNZqOpqQm73c5f//rX706mEpBIjyxaZJZ/\n1q+HvhrBixhBNQuourqaa6+9lnnz5rFv3z7Gjx/P888/j8fjwWazAWCz2fB4POccW1BQ0Pm13W7H\nbrf7FLhIpPnNb6C01HzSV51/eHO73bjd7oCfx6c7gN27d3PLLbewfft2JkyYwKOPPsqVV17JihUr\nOHr0aOf7Bg0aRHNz83cn0x2AiE9274apU2HLFhg92upopLcF1SBwXFwccXFxTJgwAYDZs2ezZ88e\nhgwZQlNTEwCNjY3ExMT4L1KRCOXxwMyZ8Otfq/MX//IpAQwZMoRhw4Zx4MABADZt2sSoUaOYPn06\nLpcLAJfLRU5Ojv8iFYlAbW0wezb827+ZSUDEn3x+DmDfvn3cd999tLW1kZCQwOuvv057ezu5ubkc\nOnSI+Ph4iouLGTBgwHcnUwlIpFvuvx/q681F3vpo5a6IpQ1hRCLMSy+Z2znu3AlXXWV1NGIlJQCR\nCLJtmznXf+tWSEqyOhqxWlANAotI4NTVQW4uvPGGOn8JLCUAkSDy9dfmYO9DD8G0aVZHI+FOJSCR\nILJwIfzf/8H//A9ERVkdjQSLoHoSWET8b+1a+P3vYc8edf7SO3QHIBIEqqrM7Ry1vLOcjwaBRcLU\n11+bg74FBer8pXfpDkDEYgsXwuHDUFys0o+cn8YARMKQ6v5iJd0BiFhEdX/pKo0BiIQR1f0lGOgO\nQMQCqvtLd2gMQCRMqO4vwUJ3ACK9SHV/8YXGAERCnOr+Emx0ByDSS1T3F19pDEAkhKnuL8FIdwAi\nAaa6v/SUxgBEQpDq/hLMdAcgEkCq+4s/aAxAJMSo7i/BTncAIgGgur/4k8YAREKE6v4SKnxOAO3t\n7YwbN47p06cD0NzcjMPhICkpiaysLFpaWvwWpEgoeewxGDHCrP+LBDOfE8ALL7xASkoKUd8WN51O\nJw6HgwMHDpCZmYnT6fRbkCKh4lTd/5VXVPeX4OdTAqirq2P9+vXcd999nXWpsrIy8vPzAcjPz6ek\npMR/UYqEgPZ2ePBBMwlcfbXV0YhcnE+zgH70ox+xfPlyvvzyy87XPB4PNpsNAJvNhsfjOe+xBQUF\nnV/b7XbsdrsvIYgEnb17ISYGbr7Z6kgk1Lndbtxud8DP0+0E8M477xATE8O4ceMuGGBUVFRnaehs\npycAkXCyZQtMnmx1FBIOzv5wXFhYGJDzdDsBbN++nbKyMtavX8/XX3/Nl19+ydy5c7HZbDQ1NTFk\nyBAaGxuJiYkJRLwiQev99+Hf/93qKES6rkfPAVRUVPDzn/+ct99+m8cff5zBgwfzxBNP4HQ6aWlp\nOWcgWM8BSLj65hsYPBiqq82/RfwpaJ8DOFXqefLJJ3nvvfdISkri/fff58knn+xxcCKh4o9/hIQE\ndf4SWvQksIgfLFkCzc3wi19YHYmEo6C9AxARcwD4jjusjkKke3QHINJDX38N11wDDQ1w1VVWRyPh\nSHcAIkFqxw4YNUqdv4QeJQCRHnr/fZV/JDQpAYj0kB4Ak1ClMQCRHvj738FmA48Hvvc9q6ORcKUx\nAJEgtHUrjBunzl9CkxKASA9o+qeEMiUAkR7QALCEMo0BiPjo2DGIi4MjR+DSS62ORsKZxgBEgswH\nH0B6ujp/CV1KACI+0vRPCXVKACI+Uv1fQp3GAER88MUXMHy4+Xd0tNXRSLjTGIBIEHG74Z/+SZ2/\nhDYlABEfqPwj4UAJQMQHGgCWcKAEINJNjY3Q1ARjx1odiUjPKAGIdJPbDbfdBpdcYnUkIj2jBCDS\nTar/S7hQAhDpJtX/JVwoAYh0w6FD8OWX5haQIqFOCUCkG059+u+j/zkSBny6jGtra5k8eTKjRo1i\n9OjRvPjiiwA0NzfjcDhISkoiKyuLlpYWvwYrYrX331f5R8KHT0tBNDU10dTUxNixY2ltbWX8+PGU\nlJTw+uuvc8011/D444+zbNkyjh49itPp/O5kWgpCQphhwPXXw+bNkJRkdTQSSYJqKYghQ4Yw9ttJ\n0P3792fkyJHU19dTVlZGfn4+APn5+ZSUlPgvUhGLHTwIHR2QmGh1JCL+0benP6Cmpoa9e/eSnp6O\nx+PBZrMBYLPZ8Hg857y/oKCg82u73Y7dbu9pCCK94tT0z6goqyORcOd2u3G73QE/T49WA21tbeX2\n22/nJz/5CTk5OQwcOJCjR492fn/QoEE0Nzd/dzKVgCSE5eWBwwHz51sdiUSaoCoBAXzzzTfMmjWL\nuXPnkpOTA5if+puamgBobGwkJibGP1GKWMwwtAG8hB+fEoBhGCxYsICUlBQeffTRztezs7NxuVwA\nuFyuzsQgEur274crroD4eKsjEfEfn0pAW7du5bbbbmPMmDFEfVsQLSoqYuLEieTm5nLo0CHi4+Mp\nLi5mwIAB351MJSAJUStWwN698OqrVkcikShQfad2BBPpglmzYOZMuOceqyORSKQEIGKRjg649lr4\n+GO47jqro5FIFHSDwCKRYt8+MwGo85dwowQgchFa/VPClRKAyEVo/X8JVxoDEPHi5Em45hqoqjLL\nQCJW0BiAiAU++shcAE6dv4QjJQARL/T0r4QzJQARL7T+v4QzjQGIXEBbGwweDLW1cNoD7SK9TmMA\nIr1s50648UZ1/hK+lABELkDTPyXcKQGIXIAGgCXcaQxA5DxOnDCnfjY1Qf/+VkcjkU5jACK9aPt2\nSEtT5y/hTQlA5Dw0/VMigRKAyHmo/i+RQGMAImf56isYOhQOH4bLL7c6GhGNAYj0mq1bYcIEdf4S\n/pQARM6i+f8SKZQARM6iAWCJFBoDEDnN0aNwww1w5Aj062d1NCImjQGI9IKKCrjlFnX+EhmUAEKY\n2+22OoSw4na7Nf3Tj3R9Bj+/J4Dy8nKSk5NJTExk2bJl/v7xchr9B/Mvt9ut+r8f6foMfn5NAO3t\n7Tz44IOUl5dTWVnJb3/7W/bv3+/PU4gEzN//bq79f9NNVkci0jv8mgB27drFiBEjiI+PJzo6mjlz\n5lBaWurPU4gETE0NZGRA375WRyLSO/x6qdfX1zNs2LDOf8fFxbFz584z3hMVFeXPU0a8wsJCq0MI\nM4XoEvUfXZ/Bza8J4GKdu6aAiogED7+WgGJjY6mtre38d21tLXFxcf48hYiI+IlfE8DNN99MVVUV\nNTU1tLW1sXbtWrKzs/15ChER8RO/loD69u3LihUrmDJlCu3t7SxYsICRI0f68xQiIuInPboDON+c\n/6lTp/Lpp5/y2Wef8dRTT/Hwww+TmJhIWloae/fu9XosQHNzMw6Hg6SkJLKysmhpaelJiCGlK89Q\ndLc9CwoKiIuLY9y4cYwbN47y8vKA/x7BoiftOX/+fGw2G6mpqWe8P1Kvz0C0pa7N7rdnbW0tkydP\nZtSoUYwePZoXX3yx8/0+XZuGj06ePGkkJCQY1dXVRltbm5GWlmZUVlae8Z53333XmDp1qmEYhrFj\nxw4jPT39oscuXrzYWLZsmWEYhuF0Oo0nnnjC1xBDSqDas6CgwHjuued695cJAj1pT8MwjA8++MDY\ns2ePMXr06DOOicTrM1BtqWuz++3Z2Nho7N271zAMw/jqq6+MpKQkY//+/YZh+HZt+nwH0JU5/2Vl\nZeTn5wOQnp5OS0sLTU1NXo89/Zj8/HxKSkp8DTGkBKo9ITJnX/WkPQEyMjIYOHDgOT83Eq/PQLUl\n6NrsTnt6PB6GDBnC2LFjAejfvz8jR46kvr7+nGO6em36nADON+f/VCAXe09DQ8MFj/V4PNhsNgBs\nNhsej8fXEENKoNoT4Je//CVpaWksWLAgYkoWPWlPbyLx+gxUW4KuTeh6e9bV1Z3xnpqaGvbu3Ut6\nejrg27XpcwLo6gNdXcnwhmGc9+dFRUVFzINj/mzP091///1UV1fzpz/9iaFDh7Jo0SJfwgs5vrZn\nd663SLk+A9WWuja989aera2tzJ49mxdeeIH+/fuf9xxdOY/PCaArc/7Pfk9dXR1xcXHnfT02NhYw\nM9epW8fGxkZiYmJ8DTGk+LM9Tz82Jiam82K477772LVrV4B/k+Dga3ueug4vJBKvz0C1pa5NU3fb\n85tvvmHWrFnce++95OTkdL7Hl2vT5wTQlTn/2dnZvPnmmwDs2LGDAQMGYLPZvB6bnZ2Ny+UCwOVy\nnfELhrNAtWdjY2Pn8W+99dY5MzHCVU/a05tIvD4D1Za6NrvfnoZhsGDBAlJSUnj00UfPOabb12ZP\nRrPXr19vJCUlGQkJCcbSpUsNwzCMVatWGatWrep8zwMPPGAkJCQYY8aMMT766COvxxqGYXzxxRdG\nZmamkZiYaDgcDuPo0aM9CTGkBKI9586da6SmphpjxowxZsyYYTQ1NfXeL2SxnrTnnDlzjKFDhxr9\n+vUz4uLijNdee80wjMi9PgPRlro2u9+eH374oREVFWWkpaUZY8eONcaOHWts2LDBMAzfrs1e3RJS\nRESCh3YEExGJUEoAIiIRSglARCRCKQGIiEQoJQARkQilBCAiEqH+H8V5JfpdV49xAAAAAElFTkSu\nQmCC\n"
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Using multiprocessing (doesn't work in IPython):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "if 0:\n",
      "    import multiprocessing\n",
      "    pool = multiprocessing.Pool()\n",
      "    plot(V0, pool.map(IF, V0))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 21
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Using IPython:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython import parallel\n",
      "rc = parallel.Client()\n",
      "view = rc[:]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%px\n",
      "from brian import *\n",
      "import gc"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%time plot(V0, view.map_sync(IF, V0))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "CPU times: user 19.93 s, sys: 0.00 s, total: 19.93 s\n",
        "Wall time: 19.92 s\n"
       ]
      },
      {
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "[<matplotlib.lines.Line2D at 0x80bbc90>]"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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wjMi9PgPRlro2u9+eH374oREVFWWkpaUZY8eONcaOHWts2LDBMAzfrs1e3RJS\nRESCh3YEExGJUEoAIiIRSglARCRCKQGIiEQoJQARkQilBCAiEqH+H8V5JfpdV49xAAAAAElFTkSu\nQmCC\n"
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There are also many other options for parallel execution of code, including:\n",
      "\n",
      "* **playdoh** written by Brian's very own Cyrille Rossant. This library also allows you to easily apply global optimisation algorithms running in parallel over multiple CPUs and machines, for example for fitting models to data.\n",
      "* Brian's ``run_tasks`` function, but we'll come back to that later."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "But before you start using multiple CPUs..."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Can you just do something like this?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def IF_vectorised(V0):\n",
      "    brianreset()\n",
      "    \n",
      "    eqs = '''\n",
      "    dv/dt=(v0-v)/(10*ms) : volt\n",
      "    v0 : volt\n",
      "    '''\n",
      "    group = NeuronGroup(len(V0), eqs, threshold='v>10*mV', reset='v = 0*mV')   \n",
      "    group.v0 = V0\n",
      "    monitor = SpikeCounter(group)\n",
      "    duration = 1*second\n",
      "    run(duration)\n",
      "    return monitor.count/duration\n",
      "\n",
      "%time plot(V0, IF_vectorised(V0))\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "CPU times: user 5.72 s, sys: 0.00 s, total: 5.72 s\n",
        "Wall time: 5.72 s\n"
       ]
      },
      {
       "output_type": "pyout",
       "prompt_number": 25,
       "text": [
        "[<matplotlib.lines.Line2D at 0x93c20d0>]"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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MHjzYcLlcxqFDhzoTYkSx4nrOmDHDSE9PNzIyMoypU6cajY2NXfcH2awz13P6\n9OlG//79jR49ehhJSUnGiy++aBhG7N6fVlxL3ZuBX8933nnHiIuLM4YPH26MGDHCGDFihLF27VrD\nMIK7N7t0T2AREQkfWhxXRCRGKQGIiMQoJQARkRilBCAiEqOUAEREYpQSgIhIjPp/02kw1GM+TXkA\nAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Managing simulation data"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Good options include:\n",
      "\n",
      "* Using joblib and writing all your code as if it was running from scratch each time, but automatically cache the results.\n",
      "* Writing data to a shelf file or database.\n",
      "\n",
      "Brian has a specific solution based on shelf files, but which allows for the use of multiple CPUs and machines in parallel.\n",
      "\n",
      "* ``DataManager`` object\n",
      "  - uses multiple shelf files (one per machine)\n",
      "  - controls access via a single process (because the databases underlying shelf are not process safe)\n",
      "* ``run_tasks`` function\n",
      "  - like a parallel ``map``\n",
      "  - the data is written into a ``DataManager`` object\n",
      "  - has an optional GUI allowing control over running simulations"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "if 0: # doesn't work in IPython\n",
      "    from brian import *\n",
      "    from brian.tools.datamanager import *\n",
      "    from brian.tools.taskfarm import *\n",
      "    \n",
      "    def find_rate(k, report):\n",
      "        eqs = '''\n",
      "        dV/dt = (k-V)/(10*ms) : 1\n",
      "        '''\n",
      "        G = NeuronGroup(1000, eqs, reset=0, threshold=1)\n",
      "        M = SpikeCounter(G)\n",
      "        run(30*second, report=report)\n",
      "        return (k, mean(M.count)/30)\n",
      "    \n",
      "    if __name__=='__main__':\n",
      "        N = 20\n",
      "        dataman = DataManager('taskfarmexample')\n",
      "        if dataman.itemcount()<N:\n",
      "            M = N-dataman.itemcount()\n",
      "            run_tasks(dataman, find_rate, rand(M)*19+1)\n",
      "        X, Y = zip(*dataman.values())\n",
      "        plot(X, Y, '.')\n",
      "        xlabel('k')\n",
      "        ylabel('Firing rate (Hz)')\n",
      "        show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.core.display import Image\n",
      "Image(filename='taskcontrol.jpg')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "jpeg": 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6dKbckcgDHon4aEWuQPgX8KF5/p/z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Rj5pvBSU1RUzaNEUbuVUpJriK3EJmegkmiiXBNXmkSKNcA01SOq1OBWrEKCQr27b7vdb+z2ywh8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\n9h3zw/8APP8Ay+//ALgn37r3Xv8Aho8/97Dvnh/55/5ff/3BPv3Xuvf8NHn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tvltoHR7h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cWyoslRd75bAbg7QV83uWCoze4dqbf2xtrau4cVXUuZgrtl7g2xjdmYqTHV2DkxtVQ19BDX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QOqSmUwu8sgMYjhWIiaRHns1uQ/zdzDHeck8xwPt1zBuE9huiNC/hF4VtbdhLLK8UskPh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\nX//Z\n",
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "<IPython.core.display.Image at 0x57fe330>"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Understanding Brian's Network"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "When you call ``run()``, what happens is:\n",
      "\n",
      "* Brian creates a ``Network()`` object\n",
      "* It adds all existing Brian objects to this network\n",
      "  - Actually, the rule is slightly more complex than this, see the discussion of 'magic' in the docs for more details.\n",
      "* It calls ``Network.run()`` on this\n",
      "\n",
      "The way ``Network.run()`` works is:\n",
      "\n",
      "* It builds an 'update schedule'.\n",
      "  - This is the order in which objects are updated\n",
      "  - Normally, this is\n",
      "     - Numerical integration step\n",
      "     - Thresholding operation\n",
      "     - Synaptic propagation\n",
      "     - Resets\n",
      "  - You can change this.\n",
      "  - You can choose to have certain objects update at specific points in this schedule\n",
      "     - always at the start\n",
      "     - always at the end\n",
      "     - always just before synaptic propagation\n",
      "     - etc.\n",
      "* At each time step:\n",
      "  - Choose a clock to process\n",
      "     - The one with the lowest current time\n",
      "     - If several have the same time, they can be ordered for more precise control\n",
      "  - Process all objects with this clock\n",
      "  - Increment that clock's time\n",
      "* This is repeated until all clocks have run for the specified duration."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Network operations"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The `NetworkOperation` object, and `network_operation` decorator allow you to run arbitrary code at every timestep. This is one of the main mechanisms for extending Brian to do new things that we didn't think of."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "brianreset()\n",
      "\n",
      "N = 5\n",
      "G = NeuronGroup(N, 'dV/dt = -V/(10*ms) : 1')\n",
      "@network_operation(clock=EventClock(dt=5*ms))\n",
      "def random_input():\n",
      "    i = randint(N)\n",
      "    G.V[i] += 1\n",
      "M = StateMonitor(G, 'V', record=True)\n",
      "run(100*ms)\n",
      "plot(M.times, M.values.T+3*arange(N)[newaxis, :]);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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N46OWfvtb4JZb+Milkydde89A1tICFBT4ugrih/w32PsSAlIp8Ic/AEVFPGxG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\njGDkUQAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Some useful Brian features you may not know"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "TimedArray"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "brianreset()\n",
      "\n",
      "N = 5\n",
      "duration = 100 * ms\n",
      "Vr = -60 * mV\n",
      "Vt = -50 * mV\n",
      "tau = 10 * ms\n",
      "Rmin = 1 * Mohm\n",
      "Rmax = 10 * Mohm\n",
      "freq = 50 * Hz\n",
      "k = 10 * nA\n",
      "\n",
      "eqs = '''\n",
      "dV/dt = (-(V-Vr)+R*I)/tau : volt\n",
      "R : ohm\n",
      "I : amp\n",
      "'''\n",
      "\n",
      "G = NeuronGroup(N, eqs, reset='V=Vr', threshold='V>Vt')\n",
      "G.R = linspace(Rmin, Rmax, N)\n",
      "\n",
      "t = linspace(0 * second, duration, int(duration / defaultclock.dt))\n",
      "I = clip(k * sin(2 * pi * freq * t), 0, Inf)\n",
      "G.I = TimedArray(I)\n",
      "\n",
      "M = MultiStateMonitor(G, record=True)\n",
      "\n",
      "run(duration)\n",
      "\n",
      "subplot(211)\n",
      "M['I'].plot()\n",
      "ylabel('I (amp)')\n",
      "subplot(212)\n",
      "M['V'].plot()\n",
      "ylabel('V (volt)')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "<matplotlib.text.Text at 0x9ac5630>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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YjsaXCPtafDj0kZsDhWCGj85MH61bjySEJ9K88sor1NTU4Pf7+7naYi08u7dV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RnbSVVBFcEECN0mJv2MZ38cL6REKK4UBFOg+dSbbGtDOAarVhYwYiQcc7Rf42mX2XtjYzLJlEEh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\nRRZZDCn+P4tRFtyZ0JQXAAAAAElFTkSuQmCC\n"
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Linked variables"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "brianreset()\n",
      "\n",
      "N = 5\n",
      "f = 50 * Hz\n",
      "a_min = 1.0\n",
      "a_max = 100.0\n",
      "tau_haircell = 50 * ms\n",
      "tau = 10 * ms\n",
      "duration = 100 * ms\n",
      "\n",
      "eqs_haircells = '''\n",
      "input = a*sin(2*pi*f*t) : 1\n",
      "x = clip(input, 0, Inf)**(1.0/3.0) : 1\n",
      "a : 1\n",
      "dy/dt = (x-y)/tau_haircell : 1 \n",
      "'''\n",
      "\n",
      "haircells = NeuronGroup(N, eqs_haircells)\n",
      "haircells.a = linspace(a_min, a_max, N)\n",
      "M_haircells = MultiStateMonitor(haircells, vars=('input', 'y'), record=True)\n",
      "\n",
      "eqs_nervefibres = '''\n",
      "dV/dt = (I-V)/tau : 1\n",
      "I : 1\n",
      "'''\n",
      "nervefibres = NeuronGroup(N, eqs_nervefibres, reset=0, threshold=1)\n",
      "nervefibres.I = linked_var(haircells, 'y')\n",
      "M_nervefibres = MultiStateMonitor(nervefibres, record=True)\n",
      "\n",
      "run(duration)\n",
      "\n",
      "subplot(221)\n",
      "M_haircells['input'].plot()\n",
      "ylabel('haircell.input')\n",
      "subplot(222)\n",
      "M_haircells['y'].plot()\n",
      "ylabel('haircell.y')\n",
      "subplot(223)\n",
      "M_nervefibres['I'].plot()\n",
      "ylabel('nervefibres.I')\n",
      "subplot(224)\n",
      "M_nervefibres['V'].plot()\n",
      "ylabel('nervefibres.V')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "brian.equations   : WARNING  Equation variable t also exists in the namespace\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "brian.equations   : WARNING  Equation variable x also exists in the namespace\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "brian.equations   : WARNING  Equation variable I also exists in the namespace\n"
       ]
      },
      {
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "<matplotlib.text.Text at 0xa005050>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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QASEET2Zk8FJYGG4tg4bLy2HaNMlOOnSodEwuh7ffhttuk5b4s7M7rNMzoaG8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\ntkXTrQuTP+3B8luW14sR8bD3YGL4RCaGT0QIwcnck2w/v51vj33LjE0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WOvKN4dzHmfL0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\n"
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Remote control"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Allows us to control a running Brian script.\n",
      "\n",
      "Run the script with a ``RemoteControlServer`` object, like this:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "brianreset()\n",
      "\n",
      "eqs = '''\n",
      "dV/dt = (I-V)/(10*ms)+0.1*xi*(2/(10*ms))**.5 : 1\n",
      "I : 1\n",
      "'''\n",
      "\n",
      "G = NeuronGroup(3, eqs, reset=0, threshold=1)\n",
      "M = RecentStateMonitor(G, 'V', duration=50*ms)\n",
      "\n",
      "server = RemoteControlServer()\n",
      "\n",
      "run(1e10*second)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "brian.equations   : WARNING  Equation variable I also exists in the namespace\n"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now you can control it like this (we'll run these commands in a separate IPython console):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "if 0:\n",
      "    from brian import *\n",
      "    client = RemoteControlClient()\n",
      "    clf(); plot(*client.evaluate('(M.times, M.values)'))\n",
      "    client.execute('G.I = 1.1')\n",
      "    clf(); plot(*client.evaluate('(M.times, M.values)'))\n",
      "    client.stop()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Linear, nonlinear and multilinear equations"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "When you create a ``NeuronGroup`` in Brian, it automatically selects what it thinks is the best way to integrate the equations.\n",
      "\n",
      "* If the equations are linear, they can be solved exactly.\n",
      "* If the equations are nonlinear, a numerical method is used.\n",
      "* By default, the numerical method is forward Euler, but alternative methods can be selected.\n",
      "\n",
      "There is a limitation with linear equations though, which will not be present in Brian 2, namely that the equations have to be identical for all neurons. For example, this will be integrated exactly:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def getsol_exact():\n",
      "    brianreset()\n",
      "    \n",
      "    tau = 10*ms\n",
      "    eqs = '''\n",
      "    dv/dt = -v/tau : 1\n",
      "    '''\n",
      "    G = NeuronGroup(1, eqs)\n",
      "    G.v = 1\n",
      "    M = StateMonitor(G, 'v', record=True)\n",
      "    run(100*ms)\n",
      "    return M[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "But this will not:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def getsol_numerical():\n",
      "    brianreset()\n",
      "    \n",
      "    eqs = '''\n",
      "    dv/dt = -v/tau : 1\n",
      "    tau : second\n",
      "    '''\n",
      "    G = NeuronGroup(1, eqs)\n",
      "    G.v = 1\n",
      "    G.tau = 10*ms\n",
      "    M = StateMonitor(G, 'v', record=True)\n",
      "    run(100*ms)\n",
      "    return M[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "exact = getsol_exact()\n",
      "numerical = getsol_numerical()\n",
      "figure(figsize=(10,4))\n",
      "subplot(121)\n",
      "title('Solutions')\n",
      "plot(exact)\n",
      "plot(numerical)\n",
      "subplot(122)\n",
      "title('Difference')\n",
      "plot(exact-numerical)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 12,
       "text": [
        "[<matplotlib.lines.Line2D at 0x9c85d30>]"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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3AwegZUuzU1wZHx8YNUqT4kXswWIYhmH3k1gsXOppTp0upcGspuy98yhhrevb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\nxE5UaImIiIjYiQotERERETv5/5dpY5rzRTTmAAAAAElFTkSuQmCC\n"
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The reason is that the second form with tau as a parameter would allow each neuron to be a different linear equation, and so it has to treat it as nonlinear. There is a solution though: ``brian.experimental.multilinearstateupdater.MultiLinearNeuronGroup`` (see the docs)."
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Deep Brian voodoo: custom resets and refractoriness"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The system for resets and refractoriness in Brian is slightly limited and this will be corrected in Brian 2. For the moment though, there are some workarounds:\n",
      "\n",
      "* ``SimpleCustomRefractoriness``\n",
      "* ``CustomRefractoriness``\n",
      "\n",
      "The way the reset and refractoriness conditions work in Brian is that you can specify an arbitrary reset condition, and during the refractory period this will be called each time step on the neurons that are refractory.\n",
      "\n",
      "This would not allow you to, for example, combine an adaptive threshold with a refractory period. Here's how to do that:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "brianreset()\n",
      "eqs = '''\n",
      "dv/dt = -v/(10*ms) : 1\n",
      "dvt/dt = (1-vt)/(100*ms) : 1\n",
      "'''\n",
      "def reset(G, spikes):\n",
      "    G.vt[spikes] += 1\n",
      "    G.v[spikes] = 0\n",
      "inp = PoissonGroup(1, 100*Hz)\n",
      "refrac = SimpleCustomRefractoriness(reset, 10*ms, 'v')\n",
      "G = NeuronGroup(1, eqs, threshold='v>vt', reset=refrac)\n",
      "G.vt = 1\n",
      "C = Connection(inp, G, 'v', weight=0.5)\n",
      "M = MultiStateMonitor(G, record=True)\n",
      "run(500*ms)\n",
      "figure(figsize=(10, 8))\n",
      "M.plot()\n",
      "ylim(-0.1, 3.0)\n",
      "legend()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "brian.experimental.new_c_propagate: WARNING  Using new C based propagation function.\n"
       ]
      },
      {
       "output_type": "pyout",
       "prompt_number": 23,
       "text": [
        "<matplotlib.legend.Legend at 0x9c7ed10>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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cV9YnMpdT6kFFEQ2w664Tdf1778kuESWKqwIrO9yghxwCrFwpdkyfNSvK2SQ2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\n8c+nKmi1VwHrWIUaQ6l1IF4hVKVWCSorQNwbL0sqw96Te3H12lXZTiH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yAAAN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\nDAaDEv8fAhF3iiIWMIkAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "For even more control, you can choose a separate reset and refractoriness function to be called at the beginning and during the refractory period, respectively:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "brianreset()\n",
      "eqs = '''\n",
      "dv/dt = -v/(10*ms) : 1\n",
      "dvt/dt = (1-vt)/(100*ms) : 1\n",
      "savevt : 1\n",
      "'''\n",
      "def resetfunc(G, spikes):\n",
      "    G.vt[spikes] += 1\n",
      "    G.savevt[spikes] = G.vt[spikes]\n",
      "    G.v[spikes] = 0\n",
      "def refracfunc(G, indices):\n",
      "    G.vt[indices] = G.savevt[indices]\n",
      "    G.v[indices] = 0\n",
      "inp = PoissonGroup(1, 100*Hz)\n",
      "refrac = CustomRefractoriness(resetfunc, 10*ms, refracfunc)\n",
      "G = NeuronGroup(1, eqs, threshold='v>vt', reset=refrac)\n",
      "G.vt = 1\n",
      "C = Connection(inp, G, 'v', weight=0.5)\n",
      "M = MultiStateMonitor(G, record=True)\n",
      "run(500*ms)\n",
      "figure(figsize=(10, 8))\n",
      "M.plot()\n",
      "ylim(-0.1, 3.0)\n",
      "legend()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "brian.experimental.new_c_propagate: WARNING  Using new C based propagation function.\n"
       ]
      },
      {
       "output_type": "pyout",
       "prompt_number": 25,
       "text": [
        "<matplotlib.legend.Legend at 0x974ecf0>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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YrEi9NMo/Kyi3Q27MbjabQ4KkCu3KtVPdkKC16OnXE/mc82H84fGiS6FMMFgR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      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "And finally... (if there is any time)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Any questions?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}