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  "name": "",
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  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Timing function calls in Python"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import time\n",
      "\n",
      "def time_it(f):\n",
      "    time_it.active = 0\n",
      "\n",
      "    def tt(*args, **kwargs):\n",
      "        time_it.active += 1\n",
      "        t0 = time.time()\n",
      "        tabs = '\\t'*(time_it.active - 1)\n",
      "        name = f.__name__\n",
      "        print('{tabs}Executing <{name}>'.format(tabs=tabs, name=name))\n",
      "        res = f(*args, **kwargs)\n",
      "        print('{tabs}Function <{name}> execution time: {time:.3f} seconds'.format(\n",
      "            tabs=tabs, name=name, time=time.time() - t0))\n",
      "        time_it.active -= 1\n",
      "        return res\n",
      "    return tt\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 79
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import time\n",
      "import scipy.ndimage as nd\n",
      "import numpy as n\n",
      "\n",
      "@time_it\n",
      "def do_all(data, blurs):\n",
      "    for blur in blurs:\n",
      "        process(data, blur)\n",
      "        \n",
      "@time_it\n",
      "def process(data, amount):\n",
      "    blurred = nd.gaussian_filter(data, amount)\n",
      "    out = get_stats(blurred)\n",
      "    return out\n",
      "\n",
      "@time_it\n",
      "def get_stats(c):\n",
      "    return c.mean(), c.std()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 80
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = n.random.randn(5000,5000)\n",
      "blurs = n.arange(0,40,10)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "do_all(data, blurs)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Executing <do_all>\n",
        "\tExecuting <process>\n",
        "\t\tExecuting <get_stats>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t\tFunction <get_stats> execution time: 0.229 seconds"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\tFunction <process> execution time: 0.350 seconds\n",
        "\tExecuting <process>\n",
        "\t\tExecuting <get_stats>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t\tFunction <get_stats> execution time: 0.244 seconds"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\tFunction <process> execution time: 3.261 seconds\n",
        "\tExecuting <process>\n",
        "\t\tExecuting <get_stats>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t\tFunction <get_stats> execution time: 0.224 seconds"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\tFunction <process> execution time: 5.048 seconds\n",
        "\tExecuting <process>\n",
        "\t\tExecuting <get_stats>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t\tFunction <get_stats> execution time: 0.278 seconds"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\tFunction <process> execution time: 6.958 seconds\n",
        "Function <do_all> execution time: 15.617 seconds\n"
       ]
      }
     ],
     "prompt_number": 81
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}