profiling_line_memory.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following cells have dependencies which can be installed using:\n",
    "\n",
    "    pip install line_profiler\n",
    "    pip install memory_profiler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%load_ext line_profiler\n",
    "%load_ext memory_profiler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# some small functions for example purposes\n",
    "import numpy as np\n",
    "\n",
    "def func(n, a):\n",
    "  y = np.arange(n)\n",
    "  y = np.exp(-y*a)\n",
    "  return y\n",
    "\n",
    "def gunc(n, a):\n",
    "  y = np.exp(-n*a)\n",
    "  return y\n",
    "\n",
    "def hunc(n, a):\n",
    "  y1 = func(n, a)\n",
    "  y2 = gunc(n, a)\n",
    "  return y1, y2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%lprun -f func hunc(50000, 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "peak memory: 62.31 MiB, increment: 1.10 MiB\n"
     ]
    }
   ],
   "source": [
    "%memit hunc(50000, 0.5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (venv)",
   "language": "python",
   "name": "venv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}