{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> This is one of the 100 recipes of the [IPython Cookbook](http://ipython-books.github.io/), the definitive guide to high-performance scientific computing and data science in Python.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5.4. Accelerating Python code with Cython"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use Cython to accelerate the generation of the Mandelbrot fractal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We initialize the simulation and generate the grid\n",
    "in the complex plane."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "size = 200\n",
    "iterations = 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pure Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def mandelbrot_python(m, size, iterations):\n",
    "    for i in range(size):\n",
    "        for j in range(size):\n",
    "            c = -2 + 3./size*j + 1j*(1.5-3./size*i)\n",
    "            z = 0\n",
    "            for n in range(iterations):\n",
    "                if np.abs(z) <= 10:\n",
    "                    z = z*z + c\n",
    "                    m[i, j] = n\n",
    "                else:\n",
    "                    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%timeit -n1 -r1 m = np.zeros((size, size))\n",
    "mandelbrot_python(m, size, iterations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cython versions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We first import Cython."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#%load_ext cythonmagic\n",
    "%load_ext Cython"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Take 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we just add the %%cython magic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%cython -a\n",
    "import numpy as np\n",
    "\n",
    "def mandelbrot_cython(m, size, iterations):\n",
    "    for i in range(size):\n",
    "        for j in range(size):\n",
    "            c = -2 + 3./size*j + 1j*(1.5-3./size*i)\n",
    "            z = 0\n",
    "            for n in range(iterations):\n",
    "                if np.abs(z) <= 10:\n",
    "                    z = z*z + c\n",
    "                    m[i, j] = n\n",
    "                else:\n",
    "                    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%timeit -n1 -r1 m = np.zeros((size, size), dtype=np.int32)\n",
    "mandelbrot_cython(m, size, iterations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Virtually no speedup."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Take 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we add type information, using memory views for NumPy arrays."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%cython -a\n",
    "import numpy as np\n",
    "\n",
    "def mandelbrot_cython(int[:,::1] m, \n",
    "                      int size, \n",
    "                      int iterations):\n",
    "    cdef int i, j, n\n",
    "    cdef complex z, c\n",
    "    for i in range(size):\n",
    "        for j in range(size):\n",
    "            c = -2 + 3./size*j + 1j*(1.5-3./size*i)\n",
    "            z = 0\n",
    "            for n in range(iterations):\n",
    "                if z.real**2 + z.imag**2 <= 100:\n",
    "                    z = z*z + c\n",
    "                    m[i, j] = n\n",
    "                else:\n",
    "                    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%timeit -n1 -r1 m = np.zeros((size, size), dtype=np.int32)\n",
    "mandelbrot_cython(m, size, iterations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Interesting speedup!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> You'll find all the explanations, figures, references, and much more in the book (to be released later this summer).\n",
    "\n",
    "> [IPython Cookbook](http://ipython-books.github.io/), by [Cyrille Rossant](http://cyrille.rossant.net), Packt Publishing, 2014 (500 pages)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}