cython benchmark

cython-benchmark.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext Cython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%cython\n",
    "\n",
    "import numpy as np\n",
    "cimport numpy as cnp\n",
    "\n",
    "mu, sigma = 10.64, .35\n",
    "np.random.seed(1234)\n",
    "d = np.random.lognormal(mu, sigma, 10000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_tax(d):\n",
    "    tax_seg1 = d[(d > 256303)] * 0.45 - 16164.53\n",
    "    tax_seg2 = d[(d > 54057) & (d <= 256303)] * 0.42 - 8475.44\n",
    "    seg3 = d[(d > 13769) & (d <= 54057)] - 13769\n",
    "    seg4 = d[(d > 8820) & (d <= 13769)] - 8820\n",
    "    prog_seg3 = seg3 * 0.0000022376 + 0.2397\n",
    "    prog_seg4 = seg4 * 0.0000100727 + 0.14\n",
    "    return (\n",
    "        np.sum(tax_seg1) +\n",
    "        np.sum(tax_seg2) +\n",
    "        np.sum(seg3 * prog_seg3 + 939.57) +\n",
    "        np.sum(seg4 * prog_seg4)\n",
    "    ) / np.sum(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "%%cython -a\n",
    "# cython: np_pythran=True\n",
    "# cython: language=c++\n",
    "\n",
    "import numpy as np\n",
    "cimport numpy as cnp\n",
    "\n",
    "def calculate_tax_cython(cnp.ndarray[double, ndim=1] d):\n",
    "    tax_seg1 = d[(d > 256303)] * 0.45 - 16164.53\n",
    "    tax_seg2 = d[(d > 54057) & (d <= 256303)] * 0.42 - 8475.44\n",
    "    seg3 = d[(d > 13769) & (d <= 54057)] - 13769\n",
    "    seg4 = d[(d > 8820) & (d <= 13769)] - 8820\n",
    "    prog_seg3 = seg3 * 0.0000022376 + 0.2397\n",
    "    prog_seg4 = seg4 * 0.0000100727 + 0.14\n",
    "    return (\n",
    "        np.sum(tax_seg1) +\n",
    "        np.sum(tax_seg2) +\n",
    "        np.sum(seg3 * prog_seg3 + 939.57) +\n",
    "        np.sum(seg4 * prog_seg4)\n",
    "    ) / np.sum(d)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%timeit calculate_tax(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%timeit calculate_tax_cython(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}