{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Retrieving top-$k$ indices with argsort and using argpartition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.86 s, sys: 72 ms, total: 3.94 s\n",
      "Wall time: 3.9 s\n"
     ]
    }
   ],
   "source": [
    "%time x = np.random.randn(2 ** 26)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "i = 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 20 s, sys: 72 ms, total: 20.1 s\n",
      "Wall time: 20.1 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "result = np.argsort(x)[:i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 916 ms, sys: 60 ms, total: 976 ms\n",
      "Wall time: 976 ms\n"
     ]
    }
   ],
   "source": [
    "%%time \n",
    "\n",
    "result = np.argsort(\n",
    "  np.partition(x, kth=i)[:i])"
   ]
  }
 ],
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