{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# choose 函数实现条件筛选"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对于数组，我们有时候需要进行类似 `switch` 和 `case` 进行条件选择，此时使用 choose 函数十分方便："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[11, 10, 11],\n",
       "       [12, 11, 10],\n",
       "       [11, 12, 12]])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "control = np.array([[1,0,1],\n",
    "                    [2,1,0],\n",
    "                    [1,2,2]])\n",
    "\n",
    "np.choose(control, [10, 11, 12])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在上面的例子中，`choose` 将 `0,1,2` 对应的值映射为了 `10, 11, 12`，这里的 `0,1,2` 表示对应的下标。\n",
    "\n",
    "事实上， `choose` 不仅仅能接受下标参数，还可以接受下标所在的位置："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[10,  1, 10],\n",
       "       [23, 10,  5],\n",
       "       [10, 27, 28]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i0 = np.array([[0,1,2],\n",
    "               [3,4,5],\n",
    "               [6,7,8]])\n",
    "i2 = np.array([[20,21,22],\n",
    "               [23,24,25],\n",
    "               [26,27,28]])\n",
    "control = np.array([[1,0,1],\n",
    "                    [2,1,0],\n",
    "                    [1,2,2]])\n",
    "\n",
    "np.choose(control, [i0, 10, i2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里，`control` 传入第一个 `1` 对应的是 10，传入的第一个 `0` 对应于 `i0` 相应位置的值即 `1`，剩下的以此类推。 \n",
    "\n",
    "下面的例子将数组中所有小于 `10` 的值变成了 `10`。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ True,  True,  True],\n",
       "       [False, False, False],\n",
       "       [False, False, False]], dtype=bool)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([[ 0, 1, 2], \n",
    "              [10,11,12], \n",
    "              [20,21,22]])\n",
    "\n",
    "a < 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[10, 10, 10],\n",
       "       [10, 11, 12],\n",
       "       [20, 21, 22]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.choose(a < 10, (a, 10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面的例子将数组中所有小于 10 的值变成了 10，大于 15 的值变成了 15。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 1, 1],\n",
       "       [0, 0, 0],\n",
       "       [2, 2, 2]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([[ 0, 1, 2], \n",
    "              [10,11,12], \n",
    "              [20,21,22]])\n",
    "\n",
    "lt = a < 10\n",
    "gt = a > 15\n",
    "\n",
    "choice = lt + 2 * gt\n",
    "choice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[10, 10, 10],\n",
       "       [10, 11, 12],\n",
       "       [15, 15, 15]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.choose(choice, (a, 10, 15))"
   ]
  }
 ],
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