03-numpy/03.12-matrix-object.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 矩阵"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用 `mat` 方法将 `2` 维数组转化为矩阵："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[1, 2, 4],\n",
       "        [2, 5, 3],\n",
       "        [7, 8, 9]])"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "a = np.array([[1,2,4],\n",
    "              [2,5,3], \n",
    "              [7,8,9]])\n",
    "A = np.mat(a)\n",
    "A"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "也可以使用 **Matlab** 的语法传入一个字符串来生成矩阵："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[1, 2, 4],\n",
       "        [2, 5, 3],\n",
       "        [7, 8, 9]])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.mat('1,2,4;2,5,3;7,8,9')\n",
    "A"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "利用分块创造新的矩阵："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[ 1,  2, 10, 20],\n",
       "        [ 3,  4, 30, 40],\n",
       "        [10, 20,  1,  2],\n",
       "        [30, 40,  3,  4]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([[ 1, 2],\n",
    "              [ 3, 4]])\n",
    "b = np.array([[10,20], \n",
    "              [30,40]])\n",
    "\n",
    "np.bmat('a,b;b,a')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "矩阵与向量的乘法："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1],\n",
       "       [2],\n",
       "       [3]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.array([[1], [2], [3]])\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[17],\n",
       "        [21],\n",
       "        [50]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A * x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`A.I` 表示 `A` 矩阵的逆矩阵："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[  1.00000000e+00   0.00000000e+00   0.00000000e+00]\n",
      " [  0.00000000e+00   1.00000000e+00   2.08166817e-17]\n",
      " [  2.22044605e-16  -8.32667268e-17   1.00000000e+00]]\n"
     ]
    }
   ],
   "source": [
    "print A * A.I"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "矩阵指数表示矩阵连乘："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 6497  9580  9836]\n",
      " [ 7138 10561 10818]\n",
      " [18434 27220 27945]]\n"
     ]
    }
   ],
   "source": [
    "print A ** 4"
   ]
  }
 ],
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