Numpy_learning/random.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# numpy.random.RandomState()函数用法\n",
    "\n",
    "1. 使用numpy.random.RandomState(1).uniform(1,2,(3,4))函数生成一个3行4列的数组，其中每个元素都是在[1,2]区间内<font color=red>均匀分布</font>的随机数\n",
    "这里 “1” 为随机数种子，只要随机数种子seed相同，产生的随机数系列就相同。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RandomState(MT19937) \n",
      "\n",
      "[[1.417022   1.72032449 1.00011437 1.30233257]\n",
      " [1.14675589 1.09233859 1.18626021 1.34556073]\n",
      " [1.39676747 1.53881673 1.41919451 1.6852195 ]]\n"
     ]
    }
   ],
   "source": [
    "rdm = np.random.RandomState(1)  #  定义一个随机数种子\n",
    "print(rdm,\"\\n\")\n",
    "a = rdm.uniform(1,2,(3,4))  # 产生一个3行4列的数组，其中每个元素都是在[1,2]区间内均匀分布的随机数\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. 使用numpy.random.RandomState(1).rand(d0,d1,…,dn)函数生成一个给定维度的数组，其中每个元素在[0,1)之间（包含0，不包含1），dn表示各个维度，返回值为指定维度的array\n",
    "   - rand(0)：表示随机产生一个空数组。\n",
    "   - rand(n)：表示随机产生一个一维的，每个元素在[0,1)之间的n个数字的数组。\n",
    "   - rand(m,n)：表示随机产生一个m行n列的二维数组。\n",
    "   - rand(d0,d1,…,dn)：表示随机生成一个$d0×d1×\\cdots×dn$维度的数组。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[] \n",
      "\n",
      "[0.90340192 0.1374747  0.13927635] \n",
      "\n",
      "[[0.80739129 0.39767684]] \n",
      "\n",
      "[[[0.1653542  0.92750858]\n",
      "  [0.34776586 0.7508121 ]\n",
      "  [0.72599799 0.88330609]\n",
      "  [0.62367221 0.75094243]]\n",
      "\n",
      " [[0.34889834 0.26992789]\n",
      "  [0.89588622 0.42809119]\n",
      "  [0.96484005 0.6634415 ]\n",
      "  [0.62169572 0.11474597]]\n",
      "\n",
      " [[0.94948926 0.44991213]\n",
      "  [0.57838961 0.4081368 ]\n",
      "  [0.23702698 0.90337952]\n",
      "  [0.57367949 0.00287033]]] \n",
      "\n"
     ]
    }
   ],
   "source": [
    "a = rdm.rand(0)  #生成一个空数组\n",
    "b = rdm.rand(3)  # 生成一个一维的，每个元素在[0,1)之间的3个数字的数组\n",
    "c = rdm.rand(1,2)  # 随机产生一个1行2列的，每个元素在[0,1)之间的二维数组\n",
    "d = rdm.rand(3,4,2)  # 生成一个3×4×2维度的，每个元素在[0,1)之间的三维数组\n",
    "print(a,\"\\n\")\n",
    "print(b,\"\\n\")\n",
    "print(c,\"\\n\")\n",
    "print(d,\"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " ##  基于 numpy.random.RandomState(int).rand(d0,d1,…,dn) 与基于numpy.random.rand(d0,d1,…,dn)，生成随机数组的区别\n",
    " 使用RandomState(int)可以自定义随机数种子，以保证每次执行代码，生成的数组都相同。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# numpy里random总结：\n",
    "\n",
    "1. np.random.randn()\n",
    "语法： numpy.random.randn(d0,d1,…,dn)\n",
    "功能： 用法同np.random.rand()一样，只是服从正态分布。用法同上。\n",
    "说明：\n",
    "标准正态分布又称为u分布，是以0为均值、以1为标准差的正态分布，记为N（0，1）。\n",
    "randn函数返回一个或一组样本，具有标准正态分布。\n",
    "dn表格每个维度\n",
    "返回值为指定维度的array\n",
    "\n",
    "2. np.random.randint()\n",
    "语法： numpy.random.randint(low, high=None, size=None, dtype=’l’)\n",
    "功能： 通过low来指定起点，通过high来指定终点，通过size参数来指定数组的维度，通过dtype来确定类型。\n",
    "说明：\n",
    "返回值为随机整数，范围区间为[low,high），包含low，不包含high\n",
    "参数：low为最小值，high为最大值，size为数组维度大小，dtype为数据类型，默认的数据类型是np.int\n",
    "high没有填写时，默认生成随机数的范围是[0，low)\n",
    "\n",
    "3. np.random.random(size=None)\n",
    "语法： numpy.random.random(size=None)\n",
    "功能： 生成[0,1)之间的浮点数，通过size参数来指定维数。\n",
    "说明：\n",
    "size : int or tuple of ints, optional.\n",
    "Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned. \n",
    "\n",
    "4. numpy.random.rand()\n",
    "均匀分布\n",
    "范围 [0, 1)\n",
    "\n",
    "5. numpy.random.normal(loc=mu, scale=sigma, size)\n",
    "正态分布\n",
    "mu，均值\n",
    "sigma，标准差\n",
    "size，数据shape，默认一个值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 0 0 0] \n",
      "\n",
      "[[ 2  1  0]\n",
      " [-2  0  0]] \n",
      "\n",
      "0.9888926077885405 \n",
      "\n",
      "[0.32897483] \n",
      "\n",
      "[0.96680953 0.76946094] \n",
      "\n",
      "[[0.0936316  0.2776172  0.16938396]\n",
      " [0.21494328 0.26245945 0.22463559]] \n",
      "\n",
      "[0.36292738 0.51118156 0.35250669] \n",
      "\n",
      "[[ 0.07101816  0.1111697  -0.89099377]] \n",
      "\n"
     ]
    }
   ],
   "source": [
    "y1 = np.random.randint(1,size=4)\n",
    "print(y1,\"\\n\")     #返回[0，1)之间的整数，只有0\n",
    "y2 = np.random.randint(-2,3,size=(2,3))\n",
    "print(y2,\"\\n\")      #输出为每个元素在[-2,3)之间的整数，维度为2×3的数组\n",
    "\n",
    "z1 = np.random.random()  #生成单个数字\n",
    "print(z1,\"\\n\")\n",
    "z2 = np.random.random(1)  #生成一维的数组\n",
    "print(z2,\"\\n\")\n",
    "z3 = np.random.random(2)  #生成1×2的数组\n",
    "print(z3,\"\\n\")\n",
    "z4 = np.random.random((2,3))   #生成一个2行3列的数组\n",
    "print(z4,\"\\n\")\n",
    "\n",
    "z5 = np.random.rand(3)  # 生成1×3的数组\n",
    "print(z5,\"\\n\")\n",
    "\n",
    "z6 = np.random.normal(0,1,(1,3))\n",
    "print(z6,\"\\n\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.13 ('gym')",
   "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": "3.9.13"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "eb62451c918ef6a4174992a3510c06ea27ba0bc2fc5ee7a9f470b6f52b0b170f"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}