NumpyClassLive.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Numpy Tutorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.2437007 ,  0.20664325, -0.5526014 ,  0.09661953, -1.38473488,\n",
       "        0.15775498, -0.57295656,  0.60728466,  0.32191915, -1.14687457,\n",
       "       -1.0738633 ,  0.08957938,  1.7921492 ,  0.61082385,  0.48029965,\n",
       "       -1.67994052,  0.08845947,  1.30556059,  0.36737336, -2.39534695])"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "np.random.randn(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.ones(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[[1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.]],\n",
       "\n",
       "        [[1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.]]],\n",
       "\n",
       "\n",
       "       [[[1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.]],\n",
       "\n",
       "        [[1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.],\n",
       "         [1., 1., 1., 1., 1.]]]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.reshape(2,2,5,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.arange(20).reshape(5,4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  1,  2,  3],\n",
       "       [ 4,  5,  6,  7],\n",
       "       [ 8,  9, 10, 11],\n",
       "       [12, 13, 14, 15],\n",
       "       [16, 17, 18, 19]])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = np.array_split(a, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([[ 0,  1,  2,  3],\n",
       "        [ 4,  5,  6,  7],\n",
       "        [ 8,  9, 10, 11]]), array([[12, 13, 14, 15],\n",
       "        [16, 17, 18, 19]])]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "160"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.size * a.itemsize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "112"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sys import getsizeof\n",
    "getsizeof(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "160"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.nbytes"
   ]
  }
 ],
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