e04-numpy-matematyka-rozwiazania.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NumPy - Matematyka - zadania"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Numpy Broadcasting Arithmetic\n",
    "\n",
    "1. Użyj danych z sekcji \"Input\" (patrz poniżej)\n",
    "1. Dla danych: ``a: ndarray``, ``b: ndarray``, ``c: ndarray``\n",
    "1. Oblicz pierwiastek kwadratowy każdego z elementu w ``a`` i ``b``\n",
    "1. Oblicz drugą potęgę (kwadrat) każdego z elementu w ``c``\n",
    "1. Dodaj elementy z ``a`` do ``b``\n",
    "1. Przemnóż wynik przez ``c``\n",
    "1. Porównaj wyniki z sekcją \"Output\" (patrz poniżej)\n",
    "\n",
    "Output:\n",
    "```python\n",
    "array([[ 1.41421356,  2.73205081],\n",
    "       [45.254834  ,  0.        ]])\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.41421356,  2.73205081],\n",
       "       [45.254834  ,  0.        ]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([[0, 1], [2, 3]], float)\n",
    "b = np.array([2, 3], float)\n",
    "c = np.array([[1, 1], [4, 0]], float)\n",
    "\n",
    "a = a ** (1/2)\n",
    "b = b ** (1/2)\n",
    "c = c ** 2\n",
    "\n",
    "(a + b) * c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Numpy Broadcasting Type Cast\n",
    "1. Dla danych: ``a: ndarray``, ``b: ndarray`` (patrz sekcja input)\n",
    "1. Dodaj ``a`` i ``b``\n",
    "1. Dodaj ``b`` i ``a``\n",
    "1. Co się stało?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.array([[1, 0], [0, 1]])\n",
    "b = [[4, 1], [2, 2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5, 1],\n",
       "       [2, 3]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5, 1],\n",
       "       [2, 3]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b + a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Numpy Broadcasting Matmul\n",
    "\n",
    "1. Dla danych: ``a: ndarray``, ``b: ndarray`` (patrz sekcja input)\n",
    "1. Przemnóż ``a`` i ``b`` używając mnożenia skalarnego\n",
    "1. Przemnóż ``a`` i ``b`` używając mnożenia macierzowego\n",
    "1. Przemnóż ``b`` i ``a`` używając mnożenia skalarnego\n",
    "1. Przemnóż ``b`` i ``a`` używając mnożenia macierzowego\n",
    "1. Omów wyniki"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.array([[1,0,1,0],\n",
    "              [0,1,1,0],\n",
    "              [3,2,1,0],\n",
    "              [4,1,2,0]])\n",
    "\n",
    "b = np.array([[4,1],\n",
    "              [2,2],\n",
    "              [5,1],\n",
    "              [2,3]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "operands could not be broadcast together with shapes (4,4) (4,2) ",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-9bc1a869709f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (4,4) (4,2) "
     ]
    }
   ],
   "source": [
    "a * b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 9,  2],\n",
       "       [ 7,  3],\n",
       "       [21,  8],\n",
       "       [28,  8]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a @ b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "operands could not be broadcast together with shapes (4,2) (4,4) ",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-10-f0e4c0ee4ba0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mb\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (4,2) (4,4) "
     ]
    }
   ],
   "source": [
    "b * a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "matmul: Input operand 1 has a mismatch in its core dimension 0, with gufunc signature (n?,k),(k,m?)->(n?,m?) (size 4 is different from 2)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-11-6948e4cb9803>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mb\u001b[0m \u001b[0;34m@\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m: matmul: Input operand 1 has a mismatch in its core dimension 0, with gufunc signature (n?,k),(k,m?)->(n?,m?) (size 4 is different from 2)"
     ]
    }
   ],
   "source": [
    "b @ a"
   ]
  }
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