np_reshape_for_tensor_operations.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "written for https://stackoverflow.com/q/49933144/425458"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "u = np.concatenate((np.ones((3, 1)), np.zeros((3,1))), axis=1).reshape(3,1,2)\n",
    "v = np.concatenate((np.zeros((3, 1)), np.ones((3,1))), axis=1).reshape(3,1,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "can only specify one unknown dimension",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-13-c2d6fb40d027>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mw\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mu\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m: can only specify one unknown dimension"
     ]
    }
   ],
   "source": [
    "w = u.reshape(-1,1,-1,-1) - v.reshape(1,-1,-1,-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 3, 1, 2)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "U = np.random.randint(0,2,size=(3,3))\n",
    "V = np.random.randint(0,2, size=(3,3,4,5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 3, 3, 3, 4, 5)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.multiply.outer(U,V).shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[[0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]]\n",
      "\n",
      "  [[0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]]\n",
      "\n",
      "  [[0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]]]\n",
      "\n",
      "\n",
      " [[[0 1 0 1 0]\n",
      "   [2 2 2 0 2]\n",
      "   [1 1 1 0 2]\n",
      "   [1 0 1 2 1]]\n",
      "\n",
      "  [[2 2 0 2 1]\n",
      "   [2 2 2 0 1]\n",
      "   [0 0 0 0 1]\n",
      "   [1 1 0 2 2]]\n",
      "\n",
      "  [[1 1 1 0 0]\n",
      "   [1 1 1 1 2]\n",
      "   [1 1 1 2 1]\n",
      "   [2 1 1 2 1]]]\n",
      "\n",
      "\n",
      " [[[0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]]\n",
      "\n",
      "  [[0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]]\n",
      "\n",
      "  [[0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]\n",
      "   [0 0 0 0 0]]]]\n",
      "[[1 1 0 2 1]\n",
      " [2 2 2 0 1]\n",
      " [1 1 0 0 2]\n",
      " [1 0 1 2 2]]\n"
     ]
    }
   ],
   "source": [
    "print(np.einsum('ab,bcde', U, V))\n",
    "print(np.einsum('ab,abcd', U, V))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[[0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0]],\n",
       "\n",
       "        [[0, 0, 0, 0, 1],\n",
       "         [0, 1, 1, 1, 1],\n",
       "         [1, 0, 0, 0, 0],\n",
       "         [1, 0, 1, 0, 0]],\n",
       "\n",
       "        [[0, 0, 1, 1, 0],\n",
       "         [0, 0, 1, 1, 1],\n",
       "         [1, 0, 0, 1, 1],\n",
       "         [0, 1, 1, 1, 1]]],\n",
       "\n",
       "\n",
       "       [[[0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0]],\n",
       "\n",
       "        [[0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0]],\n",
       "\n",
       "        [[0, 0, 0, 1, 1],\n",
       "         [1, 0, 1, 1, 1],\n",
       "         [0, 1, 0, 1, 1],\n",
       "         [0, 1, 0, 1, 1]]],\n",
       "\n",
       "\n",
       "       [[[1, 1, 1, 1, 0],\n",
       "         [0, 1, 0, 1, 1],\n",
       "         [1, 0, 1, 1, 0],\n",
       "         [1, 0, 0, 0, 0]],\n",
       "\n",
       "        [[0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0]],\n",
       "\n",
       "        [[1, 0, 1, 0, 1],\n",
       "         [0, 0, 1, 0, 0],\n",
       "         [1, 1, 1, 1, 0],\n",
       "         [1, 0, 0, 1, 0]]]])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "U[...,None,None]*V"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 0, 0],\n",
       "       [1, 1, 0],\n",
       "       [0, 0, 0]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "U"
   ]
  }
 ],
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