{ "cells": [ { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 5, 6, 10, 12],\n", " [ 7, 8, 14, 16],\n", " [15, 18, 20, 24],\n", " [21, 24, 28, 32]])" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from scipy import linalg\r\n", "import numpy as np\r\n", "a = np.array([[1, 2], [3, 4]])\r\n", "b = np.array([[5, 6], [7, 8]])\r\n", "linalg.kron(a, b)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 5, 12],\n", " [ 7, 16],\n", " [15, 24],\n", " [21, 32]])" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "linalg.khatri_rao(a, b)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 8. , -6. , -4. , 3. ],\n", " [-7. , 5. , 3.5 , -2.5 ],\n", " [-6. , 4.5 , 2. , -1.5 ],\n", " [ 5.25, -3.75, -1.75, 1.25]])" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "linalg.inv(linalg.kron(a, b))" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 8. , -6. , -4. , 3. ],\n", " [-7. , 5. , 3.5 , -2.5 ],\n", " [-6. , 4.5 , 2. , -1.5 ],\n", " [ 5.25, -3.75, -1.75, 1.25]])" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "linalg.kron(linalg.inv(a), linalg.inv(b))" ] } ], "metadata": { "interpreter": { "hash": "50666865514ce8fadc5b7568d4a3d74bf2a0096f71e6d07e06e277213ef05d37" }, "kernelspec": { "display_name": "Python 3.7.9 64-bit ('env_ISYE8803': venv)", "name": "python3" }, "language_info": { "name": "python", "version": "" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }