|
| 1 | +{ |
| 2 | + "cells": [ |
| 3 | + { |
| 4 | + "cell_type": "code", |
| 5 | + "execution_count": 1, |
| 6 | + "id": "678ce984-841d-49bd-b2c5-8586aaed05b2", |
| 7 | + "metadata": {}, |
| 8 | + "outputs": [], |
| 9 | + "source": [ |
| 10 | + "import numpy as np\n", |
| 11 | + "import pandas as pd" |
| 12 | + ] |
| 13 | + }, |
| 14 | + { |
| 15 | + "cell_type": "markdown", |
| 16 | + "id": "c8866271-04d5-4bd6-9916-f55bc5889968", |
| 17 | + "metadata": {}, |
| 18 | + "source": [ |
| 19 | + "### Eigenvalues and Eigenvectors of a square array" |
| 20 | + ] |
| 21 | + }, |
| 22 | + { |
| 23 | + "cell_type": "code", |
| 24 | + "execution_count": 3, |
| 25 | + "id": "346bcf67-e5be-49d2-8e22-31d87ed416cd", |
| 26 | + "metadata": {}, |
| 27 | + "outputs": [ |
| 28 | + { |
| 29 | + "name": "stdin", |
| 30 | + "output_type": "stream", |
| 31 | + "text": [ |
| 32 | + "Enter size of square array: 2\n", |
| 33 | + "Enter a square array in row-wise manner: 1 2 2 1\n" |
| 34 | + ] |
| 35 | + }, |
| 36 | + { |
| 37 | + "name": "stdout", |
| 38 | + "output_type": "stream", |
| 39 | + "text": [ |
| 40 | + "\n", |
| 41 | + "SUCCESS: Reshape operation completed\n", |
| 42 | + "Given square array is\n", |
| 43 | + "[[1 2]\n", |
| 44 | + " [2 1]]\n", |
| 45 | + "The eigenvalues of the above square array is\n", |
| 46 | + "[ 3. -1.]\n", |
| 47 | + "The eigenvectors of the above square array is\n", |
| 48 | + "[[ 0.70710678 -0.70710678]\n", |
| 49 | + " [ 0.70710678 0.70710678]]\n" |
| 50 | + ] |
| 51 | + } |
| 52 | + ], |
| 53 | + "source": [ |
| 54 | + "arr_shape = int(input(\"Enter size of square array: \"))\n", |
| 55 | + "arr = list(map(int,input(\"Enter a square array in row-wise manner: \").split()))\n", |
| 56 | + "\n", |
| 57 | + "if len(arr) == arr_shape**2 :\n", |
| 58 | + " sq_arr = np.array(arr, dtype=int).reshape(arr_shape, arr_shape)\n", |
| 59 | + " print(\"\\nSUCCESS: Reshape operation completed\")\n", |
| 60 | + " print(f\"Given square array is\")\n", |
| 61 | + " print(sq_arr)\n", |
| 62 | + " \n", |
| 63 | + " eig_val, eig_vec = np.linalg.eig(sq_arr)\n", |
| 64 | + " print(\"The eigenvalues of the above square array is\")\n", |
| 65 | + " print(eig_val)\n", |
| 66 | + " print(\"The eigenvectors of the above square array is\")\n", |
| 67 | + " print(eig_vec)\n", |
| 68 | + "else:\n", |
| 69 | + " print(f\"ERROR: Cannot reshape array of size {len(arr)} into {(arr_shape, arr_shape)}\")" |
| 70 | + ] |
| 71 | + }, |
| 72 | + { |
| 73 | + "cell_type": "code", |
| 74 | + "execution_count": null, |
| 75 | + "id": "897a5000-e52d-4a07-afc1-2b722ec423e5", |
| 76 | + "metadata": {}, |
| 77 | + "outputs": [], |
| 78 | + "source": [] |
| 79 | + } |
| 80 | + ], |
| 81 | + "metadata": { |
| 82 | + "kernelspec": { |
| 83 | + "display_name": "Python 3", |
| 84 | + "language": "python", |
| 85 | + "name": "python3" |
| 86 | + }, |
| 87 | + "language_info": { |
| 88 | + "codemirror_mode": { |
| 89 | + "name": "ipython", |
| 90 | + "version": 3 |
| 91 | + }, |
| 92 | + "file_extension": ".py", |
| 93 | + "mimetype": "text/x-python", |
| 94 | + "name": "python", |
| 95 | + "nbconvert_exporter": "python", |
| 96 | + "pygments_lexer": "ipython3", |
| 97 | + "version": "3.8.5" |
| 98 | + } |
| 99 | + }, |
| 100 | + "nbformat": 4, |
| 101 | + "nbformat_minor": 5 |
| 102 | +} |
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