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| 1 | +{ |
| 2 | + "cells": [ |
| 3 | + { |
| 4 | + "cell_type": "code", |
| 5 | + "execution_count": 1, |
| 6 | + "id": "8ddc2bc7-042f-4552-92a3-f9047a132e56", |
| 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": "30c3a8f2-797e-4427-9acd-0ea951421e92", |
| 17 | + "metadata": {}, |
| 18 | + "source": [ |
| 19 | + "### Determinant of a square array" |
| 20 | + ] |
| 21 | + }, |
| 22 | + { |
| 23 | + "cell_type": "code", |
| 24 | + "execution_count": 22, |
| 25 | + "id": "16a039d2-473c-4b23-8d08-108b0edae19b", |
| 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: 3 4 2 2\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 | + "[[3 4]\n", |
| 44 | + " [2 2]]\n", |
| 45 | + "\n", |
| 46 | + "The approx. determinant of the above square array is -2.0\n", |
| 47 | + "The absolute determinant of the above square array is -1.9999999999999998\n" |
| 48 | + ] |
| 49 | + } |
| 50 | + ], |
| 51 | + "source": [ |
| 52 | + "arr_shape = int(input(\"Enter size of square array: \"))\n", |
| 53 | + "arr = list(map(int,input(\"Enter a square array in row-wise manner: \").split()))\n", |
| 54 | + "\n", |
| 55 | + "if len(arr) == arr_shape**2 :\n", |
| 56 | + " sq_arr = np.array(arr, dtype=int).reshape(arr_shape, arr_shape)\n", |
| 57 | + " print(\"\\nSUCCESS: Reshape operation completed\")\n", |
| 58 | + " print(f\"Given square array is\")\n", |
| 59 | + " print(sq_arr)\n", |
| 60 | + " print(f\"\\nThe approx. determinant of the above square array is {round(np.linalg.det(sq_arr),0)}\")\n", |
| 61 | + " print(f\"The absolute determinant of the above square array is {np.linalg.det(sq_arr)}\")\n", |
| 62 | + "else:\n", |
| 63 | + " print(f\"ERROR: Cannot reshape array of size {len(arr)} into {(arr_shape, arr_shape)}\")" |
| 64 | + ] |
| 65 | + }, |
| 66 | + { |
| 67 | + "cell_type": "code", |
| 68 | + "execution_count": null, |
| 69 | + "id": "35643ed3-5bfe-443a-adf0-df266ba9da72", |
| 70 | + "metadata": {}, |
| 71 | + "outputs": [], |
| 72 | + "source": [] |
| 73 | + } |
| 74 | + ], |
| 75 | + "metadata": { |
| 76 | + "kernelspec": { |
| 77 | + "display_name": "Python 3", |
| 78 | + "language": "python", |
| 79 | + "name": "python3" |
| 80 | + }, |
| 81 | + "language_info": { |
| 82 | + "codemirror_mode": { |
| 83 | + "name": "ipython", |
| 84 | + "version": 3 |
| 85 | + }, |
| 86 | + "file_extension": ".py", |
| 87 | + "mimetype": "text/x-python", |
| 88 | + "name": "python", |
| 89 | + "nbconvert_exporter": "python", |
| 90 | + "pygments_lexer": "ipython3", |
| 91 | + "version": "3.8.5" |
| 92 | + } |
| 93 | + }, |
| 94 | + "nbformat": 4, |
| 95 | + "nbformat_minor": 5 |
| 96 | +} |
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