From 34d26b36d724add3cc2e067f2e9ed843fe41776b Mon Sep 17 00:00:00 2001 From: MadhuraWani803 <103093329+MadhuraWani803@users.noreply.github.com> Date: Sat, 25 Nov 2023 14:11:29 -0700 Subject: [PATCH] Add files via upload --- Phase 3/phase3_task0b.ipynb | 214 ++++++++++++++++++++++++++++++++++++ 1 file changed, 214 insertions(+) create mode 100644 Phase 3/phase3_task0b.ipynb diff --git a/Phase 3/phase3_task0b.ipynb b/Phase 3/phase3_task0b.ipynb new file mode 100644 index 0000000..d2c8d04 --- /dev/null +++ b/Phase 3/phase3_task0b.ipynb @@ -0,0 +1,214 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from utils import *\n", + "warnings.filterwarnings('ignore')\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "fd_collection = getCollection(\"team_5_mwdb_phase_2\", \"fd_collection\")" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "#same function as 0a\n", + "def pca_inherent_dimensionality(data, threshold):\n", + " \n", + " # Calculate the mean of the data\n", + " mean = np.mean(data, axis=0)\n", + " # Center the data by subtracting the mean\n", + " centered_data = data - mean\n", + " # Normalize the data\n", + " normalized_data = centered_data / np.std(centered_data, axis=0)\n", + "\n", + " # Reshape the centered data to ensure compatible dimensions\n", + " if(len(normalized_data.shape)==3):\n", + " reshaped_normalized_data = normalized_data.reshape(normalized_data.shape[0], normalized_data.shape[2])\n", + " else:\n", + " reshaped_normalized_data=normalized_data\n", + "\n", + " # Calculate the covariance matrix\n", + " covariance_matrix = np.dot(reshaped_normalized_data.T, reshaped_normalized_data) / (reshaped_normalized_data.shape[0] - 1)\n", + "\n", + " # Compute the eigenvalues and eigenvectors of the covariance matrix\n", + " eigenvalues, eigenvectors = np.linalg.eig(covariance_matrix)\n", + "\n", + " \n", + " # Determine the number of eigenvalues greater than the threshold\n", + " significant_eigenvalues = eigenvalues[eigenvalues > threshold]\n", + " inherent_dimensionality = len(significant_eigenvalues)\n", + "\n", + " return inherent_dimensionality" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Inherent dimensionality associated with label 0 : 140\n", + "Inherent dimensionality associated with label 1 : 134\n", + "Inherent dimensionality associated with label 2 : 75\n", + "Inherent dimensionality associated with label 3 : 182\n", + "Inherent dimensionality associated with label 4 : 27\n", + "Inherent dimensionality associated with label 5 : 186\n", + "Inherent dimensionality associated with label 6 : 20\n", + "Inherent dimensionality associated with label 7 : 20\n", + "Inherent dimensionality associated with label 8 : 22\n", + "Inherent dimensionality associated with label 9 : 26\n", + "Inherent dimensionality associated with label 10 : 22\n", + "Inherent dimensionality associated with label 11 : 16\n", + "Inherent dimensionality associated with label 12 : 63\n", + "Inherent dimensionality associated with label 13 : 48\n", + "Inherent dimensionality associated with label 14 : 20\n", + "Inherent dimensionality associated with label 15 : 42\n", + "Inherent dimensionality associated with label 16 : 44\n", + "Inherent dimensionality associated with label 17 : 24\n", + "Inherent dimensionality associated with label 18 : 21\n", + "Inherent dimensionality associated with label 19 : 60\n", + "Inherent dimensionality associated with label 20 : 23\n", + "Inherent dimensionality associated with label 21 : 28\n", + "Inherent dimensionality associated with label 22 : 30\n", + "Inherent dimensionality associated with label 23 : 53\n", + "Inherent dimensionality associated with label 24 : 22\n", + "Inherent dimensionality associated with label 25 : 34\n", + "Inherent dimensionality associated with label 26 : 35\n", + "Inherent dimensionality associated with label 27 : 34\n", + "Inherent dimensionality associated with label 28 : 24\n", + "Inherent dimensionality associated with label 29 : 25\n", + "Inherent dimensionality associated with label 30 : 27\n", + "Inherent dimensionality associated with label 31 : 33\n", + "Inherent dimensionality associated with label 32 : 25\n", + "Inherent dimensionality associated with label 33 : 31\n", + "Inherent dimensionality associated with label 34 : 33\n", + "Inherent dimensionality associated with label 35 : 37\n", + "Inherent dimensionality associated with label 36 : 31\n", + "Inherent dimensionality associated with label 37 : 25\n", + "Inherent dimensionality associated with label 38 : 31\n", + "Inherent dimensionality associated with label 39 : 42\n", + "Inherent dimensionality associated with label 40 : 32\n", + "Inherent dimensionality associated with label 41 : 33\n", + "Inherent dimensionality associated with label 42 : 21\n", + "Inherent dimensionality associated with label 43 : 16\n", + "Inherent dimensionality associated with label 44 : 16\n", + "Inherent dimensionality associated with label 45 : 25\n", + "Inherent dimensionality associated with label 46 : 48\n", + "Inherent dimensionality associated with label 47 : 49\n", + "Inherent dimensionality associated with label 48 : 20\n", + "Inherent dimensionality associated with label 49 : 26\n", + "Inherent dimensionality associated with label 50 : 43\n", + "Inherent dimensionality associated with label 51 : 39\n", + "Inherent dimensionality associated with label 52 : 15\n", + "Inherent dimensionality associated with label 53 : 31\n", + "Inherent dimensionality associated with label 54 : 42\n", + "Inherent dimensionality associated with label 55 : 56\n", + "Inherent dimensionality associated with label 56 : 29\n", + "Inherent dimensionality associated with label 57 : 40\n", + "Inherent dimensionality associated with label 58 : 38\n", + "Inherent dimensionality associated with label 59 : 19\n", + "Inherent dimensionality associated with label 60 : 32\n", + "Inherent dimensionality associated with label 61 : 21\n", + "Inherent dimensionality associated with label 62 : 19\n", + "Inherent dimensionality associated with label 63 : 41\n", + "Inherent dimensionality associated with label 64 : 15\n", + "Inherent dimensionality associated with label 65 : 37\n", + "Inherent dimensionality associated with label 66 : 27\n", + "Inherent dimensionality associated with label 67 : 16\n", + "Inherent dimensionality associated with label 68 : 19\n", + "Inherent dimensionality associated with label 69 : 22\n", + "Inherent dimensionality associated with label 70 : 18\n", + "Inherent dimensionality associated with label 71 : 22\n", + "Inherent dimensionality associated with label 72 : 25\n", + "Inherent dimensionality associated with label 73 : 16\n", + "Inherent dimensionality associated with label 74 : 28\n", + "Inherent dimensionality associated with label 75 : 39\n", + "Inherent dimensionality associated with label 76 : 28\n", + "Inherent dimensionality associated with label 77 : 24\n", + "Inherent dimensionality associated with label 78 : 19\n", + "Inherent dimensionality associated with label 79 : 30\n", + "Inherent dimensionality associated with label 80 : 19\n", + "Inherent dimensionality associated with label 81 : 41\n", + "Inherent dimensionality associated with label 82 : 27\n", + "Inherent dimensionality associated with label 83 : 17\n", + "Inherent dimensionality associated with label 84 : 31\n", + "Inherent dimensionality associated with label 85 : 21\n", + "Inherent dimensionality associated with label 86 : 42\n", + "Inherent dimensionality associated with label 87 : 29\n", + "Inherent dimensionality associated with label 88 : 31\n", + "Inherent dimensionality associated with label 89 : 16\n", + "Inherent dimensionality associated with label 90 : 42\n", + "Inherent dimensionality associated with label 91 : 23\n", + "Inherent dimensionality associated with label 92 : 42\n", + "Inherent dimensionality associated with label 93 : 37\n", + "Inherent dimensionality associated with label 94 : 111\n", + "Inherent dimensionality associated with label 95 : 18\n", + "Inherent dimensionality associated with label 96 : 28\n", + "Inherent dimensionality associated with label 97 : 16\n", + "Inherent dimensionality associated with label 98 : 27\n", + "Inherent dimensionality associated with label 99 : 19\n", + "Inherent dimensionality associated with label 100 : 29\n" + ] + } + ], + "source": [ + "unique_labels=[]\n", + "feature_space=[]\n", + "unique_labels=fd_collection.distinct(\"true_label\")\n", + "for i in range (len(unique_labels)):\n", + " label_fds = [\n", + " np.array(img_fds['fc_fd']).flatten() # get the specific feature model's feature vector\n", + " for img_fds in fd_collection.find({\"true_label\": unique_labels[i]}) # repeat for all images\n", + " ]\n", + " threshold=0.5\n", + " print(\"Inherent dimensionality associated with label\", unique_labels[i], \":\", pca_inherent_dimensionality(label_fds, threshold))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.11" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}