Merge branch 'phase3_task0a'

This commit is contained in:
Kaushik Narayan R 2023-11-28 23:02:28 -07:00
commit 324330572e
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{
"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": []
}
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