forked from SPC-education/numerics-2022
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.gitignore
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.gitignore
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.idea/
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Task 1/Assignment_1.pdf
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Task 1/Assignment_1.pdf
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Task 1/Assignment_1_ru.pdf
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Task 1/Assignment_1_ru.pdf
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Task 1/Lecture 1.ipynb
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Task 1/Lecture 1.ipynb
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Task 1/convolutions.ipynb
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Task 1/convolutions.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import itertools"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"c = 3"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Generate some data\n",
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"np.random.seed(42)\n",
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"lambda1 = np.random.normal(size=(c, c))\n",
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"lambda2 = np.random.normal(size=(c, c))\n",
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"lambda3 = np.random.normal(size=(c, c))\n",
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"G1 = np.random.normal(size=(c, c, c))\n",
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"G2 = np.random.normal(size=(c, c, c))\n",
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"U = np.random.normal(size=(c, c, c, c))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"def Z_naive(lambda1, lambda2, lambda3, G1, G2, U):\n",
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" c = lambda1.shape[0]\n",
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" Z = np.zeros(shape=(c, c, c, c))\n",
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" for a, b, c, d, e, f, g, h, i, j in itertools.product(*([range(c)]*10)):\n",
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" Z[a, h, i, j] += lambda1[a, b]*lambda2[d, e]*lambda3[g, h]*G1[c, b, d]*G2[f, e, g]*U[i, j, c, f]\n",
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" return Z"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"198 ms ± 30.6 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
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]
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}
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],
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"source": [
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"%%timeit\n",
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"Z = Z_naive(lambda1, lambda2, lambda3, G1, G2, U)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(3, 3, 3, 3)"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"Z = Z_naive(lambda1, lambda2, lambda3, G1, G2, U)\n",
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"Z.shape"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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Task 1/kmeans.ipynb
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Task 1/kmeans.ipynb
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Task 2/A.npy
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Task 2/Assignment_2.pdf
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Task 2/Assignment_2.pdf
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Task 2/Lecture 2.ipynb
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Task 2/Lecture 2.ipynb
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