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alinaselega/numpy_array_notes.ipynb

Created September 10, 2019 19:03
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Notebook Gavin and I made for illustrating numpy data structure operations
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numpy_array_notes.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Numpy Rough Notes",
"version": "0.3.2",
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "code",
"metadata": {
"id": "TiJ8lQQMbKwT",
"colab_type": "code",
"colab": {}
},
"source": [
"def f(x,y):\n",
" x = x+y\n",
" y = x-y\n",
" return (x, y)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "ZRS3xLgibTnR",
"colab_type": "code",
"outputId": "53984608-2d83-4692-a154-eab8f4e58da0",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 221
}
},
"source": [
"import numpy as np\n",
"results = np.zeros((5,2))\n",
"print(results)\n",
"for i in range(5):\n",
" results[i,:] = f(i,i+1)\n",
"print(results)\n",
"np.random.rand(2,2)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"[[0. 0.]\n",
" [0. 0.]\n",
" [0. 0.]\n",
" [0. 0.]\n",
" [0. 0.]]\n",
"[[1. 0.]\n",
" [3. 1.]\n",
" [5. 2.]\n",
" [7. 3.]\n",
" [9. 4.]]\n"
],
"name": "stdout"
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([[0.8143215 , 0.71388998],\n",
" [0.19456093, 0.05751311]])"
]
},
"metadata": {
"tags": []
},
"execution_count": 13
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "c-xK2LbddFWA",
"colab_type": "code",
"outputId": "9a957f0a-ccea-4743-df39-bb9b291b5e5c",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 204
}
},
"source": [
"print(results.shape)\n",
"print(np.concatenate([results, results], 1))\n",
"print(np.hstack([results, results]))"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"(5, 2)\n",
"[[1. 0. 1. 0.]\n",
" [3. 1. 3. 1.]\n",
" [5. 2. 5. 2.]\n",
" [7. 3. 7. 3.]\n",
" [9. 4. 9. 4.]]\n",
"[[1. 0. 1. 0.]\n",
" [3. 1. 3. 1.]\n",
" [5. 2. 5. 2.]\n",
" [7. 3. 7. 3.]\n",
" [9. 4. 9. 4.]]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "hjn7TZIicSg4",
"colab_type": "code",
"outputId": "fed8e2db-83bd-413f-f14b-72a9477560a9",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
}
},
"source": [
"def f(x,y):\n",
" x = x+y\n",
" y = x-y\n",
" return x, (x, y)\n",
"c, (a,b) = f(3,4)\n",
"print(a,b,c)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"7 3 7\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "TozygjKJdjWb",
"colab_type": "code",
"outputId": "fda18a49-e948-48c6-8838-18106c666ee1",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 68
}
},
"source": [
"print([x for x in range(10)])\n",
"l = [x for x in range(4)]\n",
"z = list(zip(l,l))\n",
"print(z)\n",
"print([x for y in z for x in y])"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n",
"[(0, 0), (1, 1), (2, 2), (3, 3)]\n"
],
"name": "stdout"
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"[0, 0, 1, 1, 2, 2, 3, 3]"
]
},
"metadata": {
"tags": []
},
"execution_count": 24
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "yhaxpIhafeDc",
"colab_type": "code",
"outputId": "b570f8f2-e37e-453d-e456-75fc05574b0c",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 102
}
},
"source": [
"a = np.array(z)\n",
"print(a.ravel())\n",
"print(a.flatten())\n",
"print(a.reshape(4*2))\n",
"print(a.reshape(-1))\n",
"a.reshape(2,2,2,-1).shape"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"[0 0 1 1 2 2 3 3]\n",
"[0 0 1 1 2 2 3 3]\n",
"[0 0 1 1 2 2 3 3]\n",
"[0 0 1 1 2 2 3 3]\n"
],
"name": "stdout"
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(2, 2, 2, 1)"
]
},
"metadata": {
"tags": []
},
"execution_count": 41
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "EcL6ZEs6gd68",
"colab_type": "code",
"outputId": "541fe830-341f-4155-fc34-2519077f286a",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 221
}
},
"source": [
"a = np.random.rand(4,4)\n",
"print(a.dot(a))\n",
"print(np.dot(a,a))\n",
"print(a@a)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"[[0.06407937 0.46642787 0.50150555 0.41982632]\n",
" [0.35461308 0.80955616 0.57644224 0.5643094 ]\n",
" [0.34637637 1.33118504 1.21895512 1.08989549]\n",
" [0.60038044 1.86484301 1.59468673 1.47127433]]\n",
"[[0.06407937 0.46642787 0.50150555 0.41982632]\n",
" [0.35461308 0.80955616 0.57644224 0.5643094 ]\n",
" [0.34637637 1.33118504 1.21895512 1.08989549]\n",
" [0.60038044 1.86484301 1.59468673 1.47127433]]\n",
"[[0.06407937 0.46642787 0.50150555 0.41982632]\n",
" [0.35461308 0.80955616 0.57644224 0.5643094 ]\n",
" [0.34637637 1.33118504 1.21895512 1.08989549]\n",
" [0.60038044 1.86484301 1.59468673 1.47127433]]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "iug5R3V8g8IV",
"colab_type": "code",
"outputId": "64ff39e8-85ad-4e82-d0c8-61609577e501",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 85
}
},
"source": [
"a[0,:]\n",
"a[:,0] = a[0,:]\n",
"a"
],
"execution_count": 0,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([[0.13979676, 0.26408563, 0.03151214, 0.3591907 ],\n",
" [0.26408563, 0.43797932, 0.56103178, 0.141232 ],\n",
" [0.03151214, 0.86672734, 0.3486368 , 0.63103214],\n",
" [0.3591907 , 0.79771853, 0.94087495, 0.86981681]])"
]
},
"metadata": {
"tags": []
},
"execution_count": 48
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "BxPgmll5hOlg",
"colab_type": "code",
"outputId": "ce618905-9b9b-4698-80b6-befe6a9d5a35",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 85
}
},
"source": [
"w, h = a.shape\n",
"a = a.ravel()\n",
"for i in np.where(a > 0.1):\n",
" a[i] = - a[i]\n",
"a.reshape(w,h)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([[-0.13979676, -0.26408563, 0.03151214, -0.3591907 ],\n",
" [-0.26408563, -0.43797932, -0.56103178, -0.141232 ],\n",
" [ 0.03151214, -0.86672734, -0.3486368 , -0.63103214],\n",
" [-0.3591907 , -0.79771853, -0.94087495, -0.86981681]])"
]
},
"metadata": {
"tags": []
},
"execution_count": 52
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "vyyEcIUNh_wp",
"colab_type": "code",
"outputId": "f222fad3-c7db-4b92-8a16-798744c897b6",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 181
}
},
"source": [
"assert (a.ravel() - a.reshape(-1)+1).max() < 1e-3\n",
"np.allclose(a,a)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "error",
"ename": "AssertionError",
"evalue": "ignored",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-58-38e7d12f7eb0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m1e-3\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mallclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mAssertionError\u001b[0m: "
]
}
]
}
]
}
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