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DevinBayly/grid.ipynb

Created June 11, 2021 19:11
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vectorization_experiment
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grid.ipynb
{
"cells": [
{
"cell_type": "markdown",
"id": "aadeb080",
"metadata": {},
"source": [
"# goal to create the poinst of a grid as a x-2 array"
]
},
{
"cell_type": "code",
"execution_count": 75,
"id": "152c0710",
"metadata": {},
"outputs": [],
"source": [
"\n",
"import numpy as np\n",
"xv,yv = np.meshgrid(np.arange(0,10),np.arange(0,10))"
]
},
{
"cell_type": "code",
"execution_count": 76,
"id": "21ecce0e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9],\n",
" [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],\n",
" [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],\n",
" [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],\n",
" [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],\n",
" [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],\n",
" [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],\n",
" [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],\n",
" [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],\n",
" [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])"
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"xv"
]
},
{
"cell_type": "code",
"execution_count": 77,
"id": "2ed6e571",
"metadata": {},
"outputs": [],
"source": [
"def vectWrap(xs,ys):\n",
" return np.array([[xs,ys]])"
]
},
{
"cell_type": "code",
"execution_count": 121,
"id": "02c52064",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20 ms ± 1.6 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
]
}
],
"source": [
"numbers = np.arange(0,100000)\n",
"%timeit [n + 1 for n in numbers]"
]
},
{
"cell_type": "code",
"execution_count": 98,
"id": "f860bba4",
"metadata": {},
"outputs": [],
"source": [
"def add1(v):\n",
" return v + 1"
]
},
{
"cell_type": "code",
"execution_count": 100,
"id": "3ec34ffb",
"metadata": {},
"outputs": [],
"source": [
"vectorizedAdd = np.vectorize(add1)"
]
},
{
"cell_type": "code",
"execution_count": 101,
"id": "236cac9f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])"
]
},
"execution_count": 101,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vectorizedAdd(numbers)"
]
},
{
"cell_type": "code",
"execution_count": 94,
"id": "86b1c58c",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4.47 ms ± 32.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
]
}
],
"source": [
"%timeit np.random.random((500,500)) + np.random.random((500,500))"
]
},
{
"cell_type": "code",
"execution_count": 104,
"id": "383e2b07",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
]
},
"execution_count": 104,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"numbers"
]
},
{
"cell_type": "code",
"execution_count": 122,
"id": "6e8b3741",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"215 µs ± 1.43 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
]
}
],
"source": [
"# return the number and then +1 \n",
"# dream about what the shape is that you want\n",
"# (n) -> (n,2)\n",
"def make2D(p):\n",
" return np.array([p,p+1])\n",
"\n",
"%timeit np.vectorize(make2D,signature=\"(n)->(2,m)\")(numbers).transpose()"
]
},
{
"cell_type": "code",
"execution_count": 123,
"id": "aa0a1532",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"28.5 ms ± 346 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
]
}
],
"source": [
"%timeit [[p,p+1] for p in numbers]"
]
},
{
"cell_type": "code",
"execution_count": 124,
"id": "cc1bbb32",
"metadata": {},
"outputs": [],
"source": [
"xv,yv = np.meshgrid(np.arange(10),np.arange(10))"
]
},
{
"cell_type": "code",
"execution_count": 126,
"id": "8a230d4b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(10, 10)"
]
},
"execution_count": 126,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"xv.shape"
]
},
{
"cell_type": "code",
"execution_count": 131,
"id": "dacc492c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1,\n",
" 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3,\n",
" 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5,\n",
" 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7,\n",
" 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])"
]
},
"execution_count": 131,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# shape that I want is (n,2)\n",
"xv.flatten()[:,None]"
]
},
{
"cell_type": "code",
"execution_count": 133,
"id": "b370b8ea",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"## pretend that the flat arrays are 2D, so just single columns that we are concatenating on\n",
"points = np.concatenate((xv.flatten()[:,None],yv.flatten()[:,None]),axis=1)\n"
]
},
{
"cell_type": "code",
"execution_count": 153,
"id": "be91ef69",
"metadata": {},
"outputs": [],
"source": [
"## for every point we want the next one over x and the next one down\n",
"def extend_point(x,y):\n",
" return np.array([[x,y],[x+1,y],[x,y+1]])"
]
},
{
"cell_type": "code",
"execution_count": 136,
"id": "74ada929",
"metadata": {},
"outputs": [],
"source": [
"def extend_pointxy(xy):\n",
" return np.array([[xy[0] + 1,xy[1]],[xy[0],xy[1]+1]])"
]
},
{
"cell_type": "code",
"execution_count": 143,
"id": "62bc5fb1",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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" [8, 9],\n",
" [9, 9]])"
]
},
"execution_count": 143,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"points"
]
},
{
"cell_type": "code",
"execution_count": 154,
"id": "8a975c01",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"destinations = np.vectorize(extend_point,signature=\"(m),(m)->(t,q,p)\")(points[:,0],points[:,1]).transpose()"
]
},
{
"cell_type": "code",
"execution_count": 158,
"id": "a7e69c78",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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"\n",
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" [ 9, 9, 10]]])"
]
},
"execution_count": 158,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"destinations"
]
},
{
"cell_type": "code",
"execution_count": 180,
"id": "7c501490",
"metadata": {},
"outputs": [],
"source": [
"correct_dest = np.transpose(destinations,axes=(0,2,1))"
]
},
{
"cell_type": "code",
"execution_count": 182,
"id": "94d25b11",
"metadata": {},
"outputs": [
{
"data": {
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" [[ 1, 2],\n",
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"\n",
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"\n",
" [[ 5, 2],\n",
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"\n",
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" [[ 8, 2],\n",
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" [10, 2],\n",
" [ 9, 3]],\n",
"\n",
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" [ 1, 3],\n",
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"\n",
" [[ 1, 3],\n",
" [ 2, 3],\n",
" [ 1, 4]],\n",
"\n",
" [[ 2, 3],\n",
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" [ 2, 4]],\n",
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" [[ 3, 3],\n",
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" [[ 4, 3],\n",
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"\n",
" [[ 5, 3],\n",
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" [ 5, 4]],\n",
"\n",
" [[ 6, 3],\n",
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"\n",
" [[ 7, 3],\n",
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"\n",
" [[ 8, 3],\n",
" [ 9, 3],\n",
" [ 8, 4]],\n",
"\n",
" [[ 9, 3],\n",
" [10, 3],\n",
" [ 9, 4]],\n",
"\n",
" [[ 0, 4],\n",
" [ 1, 4],\n",
" [ 0, 5]],\n",
"\n",
" [[ 1, 4],\n",
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" [ 1, 5]],\n",
"\n",
" [[ 2, 4],\n",
" [ 3, 4],\n",
" [ 2, 5]],\n",
"\n",
" [[ 3, 4],\n",
" [ 4, 4],\n",
" [ 3, 5]],\n",
"\n",
" [[ 4, 4],\n",
" [ 5, 4],\n",
" [ 4, 5]],\n",
"\n",
" [[ 5, 4],\n",
" [ 6, 4],\n",
" [ 5, 5]],\n",
"\n",
" [[ 6, 4],\n",
" [ 7, 4],\n",
" [ 6, 5]],\n",
"\n",
" [[ 7, 4],\n",
" [ 8, 4],\n",
" [ 7, 5]],\n",
"\n",
" [[ 8, 4],\n",
" [ 9, 4],\n",
" [ 8, 5]],\n",
"\n",
" [[ 9, 4],\n",
" [10, 4],\n",
" [ 9, 5]],\n",
"\n",
" [[ 0, 5],\n",
" [ 1, 5],\n",
" [ 0, 6]],\n",
"\n",
" [[ 1, 5],\n",
" [ 2, 5],\n",
" [ 1, 6]],\n",
"\n",
" [[ 2, 5],\n",
" [ 3, 5],\n",
" [ 2, 6]],\n",
"\n",
" [[ 3, 5],\n",
" [ 4, 5],\n",
" [ 3, 6]],\n",
"\n",
" [[ 4, 5],\n",
" [ 5, 5],\n",
" [ 4, 6]],\n",
"\n",
" [[ 5, 5],\n",
" [ 6, 5],\n",
" [ 5, 6]],\n",
"\n",
" [[ 6, 5],\n",
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" [ 6, 6]],\n",
"\n",
" [[ 7, 5],\n",
" [ 8, 5],\n",
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"\n",
" [[ 8, 5],\n",
" [ 9, 5],\n",
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"\n",
" [[ 9, 5],\n",
" [10, 5],\n",
" [ 9, 6]],\n",
"\n",
" [[ 0, 6],\n",
" [ 1, 6],\n",
" [ 0, 7]],\n",
"\n",
" [[ 1, 6],\n",
" [ 2, 6],\n",
" [ 1, 7]],\n",
"\n",
" [[ 2, 6],\n",
" [ 3, 6],\n",
" [ 2, 7]],\n",
"\n",
" [[ 3, 6],\n",
" [ 4, 6],\n",
" [ 3, 7]],\n",
"\n",
" [[ 4, 6],\n",
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" [ 4, 7]],\n",
"\n",
" [[ 5, 6],\n",
" [ 6, 6],\n",
" [ 5, 7]],\n",
"\n",
" [[ 6, 6],\n",
" [ 7, 6],\n",
" [ 6, 7]],\n",
"\n",
" [[ 7, 6],\n",
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" [ 7, 7]],\n",
"\n",
" [[ 8, 6],\n",
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" [ 8, 7]],\n",
"\n",
" [[ 9, 6],\n",
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"\n",
" [[ 0, 7],\n",
" [ 1, 7],\n",
" [ 0, 8]],\n",
"\n",
" [[ 1, 7],\n",
" [ 2, 7],\n",
" [ 1, 8]],\n",
"\n",
" [[ 2, 7],\n",
" [ 3, 7],\n",
" [ 2, 8]],\n",
"\n",
" [[ 3, 7],\n",
" [ 4, 7],\n",
" [ 3, 8]],\n",
"\n",
" [[ 4, 7],\n",
" [ 5, 7],\n",
" [ 4, 8]],\n",
"\n",
" [[ 5, 7],\n",
" [ 6, 7],\n",
" [ 5, 8]],\n",
"\n",
" [[ 6, 7],\n",
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" [ 6, 8]],\n",
"\n",
" [[ 7, 7],\n",
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"\n",
" [[ 8, 7],\n",
" [ 9, 7],\n",
" [ 8, 8]],\n",
"\n",
" [[ 9, 7],\n",
" [10, 7],\n",
" [ 9, 8]],\n",
"\n",
" [[ 0, 8],\n",
" [ 1, 8],\n",
" [ 0, 9]],\n",
"\n",
" [[ 1, 8],\n",
" [ 2, 8],\n",
" [ 1, 9]],\n",
"\n",
" [[ 2, 8],\n",
" [ 3, 8],\n",
" [ 2, 9]],\n",
"\n",
" [[ 3, 8],\n",
" [ 4, 8],\n",
" [ 3, 9]],\n",
"\n",
" [[ 4, 8],\n",
" [ 5, 8],\n",
" [ 4, 9]],\n",
"\n",
" [[ 5, 8],\n",
" [ 6, 8],\n",
" [ 5, 9]],\n",
"\n",
" [[ 6, 8],\n",
" [ 7, 8],\n",
" [ 6, 9]],\n",
"\n",
" [[ 7, 8],\n",
" [ 8, 8],\n",
" [ 7, 9]],\n",
"\n",
" [[ 8, 8],\n",
" [ 9, 8],\n",
" [ 8, 9]],\n",
"\n",
" [[ 9, 8],\n",
" [10, 8],\n",
" [ 9, 9]],\n",
"\n",
" [[ 0, 9],\n",
" [ 1, 9],\n",
" [ 0, 10]],\n",
"\n",
" [[ 1, 9],\n",
" [ 2, 9],\n",
" [ 1, 10]],\n",
"\n",
" [[ 2, 9],\n",
" [ 3, 9],\n",
" [ 2, 10]],\n",
"\n",
" [[ 3, 9],\n",
" [ 4, 9],\n",
" [ 3, 10]],\n",
"\n",
" [[ 4, 9],\n",
" [ 5, 9],\n",
" [ 4, 10]],\n",
"\n",
" [[ 5, 9],\n",
" [ 6, 9],\n",
" [ 5, 10]],\n",
"\n",
" [[ 6, 9],\n",
" [ 7, 9],\n",
" [ 6, 10]],\n",
"\n",
" [[ 7, 9],\n",
" [ 8, 9],\n",
" [ 7, 10]],\n",
"\n",
" [[ 8, 9],\n",
" [ 9, 9],\n",
" [ 8, 10]],\n",
"\n",
" [[ 9, 9],\n",
" [10, 9],\n",
" [ 9, 10]]])"
]
},
"execution_count": 182,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"correct_dest"
]
},
{
"cell_type": "code",
"execution_count": 183,
"id": "85509663",
"metadata": {},
"outputs": [],
"source": [
"np.save(\"correct_10x10grid.npy\",correct_dest)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "656f6ac6",
"metadata": {},
"outputs": [],
"source": [
"np.to_file()"
]
},
{
"cell_type": "code",
"execution_count": 160,
"id": "75f6db91",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(100, 2, 3)"
]
},
"execution_count": 160,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"destinations.shape"
]
},
{
"cell_type": "code",
"execution_count": 162,
"id": "3caf1716",
"metadata": {},
"outputs": [
{
"ename": "ValueError",
"evalue": "inconsistent size for core dimension '100': 3 vs 100",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-162-88a6c79e5ece>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvectorize\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvectorizeTranspose\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msignature\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"(100,2,3)->(100,3,2)\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdestinations\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32mc:\\users\\ohmeg\\miniconda3\\lib\\site-packages\\numpy\\lib\\function_base.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 2111\u001b[0m \u001b[0mvargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mextend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0m_n\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0m_n\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mnames\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2112\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2113\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_vectorize_call\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mvargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2114\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2115\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_get_ufunc_and_otypes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32mc:\\users\\ohmeg\\miniconda3\\lib\\site-packages\\numpy\\lib\\function_base.py\u001b[0m in \u001b[0;36m_vectorize_call\u001b[1;34m(self, func, args)\u001b[0m\n\u001b[0;32m 2185\u001b[0m \u001b[1;34m\"\"\"Vectorized call to `func` over positional `args`.\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2186\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msignature\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2187\u001b[1;33m \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_vectorize_call_with_signature\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2188\u001b[0m \u001b[1;32melif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2189\u001b[0m \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32mc:\\users\\ohmeg\\miniconda3\\lib\\site-packages\\numpy\\lib\\function_base.py\u001b[0m in \u001b[0;36m_vectorize_call_with_signature\u001b[1;34m(self, func, args)\u001b[0m\n\u001b[0;32m 2240\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0moutputs\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2241\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcore_dims\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresults\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput_core_dims\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2242\u001b[1;33m \u001b[0m_update_dim_sizes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdim_sizes\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcore_dims\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2243\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2244\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0motypes\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32mc:\\users\\ohmeg\\miniconda3\\lib\\site-packages\\numpy\\lib\\function_base.py\u001b[0m in \u001b[0;36m_update_dim_sizes\u001b[1;34m(dim_sizes, arg, core_dims)\u001b[0m\n\u001b[0;32m 1849\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mdim\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdim_sizes\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1850\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0msize\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mdim_sizes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mdim\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1851\u001b[1;33m raise ValueError(\n\u001b[0m\u001b[0;32m 1852\u001b[0m \u001b[1;34m'inconsistent size for core dimension %r: %r vs %r'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1853\u001b[0m % (dim, size, dim_sizes[dim]))\n",
"\u001b[1;31mValueError\u001b[0m: inconsistent size for core dimension '100': 3 vs 100"
]
}
],
"source": [
"def vectorizeTranspose(p):\n",
" return p.transpose()\n",
"\n",
"np.vectorize(vectorizeTranspose,signature=\"(100,2,3)->(m,n,p)\")(destinations)"
]
},
{
"cell_type": "code",
"execution_count": 166,
"id": "d60d5b43",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Collecting Pillow\n",
" Using cached Pillow-8.2.0-cp39-cp39-win_amd64.whl (2.2 MB)\n",
"Installing collected packages: Pillow\n",
"Successfully installed Pillow-8.2.0\n",
"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"source": [
"pip install Pillow"
]
},
{
"cell_type": "code",
"execution_count": 171,
"id": "2bf55395",
"metadata": {},
"outputs": [],
"source": [
"randImage =( np.random.random((100,100,3))*255).astype(\"float32\")"
]
},
{
"cell_type": "code",
"execution_count": 172,
"id": "c051a699",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "Cannot handle this data type: (1, 1, 3), <f4",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32mc:\\users\\ohmeg\\miniconda3\\lib\\site-packages\\PIL\\Image.py\u001b[0m in \u001b[0;36mfromarray\u001b[1;34m(obj, mode)\u001b[0m\n\u001b[0;32m 2771\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2772\u001b[1;33m \u001b[0mmode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrawmode\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_fromarray_typemap\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mtypekey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2773\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mKeyError\u001b[0m: ((1, 1, 3), '<f4')",
"\nThe above exception was the direct cause of the following exception:\n",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-172-5c62d1c6428c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mImage\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfromarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrandImage\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32mc:\\users\\ohmeg\\miniconda3\\lib\\site-packages\\PIL\\Image.py\u001b[0m in \u001b[0;36mfromarray\u001b[1;34m(obj, mode)\u001b[0m\n\u001b[0;32m 2772\u001b[0m \u001b[0mmode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrawmode\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_fromarray_typemap\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mtypekey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2773\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2774\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Cannot handle this data type: %s, %s\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mtypekey\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2775\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2776\u001b[0m \u001b[0mrawmode\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmode\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mTypeError\u001b[0m: Cannot handle this data type: (1, 1, 3), <f4"
]
}
],
"source": [
"Image.fromarray(randImage)"
]
},
{
"cell_type": "code",
"execution_count": 173,
"id": "43ae4bfa",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAAIAAABkCAIAAAAjeXY0AAAAQklEQVR4nO3OMRGAQBDF0LAu8lcG/h2cjdUBGpiDjjLNm4CAZQQqBnhcByLnplKdTnZfqtOa/+WTF5C15gVl5tpUbqf6JVwEe17hAAAAAElFTkSuQmCC\n",
"text/plain": [
"<PIL.Image.Image image mode=RGB size=2x100 at 0x24EB98B7C40>"
]
},
"execution_count": 173,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from PIL import Image\n",
"norm_dest = destinations/10*255\n",
"\n",
"Image.fromarray(norm_dest.astype(\"uint8\"))"
]
},
{
"cell_type": "code",
"execution_count": 176,
"id": "c504a340",
"metadata": {},
"outputs": [],
"source": [
"np.save(\"10x10grid.npy\",destinations)"
]
},
{
"cell_type": "code",
"execution_count": 175,
"id": "e1ca4635",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(100, 2, 3)"
]
},
"execution_count": 175,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"norm_dest.shape"
]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "3f812689",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(40000, 2)"
]
},
"execution_count": 64,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"points.shape"
]
},
{
"cell_type": "markdown",
"id": "0ff7856d",
"metadata": {},
"source": [
"create a 400000 by 3 x 2, with the original point in the 0 of the second dimension"
]
},
{
"attachments": {
"image.png": {
"image/png": 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"
}
},
"cell_type": "markdown",
"id": "49ec8dc7",
"metadata": {},
"source": [
"mental gymnastics for a moment ![image.png](attachment:image.png)"
]
},
{
"cell_type": "code",
"execution_count": 74,
"id": "c97276ae",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[[ 0, 0],\n",
" [ 1, 0],\n",
" [ 0, 1]],\n",
"\n",
" [[ 1, 0],\n",
" [ 2, 1],\n",
" [ 0, 1]],\n",
"\n",
" [[ 2, 0],\n",
" [ 3, 2],\n",
" [ 0, 1]],\n",
"\n",
" ...,\n",
"\n",
" [[197, 199],\n",
" [198, 197],\n",
" [199, 200]],\n",
"\n",
" [[198, 199],\n",
" [199, 198],\n",
" [199, 200]],\n",
"\n",
" [[199, 199],\n",
" [200, 199],\n",
" [199, 200]]])"
]
},
"execution_count": 74,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.concatenate((points[:,None,:],dest_aligned),axis = 1)"
]
},
{
"cell_type": "code",
"execution_count": 72,
"id": "4dccedfb",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(40000, 1, 2)"
]
},
"execution_count": 72,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"points[:,None,:].shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c13f4c75",
"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": "3.9.1"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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