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daxiongshu/gauss_rank_example.ipynb

Last active June 13, 2021 13:43
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gauss_rank_example.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0.55524998, 0.42394212, 0.01200076, 0.13974612, 0.74289723,\n",
" 0.19072088, 0.47061846, 0.61921186, 0.96994115, 0.44076614,\n",
" 0.04326316, 0.33698309, 0.47978816, 0.00819107, 0.63463167,\n",
" 0.03370001, 0.0369827 , 0.84651929, 0.25335235, 0.75172228])"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import cupy as cp\n",
"from cupyx.scipy.special import erfinv\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from scipy.special import erfinv as sp_erfinv\n",
"\n",
"x_gpu = cp.random.rand(20) # input array\n",
"x_cpu = cp.asnumpy(x_gpu)\n",
"x_gpu"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[13 9 1 5 16 6 11 14 19 10 4 8 12 0 15 2 3 18 7 17]\n",
"[13 9 1 5 16 6 11 14 19 10 4 8 12 0 15 2 3 18 7 17]\n"
]
}
],
"source": [
"r_gpu = x_gpu.argsort().argsort() # compute the rank\n",
"print(r_gpu)\n",
"\n",
"r_cpu = x_cpu.argsort().argsort() \n",
"print(r_cpu)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 0.36842105 -0.05263158 -0.89473684 -0.47368421 0.68421053 -0.36842105\n",
" 0.15789474 0.47368421 0.999999 0.05263158 -0.57894737 -0.15789474\n",
" 0.26315789 -0.999999 0.57894737 -0.78947368 -0.68421053 0.89473684\n",
" -0.26315789 0.78947368]\n",
"[ 0.36842105 -0.05263158 -0.89473684 -0.47368421 0.68421053 -0.36842105\n",
" 0.15789474 0.47368421 0.999999 0.05263158 -0.57894737 -0.15789474\n",
" 0.26315789 -0.999999 0.57894737 -0.78947368 -0.68421053 0.89473684\n",
" -0.26315789 0.78947368]\n"
]
}
],
"source": [
"r_gpu = (r_gpu/r_gpu.max()-0.5)*2 # scale to (-1,1)\n",
"epsilon = 1e-6\n",
"r_gpu = cp.clip(r_gpu,-1+epsilon,1-epsilon)\n",
"print(r_gpu)\n",
"\n",
"r_cpu = (r_cpu/r_cpu.max()-0.5)*2 # scale to (-1,1)\n",
"r_cpu = cp.clip(r_cpu,-1+epsilon,1-epsilon)\n",
"print(r_cpu)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 0.3390617 -0.0466774 -1.14541135 -0.44805114 0.70933273 -0.3390617\n",
" 0.14085661 0.44805114 3.45891074 0.0466774 -0.56893556 -0.14085661\n",
" 0.23761485 -3.45891074 0.56893556 -0.8853822 -0.70933273 1.14541135\n",
" -0.23761485 0.8853822 ]\n",
"[ 0.3390617 -0.0466774 -1.14541135 -0.44805114 0.70933273 -0.3390617\n",
" 0.14085661 0.44805114 3.45891074 0.0466774 -0.56893556 -0.14085661\n",
" 0.23761485 -3.45891074 0.56893556 -0.8853822 -0.70933273 1.14541135\n",
" -0.23761485 0.8853822 ]\n"
]
}
],
"source": [
"r_gpu = erfinv(r_gpu) # map to gaussian\n",
"print(r_gpu)\n",
"\n",
"r_cpu = sp_erfinv(r_cpu) # map to gaussian\n",
"print(r_cpu)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"GaussRank transformation\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x360 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"n_bins = 5\n",
"fig, axs = plt.subplots(1, 2, sharey=True, tight_layout=True)\n",
"fig.set_figheight(5)\n",
"fig.set_figwidth(15)\n",
"axs[0].hist(cp.asnumpy(x_gpu), bins=n_bins)\n",
"axs[0].set_title('input',fontsize=15)\n",
"axs[1].hist(cp.asnumpy(r_gpu), bins=n_bins)\n",
"axs[1].set_title('transform',fontsize=15)\n",
"print('GaussRank transformation GPU')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"GaussRank transformation CPU\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x360 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"n_bins = 5\n",
"fig, axs = plt.subplots(1, 2, sharey=True, tight_layout=True)\n",
"fig.set_figheight(5)\n",
"fig.set_figwidth(15)\n",
"axs[0].hist(x_cpu, bins=n_bins)\n",
"axs[0].set_title('input',fontsize=15)\n",
"axs[1].hist(r_cpu, bins=n_bins)\n",
"axs[1].set_title('transform',fontsize=15)\n",
"print('GaussRank transformation CPU')"
]
}
],
"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": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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