278 lines
208 KiB
Plaintext
278 lines
208 KiB
Plaintext
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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": 2,
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"id": "c2149513-456d-41aa-bdde-a5c19fe0f8a6",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import numpy as np"
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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": 64,
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"id": "f05e69a7-ac57-4ad5-8b97-363dc07b602f",
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"metadata": {},
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"outputs": [],
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"source": [
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"data = np.load('./np_data/20200212.npy')"
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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": 65,
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"id": "79181a75-e142-497b-b303-8dc57c38d3a9",
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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt"
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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": 66,
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"id": "7438c5e2-58b6-4d52-90d5-c177685b911a",
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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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"(110, 190, 11)"
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]
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},
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"execution_count": 66,
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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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"data.shape"
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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": 68,
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"id": "e23b7e6a-1c4f-4c9c-9ac1-7f78681851b5",
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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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"<matplotlib.image.AxesImage at 0x7f097f5dee50>"
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]
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},
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"execution_count": 68,
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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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"data": {
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"image/png": "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"text/plain": [
|
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"<Figure size 800x800 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"plt.figure(figsize=(8, 8))\n",
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"plt.imshow(data[0:64,0:64,0])"
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]
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},
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{
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"cell_type": "code",
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|
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"execution_count": 10,
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"id": "1e6edd78-b2d5-4f1d-8c7a-5d114e18a68f",
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"metadata": {},
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|
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"outputs": [
|
||
|
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{
|
||
|
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"data": {
|
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|
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"text/plain": [
|
||
|
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"<matplotlib.image.AxesImage at 0x7f09866cda60>"
|
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|
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]
|
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|
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},
|
||
|
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"execution_count": 10,
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|
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"metadata": {},
|
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|
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"output_type": "execute_result"
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|
|
},
|
||
|
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{
|
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|
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"data": {
|
||
|
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"image/png": "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"text/plain": [
|
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|
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"<Figure size 300x200 with 1 Axes>"
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]
|
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},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.figure(figsize=(3, 2))\n",
|
||
|
|
"plt.imshow(data[:,:,2])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 11,
|
||
|
|
"id": "fe5b2135-e1d4-472f-bf5a-1d2c883b9fa6",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x7f09865c00a0>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 300x200 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.figure(figsize=(3, 2))\n",
|
||
|
|
"plt.imshow(data[:,:,3])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 12,
|
||
|
|
"id": "dd8878fe-0ad7-4b4c-87d3-69295eff1a3c",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x7f0986472850>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 12,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 300x200 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.figure(figsize=(3, 2))\n",
|
||
|
|
"plt.imshow(data[:,:,4])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 13,
|
||
|
|
"id": "1632fd53-e8f6-4c0a-b42d-afbc570b7ef6",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x7f098642e610>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 13,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 300x200 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.figure(figsize=(3, 2))\n",
|
||
|
|
"plt.imshow(data[:,:,5])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 14,
|
||
|
|
"id": "a6fe3d2d-5c16-4b5a-bdac-9551e86923a1",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x7f098698d9d0>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 14,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 300x200 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.figure(figsize=(3, 2))\n",
|
||
|
|
"plt.imshow(data[:,:,6])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"id": "767d6d7b-a447-4a6f-b29b-998f5e1902bd",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3 (ipykernel)",
|
||
|
|
"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": "3.8.16"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 5
|
||
|
|
}
|