EEBD_AI
/
MAE_ATMO
11
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
MAE_ATMO/论文绘图.ipynb

1065 lines
538 KiB
Plaintext
Raw Permalink Normal View History

update code
2024-11-21 14:02:33 +08:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 139,
"id": "eea46721-2898-411d-a80c-a908030c6977",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import geopandas as gpd\n",
"import pandas as pd\n",
"from shapely.geometry import Point, Polygon"
]
},
{
"cell_type": "code",
"execution_count": 140,
"id": "17f63fe2-e5f6-48a3-94f8-74ef660b2868",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7f8391dc35b0>"
]
},
"execution_count": 140,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ori_data = np.load('./np_data/20200220.npy')\n",
"data = ori_data[:,:,0].copy()\n",
"plt.imshow(data, cmap='RdYlGn_r')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "326b7241-afc8-43ce-b15e-3154fbeaa2d6",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 10,
"id": "d9248def-25ef-4ae9-8425-d3a4e851afda",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7fea807c26d0>"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data = ori_data[:,:,0].copy()\n",
"plt.imshow(data)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "d41b956d-03af-46df-8ec1-ef9fa5503ccf",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 640x480 with 0 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.clf()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "bef156fa-d565-4ce8-ab33-4da917342eb1",
"metadata": {},
"outputs": [],
"source": [
"# 创建一个190x110的经纬度网格\n",
"lon_min, lat_min = 114.025, 33.525\n",
"lon_max, lat_max = 123.475, 38.975\n",
"lon_step = (lon_max - lon_min) / 190\n",
"lat_step = (lat_max - lat_min) / 110"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "1eb83907-4dff-497a-b481-3624a062a134",
"metadata": {},
"outputs": [],
"source": [
"lons = np.linspace(lon_min, lon_max, 190)\n",
"lats = np.linspace(lat_min, lat_max, 110)\n",
"lon_grid, lat_grid = np.meshgrid(lons, lats)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "9bf5b19f-0776-4562-a194-039e10e4c5e3",
"metadata": {
"scrolled": true,
"tags": []
},
"outputs": [],
"source": [
"# 初始化一个空的GeoDataFrame\n",
"gdf = gpd.GeoDataFrame(columns=['geometry', 'value'])\n",
"\n",
"# 将网格转换为多边形并添加到GeoDataFrame\n",
"for i in range(lat_grid.shape[0] - 1):\n",
" for j in range(lat_grid.shape[1] - 1):\n",
" polygon = Polygon([\n",
" (lon_grid[i, j], lat_grid[i, j]),\n",
" (lon_grid[i, j+1], lat_grid[i, j+1]),\n",
" (lon_grid[i+1, j+1], lat_grid[i+1, j+1]),\n",
" (lon_grid[i+1, j], lat_grid[i+1, j])\n",
" ])\n",
" # 使用concat而不是append\n",
" gdf = pd.concat([gdf, gpd.GeoDataFrame({'geometry': [polygon], 'value': [data[i, j]]})], ignore_index=True)\n"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "68817ef0-79d8-49e6-ada4-152f746d5e3c",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_7233/3979395723.py:2: FutureWarning: The geopandas.dataset module is deprecated and will be removed in GeoPandas 1.0. You can get the original 'naturalearth_lowres' data from https://www.naturalearthdata.com/downloads/110m-cultural-vectors/.\n",
" world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))\n"
]
}
],
"source": [
"# 读取世界地图\n",
"world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "8157b80b-a758-44f2-9739-62439b254786",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1000x1000 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n",
"world.plot(ax=ax, color='white', edgecolor='black')\n",
"\n",
"# 绘制网格\n",
"gdf.plot(ax=ax, column='value', legend=False, cmap='RdYlGn_r')\n",
"# 设置地图范围\n",
"ax.set_xlim(lon_min, lon_max)\n",
"ax.set_ylim(lat_min, lat_max)\n",
"plt.savefig('./origin.png', bbox_inches='tight')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "f98c3cb6-a13e-4b59-93f7-17706c5ef975",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "93c8c793-10bd-4e8c-aab8-7317103979b1",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"show_list = os.listdir('./out_mat/96/train/')"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "79d57a73-909c-4c69-aa1a-82c04233b50e",
"metadata": {},
"outputs": [],
"source": [
"val_list = [x for x in show_list if '20201106' in x]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b6f213fe-5f61-4c32-a475-25d421b7f440",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 68,
"id": "0306308d-d578-4114-9bfb-e2ffc2e87219",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 640x480 with 0 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for i, p in enumerate(val_list):\n",
" if i >= 10:\n",
" break\n",
" val_data = np.load(f'./out_mat/96/train/{p}')[:,:,0]\n",
" plt.imshow(val_data, cmap='RdYlGn_r')\n",
" plt.savefig(f'./figures/full/{i}.png', bbox_inches='tight')\n",
" plt.clf()"
]
},
{
"cell_type": "code",
"execution_count": 69,
"id": "0e9bf439-bc45-4ffd-823c-153e0361d360",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['20200503-439.jpg',\n",
" '20201212-1053.jpg',\n",
" '20200416-1333.jpg',\n",
" '20200505-626.jpg',\n",
" '20200516-624.jpg']"
]
},
"execution_count": 69,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"masks = [x for x in os.listdir('./out_mat/96/mask/30/')][:5]\n",
"masks"
]
},
{
"cell_type": "code",
"execution_count": 70,
"id": "4a69e0ab-cf00-402e-84f6-821ea5edd1e2",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['20201106-859.npy',\n",
" '20201106-866.npy',\n",
" '20201106-1088.npy',\n",
" '20201106-1142.npy',\n",
" '20201106-1238.npy']"
]
},
"execution_count": 70,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"new_miss = val_list[5:10]\n",
"new_miss"
]
},
{
"cell_type": "code",
"execution_count": 71,
"id": "cc86d982-d861-490c-9e5a-b94e9d18d9b1",
"metadata": {},
"outputs": [],
"source": [
"import cv2"
]
},
{
"cell_type": "code",
"execution_count": 91,
"id": "847c5cce-8109-48e1-8041-7132e5f9c3b1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 640x480 with 0 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for img, msk in zip(new_miss, masks):\n",
" img_np = np.load(f'./out_mat/96/train/{img}')[:,:,0]\n",
" msk_np = cv2.cvtColor(cv2.imread(f'./out_mat/96/mask/30/{msk}'), cv2.COLOR_BGR2GRAY)\n",
" msk_np_2 = msk_np.astype(float)\n",
" msk_np_2[msk_np_2 == 0] = np.nan\n",
" miss = img_np * msk_np_2\n",
" plt.imshow(miss, cmap='RdYlGn_r')\n",
" plt.savefig(f'./figures/miss/{img}.png', bbox_inches='tight')\n",
" plt.clf()\n",
" plt.imshow(msk_np_2, cmap='gray')\n",
" plt.savefig(f'./figures/mask/{img}.png', bbox_inches='tight')\n",
" plt.clf()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "3aab440a-32d8-4ba3-a729-daebaef80edd",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"data_list = [x for x in os.listdir('./np_data/') if 'npy' in x]\n",
"dates = list()\n",
"miss_rate_list = list()\n",
"for path in data_list:\n",
" dates.append(path.split('.')[0].strip())\n",
" data = np.load(f\"./np_data/{path}\")[:,:,0]\n",
" miss_rate = (np.isnan(data) * 1).sum() / (data.shape[0] * data.shape[1])\n",
" miss_rate_list.append(miss_rate)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "904c5576-cdfa-4dc9-b824-21bef037fc7d",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>date</th>\n",
" <th>rate</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>20201116</td>\n",
" <td>0.14933</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>20200120</td>\n",
" <td>0.054163</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>20200724</td>\n",
" <td>0.124641</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>20200622</td>\n",
" <td>0.364641</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>20200711</td>\n",
" <td>0.896986</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" date rate\n",
"0 20201116 0.14933\n",
"1 20200120 0.054163\n",
"2 20200724 0.124641\n",
"3 20200622 0.364641\n",
"4 20200711 0.896986"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"miss_df = pd.DataFrame([dates, miss_rate_list]).T\n",
"miss_df.columns = ['date', 'rate']\n",
"miss_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "1efb840f-b749-41fa-96d8-35a2f9aa1b9e",
"metadata": {},
"outputs": [],
"source": [
"miss_df.date = pd.to_datetime(miss_df.date)\n",
"miss_df['month'] = miss_df.date.apply(lambda x: x.month)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "45ddaec0-d868-4946-9d6a-e30246b2fdd1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"month\n",
"1 0.496714\n",
"2 0.445747\n",
"3 0.246096\n",
"4 0.232876\n",
"5 0.349770\n",
"6 0.427705\n",
"7 0.523877\n",
"8 0.510536\n",
"9 0.295989\n",
"10 0.393019\n",
"11 0.345657\n",
"12 0.313314\n",
"Name: rate, dtype: float64"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"miss_df.groupby('month')['rate'].mean()"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "5b7fea10-889f-448f-b1c4-7900ad3fc202",
"metadata": {},
"outputs": [],
"source": [
"import os"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "72fc40d6-fd5a-4709-9ab9-f64cd3c9db1d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"4245"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(os.listdir('./out_mat/96/mask/50/'))"
]
},
{
"cell_type": "code",
"execution_count": 69,
"id": "4623918e-1970-4fc4-8914-23357eb3bbb6",
"metadata": {},
"outputs": [],
"source": [
"with open('./POMINO_data/POMINO_v2.1_daily_20200220.txt', 'r', encoding='utf-8') as fr:\n",
" d = fr.readlines()\n",
" dd = [float(x.strip()) for x in d]\n",
" vcd = np.zeros([160,280])\n",
" ct = 0\n",
" for j in range(280):\n",
" for i in range(160):\n",
" vcd[i,j] = dd[ct]\n",
" ct += 1\n",
" if i == 159:\n",
" break"
]
},
{
"cell_type": "code",
"execution_count": 70,
"id": "b513f7b7-41e9-461d-9e0d-daf985014c10",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7fea72102820>"
]
},
"execution_count": 70,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(vcd)"
]
},
{
"cell_type": "code",
"execution_count": 106,
"id": "1a285b44-13a9-47c4-873b-d832d54c623e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(110, 190)"
]
},
"execution_count": 106,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"img1.shape"
]
},
{
"cell_type": "code",
"execution_count": 129,
"id": "1f1f9fbe-66a6-4f23-980b-2dd74867419c",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"img1 = np.load('./np_data/20200320.npy')[:,:,0]\n",
"data = img1[:96, -96:].copy()\n",
"plt.imshow(data, cmap='RdYlGn_r')\n",
"plt.xticks([])\n",
"plt.yticks([])\n",
"plt.savefig('./figures/fig4-ori_and_miss/a.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 130,
"id": "1e015fff-aaaa-44eb-846c-34079ea633fe",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(np.isnan(data) * 1, cmap='gray')\n",
"plt.xticks([])\n",
"plt.yticks([])\n",
"plt.savefig('./figures/fig4-ori_and_miss/a-mask.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 137,
"id": "f86a7a59-4b71-4f39-ae7f-6394daae5308",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"img2 = np.load('./np_data/20200621.npy')\n",
"data = img2[:,:,0][110-96:110, 20:116].copy()\n",
"plt.imshow(data, cmap='RdYlGn_r')\n",
"plt.xticks([])\n",
"plt.yticks([])\n",
"plt.savefig('./figures/fig4-ori_and_miss/b.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 138,
"id": "d45ac436-0e5b-4860-a763-265b84914b7d",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(np.isnan(data) * 1, cmap='gray')\n",
"plt.xticks([])\n",
"plt.yticks([])\n",
"plt.savefig('./figures/fig4-ori_and_miss/b-mask.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 133,
"id": "02b56763-e1f5-4091-a708-4d11dbb2ad15",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"img3 = np.load('./np_data/20200922.npy')\n",
"data = img3[:,:,0][10:106, :96].copy()\n",
"plt.imshow(data, cmap='RdYlGn_r')\n",
"plt.xticks([])\n",
"plt.yticks([])\n",
"plt.savefig('./figures/fig4-ori_and_miss/c.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 134,
"id": "45053672-473c-4001-acad-3572f68b3225",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(np.isnan(data) * 1, cmap='gray')\n",
"plt.xticks([])\n",
"plt.yticks([])\n",
"plt.savefig('./figures/fig4-ori_and_miss/c-mask.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 135,
"id": "40cfca7f-21ed-49b4-aedd-afc0d2ba8b10",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"img4 = np.load('./np_data/20201221.npy')\n",
"data = img4[:,:,0][:96, -96:].copy()\n",
"plt.imshow(data, cmap='RdYlGn_r')\n",
"plt.xticks([])\n",
"plt.yticks([])\n",
"plt.savefig('./figures/fig4-ori_and_miss/d.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 136,
"id": "264fc468-fc1f-4298-923a-4e0174c052d8",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAGFCAYAAAASI+9IAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy88F64QAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAI1klEQVR4nO3dwW7aWhRAUVJ1GjGP2v//sEqZB+bhzfZLkQo4tsE2a0kZJSEGqm7de2z8cjqdTjsA2O12Px59AAAshygAEFEAIKIAQEQBgIgCABEFAPLzlh/6/Pzcvb+/715fX3cvLy9zHxMAEzudTrvj8bh7e3vb/fjx7/XATVF4f3/f/f79e7KDA+Ax/vz5s/v169c/v3/T9tHr6+tkBwTA41z7//ymKNgyAtiGa/+fGzQDEFEAIKIAQEQBgIgCALnpOgWAZ3Z+L7Itn5FppQBARAGAiAIAMVMAnt75zGDMz6993mClAEBEAYDYPgKeztDtontuCV07tkvHMsWps1YKAEQUAIgoABAzBWCThs4N7mXscQ35/a8/ezgcdvv9/urvWCkAEFEAIKIAQMwUAK4Yso8/9TUNQ65LmIKVAgARBQAiCgDETAFYhaVed3Bu7HGOmUlMMc+wUgAgogBARAGAmCkAi7CWmcG93ft1sVIAIKIAQEQBgJgpACzImHs0T8FKAYCIAgARBQAiCgBEFACIKAAQp6QCd+OjLJbPSgGAiAIAEQUAYqYAzMYMYX2sFACIKAAQUQAgosCinU6nv75YNu/Xsnx9Lz4+Pm76HVEAIKIAQEQBgLhOgUWb+9aDuJZgbeZ+v6wUAIgoABBRACBmCmzW+d7r2PnE1I+39uNgm6wUAIgoABBRACBmCmzW1DOEod8fcixjzj13nQFTslIAIKIAQEQBgJgpwD+czwHs+/MMrBQAiCgAEFEAIKIAQEQBgIgCAHFKKnzT11NWnXK6bHN+zMjWWCkAEFEAIKIAQMwU4EaX9qXtWc9v6GvsNqXfY6UAQEQBgIgCADFTgDswcxhu6EzADGEaVgoARBQAiCgAEDMFWKBL++Nrmj8MuaXpnDOBNb1mj2alAEBEAYCIAgAxU4AFGLKffm2ffs5rIsbu+9/zWgJzhO+xUgAgogBAbB/Byq1pS+ee3C71e6wUAIgoABBRACBmCvBktjpDuGToc37mGYSVAgARBQAiCgDETAHgzDPPIKwUAIgoABBRACCiAEBEAYCIAgARBQDiOgWAkS7du2HsZ03d+xoIKwUAIgoARBQAiJkCwITWfr8KKwUAIgoARBQAiJkCwEZ9Z75hpQBARAGA2D4CWLDzLaC5P/bCSgGAiAIAEQUAIgoAK/Ly8tLXNafTqa+Pj4+bHl8UAIgoABBRACCuUwD+8vU8+KHnyE95Tv3aP4J6Lq5TAOBuRAGAiAIAMVOAJ3dpj3ro/vWU+91D5xdMw0oBgIgCABEFAGKmAE9m7vPc7+X8eTzLjOHr85zjvbRSACCiAEBEAYCYKcDGzfn5Q0Mf+9LjDZ0RbGU2sjRWCgBEFACIKAAQMwXYuCnvcTD2b0/1s9/5eW5jpQBARAGA2D4C/jLnlg/TmmNr0EoBgIgCABEFAGKmAE/GHIBLrBQAiCgAEFEAIGYKACvldpwAzEoUAIgoABAzBYAVuTRHmOKzkKwUAIgoABBRACBmCgArMvdnV1kpABBRACCiAEBEAYCIAgARBQAiCgDEdQoAG/WdaxqsFACIKAAQUQAgogBARAGAiAIAEQUAIgoARBQAiCgAEFEAIKIAQEQBgIgCABEFACIKAEQUAIgoABBRACCiAEBEAYCIAgARBQAiCgBEFACIKAAQUQAgogBARAGAiAIAEQUAIgoARBQAiCgAEFEAIKIAQEQBgIgCABEFACIKAEQUAIgoABBRACCiAEBEAYCIAgARBQAiCgBEFACIKAAQUQAgogBARAGAiAIAEQUAIgoARBQAiCgAEFEAIKIAQEQBgIgCABEFACIKAEQUAIgoABBRACCiAEBEAYCIAgARBQAiCgBEFACIKAAQUQAgogBARAGAiAIAEQUAIgoARBQAiCgAEFEAIKIAQEQBgIgCABEFACIKAEQUAIgoABBRACCiAEBEAYCIAgARBQAiCgBEFACIKAAQUQAgogBARAGAiAIAEQUAIgoARBQAiCgAkJ+PPgBguU6n08Xvv7y8bPJvT2ltz8NKAYCIAgARBQBipgB825z75Uvba/+ua89jaTMHKwUAIgoARBQAiJkC8E9D97PP98cv7ZdvZWYwt/PXcO7XzUoBgIgCABEFAGKmADzEvffKl+r8eV+7buHr9+d4zawUAIgoABBRACBmCsBkhuyPj90PH/OZQUueZzz6WKwUAIgoABBRACBmCsBs7rk/PuRvPXrffsmsFACIKAAQUQAgZgrAIl27DmHKxzZj+J+VAgARBQBi+wiYzJBtmam3h8Y8nu2k/1kpABBRACCiAEDMFHgac57iuGZT7p8/8178VlgpABBRACCiAEDMFNiUrc4N7nm+/5TmvB3nmL899e9OeevPMbcZnYKVAgARBQAiCgDETIFVW/J++r2M3aPeqqV+7tKU84o5WCkAEFEAIKIAQMwUYAXGnO9//v3zx3rUvQTWdv7+o1x6nYbMJw6Hw26/31/9OSsFACIKAEQUAIiZAqt2bb/8GdzznPs5X++xj3XP9/6Rn0U19+NbKQAQUQAgogBAzBTYlLXed2CptnLu/9BrIMY877XPuawUAIgoABDbRzyNObdC1rZFwLS29P5bKQAQUQAgogBAzBRgAmPnFUvdk17qcQ31yNtvPtJ3/l1aKQAQUQAgogBAzBRgAcbeipJpPfPrbaUAQEQBgIgCADFTgJXb6jUSjPf1vT0cDrv9fn/1d6wUAIgoABBRACBmCrACW7ktJstnpQBARAGAiAIAMVOAJ3fPeYVrIpbPSgGAiAIAEQUAYqYAPMT5LMO8YRmsFACIKAAQ20fA3fi4juWzUgAgogBARAGAmCkAi+AU1el9Z4ZjpQBARAGAiAIAEQUAIgoARBQAyE2npDo1DLi3w+Hw6EPYpGv/n98UhePxOMnBANxqv98/+hA26Xg8XnxtX043LAM+Pz937+/vu9fXVx9oBbBCp9Npdzwed29vb7sfP/49ObgpCgA8B4NmACIKAEQUAIgoABBRACCiAEBEAYD8B4CL/jqYMJxeAAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(np.isnan(data) * 1, cmap='gray')\n",
"plt.xticks([])\n",
"plt.yticks([])\n",
"plt.savefig('./figures/fig4-ori_and_miss/d-mask.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 166,
"id": "605f263e-1ef3-4fa7-be74-142c6918d682",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ori_data_16 = np.load('./np_data/20200220.npy')\n",
"data = ori_data_16[25:55,65:95,0].copy()\n",
"plt.imshow(data, cmap='RdYlGn_r')\n",
"plt.gca().axis('off') # 获取当前坐标轴并关闭\n",
"plt.savefig('./figures/fig1/color.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 167,
"id": "b7c0d144-b0f4-427c-b07c-3bb4d4d4be96",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.clf()\n",
"plt.imshow(data, cmap='gray')\n",
"plt.gca().axis('off') # 获取当前坐标轴并关闭\n",
"plt.savefig('./figures/fig1/gray.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 158,
"id": "7cfe14e9-1f71-4db2-bedf-4ce036c7496a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(30, 30)"
]
},
"execution_count": 158,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.shape"
]
},
{
"cell_type": "code",
"execution_count": 164,
"id": "d2e09df0-a482-4c03-aa3a-bbcca4024c45",
"metadata": {},
"outputs": [],
"source": [
"pd.DataFrame(data.astype(int)).to_csv('./numeric.csv', index=False)"
]
},
{
"cell_type": "code",
"execution_count": 161,
"id": "2bde0a43-b1ab-4bb4-b77a-6b74373127a3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"8 7 7 7 7 7 6 6 8 9 9 10 10 10 10 9 10 9 9 9 8 8 9 9 8 9 9 9 9 10 \n",
"8 8 7 7 7 7 7 7 8 9 9 10 10 10 9 9 9 10 10 9 9 9 9 10 9 9 10 10 10 10 \n",
"8 8 7 8 8 8 8 8 8 8 9 9 10 10 9 9 9 9 10 9 9 9 10 10 10 10 10 11 12 13 \n",
"9 9 10 9 8 9 9 9 9 9 9 9 9 10 9 9 9 9 8 9 9 9 10 10 10 11 12 14 15 16 \n",
"10 9 9 10 9 10 11 11 10 11 12 10 11 11 11 10 9 9 8 9 9 9 10 12 12 14 15 17 18 20 \n",
"8 8 8 10 10 11 12 11 11 13 12 10 11 12 12 11 10 9 8 9 9 10 12 15 16 17 19 22 25 24 \n",
"8 8 8 9 9 10 11 11 11 13 11 11 11 13 14 13 12 11 10 10 10 12 15 16 18 19 20 21 21 20 \n",
"7 8 9 9 9 9 10 10 11 10 11 12 16 17 18 19 16 15 13 12 14 15 15 15 16 16 17 18 18 16 \n",
"7 8 8 9 9 10 10 10 10 11 12 13 16 19 22 25 25 22 16 18 19 18 15 15 15 15 15 15 15 14 \n",
"8 8 7 8 9 10 12 11 10 11 13 13 15 21 22 24 25 23 19 21 22 19 16 15 14 13 13 12 12 12 \n",
"10 9 7 8 8 9 10 10 10 11 11 12 15 19 21 22 24 23 22 20 18 16 14 13 12 12 11 11 12 13 \n",
"9 8 8 9 8 9 10 11 11 12 12 14 17 19 21 20 22 23 23 19 16 15 14 12 12 12 12 11 12 12 \n",
"10 10 10 10 11 11 11 12 13 14 17 21 24 25 22 22 24 26 25 20 18 19 15 13 12 12 13 13 13 13 \n",
"10 10 10 12 12 13 13 14 15 17 21 25 28 28 26 25 28 32 27 20 15 17 17 16 15 13 13 13 13 13 \n",
"10 9 9 13 14 15 15 16 18 22 25 28 31 32 32 28 27 24 20 17 15 16 18 18 17 15 14 14 13 13 \n",
"10 10 12 14 16 17 17 23 27 30 29 30 33 37 35 30 27 23 18 15 15 16 17 17 17 18 17 17 14 13 \n",
"10 11 10 12 15 18 25 33 43 41 36 36 36 37 36 35 29 22 19 17 15 15 16 17 18 19 19 18 16 14 \n",
"12 13 11 13 15 20 30 39 47 46 39 30 28 30 34 39 31 25 21 18 17 17 17 17 17 17 17 15 16 14 \n",
"15 14 14 14 16 20 26 38 36 31 26 22 20 21 30 40 36 27 21 20 18 17 17 16 16 15 13 13 13 13 \n",
"16 15 15 15 16 17 17 18 19 20 17 15 13 16 24 28 30 22 18 17 15 15 15 15 15 14 14 14 14 13 \n",
"18 17 16 16 16 14 12 10 10 13 11 10 10 12 15 18 18 16 13 13 12 11 12 13 15 14 14 15 17 16 \n",
"18 16 17 16 15 10 8 8 8 9 10 9 10 11 12 12 11 10 8 10 9 8 8 11 13 14 14 16 17 16 \n",
"15 12 12 11 9 7 6 7 7 6 7 9 10 9 9 8 7 6 6 6 6 6 7 7 9 12 14 14 14 13 \n",
"9 7 5 6 6 6 6 6 6 5 6 8 10 8 6 5 4 5 5 4 5 6 6 7 7 10 11 11 10 7 \n",
"4 3 4 4 5 6 7 7 8 7 8 9 11 8 5 5 4 4 4 4 5 6 6 6 7 9 9 6 6 4 \n",
"4 2 4 5 6 8 10 8 9 9 10 12 11 9 5 4 4 4 3 4 5 5 6 6 6 7 7 5 4 4 \n",
"3 3 3 5 7 11 15 11 11 11 11 11 12 8 5 4 3 3 3 4 5 5 6 5 5 5 6 6 5 5 \n",
"4 4 5 7 9 13 14 14 14 11 10 11 15 9 6 4 3 3 4 4 4 4 5 6 6 5 5 7 6 6 \n",
"4 4 6 8 9 14 16 18 14 10 10 15 17 12 6 4 3 4 3 4 4 3 5 5 5 4 4 6 7 6 \n",
"4 4 5 5 9 11 13 19 14 10 14 17 15 9 5 4 3 5 5 4 4 4 4 5 5 4 3 4 5 5 \n"
]
}
],
"source": [
"for i in range(data.shape[0]):\n",
" for j in range(data.shape[1]):\n",
" print(int(data[i][j]), end=' ')\n",
" print()"
]
},
{
"cell_type": "code",
"execution_count": 168,
"id": "bc1b4e5e-52b5-462c-8fbf-e1ebaeca382f",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>train</th>\n",
" <th>validation</th>\n",
" <th>test</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>9624</td>\n",
" <td>1500</td>\n",
" <td>1743</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>6534</td>\n",
" <td>1117</td>\n",
" <td>1150</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>5380</td>\n",
" <td>840</td>\n",
" <td>956</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>5211</td>\n",
" <td>818</td>\n",
" <td>890</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" train validation test\n",
"0 9624 1500 1743\n",
"1 6534 1117 1150\n",
"2 5380 840 956\n",
"3 5211 818 890"
]
},
"execution_count": 168,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "code",
"execution_count": 169,
"id": "534dd823-08b2-419f-bb83-10f211fc2533",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "0db4e06f-4027-4e45-809c-b63a2cdfe15b",
"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
}