result
This commit is contained in:
Victor Phan
@@ -2,10 +2,18 @@
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"cells": [
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"cells": [
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 1,
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"id": "17da4353",
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"id": "17da4353",
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"✅ Import thành công\n"
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]
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}
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],
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"source": [
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"source": [
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"# Import libraries\n",
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"# Import libraries\n",
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"import numpy as np\n",
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"import numpy as np\n",
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@@ -32,10 +40,18 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 2,
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"id": "9c063be3",
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"id": "9c063be3",
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"✅ Kết nối Element84 Earth Search thành công\n"
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]
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}
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],
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"source": [
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"source": [
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"# Kết nối Element84 Earth Search (AWS-hosted STAC API)\n",
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"# Kết nối Element84 Earth Search (AWS-hosted STAC API)\n",
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"catalog = pystac_client.Client.open(\n",
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"catalog = pystac_client.Client.open(\n",
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@@ -46,17 +62,41 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 4,
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"id": "d87beed2",
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"id": "d87beed2",
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"✅ Đã đọc shapefile: 1130 points\n",
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" Columns: ['No', 'X', 'Y', 'LU2022', 'Hientrang', 'HT_code', 'geometry']\n",
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" CRS: EPSG:32648\n",
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"⚠️ Không tìm thấy column class, hiển thị 5 dòng đầu:\n",
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" No X Y LU2022 Hientrang HT_code \\\n",
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"0 1.0 603860.819 1081162.862 Pomelo CLN 3 \n",
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"1 2.0 601306.410 1082782.940 Pomelo CLN 3 \n",
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"2 3.0 601084.510 1081351.870 Pomelo CLN 3 \n",
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"3 4.0 602193.760 1079205.220 Pomelo CLN 3 \n",
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"4 5.0 602459.000 1080946.000 Pomelo CLN 3 \n",
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"\n",
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" geometry longitude latitude \n",
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"0 POINT (603860.819 1081162.862) 603860.819 1081162.862 \n",
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"1 POINT (601306.41 1082782.94) 601306.410 1082782.940 \n",
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"2 POINT (601084.51 1081351.87) 601084.510 1081351.870 \n",
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"3 POINT (602193.76 1079205.22) 602193.760 1079205.220 \n",
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"4 POINT (602459 1080946) 602459.000 1080946.000 \n"
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]
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}
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],
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"source": [
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"source": [
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"# Tạo file CSV training data từ shapefile\n",
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"# Tạo file CSV training data từ shapefile\n",
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"import geopandas as gpd\n",
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"import geopandas as gpd\n",
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"import pandas as pd\n",
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"import pandas as pd\n",
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"\n",
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"\n",
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"# Đọc shapefile training data\n",
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"# Đọc shapefile training data\n",
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"shapefile_path = \"/media/x79/2A7D-FAA0/remote-sensing/train/ST_training_data_updated_1130points_new.shp\"\n",
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"shapefile_path = \"/home/jovyan/remote-sensing/train/ST_training_data_updated_1130points_new.shp\"\n",
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"gdf = gpd.read_file(shapefile_path)\n",
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"gdf = gpd.read_file(shapefile_path)\n",
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"\n",
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"\n",
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"print(f\"✅ Đã đọc shapefile: {len(gdf)} points\")\n",
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"print(f\"✅ Đã đọc shapefile: {len(gdf)} points\")\n",
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@@ -100,10 +140,20 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 5,
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"id": "83784d01",
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"id": "83784d01",
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" Tìm thấy 45 scenes Sentinel-2\n",
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"✅ Sentinel-2 raw: FrozenMappingWarningOnValuesAccess({'y': 8874, 'x': 9902, 'time': 28})\n",
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" Variables: ['red', 'green', 'blue', 'nir', 'swir16', 'swir22', 'scl']\n"
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]
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}
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],
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"source": [
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"source": [
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"# Cấu hình vùng và thời gian\n",
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"# Cấu hình vùng và thời gian\n",
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"date_range = (\"2022-09-01\", \"2023-10-01\")\n",
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"date_range = (\"2022-09-01\", \"2023-10-01\")\n",
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@@ -142,10 +192,29 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 6,
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"id": "c3faed92",
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"id": "c3faed92",
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"ename": "ValueError",
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"evalue": "dimension time on 0th function argument to apply_ufunc with dask='parallelized' consists of multiple chunks, but is also a core dimension. To fix, either rechunk into a single array chunk along this dimension, i.e., ``.chunk(dict(time=-1))``, or pass ``allow_rechunk=True`` in ``dask_gufunc_kwargs`` but beware that this may significantly increase memory usage.",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[6], line 33\u001b[0m\n\u001b[1;32m 31\u001b[0m data_clean \u001b[38;5;241m=\u001b[39m mask_clean(data_sen2)\n\u001b[1;32m 32\u001b[0m data_ndvi \u001b[38;5;241m=\u001b[39m calculate_indices(data_clean, index\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNDVI\u001b[39m\u001b[38;5;124m\"\u001b[39m, satellite_mission\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ms2\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 33\u001b[0m data_fill \u001b[38;5;241m=\u001b[39m \u001b[43mfill_nan\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata_ndvi\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 34\u001b[0m data_sen2_monthly \u001b[38;5;241m=\u001b[39m data_fill\u001b[38;5;241m.\u001b[39mresample(time\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m1MS\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39mmean()\u001b[38;5;241m.\u001b[39mcompute()\n\u001b[1;32m 36\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m✅ S2 monthly shape: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdata_sen2_monthly\u001b[38;5;241m.\u001b[39mdims\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n",
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"Cell \u001b[0;32mIn[6], line 28\u001b[0m, in \u001b[0;36mfill_nan\u001b[0;34m(ds)\u001b[0m\n\u001b[1;32m 26\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfill_nan\u001b[39m(ds):\n\u001b[1;32m 27\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Fill NaN bằng interpolation theo thời gian\"\"\"\u001b[39;00m\n\u001b[0;32m---> 28\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mds\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minterpolate_na\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdim\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtime\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlinear\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfill_value\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mextrapolate\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m/env/lib/python3.12/site-packages/xarray/core/dataset.py:6773\u001b[0m, in \u001b[0;36mDataset.interpolate_na\u001b[0;34m(self, dim, method, limit, use_coordinate, max_gap, **kwargs)\u001b[0m\n\u001b[1;32m 6655\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Fill in NaNs by interpolating according to different methods.\u001b[39;00m\n\u001b[1;32m 6656\u001b[0m \n\u001b[1;32m 6657\u001b[0m \u001b[38;5;124;03mParameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 6769\u001b[0m \u001b[38;5;124;03m D (x) float64 40B 5.0 3.0 1.0 -1.0 4.0\u001b[39;00m\n\u001b[1;32m 6770\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 6771\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mxarray\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcore\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmissing\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m _apply_over_vars_with_dim, interp_na\n\u001b[0;32m-> 6773\u001b[0m new \u001b[38;5;241m=\u001b[39m \u001b[43m_apply_over_vars_with_dim\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 6774\u001b[0m \u001b[43m \u001b[49m\u001b[43minterp_na\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 6775\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 6776\u001b[0m \u001b[43m \u001b[49m\u001b[43mdim\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdim\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 6777\u001b[0m \u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 6778\u001b[0m \u001b[43m \u001b[49m\u001b[43mlimit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlimit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 6779\u001b[0m \u001b[43m \u001b[49m\u001b[43muse_coordinate\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_coordinate\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 6780\u001b[0m \u001b[43m \u001b[49m\u001b[43mmax_gap\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmax_gap\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 6781\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 6782\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 6783\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m new\n",
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"File \u001b[0;32m/env/lib/python3.12/site-packages/xarray/core/missing.py:222\u001b[0m, in \u001b[0;36m_apply_over_vars_with_dim\u001b[0;34m(func, self, dim, **kwargs)\u001b[0m\n\u001b[1;32m 220\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m name, var \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata_vars\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m 221\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m dim \u001b[38;5;129;01min\u001b[39;00m var\u001b[38;5;241m.\u001b[39mdims:\n\u001b[0;32m--> 222\u001b[0m ds[name] \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvar\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdim\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdim\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 223\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 224\u001b[0m ds[name] \u001b[38;5;241m=\u001b[39m var\n",
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"File \u001b[0;32m/env/lib/python3.12/site-packages/xarray/core/missing.py:367\u001b[0m, in \u001b[0;36minterp_na\u001b[0;34m(self, dim, use_coordinate, method, limit, max_gap, keep_attrs, **kwargs)\u001b[0m\n\u001b[1;32m 365\u001b[0m warnings\u001b[38;5;241m.\u001b[39mfilterwarnings(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moverflow\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;167;01mRuntimeWarning\u001b[39;00m)\n\u001b[1;32m 366\u001b[0m warnings\u001b[38;5;241m.\u001b[39mfilterwarnings(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minvalid value\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;167;01mRuntimeWarning\u001b[39;00m)\n\u001b[0;32m--> 367\u001b[0m arr \u001b[38;5;241m=\u001b[39m \u001b[43mapply_ufunc\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 368\u001b[0m \u001b[43m \u001b[49m\u001b[43minterpolator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 369\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 370\u001b[0m \u001b[43m \u001b[49m\u001b[43mindex\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 371\u001b[0m \u001b[43m \u001b[49m\u001b[43minput_core_dims\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43m[\u001b[49m\u001b[43mdim\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mdim\u001b[49m\u001b[43m]\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 372\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_core_dims\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43m[\u001b[49m\u001b[43mdim\u001b[49m\u001b[43m]\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 373\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_dtypes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 374\u001b[0m \u001b[43m \u001b[49m\u001b[43mdask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mparallelized\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 375\u001b[0m \u001b[43m \u001b[49m\u001b[43mvectorize\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 376\u001b[0m \u001b[43m \u001b[49m\u001b[43mkeep_attrs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkeep_attrs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 377\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mtranspose(\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdims)\n\u001b[1;32m 379\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m limit \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 380\u001b[0m arr \u001b[38;5;241m=\u001b[39m arr\u001b[38;5;241m.\u001b[39mwhere(valids)\n",
|
||||||
|
"File \u001b[0;32m/env/lib/python3.12/site-packages/xarray/core/computation.py:1265\u001b[0m, in \u001b[0;36mapply_ufunc\u001b[0;34m(func, input_core_dims, output_core_dims, exclude_dims, vectorize, join, dataset_join, dataset_fill_value, keep_attrs, kwargs, dask, output_dtypes, output_sizes, meta, dask_gufunc_kwargs, on_missing_core_dim, *args)\u001b[0m\n\u001b[1;32m 1263\u001b[0m \u001b[38;5;66;03m# feed DataArray apply_variable_ufunc through apply_dataarray_vfunc\u001b[39;00m\n\u001b[1;32m 1264\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(a, DataArray) \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m args):\n\u001b[0;32m-> 1265\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mapply_dataarray_vfunc\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1266\u001b[0m \u001b[43m \u001b[49m\u001b[43mvariables_vfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1267\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1268\u001b[0m \u001b[43m \u001b[49m\u001b[43msignature\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msignature\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1269\u001b[0m \u001b[43m \u001b[49m\u001b[43mjoin\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1270\u001b[0m \u001b[43m \u001b[49m\u001b[43mexclude_dims\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexclude_dims\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1271\u001b[0m \u001b[43m \u001b[49m\u001b[43mkeep_attrs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkeep_attrs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1272\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1273\u001b[0m \u001b[38;5;66;03m# feed Variables directly through apply_variable_ufunc\u001b[39;00m\n\u001b[1;32m 1274\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(a, Variable) \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m args):\n",
|
||||||
|
"File \u001b[0;32m/env/lib/python3.12/site-packages/xarray/core/computation.py:307\u001b[0m, in \u001b[0;36mapply_dataarray_vfunc\u001b[0;34m(func, signature, join, exclude_dims, keep_attrs, *args)\u001b[0m\n\u001b[1;32m 302\u001b[0m result_coords, result_indexes \u001b[38;5;241m=\u001b[39m build_output_coords_and_indexes(\n\u001b[1;32m 303\u001b[0m args, signature, exclude_dims, combine_attrs\u001b[38;5;241m=\u001b[39mkeep_attrs\n\u001b[1;32m 304\u001b[0m )\n\u001b[1;32m 306\u001b[0m data_vars \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mgetattr\u001b[39m(a, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvariable\u001b[39m\u001b[38;5;124m\"\u001b[39m, a) \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m args]\n\u001b[0;32m--> 307\u001b[0m result_var \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdata_vars\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 309\u001b[0m out: \u001b[38;5;28mtuple\u001b[39m[DataArray, \u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m] \u001b[38;5;241m|\u001b[39m DataArray\n\u001b[1;32m 310\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m signature\u001b[38;5;241m.\u001b[39mnum_outputs \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n",
|
||||||
|
"File \u001b[0;32m/env/lib/python3.12/site-packages/xarray/core/computation.py:764\u001b[0m, in \u001b[0;36mapply_variable_ufunc\u001b[0;34m(func, signature, exclude_dims, dask, output_dtypes, vectorize, keep_attrs, dask_gufunc_kwargs, *args)\u001b[0m\n\u001b[1;32m 762\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m axis, dim \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(core_dims, start\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;28mlen\u001b[39m(core_dims)):\n\u001b[1;32m 763\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(data\u001b[38;5;241m.\u001b[39mchunks[axis]) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m--> 764\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 765\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdimension \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdim\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m on \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mn\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124mth function argument to \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 766\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mapply_ufunc with dask=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mparallelized\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m consists of \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 767\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmultiple chunks, but is also a core dimension. To \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 768\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfix, either rechunk into a single array chunk along \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 769\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mthis dimension, i.e., ``.chunk(dict(\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdim\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m=-1))``, or \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 770\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpass ``allow_rechunk=True`` in ``dask_gufunc_kwargs`` \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 771\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbut beware that this may significantly increase memory usage.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 772\u001b[0m )\n\u001b[1;32m 773\u001b[0m dask_gufunc_kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mallow_rechunk\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 775\u001b[0m output_sizes \u001b[38;5;241m=\u001b[39m dask_gufunc_kwargs\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moutput_sizes\u001b[39m\u001b[38;5;124m\"\u001b[39m, {})\n",
|
||||||
|
"\u001b[0;31mValueError\u001b[0m: dimension time on 0th function argument to apply_ufunc with dask='parallelized' consists of multiple chunks, but is also a core dimension. To fix, either rechunk into a single array chunk along this dimension, i.e., ``.chunk(dict(time=-1))``, or pass ``allow_rechunk=True`` in ``dask_gufunc_kwargs`` but beware that this may significantly increase memory usage."
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"# Tiền xử lý Sentinel-2: cloud mask + NDVI + resampling\n",
|
"# Tiền xử lý Sentinel-2: cloud mask + NDVI + resampling\n",
|
||||||
"\n",
|
"\n",
|
||||||
@@ -663,11 +732,33 @@
|
|||||||
"plt.tight_layout()\n",
|
"plt.tight_layout()\n",
|
||||||
"plt.show()\n"
|
"plt.show()\n"
|
||||||
]
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "d4805767-4f58-4464-930c-66fcbb341cc2",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": []
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"metadata": {
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 3 (ipykernel)",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python3"
|
||||||
|
},
|
||||||
"language_info": {
|
"language_info": {
|
||||||
"name": "python"
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 3
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython3",
|
||||||
|
"version": "3.12.3"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
"nbformat": 4,
|
"nbformat": 4,
|
||||||
|
|||||||
Reference in New Issue
Block a user