Upload vis_rdr.ipynb

vis_rdr.ipynb

@@ -0,0 +1,130 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "91dcaf61-f160-4d17-a921-80a5c4ace5e5",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "FileNotFoundError",
+     "evalue": "[Errno 2] No such file or directory: './SAR2RDR-Dataset/RDR/test/RDR_CMP_HSP_PUB_202401211300.npy'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
+      "\u001b[31mFileNotFoundError\u001b[39m                         Traceback (most recent call last)",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[19]\u001b[39m\u001b[32m, line 32\u001b[39m\n\u001b[32m     30\u001b[39m lat = np.loadtxt(\u001b[33m'\u001b[39m\u001b[33m./lonlat/RDR_lat.txt\u001b[39m\u001b[33m'\u001b[39m, delimiter=\u001b[33m'\u001b[39m\u001b[33m,\u001b[39m\u001b[33m'\u001b[39m).reshape(\u001b[32m2881\u001b[39m, \u001b[32m2305\u001b[39m)[::-\u001b[32m1\u001b[39m]\n\u001b[32m     31\u001b[39m lon = np.loadtxt(\u001b[33m'\u001b[39m\u001b[33m./lonlat/RDR_lon.txt\u001b[39m\u001b[33m'\u001b[39m, delimiter=\u001b[33m'\u001b[39m\u001b[33m,\u001b[39m\u001b[33m'\u001b[39m).reshape(\u001b[32m2881\u001b[39m, \u001b[32m2305\u001b[39m)[::-\u001b[32m1\u001b[39m]\n\u001b[32m---> \u001b[39m\u001b[32m32\u001b[39m rdr = \u001b[43mnp\u001b[49m\u001b[43m.\u001b[49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43m./SAR2RDR-Dataset/RDR/test/RDR_CMP_HSP_PUB_202401211300.npy\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m     34\u001b[39m y0, y1 = \u001b[32m1200\u001b[39m - \u001b[32m200\u001b[39m, \u001b[32m1200\u001b[39m + \u001b[32m980\u001b[39m   \u001b[38;5;66;03m# 1000 : 2180\u001b[39;00m\n\u001b[32m     35\u001b[39m x0, x1 = \u001b[32m1121\u001b[39m - \u001b[32m328\u001b[39m, \u001b[32m1121\u001b[39m + \u001b[32m772\u001b[39m   \u001b[38;5;66;03m#  793 : 1893\u001b[39;00m\n",
+      "\u001b[36mFile \u001b[39m\u001b[32m/opt/conda/lib/python3.11/site-packages/numpy/lib/_npyio_impl.py:451\u001b[39m, in \u001b[36mload\u001b[39m\u001b[34m(file, mmap_mode, allow_pickle, fix_imports, encoding, max_header_size)\u001b[39m\n\u001b[32m    449\u001b[39m     own_fid = \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[32m    450\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m451\u001b[39m     fid = stack.enter_context(\u001b[38;5;28mopen\u001b[39m(os.fspath(file), \u001b[33m\"\u001b[39m\u001b[33mrb\u001b[39m\u001b[33m\"\u001b[39m))\n\u001b[32m    452\u001b[39m     own_fid = \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[32m    454\u001b[39m \u001b[38;5;66;03m# Code to distinguish from NumPy binary files and pickles.\u001b[39;00m\n",
+      "\u001b[31mFileNotFoundError\u001b[39m: [Errno 2] No such file or directory: './SAR2RDR-Dataset/RDR/test/RDR_CMP_HSP_PUB_202401211300.npy'"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib\n",
+    "import cartopy.crs as ccrs\n",
+    "import cartopy.feature as cfeature\n",
+    "\n",
+    "def my_cmap_radar_kma():\n",
+    "    colors = ['#c3c3c7',\n",
+    "              '#ffffff', '#009bf5', '#004af5',\n",
+    "              '#00ff00', '#00be00', '#008c00', '#005a00',\n",
+    "              '#ffff00', '#ffdc1f', '#f9cd00', '#e0b900', '#ccaa00',\n",
+    "              '#ff6600', '#ff3200', '#d20000', '#b40000',\n",
+    "              '#e0a9ff', '#cc6aff', '#b329ff', '#9300e4',\n",
+    "              '#b3b4de', '#4c4eb1', '#000390', '#000000']\n",
+    "    bounds_vals = [-1e-5, 0, 0.1, 0.5, 1.0, 2, 3, 4, 5, 6, 7,\n",
+    "                   8, 9, 10, 15, 20, 25, 30, 40, 50, 60, 70, 90, 110, 150, 200]\n",
+    "    bounds_labels = ['', 0, 0.1, 0.5, 1, 2, 3, 4, 5, 6, 7,\n",
+    "                     8, 9, 10, 15, 20, 25, 30, 40, 50, 60, 70, 90, 110, 150, '']\n",
+    "\n",
+    "    cmap = matplotlib.colors.ListedColormap(colors, name=\"kma_radar\").with_extremes(under='#ffffff')\n",
+    "    norm = matplotlib.colors.BoundaryNorm(bounds_vals, cmap.N)\n",
+    "    try:\n",
+    "        matplotlib.colormaps.register(cmap=cmap)\n",
+    "    except Exception:\n",
+    "        pass\n",
+    "    return cmap, bounds_vals, bounds_labels, norm\n",
+    "\n",
+    "cmap_radar_kma, bounds_vals, bounds_labels, kma_norm = my_cmap_radar_kma()\n",
+    "\n",
+    "lat = np.loadtxt('./lonlat/RDR_lat.txt', delimiter=',').reshape(2881, 2305)[::-1]\n",
+    "lon = np.loadtxt('./lonlat/RDR_lon.txt', delimiter=',').reshape(2881, 2305)[::-1]\n",
+    "rdr = np.load(\"./SAR2RDR-Dataset/RDR/test/RDR_CMP_HSP_PUB_202401211300.npy\")\n",
+    "\n",
+    "y0, y1 = 1200 - 200, 1200 + 980   # 1000 : 2180\n",
+    "x0, x1 = 1121 - 328, 1121 + 772   #  793 : 1893\n",
+    "\n",
+    "projection = ccrs.LambertConformal(\n",
+    "    central_longitude=float(lon.mean()),\n",
+    "    central_latitude=float(lat.mean()),\n",
+    "    standard_parallels=(30, 60),\n",
+    ")\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(10, 8), subplot_kw={'projection': projection})\n",
+    "ax.add_feature(cfeature.COASTLINE.with_scale('50m'), linewidth=0.5)\n",
+    "ax.add_feature(cfeature.BORDERS.with_scale('50m'), linewidth=0.5)\n",
+    "ax.set_extent([lon.min(), lon.max(), lat.min(), lat.max()], crs=ccrs.PlateCarree())\n",
+    "\n",
+    "# radar\n",
+    "im = ax.pcolormesh(\n",
+    "    lon, lat, rdr,\n",
+    "    cmap=cmap_radar_kma, norm=kma_norm,\n",
+    "    shading='auto', rasterized=True,\n",
+    "    transform=ccrs.PlateCarree(), alpha=0.9\n",
+    ")\n",
+    "\n",
+    "cbar = plt.colorbar(im, ax=ax, orientation='vertical',\n",
+    "                    boundaries=bounds_vals, ticks=bounds_vals, extend='max')\n",
+    "cbar.ax.set_yticklabels([str(x) if x != '' else '' for x in bounds_labels])\n",
+    "\n",
+    "\n",
+    "ax.plot(lon[y0, x0:x1], lat[y0, x0:x1],\n",
+    "        transform=ccrs.PlateCarree(), color='red', linewidth=1.8)\n",
+    "\n",
+    "ax.plot(lon[y0:y1, x1-1], lat[y0:y1, x1-1],\n",
+    "        transform=ccrs.PlateCarree(), color='red', linewidth=1.8)\n",
+    "\n",
+    "ax.plot(lon[y1-1, x0:x1][::-1], lat[y1-1, x0:x1][::-1],\n",
+    "        transform=ccrs.PlateCarree(), color='red', linewidth=1.8)\n",
+    "\n",
+    "ax.plot(lon[y0:y1, x0][::-1], lat[y0:y1, x0][::-1],\n",
+    "        transform=ccrs.PlateCarree(), color='red', linewidth=1.8)\n",
+    "\n",
+    "plt.title(\"KMA Radar (LCC Projection) — window outlined\")\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a5f5b20c-df64-4873-9fee-854cc2e5a1ad",
+   "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": "3.11.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}