wxee-02.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "32075ec0-1338-4bfa-8fb5-74c5899031a6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import ee\n",
    "import wxee\n",
    "\n",
    "wxee.Initialize()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9571fc33-6406-4cbe-b0a0-4fe7022fee4f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 46.9 ms\n",
      "Wall time: 2.28 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "8760"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# ds.to_zarr(\"hello.zarr\");\n",
    "ic = (ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY')\n",
    "      .filterDate('1992-01-01', '1992-12-31')\n",
    "      .select(['temperature_2m', 'u_component_of_wind_10m', 'v_component_of_wind_10m'])\n",
    ")\n",
    "ic.size().getInfo()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a6d2062f-183a-45cf-8922-5ca308fafaef",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "da8b0b510bd84c37bdcd1f8b586c30dc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Requesting data:   0%|          | 0/8760 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "EEException",
     "evalue": "Image.clipToBoundsAndScale: The geometry for image clipping must be bounded.",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31m_RemoteTraceback\u001b[0m                          Traceback (most recent call last)",
      "\u001b[1;31m_RemoteTraceback\u001b[0m: \n\"\"\"\nTraceback (most recent call last):\n  File \"C:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\ee\\data.py\", line 354, in _execute_cloud_call\n    return call.execute(num_retries=num_retries)\n  File \"C:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\googleapiclient\\_helpers.py\", line 130, in positional_wrapper\n    return wrapped(*args, **kwargs)\n  File \"C:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\googleapiclient\\http.py\", line 938, in execute\n    raise HttpError(resp, content, uri=self.uri)\ngoogleapiclient.errors.HttpError: <HttpError 400 when requesting https://earthengine-highvolume.googleapis.com/v1/projects/earthengine-legacy/thumbnails?fields=name&alt=json returned \"Image.clipToBoundsAndScale: The geometry for image clipping must be bounded.\". Details: \"Image.clipToBoundsAndScale: The geometry for image clipping must be bounded.\">\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n  File \"C:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\joblib\\_parallel_backends.py\", line 273, in _wrap_func_call\n    return func()\n  File \"C:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\joblib\\parallel.py\", line 589, in __call__\n    return [func(*args, **kwargs)\n  File \"C:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\joblib\\parallel.py\", line 589, in <listcomp>\n    return [func(*args, **kwargs)\n  File \"C:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\wxee\\image.py\", line 236, in _get_url\n    url = img.getDownloadURL(\n  File \"C:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\ee\\image.py\", line 477, in getDownloadURL\n    return data.makeDownloadUrl(data.getDownloadId(request))\n  File \"C:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\ee\\data.py\", line 1269, in getDownloadId\n    result = _execute_cloud_call(\n  File \"C:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\ee\\data.py\", line 356, in _execute_cloud_call\n    raise _translate_cloud_exception(e)  # pylint: disable=raise-missing-from\nee.ee_exception.EEException: Image.clipToBoundsAndScale: The geometry for image clipping must be bounded.\n\"\"\"",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mEEException\u001b[0m                               Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[3], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m ds \u001b[38;5;241m=\u001b[39m \u001b[43mic\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_xarray\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m      2\u001b[0m ds\n",
      "File \u001b[1;32mC:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\wxee\\collection.py:117\u001b[0m, in \u001b[0;36mImageCollection.to_xarray\u001b[1;34m(self, path, region, scale, crs, masked, nodata, num_cores, progress, max_attempts)\u001b[0m\n\u001b[0;32m     72\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Convert an image collection to an xarray.Dataset. The :code:`system:time_start` property of each image in the\u001b[39;00m\n\u001b[0;32m     73\u001b[0m \u001b[38;5;124;03mcollection is used to arrange the time dimension, and each image variable is loaded as a separate array in\u001b[39;00m\n\u001b[0;32m     74\u001b[0m \u001b[38;5;124;03mthe dataset.\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    114\u001b[0m \u001b[38;5;124;03m>>> col.wx.to_xarray(scale=40000, crs=\"EPSG:5070\", nodata=-9999)\u001b[39;00m\n\u001b[0;32m    115\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m    116\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m tempfile\u001b[38;5;241m.\u001b[39mTemporaryDirectory(prefix\u001b[38;5;241m=\u001b[39mconstants\u001b[38;5;241m.\u001b[39mTMP_PREFIX) \u001b[38;5;28;01mas\u001b[39;00m tmp:\n\u001b[1;32m--> 117\u001b[0m     files \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_obj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_tif\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    118\u001b[0m \u001b[43m        \u001b[49m\u001b[43mout_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtmp\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    119\u001b[0m \u001b[43m        \u001b[49m\u001b[43mregion\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mregion\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    120\u001b[0m \u001b[43m        \u001b[49m\u001b[43mscale\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mscale\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    121\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcrs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcrs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    122\u001b[0m \u001b[43m        \u001b[49m\u001b[43mfile_per_band\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[0;32m    123\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmasked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmasked\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    124\u001b[0m \u001b[43m        \u001b[49m\u001b[43mnodata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnodata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    125\u001b[0m \u001b[43m        \u001b[49m\u001b[43mnum_cores\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnum_cores\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    126\u001b[0m \u001b[43m        \u001b[49m\u001b[43mprogress\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprogress\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    127\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmax_attempts\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmax_attempts\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    128\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    130\u001b[0m     ds \u001b[38;5;241m=\u001b[39m _dataset_from_files(files, masked, nodata)\n\u001b[0;32m    132\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m path:\n",
      "File \u001b[1;32mC:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\wxee\\collection.py:212\u001b[0m, in \u001b[0;36mImageCollection.to_tif\u001b[1;34m(self, out_dir, prefix, region, scale, crs, file_per_band, masked, nodata, num_cores, progress, max_attempts)\u001b[0m\n\u001b[0;32m    208\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m Parallel(n_jobs\u001b[38;5;241m=\u001b[39mnum_cores, backend\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mthreading\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m p:\n\u001b[0;32m    209\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m parallel_tqdm(\n\u001b[0;32m    210\u001b[0m         tqdm(desc\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRequesting data\u001b[39m\u001b[38;5;124m\"\u001b[39m, total\u001b[38;5;241m=\u001b[39mn, disable\u001b[38;5;241m=\u001b[39m\u001b[38;5;129;01mnot\u001b[39;00m progress)\n\u001b[0;32m    211\u001b[0m     ):\n\u001b[1;32m--> 212\u001b[0m         urls \u001b[38;5;241m=\u001b[39m \u001b[43mp\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    213\u001b[0m \u001b[43m            \u001b[49m\u001b[43mdelayed\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_url\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    214\u001b[0m \u001b[43m                \u001b[49m\u001b[43mregion\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mscale\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfile_per_band\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnodata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_attempts\u001b[49m\n\u001b[0;32m    215\u001b[0m \u001b[43m            \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    216\u001b[0m \u001b[43m            \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mimg\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mimgs\u001b[49m\n\u001b[0;32m    217\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    219\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m parallel_tqdm(\n\u001b[0;32m    220\u001b[0m         tqdm(desc\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDownloading data\u001b[39m\u001b[38;5;124m\"\u001b[39m, total\u001b[38;5;241m=\u001b[39mn, disable\u001b[38;5;241m=\u001b[39m\u001b[38;5;129;01mnot\u001b[39;00m progress)\n\u001b[0;32m    221\u001b[0m     ):\n\u001b[0;32m    222\u001b[0m         img_urls \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mzip\u001b[39m(imgs, urls)\n",
      "File \u001b[1;32mC:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\joblib\\parallel.py:1952\u001b[0m, in \u001b[0;36mParallel.__call__\u001b[1;34m(self, iterable)\u001b[0m\n\u001b[0;32m   1946\u001b[0m \u001b[38;5;66;03m# The first item from the output is blank, but it makes the interpreter\u001b[39;00m\n\u001b[0;32m   1947\u001b[0m \u001b[38;5;66;03m# progress until it enters the Try/Except block of the generator and\u001b[39;00m\n\u001b[0;32m   1948\u001b[0m \u001b[38;5;66;03m# reach the first `yield` statement. This starts the aynchronous\u001b[39;00m\n\u001b[0;32m   1949\u001b[0m \u001b[38;5;66;03m# dispatch of the tasks to the workers.\u001b[39;00m\n\u001b[0;32m   1950\u001b[0m \u001b[38;5;28mnext\u001b[39m(output)\n\u001b[1;32m-> 1952\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m output \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mreturn_generator \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43moutput\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mC:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\joblib\\parallel.py:1595\u001b[0m, in \u001b[0;36mParallel._get_outputs\u001b[1;34m(self, iterator, pre_dispatch)\u001b[0m\n\u001b[0;32m   1592\u001b[0m     \u001b[38;5;28;01myield\u001b[39;00m\n\u001b[0;32m   1594\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backend\u001b[38;5;241m.\u001b[39mretrieval_context():\n\u001b[1;32m-> 1595\u001b[0m         \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_retrieve()\n\u001b[0;32m   1597\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mGeneratorExit\u001b[39;00m:\n\u001b[0;32m   1598\u001b[0m     \u001b[38;5;66;03m# The generator has been garbage collected before being fully\u001b[39;00m\n\u001b[0;32m   1599\u001b[0m     \u001b[38;5;66;03m# consumed. This aborts the remaining tasks if possible and warn\u001b[39;00m\n\u001b[0;32m   1600\u001b[0m     \u001b[38;5;66;03m# the user if necessary.\u001b[39;00m\n\u001b[0;32m   1601\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
      "File \u001b[1;32mC:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\joblib\\parallel.py:1699\u001b[0m, in \u001b[0;36mParallel._retrieve\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1692\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_wait_retrieval():\n\u001b[0;32m   1693\u001b[0m \n\u001b[0;32m   1694\u001b[0m     \u001b[38;5;66;03m# If the callback thread of a worker has signaled that its task\u001b[39;00m\n\u001b[0;32m   1695\u001b[0m     \u001b[38;5;66;03m# triggered an exception, or if the retrieval loop has raised an\u001b[39;00m\n\u001b[0;32m   1696\u001b[0m     \u001b[38;5;66;03m# exception (e.g. `GeneratorExit`), exit the loop and surface the\u001b[39;00m\n\u001b[0;32m   1697\u001b[0m     \u001b[38;5;66;03m# worker traceback.\u001b[39;00m\n\u001b[0;32m   1698\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_aborting:\n\u001b[1;32m-> 1699\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_raise_error_fast\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1700\u001b[0m         \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[0;32m   1702\u001b[0m     \u001b[38;5;66;03m# If the next job is not ready for retrieval yet, we just wait for\u001b[39;00m\n\u001b[0;32m   1703\u001b[0m     \u001b[38;5;66;03m# async callbacks to progress.\u001b[39;00m\n",
      "File \u001b[1;32mC:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\joblib\\parallel.py:1734\u001b[0m, in \u001b[0;36mParallel._raise_error_fast\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1730\u001b[0m \u001b[38;5;66;03m# If this error job exists, immediatly raise the error by\u001b[39;00m\n\u001b[0;32m   1731\u001b[0m \u001b[38;5;66;03m# calling get_result. This job might not exists if abort has been\u001b[39;00m\n\u001b[0;32m   1732\u001b[0m \u001b[38;5;66;03m# called directly or if the generator is gc'ed.\u001b[39;00m\n\u001b[0;32m   1733\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m error_job \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-> 1734\u001b[0m     \u001b[43merror_job\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_result\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mC:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\joblib\\parallel.py:736\u001b[0m, in \u001b[0;36mBatchCompletionCallBack.get_result\u001b[1;34m(self, timeout)\u001b[0m\n\u001b[0;32m    730\u001b[0m backend \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparallel\u001b[38;5;241m.\u001b[39m_backend\n\u001b[0;32m    732\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m backend\u001b[38;5;241m.\u001b[39msupports_retrieve_callback:\n\u001b[0;32m    733\u001b[0m     \u001b[38;5;66;03m# We assume that the result has already been retrieved by the\u001b[39;00m\n\u001b[0;32m    734\u001b[0m     \u001b[38;5;66;03m# callback thread, and is stored internally. It's just waiting to\u001b[39;00m\n\u001b[0;32m    735\u001b[0m     \u001b[38;5;66;03m# be returned.\u001b[39;00m\n\u001b[1;32m--> 736\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_return_or_raise\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    738\u001b[0m \u001b[38;5;66;03m# For other backends, the main thread needs to run the retrieval step.\u001b[39;00m\n\u001b[0;32m    739\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n",
      "File \u001b[1;32mC:\\ProgramData\\Miniconda3\\envs\\rgee\\lib\\site-packages\\joblib\\parallel.py:754\u001b[0m, in \u001b[0;36mBatchCompletionCallBack._return_or_raise\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    752\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    753\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstatus \u001b[38;5;241m==\u001b[39m TASK_ERROR:\n\u001b[1;32m--> 754\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_result\n\u001b[0;32m    755\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_result\n\u001b[0;32m    756\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n",
      "\u001b[1;31mEEException\u001b[0m: Image.clipToBoundsAndScale: The geometry for image clipping must be bounded."
     ]
    }
   ],
   "source": [
    "ds = ic.wx.to_xarray()\n",
    "ds\n"
   ]
  }
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