skip execution of download cells, skip noaa-coastal-lidar

Author: scottyhq

docs/datasets/NCALM.ipynb

@@ -87,7 +87,7 @@
    "outputs": [],
    "source": [
     "buffer_size = 0.01\n",
-    "centroid = gf_ncalm.centroid\n",
+    "centroid = gf_ncalm.centroid[0]\n",
     "mini_aoi = gpd.GeoDataFrame(\n",
     "    geometry=[\n",
     "        box(\n",
@@ -111,7 +111,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%time\n",
     "da_ncalm_dtm = coincident.io.xarray.load_ncalm_dem(\n",
     "    aoi=mini_aoi, product=\"dtm\", dataset_id=gf_ncalm[\"name\"].item()\n",
     ")"
@@ -158,16 +157,16 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%time\n",
+    "# Uncomment to download clipped_WALL_GEG_1M_dtm.tif\n",
     "\n",
-    "local_output_dir = \"/tmp/ncalm/\"\n",
+    "# local_output_dir = \"/tmp/ncalm/\"\n",
     "\n",
-    "coincident.io.download.download_ncalm_dem(\n",
-    "    aoi=mini_aoi,\n",
-    "    dataset_id=gf_ncalm[\"name\"].item(),\n",
-    "    product=\"dtm\",\n",
-    "    output_dir=local_output_dir,\n",
-    ")"
+    "# coincident.io.download.download_ncalm_dem(\n",
+    "#     aoi=mini_aoi,\n",
+    "#     dataset_id=gf_ncalm[\"name\"].item(),\n",
+    "#     product=\"dtm\",\n",
+    "#     output_dir=local_output_dir,\n",
+    "# )"
    ]
   },
   {
@@ -185,7 +184,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%time\n",
     "gf_ncalm_lpc_tiles = coincident.io.download.fetch_lpc_tiles(\n",
     "    aoi=mini_aoi, dataset_id=gf_ncalm.name.item(), provider=\"NCALM\"\n",
     ")"

docs/datasets/noaa-coastal-lidar.ipynb

@@ -64,7 +64,7 @@
    "source": [
     "# Plot the entire footprint for this scene and a subset region\n",
     "buffer_size = 0.02\n",
-    "centroid = gf_noaa.centroid\n",
+    "centroid = gf_noaa.geometry.centroid[0]\n",
     "mini_aoi = gpd.GeoDataFrame(\n",
     "    geometry=[\n",
     "        box(\n",

docs/examples/dem_and_lpc.ipynb

@@ -290,7 +290,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "skip-execution"
+    ]
+   },
    "outputs": [],
    "source": [
     "coincident.io.download.download_neon_dem(\n",
@@ -305,7 +309,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "skip-execution"
+    ]
+   },
    "outputs": [],
    "source": [
     "# USGS_1M_13_x71y440_CO_CentralEasternPlains_2020_D20.tif:  236MB\n",

src/coincident/io/xarray.py

@@ -588,7 +588,10 @@ def _fetch_noaa_tile_geometry(
     url: str,
 ) -> tuple[str, Polygon, rasterio.crs.CRS]:
     # Open the raster header from S3 using rasterio.Env for proper configuration.
-    with rasterio.Env(), rasterio.open(url) as src:
+    with (
+        rasterio.Env(GDAL_DISABLE_READDIR_ON_OPEN="EMPTY_DIR"),
+        rasterio.open(url) as src,
+    ):
         bounds = src.bounds
         tile_crs = src.crs
     # Create a shapely bounding box polygon from the raster bounds.
@@ -732,7 +735,6 @@ def load_gliht(
     -----
     - Only HTTPS GeoTIFF assets with the "data" role are considered.
     - NASA Earthdata authentication is handled via environment variables and cookies.
-    - The function expects the item to have a `datetime` attribute.
     """
 
     asset_items = item.assets
@@ -762,7 +764,6 @@ def load_gliht(
         GDAL_HTTP_COOKIEFILE="/tmp/cookies.txt",
         GDAL_HTTP_COOKIEJAR="/tmp/cookies.txt",
     ):
-        # Unfortunately NASA STAC doesn't have proj extension, so we have to open one...
         da = rioxarray.open_rasterio(
             data_assets[asset_keys_to_load[0]]["href"],
             masked=mask,