cannot compute affected area from large mask

[JinIgarashi]

this is related to RWI (#62).

currently it uses mask raster by mask layer with rasterio. the function is implemented at below.

geo-cb-surge/cbsurge/components/rwi/__init__.py

Lines 163 to 202 in e45e49c

	def clip_raster_with_mask(self, source, mask, output_path):
	"""
	Clips the raster data at 'source' using the mask raster at 'mask' and saves the result to 'output_path'.
	:param source: Path to the source raster file.
	:param mask: Path to the mask raster file (e.g., project.raster_mask).
	:param output_path: File path to save the clipped raster.
	"""
	# Open the mask raster and read the first band
	with rasterio.open(mask) as mask_src:
	mask_data = mask_src.read(1)
	# Define the mask region as areas where the value is greater than 0 (adjust condition as needed)
	binary_mask = mask_data > 0
	# Extract polygons from the mask raster based on the binary_mask
	mask_shapes = []
	for geom, value in rasterio.features.shapes(mask_data, mask=binary_mask, transform=mask_src.transform):
	# If the value equals 1, use that region as a mask
	if value == 1:
	mask_shapes.append(shape(geom))
	# Open the main raster and clip it using the extracted polygons
	with rasterio.open(source) as src:
	# Convert the polygon geometries to dict format using mapping()
	out_image, out_transform = rasterio.mask.mask(src, [mapping(geom) for geom in mask_shapes], crop=True)
	out_meta = src.meta.copy()
	# Update the metadata
	out_meta.update({
	"driver": "COG",
	"height": out_image.shape[1],
	"width": out_image.shape[2],
	"transform": out_transform,
	"compress": 'zstd',
	"predictor": 2
	})
	# Save the clipped raster to the output file
	with rasterio.open(output_path, "w", **out_meta) as dest:
	dest.write(out_image)

the code fails if raster data is large area. need to find better way to mask raster.