def compute_subset_gdal(inputs=[], args=[]):
"""
Runs the subset computation, creating a raster dataset as output.
"""
raster, clip = inputs[0], inputs[1]
raster_img = raster.get_data()
if clip.get_epsg() != raster.get_epsg():
clip.reproject(raster.get_epsg())
clip_json = clip.get_data().geometry.unary_union.__geo_interface__
# Passing "None" as second arg instead of a file path. This tells gdal_clip
# not to write the output dataset to a tiff file on disk
output_dataset = gdal_clip(raster_img, None, clip_json)
if output_dataset is None:
return None
# Copy data to new GDALDataObject
outputDataObject = GDALDataObject()
outputDataObject.set_data(output_dataset)
outputDataObject._datatype = gaia.types.RASTER
# Instantiate temporary reader to (only) parse metadata
reader = GaiaGDALReader('internal.tif')
reader.load_metadata(outputDataObject)
return outputDataObject
def compute_subset_gdal(inputs=[], args=[]):
"""
Runs the subset computation, creating a raster dataset as output.
"""
raster, clip = inputs[0], inputs[1]
raster_img = raster.get_data()
if clip.get_epsg() != raster.get_epsg():
clip.reproject(raster.get_epsg())
clip_json = clip.get_data().geometry.unary_union.__geo_interface__
# Passing "None" as second arg instead of a file path. This tells gdal_clip
# not to write the output dataset to a tiff file on disk
output_dataset = gdal_clip(raster_img, None, clip_json)
if output_dataset is None:
return None
# Copy data to new GDALDataObject
outputDataObject = GDALDataObject()
outputDataObject.set_data(output_dataset)
outputDataObject._datatype = gaia.types.RASTER
# Instantiate temporary reader to (only) parse metadata
reader = GaiaGDALReader('internal.tif')
reader.load_metadata(outputDataObject)
return outputDataObject
def compute(self):
raster, clip = self.inputs[0], self.inputs[1]
raster_img = raster.read()
clip_df = clip.read(epsg=raster.get_epsg())
# Merge all features in vector input
raster_output = self.output.uri
self.output.create_output_dir(raster_output)
clip_json = clip_df.geometry.unary_union.__geo_interface__
self.output.data = gdal_clip(raster_img, raster_output, clip_json)
def compute(self):
raster, clip = self.inputs[0], self.inputs[1]
raster_img = raster.read()
clip_df = clip.read(epsg=raster.get_epsg())
# Merge all features in vector input
raster_output = self.output.uri
self.output.create_output_dir(raster_output)
clip_json = clip_df.geometry.unary_union.__geo_interface__
self.output.data = gdal_clip(raster_img, raster_output, clip_json)
def compute_subset_gdal(inputs=[], args=[]):
"""
Runs the subset computation, creating a raster dataset as output.
"""
raster, clip = inputs[0], inputs[1]
raster_img = raster.get_data()
if clip.get_epsg() != raster.get_epsg():
clip.reproject(raster.get_epsg())
clip_json = clip.get_data().geometry.unary_union.__geo_interface__
# Passing "None" as second arg instead of a file path. This tells gdal_clip
# not to write the output dataset to a tiff file on disk
output_dataset = gdal_clip(raster_img, None, clip_json)
outputDataObject = GDALDataObject()
outputDataObject.set_data(output_dataset)
return outputDataObject