def test_aggregate_raster_values_all_polys(self):
"""PyGeoprocessing: test aggregate raster values as a lump."""
import pygeoprocessing
base_raster_path = os.path.join(TEST_DATA,
'aggregate_raster_values_data',
'base_raster.tif')
shapefile_path = os.path.join(TEST_DATA,
'aggregate_raster_values_data',
'watershed.shp')
result = pygeoprocessing.aggregate_raster_values_uri(
base_raster_path, shapefile_path)
expected_result = pygeoprocessing.AggregatedValues(
total={9999: 398428.0},
pixel_mean={9999: 1.0},
hectare_mean={9999: 11.111194773692587},
n_pixels={9999: 398428.0},
pixel_min={9999: 1.0},
pixel_max={9999: 1.0})
for metric in [
'total', 'pixel_mean', 'hectare_mean', 'n_pixels', 'pixel_min',
'pixel_max'
]:
_assert_deep_almost_equal(self,
getattr(expected_result, metric),
getattr(result, metric),
places=6)
def test_aggregate_raster_values_include_nodata(self):
"""PyGeoprocessing: test aggregate raster values, include nodata."""
import pygeoprocessing
base_raster_path = os.path.join(TEST_DATA,
'aggregate_raster_values_data',
'base_raster.tif')
shapefile_path = os.path.join(TEST_DATA,
'aggregate_raster_values_data',
'overlap_watershed.shp')
result = pygeoprocessing.aggregate_raster_values_uri(
base_raster_path,
shapefile_path,
shapefile_field='DN',
all_touched=False,
polygons_might_overlap=True,
ignore_nodata=False)
expected_result = pygeoprocessing.AggregatedValues(
total={
1: 3.0,
2: 398425.0,
3: 5.0
},
pixel_mean={
1: 1.0,
2: 1.0,
3: 0.41666666666666669
},
hectare_mean={
1: 11.111111110950143,
2: 11.111111110937156,
3: 3.6282805923682009
},
n_pixels={
1: 3.0,
2: 398425.0,
3: 12.0
},
pixel_min={
1: 1.0,
2: 1.0,
3: 1.0
},
pixel_max={
1: 1.0,
2: 1.0,
3: 1.0
})
for metric in [
'total', 'pixel_mean', 'hectare_mean', 'n_pixels', 'pixel_min',
'pixel_max'
]:
_assert_deep_almost_equal(self,
getattr(expected_result, metric),
getattr(result, metric),
places=6)