def test_ufrm_regression(self):
"""UFRM: regression test."""
from natcap.invest import urban_flood_risk_mitigation
args = self._make_args()
urban_flood_risk_mitigation.execute(args)
result_vector = gdal.OpenEx(
os.path.join(args['workspace_dir'],
'flood_risk_service_Test1.shp'), gdal.OF_VECTOR)
result_layer = result_vector.GetLayer()
# Check that all four expected fields are there.
self.assertEqual(
set(('aff.bld', 'serv.blt', 'rnf_rt_idx', 'rnf_rt_m3',
'flood_vol')),
set(field.GetName() for field in result_layer.schema))
result_feature = next(result_layer)
for fieldname, expected_value in (('aff.bld', 187010830.32202843),
('serv.blt', 13253546667257.65),
('rnf_rt_idx', 0.70387527942),
('rnf_rt_m3', 70870.4765625),
('flood_vol', 29815.640625)):
result_val = result_feature.GetField(fieldname)
places_to_round = (
int(round(numpy.log(expected_value) / numpy.log(10))) - 6)
self.assertAlmostEqual(result_val,
expected_value,
places=-places_to_round)
result_feature = None
result_layer = None
result_vector = None
def test_ufrm_value_error_on_bad_soil(self):
"""UFRM: assert exception on bad soil raster values."""
from natcap.invest import urban_flood_risk_mitigation
args = self._make_args()
bad_soil_raster = os.path.join(self.workspace_dir,
'bad_soilgroups.tif')
value_map = {
1: 1,
2: 2,
3: 9, # only 1, 2, 3, 4 are valid values for this raster.
4: 4
}
pygeoprocessing.reclassify_raster(
(args['soils_hydrological_group_raster_path'], 1), value_map,
bad_soil_raster, gdal.GDT_Int16, -9)
args['soils_hydrological_group_raster_path'] = bad_soil_raster
with self.assertRaises(ValueError) as cm:
urban_flood_risk_mitigation.execute(args)
actual_message = str(cm.exception)
expected_message = (
'Check that the Soil Group raster does not contain')
self.assertTrue(expected_message in actual_message)
def test_ufrm_regression_no_infrastructure(self):
"""UFRM: regression for no infrastructure."""
from natcap.invest import urban_flood_risk_mitigation
args = self._make_args()
del args['built_infrastructure_vector_path']
urban_flood_risk_mitigation.execute(args)
result_raster = gdal.OpenEx(
os.path.join(args['workspace_dir'],
'Runoff_retention_m3_Test1.tif'), gdal.OF_RASTER)
band = result_raster.GetRasterBand(1)
array = band.ReadAsArray()
nodata = band.GetNoDataValue()
band = None
result_raster = None
result_sum = numpy.sum(array[~numpy.isclose(array, nodata)])
# expected result observed from regression run.
expected_result = 156070.36
self.assertAlmostEqual(result_sum, expected_result, places=0)
def test_ufrm_value_error_on_bad_lucode(self):
"""UFRM: assert exception on missing lucodes."""
import pandas
from natcap.invest import urban_flood_risk_mitigation
args = self._make_args()
bad_cn_table_path = os.path.join(self.workspace_dir,
'bad_cn_table.csv')
cn_table = pandas.read_csv(args['curve_number_table_path'])
# drop a row with an lucode known to exist in lulc raster
# This is a code that will successfully index into the
# CN table sparse matrix, but will not return valid data.
bad_cn_table = cn_table[cn_table['lucode'] != 0]
bad_cn_table.to_csv(bad_cn_table_path, index=False)
args['curve_number_table_path'] = bad_cn_table_path
with self.assertRaises(ValueError) as cm:
urban_flood_risk_mitigation.execute(args)
actual_message = str(cm.exception)
expected_message = (
f'The biophysical table is missing a row for lucode(s) {[0]}')
self.assertEqual(expected_message, actual_message)
# drop rows with lucodes known to exist in lulc raster
# These are codes that will raise an IndexError on
# indexing into the CN table sparse matrix. The test
# LULC raster has values from 0 to 21.
bad_cn_table = cn_table[cn_table['lucode'] < 15]
bad_cn_table.to_csv(bad_cn_table_path, index=False)
args['curve_number_table_path'] = bad_cn_table_path
with self.assertRaises(ValueError) as cm:
urban_flood_risk_mitigation.execute(args)
actual_message = str(cm.exception)
expected_message = (
f'The biophysical table is missing a row for lucode(s) '
f'{[16, 17, 18, 21]}')
self.assertEqual(expected_message, actual_message)
def test_ufrm_regression(self):
"""UFRM: regression test."""
from natcap.invest import urban_flood_risk_mitigation
args = self._make_args()
urban_flood_risk_mitigation.execute(args)
result_vector = gdal.OpenEx(
os.path.join(args['workspace_dir'],
'flood_risk_service_Test1.shp'), gdal.OF_VECTOR)
result_layer = result_vector.GetLayer()
result_feature = next(result_layer)
result_val = result_feature.GetField('serv_bld')
result_feature = None
result_layer = None
result_vector = None
# expected result observed from regression run.
expected_result = 13253546667257.65
places_to_round = (
int(round(numpy.log(expected_result) / numpy.log(10))) - 6)
self.assertAlmostEqual(result_val,
expected_result,
places=-places_to_round)
def test_ufrm_regression_no_infrastructure(self):
"""UFRM: regression for no infrastructure."""
from natcap.invest import urban_flood_risk_mitigation
args = self._make_args()
del args['built_infrastructure_vector_path']
urban_flood_risk_mitigation.execute(args)
result_raster = gdal.OpenEx(
os.path.join(args['workspace_dir'],
'Runoff_retention_m3_Test1.tif'), gdal.OF_RASTER)
band = result_raster.GetRasterBand(1)
array = band.ReadAsArray()
nodata = band.GetNoDataValue()
band = None
result_raster = None
result_sum = numpy.sum(array[~numpy.isclose(array, nodata)])
# expected result observed from regression run.
expected_result = 156070.36
self.assertAlmostEqual(result_sum, expected_result, places=0)
result_vector = gdal.OpenEx(
os.path.join(args['workspace_dir'],
'flood_risk_service_Test1.shp'), gdal.OF_VECTOR)
result_layer = result_vector.GetLayer()
result_feature = next(result_layer)
# Check that only the two expected fields are there.
self.assertEqual(set(('rnf_rt_idx', 'rnf_rt_m3', 'flood_vol')),
set(field.GetName() for field in result_layer.schema))
for fieldname, expected_value in (('rnf_rt_idx', 0.70387527942),
('rnf_rt_m3', 70870.4765625),
('flood_vol', 29815.640625)):
result_val = result_feature.GetField(fieldname)
places_to_round = (
int(round(numpy.log(expected_value) / numpy.log(10))) - 6)
self.assertAlmostEqual(result_val,
expected_value,
places=-places_to_round)
def test_ufrm_invalid_validation(self):
"""UFRM: assert validation error on bad args."""
from natcap.invest import urban_flood_risk_mitigation
with self.assertRaises(ValueError):
urban_flood_risk_mitigation.execute({})
