def test_aggregate_vector_preexists(self):
"""SWY test that model deletes a preexisting aggregate output result"""
from natcap.invest.seasonal_water_yield import seasonal_water_yield
# Set up data so there is enough code to do an aggregate over the
# rasters but the output vector already exists
aoi_path = os.path.join(self.workspace_dir, 'watershed.shp')
make_simple_shp(aoi_path, (1180000.0, 690000.0))
l_path = os.path.join(self.workspace_dir, 'L.tif')
make_recharge_raster(l_path)
aggregate_vector_path = os.path.join(self.workspace_dir,
'aggregated_results_swy.shp')
make_simple_shp(aggregate_vector_path, (1180000.0, 690000.0))
seasonal_water_yield._aggregate_recharge(aoi_path, l_path, l_path,
aggregate_vector_path)
# test if aggregate is expected
agg_results_csv_path = os.path.join(self.workspace_dir,
'agg_results_base.csv')
make_agg_results_csv(agg_results_csv_path, vector_exists=True)
result_vector = ogr.Open(aggregate_vector_path)
result_layer = result_vector.GetLayer()
incorrect_value_list = []
with open(agg_results_csv_path, 'r') as agg_result_file:
for line in agg_result_file:
fid, vri_sum, qb_val = [float(x) for x in line.split(',')]
feature = result_layer.GetFeature(int(fid))
for field, value in [('vri_sum', vri_sum), ('qb', qb_val)]:
if not numpy.isclose(
feature.GetField(field), value, rtol=1e-6):
incorrect_value_list.append(
'Unexpected value on feature %d, '
'expected %f got %f' %
(fid, value, feature.GetField(field)))
ogr.Feature.__swig_destroy__(feature)
feature = None
result_layer = None
ogr.DataSource.__swig_destroy__(result_vector)
result_vector = None
if incorrect_value_list:
raise AssertionError('\n' + '\n'.join(incorrect_value_list))
def test_aggregate_vector_preexists(self):
"""SWY test that model deletes a preexisting aggregate output result"""
from natcap.invest.seasonal_water_yield import seasonal_water_yield
# Set up data so there is enough code to do an aggregate over the
# rasters but the output vector already exists
for file_path in glob.glob(os.path.join(SAMPLE_DATA, "watershed.*")):
shutil.copy(file_path, self.workspace_dir)
aoi_path = os.path.join(SAMPLE_DATA, 'watershed.shp')
l_path = os.path.join(REGRESSION_DATA, 'L.tif')
aggregate_vector_path = os.path.join(
self.workspace_dir, 'watershed.shp')
seasonal_water_yield._aggregate_recharge(
aoi_path, l_path, l_path, aggregate_vector_path)
# test if aggregate is expected
tolerance_places = 1 # this was an experimentally acceptable value
agg_results_base_path = os.path.join(
REGRESSION_DATA, 'l_agg_results.csv')
result_vector = ogr.Open(aggregate_vector_path)
result_layer = result_vector.GetLayer()
incorrect_value_list = []
with open(agg_results_base_path, 'rb') as agg_result_file:
for line in agg_result_file:
fid, vri_sum, qb_val = [float(x) for x in line.split(',')]
feature = result_layer.GetFeature(int(fid))
for field, value in [('vri_sum', vri_sum), ('qb', qb_val)]:
if not numpy.isclose(
feature.GetField(field), value, rtol=1e-6):
incorrect_value_list.append(
'Unexpected value on feature %d, '
'expected %f got %f' % (
fid, value, feature.GetField(field)))
ogr.Feature.__swig_destroy__(feature)
feature = None
result_layer = None
ogr.DataSource.__swig_destroy__(result_vector)
result_vector = None
if incorrect_value_list:
raise AssertionError('\n' + '\n'.join(incorrect_value_list))