def test_dem(self):
task = SentinelHubDemTask(resolution=10,
feature=(FeatureType.DATA_TIMELESS, 'DEM'),
max_threads=3)
eopatch = task.execute(bbox=self.bbox)
dem = eopatch.data_timeless['DEM']
width, height = self.size
self.assertTrue(dem.shape == (height, width, 1))
def test_dem_cop(self):
task = SentinelHubDemTask(
data_collection=DataCollection.DEM_COPERNICUS_30,
resolution=10,
feature=(FeatureType.DATA_TIMELESS, 'DEM_30'),
max_threads=3)
eopatch = task.execute(bbox=self.bbox)
dem = eopatch.data_timeless['DEM_30']
width, height = self.size
self.assertTrue(dem.shape == (height, width, 1))
def test_dem_wrong_feature(self):
with self.assertRaises(
ValueError,
msg='Expected a ValueError when providing a wrong feature.'):
SentinelHubDemTask(resolution=10,
feature=(FeatureType.DATA, 'DEM'),
max_threads=3)
if __name__ == '__main__':
# path = 'E:/Data/PerceptiveSentinel'
path = '/home/beno/Documents/test/Slovenia/'
size_small = (337, 333)
size_big = (505, 500)
load = LoadTask(path, lazy_loading=True)
save_path_location = path
if not os.path.isdir(save_path_location):
os.makedirs(save_path_location)
save = SaveTask(save_path_location,
overwrite_permission=OverwritePermission.OVERWRITE_PATCH)
dem = SentinelHubDemTask((FeatureType.DATA_TIMELESS, 'DEM'), size=size_big)
grad = AddGradientTask((FeatureType.DATA_TIMELESS, 'DEM'),
(FeatureType.DATA_TIMELESS, 'INCLINATION'))
workflow = LinearWorkflow(load, dem, grad, save)
no_patches = 1061
execution_args = []
for i in range(no_patches):
i = i + 2
execution_args.append({
load: {
'eopatch_folder': 'eopatch_{}'.format(i)
},
save: {
def test_dem_wrong_feature(self):
with pytest.raises(ValueError):
SentinelHubDemTask(resolution=10,
feature=(FeatureType.DATA, "DEM"),
max_threads=3)
