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)