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check_element_class_of_layer(test_wkw_path, "prediction", "float", np.float32) - check_element_class_of_layer(test_wkw_path, "segmentation", "double", np.float64) - check_element_class_of_layer(test_wkw_path, "color", "uint24", np.uint8) + check_element_class_of_layer( + test_wkw_path, "prediction", "float", np.dtype(np.float32) + ) + check_element_class_of_layer( + test_wkw_path, "segmentation", "double", np.dtype(np.float64) + ) + check_element_class_of_layer(test_wkw_path, "color", "uint24", np.dtype(np.uint8)) def check_element_class_of_layer( test_wkw_path: Path, layer_name: str, expected_element_class: str, - expected_dtype: type, + expected_dtype: np.dtype, ) -> None: datasource_properties = read_datasource_properties(test_wkw_path) layer_to_check = None diff --git a/wkcuber/wkcuber/convert_nifti.py b/wkcuber/wkcuber/convert_nifti.py index e9ac102ff..614b2907f 100644 --- a/wkcuber/wkcuber/convert_nifti.py +++ b/wkcuber/wkcuber/convert_nifti.py @@ -196,7 +196,6 @@ def convert_nifti( # Writing wkw compressed requires files of shape (shard_size, shard_size, shard_size) # Pad data accordingly padding_offset = shard_size - np.array(cube_data.shape[1:4]) % shard_size - padding_offset = (0, 0, 0) cube_data = np.pad( cube_data, ( diff --git a/wkcuber/wkcuber/convert_raw.py b/wkcuber/wkcuber/convert_raw.py index 82d72a1cd..16c5abef7 100644 --- a/wkcuber/wkcuber/convert_raw.py +++ b/wkcuber/wkcuber/convert_raw.py @@ -143,7 +143,7 @@ def _raw_chunk_converter( flip_axes: Optional[Union[int, Tuple[int, ...]]], ) -> None: logging.info(f"Conversion of {bounding_box.topleft}") - source_data = np.memmap( + source_data: np.memmap = np.memmap( source_raw_path, dtype=input_dtype, mode="r", shape=(1,) + shape, order=order )