Allow newer numpy versions (#697)

* allow newer numpy versions
* fix types
* Merge branch 'master' of github.com:scalableminds/webknossos-libs into allow-new-numpy
* do not use numpy.typing module which was introduced in 1.20 to remain backwards compatible
* Merge branch 'master' into allow-new-numpy

Author: daniel-wer

wkcuber/poetry.lock

@@ -19,7 +19,7 @@ GitPython = "^3.0.5"
 imagecodecs = "^2020.5.30"
 natsort = "^6.2.0"
 nibabel = "^2.5.1"
-numpy = "1.19.5"
+numpy = "^1.19.5"
 pillow = ">=6.2.1,<9.0.0"
 requests = "^2.22.0"
 scikit-image = "^0.18.3"

wkcuber/pyproject.toml

@@ -38,16 +38,20 @@ def test_element_class_conversion(tmp_path: Path) -> None:
 
     refresh_metadata(test_wkw_path)
 
-    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

wkcuber/tests/test_metadata.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,
         (

wkcuber/wkcuber/convert_nifti.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
     )