Unverified Commit 252a7fd7 authored by Nicola Soranzo's avatar Nicola Soranzo
Browse files

Fix type annotation for NumPy 2.3.0 

Fix the following issues in py313-test_galaxy_packages :

```
galaxy/tool_util/verify/asserts/image.py:763: error: Incompatible types in
assignment (expression has type "list[Any]", variable has type
"ndarray[tuple[Any, ...], dtype[Any]]")  [assignment]
            present_labels = [label for label in present_labels if label i...
                             ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...
galaxy/tool_util/verify/asserts/image.py:770: error: Incompatible types in
assignment (expression has type "list[Any]", variable has type
"ndarray[tuple[Any, ...], dtype[Any]]")  [assignment]
        present_labels = [label for label in present_labels if label not i...
                         ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...
galaxy/tool_util/verify/asserts/image.py:773: error: Incompatible return value
type (got
"tuple[ndarray[tuple[Any, ...], dtype[Any]], ndarray[tuple[Any, ...], dtype[Any]]]",
expected "tuple[ndarray[tuple[Any, ...], dtype[Any]], list[Any]]")
[return-value]
        return im_arr, present_labels
               ^~~~~~~~~~~~~~~~~~~~~~
```
parent 162fe283

lib/galaxy/tool_util/verify/asserts/image.py

+10 −10
Original line number Diff line number Diff line
@@ -320,19 +320,19 @@ CenterOfMassEps = Annotated[ 
    ),

]

Labels = Annotated[

    Optional[Union[str, List[int]]],

    Optional[Union[str, List[Union[float, int]]]],

    AssertionParameter(

        "List of labels, separated by a comma. Labels *not* on this list will be excluded from consideration. Cannot be used in combination with ``exclude_labels``.",

        xml_type="xs:string",

        json_type="typing.Optional[typing.List[int]]",

        json_type=f"typing.Optional[typing.List[{JSON_STRICT_NUMBER}]]",

    ),

]

ExcludeLabels = Annotated[

    Optional[Union[str, List[int]]],

    Optional[Union[str, List[Union[float, int]]]],

    AssertionParameter(

        "List of labels to be excluded from consideration, separated by a comma. The primary usage of this attribute is to exclude the background of a label image. Cannot be used in combination with ``labels``.",

        xml_type="xs:string",

        json_type="typing.Optional[typing.List[int]]",

        json_type=f"typing.Optional[typing.List[{JSON_STRICT_NUMBER}]]",

    ),

]

MeanObjectSize = Annotated[
@@ -734,8 +734,8 @@ def _get_image_labels( 
    channel: Optional[Union[int, str]] = None,

    slice: Optional[Union[int, str]] = None,

    frame: Optional[Union[int, str]] = None,

    labels: Optional[Union[str, List[int]]] = None,

    exclude_labels: Optional[Union[str, List[int]]] = None,

    labels: Labels = None,

    exclude_labels: ExcludeLabels = None,

) -> Tuple["numpy.typing.NDArray", List[Any]]:

    """

    Determines the unique labels in the output image or a specific channel.
@@ -743,7 +743,7 @@ def _get_image_labels( 
    assert labels is None or exclude_labels is None

    im_arr = _get_image(output_bytes, channel, slice, frame)



    def cast_label(label):

    def cast_label(label: str) -> Union[float, int]:

        label = label.strip()

        if numpy.issubdtype(im_arr.dtype, numpy.integer):

            return int(label)
@@ -752,12 +752,12 @@ def _get_image_labels( 
        raise AssertionError(f'Unsupported image label type: "{im_arr.dtype}"')



    # Determine labels present in the image.

    present_labels = numpy.unique(im_arr)

    present_labels: List[Any] = numpy.unique(im_arr).tolist()



    # Apply filtering due to `labels` (keep only those).

    if labels is None:

        labels = []

    if isinstance(labels, str):

    elif isinstance(labels, str):

        labels = [cast_label(label) for label in labels.split(",") if len(label) > 0]

    if len(labels) > 0:

        present_labels = [label for label in present_labels if label in labels]
@@ -765,7 +765,7 @@ def _get_image_labels( 
    # Apply filtering due to `exclude_labels`.

    if exclude_labels is None:

        exclude_labels = []

    if isinstance(exclude_labels, str):

    elif isinstance(exclude_labels, str):

        exclude_labels = [cast_label(label) for label in exclude_labels.split(",") if len(label) > 0]

    present_labels = [label for label in present_labels if label not in exclude_labels]