From 95fe74d633f5a9dd7415b891920e679d5661c658 Mon Sep 17 00:00:00 2001
From: Tom Close <tom.g.close@gmail.com>
Date: Thu, 12 Sep 2024 14:41:27 +1000
Subject: [PATCH] fixed up mypy errors

---
 extras/fileformats/extras/medimage/diffusion.py | 5 +++--
 extras/fileformats/extras/medimage/nifti.py     | 6 +++---
 fileformats/medimage/dicom.py                   | 4 ++--
 3 files changed, 8 insertions(+), 7 deletions(-)

diff --git a/extras/fileformats/extras/medimage/diffusion.py b/extras/fileformats/extras/medimage/diffusion.py
index 49bdb20..f8ec108 100644
--- a/extras/fileformats/extras/medimage/diffusion.py
+++ b/extras/fileformats/extras/medimage/diffusion.py
@@ -1,3 +1,4 @@
+import typing as ty
 import numpy as np
 import numpy.typing
 from fileformats.core import extra_implementation
@@ -5,12 +6,12 @@
 
 
 @extra_implementation(Bval.read_array)
-def bval_read_array(bval: Bval) -> numpy.typing.NDArray[np.floating]:  # noqa
+def bval_read_array(bval: Bval) -> numpy.typing.NDArray[np.floating[ty.Any]]:  # noqa
     return np.asarray([float(ln) for ln in bval.read_contents().split()])
 
 
 @extra_implementation(DwiEncoding.read_array)
-def bvec_read_array(bvec: Bvec) -> numpy.typing.NDArray[np.floating]:  # noqa
+def bvec_read_array(bvec: Bvec) -> numpy.typing.NDArray[np.floating[ty.Any]]:  # noqa
     bvals = bvec.b_values_file.read_array()
     directions = np.asarray(
         [[float(x) for x in ln.split()] for ln in bvec.read_contents().splitlines()]
diff --git a/extras/fileformats/extras/medimage/nifti.py b/extras/fileformats/extras/medimage/nifti.py
index a0c87a6..aa7bdfc 100644
--- a/extras/fileformats/extras/medimage/nifti.py
+++ b/extras/fileformats/extras/medimage/nifti.py
@@ -28,15 +28,15 @@
 def nifti_read_metadata(
     nifti: Nifti, selected_keys: ty.Optional[ty.Collection[str]] = None
 ) -> ty.Mapping[str, ty.Any]:
-    metadata = dict(nibabel.load(nifti.fspath).header)  # type: ignore[attr-defined]
+    metadata = dict(nibabel.load(nifti.fspath).header)
     if selected_keys:
         metadata = {k: v for k, v in metadata.items() if k in selected_keys}
     return metadata
 
 
 @extra_implementation(MedicalImage.read_array)
-def nifti_data_array(nifti: Nifti) -> numpy.typing.NDArray[np.floating]:  # noqa
-    return nibabel.load(nifti.fspath).get_data()  # type: ignore[attr-defined, no-any-return]
+def nifti_data_array(nifti: Nifti) -> numpy.typing.NDArray[np.floating[ty.Any]]:  # noqa
+    return nibabel.load(nifti.fspath).get_data()  # type: ignore[no-any-return]
 
 
 @extra_implementation(MedicalImage.vox_sizes)
diff --git a/fileformats/medimage/dicom.py b/fileformats/medimage/dicom.py
index 232e7ce..48465cb 100644
--- a/fileformats/medimage/dicom.py
+++ b/fileformats/medimage/dicom.py
@@ -62,7 +62,7 @@ def from_paths(
         fspaths : ty.Iterable[Path]
             the fspaths pointing to the DICOM files
         common_ok : bool, optional
-            included to match the signature of the overriden method, but ignored as each
+            included to match the signature of the overridden method, but ignored as each
             dicom should belong to only one series.
         selected_keys : ty.Optional[ty.Collection[str]], optional
             metadata keys to load from the DICOM files, typically used for performance
@@ -101,7 +101,7 @@ def dicom_collection_read_metadata(
     base_class: ty.Union[ty.Type[TypedSet], ty.Type[Directory]] = (
         TypedSet if isinstance(collection, DicomSeries) else Directory
     )
-    for dicom in base_class.contents.__get__(collection):  # type: ignore[union-attr, arg-type]
+    for dicom in base_class.contents.__get__(collection):  # type: ignore[arg-type]
         if selected_keys is not None:
             dicom = Dicom(dicom, metadata_keys=selected_keys)
         for key, val in dicom.metadata.items():