ENH: Drop typing.Type for type

Author: effigies

nibabel/analyze.py

@@ -83,8 +83,6 @@
 """
 from __future__ import annotations
 
-from typing import Type
-
 import numpy as np
 
 from .arrayproxy import ArrayProxy
@@ -895,7 +893,7 @@ def may_contain_header(klass, binaryblock):
 class AnalyzeImage(SpatialImage):
     """Class for basic Analyze format image"""
 
-    header_class: Type[AnalyzeHeader] = AnalyzeHeader
+    header_class: type[AnalyzeHeader] = AnalyzeHeader
     header: AnalyzeHeader
     _meta_sniff_len = header_class.sizeof_hdr
     files_types: tuple[tuple[str, str], ...] = (('image', '.img'), ('header', '.hdr'))

nibabel/filebasedimages.py

@@ -12,7 +12,6 @@
 import io
 import typing as ty
 from copy import deepcopy
-from typing import Type
 from urllib import request
 
 from ._compression import COMPRESSION_ERRORS
@@ -158,7 +157,7 @@ class FileBasedImage:
     work.
     """
 
-    header_class: Type[FileBasedHeader] = FileBasedHeader
+    header_class: type[FileBasedHeader] = FileBasedHeader
     _meta_sniff_len: int = 0
     files_types: tuple[ExtensionSpec, ...] = (('image', None),)
     valid_exts: tuple[str, ...] = ()

nibabel/minc1.py

@@ -10,7 +10,6 @@
 from __future__ import annotations
 
 from numbers import Integral
-from typing import Type
 
 import numpy as np
 
@@ -307,7 +306,7 @@ class Minc1Image(SpatialImage):
     load.
     """
 
-    header_class: Type[MincHeader] = Minc1Header
+    header_class: type[MincHeader] = Minc1Header
     header: MincHeader
     _meta_sniff_len: int = 4
     valid_exts: tuple[str, ...] = ('.mnc',)

nibabel/nifti1.py

@@ -14,7 +14,6 @@
 
 import warnings
 from io import BytesIO
-from typing import Type
 
 import numpy as np
 import numpy.linalg as npl
@@ -90,8 +89,8 @@
 # datatypes not in analyze format, with codes
 if have_binary128():
     # Only enable 128 bit floats if we really have IEEE binary 128 longdoubles
-    _float128t: Type[np.generic] = np.longdouble
-    _complex256t: Type[np.generic] = np.longcomplex
+    _float128t: type[np.generic] = np.longdouble
+    _complex256t: type[np.generic] = np.longcomplex
 else:
     _float128t = np.void
     _complex256t = np.void