Merge pull request #1115 from nipy/enh/type_annotations

ENH: Add minimal type annotations and run mypy in CI

Author: effigies

.github/workflows/misc.yml

@@ -24,7 +24,7 @@ jobs:
       matrix:
         python-version: ["3.10"]
         install: ['pip']
-        check: ['style', 'doctest']
+        check: ['style', 'doctest', 'typing']
         pip-flags: ['']
         depends: ['REQUIREMENTS']
     env:

.pre-commit-config.yaml

@@ -25,3 +25,15 @@ repos:
     hooks:
       - id: flake8
         exclude: "^(doc|nisext|tools)/"
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: v0.991
+    hooks:
+      - id: mypy
+        # Sync with project.optional-dependencies.typing
+        additional_dependencies:
+          - pytest
+          - types-setuptools
+          - types-Pillow
+          - pydicom
+        # Sync with tool.mypy['exclude']
+        exclude: "^(doc|nisext|tools)/|.*/tests/"

nibabel/analyze.py

@@ -81,14 +81,17 @@
 can be loaded with and without a default flip, so the saved zoom will not
 constrain the affine.
 """
+from __future__ import annotations
+
+from typing import Type
 
 import numpy as np
 
 from .arrayproxy import ArrayProxy
 from .arraywriters import ArrayWriter, WriterError, get_slope_inter, make_array_writer
 from .batteryrunners import Report
 from .fileholders import copy_file_map
-from .spatialimages import HeaderDataError, HeaderTypeError, SpatialImage
+from .spatialimages import HeaderDataError, HeaderTypeError, SpatialHeader, SpatialImage
 from .volumeutils import (
     apply_read_scaling,
     array_from_file,
@@ -131,7 +134,7 @@
     ('glmax', 'i4'),
     ('glmin', 'i4'),
 ]
-data_history_dtd = [
+data_history_dtd: list[tuple[str, str] | tuple[str, str, tuple[int, ...]]] = [
     ('descrip', 'S80'),
     ('aux_file', 'S24'),
     ('orient', 'S1'),
@@ -172,7 +175,7 @@
 data_type_codes = make_dt_codes(_dtdefs)
 
 
-class AnalyzeHeader(LabeledWrapStruct):
+class AnalyzeHeader(LabeledWrapStruct, SpatialHeader):
     """Class for basic analyze header
 
     Implements zoom-only setting of affine transform, and no image
@@ -892,11 +895,11 @@ def may_contain_header(klass, binaryblock):
 class AnalyzeImage(SpatialImage):
     """Class for basic Analyze format image"""
 
-    header_class = AnalyzeHeader
+    header_class: Type[AnalyzeHeader] = AnalyzeHeader
     _meta_sniff_len = header_class.sizeof_hdr
-    files_types = (('image', '.img'), ('header', '.hdr'))
-    valid_exts = ('.img', '.hdr')
-    _compressed_suffixes = ('.gz', '.bz2', '.zst')
+    files_types: tuple[tuple[str, str], ...] = (('image', '.img'), ('header', '.hdr'))
+    valid_exts: tuple[str, ...] = ('.img', '.hdr')
+    _compressed_suffixes: tuple[str, ...] = ('.gz', '.bz2', '.zst')
 
     makeable = True
     rw = True

nibabel/benchmarks/bench_arrayproxy_slicing.py

@@ -26,7 +26,7 @@
 
 # if memory_profiler is installed, we get memory usage results
 try:
-    from memory_profiler import memory_usage
+    from memory_profiler import memory_usage  # type: ignore
 except ImportError:
     memory_usage = None
 

nibabel/brikhead.py

@@ -27,7 +27,6 @@
 am aware) always be >= 1. This permits sub-brick indexing common in AFNI
 programs (e.g., example4d+orig'[0]').
 """
-
 import os
 import re
 from copy import deepcopy

nibabel/casting.py

@@ -3,6 +3,7 @@
 Most routines work round some numpy oddities in floating point precision and
 casting.  Others work round numpy casting to and from python ints
 """
+from __future__ import annotations
 
 import warnings
 from numbers import Integral
@@ -110,7 +111,7 @@ def float_to_int(arr, int_type, nan2zero=True, infmax=False):
 
 
 # Cache range values
-_SHARED_RANGES = {}
+_SHARED_RANGES: dict[tuple[type, type], tuple[np.number, np.number]] = {}
 
 
 def shared_range(flt_type, int_type):

nibabel/cmdline/dicomfs.py

@@ -25,7 +25,7 @@ class dummy_fuse:
 
 
 try:
-    import fuse
+    import fuse  # type: ignore
 
     uid = os.getuid()
     gid = os.getgid()

nibabel/ecat.py

@@ -50,7 +50,7 @@
 
 from .arraywriters import make_array_writer
 from .fileslice import canonical_slicers, predict_shape, slice2outax
-from .spatialimages import SpatialImage
+from .spatialimages import SpatialHeader, SpatialImage
 from .volumeutils import array_from_file, make_dt_codes, native_code, swapped_code
 from .wrapstruct import WrapStruct
 
@@ -243,7 +243,7 @@
 patient_orient_neurological = [1, 3, 5, 7]
 
 
-class EcatHeader(WrapStruct):
+class EcatHeader(WrapStruct, SpatialHeader):
     """Class for basic Ecat PET header
 
     Sub-parts of standard Ecat File

nibabel/externals/netcdf.py

@@ -871,6 +871,7 @@ def __setattr__(self, attr, value):
             pass
         self.__dict__[attr] = value
 
+    @property
     def isrec(self):
         """Returns whether the variable has a record dimension or not.
 
@@ -881,16 +882,15 @@ def isrec(self):
 
         """
         return bool(self.data.shape) and not self._shape[0]
-    isrec = property(isrec)
 
+    @property
     def shape(self):
         """Returns the shape tuple of the data variable.
 
         This is a read-only attribute and can not be modified in the
         same manner of other numpy arrays.
         """
         return self.data.shape
-    shape = property(shape)
 
     def getValue(self):
         """

nibabel/filebasedimages.py

@@ -7,9 +7,11 @@
 #
 ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
 """Common interface for any image format--volume or surface, binary or xml."""
+from __future__ import annotations
 
 import io
 from copy import deepcopy
+from typing import Type
 from urllib import request
 
 from .fileholders import FileHolder
@@ -74,7 +76,6 @@ class FileBasedImage:
 
     properties:
 
-       * shape
        * header
 
     methods:
@@ -118,25 +119,6 @@ class FileBasedImage:
 
        img.to_file_map()
 
-    You can get the data out again with::
-
-        img.get_fdata()
-
-    Less commonly, for some image types that support it, you might want to
-    fetch out the unscaled array via the object containing the data::
-
-        unscaled_data = img.dataoobj.get_unscaled()
-
-    Analyze-type images (including nifti) support this, but others may not
-    (MINC, for example).
-
-    Sometimes you might to avoid any loss of precision by making the
-    data type the same as the input::
-
-        hdr = img.header
-        hdr.set_data_dtype(data.dtype)
-        img.to_filename(fname)
-
     **Files interface**
 
     The image has an attribute ``file_map``.  This is a mapping, that has keys
@@ -158,20 +140,20 @@ class FileBasedImage:
     contain enough information so that an existing image instance can save
     itself back to the files pointed to in ``file_map``.  When a file holder
     holds active file-like objects, then these may be affected by the
-    initial file read; in this case, the contains file-like objects need to
+    initial file read; in this case, the file-like objects need to
     carry the position at which a write (with ``to_file_map``) should place the
     data.  The ``file_map`` contents should therefore be such, that this will
     work.
     """
 
-    header_class = FileBasedHeader
-    _meta_sniff_len = 0
-    files_types = (('image', None),)
-    valid_exts = ()
-    _compressed_suffixes = ()
+    header_class: Type[FileBasedHeader] = FileBasedHeader
+    _meta_sniff_len: int = 0
+    files_types: tuple[tuple[str, str | None], ...] = (('image', None),)
+    valid_exts: tuple[str, ...] = ()
+    _compressed_suffixes: tuple[str, ...] = ()
 
-    makeable = True  # Used in test code
-    rw = True  # Used in test code
+    makeable: bool = True  # Used in test code
+    rw: bool = True  # Used in test code
 
     def __init__(self, header=None, extra=None, file_map=None):
         """Initialize image