update

docs/source/conf.py

@@ -9,13 +9,17 @@
 # add these directories to sys.path here. If the directory is relative to the
 # documentation root, use os.path.abspath to make it absolute, like shown here.
 
+import ast
+import dataclasses
+import inspect
 import os
 import sys
+
 from sphinx_pyproject import SphinxConfig
-from urllib.parse import quote
 
-from mrpro  import __version__ as project_version
-config = SphinxConfig('../../pyproject.toml', globalns=globals(), config_overrides = {'version': project_version})
+from mrpro import __version__ as project_version
+
+config = SphinxConfig('../../pyproject.toml', globalns=globals(), config_overrides={'version': project_version})
 sys.path.insert(0, os.path.abspath('../../src'))  # Source code dir relative to this file
 
 # -- Project information -----------------------------------------------------
@@ -33,15 +37,13 @@
     'sphinx.ext.doctest',
     'sphinx.ext.autodoc',
     'sphinx.ext.autosummary',
-  #  'sphinx.ext.linkcode',
-  'sphinx_github_style',
+    'sphinx_github_style',
     'sphinx.ext.napoleon',
     'myst_nb',
     'sphinx.ext.mathjax',
     'sphinx-mathjax-offline',
     'sphinx.ext.intersphinx',
-  #  'sphinx_autodoc_typehints',
-
+    'sphinx_autodoc_typehints',
 ]
 intersphinx_mapping = {
     'torch': ('https://pytorch.org/docs/stable/', None),
@@ -58,17 +60,20 @@
 }
 
 napoleon_use_param = True
+napoleon_use_rtype = False
 typehints_defaults = 'comma'
 typehints_use_signature = True
 typehints_use_signature_return = True
+typehints_use_rtype = False
 autosummary_generate = True
 autosummary_imported_members = False
 autosummary_ignore_module_all = False
 autodoc_member_order = 'groupwise'
+autodoc_preserve_defaults = True
+autodoc_class_signature = 'separated'
 templates_path = ['_templates']
 exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
 source_suffix = {'.rst': 'restructuredtext', '.txt': 'restructuredtext', '.md': 'markdown'}
-autodoc_class_signature = 'separated'
 myst_enable_extensions = [
     'amsmath',
     'dollarmath',
@@ -96,24 +101,30 @@
     'github_version': 'main',
 }
 linkcode_blob = html_context['github_version']
-autodoc_preserve_defaults=True
 
 
-import inspect, ast,dataclasses
 def get_lambda_source(obj):
+    """Convert lambda to source code."""
     source = inspect.getsource(obj)
     for node in ast.walk(ast.parse(source.strip())):
         if isinstance(node, ast.Lambda):
             return ast.unparse(node.body)
-class DefaultValue():
+
+
+class DefaultValue:
+    """Used to store default values of dataclass fields with default factory."""
+
     def __init__(self, value):
         self.value = value
 
     def __repr__(self):
+        """This is called by sphinx when rendering the default value."""
         return self.value
 
+
 def rewrite_dataclass_init_default_factories(app, obj, bound_method) -> None:
-    if (not "init" in str(obj)
+    if (
+        not 'init' in str(obj)
         or not getattr(obj, '__defaults__', None)
         or not any(isinstance(d, dataclasses._HAS_DEFAULT_FACTORY_CLASS) for d in obj.__defaults__)
     ):
@@ -127,16 +138,16 @@ def rewrite_dataclass_init_default_factories(app, obj, bound_method) -> None:
         if field.default_factory is not dataclasses.MISSING:
             if not field.name in parameters:
                 continue
-            if field.default_factory.__name__ == "<lambda>":
-                defaults[field.name]  = DefaultValue(get_lambda_source(field.default_factory))
+            if field.default_factory.__name__ == '<lambda>':
+                defaults[field.name] = DefaultValue(get_lambda_source(field.default_factory))
             else:
-                defaults[field.name] = DefaultValue(field.default_factory.__name__ + "()")
-    new_defaults = tuple(defaults.get(name,param.default) for name, param in parameters.items() if param.default!=inspect._empty)
+                defaults[field.name] = DefaultValue(field.default_factory.__name__ + '()')
+    new_defaults = tuple(defaults.get(name, param.default) for name, param in parameters.items() if param.default != inspect._empty)
     obj.__defaults__ = new_defaults
 
+
 def setup(app):
     # forces mathjax on all pages
     app.set_html_assets_policy('always')
     # rewrite dataclass init signature
-    app.connect("autodoc-before-process-signature", rewrite_dataclass_init_default_factories)
-
+    app.connect('autodoc-before-process-signature', rewrite_dataclass_init_default_factories)

src/mrpro/data/KTrajectory.py

@@ -31,10 +31,10 @@ class KTrajectory(MoveDataMixin):
     """Trajectory in z direction / phase encoding direction k2 if Cartesian. Shape `(*other,k2,k1,k0)`"""
 
     ky: torch.Tensor
-    """Trajectory in y direction / phase encoding direction k1 if Cartesian. Shape (*other,k2,k1,k0)"""
+    """Trajectory in y direction / phase encoding direction k1 if Cartesian. Shape `(*other,k2,k1,k0)`"""
 
     kx: torch.Tensor
-    """Trajectory in x direction / phase encoding direction k0 if Cartesian. Shape (*other,k2,k1,k0)"""
+    """Trajectory in x direction / phase encoding direction k0 if Cartesian. Shape `(*other,k2,k1,k0)`"""
 
     grid_detection_tolerance: float = 1e-3
     """tolerance of how close trajectory positions have to be to integer grid points."""

src/mrpro/data/Rotation.py

@@ -906,7 +906,7 @@ def as_matrix(self) -> torch.Tensor:
         """Represent as rotation matrix.
 
         3D rotations can be represented using rotation matrices, which
-        are 3 x 3 real orthogonal matrices with determinant equal to +1 [ROTa]_
+        are 3 x 3 real orthogonal matrices with determinant equal to +1 [ROT]_
         for proper rotations and -1 for improper rotations.
 
         Returns
@@ -916,7 +916,7 @@ def as_matrix(self) -> torch.Tensor:
 
         References
         ----------
-        .. [ROTa] Rotation matrix https://en.wikipedia.org/wiki/Rotation_matrix#In_three_dimensions
+        .. [ROT] Rotation matrix https://en.wikipedia.org/wiki/Rotation_matrix#In_three_dimensions
         """
         quaternions = self._quaternions
         matrix = _quaternion_to_matrix(quaternions)

src/mrpro/operators/LinearOperator.py

@@ -114,14 +114,14 @@ def operator_norm(
             the function throws an `ValueError`.
         dim
             The dimensions of the tensors on which the operator operates. The choice of `dim` determines how
-            the operator norm is inperpreted.
-            For example, for a matrix-vector multiplication with a batched matrix tensor of shape
-            `(batch1, batch2, row, column)` and a batched input tensor of shape `(batch1, batch2, row)`:
+            the operator norm is inperpreted. For example, for a matrix-vector multiplication with a batched matrix
+            tensor of shape `(batch1, batch2, row, column)` and a batched input tensor of shape `(batch1, batch2, row)`:
             - If `dim=None`, the operator is considered as a block diagonal matrix with batch1*batch2 blocks
-              and the result is a tensor containing a single norm value (shape `(1, 1, 1)`).
+            and the result is a tensor containing a single norm value (shape `(1, 1, 1)`).
             - If `dim=(-1)`, `batch1*batch2` matrices are considered, and for each a separate operator norm is computed.
             - If `dim=(-1,-2)`, `batch1` matrices with `batch2` blocks are considered, and for each matrix a
-              separate operator norm is computed.
+            separate operator norm is computed.
+
             Thus, the choice of `dim` determines implicitly determines the domain of the operator.
         max_iterations
             maximum number of iterations