Create general function for constructing VerticalStack linop by itera…

…ting over axes

scico/linop/_diff.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-# Copyright (C) 2020-2023 by SCICO Developers
+# Copyright (C) 2020-2024 by SCICO Developers
 # All rights reserved. BSD 3-clause License.
 # This file is part of the SCICO package. Details of the copyright and
 # user license can be found in the 'LICENSE' file distributed with the
@@ -17,11 +17,10 @@
 import numpy as np
 
 import scico.numpy as snp
-from scico.numpy.util import parse_axes
 from scico.typing import Axes, DType, Shape
 
 from ._linop import LinearOperator
-from ._stack import VerticalStack
+from ._stack import VerticalStack, linop_over_axes
 
 
 class FiniteDifference(VerticalStack):
@@ -81,22 +80,16 @@ def __init__(
             jit: If ``True``, jit the evaluation, adjoint, and gram
                 functions of the :class:`LinearOperator`.
         """
-
-        if axes is None:
-            axes_list = tuple(range(len(input_shape)))
-        elif isinstance(axes, (list, tuple)):
-            axes_list = axes  # type: ignore
-        else:
-            axes_list = (axes,)
-        self.axes = parse_axes(axes_list, input_shape)
-        single_kwargs = dict(
-            input_dtype=input_dtype, prepend=prepend, append=append, circular=circular, jit=False
+        self.axes, ops = linop_over_axes(
+            SingleAxisFiniteDifference,
+            input_shape,
+            axes=axes,
+            input_dtype=input_dtype,
+            prepend=prepend,
+            append=append,
+            circular=circular,
+            jit=False,
         )
-        ops = [
-            SingleAxisFiniteDifference(input_shape, axis=axis, **single_kwargs)  # type: ignore
-            for axis in axes_list
-        ]
-
         super().__init__(
             ops,  # type: ignore
             jit=jit,

scico/linop/_stack.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-# Copyright (C) 2022-2023 by SCICO Developers
+# Copyright (C) 2022-2024 by SCICO Developers
 # All rights reserved. BSD 3-clause License.
 # This file is part of the SCICO package. Details of the copyright and
 # user license can be found in the 'LICENSE' file distributed with the
@@ -9,12 +9,14 @@
 
 from __future__ import annotations
 
-from typing import Optional, Sequence, Union
+from typing import Any, List, Optional, Sequence, Union
 
 import scico.numpy as snp
 from scico.numpy import Array, BlockArray
+from scico.numpy.util import parse_axes
 from scico.operator._stack import DiagonalStack as DStack
 from scico.operator._stack import VerticalStack as VStack
+from scico.typing import Axes, Shape
 
 from ._linop import LinearOperator
 
@@ -142,3 +144,46 @@ def _adj(self, y: Union[Array, BlockArray]) -> Union[Array, BlockArray]:  # type
         if self.collapse_input:
             return snp.stack(result)
         return snp.blockarray(result)
+
+
+def linop_over_axes(
+    linop: type[LinearOperator],
+    input_shape: Shape,
+    *args: Any,
+    axes: Optional[Axes] = None,
+    **kwargs: Any,
+) -> List[LinearOperator]:
+    """Construct a list of :class:`LinearOperator` by iterating over axes.
+
+    Construct a list of :class:`LinearOperator` by iterating over a
+    specified sequence of axes, passing each value in sequence to the
+    `axis` keyword argument of the :class:`LinearOperator` initializer.
+
+    Args:
+        linop: Type of :class:`LinearOperator` to construct for each axis.
+        input_shape: Shape of input array.
+        *args: Positional arguments for the :class:`LinearOperator`
+            initializer.
+        axes: Axis or axes over which to construct the list. If not
+            specified, or ``None``, use all axes corresponding to
+            `input_shape`.
+        **kwargs: Keyword arguments for the :class:`LinearOperator`
+            initializer.
+
+    Returns:
+        A tuple (`axes`, `ops`) where `axes` is a tuple of the axes used
+        to construct that list of list of :class:`LinearOperator`, and
+        `ops` is the list itself.
+    """
+    if axes is None:
+        axes = tuple(range(len(input_shape)))
+    elif not isinstance(axes, (list, tuple)):
+        axes = (axes,)
+    if axes is None:
+        axis_list = tuple(range(len(input_shape)))
+    elif isinstance(axes, (list, tuple)):
+        axis_list = axes  # type: ignore
+    else:
+        axis_list = (axes,)
+    axes = parse_axes(axes, input_shape)
+    return axes, [linop(input_shape, *args, axis=axis, **kwargs) for axis in axes]  # type: ignore