MTN fix compat numpy2

.github/workflows/pypi_upload.yml

@@ -21,7 +21,7 @@ jobs:
       - name: Install Python 3
         uses: actions/setup-python@v4
         with:
-          python-version: 3.8
+          python-version: 3.12
       - name: Install dependencies
         run: |
           $CONDA/bin/conda config --env --append channels conda-forge

.github/workflows/pytest.yml

@@ -16,7 +16,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.9", "3.10"]
+        python-version: ["3.11", "3.12"]
         os: [ubuntu-latest, macOS-latest, windows-latest]
 
     steps:

.readthedocs.yaml

@@ -7,9 +7,9 @@ version: 2
 
 # Set the version of Python and other tools you might need
 build:
-  os: ubuntu-20.04
+  os: ubuntu-22.04
   tools:
-    python: "3.9"
+    python: "3.11"
   apt_packages:
     - graphviz
 

LICENSE

@@ -1,6 +1,6 @@
 BSD 3-Clause License
 
-Copyright (c) 2015-2022, Triad National Security, LLC.
+Copyright (c) 2015-2025, Triad National Security, LLC.
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without

docs/source/automodule.py

@@ -29,9 +29,13 @@ def _fix_disable(cls, nstnm):
     coattr.append(co.co_posonlyargcount)
 coattr.extend([co.co_kwonlyargcount, co.co_nlocals, co.co_stacksize,
                co.co_flags, _fix_disable.__code__.co_code, co.co_consts,
-               co.co_names, co.co_varnames, co.co_filename, co.co_name,
-               co.co_firstlineno, co.co_lnotab, co.co_freevars,
-               co.co_cellvars])
+               co.co_names, co.co_varnames, co.co_filename, co.co_name])
+if hasattr(co, 'co_qualname'):
+    coattr.append(co.co_qualname)
+coattr.extend([co.co_firstlineno, co.co_lnotab])
+if hasattr(co, 'co_exceptiontable'):
+    coattr.append(co.co_exceptiontable)
+coattr.extend([co.co_freevars, co.co_cellvars])
 sporco.common._fix_nested_class_lookup.__code__ = CodeType(*coattr)
 
 

docs/source/conf.py

@@ -311,13 +311,14 @@
 
 
 # Intersphinx mapping
-intersphinx_mapping = {'https://docs.python.org/3/': None,
-                       'https://numpy.org/doc/stable/': None,
-                       'https://docs.scipy.org/doc/scipy/reference/': None,
-                       'https://matplotlib.org/': None,
-                       'http://hgomersall.github.io/pyFFTW/': None,
-                       'https://docs.cupy.dev/en/stable/': None
-                      }
+intersphinx_mapping = {
+    "python": ("https://docs.python.org/3/", None),
+    "numpy": ("https://numpy.org/doc/stable/", None),
+    "scipy": ("https://docs.scipy.org/doc/scipy/", None),
+    "matplotlib": ("https://matplotlib.org/stable/", None),
+    "pyfftw": ("http://hgomersall.github.io/pyFFTW/", None),
+    "cupy": ("https://docs.cupy.dev/en/stable/", None)
+}
 # Added timeout due to periodic scipy.org down time
 #intersphinx_timeout = 30
 

docs/source/modules/index.rst

@@ -119,8 +119,3 @@ API Reference
    sporco.dictlrn.onlinecdl
    sporco.cuda
    sporco.cupy
-   sporco.fista.bpdn
-   sporco.fista.cbpdn
-   sporco.fista.ccmod
-   sporco.fista.fista
-   sporco.fista.ppp

docs/source/modules/sporco.cuda.rst

@@ -43,12 +43,12 @@ The content of the ``sporco.cuda`` namespace is summarised below. For full detai
 Always available
 ~~~~~~~~~~~~~~~~
 
-.. np:attribute:: have_cuda
+.. py:attribute:: have_cuda
 
    A boolean value indicating whether the import of ``sporco_cuda`` succeeded.
 
 
-.. np:function:: device_count()
+.. py:function:: device_count()
 
    Get the number of CUDA GPU devices installed on the host system. Returns 0
    if no devices are installed or if the import of ``sporco_cuda`` failed.
@@ -62,7 +62,7 @@ Always available
 Only available if ``have_cuda`` is `True`
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. np:function:: current_device(id=None)
+.. py:function:: current_device(id=None)
 
    Get or set the current CUDA GPU device. The current device is not set
    if `id` is None.
@@ -79,7 +79,7 @@ Only available if ``have_cuda`` is `True`
 
 
 
-.. np:function:: memory_info()
+.. py:function:: memory_info()
 
    Get memory information for the current CUDA GPU device.
 
@@ -92,7 +92,7 @@ Only available if ``have_cuda`` is `True`
 
 
 
-.. np:function:: device_name(int dev=0)
+.. py:function:: device_name(int dev=0)
 
    Get hardware model name for the specified CUDA GPU device.
 
@@ -108,7 +108,7 @@ Only available if ``have_cuda`` is `True`
 
 
 
-.. np:function:: cbpdn(D, S, lmbda, opt, dev=0)
+.. py:function:: cbpdn(D, S, lmbda, opt, dev=0)
 
    A GPU-accelerated version of :class:`.admm.cbpdn.ConvBPDN`. Multiple
    images and multi-channel images in input signal ``S`` are currently not
@@ -136,7 +136,7 @@ Only available if ``have_cuda`` is `True`
 
 
 
-.. np:function:: cbpdngrd(D, S, lmbda, mu, opt, dev=0)
+.. py:function:: cbpdngrd(D, S, lmbda, mu, opt, dev=0)
 
    A GPU-accelerated version of :class:`.admm.cbpdn.ConvBPDNGradReg`.
    Multiple images and multi-channel images in input signal ``S`` are
@@ -166,7 +166,7 @@ Only available if ``have_cuda`` is `True`
 
 
 
-.. np:function:: cbpdnmsk(D, s, w, lmbda, opt, dev=0)
+.. py:function:: cbpdnmsk(D, s, w, lmbda, opt, dev=0)
 
    A GPU-accelerated version of :class:`.admm.cbpdn.AddMaskSim` used
    together with :class:`.admm.cbpdn.ConvBPDN`, providing a spatial
@@ -208,7 +208,7 @@ Only available if ``have_cuda`` is `True`
 
 
 
-.. np:function:: cbpdngrdmsk(D, s, w, lmbda, mu, opt, dev=0)
+.. py:function:: cbpdngrdmsk(D, s, w, lmbda, mu, opt, dev=0)
 
    A GPU-accelerated version of of :class:`.admm.cbpdn.AddMaskSim`
    used together with :class:`.admm.cbpdn.ConvBPDNGradReg`, providing

docs/source/modules/sporco.cupy.rst

@@ -84,25 +84,25 @@ Utility Functions
 Since it is necessary to explicitly convert between `NumPy <http://www.numpy.org/>`__ arrays and `CuPy <https://cupy.chainer.org/>`__ arrays, a number of utility functions in ``sporco.cupy`` support this conversion in a way that behaves correctly independent of the value of ``sporco.cupy.have_cupy``, in that conversion is performed when the value is ``True``, and no conversion is perfomed when it is ``False``.
 
 
-.. np:function:: array_module(*args)
+.. py:function:: array_module(*args)
 
    Get the array module (``numpy`` or ``cupy``) of the array argument. This
    function is an alias for :func:`cupy.get_array_module`.
 
 
-.. np:function:: np2cp(u)
+.. py:function:: np2cp(u)
 
    Convert a ``numpy`` ndarray to a ``cupy`` array. This function is an alias
    for :func:`cupy.asarray`
 
 
-.. np:function:: cp2np(u)
+.. py:function:: cp2np(u)
 
    Convert a ``cupy`` array to a ``numpy`` ndarray. This function is an alias
    for :func:`cupy.asnumpy`
 
 
-.. np:function:: cupy_wrapper(func)
+.. py:function:: cupy_wrapper(func)
 
    A wrapper function that converts ``numpy`` ndarray arguments to ``cupy``
    arrays, and convert any ``cupy`` arrays returned by the wrapped function
@@ -116,14 +116,14 @@ Since it is necessary to explicitly convert between `NumPy <http://www.numpy.org
 Some additional utility functions provide useful functionality when package `GPUtil <https://github.com/anderskm/gputil>`__ is installed, and return fixed default return values when it is not installed:
 
 
-.. np:function:: gpu_info()
+.. py:function:: gpu_info()
 
    Return a list of namedtuples representing attributes of each GPU
    device. Returns an empty list if
    `GPUtil <https://github.com/anderskm/gputil>`_ is not installed.
 
 
-.. np:function:: gpu_load(wproc=0.5, wmem=0.5)
+.. py:function:: gpu_load(wproc=0.5, wmem=0.5)
 
    Return a list of namedtuples representing the current load for
    each GPU device. The processor and memory loads are fractions
@@ -133,21 +133,21 @@ Some additional utility functions provide useful functionality when package `GPU
    `GPUtil <https://github.com/anderskm/gputil>`_ is not installed.
 
 
-.. np:function:: device_by_load(wproc=0.5, wmem=0.5)
+.. py:function:: device_by_load(wproc=0.5, wmem=0.5)
 
    Get a list of GPU device ids ordered by increasing weighted
    average of processor and memory load. Returns an empty list if
    `GPUtil <https://github.com/anderskm/gputil>`_ is not installed.
 
 
-.. np:function:: select_device_by_load(wproc=0.5, wmem=0.5)
+.. py:function:: select_device_by_load(wproc=0.5, wmem=0.5)
 
    Set the current device for cupy as the device with the lowest
    weighted average of processor and memory load. Returns 0 if
    `GPUtil <https://github.com/anderskm/gputil>`_ is not installed.
 
 
-.. np:function:: available_gpu(*args, **kwargs)
+.. py:function:: available_gpu(*args, **kwargs)
 
    Get the device id for an available GPU when multiple GPUs are installed.
    This function is an alias for ``GPUtil.getAvailable``. Returns 0 if

examples/scripts/sc/gwnden_clr.py

@@ -46,14 +46,14 @@
 blocks = array.extract_blocks(imgn, blksz, stpsz)
 blockmeans = np.mean(blocks, axis=(0, 1))
 blocks -= blockmeans
-blocks = blocks.reshape(np.product(blksz), -1)
+blocks = blocks.reshape(np.prod(blksz), -1)
 
 
 """
 Load dictionary.
 """
 
-D = util.convdicts()['RGB:8x8x3x64'].reshape(np.product(blksz), -1)
+D = util.convdicts()['RGB:8x8x3x64'].reshape(np.prod(blksz), -1)
 
 
 """

requirements.txt

@@ -1,6 +1,6 @@
 future
-numpy>=1.12
-scipy>=0.19.1
+numpy>=1.26.4
+scipy>=1.12.0
 imageio
 matplotlib>=1.3.1
 pyfftw>=0.10.4

sporco/admm/admm.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-# Copyright (C) 2015-2020 by Brendt Wohlberg <brendt@ieee.org>
+# Copyright (C) 2015-2025 by Brendt Wohlberg <brendt@ieee.org>
 # All rights reserved. BSD 3-clause License.
 # This file is part of the SPORCO package. Details of the copyright
 # and user license can be found in the 'LICENSE.txt' file distributed
@@ -235,7 +235,7 @@ def __init__(self, Nx, yshape, ushape, dtype, opt=None):
         self.Nx = Nx
         # Working variable U has the same dimensionality as constant c
         # in the constraint Ax + By = c
-        self.Nc = np.product(np.array(ushape))
+        self.Nc = np.prod(np.array(ushape))
 
         # DataType option overrides data type inferred from __init__
         # parameters of derived class
@@ -862,7 +862,7 @@ def __init__(self, xshape, dtype, opt=None):
 
         if opt is None:
             opt = ADMMEqual.Options()
-        Nx = np.product(np.array(xshape))
+        Nx = np.prod(np.array(xshape))
         super(ADMMEqual, self).__init__(Nx, xshape, xshape, dtype, opt)
 
 

sporco/admm/cbpdntv.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-# Copyright (C) 2016-2019 by Brendt Wohlberg <brendt@ieee.org>
+# Copyright (C) 2016-2025 by Brendt Wohlberg <brendt@ieee.org>
 # All rights reserved. BSD 3-clause License.
 # This file is part of the SPORCO package. Details of the copyright
 # and user license can be found in the 'LICENSE.txt' file distributed
@@ -199,7 +199,7 @@ def __init__(self, D, S, lmbda, mu=0.0, opt=None, dimK=None, dimN=2):
         self.cri = cr.CSC_ConvRepIndexing(D, S, dimK=dimK, dimN=dimN)
 
         # Call parent class __init__
-        Nx = np.product(np.array(self.cri.shpX))
+        Nx = np.prod(np.array(self.cri.shpX))
         yshape = self.cri.shpX + (len(self.cri.axisN)+1,)
         super(ConvBPDNScalarTV, self).__init__(Nx, yshape, yshape,
                                                S.dtype, opt)
@@ -908,7 +908,7 @@ def __init__(self, D, S, lmbda, mu=0.0, opt=None, dimK=None, dimN=2):
         self.cri = cr.CSC_ConvRepIndexing(D, S, dimK=dimK, dimN=dimN)
 
         # Call parent class __init__
-        Nx = np.product(np.array(self.cri.shpX))
+        Nx = np.prod(np.array(self.cri.shpX))
         yshape = list(self.cri.shpX)
         yshape[self.cri.axisM] += len(self.cri.axisN) * self.cri.Cd
         super(ConvBPDNRecTV, self).__init__(Nx, yshape, yshape,

sporco/admm/parcbpdn.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
-# Copyright (C) 2018 by Erik Skau <ewskau@gmail.com>
-#                       Brendt Wohlberg <brendt@ieee.org>
+# Copyright (C) 2018-2025 by Erik Skau <ewskau@gmail.com>
+#                            Brendt Wohlberg <brendt@ieee.org>
 # All rights reserved. BSD 3-clause License.
 # This file is part of the SPORCO package. Details of the copyright
 # and user license can be found in the 'LICENSE.txt' file distributed
@@ -105,7 +105,7 @@ def mpraw_as_np(shape, dtype):
       Numpy array
     """
 
-    sz = int(np.product(shape))
+    sz = int(np.prod(shape))
     csz = sz * np.dtype(dtype).itemsize
     raw = mp.RawArray('c', csz)
     return np.frombuffer(raw, dtype=dtype, count=sz).reshape(shape)