Script 'mail_helper' called by obssrc Hello community, here is the log from the commit of package python-scikit-umfpack for openSUSE:Factory checked in at 2022-04-04 19:26:32 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Comparing /work/SRC/openSUSE:Factory/python-scikit-umfpack (Old) and /work/SRC/openSUSE:Factory/.python-scikit-umfpack.new.1900 (New) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-scikit-umfpack" Mon Apr 4 19:26:32 2022 rev:6 rq:966736 version:0.3.2 Changes: -------- --- /work/SRC/openSUSE:Factory/python-scikit-umfpack/python-scikit-umfpack.changes 2021-09-09 23:07:55.072856981 +0200 +++ /work/SRC/openSUSE:Factory/.python-scikit-umfpack.new.1900/python-scikit-umfpack.changes 2022-04-04 19:26:54.696180121 +0200 @@ -1,0 +2,7 @@ +Sat Apr 2 20:13:01 UTC 2022 - Ben Greiner <c...@bnavigator.de> + +- Add scikit-umfpack-pr68-scipy-sparse-linalg.patch + gh#scikit-umfpack/scikit-umfpack#68 +- x86_64 is the only platform where this works + +------------------------------------------------------------------- New: ---- scikit-umfpack-pr68-scipy-sparse-linalg.patch ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Other differences: ------------------ ++++++ python-scikit-umfpack.spec ++++++ --- /var/tmp/diff_new_pack.vrMJTi/_old 2022-04-04 19:26:55.224174067 +0200 +++ /var/tmp/diff_new_pack.vrMJTi/_new 2022-04-04 19:26:55.228174021 +0200 @@ -1,7 +1,7 @@ # # spec file for package python-scikit-umfpack # -# Copyright (c) 2021 SUSE LLC +# Copyright (c) 2022 SUSE LLC # # All modifications and additions to the file contributed by third parties # remain the property of their copyright owners, unless otherwise agreed @@ -17,7 +17,6 @@ %{?!python_module:%define python_module() python-%{**} python3-%{**}} -%global skip_python36 1 %define oldpython python Name: python-scikit-umfpack Version: 0.3.2 @@ -27,6 +26,8 @@ URL: https://github.com/scikit-umfpack/scikit-umfpack Source0: https://files.pythonhosted.org/packages/source/s/scikit-umfpack/scikit-umfpack-%{version}.tar.gz Patch0: do-not-use-numpy-decorators.patch +# PATCH-FIX-UPSTREAM scikit-umfpack-pr68-scipy-sparse-linalg.patch -- gh#scikit-umfpack/scikit-umfpack68 +Patch1: scikit-umfpack-pr68-scipy-sparse-linalg.patch BuildRequires: %{python_module devel} BuildRequires: %{python_module numpy-devel >= 1.14.3} BuildRequires: %{python_module scipy >= 1.0.0rc1} @@ -40,7 +41,7 @@ BuildRequires: swig Requires: python-numpy >= 1.14.3 Requires: python-scipy >= 1.0.0rc1 -ExcludeArch: aarch64 ppc64 ppc64le +ExclusiveArch: x86_64 # SECTION test requirements BuildRequires: %{python_module pytest} # /SECTION @@ -81,6 +82,6 @@ %license LICENSE %dir %{python_sitearch}/scikits/ %{python_sitearch}/scikits/umfpack/ -%{python_sitearch}/scikit_umfpack-%{version}-py*.egg-info +%{python_sitearch}/scikit_umfpack-%{version}*-info %changelog ++++++ scikit-umfpack-pr68-scipy-sparse-linalg.patch ++++++ Index: scikit-umfpack-0.3.2/scikits/umfpack/tests/test_umfpack.py =================================================================== --- scikit-umfpack-0.3.2.orig/scikits/umfpack/tests/test_umfpack.py +++ scikit-umfpack-0.3.2/scikits/umfpack/tests/test_umfpack.py @@ -11,8 +11,7 @@ import warnings from numpy.testing import assert_array_almost_equal, run_module_suite from scipy import rand, matrix, diag, eye -from scipy.sparse import csc_matrix, spdiags, SparseEfficiencyWarning -from scipy.sparse.linalg import linsolve +from scipy.sparse import csc_matrix, linalg, spdiags, SparseEfficiencyWarning import numpy as np import scikits.umfpack as um @@ -45,51 +44,51 @@ class TestScipySolvers(_DeprecationAccep def test_solve_complex_umfpack(self): # Solve with UMFPACK: double precision complex - linsolve.use_solver(useUmfpack=True) + linalg.use_solver(useUmfpack=True) a = self.a.astype('D') b = self.b - x = linsolve.spsolve(a, b) + x = linalg.spsolve(a, b) assert_array_almost_equal(a*x, b) @unittest.skipIf(_is_32bit_platform, reason="requires 64 bit platform") def test_solve_complex_long_umfpack(self): # Solve with UMFPACK: double precision complex, long indices - linsolve.use_solver(useUmfpack=True) + linalg.use_solver(useUmfpack=True) a = _to_int64(self.a.astype('D')) b = self.b - x = linsolve.spsolve(a, b) + x = linalg.spsolve(a, b) assert_array_almost_equal(a*x, b) def test_solve_umfpack(self): # Solve with UMFPACK: double precision - linsolve.use_solver(useUmfpack=True) + linalg.use_solver(useUmfpack=True) a = self.a.astype('d') b = self.b - x = linsolve.spsolve(a, b) + x = linalg.spsolve(a, b) assert_array_almost_equal(a*x, b) @unittest.skipIf(_is_32bit_platform, reason="requires 64 bit platform") def test_solve_long_umfpack(self): # Solve with UMFPACK: double precision - linsolve.use_solver(useUmfpack=True) + linalg.use_solver(useUmfpack=True) a = _to_int64(self.a.astype('d')) b = self.b - x = linsolve.spsolve(a, b) + x = linalg.spsolve(a, b) assert_array_almost_equal(a*x, b) def test_solve_sparse_rhs(self): # Solve with UMFPACK: double precision, sparse rhs - linsolve.use_solver(useUmfpack=True) + linalg.use_solver(useUmfpack=True) a = self.a.astype('d') b = csc_matrix(self.b).T - x = linsolve.spsolve(a, b) + x = linalg.spsolve(a, b) assert_array_almost_equal(a*x, self.b) def test_factorized_umfpack(self): # Prefactorize (with UMFPACK) matrix for solving with multiple rhs - linsolve.use_solver(useUmfpack=True) + linalg.use_solver(useUmfpack=True) a = self.a.astype('d') - solve = linsolve.factorized(a) + solve = linalg.factorized(a) x1 = solve(self.b) assert_array_almost_equal(a*x1, self.b) @@ -99,9 +98,9 @@ class TestScipySolvers(_DeprecationAccep @unittest.skipIf(_is_32bit_platform, reason="requires 64 bit platform") def test_factorized_long_umfpack(self): # Prefactorize (with UMFPACK) matrix for solving with multiple rhs - linsolve.use_solver(useUmfpack=True) + linalg.use_solver(useUmfpack=True) a = _to_int64(self.a.astype('d')) - solve = linsolve.factorized(a) + solve = linalg.factorized(a) x1 = solve(self.b) assert_array_almost_equal(a*x1, self.b) @@ -110,9 +109,9 @@ class TestScipySolvers(_DeprecationAccep def test_factorized_without_umfpack(self): # Prefactorize matrix for solving with multiple rhs - linsolve.use_solver(useUmfpack=False) + linalg.use_solver(useUmfpack=False) a = self.a.astype('d') - solve = linsolve.factorized(a) + solve = linalg.factorized(a) x1 = solve(self.b) assert_array_almost_equal(a*x1, self.b)