MAINT: next round of 1.9.0 backports

.github/workflows/linux_meson.yml

@@ -101,6 +101,7 @@ jobs:
     - name: Test SciPy
       run: |
         export OMP_NUM_THREADS=2
+        export SCIPY_USE_PROPACK=1
         python dev.py -n -j 2
 
   test_venv_install:

.github/workflows/macos_meson.yml

@@ -112,6 +112,7 @@ jobs:
       run: |
         conda activate scipy-dev
         export OMP_NUM_THREADS=2
+        export SCIPY_USE_PROPACK=1
         python dev.py -n -j 2
 
     - name: Ccache statistics

.github/workflows/windows.yml

@@ -79,6 +79,7 @@ jobs:
       - name: prep-test
         run: |
           echo "PYTHONPATH=${env:installed_path}" >> $env:GITHUB_ENV
+          echo "SCIPY_USE_PROPACK=1" >> $env:GITHUB_ENV
       - name: test
         run: |
           mkdir tmp

azure-pipelines.yml

@@ -182,7 +182,7 @@ stages:
             curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py && \
             python3.8 get-pip.py && \
             pip3 --version && \
-            pip3 install setuptools==59.6.0 wheel numpy==1.18.5 cython==0.29.21 pybind11 pytest pytest-timeout pytest-xdist pytest-env pytest-cov Pillow mpmath pythran==0.10.0 && \
+            pip3 install setuptools==59.6.0 wheel numpy==1.18.5 cython==0.29.21 pybind11 pytest pytest-timeout pytest-xdist pytest-env pytest-cov Pillow mpmath pythran==0.11.0 && \
             apt-get -y install gcc-5 g++-5 gfortran-8 wget && \
             cd .. && \
             mkdir openblas && cd openblas && \
@@ -295,7 +295,7 @@ stages:
         numpy==1.21.4
         Pillow
         pybind11
-        pythran==0.10.0
+        pythran==0.11.0
         pytest
         pytest-cov
         pytest-env

doc/source/_static/scipy.css

@@ -38,18 +38,21 @@ Nat Methods 8, 441 (2011). https://doi.org/10.1038/nmeth.1618
 #version_switcher_button[data-active-version-name*="dev"] {
   background-color: #E69F00;
   border-color: #E69F00;
+  color: white;
 }
 
 /* green for `stable` */
 #version_switcher_button[data-active-version-name*="stable"] {
   background-color: #009E73;
   border-color: #009E73;
+  color: white;
 }
 
 /* red for `old` */
 #version_switcher_button:not([data-active-version-name*="stable"]):not([data-active-version-name*="dev"]):not([data-active-version-name*="pull"]) {
   background-color: #980F0F;
   border-color: #980F0F;
+  color: white;
 }
 
 /* Taken from NumPy */
@@ -159,3 +162,40 @@ h3 {
   margin-bottom: 0rem;
   color: #484848;
 }
+
+
+/* Dark theme tweaking
+
+Matplotlib images are in png and inverted while other output
+types are assumed to be normal images.
+
+*/
+html[data-theme=dark] img[src*='.png'] {
+    filter: invert(0.82) brightness(0.8) contrast(1.2);
+}
+
+html[data-theme=dark] .MathJax_SVG *  {
+    fill: var(--pst-color-text-base);
+}
+
+/* Main index page overview cards */
+html[data-theme=dark] .shadow {
+    box-shadow: 0 .5rem 1rem rgba(250, 250, 250, .6) !important
+}
+
+html[data-theme=dark] .intro-card .card-header {
+  background-color:var(--pst-color-background);
+  color: #150458 !important;
+}
+
+html[data-theme=dark] .intro-card .card-footer {
+  background-color:var(--pst-color-background);
+}
+
+html[data-theme=dark] h1 {
+  color: var(--pst-color-primary);
+}
+
+html[data-theme=dark] h3 {
+  color: #0a6774;
+}

doc/source/conf.py

@@ -185,9 +185,9 @@
 html_favicon = '_static/favicon.ico'
 
 html_theme_options = {
-  "logo_link": "index",
   "github_url": "https://github.com/scipy/scipy",
-  "navbar_end": ["version-switcher", "navbar-icon-links"],
+  "twitter_url": "https://twitter.com/SciPy_team",
+  "navbar_end": ["theme-switcher", "version-switcher", "navbar-icon-links"],
   "switcher": {
       "json_url": "https://scipy.github.io/devdocs/_static/version_switcher.json",
       "version_match": version,

doc_requirements.txt

@@ -1,7 +1,7 @@
 # Note: this should disappear at some point. For now, please keep it
 #       in sync with the doc dependencies in pyproject.toml
-Sphinx!=3.1.0, !=4.1.0
-pydata-sphinx-theme>=0.8.1
+Sphinx!=4.1.0
+pydata-sphinx-theme>=0.9.0
 sphinx-panels>=0.5.2
 sphinx-tabs
 numpydoc

environment.yml

@@ -18,7 +18,7 @@ dependencies:
   - pkg-config  # note: not available on Windows
   - libblas=*=*openblas  # helps avoid pulling in MKL
   - pybind11
-  - pythran>=0.9.12
+  - pythran>=0.11.0
   # For testing and benchmarking
   - pytest
   - pytest-cov
@@ -32,7 +32,7 @@ dependencies:
   - numpydoc
   - ipython
   - matplotlib
-  - pydata-sphinx-theme>=0.8.1
+  - pydata-sphinx-theme>=0.9.0
   - sphinx-panels
   - sphinx-tabs
   # For linting

pyproject.toml

@@ -13,7 +13,7 @@ requires = [
     "meson-python>=0.5.0",
     "Cython>=0.29.21",
     "pybind11>=2.4.3",
-    "pythran>=0.9.12",
+    "pythran>=0.11.0",
     # `wheel` is needed for non-isolated builds, given that `meson-python`
     # doesn't list it as a runtime requirement (at least in 0.5.0)
     "wheel",
@@ -101,8 +101,8 @@ test = [
     "scikit-umfpack",
 ]
 doc = [
-    "sphinx!=3.1.0, !=4.1.0",
-    "pydata-sphinx-theme>=0.8.1",
+    "sphinx!=4.1.0",
+    "pydata-sphinx-theme>=0.9.0",
     "sphinx-panels>=0.5.2",
     "matplotlib>2",
     "numpydoc",

scipy/optimize/tests/test_linprog.py

@@ -2,6 +2,7 @@
 Unit test for Linear Programming
 """
 import sys
+import platform
 
 import numpy as np
 from numpy.testing import (assert_, assert_allclose, assert_equal,
@@ -2199,6 +2200,10 @@ class TestLinprogHiGHSMIP():
     method = "highs"
     options = {}
 
+    @pytest.mark.xfail(condition=(sys.maxsize < 2 ** 32 and
+                       platform.system() == "Linux"),
+                       run=False,
+                       reason="gh-16347")
     def test_mip1(self):
         # solve non-relaxed magic square problem (finally!)
         # also check that values are all integers - they don't always

scipy/optimize/tests/test_milp.py

@@ -57,8 +57,10 @@ def test_milp_iv():
         milp([1, 2, 3], bounds=([1, 2, 3], [set(), 4, 5]))
 
 
-@pytest.mark.xfail(strict=True, reason="Needs to be fixed in `_highs_wrapper`")
+@pytest.mark.xfail(run=False,
+                   reason="Needs to be fixed in `_highs_wrapper`")
 def test_milp_options(capsys):
+    # run=False now because of gh-16347
     message = "Unrecognized options detected: {'ekki'}..."
     options = {'ekki': True}
     with pytest.warns(RuntimeWarning, match=message):

scipy/sparse/linalg/_eigen/_svds.py

@@ -1,3 +1,4 @@
+import os
 import numpy as np
 
 from .arpack import _arpack  # type: ignore[attr-defined]
@@ -6,7 +7,11 @@
 from scipy._lib._util import check_random_state
 from scipy.sparse.linalg._interface import LinearOperator, aslinearoperator
 from scipy.sparse.linalg._eigen.lobpcg import lobpcg  # type: ignore[no-redef]
-from scipy.sparse.linalg._svdp import _svdp
+if os.environ.get("SCIPY_USE_PROPACK"):
+    from scipy.sparse.linalg._svdp import _svdp
+    HAS_PROPACK = True
+else:
+    HAS_PROPACK = False
 from scipy.linalg import svd
 
 arpack_int = _arpack.timing.nbx.dtype
@@ -297,6 +302,12 @@ def matmat_XH_X(x):
         eigvec, _ = np.linalg.qr(eigvec)
 
     elif solver == 'propack':
+        if not HAS_PROPACK:
+            raise ValueError("`solver='propack'` is opt-in due "
+                             "to potential issues on Windows, "
+                             "it can be enabled by setting the "
+                             "`SCIPY_USE_PROPACK` environment "
+                             "variable before importing scipy")
         jobu = return_singular_vectors in {True, 'u'}
         jobv = return_singular_vectors in {True, 'vh'}
         irl_mode = (which == 'SM')

scipy/sparse/linalg/_eigen/tests/test_svds.py

@@ -1,3 +1,4 @@
+import os
 import re
 import copy
 import numpy as np
@@ -8,6 +9,10 @@
 from scipy.linalg import hilbert, svd, null_space
 from scipy.sparse import csc_matrix, isspmatrix, spdiags, random
 from scipy.sparse.linalg import LinearOperator, aslinearoperator
+if os.environ.get("SCIPY_USE_PROPACK"):
+    has_propack = True
+else:
+    has_propack = False
 from scipy.sparse.linalg import svds
 from scipy.sparse.linalg._eigen.arpack import ArpackNoConvergence
 
@@ -157,6 +162,8 @@ def test_svds_input_validation_k_1(self, k):
 
         # propack can do complete SVD
         if self.solver == 'propack' and k == 3:
+            if not has_propack:
+                pytest.skip("PROPACK not enabled")
             res = svds(A, k=k, solver=self.solver)
             _check_svds(A, k, *res, check_usvh_A=True, check_svd=True)
             return
@@ -257,6 +264,9 @@ def test_svds_input_validation_return_singular_vectors(self, rsv):
     @pytest.mark.parametrize("k", [3, 5])
     @pytest.mark.parametrize("which", ["LM", "SM"])
     def test_svds_parameter_k_which(self, k, which):
+        if self.solver == 'propack':
+            if not has_propack:
+                pytest.skip("PROPACK not available")
         # check that the `k` parameter sets the number of eigenvalues/
         # eigenvectors returned.
         # Also check that the `which` parameter sets whether the largest or
@@ -274,6 +284,9 @@ def test_svds_parameter_k_which(self, k, which):
 
     # loop instead of parametrize for simplicity
     def test_svds_parameter_tol(self):
+        if self.solver == 'propack':
+            if not has_propack:
+                pytest.skip("PROPACK not available")
         return  # TODO: needs work, disabling for now
         # check the effect of the `tol` parameter on solver accuracy by solving
         # the same problem with varying `tol` and comparing the eigenvalues
@@ -315,6 +328,9 @@ def err(tol):
             assert error > accuracy/10
 
     def test_svd_v0(self):
+        if self.solver == 'propack':
+            if not has_propack:
+                pytest.skip("PROPACK not available")
         # check that the `v0` parameter affects the solution
         n = 100
         k = 1
@@ -347,6 +363,9 @@ def test_svd_v0(self):
             assert_equal(res1a, res1b)
 
     def test_svd_random_state(self):
+        if self.solver == 'propack':
+            if not has_propack:
+                pytest.skip("PROPACK not available")
         # check that the `random_state` parameter affects the solution
         # Admittedly, `n` and `k` are chosen so that all solver pass all
         # these checks. That's a tall order, since LOBPCG doesn't want to
@@ -379,6 +398,10 @@ def test_svd_random_state(self):
                                               np.random.RandomState(0),
                                               np.random.default_rng(0)))
     def test_svd_random_state_2(self, random_state):
+        if self.solver == 'propack':
+            if not has_propack:
+                pytest.skip("PROPACK not available")
+
         n = 100
         k = 1
 
@@ -397,6 +420,10 @@ def test_svd_random_state_2(self, random_state):
                                               np.random.RandomState(0),
                                               np.random.default_rng(0)))
     def test_svd_random_state_3(self, random_state):
+        if self.solver == 'propack':
+            if not has_propack:
+                pytest.skip("PROPACK not available")
+
         n = 100
         k = 5
 
@@ -417,6 +444,9 @@ def test_svd_random_state_3(self, random_state):
     def test_svd_maxiter(self):
         # check that maxiter works as expected: should not return accurate
         # solution after 1 iteration, but should with default `maxiter`
+        if self.solver == 'propack':
+            if not has_propack:
+                pytest.skip("PROPACK not available")
         A = hilbert(6)
         k = 1
         u, s, vh = sorted_svd(A, k)
@@ -443,6 +473,10 @@ def test_svd_maxiter(self):
     @pytest.mark.parametrize("shape", ((5, 7), (6, 6), (7, 5)))
     def test_svd_return_singular_vectors(self, rsv, shape):
         # check that the return_singular_vectors parameter works as expected
+        if self.solver == 'propack':
+            if not has_propack:
+                pytest.skip("PROPACK not available")
+
         rng = np.random.default_rng(0)
         A = rng.random(shape)
         k = 2
@@ -521,6 +555,10 @@ def test_svd_return_singular_vectors(self, rsv, shape):
                                          aslinearoperator))
     def test_svd_simple(self, A, k, real, transpose, lo_type):
 
+        if self.solver == 'propack':
+            if not has_propack:
+                pytest.skip("PROPACK not available")
+
         A = np.asarray(A)
         A = np.real(A) if real else A
         A = A.T if transpose else A
@@ -547,6 +585,9 @@ def test_svd_simple(self, A, k, real, transpose, lo_type):
 
     def test_svd_linop(self):
         solver = self.solver
+        if self.solver == 'propack':
+            if not has_propack:
+                pytest.skip("PROPACK not available")
 
         nmks = [(6, 7, 3),
                 (9, 5, 4),
@@ -720,6 +761,8 @@ def test_svd_LM_zeros_matrix(self, shape, dtype):
     # ARPACK supports only dtype float, complex, or np.float32
     @pytest.mark.parametrize("dtype", (float, complex, np.float32))
     def test_small_sigma(self, shape, dtype):
+        if not has_propack:
+            pytest.skip("PROPACK not enabled")
         # https://github.com/scipy/scipy/pull/11829
         if dtype == complex and self.solver == 'propack':
             pytest.skip("PROPACK unsupported for complex dtype")
@@ -743,6 +786,8 @@ def test_small_sigma(self, shape, dtype):
     @pytest.mark.filterwarnings("ignore:The problem size")
     @pytest.mark.parametrize("dtype", (float, complex, np.float32))
     def test_small_sigma2(self, dtype):
+        if not has_propack:
+            pytest.skip("PROPACK not enabled")
         # https://github.com/scipy/scipy/issues/11406
         if dtype == complex and self.solver == 'propack':
             pytest.skip("PROPACK unsupported for complex dtype")

scipy/spatial/_qhull.pyx

@@ -2822,8 +2822,9 @@ class HalfspaceIntersection(_QhullUser):
 
         # Run qhull
         mode_option = "H"
-        qhull = _Qhull(mode_option.encode(), halfspaces, qhull_options, required_options=None,
-                       incremental=incremental, interior_point=interior_point)
+        qhull = _Qhull(mode_option.encode(), halfspaces, qhull_options,
+                       required_options=None, incremental=incremental,
+                       interior_point=self.interior_point)
 
         _QhullUser.__init__(self, qhull, incremental=incremental)