MAINT: Bump Array API to 2024.12 (scipy#22687)

* Bump Array API to 2024.12

* nit [skip ci]

---------

Co-authored-by: Lucas Colley <[email protected]>

Author: crusaderky

pyproject.toml

@@ -82,7 +82,7 @@ test = [
     "scikit-umfpack",
     "pooch",
     "hypothesis>=6.30",
-    "array-api-strict>=2.0,<2.1.1",
+    "array-api-strict>=2.3",
     "Cython",
     "meson",
     'ninja; sys_platform != "emscripten"',

pytest.ini

@@ -17,7 +17,6 @@ filterwarnings =
     ignore:.*`numpy.core` has been made officially private.*:DeprecationWarning
     ignore:.*In the future `np.long` will be defined as.*:FutureWarning
     ignore:.*JAX is multithreaded.*:RuntimeWarning
-    ignore:.*The 2023.12 version of the array API specification is still preliminary.*:UserWarning
     ignore:^Using the slower implmentation::cupy
     ignore:Using the slower implementation::cupy
     ignore:Jitify is performing a one-time only warm-up::cupy

scipy/conftest.py

@@ -143,8 +143,8 @@ def num_parallel_threads():
     try:
         import array_api_strict
         xp_available_backends.update({'array_api_strict': array_api_strict})
-        if _pep440.parse(array_api_strict.__version__) < _pep440.Version('2.0'):
-            raise ImportError("array-api-strict must be >= version 2.0")
+        if _pep440.parse(array_api_strict.__version__) < _pep440.Version('2.3'):
+            raise ImportError("array-api-strict must be >= version 2.3")
         array_api_strict.set_array_api_strict_flags(
             api_version='2024.12'
         )

scipy/integrate/_tanhsinh.py

@@ -470,10 +470,7 @@ def customize_result(res, shape):
         # If the integration limits were such that b < a, we reversed them
         # to perform the calculation, and the final result needs to be negated.
         if log and xp.any(negative):
-            dtype = res['integral'].dtype
-            pi = xp.asarray(xp.pi, dtype=dtype)[()]
-            j = xp.asarray(1j, dtype=xp.complex64)[()]  # minimum complex type
-            res['integral'] = res['integral'] + negative*pi*j
+            res['integral'] = res['integral'] + negative * xp.pi * 1.0j
         else:
             res['integral'][negative] *= -1
 

scipy/signal/tests/test_windows.py

@@ -499,7 +499,6 @@ def test_basic(self, xp):
                                     0.5985765418119844], dtype=xp.float64))
 
 
-@skip_xp_backends("torch", reason="implementation needs 2023.12 standard")
 class TestKaiserBesselDerived:
 
     def test_basic(self, xp):

scipy/special/_logsumexp.py

@@ -225,8 +225,7 @@ def _logsumexp(a, b, axis, return_sign, xp):
             m = xp.abs(m)
         else:
             # `a_max` can have a sign component for complex input
-            j = xp.asarray(1j, dtype=a_max.dtype)
-            sgn = sgn * xp.exp(xp.imag(a_max) * j)
+            sgn = sgn * xp.exp(xp.imag(a_max) * 1.0j)
 
     # Take log and undo shift
     out = xp.log1p(s) + xp.log(m) + a_max

scipy/stats/_morestats.py

@@ -2892,14 +2892,13 @@ def bartlett(*samples, axis=0):
     ssq = [arr[xp.newaxis, ...] for arr in ssq]
     Ni = xp.concat(Ni, axis=0)
     ssq = xp.concat(ssq, axis=0)
-    # sum dtype can be removed when 2023.12 rules kick in
     dtype = Ni.dtype
-    Ntot = xp.sum(Ni, axis=0, dtype=dtype)
+    Ntot = xp.sum(Ni, axis=0)
     spsq = xp.sum((Ni - 1)*ssq, axis=0, dtype=dtype) / (Ntot - k)
     numer = ((Ntot - k) * xp.log(spsq)
              - xp.sum((Ni - 1)*xp.log(ssq), axis=0, dtype=dtype))
     denom = (1 + 1/(3*(k - 1))
-             * ((xp.sum(1/(Ni - 1), axis=0, dtype=dtype)) - 1/(Ntot - k)))
+             * ((xp.sum(1/(Ni - 1), axis=0)) - 1/(Ntot - k)))
     T = numer / denom
 
     chi2 = _SimpleChi2(xp.asarray(k-1))