raise warning similar to numpy >= 2.0

README.md

@@ -82,5 +82,5 @@ The package also provides `mkl_fft._numpy_fft` and `mkl_fft._scipy_fft` interfac
 
 To build ``mkl_fft`` from sources on Linux:
   - install a recent version of MKL, if necessary;
-  - execute ``source /path_to_oneapi/mkl/latest/env/vars.sh`` ;
+  - execute ``source /path_to_oneapi/mkl/latest/env/vars.sh``;
   - execute ``python -m pip install .``

mkl_fft/_numpy_fft.py

@@ -71,7 +71,9 @@
 ]
 
 import re
+import warnings
 
+import numpy as np
 from numpy import array, asanyarray, conjugate, prod, sqrt, take
 
 from . import _float_utils
@@ -688,22 +690,46 @@ def ihfft(a, n=None, axis=-1, norm=None):
     return output
 
 
-def _cook_nd_args(a, s=None, axes=None, invreal=0):
+# copied from: https://github.com/numpy/numpy/blob/main/numpy/fft/_pocketfft.py
+def _cook_nd_args(a, s=None, axes=None, invreal=False):
     if s is None:
-        shapeless = 1
+        shapeless = True
         if axes is None:
             s = list(a.shape)
         else:
             s = take(a.shape, axes)
     else:
-        shapeless = 0
+        shapeless = False
     s = list(s)
     if axes is None:
+        if not shapeless and np.__version__ >= "2.0":
+            msg = (
+                "`axes` should not be `None` if `s` is not `None` "
+                "(Deprecated in NumPy 2.0). In a future version of NumPy, "
+                "this will raise an error and `s[i]` will correspond to "
+                "the size along the transformed axis specified by "
+                "`axes[i]`. To retain current behaviour, pass a sequence "
+                "[0, ..., k-1] to `axes` for an array of dimension k."
+            )
+            warnings.warn(msg, DeprecationWarning, stacklevel=3)
         axes = list(range(-len(s), 0))
     if len(s) != len(axes):
         raise ValueError("Shape and axes have different lengths.")
     if invreal and shapeless:
         s[-1] = (a.shape[axes[-1]] - 1) * 2
+    if None in s and np.__version__ >= "2.0":
+        msg = (
+            "Passing an array containing `None` values to `s` is "
+            "deprecated in NumPy 2.0 and will raise an error in "
+            "a future version of NumPy. To use the default behaviour "
+            "of the corresponding 1-D transform, pass the value matching "
+            "the default for its `n` parameter. To use the default "
+            "behaviour for every axis, the `s` argument can be omitted."
+        )
+        warnings.warn(msg, DeprecationWarning, stacklevel=3)
+    # use the whole input array along axis `i` if `s[i] == -1 or None`
+    s = [a.shape[_a] if _s in [-1, None] else _s for _s, _a in zip(s, axes)]
+
     return s, axes
 
 
@@ -808,6 +834,7 @@ def fftn(a, s=None, axes=None, norm=None):
     """
     _check_norm(norm)
     x = _float_utils.__downcast_float128_array(a)
+    s, axes = _cook_nd_args(x, s, axes)
 
     if norm in (None, "backward"):
         fsc = 1.0
@@ -920,6 +947,7 @@ def ifftn(a, s=None, axes=None, norm=None):
     """
     _check_norm(norm)
     x = _float_utils.__downcast_float128_array(a)
+    s, axes = _cook_nd_args(x, s, axes)
 
     if norm in (None, "backward"):
         fsc = 1.0
@@ -1215,16 +1243,15 @@ def rfftn(a, s=None, axes=None, norm=None):
     """
     _check_norm(norm)
     x = _float_utils.__downcast_float128_array(a)
+    s, axes = _cook_nd_args(x, s, axes)
 
     if norm in (None, "backward"):
         fsc = 1.0
     elif norm == "forward":
         x = asanyarray(x)
-        s, axes = _cook_nd_args(x, s, axes)
         fsc = frwd_sc_nd(s, x.shape)
     else:
         x = asanyarray(x)
-        s, axes = _cook_nd_args(x, s, axes)
         fsc = sqrt(frwd_sc_nd(s, x.shape))
 
     return trycall(
@@ -1369,16 +1396,15 @@ def irfftn(a, s=None, axes=None, norm=None):
     """
     _check_norm(norm)
     x = _float_utils.__downcast_float128_array(a)
+    s, axes = _cook_nd_args(x, s, axes, invreal=True)
 
     if norm in (None, "backward"):
         fsc = 1.0
     elif norm == "forward":
         x = asanyarray(x)
-        s, axes = _cook_nd_args(x, s, axes, invreal=1)
         fsc = frwd_sc_nd(s, x.shape)
     else:
         x = asanyarray(x)
-        s, axes = _cook_nd_args(x, s, axes, invreal=1)
         fsc = sqrt(frwd_sc_nd(s, x.shape))
 
     return trycall(

mkl_fft/_pydfti.pyx

@@ -1100,7 +1100,7 @@ def _fftnd_impl(x, s=None, axes=None, overwrite_x=False, direction=+1, double fs
                 _direct_fftnd,
                 {'overwrite_x': overwrite_x, 'direction': direction, 'fsc': fsc},
                 res
-                )
+            )
         else:
             sc = <object> fsc
             return _iter_fftnd(x, s=s, axes=axes,
@@ -1200,7 +1200,7 @@ def rfftn(x, s=None, axes=None, fwd_scale=1.0):
             a = _fix_dimensions(a, tuple(ss), axes)
         if len(set(axes)) == len(axes) and len(axes) == a.ndim and len(axes) > 2:
             ss, aa = _remove_axis(s, axes, -1)
-            ind = [slice(None,None,1),] * len(s)
+            ind = [slice(None, None, 1),] * len(s)
             for ii in range(a.shape[la]):
                 ind[la] = ii
                 tind = tuple(ind)

mkl_fft/tests/test_interfaces.py

@@ -121,6 +121,7 @@ def test_scipy_rfftn(norm, dtype):
     assert np.allclose(x, xx, atol=tol, rtol=tol)
 
 
+@pytest.mark.filterwarnings("ignore::DeprecationWarning")
 @pytest.mark.parametrize("norm", [None, "forward", "backward", "ortho"])
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 def test_numpy_rfftn(norm, dtype):

mkl_fft/tests/test_pocketfft.py

@@ -510,7 +510,7 @@ def test_s_negative_1(self, op):
         # should use the whole input array along the first axis
         assert op(x, s=(-1, 5), axes=(0, 1)).shape == (10, 5)
 
-    @pytest.mark.skip("no warning is raised in mkl_ftt")
+    @pytest.mark.skipif(np.__version__ < "2.0", reason="Requires numpy >= 2.0")
     @pytest.mark.parametrize(
         "op", [mkl_fft.fftn, mkl_fft.ifftn, mkl_fft.rfftn, mkl_fft.irfftn]
     )
@@ -519,14 +519,14 @@ def test_s_axes_none(self, op):
         with pytest.warns(match="`axes` should not be `None` if `s`"):
             op(x, s=(-1, 5))
 
-    @pytest.mark.skip("no warning is raised in mkl_ftt")
+    @pytest.mark.skipif(np.__version__ < "2.0", reason="Requires numpy >= 2.0")
     @pytest.mark.parametrize("op", [mkl_fft.fft2, mkl_fft.ifft2])
     def test_s_axes_none_2D(self, op):
         x = np.arange(100).reshape(10, 10)
         with pytest.warns(match="`axes` should not be `None` if `s`"):
             op(x, s=(-1, 5), axes=None)
 
-    @pytest.mark.skip("no warning is raised in mkl_ftt")
+    @pytest.mark.skipif(np.__version__ < "2.0", reason="Requires numpy >= 2.0")
     @pytest.mark.parametrize(
         "op",
         [