include a test

.github/workflows/conda-package-cf.yml

@@ -117,7 +117,7 @@ jobs:
       - name: Install mkl_fft
         run: |
           CHANNELS="-c $GITHUB_WORKSPACE/channel ${{ env.CHANNELS }}"
-          conda create -n ${{ env.TEST_ENV_NAME }} python=${{ matrix.python_ver }} ${{ matrix.numpy }} $PACKAGE_NAME pytest $CHANNELS
+          conda create -n ${{ env.TEST_ENV_NAME }} python=${{ matrix.python_ver }} ${{ matrix.numpy }} $PACKAGE_NAME pytest scipy $CHANNELS
           # Test installed packages
           conda list -n ${{ env.TEST_ENV_NAME }}
       - name: Run tests
@@ -268,7 +268,7 @@ jobs:
              SET PACKAGE_VERSION=%%F
           )
           SET "TEST_DEPENDENCIES=pytest pytest-cov"
-          conda install -n ${{ env.TEST_ENV_NAME }} ${{ env.PACKAGE_NAME }}=%PACKAGE_VERSION% %TEST_DEPENDENCIES% python=${{ matrix.python }} ${{ matrix.numpy }} -c ${{ env.workdir }}/channel ${{ env.CHANNELS }}
+          conda install -n ${{ env.TEST_ENV_NAME }} ${{ env.PACKAGE_NAME }}=%PACKAGE_VERSION% %TEST_DEPENDENCIES% python=${{ matrix.python }} ${{ matrix.numpy }} scipy -c ${{ env.workdir }}/channel ${{ env.CHANNELS }}
       - name: Report content of test environment
         shell: cmd /C CALL {0}
         run: |

.github/workflows/conda-package.yml

@@ -116,7 +116,7 @@ jobs:
       - name: Install mkl_fft
         run: |
           CHANNELS="-c $GITHUB_WORKSPACE/channel ${{ env.CHANNELS }}"
-          conda create -n ${{ env.TEST_ENV_NAME }} python=${{ matrix.python }} $PACKAGE_NAME pytest $CHANNELS
+          conda create -n ${{ env.TEST_ENV_NAME }} python=${{ matrix.python }} $PACKAGE_NAME scipy pytest $CHANNELS
           # Test installed packages
           conda list -n ${{ env.TEST_ENV_NAME }}
       - name: Run tests
@@ -267,7 +267,7 @@ jobs:
              SET PACKAGE_VERSION=%%F
           )
           SET "TEST_DEPENDENCIES=pytest pytest-cov"
-          conda install -n ${{ env.TEST_ENV_NAME }} ${{ env.PACKAGE_NAME }}=%PACKAGE_VERSION% %TEST_DEPENDENCIES% python=${{ matrix.python }} -c ${{ env.workdir }}/channel ${{ env.CHANNELS }}
+          conda install -n ${{ env.TEST_ENV_NAME }} ${{ env.PACKAGE_NAME }}=%PACKAGE_VERSION% %TEST_DEPENDENCIES% python=${{ matrix.python }} scipy -c ${{ env.workdir }}/channel ${{ env.CHANNELS }}
       - name: Report content of test environment
         shell: cmd /C CALL {0}
         run: |

.gitignore

@@ -3,7 +3,8 @@ build/
 mkl_fft.egg-info/
 mkl_fft/__pycache__/
 mkl_fft/_pydfti.c
-mkl_fft/_pydfti.cpython-310-x86_64-linux-gnu.so
+mkl_fft/_pydfti.cpython*.so
 mkl_fft/interfaces/__pycache__/
 mkl_fft/src/mklfft.c
 mkl_fft/tests/__pycache__/
+mkl_fft/tests/from_scipy/__pycache__/

conda-recipe-cf/meta.yaml

@@ -32,6 +32,7 @@ test:
       - pytest -v --pyargs mkl_fft
     requires:
       - pytest
+      - scipy
     imports:
       - mkl_fft
       - mkl_fft.interfaces

conda-recipe/meta.yaml

@@ -32,6 +32,7 @@ test:
       - pytest -v --pyargs mkl_fft
     requires:
       - pytest
+      - scipy
     imports:
       - mkl_fft
       - mkl_fft.interfaces

mkl_fft/__init__.py

@@ -24,6 +24,7 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
+
 import mkl_fft.interfaces
 
 from . import _init_helper

mkl_fft/_fft_utils.py

@@ -0,0 +1,51 @@
+#!/usr/bin/env python
+# Copyright (c) 2025, Intel Corporation
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+#     * Redistributions of source code must retain the above copyright notice,
+#       this list of conditions and the following disclaimer.
+#     * Redistributions in binary form must reproduce the above copyright
+#       notice, this list of conditions and the following disclaimer in the
+#       documentation and/or other materials provided with the distribution.
+#     * Neither the name of Intel Corporation nor the names of its contributors
+#       may be used to endorse or promote products derived from this software
+#       without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+import numpy as np
+
+__all__ = ["check_norm", "compute_fwd_scale"]
+
+
+def check_norm(norm):
+    if norm not in (None, "ortho", "forward", "backward"):
+        raise ValueError(
+            f"Invalid norm value {norm} should be None, 'ortho', 'forward', "
+            "or 'backward'."
+        )
+
+
+def compute_fwd_scale(norm, n, shape):
+    check_norm(norm)
+    if norm in (None, "backward"):
+        return 1.0
+
+    ss = n if n is not None else shape
+    nn = np.prod(ss)
+    fsc = 1 / nn if nn != 0 else 1
+    if norm == "forward":
+        return fsc
+    else:  # norm == "ortho"
+        return np.sqrt(fsc)

mkl_fft/_float_utils.py

@@ -91,5 +91,5 @@ def __supported_array_or_not_implemented(x):
     if hasattr(np, "complex256"):
         black_list.append(np.complex256)
     if __x.dtype in black_list:
-        return NotImplemented
+        raise NotImplementedError
     return __x

mkl_fft/_numpy_fft.py

@@ -74,36 +74,59 @@
 import warnings
 
 import numpy as np
-from numpy import array, conjugate, prod, sqrt, take
 
-from . import _float_utils
-from . import _pydfti as mkl_fft  # pylint: disable=no-name-in-module
+import mkl_fft
 
+from ._fft_utils import check_norm, compute_fwd_scale
+from ._float_utils import __downcast_float128_array
 
-def _compute_fwd_scale(norm, n, shape):
-    _check_norm(norm)
-    if norm in (None, "backward"):
-        return 1.0
 
-    ss = n if n is not None else shape
-    nn = prod(ss)
-    fsc = 1 / nn if nn != 0 else 1
-    if norm == "forward":
-        return fsc
-    else:  # norm == "ortho"
-        return sqrt(fsc)
-
-
-def _check_norm(norm):
-    if norm not in (None, "ortho", "forward", "backward"):
-        raise ValueError(
-            f"Invalid norm value {norm} should be None, 'ortho', 'forward', "
-            "or 'backward'."
+# copied with modifications 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 = True
+        if axes is None:
+            s = list(a.shape)
+        else:
+            s = np.take(a.shape, axes)
+    else:
+        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
 
 
 def _swap_direction(norm):
-    _check_norm(norm)
+    check_norm(norm)
     _swap_direction_map = {
         "backward": "forward",
         None: "forward",
@@ -218,8 +241,8 @@ def fft(a, n=None, axis=-1, norm=None):
 
     """
 
-    x = _float_utils.__downcast_float128_array(a)
-    fsc = _compute_fwd_scale(norm, n, x.shape[axis])
+    x = __downcast_float128_array(a)
+    fsc = compute_fwd_scale(norm, n, x.shape[axis])
 
     return trycall(mkl_fft.fft, (x,), {"n": n, "axis": axis, "fwd_scale": fsc})
 
@@ -311,8 +334,8 @@ def ifft(a, n=None, axis=-1, norm=None):
 
     """
 
-    x = _float_utils.__downcast_float128_array(a)
-    fsc = _compute_fwd_scale(norm, n, x.shape[axis])
+    x = __downcast_float128_array(a)
+    fsc = compute_fwd_scale(norm, n, x.shape[axis])
 
     return trycall(mkl_fft.ifft, (x,), {"n": n, "axis": axis, "fwd_scale": fsc})
 
@@ -402,8 +425,8 @@ def rfft(a, n=None, axis=-1, norm=None):
 
     """
 
-    x = _float_utils.__downcast_float128_array(a)
-    fsc = _compute_fwd_scale(norm, n, x.shape[axis])
+    x = __downcast_float128_array(a)
+    fsc = compute_fwd_scale(norm, n, x.shape[axis])
 
     return trycall(mkl_fft.rfft, (x,), {"n": n, "axis": axis, "fwd_scale": fsc})
 
@@ -495,8 +518,8 @@ def irfft(a, n=None, axis=-1, norm=None):
 
     """
 
-    x = _float_utils.__downcast_float128_array(a)
-    fsc = _compute_fwd_scale(norm, n, 2 * (x.shape[axis] - 1))
+    x = __downcast_float128_array(a)
+    fsc = compute_fwd_scale(norm, n, 2 * (x.shape[axis] - 1))
 
     return trycall(
         mkl_fft.irfft, (x,), {"n": n, "axis": axis, "fwd_scale": fsc}
@@ -581,10 +604,10 @@ def hfft(a, n=None, axis=-1, norm=None):
     """
 
     norm = _swap_direction(norm)
-    x = _float_utils.__downcast_float128_array(a)
-    x = array(x, copy=True, dtype=complex)
-    conjugate(x, out=x)
-    fsc = _compute_fwd_scale(norm, n, 2 * (x.shape[axis] - 1))
+    x = __downcast_float128_array(a)
+    x = np.array(x, copy=True, dtype=complex)
+    np.conjugate(x, out=x)
+    fsc = compute_fwd_scale(norm, n, 2 * (x.shape[axis] - 1))
 
     return trycall(
         mkl_fft.irfft, (x,), {"n": n, "axis": axis, "fwd_scale": fsc}
@@ -651,61 +674,18 @@ def ihfft(a, n=None, axis=-1, norm=None):
 
     # The copy may be required for multithreading.
     norm = _swap_direction(norm)
-    x = _float_utils.__downcast_float128_array(a)
-    x = array(x, copy=True, dtype=float)
-    fsc = _compute_fwd_scale(norm, n, x.shape[axis])
+    x = __downcast_float128_array(a)
+    x = np.array(x, copy=True, dtype=float)
+    fsc = compute_fwd_scale(norm, n, x.shape[axis])
 
     output = trycall(
         mkl_fft.rfft, (x,), {"n": n, "axis": axis, "fwd_scale": fsc}
     )
 
-    conjugate(output, out=output)
+    np.conjugate(output, out=output)
     return output
 
 
-# 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 = True
-        if axes is None:
-            s = list(a.shape)
-        else:
-            s = take(a.shape, axes)
-    else:
-        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
-
-
 def fftn(a, s=None, axes=None, norm=None):
     """
     Compute the N-dimensional discrete Fourier Transform.
@@ -806,9 +786,9 @@ def fftn(a, s=None, axes=None, norm=None):
 
     """
 
-    x = _float_utils.__downcast_float128_array(a)
+    x = __downcast_float128_array(a)
     s, axes = _cook_nd_args(x, s, axes)
-    fsc = _compute_fwd_scale(norm, s, x.shape)
+    fsc = compute_fwd_scale(norm, s, x.shape)
 
     return trycall(mkl_fft.fftn, (x,), {"s": s, "axes": axes, "fwd_scale": fsc})
 
@@ -913,9 +893,9 @@ def ifftn(a, s=None, axes=None, norm=None):
 
     """
 
-    x = _float_utils.__downcast_float128_array(a)
+    x = __downcast_float128_array(a)
     s, axes = _cook_nd_args(x, s, axes)
-    fsc = _compute_fwd_scale(norm, s, x.shape)
+    fsc = compute_fwd_scale(norm, s, x.shape)
 
     return trycall(
         mkl_fft.ifftn, (x,), {"s": s, "axes": axes, "fwd_scale": fsc}
@@ -1201,9 +1181,9 @@ def rfftn(a, s=None, axes=None, norm=None):
 
     """
 
-    x = _float_utils.__downcast_float128_array(a)
+    x = __downcast_float128_array(a)
     s, axes = _cook_nd_args(x, s, axes)
-    fsc = _compute_fwd_scale(norm, s, x.shape)
+    fsc = compute_fwd_scale(norm, s, x.shape)
 
     return trycall(
         mkl_fft.rfftn, (x,), {"s": s, "axes": axes, "fwd_scale": fsc}
@@ -1345,9 +1325,9 @@ def irfftn(a, s=None, axes=None, norm=None):
 
     """
 
-    x = _float_utils.__downcast_float128_array(a)
+    x = __downcast_float128_array(a)
     s, axes = _cook_nd_args(x, s, axes, invreal=True)
-    fsc = _compute_fwd_scale(norm, s, x.shape)
+    fsc = compute_fwd_scale(norm, s, x.shape)
 
     return trycall(
         mkl_fft.irfftn, (x,), {"s": s, "axes": axes, "fwd_scale": fsc}

mkl_fft/_pydfti.pyx

@@ -1335,11 +1335,11 @@ def ifftn(x, s=None, axes=None, overwrite_x=False, fwd_scale=1.0):
 
 
 def rfft2(x, s=None, axes=(-2, -1), fwd_scale=1.0):
-    return rfftn(x, s=s, axes=axes, fsc=fwd_scale)
+    return rfftn(x, s=s, axes=axes, fwd_scale=fwd_scale)
 
 
 def irfft2(x, s=None, axes=(-2, -1), fwd_scale=1.0):
-    return irfftn(x, s=s, axes=axes, fsc=fwd_scale)
+    return irfftn(x, s=s, axes=axes, fwd_scale=fwd_scale)
 
 
 def _remove_axis(s, axes, axis_to_remove):