update _scipy_fft.py (#145)

* create a new util file

* update _scipy_fft.py

* update _scipy_fftpack.py

* add new scipy tests

* get rid of double leading underscore

Author: vtavana

.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 pytest scipy $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

@@ -1,9 +1,10 @@
-_vendored/__pycache__/
+# CMake build and local install directory
 build/
 mkl_fft.egg-info/
-mkl_fft/__pycache__/
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+
 mkl_fft/_pydfti.c
-mkl_fft/_pydfti.cpython-310-x86_64-linux-gnu.so
-mkl_fft/interfaces/__pycache__/
+mkl_fft/_pydfti.cpython*.so
 mkl_fft/src/mklfft.c
-mkl_fft/tests/__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/_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

@@ -27,13 +27,13 @@
 import numpy as np
 
 __all__ = [
-    "__upcast_float16_array",
-    "__downcast_float128_array",
-    "__supported_array_or_not_implemented",
+    "_upcast_float16_array",
+    "_downcast_float128_array",
+    "_supported_array_or_not_implemented",
 ]
 
 
-def __upcast_float16_array(x):
+def _upcast_float16_array(x):
     """
     Used in _scipy_fft to upcast float16 to float32,
     instead of float64, as mkl_fft would do
@@ -46,18 +46,18 @@ def __upcast_float16_array(x):
         if xdt == np.longdouble and not xdt == np.float64:
             raise ValueError("type %s is not supported" % xdt)
     if not isinstance(x, np.ndarray):
-        __x = np.asarray(x)
-        xdt = __x.dtype
+        _x = np.asarray(x)
+        xdt = _x.dtype
         if xdt == np.half:
             # no half-precision routines, so convert to single precision
-            return np.asarray(__x, dtype=np.float32)
+            return np.asarray(_x, dtype=np.float32)
         if xdt == np.longdouble and not xdt == np.float64:
             raise ValueError("type %s is not supported" % xdt)
-        return __x
+        return _x
     return x
 
 
-def __downcast_float128_array(x):
+def _downcast_float128_array(x):
     """
     Used in _numpy_fft to unsafely downcast float128/complex256 to
     complex128, instead of raising an error
@@ -69,27 +69,27 @@ def __downcast_float128_array(x):
         elif xdt == np.clongdouble and not xdt == np.complex128:
             return np.asarray(x, dtype=np.complex128)
     if not isinstance(x, np.ndarray):
-        __x = np.asarray(x)
-        xdt = __x.dtype
+        _x = np.asarray(x)
+        xdt = _x.dtype
         if xdt == np.longdouble and not xdt == np.float64:
             return np.asarray(x, dtype=np.float64)
         elif xdt == np.clongdouble and not xdt == np.complex128:
             return np.asarray(x, dtype=np.complex128)
-        return __x
+        return _x
     return x
 
 
-def __supported_array_or_not_implemented(x):
+def _supported_array_or_not_implemented(x):
     """
     Used in _scipy_fft to convert array to float32,
-    float64, complex64, or complex128 type or return NotImplemented
+    float64, complex64, or complex128 type or raise NotImplementedError
     """
-    __x = np.asarray(x)
+    _x = np.asarray(x)
     black_list = [np.half]
     if hasattr(np, "float128"):
         black_list.append(np.float128)
     if hasattr(np, "complex256"):
         black_list.append(np.complex256)
-    if __x.dtype in black_list:
-        return NotImplemented
-    return __x
+    if _x.dtype in black_list:
+        raise NotImplementedError
+    return _x