Merge branch 'master' into permit-build-python-3.13

Author: ndgrigorian

.github/workflows/build_pip.yaml

@@ -35,7 +35,7 @@ jobs:
         with:
           fetch-depth: 0
 
-      - uses: conda-incubator/setup-miniconda@505e6394dae86d6a5c7fbb6e3fb8938e3e863830 # v3.1.1
+      - uses: conda-incubator/setup-miniconda@835234971496cad1653abb28a638a281cf32541f # v3.2.0
         with:
           use-mamba: true
           miniforge-version: latest

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

@@ -143,7 +143,7 @@ jobs:
           pytest -v --pyargs $MODULE_NAME
 
   build_windows:
-    runs-on: windows-2019
+    runs-on: windows-latest
 
     strategy:
       matrix:
@@ -158,7 +158,7 @@ jobs:
         with:
           fetch-depth: 0
 
-      - uses: conda-incubator/setup-miniconda@505e6394dae86d6a5c7fbb6e3fb8938e3e863830 # v3.1.1
+      - uses: conda-incubator/setup-miniconda@835234971496cad1653abb28a638a281cf32541f # v3.2.0
         with:
           miniforge-version: latest
           activate-environment: build
@@ -181,6 +181,9 @@ jobs:
             ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-python-${{ matrix.python }}-
             ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-
 
+      - name: Setup MSVC
+        uses: ilammy/msvc-dev-cmd@0b201ec74fa43914dc39ae48a89fd1d8cb592756 # v1.13.0
+
       - name: Build conda package with NumPy 2.0
         run: |
           conda activate
@@ -209,7 +212,7 @@ jobs:
         python_ver: ['3.9', '3.10', '3.11', '3.12']
         numpy: ['numpy"<2"', 'numpy">=2"']
         experimental: [false]
-        runner: [windows-2019]
+        runner: [windows-latest]
     continue-on-error: ${{ matrix.experimental }}
     env:
       workdir: '${{ github.workspace }}'
@@ -221,7 +224,7 @@ jobs:
         with:
           name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python_ver }}
 
-      - uses: conda-incubator/setup-miniconda@505e6394dae86d6a5c7fbb6e3fb8938e3e863830 # v3.1.1
+      - uses: conda-incubator/setup-miniconda@835234971496cad1653abb28a638a281cf32541f # v3.2.0
         with:
           miniforge-version: latest
           activate-environment: ${{ env.TEST_ENV_NAME }}

.github/workflows/conda-package.yml

@@ -55,7 +55,7 @@ jobs:
 
       - name: Build conda package
         run: |
-          CHANNELS="-c conda-forge -c https://software.repos.intel.com/python/conda --override-channels"
+          CHANNELS="-c https://software.repos.intel.com/python/conda -c conda-forge --override-channels"
           VERSIONS="--python ${{ matrix.python }}"
           TEST="--no-test"
 
@@ -101,8 +101,17 @@ jobs:
           mkdir -p $GITHUB_WORKSPACE/channel/linux-64
           mv ${PACKAGE_NAME}-*.conda $GITHUB_WORKSPACE/channel/linux-64
           conda index $GITHUB_WORKSPACE/channel
-          # Test channel
-          conda search $PACKAGE_NAME -c $GITHUB_WORKSPACE/channel --override-channels
+
+      - name: Test conda channel
+        run: |
+          conda search $PACKAGE_NAME -c $GITHUB_WORKSPACE/channel --override-channels --info --json > $GITHUB_WORKSPACE/ver.json
+          cat $GITHUB_WORKSPACE/ver.json
+
+      - name: Get package version
+        run: |
+          export PACKAGE_VERSION=$(python -c "${{ env.VER_SCRIPT1 }} ${{ env.VER_SCRIPT2 }}")
+          echo PACKAGE_VERSION=${PACKAGE_VERSION}
+          echo "PACKAGE_VERSION=$PACKAGE_VERSION" >> $GITHUB_ENV
 
       - name: Collect dependencies
         run: |
@@ -131,8 +140,7 @@ jobs:
       - name: Install mkl_fft
         run: |
           CHANNELS="-c $GITHUB_WORKSPACE/channel ${{ env.CHANNELS }}"
-          conda create -n ${{ env.TEST_ENV_NAME }} python=${{ matrix.python }} "scipy>=1.10" $CHANNELS
-          conda install -n ${{ env.TEST_ENV_NAME }} $PACKAGE_NAME pytest $CHANNELS
+          conda create -n ${{ env.TEST_ENV_NAME }} $PACKAGE_NAME=${{ env.PACKAGE_VERSION }} python=${{ matrix.python }} pytest "scipy>=1.10" $CHANNELS
           # Test installed packages
           conda list -n ${{ env.TEST_ENV_NAME }}
 
@@ -143,7 +151,7 @@ jobs:
           pytest -v --pyargs $MODULE_NAME
 
   build_windows:
-    runs-on: windows-2019
+    runs-on: windows-latest
 
     strategy:
       matrix:
@@ -158,7 +166,7 @@ jobs:
         with:
           fetch-depth: 0
 
-      - uses: conda-incubator/setup-miniconda@505e6394dae86d6a5c7fbb6e3fb8938e3e863830 # v3.1.1
+      - uses: conda-incubator/setup-miniconda@835234971496cad1653abb28a638a281cf32541f # v3.2.0
         with:
           miniforge-version: latest
           activate-environment: build
@@ -183,6 +191,9 @@ jobs:
             ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-python-${{ matrix.python }}-
             ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-
 
+      - name: Setup MSVC
+        uses: ilammy/msvc-dev-cmd@0b201ec74fa43914dc39ae48a89fd1d8cb592756 # v1.13.0
+
       - name: Build conda package
         run: |
           conda activate
@@ -210,7 +221,7 @@ jobs:
       matrix:
         python: ['3.9', '3.10', '3.11', '3.12']
         experimental: [false]
-        runner: [windows-2019]
+        runner: [windows-latest]
     continue-on-error: ${{ matrix.experimental }}
     env:
       workdir: '${{ github.workspace }}'
@@ -222,7 +233,7 @@ jobs:
         with:
           name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
 
-      - uses: conda-incubator/setup-miniconda@505e6394dae86d6a5c7fbb6e3fb8938e3e863830 # v3.1.1
+      - uses: conda-incubator/setup-miniconda@835234971496cad1653abb28a638a281cf32541f # v3.2.0
         with:
           miniforge-version: latest
           activate-environment: ${{ env.TEST_ENV_NAME }}

.github/workflows/openssf-scorecard.yml

@@ -39,7 +39,7 @@ jobs:
           persist-credentials: false
 
       - name: "Run analysis"
-        uses: ossf/scorecard-action@f49aabe0b5af0936a0987cfb85d86b75731b0186 # v2.4.1
+        uses: ossf/scorecard-action@05b42c624433fc40578a4040d5cf5e36ddca8cde # v2.4.2
         with:
           results_file: results.sarif
           results_format: sarif
@@ -69,6 +69,6 @@ jobs:
 
       # Upload the results to GitHub's code scanning dashboard.
       - name: "Upload to code-scanning"
-        uses: github/codeql-action/upload-sarif@60168efe1c415ce0f5521ea06d5c2062adbeed1b # v3.28.17
+        uses: github/codeql-action/upload-sarif@fca7ace96b7d713c7035871441bd52efbe39e27e # v3.28.19
         with:
           sarif_file: results.sarif

.gitignore

@@ -7,4 +7,5 @@ __pycache__/
 
 mkl_fft/_pydfti.c
 mkl_fft/_pydfti.cpython*.so
+mkl_fft/_pydfti.*-win_amd64.pyd
 mkl_fft/src/mklfft.c

CHANGELOG.md

@@ -4,7 +4,7 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [dev] (MM/DD/YY)
+## [2.0.0] (05/DD/2025)
 
 ### Added
 * Added Hermitian FFT functions to SciPy interface `mkl_fft.interfaces.scipy_fft`: `hfft`, `ihfft`, `hfftn`, `ihfftn`, `hfft2`, and `ihfft2` [gh-161](https://github.com/IntelPython/mkl_fft/pull/161)
@@ -14,6 +14,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Changed
 * NumPy interface `mkl_fft.interfaces.numpy_fft` is aligned with numpy-2.x.x [gh-139](https://github.com/IntelPython/mkl_fft/pull/139), [gh-157](https://github.com/IntelPython/mkl_fft/pull/157)
 * To set `mkl_fft` as the backend for SciPy is only possible through `mkl_fft.interfaces.scipy_fft` [gh-179](https://github.com/IntelPython/mkl_fft/pull/179)
+* SciPy interface `mkl_fft.interfaces.scipy_fft` uses the same function from SciPy for handling `s` and `axes` for N-D FFTs [gh-181](https://github.com/IntelPython/mkl_fft/pull/181)
+
+### Fixed
+* Fixed an issue for calling `mkl_fft.interfaces.numpy.fftn` with an empty axes [gh-139](https://github.com/IntelPython/mkl_fft/pull/139)
+* Fixed an issue for calling `mkl_fft.interfaces.numpy.fftn` with a zero-size array [gh-139](https://github.com/IntelPython/mkl_fft/pull/139)
+* Fixed inconsistency of input and output arrays dtype for `irfft` function [gh-180](https://github.com/IntelPython/mkl_fft/pull/180)
+* Fixed issues with `set_workers` function in SciPy interface `mkl_fft.interfaces.scipy_fft` [gh-183](https://github.com/IntelPython/mkl_fft/pull/183)
 
 ## [1.3.14] (04/10/2025)
 

README.md

@@ -4,8 +4,17 @@
 [![Conda package with conda-forge channel only](https://github.com/IntelPython/mkl_fft/actions/workflows/conda-package-cf.yml/badge.svg)](https://github.com/IntelPython/mkl_fft/actions/workflows/conda-package-cf.yml)
 [![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/IntelPython/mkl_fft/badge)](https://securityscorecards.dev/viewer/?uri=github.com/IntelPython/mkl_fft)
 
+# Introduction
 `mkl_fft` started as a part of Intel® Distribution for Python* optimizations to NumPy, and is now being released
-as a stand-alone package. It can be installed into conda environment from Intel's channel using:
+as a stand-alone package. It offers a thin layered interface for the Intel® oneAPI Math Kernel Library (OneMKL) FFT functionality that allows efficient access to native FFT optimizations from a range of NumPy and SciPy functions. As a result, its performance is close to the performance of native C/Intel® OneMKL. The optimizations are provided for real and complex data types in both single and double precisions for in-place and out-of-place modes of operation. For analyzing the performance use [FFT benchmarks](https://github.com/intelpython/fft_benchmark).
+
+Thanks to Intel® OneMKL’s flexibility in its supports for arbitrarily strided input and output arrays both one-dimensional and multi-dimensional Fast Fourier Transforms along distinct axes can be performed directly, without the need to copy the input into a contiguous array first. Furthermore, input strides can be arbitrary, including negative or zero, as long as strides remain an integer multiple of array’s item size, otherwise a copy will be made.
+
+More details can be found in ["Accelerating Scientific Python with Intel Optimizations"](https://proceedings.scipy.org/articles/shinma-7f4c6e7-00f) from Proceedings of the 16th Python in Science Conference (SciPy 2017).
+
+---
+# Installation
+`mkl_fft` can be installed into conda environment from Intel's channel using:
 
 ```
    conda install -c https://software.repos.intel.com/python/conda mkl_fft
@@ -34,22 +43,12 @@ If command above installs NumPy package from the PyPI, please use following comm
 Where `<numpy_version>` should be the latest version from https://software.repos.intel.com/python/conda/
 
 ---
+# How to use?
+## `mkl_fft.interfaces` module
+The recommended way to use `mkl_fft` package is through `mkl_fft.interfaces` module. These interfaces act as drop-in replacements for equivalent functions in NumPy and SciPy. Learn more about these interfaces [here](https://github.com/IntelPython/mkl_fft/blob/master/mkl_fft/interfaces/README.md).
 
-Since MKL FFT supports performing discrete Fourier transforms over non-contiguously laid out arrays, OneMKL can be directly
-used on any well-behaved floating point array with no internal overlaps for both in-place and not in-place transforms of
-arrays in single and double floating point precision.
-
-This eliminates the need to copy input array contiguously into an intermediate buffer.
-
-`mkl_fft` directly supports N-dimensional Fourier transforms.
-
-More details can be found in [SciPy 2017 conference proceedings](https://github.com/scipy-conference/scipy_proceedings/tree/2017/papers/oleksandr_pavlyk).
-
----
-
-The `mkl_fft` package offers interfaces that act as drop-in replacements for equivalent functions in NumPy and SciPy. Learn more about these interfaces [here](https://github.com/IntelPython/mkl_fft/blob/master/mkl_fft/interfaces/README.md).
-
-While using these interfaces is the easiest way to leverage `mk_fft`, one can also use `mkl_fft` directly with the following FFT functions:
+## `mkl_fft` package
+While using the interfaces module is the recommended way to leverage `mk_fft`, one can also use `mkl_fft` directly with the following FFT functions:
 
 ### complex-to-complex (c2c) transforms:
 
@@ -84,6 +83,7 @@ numpy.allclose(mkl_res, np_res)
 ```
 
 ---
+# Building from source
 
 To build `mkl_fft` from sources on Linux with Intel® OneMKL:
   - create a virtual environment: `python3 -m venv fft_env`
@@ -93,6 +93,7 @@ To build `mkl_fft` from sources on Linux with Intel® OneMKL:
   - `git clone https://github.com/IntelPython/mkl_fft.git mkl_fft`
   - `cd mkl_fft`
   - `python -m pip install .`
+  - `pip install scipy` (optional: for using `mkl_fft.interface.scipy_fft` module)
   - `cd ..`
   - `python -c "import mkl_fft"`
 
@@ -103,5 +104,6 @@ To build `mkl_fft` from sources on Linux with conda follow these steps:
   - `git clone https://github.com/IntelPython/mkl_fft.git mkl_fft`
   - `cd mkl_fft`
   - `python -m pip install .`
+  - `conda install scipy` (optional: for using `mkl_fft.interface.scipy_fft` module)
   - `cd ..`
   - `python -c "import mkl_fft"`

conda-recipe-cf/meta.yaml

@@ -1,4 +1,4 @@
-{% set version = "1.3.14" %}
+{% set version = "2.0.0" %}
 {% set buildnumber = 0 %}
 
 package:
@@ -32,7 +32,7 @@ test:
       - pytest -v --pyargs mkl_fft
     requires:
       - pytest
-      - scipy
+      - scipy >=1.10
     imports:
       - mkl_fft
       - mkl_fft.interfaces

conda-recipe/meta.yaml

@@ -1,4 +1,4 @@
-{% set version = "1.3.14" %}
+{% set version = "2.0.0" %}
 {% set buildnumber = 0 %}
 
 package:
@@ -20,6 +20,7 @@ requirements:
       - python
       - setuptools >=77
       - mkl-devel
+      - mkl-devel 2024.2.*  # [py==39 or py==310]
       - cython
       - numpy-base
     run:
@@ -32,7 +33,7 @@ test:
       - pytest -v --pyargs mkl_fft
     requires:
       - pytest
-      - scipy
+      - scipy >=1.10
     imports:
       - mkl_fft
       - mkl_fft.interfaces