{"id":20433747,"url":"https://github.com/intelpython/mkl_fft","last_synced_at":"2025-04-08T08:13:19.569Z","repository":{"id":26837687,"uuid":"105945677","full_name":"IntelPython/mkl_fft","owner":"IntelPython","description":"NumPy-based Python interface to Intel (R) MKL FFT functionality","archived":false,"fork":false,"pushed_at":"2025-03-31T21:53:24.000Z","size":306,"stargazers_count":65,"open_issues_count":30,"forks_count":18,"subscribers_count":8,"default_branch":"master","last_synced_at":"2025-04-01T05:36:03.007Z","etag":null,"topics":["fft","mkl","numpy"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/IntelPython.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGES.rst","contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2017-10-05T22:13:50.000Z","updated_at":"2025-03-31T19:49:32.000Z","dependencies_parsed_at":"2024-02-20T22:28:10.676Z","dependency_job_id":"34b58eb7-cc3e-4fc0-9d7c-9f606e7884f1","html_url":"https://github.com/IntelPython/mkl_fft","commit_stats":{"total_commits":132,"total_committers":9,"mean_commits":"14.666666666666666","dds":0.09848484848484851,"last_synced_commit":"23f6b04f7c3dcd1af25313acd3601a8bac32113f"},"previous_names":[],"tags_count":29,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IntelPython%2Fmkl_fft","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IntelPython%2Fmkl_fft/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IntelPython%2Fmkl_fft/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IntelPython%2Fmkl_fft/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/IntelPython","download_url":"https://codeload.github.com/IntelPython/mkl_fft/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247801169,"owners_count":20998339,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["fft","mkl","numpy"],"created_at":"2024-11-15T08:20:51.326Z","updated_at":"2025-04-08T08:13:19.560Z","avatar_url":"https://github.com/IntelPython.png","language":"Python","readme":"## ``mkl_fft`` --  a NumPy-based Python interface to Intel (R) MKL FFT functionality\n[![Conda package](https://github.com/IntelPython/mkl_fft/actions/workflows/conda-package.yml/badge.svg)](https://github.com/IntelPython/mkl_fft/actions/workflows/conda-package.yml)\n[![Editable build using pip and pre-release NumPy](https://github.com/IntelPython/mkl_fft/actions/workflows/build_pip.yaml/badge.svg)](https://github.com/IntelPython/mkl_fft/actions/workflows/build_pip.yaml)\n[![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)\n\n`mkl_fft` started as a part of Intel (R) Distribution for Python* optimizations to NumPy, and is now being released\nas a stand-alone package. It can be installed into conda environment using\n\n```\n   conda install -c https://software.repos.intel.com/python/conda mkl_fft\n```\n\nor from conda-forge channel:\n\n```\n   conda install -c conda-forge mkl_fft\n```\n\n---\n\nTo install mkl_fft Pypi package please use following command:\n\n```\n   python -m pip install --index-url https://software.repos.intel.com/python/pypi --extra-index-url https://pypi.org/simple mkl_fft\n```\n\nIf command above installs NumPy package from the Pypi, please use following command to install Intel optimized NumPy wheel package from Intel Pypi Cloud:\n\n```\n   python -m pip install --index-url https://software.repos.intel.com/python/pypi --extra-index-url https://pypi.org/simple mkl_fft numpy==\u003cnumpy_version\u003e\n```\n\nWhere `\u003cnumpy_version\u003e` should be the latest version from https://software.repos.intel.com/python/conda/\n\n---\n\nSince MKL FFT supports performing discrete Fourier transforms over non-contiguously laid out arrays, MKL can be directly\nused on any well-behaved floating point array with no internal overlaps for both in-place and not in-place transforms of\narrays in single and double floating point precision.\n\nThis eliminates the need to copy input array contiguously into an intermediate buffer.\n\n`mkl_fft` directly supports N-dimensional Fourier transforms.\n\nMore details can be found in SciPy 2017 conference proceedings:\n     https://github.com/scipy-conference/scipy_proceedings/tree/2017/papers/oleksandr_pavlyk\n\n---\n\nIt implements the following functions:\n\n### Complex transforms, similar to those in `scipy.fftpack`:\n\n`fft(x, n=None, axis=-1, overwrite_x=False)`\n\n`ifft(x, n=None, axis=-1, overwrite_x=False)`\n\n`fft2(x, shape=None, axes=(-2,-1), overwrite_x=False)`\n\n`ifft2(x, shape=None, axes=(-2,-1), overwrite_x=False)`\n\n`fftn(x, n=None, axes=None, overwrite_x=False)`\n\n`ifftn(x, n=None, axes=None, overwrite_x=False)`\n\n### Real transforms\n\n`rfft(x, n=None, axis=-1, overwrite_x=False)` - real 1D Fourier transform, like `scipy.fftpack.rfft`\n\n`rfft_numpy(x, n=None, axis=-1)` - real 1D Fourier transform, like `numpy.fft.rfft`\n\n`rfft2_numpy(x, s=None, axes=(-2,-1))` - real 2D Fourier transform, like `numpy.fft.rfft2`\n\n`rfftn_numpy(x, s=None, axes=None)` - real ND Fourier transform, like `numpy.fft.rfftn`\n\n... and similar `irfft*` functions.\n\n\nThe package also provides `mkl_fft._numpy_fft` and `mkl_fft._scipy_fft` interfaces which provide drop-in replacements for equivalent functions in NumPy and SciPy respectively.\n\n---\n\nTo build ``mkl_fft`` from sources on Linux:\n  - install a recent version of MKL, if necessary;\n  - execute ``source /path_to_oneapi/mkl/latest/env/vars.sh``;\n  - execute ``python -m pip install .``\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fintelpython%2Fmkl_fft","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fintelpython%2Fmkl_fft","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fintelpython%2Fmkl_fft/lists"}