{"id":17066261,"url":"https://github.com/hendriks73/jipesfft","last_synced_at":"2026-04-17T15:31:40.613Z","repository":{"id":57727419,"uuid":"417439004","full_name":"hendriks73/jipesFFT","owner":"hendriks73","description":"Native FFT for 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2.1](https://img.shields.io/badge/License-LGPL_2.1-blue.svg)](https://www.gnu.org/licenses/old-licenses/lgpl-2.1.html)\n[![Maven Central](https://maven-badges.herokuapp.com/maven-central/com.tagtraum/jipesfft/badge.svg)](https://maven-badges.herokuapp.com/maven-central/com.tagtraum/jipesfft)\n[![Build and Test](https://github.com/hendriks73/jipesFFT/workflows/Build%20and%20Test/badge.svg?branch=dev)](https://github.com/hendriks73/jipesFFT/actions?query=branch%3Adev++)\n[![CodeCov](https://codecov.io/gh/hendriks73/jipesFFT/branch/dev/graph/badge.svg?token=DFf7RcXFkf)](https://codecov.io/gh/hendriks73/jipesFFT/tree/dev)\n\n\n# jipesFFT\n\nNative FFT (Fast Fourier Transformation) implementations for Java\n(macOS, Windows, Linux).\n\nThe macOS version uses Apple's [Accelerate\nframework](https://developer.apple.com/documentation/accelerate).\nWindows and Linux versions use more ordinary implementations.\n\n\n## Installation\n\njipesFFT is released via [Maven](https://maven.apache.org).\nYou can install it via the following dependency:\n\n```xml\n\u003cdependencies\u003e\n    \u003cdependency\u003e\n        \u003cgroupId\u003ecom.tagtraum\u003c/groupId\u003e\n        \u003cartifactId\u003ejipesfft-complete\u003c/artifactId\u003e\n    \u003c/dependency\u003e\n\u003c/dependencies\u003e\n```\n\n## Usage\n\nHere's a simple example that demonstrates how the `com.tagtraum.jipesfft.FFT`\nclass can be used:\n\n```java\nimport com.tagtraum.jipesfft.FFT;\n\nclass Demo {\n    public static void main(final String[] args) {\n        // Create a new FFT instance suitable\n        // for a window length of 8 samples.\n        // Do this in a \"try\" statement to ensure native resources\n        // are freed in a timely fashion.\n        try (final FFT fft = new FFT(8)) {\n            final float[] result = fft.transform(new float[]{0, 0, 0, 1, 0, 0, 0, 1});\n            // real part of the complex result\n            float[] real = result[FFT.REAL];\n            // imaginary part of the complex result\n            float[] imaginary = result[FFT.IMAGINARY];\n            // frequencies for the result - must still be multiplied with sampling\n            // frequency. Second half of frequency array is not necessarily useful.\n            float[] frequencies = result[FFT.FREQUENCY];\n\n            // go on and do something with it...\n        }\n    }\n}\n```\n\n## Java Module\n\njipesFFT is shipped as a Java module\n(see [JPMS](https://en.wikipedia.org/wiki/Java_Platform_Module_System))\nwith the name `tagtraum.jipesfft`.\n\n\n## API\n\nYou can find the complete [API here](https://hendriks73.github.io/jipesFFT/).\n                       \n\n## Additional Resources\n\n- [Discrete Fourier Transform (Wikipedia)](https://en.wikipedia.org/wiki/Discrete_Fourier_transform)\n- [Intro to Discrete Fourier Transform by M. Müller and F. Zalkow](https://www.audiolabs-erlangen.de/resources/MIR/FMP/C2/C2_DFT-FFT.html)\n- [Fast Fourier Transform (algorithm)](https://en.wikipedia.org/wiki/Fast_Fourier_transform)\n- [Nyquist Frequency](https://en.wikipedia.org/wiki/Nyquist_frequency)\n- [Fundamentals of Music Processing by Meinard Müller](https://www.springer.com/gp/book/9783030698072) ","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhendriks73%2Fjipesfft","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhendriks73%2Fjipesfft","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhendriks73%2Fjipesfft/lists"}