jSciPy
jSciPy provides Java scientific computing tools for signal processing, FFT, filtering, power spectral density, and DCT.
About jSciPy
jSciPy is an open-source Java library for scientific computing and signal processing on the JVM and Android, with APIs modeled on Python's SciPy. It includes digital filters, Fourier and cosine transforms, spectral estimation, waveform generation, convolution and correlation, peak detection, interpolation, polynomial tools, and an RK4 ODE solver.
Stable releases are published to Maven Central and are added as a Gradle dependency, with no other prerequisites stated for use.
Key features
- Butterworth, Chebyshev, Elliptic, Bessel and FIR filters with filtfilt, lfilter, sosfilt modes
- 1D FFT/IFFT, real RFFT/IRFFT, 2D FFT, STFT/ISTFT and Hilbert transform
- DCT/IDCT, Welch PSD, spectrogram and periodogram analysis
- Chirp, square, sawtooth, Gaussian pulse and unit impulse waveform generation
- Savitzky-Golay smoothing, median filter, detrending, resampling and peak detection
- Interpolation, polynomial fitting, and RK4 ODE solver
Best for: Java and Android developers who need SciPy-like signal processing functions for machine learning or signal pipelines on the JVM.
Good for
- Provides SciPy-like APIs for JVM and Android projects
- Tested against Python SciPy using a Golden Master approach
- Distributed via Maven Central with no prerequisites stated for use
jSciPy at a glance
- Website
- github.com/hissain/jscipy
- Category
- Development › Developer Tools
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Platforms
- Android
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
Guides for Developer Tools
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jSciPy FAQ
Does jSciPy support Android?
Yes, it is designed for use on the JVM and Android.
How is jSciPy added to a project?
Stable releases are published to Maven Central and added as a Gradle dependency, with no other prerequisites stated.
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