Add jSciPy library to scientific computing section#1165
Merged
akullpp merged 1 commit intoakullpp:masterfrom Jan 11, 2026
Merged
Add jSciPy library to scientific computing section#1165akullpp merged 1 commit intoakullpp:masterfrom
akullpp merged 1 commit intoakullpp:masterfrom
Conversation
jSciPy is a Java library designed for scientific computing, offering functionalities inspired by popular scientific computing libraries. It currently provides modules for signal processing, including Butterworth filters, peak finding algorithms, and an RK4 solver for ordinary differential equations.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
jSciPy is a Java library for scientific computing, providing functionality inspired by widely used scientific toolkits. It currently includes modules for signal processing, such as Butterworth filters, peak detection algorithms, and an RK4 solver for ordinary differential equations.
In modern machine learning workflows, most signal processing tasks rely on Python's SciPy utilities. However, there is no Java library that replicates SciPy's behavior with comparable completeness and consistency. This creates a significant gap for teams building ML or signal processing pipelines on the JVM. jSciPy aims to fill this gap, and the demand for such a library is higher than ever.