{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/6"},{"label":"Physics","url":"https://skillfed.io/packages/category/scientific-engineering-physics"},{"label":"Astronomy","url":"https://skillfed.io/packages/category/scientific-engineering-astronomy"}],"enrichment":{"capability":"LALSuite provides data analysis routines for searching and characterizing astrophysical signals in gravitational-wave time-series data from ground-based detectors like LIGO, Virgo, and KAGRA.","skillfed_tags":["gravitational-waves","astrophysics","signal-processing"],"use_cases":["Simulate gravitational waveforms from compact binary mergers and other astrophysical sources for detector characterization.","Search gravitational-wave detector data for transient burst signals and characterize their properties.","Perform Bayesian parameter estimation on detected gravitational-wave events to infer source properties.","Analyze pulsar and continuous-wave gravitational-wave data using specialized algorithms.","Build custom gravitational-wave analysis pipelines combining multiple LALSuite components."],"what_it_does":"LALSuite is a comprehensive C99 library suite with Python bindings for gravitational-wave data analysis, developed collaboratively by the LIGO Scientific Collaboration, Virgo Collaboration, and KAGRA Collaboration. It provides modular components for waveform simulation, signal detection, parameter estimation, and characterization across multiple gravitational-wave source types\u2014from compact binary inspirals to pulsar continuous waves and burst signals.\n\nThe package bundles nine specialized modules (LAL, LALFrame, LALMetaIO, LALSimulation, LALBurst, LALInspiral, LALInference, LALPulsar, LALApps) into a single installation. It depends on eight runtime packages including numpy, scipy, astropy, matplotlib, python-dateutil, igwn-ligolw, igwn-segments, and lscsoft-glue, making it suitable for research environments with scientific Python stacks already in place. Installation is straightforward via pip with prebuilt wheels, though optional extras (lalinference, lalpulsar, test) allow users to install only the dependencies they need.","worth_installing":"Yes, for gravitational-wave research. LALSuite is the standard library for LIGO/Virgo/KAGRA data analysis, actively maintained, production-stable, and carries no known security vulnerabilities. Medium install friction is acceptable given the domain-specific nature and scientific audience. GPL-2+ copyleft licensing is standard for academic physics software and poses no barrier for research use. Install only if you are working with gravitational-wave detector data or waveform modeling."},"id":"lalsuite","links":{"html":"https://skillfed.io/packages/lalsuite","md":"https://skillfed.io/packages/lalsuite.md","pypi":"https://pypi.org/project/lalsuite/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-13","license_spdx":null,"license_treatment":"copyleft","name":"lalsuite","python_support":"supports_current","summary":"LVK Algorithm Library Suite - LALSuite"},"popularity":{"monthly_downloads":190686,"position":9902,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"7.26.15"}