hopsy - a methods marketplace for convex polytope sampling in Python

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Abstract Summary Effective collaboration between developers of Bayesian inference methods and users is key to advance our quantitative understanding of biosystems. We here present hopsy , a versatile open source platform designed to provide convenient access to powerful Markov chain Monte Carlo sampling algorithms tailored to models defined on convex polytopes (CP). Based on the high-performance C++ sampling library HOPS , hopsy inherits its strengths and extends its functionalities with the accessibility of the Python programming language. A versatile plugin-mechanism enables seamless integration with domain-specific models, providing method developers with a framework for testing, benchmarking, and distributing CP samplers to approach real-world inference tasks. We showcase hopsy by solving common and newly composed domain-specific sampling problems, highlighting important design choices. By likening hopsy to a marketplace, we emphasize its role in bringing together users and developers, where users get access to state-of-the-art methods, and developers contribute their own innovative solutions for challenging domain-specific inference problems. Availability and Implementation Sources, documentation and a continuously updated list of sampling algorithms are available at https://jugit.fz-juelich.de/IBG-1/ModSim/hopsy , with Linux, Windows and MacOS binaries at https://pypi.org/project/hopsy/ . Contact k.noeh@fz-juelich.de

Authors 5

1. Richard Dominik Paul

   Forschungszentrum Jülich

   Affiliation as printed

   Institute of Advanced Simulations, IAS-8: Data Analytics and Machine Learning, Forschungszentrum Jülich, Wilhelm-Johnen-Str., 52428 Jülich, Germany

   Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich, Wilhelm-Johnen-Str., 52428 Jülich, Germany

   Institute of Advanced Simulations, IAS-8: Data Analytics and Machine Learning, Forschungszentrum Jülich, Wilhelm-Johnen-Str., 548 Jülich, Germany

2. Johann F. Jadebeck Aachen Computational Systems Biotechnology

   Forschungszentrum Jülich · RWTH Aachen University

   Affiliation as printed

   Computational Systems Biotechnology (AVT.CSB), RWTH Aachen University, Forckenbeckstr., 52074 Aachen, Germany

   Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich, Wilhelm-Johnen-Str., 52428 Jülich, Germany

   Institute of Bio- and Geosciences, IBG-: Biotechnology, Forschungszentrum Jülich, Wilhelm-Johnen-Str., 52428 Jülich, Germany

3. Anton Stratmann Aachen Computational Systems Biotechnology

   Forschungszentrum Jülich · RWTH Aachen University

   Affiliation as printed

   Computational Systems Biotechnology (AVT.CSB), RWTH Aachen University, Forckenbeckstr., 52074 Aachen, Germany

   Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich, Wilhelm-Johnen-Str., 52428 Jülich, Germany

   Institute of Bio- and Geosciences, IBG-: Biotechnology, Forschungszentrum Jülich, Wilhelm-Johnen-Str., 52428 Jülich, Germany

4. Wolfgang Wiechert Aachen Computational Systems Biotechnology

   Forschungszentrum Jülich · RWTH Aachen University

   Affiliation as printed

   Computational Systems Biotechnology (AVT.CSB), RWTH Aachen University, Forckenbeckstr., 52074 Aachen, Germany

   Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich, Wilhelm-Johnen-Str., 52428 Jülich, Germany

   Institute of Bio- and Geosciences, IBG-: Biotechnology, Forschungszentrum Jülich, Wilhelm-Johnen-Str., 52428 Jülich, Germany

5. Katharina Nöh corresponding

   Forschungszentrum Jülich

   Affiliation as printed

   Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich, Wilhelm-Johnen-Str., 52428 Jülich, Germany

   Institute of Bio- and Geosciences, IBG-: Biotechnology, Forschungszentrum Jülich, Wilhelm-Johnen-Str., 52428 Jülich, Germany