{"title":"TrackSegNet: a tool for trajectory segmentation into\u0000diffusive states using supervised deep learning","authors":"Hélène Kabbech, Ihor Smal","doi":"10.21105/joss.06157","DOIUrl":"https://doi.org/10.21105/joss.06157","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141266773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MousebreedeR: A novel software to assist in the design\u0000of breeding schema for complex genotypes of experimental\u0000organisms","authors":"M. Sportiello, David J. Topham","doi":"10.21105/joss.06474","DOIUrl":"https://doi.org/10.21105/joss.06474","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141266338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"OpenTerrace: A fast, flexible and extendable Python\u0000framework for thermal energy storage packed bed simulations","authors":"J. Hærvig","doi":"10.21105/joss.06411","DOIUrl":"https://doi.org/10.21105/joss.06411","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141266769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"omni-fig: Unleashing Project Configuration and\u0000Organization in Python","authors":"Felix Leeb","doi":"10.21105/joss.05350","DOIUrl":"https://doi.org/10.21105/joss.05350","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141267265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Guillaume Fieni, Daniel Romero Acero, Pierre Rust, Romain Rouvoy
{"title":"PowerAPI: A Python framework for building\u0000software-defined power meters","authors":"Guillaume Fieni, Daniel Romero Acero, Pierre Rust, Romain Rouvoy","doi":"10.21105/joss.06670","DOIUrl":"https://doi.org/10.21105/joss.06670","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141267925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anya E. Vostinar, Alexander Lalejini, Charles Ofria, Emily Dolson, M. Moreno
{"title":"Empirical: A scientific software library for research,\u0000education, and public engagement","authors":"Anya E. Vostinar, Alexander Lalejini, Charles Ofria, Emily Dolson, M. Moreno","doi":"10.21105/joss.06617","DOIUrl":"https://doi.org/10.21105/joss.06617","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141273970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thomas Seidler, Fabian Emmerich, Kristian Ehlert, R. Berner, Oliver Nagel-Kanzler, Norbert Schultz, Markus Quade, Martin G. Schultz, Markus Abel
{"title":"Mantik: A Workflow Platform for the Development of\u0000Artificial Intelligence on High-Performance Computing\u0000Infrastructures","authors":"Thomas Seidler, Fabian Emmerich, Kristian Ehlert, R. Berner, Oliver Nagel-Kanzler, Norbert Schultz, Markus Quade, Martin G. Schultz, Markus Abel","doi":"10.21105/joss.06136","DOIUrl":"https://doi.org/10.21105/joss.06136","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141273261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jonas Schuhmacher, Emmanuel Blazquez, Fabio Gratl, Dario Izzo, Pablo Gómez
Polyhedral gravity models are essential for modeling the gravitational field of irregular bodies, such as asteroids and comets. We present an open-source C++ library for the efficient, parallelized computation of a polyhedral gravity model following the line integral approach by Tsoulis (Tsoulis,
{"title":"Efficient Polyhedral Gravity Modeling in Modern C++ and\u0000Python","authors":"Jonas Schuhmacher, Emmanuel Blazquez, Fabio Gratl, Dario Izzo, Pablo Gómez","doi":"10.21105/joss.06384","DOIUrl":"https://doi.org/10.21105/joss.06384","url":null,"abstract":"Polyhedral gravity models are essential for modeling the gravitational field of irregular bodies, such as asteroids and comets. We present an open-source C++ library for the efficient, parallelized computation of a polyhedral gravity model following the line integral approach by Tsoulis (Tsoulis,","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141278641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
James W. Nightingale, Richard Massey, J. Kegerreis, R. Hayes
{"title":"PyAutoCTI: Open-Source Charge Transfer Inefficiency\u0000Calibration","authors":"James W. Nightingale, Richard Massey, J. Kegerreis, R. Hayes","doi":"10.21105/joss.04904","DOIUrl":"https://doi.org/10.21105/joss.04904","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141278771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Summary Asteroseismology, the study of stellar pulsations, offers insights into the internal structures and evolution of stars. Analysing the variations in a star’s brightness allows the determination of fundamental properties such as mass, radius, age, and chemical composition. Asteroseismology heavily relies on computational tools, but a significant number of them are closed-source, thus inaccessible to the broader astronomic community. This manuscript presents Foam , a Python package designed to perform forward asteroseismic modelling of stars exhibiting gravity modes. It automates and streamlines a considerable fraction of the modelling process, comparing grids of theoretical stellar models and their oscillation frequencies to observed frequency sets in stars. Foam offers the flexibility to employ diverse modelling approaches, allowing users to choose different methodologies for matching theoretically predicted oscillations to observations. It provides options to utilise various sets of observables for comparison with their theoretical counterparts, employ different merit functions for assessing goodness of fit, and to incorporate nested subgrids in a statistically rigorous manner. For applications of these methodologies in modelling observed gravity modes, refer to Michielsen et al. (2021) and Michielsen et al. (2023).
{"title":"Foam: A Python package for forward asteroseismic\u0000modelling of gravity modes","authors":"M. Michielsen","doi":"10.21105/joss.05884","DOIUrl":"https://doi.org/10.21105/joss.05884","url":null,"abstract":"Summary Asteroseismology, the study of stellar pulsations, offers insights into the internal structures and evolution of stars. Analysing the variations in a star’s brightness allows the determination of fundamental properties such as mass, radius, age, and chemical composition. Asteroseismology heavily relies on computational tools, but a significant number of them are closed-source, thus inaccessible to the broader astronomic community. This manuscript presents Foam , a Python package designed to perform forward asteroseismic modelling of stars exhibiting gravity modes. It automates and streamlines a considerable fraction of the modelling process, comparing grids of theoretical stellar models and their oscillation frequencies to observed frequency sets in stars. Foam offers the flexibility to employ diverse modelling approaches, allowing users to choose different methodologies for matching theoretically predicted oscillations to observations. It provides options to utilise various sets of observables for comparison with their theoretical counterparts, employ different merit functions for assessing goodness of fit, and to incorporate nested subgrids in a statistically rigorous manner. For applications of these methodologies in modelling observed gravity modes, refer to Michielsen et al. (2021) and Michielsen et al. (2023).","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141276292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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