Yan-Kai Chen, Douglas R. Houston, Manfred Auer, Steven Shave
{"title":"OpenFEPOPS: A Python implementation of the FEPOPS molecular similarity technique","authors":"Yan-Kai Chen, Douglas R. Houston, Manfred Auer, Steven Shave","doi":"10.21105/joss.05763","DOIUrl":"https://doi.org/10.21105/joss.05763","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":" 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135241389","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":"pyflowline: a mesh-independent river network generator for hydrologic models","authors":"Chang Liao, Matt G Cooper","doi":"10.21105/joss.05446","DOIUrl":"https://doi.org/10.21105/joss.05446","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"40 20","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135432380","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}
Mike Shengbo Wang, Florian Beutler, Naonori S. Sugiyama
Triumvirate is a Python/C++ package for measuring the three-point clustering statistics in large-scale structure (LSS) cosmological analyses. Given a catalogue of discrete particles (such as galaxies) with their spatial coordinates, it computes estimators of the multipoles of the three-point correlation function, also known as the bispectrum in Fourier space, in the tri-polar spherical harmonic (TripoSH) decomposition proposed by Sugiyama et al. (2019). The objective of Triumvirate is to provide efficient end-to-end measurement of clustering statistics which can be fed into downstream galaxy survey analyses to constrain and test cosmological models. To this end, it builds upon the original algorithms in the hitomi code developed by Sugiyama et al. (2018, 2019), and supplies a user-friendly interface with flexible input/output (I/O) of catalogue data and measurement results, with the built program configurable through external parameter files and tracked through enhanced logging and warning/exception handling. For completeness and complementarity, methods for measuring two-point clustering statistics are also included in the package.
{"title":"Triumvirate: A Python/C++ package for three-point clustering measurements","authors":"Mike Shengbo Wang, Florian Beutler, Naonori S. Sugiyama","doi":"10.21105/joss.05571","DOIUrl":"https://doi.org/10.21105/joss.05571","url":null,"abstract":"Triumvirate is a Python/C++ package for measuring the three-point clustering statistics in large-scale structure (LSS) cosmological analyses. Given a catalogue of discrete particles (such as galaxies) with their spatial coordinates, it computes estimators of the multipoles of the three-point correlation function, also known as the bispectrum in Fourier space, in the tri-polar spherical harmonic (TripoSH) decomposition proposed by Sugiyama et al. (2019). The objective of Triumvirate is to provide efficient end-to-end measurement of clustering statistics which can be fed into downstream galaxy survey analyses to constrain and test cosmological models. To this end, it builds upon the original algorithms in the hitomi code developed by Sugiyama et al. (2018, 2019), and supplies a user-friendly interface with flexible input/output (I/O) of catalogue data and measurement results, with the built program configurable through external parameter files and tracked through enhanced logging and warning/exception handling. For completeness and complementarity, methods for measuring two-point clustering statistics are also included in the package.","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135480416","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}
Ishaan Desai, Erik Scheurer, Carina Bringedal, Benjamin Uekermann
The Micro Manager facilitates coupling between simulation software packages, which solve problems at different physical scales. Broadly speaking, simulation-based analysis is an effective tool to gain insights in real-world scenarios without incurring the high cost of prototyping and testing. Complex simulations are oftentimes broken down into simpler components, which are resolved by tailor-made software. Such complex simulations can be of multiphysics nature, meaning different physics are solved in different parts of the domain. To do such multiphysics simulations, we can couple different software packages together. preCICE (Chourdakis et al., 2022) is an open-source coupling library for partitioned multiphysics simulations. However, sometimes the coupling is not just between different physics but also different physical scales, which is frequently referred to as multiscale coupling. To understand how the scales affect each other, both scales need to be solved simultaneously while being coupled in a bi-directional manner. The Micro Manager, together with preCICE, is capable of handling a multiphysics and multiscale coupling. We refer to the coarse scale as the macro scale, and the fine scale as the micro scale. The name Micro Manager is derived from its core functionality of controlling a set of micro-scale simulations and coupling them to one macro-scale simulation via preCICE.
{"title":"Micro Manager: a Python package for adaptive and flexible two-scale coupling","authors":"Ishaan Desai, Erik Scheurer, Carina Bringedal, Benjamin Uekermann","doi":"10.21105/joss.05842","DOIUrl":"https://doi.org/10.21105/joss.05842","url":null,"abstract":"The Micro Manager facilitates coupling between simulation software packages, which solve problems at different physical scales. Broadly speaking, simulation-based analysis is an effective tool to gain insights in real-world scenarios without incurring the high cost of prototyping and testing. Complex simulations are oftentimes broken down into simpler components, which are resolved by tailor-made software. Such complex simulations can be of multiphysics nature, meaning different physics are solved in different parts of the domain. To do such multiphysics simulations, we can couple different software packages together. preCICE (Chourdakis et al., 2022) is an open-source coupling library for partitioned multiphysics simulations. However, sometimes the coupling is not just between different physics but also different physical scales, which is frequently referred to as multiscale coupling. To understand how the scales affect each other, both scales need to be solved simultaneously while being coupled in a bi-directional manner. The Micro Manager, together with preCICE, is capable of handling a multiphysics and multiscale coupling. We refer to the coarse scale as the macro scale, and the fine scale as the micro scale. The name Micro Manager is derived from its core functionality of controlling a set of micro-scale simulations and coupling them to one macro-scale simulation via preCICE.","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"345 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135475294","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":"measr: Bayesian psychometric measurement using Stan","authors":"W. Jake Thompson","doi":"10.21105/joss.05742","DOIUrl":"https://doi.org/10.21105/joss.05742","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"19 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135589505","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}
Jackson W. Burns, Kevin A. Spiekermann, Himaghna Bhattacharjee, Dionisios G. Vlachos, William H. Green
{"title":"Machine Learning Validation via Rational Dataset Sampling with astartes","authors":"Jackson W. Burns, Kevin A. Spiekermann, Himaghna Bhattacharjee, Dionisios G. Vlachos, William H. Green","doi":"10.21105/joss.05996","DOIUrl":"https://doi.org/10.21105/joss.05996","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"79 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135725093","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}
David McCoy, Alejandro Schuler, Alan Hubbard, Mark van der Laan
McCoy et al., (2023). SuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in R. Journal of Open Source Software, 8(91), 5422, https://doi.org/10.21105/joss.05422
{"title":"SuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in R","authors":"David McCoy, Alejandro Schuler, Alan Hubbard, Mark van der Laan","doi":"10.21105/joss.05422","DOIUrl":"https://doi.org/10.21105/joss.05422","url":null,"abstract":"McCoy et al., (2023). SuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in R. Journal of Open Source Software, 8(91), 5422, https://doi.org/10.21105/joss.05422","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"56 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135725280","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}
Ilian Pihlajamaa, Corentin C. L. Laudicina, Thomas Voigtmann, Liesbeth M. C. Janssen
Pihlajamaa et al., (2023). ModeCouplingTheory.jl: A solver for mode-coupling-theory-like integro-differential equations. Journal of Open Source Software, 8(91), 5737, https://doi.org/10.21105/joss.05737
{"title":"ModeCouplingTheory.jl: A solver for mode-coupling-theory-like integro-differential equations","authors":"Ilian Pihlajamaa, Corentin C. L. Laudicina, Thomas Voigtmann, Liesbeth M. C. Janssen","doi":"10.21105/joss.05737","DOIUrl":"https://doi.org/10.21105/joss.05737","url":null,"abstract":"Pihlajamaa et al., (2023). ModeCouplingTheory.jl: A solver for mode-coupling-theory-like integro-differential equations. Journal of Open Source Software, 8(91), 5737, https://doi.org/10.21105/joss.05737","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"42 16","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135820023","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}
Chang et al., (2023). GGoutlieR: an R package to identify and visualize unusual geo-genetic patterns of biological samples. Journal of Open Source Software, 8(91), 5687, https://doi.org/10.21105/joss.05687
{"title":"GGoutlieR: an R package to identify and visualize unusual geo-genetic patterns of biological samples","authors":"Che-Wei Chang, Karl Schmid","doi":"10.21105/joss.05687","DOIUrl":"https://doi.org/10.21105/joss.05687","url":null,"abstract":"Chang et al., (2023). GGoutlieR: an R package to identify and visualize unusual geo-genetic patterns of biological samples. Journal of Open Source Software, 8(91), 5687, https://doi.org/10.21105/joss.05687","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"47 3-4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135270971","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}
Lucas Esclapez, Marc Day, John Bell, Anne Felden, Candace Gilet, Ray Grout, Marc Henry de Frahan, Emmanuel Motheau, Andrew Nonaka, Landon Owen, Bruce Perry, Jon Rood, Nicolas Wimer, Weiqun Zhang
{"title":"PeleLMeX: an AMR Low Mach Number Reactive Flow Simulation Code without level sub-cycling","authors":"Lucas Esclapez, Marc Day, John Bell, Anne Felden, Candace Gilet, Ray Grout, Marc Henry de Frahan, Emmanuel Motheau, Andrew Nonaka, Landon Owen, Bruce Perry, Jon Rood, Nicolas Wimer, Weiqun Zhang","doi":"10.21105/joss.05450","DOIUrl":"https://doi.org/10.21105/joss.05450","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"2008 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135813640","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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