Fred Shone, Theodore Chatziioannou, B. Pickering, Kasia Kozlowska, Michael Fitzmaurice
{"title":"PAM: Population Activity Modeller","authors":"Fred Shone, Theodore Chatziioannou, B. Pickering, Kasia Kozlowska, Michael Fitzmaurice","doi":"10.21105/joss.06097","DOIUrl":"https://doi.org/10.21105/joss.06097","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":"140 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140668556","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}
Clàudia Rodés-Bachs, Jon Sampedro, Russell Horowitz, Dirk-Jan Van de Ven, R. Cui, Alicia Zhao, Matthew Zwerling, Zarrar Khan
{"title":"gcamreport: An R tool to process and standardize GCAM\u0000outputs","authors":"Clàudia Rodés-Bachs, Jon Sampedro, Russell Horowitz, Dirk-Jan Van de Ven, R. Cui, Alicia Zhao, Matthew Zwerling, Zarrar Khan","doi":"10.21105/joss.05975","DOIUrl":"https://doi.org/10.21105/joss.05975","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":"16 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140676408","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}
Xin Zhao, M. Chepeliev, P. Patel, Marshall A Wise, Katherine Calvin, Kanishka B. Narayan, Chris R. Vernon
The gcamfaostat R package is designed for the preparation, processing, and synthesis of the Food and Agriculture Organization (FAO) Statistics (FAOSTAT) agroeconomic data. The primary purpose is to facilitate FAOSTAT data use in global economic and multisector dynamic models while ensuring transparency, traceability, and reproducibility. Here, we provide an overview of the development of gcamfaostat v1.0.0 and demonstrate its capabilities in generating and maintaining agroeconomic data required for the Global Change Analysis Model (GCAM). Our initiative seeks to enhance the quality and accessibility of data for the global agroeconomic modeling community, with the aim of fostering more robust and harmonized outcomes in a collaborative, efficient, and open-source framework. The processed data and visualizations offered by gcamfaostat can also be valuable to a broader audience interested in gaining insights into the intricacies of global agriculture.
gcamfaostat R 软件包设计用于准备、处理和综合粮食及农业组织（FAO）统计（FAOSTAT）的农业经济数据。其主要目的是促进 FAOSTAT 数据在全球经济和多部门动态模型中的使用，同时确保透明度、可追溯性和可重复性。在此，我们将概述 gcamfaostat v1.0.0 的开发过程，并展示其在生成和维护全球变化分析模型（GCAM）所需的农业经济数据方面的能力。我们的倡议旨在提高全球农业经济建模界的数据质量和可访问性，目的是在一个协作、高效和开源的框架内促进更强大和更协调的成果。gcamfaostat 提供的经过处理的数据和可视化效果，对于有兴趣深入了解错综复杂的全球农业的广大受众来说，也是非常有价值的。
{"title":"gcamfaostat: An R package to prepare, process, and\u0000synthesize FAOSTAT data for global agroeconomic and multisector dynamic\u0000modeling","authors":"Xin Zhao, M. Chepeliev, P. Patel, Marshall A Wise, Katherine Calvin, Kanishka B. Narayan, Chris R. Vernon","doi":"10.21105/joss.06388","DOIUrl":"https://doi.org/10.21105/joss.06388","url":null,"abstract":"The gcamfaostat R package is designed for the preparation, processing, and synthesis of the Food and Agriculture Organization (FAO) Statistics (FAOSTAT) agroeconomic data. The primary purpose is to facilitate FAOSTAT data use in global economic and multisector dynamic models while ensuring transparency, traceability, and reproducibility. Here, we provide an overview of the development of gcamfaostat v1.0.0 and demonstrate its capabilities in generating and maintaining agroeconomic data required for the Global Change Analysis Model (GCAM). Our initiative seeks to enhance the quality and accessibility of data for the global agroeconomic modeling community, with the aim of fostering more robust and harmonized outcomes in a collaborative, efficient, and open-source framework. The processed data and visualizations offered by gcamfaostat can also be valuable to a broader audience interested in gaining insights into the intricacies of global agriculture.","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":"29 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140676044","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}
ZodiPy is an Astropy-affiliated Python package for zodiacal light simulations. Its purpose is to provide the astrophysics and cosmology communities with an accessible and easy-to-use Python interface to existing zodiacal light models, assisting in the analysis of infrared astrophysical data and enabling quick and easy zodiacal light forecasting for future experiments. ZodiPy implements the Kelsall et al. (1998) and the Planck Collaboration et al. (2014) interplanetary dust models, which allow for zodiacal light simulations between 1.25−240𝜇 m and 30−857 GHz, respectively, with the possibility of extrapolating the models to other frequencies.
{"title":"ZodiPy: A Python package for zodiacal light\u0000simulations","authors":"Metin San","doi":"10.21105/joss.06648","DOIUrl":"https://doi.org/10.21105/joss.06648","url":null,"abstract":"ZodiPy is an Astropy-affiliated Python package for zodiacal light simulations. Its purpose is to provide the astrophysics and cosmology communities with an accessible and easy-to-use Python interface to existing zodiacal light models, assisting in the analysis of infrared astrophysical data and enabling quick and easy zodiacal light forecasting for future experiments. ZodiPy implements the Kelsall et al. (1998) and the Planck Collaboration et al. (2014) interplanetary dust models, which allow for zodiacal light simulations between 1.25−240𝜇 m and 30−857 GHz, respectively, with the possibility of extrapolating the models to other frequencies.","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":"104 47","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140680257","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 Berlok, Léna Jlassi, E. Puchwein, T. Haugbølle
We present Paicos, a new object-oriented Python package for analyzing simulations performed with Arepo. Paicos strives to reduce the learning curve for students and researchers getting started with Arepo simulations. As such, Paicos includes many examples in the form of Python scripts and Jupyter notebooks as well as an online documentation describing the installation procedure and recommended first steps. Paicos' main features are automatic handling of cosmological and physical units, computation of derived variables, 2D visualization (slices and projections), 1D and 2D histograms, and easy saving and loading of derived data including units and all the relevant metadata.
{"title":"Paicos: A Python package for analysis of (cosmological)\u0000simulations performed with Arepo","authors":"Thomas Berlok, Léna Jlassi, E. Puchwein, T. Haugbølle","doi":"10.21105/joss.06296","DOIUrl":"https://doi.org/10.21105/joss.06296","url":null,"abstract":"We present Paicos, a new object-oriented Python package for analyzing simulations performed with Arepo. Paicos strives to reduce the learning curve for students and researchers getting started with Arepo simulations. As such, Paicos includes many examples in the form of Python scripts and Jupyter notebooks as well as an online documentation describing the installation procedure and recommended first steps. Paicos' main features are automatic handling of cosmological and physical units, computation of derived variables, 2D visualization (slices and projections), 1D and 2D histograms, and easy saving and loading of derived data including units and all the relevant metadata.","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":"8 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140681382","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":"sectionproperties: A Python package for the analysis of\u0000arbitrary cross-sections using the finite element method","authors":"Robbie van Leeuwen, Connor Ferster","doi":"10.21105/joss.06105","DOIUrl":"https://doi.org/10.21105/joss.06105","url":null,"abstract":"package","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":" 27","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140683351","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":"AHGestimation: An R package for computing robust, mass\u0000preserving hydraulic geometries and rating curves","authors":"J. M. Johnson, Shahab Afshari, Arash Modaresi Rad","doi":"10.21105/joss.06145","DOIUrl":"https://doi.org/10.21105/joss.06145","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":" 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140686675","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":"UltraDark.jl: A Julia package for simulation of\u0000cosmological scalar fields","authors":"Nathan Musoke","doi":"10.21105/joss.06035","DOIUrl":"https://doi.org/10.21105/joss.06035","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":" 42","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140692605","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":"Fitspy: A Python package for spectral\u0000decomposition","authors":"Patrick Quéméré","doi":"10.21105/joss.05868","DOIUrl":"https://doi.org/10.21105/joss.05868","url":null,"abstract":"","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":"78 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140702739","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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