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A Python implementation of CLUMP, the Code Library to generate Universal Multi-sphere Particles 用于生成通用多球粒子的代码库 CLUMP 的 Python 实现
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-11-23 DOI: 10.1016/j.softx.2024.101957
Ahmet Utku Canbolat , Sadegh Nadimi , Vasileios Angelidakis
{"title":"A Python implementation of CLUMP, the Code Library to generate Universal Multi-sphere Particles","authors":"Ahmet Utku Canbolat ,&nbsp;Sadegh Nadimi ,&nbsp;Vasileios Angelidakis","doi":"10.1016/j.softx.2024.101957","DOIUrl":"10.1016/j.softx.2024.101957","url":null,"abstract":"<div><div>Multi-spheres are widely employed to model non-spherical particles in the Discrete Element Method. For the past three years, the <span>CLUMP</span> code has provided the means to compare different multi-sphere particle generation methods in a quantitative manner, via the implementation of different particle generation methods within a single software package. This paper reports on the evolution of the software, underpinned by the following recent developments: (1) a <span>Python</span> implementation of <span>CLUMP</span>, which is maintained alongside the original <span>MATLAB</span> code, and (2) the extension of the Euclidean transform method proposed in the original <span>CLUMP</span> paper to bonded and crushable particles. The new <span>Python</span> implementation and feature development enhance the accessibility of the software to a wider user base and generalize its applicability to a more diverse set of problems.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"29 ","pages":"Article 101957"},"PeriodicalIF":2.4,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
pyRoCS: A Python package to evaluate the resilience of complex systems pyRoCS：评估复杂系统复原力的 Python 软件包
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-11-21 DOI: 10.1016/j.softx.2024.101977
Amanda Wachtel, Thushara Gunda, Susan Caskey, Ryan Cooper, Thomas Womack, Kirk Bonney, Kenneth Kliesner
{"title":"pyRoCS: A Python package to evaluate the resilience of complex systems","authors":"Amanda Wachtel,&nbsp;Thushara Gunda,&nbsp;Susan Caskey,&nbsp;Ryan Cooper,&nbsp;Thomas Womack,&nbsp;Kirk Bonney,&nbsp;Kenneth Kliesner","doi":"10.1016/j.softx.2024.101977","DOIUrl":"10.1016/j.softx.2024.101977","url":null,"abstract":"<div><div>This paper introduces pyRoCS, an open source Python-based software that enables users to quantify resilience of complex systems. The metrics used to quantify resilience are sourced from peer-reviewed publications across multiple domains, including information theory, biosciences, and complex systems. Functions within associated domain modules can be combined based on user needs to support the characterization of resilience. Data structures from various domains (e.g., media coverage, organizational structures, and hazard analyses in critical infrastructures) could be analyzed using metrics within pyRoCS, including those collected in the field or derived from modeling and simulations. The conversion of these existing metrics into a formal software package increases the robustness and transparency of current implementations. Furthermore, the inclusion of multiple disciplinary metrics enables exploration of how resilience concepts are translated into practice, an area of interest in multiple domains.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"29 ","pages":"Article 101977"},"PeriodicalIF":2.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
“streetscape” package in R: A reproducible method for analyzing open-source street view datasets and facilitating research for urban analytics R 中的 "streetcape "软件包：分析开源街景数据集和促进城市分析研究的可复制方法
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-11-21 DOI: 10.1016/j.softx.2024.101981
Xiaohao Yang, Mark Lindquist, Derek Van Berkel
{"title":"“streetscape” package in R: A reproducible method for analyzing open-source street view datasets and facilitating research for urban analytics","authors":"Xiaohao Yang,&nbsp;Mark Lindquist,&nbsp;Derek Van Berkel","doi":"10.1016/j.softx.2024.101981","DOIUrl":"10.1016/j.softx.2024.101981","url":null,"abstract":"<div><div>Street view imagery (SVI) is an increasingly important data source for urban analytics and environmental researchers studying the visual quality of the built environment. Compared to remote sensing imagery, SVI can provide a different plane of perspective at ground level and better determine the interplay between urban physical settings and socio-ecological factors that enhance well-being and sustainability. Mapillary, a platform for volunteered street view imagery, has emerged as a promising alternative to Google Street View, offering greater accessibility. Nonetheless, the utility of this open-source database can be limited by the current Mapillary Application Programming Interface (API), which only partially meets the needs of urban analytics research. To address this, we introduce \"streetscape,\" an R package designed to provide user-friendly functions for collecting and analyzing street view imagery data from Mapillary. In addition, the package supports the generation of surveys for the qualitative study of urban landscapes.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"29 ","pages":"Article 101981"},"PeriodicalIF":2.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
LeXInt: GPU-accelerated exponential integrators package LeXInt：GPU 加速指数积分器软件包
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-11-21 DOI: 10.1016/j.softx.2024.101949
Pranab J. Deka , Alexander Moriggl, Lukas Einkemmer
{"title":"LeXInt: GPU-accelerated exponential integrators package","authors":"Pranab J. Deka ,&nbsp;Alexander Moriggl,&nbsp;Lukas Einkemmer","doi":"10.1016/j.softx.2024.101949","DOIUrl":"10.1016/j.softx.2024.101949","url":null,"abstract":"<div><div>We present an open-source <span>CUDA</span>-based package, for the temporal integration of differential equations, that consists of a compilation of exponential integrators where the action of the matrix exponential or the <span><math><msub><mrow><mi>φ</mi></mrow><mrow><mi>l</mi></mrow></msub></math></span> functions on a vector is approximated using the method of polynomial interpolation at Leja points. Using a couple of test examples on an NVIDIA A100 GPU, we show that one can achieve significant speedups using <span>CUDA</span> over the corresponding CPU code. <span>LeXInt</span>, written in a modular format, facilitates integration into existing software packages (written in <span>C++</span> or <span>CUDA</span>), for temporal integration of differential equations.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"29 ","pages":"Article 101949"},"PeriodicalIF":2.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
HOPE: Holistic Optimization Program for Electricity HOPE：电力整体优化计划
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-11-21 DOI: 10.1016/j.softx.2024.101982
Shen Wang , Ziying Song , Mahdi Mehrtash , Benjamin F. Hobbs
{"title":"HOPE: Holistic Optimization Program for Electricity","authors":"Shen Wang ,&nbsp;Ziying Song ,&nbsp;Mahdi Mehrtash ,&nbsp;Benjamin F. Hobbs","doi":"10.1016/j.softx.2024.101982","DOIUrl":"10.1016/j.softx.2024.101982","url":null,"abstract":"<div><div>In this paper, we present a novel open-source electricity systems optimization tool, the Holistic Optimization Program for Electricity (HOPE), to assess emerging generation technology, inform policy design, and support planning. With a highly transparent, interpretable, and compact model design, HOPE easily allows user access and modification, serving its main goal to benefit users beyond engineer communities and facilitate collaboration across the science-policy boundary. By activating different modes, the current version of HOPE (v1.0) offers flexibility in serving as either a Generation and Transmission Expansion Planning tool (GTEP) or a Production Cost Modelling tool (PCM). It includes modelling features such as long-term resource investments, short-term system operations, and a detailed representation of policies across various levels of regulated institutions. This paper outlines the building blocks of the model and its software structure. Case study results from using HOPE for the state of Maryland as well as the Pennsylvania-New Jersey-Maryland (PJM) footprint are also provided.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"29 ","pages":"Article 101982"},"PeriodicalIF":2.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
NiaAML: AutoML for classification and regression pipelines NiaAML：用于分类和回归管道的 AutoML
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-11-20 DOI: 10.1016/j.softx.2024.101974
Iztok Fister Jr. , Laurenz A. Farthofer , Luka Pečnik , Iztok Fister , Andreas Holzinger
{"title":"NiaAML: AutoML for classification and regression pipelines","authors":"Iztok Fister Jr. ,&nbsp;Laurenz A. Farthofer ,&nbsp;Luka Pečnik ,&nbsp;Iztok Fister ,&nbsp;Andreas Holzinger","doi":"10.1016/j.softx.2024.101974","DOIUrl":"10.1016/j.softx.2024.101974","url":null,"abstract":"<div><div>In this paper we present NiaAML, an AutoML framework that we have developed for creating machine learning pipelines and hyperparameter tuning. The composition of machine learning pipelines is presented as an optimization problem that can be solved using various stochastic, population-based, nature-inspired algorithms. Nature-inspired algorithms are powerful tools for solving real-world optimization problems, especially those that are highly complex, nonlinear, and involve large search spaces where traditional algorithms may struggle. They are applied widely in various fields, including robotics, operations research, and bioinformatics. This paper provides a comprehensive overview of the software architecture, and describes the main tasks of NiaAML, including the automatic composition of classification and regression pipelines. The overview is supported by an practical illustrative example.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"29 ","pages":"Article 101974"},"PeriodicalIF":2.4,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
CDSupdate: A meta-interface for ERA5 download request, management and storage CDSupdate：用于ERA5下载请求、管理和存储的元接口
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-11-19 DOI: 10.1016/j.softx.2024.101965
Andreia N.S. Hisi , Yoann Robin , Davide Faranda , Mathieu Vrac
{"title":"CDSupdate: A meta-interface for ERA5 download request, management and storage","authors":"Andreia N.S. Hisi ,&nbsp;Yoann Robin ,&nbsp;Davide Faranda ,&nbsp;Mathieu Vrac","doi":"10.1016/j.softx.2024.101965","DOIUrl":"10.1016/j.softx.2024.101965","url":null,"abstract":"<div><div>CDSupdate is a Python package that automates the process of retrieving, processing, and managing climate data from the Copernicus Climate Change Service (C3S) Climate Data Store (CDS). The tool generates daily climate data summaries, performs calculations to create custom variables such as <em>relative humidity</em> and <em>heat index</em> which serve as risk assessments, and organizes the data into a user-friendly format. By simplifying data retrieval and performing on-the-fly calculations, it saves users valuable time and effort, enabling more focus on data analysis and interpretation.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101965"},"PeriodicalIF":2.4,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142704696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PACU: Precision agriculture computational utilities PACU：精准农业计算实用程序
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-11-19 DOI: 10.1016/j.softx.2024.101971
Caio L. dos Santos, Fernando E. Miguez
{"title":"PACU: Precision agriculture computational utilities","authors":"Caio L. dos Santos,&nbsp;Fernando E. Miguez","doi":"10.1016/j.softx.2024.101971","DOIUrl":"10.1016/j.softx.2024.101971","url":null,"abstract":"<div><div>The field of precision agriculture relies on collecting and processing several types of data to assess temporal and spatial variability. We developed the <em>pacu</em> R package to provide a comprehensive and transparent framework for precision agriculture applications. The package includes functions to process and visualize yield monitor data from production and experimental fields. In addition, <em>pacu</em> facilitates the retrieval, processing, and visualization of satellite images from Copernicus Data Space. Lastly, there are functions to retrieve, summarize, and visualize long-term weather data. The current package is intended to facilitate the access by researchers and agronomists to routine precision agriculture computational utilities.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101971"},"PeriodicalIF":2.4,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142704695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The pymcdm-reidentify tool: Advanced methods for MCDA model re-identification pymcdm-reidentify 工具：MCDA 模型再识别的高级方法
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-11-15 DOI: 10.1016/j.softx.2024.101960
Bartłomiej Kizielewicz, Wojciech Sałabun
{"title":"The pymcdm-reidentify tool: Advanced methods for MCDA model re-identification","authors":"Bartłomiej Kizielewicz,&nbsp;Wojciech Sałabun","doi":"10.1016/j.softx.2024.101960","DOIUrl":"10.1016/j.softx.2024.101960","url":null,"abstract":"<div><div>The <span>pymcdm-reidentify</span> tool addresses the challenge of reconstructing multi-criteria decision analysis (MCDA) and decision-making (MCDM) models when original parameters are unavailable, but rankings are known. This Python package integrates with existing MCDA libraries and uses stochastic optimization to determine model parameters such as criterion weights and reference objects. Built on the <span>pymcdm</span> and <span>Mealpy</span> libraries, <span>pymcdm-reidentify</span> offers advanced methods for model re-identification, including visualization and fuzzy normalization. Its capabilities facilitate the update and adaptation of decision models, enhancing accuracy and efficiency in both academic and practical applications.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101960"},"PeriodicalIF":2.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Version [1.0]- HAT-VIS — A MATLAB-based hypergraph visualization tool 版本 [1.0]- HAT-VIS - 基于 MATLAB 的超图可视化工具
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-11-15 DOI: 10.1016/j.softx.2024.101963
Tímea Czvetkó, János Abonyi
{"title":"Version [1.0]- HAT-VIS — A MATLAB-based hypergraph visualization tool","authors":"Tímea Czvetkó,&nbsp;János Abonyi","doi":"10.1016/j.softx.2024.101963","DOIUrl":"10.1016/j.softx.2024.101963","url":null,"abstract":"<div><div>HAT-VIS is a hypergraph visualization tool designed within the MATLAB environment, serving to depict the inherent relationships present within hypergraphs. The current scarcity of MATLAB tools dedicated to the analysis and visualization of hypergraphs necessitated the development of the HAT-VIS, which can be an independent, standalone tool or integrated within the HAT: Hypergraph Analysis Toolbox and other MATLAB libraries. HAT-VIS offers a valuable resource for visualizing hypergraphs by leveraging vertex similarities through multidimensional scaling, providing additional interpretable insights based on the location of vertices, in contrast to the predominantly employed forced layout techniques in existing hypergraph visualization tools. The proposed tool can be used to inform decision making by discovering relationships between vertices. The applicability of HAT-VIS is demonstrated through an illustrative case study on the development of electric vehicles.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101963"},"PeriodicalIF":2.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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