Journal of open source software最新文献

{"title":"LightLogR: Reproducible analysis of personal light exposure data.","authors":"Johannes Zauner, Steffen Hartmeyer, Manuel Spitschan","doi":"10.21105/joss.07601","DOIUrl":"10.21105/joss.07601","url":null,"abstract":"<p><p>Light plays an important role in human health and well-being, which necessitates the study of the effects of personal light exposure in real-world settings, measured by means of wearable devices. A growing number of studies incorporate these kinds of data to assess associations between light and health outcomes. Yet with few or missing standards, guidelines, and frameworks, it is challenging setting up measurements, analysing the data, and comparing outcomes between studies. Overall, time series data from wearable light loggers are significantly more complex compared to controlled stimuli used in laboratory studies. In this paper, we introduce LightLogR, a novel resource to facilitate these research efforts. The package for R statistical software is open-source and permissively MIT-licenced. As part of a developing software ecosystem, LightLogR is built with common challenges of current and future datasets in mind. The package standardises many tasks for importing and processing personal light exposure data. It allows for quick as well as detailed insights into the datasets through summary and visualisation tools. Furthermore, LightLogR incorporates major metrics commonly used in the field (61 metrics across 17 metric families), all while embracing an inherently hierarchical, participant-based data structure.</p>","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"10 107","pages":"7601"},"PeriodicalIF":0.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7617517/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BART-Survival: A Bayesian machine learning approach to survival analyses in Python.","authors":"Jacob Tiegs, Julia Raykin, Ilia Rochlin","doi":"10.21105/joss.07213","DOIUrl":"10.21105/joss.07213","url":null,"abstract":"<p><p>BART-Survival is a Python package that allows time-to-event (survival) analyses in discrete-time using the non-parametric machine learning algorithm, Bayesian Additive Regression Trees (BART). BART-Survival combines the performance of the BART algorithm with the complementary data and model formatting required to complete the survival analyses. The library contains a convenient application programming interface (API) that allows a simple approach when using the library for survival analyses, while maintaining capabilities for added complexity when desired. The package is intended for analysts exploring use of flexible non-parametric alternatives to traditional (semi-)parametric survival analyses.</p>","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"10 105","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11848778/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143495117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IMPPY3D: Image Processing in Python for 3D Image Stacks.","authors":"Newell H Moser, Alexander K Landauer, Orion L Kafka","doi":"10.21105/joss.07405","DOIUrl":"10.21105/joss.07405","url":null,"abstract":"<p><p>Image Processing in Python for 3D image stacks, or IMPPY3D, is a free and open-source software (FOSS) repository that simplifies post-processing and 3D shape characterization for grayscale image stacks, otherwise known as volumetric images, 3D images, or voxel models. While IMPPY3D, pronounced impee-three-dee, was originally created for post-processing image stacks generated from X-ray computed tomography (XCT) measurements, it can be applied generally in post-processing 2D and 3D images. IMPPY3D includes tools for segmenting volumetric images and characterizing the 3D shape of features or regions of interest. These functionalities have proven useful in 3D shape analysis of powder particles, porous polymers, concrete aggregates, internal pores/defects, and more (see the Research Applications section). IMPPY3D consists of a combination of original Python scripts, Cython extensions, and convenience wrappers for popular third-party libraries like SciKit-Image (Walt et al., 2014), OpenCV (Bradski, 2000), and PyVista (Sullivan & Kaszynski, 2019). Highlighted capabilities of IMPPY3D include: varying image processing parameters interactively, applying numerous 2D/3D image filters (e.g., blurring/sharpening, denoising, erosion/dilation), segmenting and labeling continuous 3D objects, precisely rotating and re-slicing an image stack in 3D, generating rotated bounding boxes fitted to voxelized features, converting image stacks into 3D voxel models, exporting 3D models as Visualization Toolkik (VTK) files for ParaView (Ayachit, 2015), and converting voxel models into smooth mesh-based models. Additional information and example scripts can be found in the included ReadMe files within the IMPPY3D GitHub repository (Moser, Landauer, et al., 2024). As a visualized example, Figure 1 demonstrates the high-level steps to characterize powder particles using IMPPY3D. This workflow is also similar to how pores can be visualized and characterized in metal-based additive manufacturing. Additional research applications for IMPPY3D are discussed in a later section.</p>","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"10 108","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11984349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144061275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"harmonize-wq: Standardize, clean and wrangle Water Quality Portal data into more analytic-ready formats.","authors":"Justin Bousquin, Cristina A Mullin","doi":"10.21105/joss.07305","DOIUrl":"10.21105/joss.07305","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"9 102","pages":"7305"},"PeriodicalIF":0.0,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11694891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"primerForge: a Python program for identifying primer pairs capable of distinguishing groups of genomes from each other.","authors":"Joseph S Wirth, Lee S Katz, Grant M Williams, Jessica C Chen","doi":"10.21105/joss.06850","DOIUrl":"10.21105/joss.06850","url":null,"abstract":"<p><p>In both molecular epidemiology and microbial ecology, it is useful to be able to categorize specific strains of microorganisms in either an ingroup or an outgroup in a given population, e.g. to distinguish a pathogenic strain of interest from its non-virulent relatives. An \"ingroup\" refers to a group of microbes that are the primary focus of study or interest. Conversely, an \"outgroup\" consists of microbes that are closely-related to, but have evolved separately from, the ingroup. While whole genome sequencing and downstream phylogenetic analyses can be employed to do this, these techniques are often slow and can be resource intensive. Additionally, the laboratory would have to sequence the whole genome to use these tools to determine whether or not a new sample is part of the ingroup or outgroup. Alternatively, polymerase chain reaction (PCR) can be used to amplify regions of genetic material that are specific to the strain(s) of interest. PCR is faster, less expensive, and more accessible than whole genome sequencing, so having a PCR-based approach can accelerate the detection of specific strain(s) of microbes and facilitate diagnoses and/or population studies.</p>","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"9 101","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11611387/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142775945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"small_gicp: Efficient and parallel algorithms for point\u0000cloud registration","authors":"Kenji Koide","doi":"10.21105/joss.06948","DOIUrl":"https://doi.org/10.21105/joss.06948","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141920298","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":"gollum: An intuitive programmatic and visual interface\u0000for precomputed synthetic spectral model grids","authors":"Sujay Shankar, M. Gully-Santiago, Caroline V. Morley, Jiayi Cao, Kyle F. Kaplan, Karina Kimani-Stewart, Diana Gonzalez-Argúeta","doi":"10.21105/joss.06601","DOIUrl":"https://doi.org/10.21105/joss.06601","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"2 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141921486","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":"regional-mom6: A Python package for automatic\u0000generation of regional configurations for the Modular Ocean Model\u00006","authors":"Ashley J. Barnes, Navid C. Constantinou, A. Gibson, A. Kiss, Chris Chapman, John Reilly, Dhruv Bhagtani, Luwei Yang","doi":"10.21105/joss.06857","DOIUrl":"https://doi.org/10.21105/joss.06857","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"48 49","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141923956","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":"ExoTiC-LD: thirty seconds to stellar limb-darkening\u0000coefficients","authors":"D. Grant, H. Wakeford","doi":"10.21105/joss.06816","DOIUrl":"https://doi.org/10.21105/joss.06816","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"4 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141921851","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":"XRTpy: A Hinode-X-Ray Telescope Python Package","authors":"Joy Velasquez, Nicholas Murphy, Katharine K. Reeves, Jonathan Slavin, Mark Weber, Will T. Barnes","doi":"10.21105/joss.06396","DOIUrl":"https://doi.org/10.21105/joss.06396","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"49 42","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141923930","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}