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bayes_traj

bayes_traj: A Python package for Bayesian trajectory analysis - Published in JOSS (2025)

https://github.com/acil-bwh/bayes_traj

Science Score: 100.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 1 DOI reference(s) in JOSS metadata
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 2 committers (50.0%) from academic institutions
  • ○
    Institutional organization owner
  • ✓
    JOSS paper metadata
    Published in Journal of Open Source Software

Scientific Fields

Economics Social Sciences - 85% confidence
Last synced: 4 months ago · JSON representation ·

Repository

Algorithms and tools for Bayesian trajectory modeling

Basic Info
  • Host: GitHub
  • Owner: acil-bwh
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: master
  • Size: 38.3 MB
Statistics
  • Stars: 6
  • Watchers: 2
  • Forks: 2
  • Open Issues: 2
  • Releases: 0
Created over 5 years ago · Last pushed 7 months ago
Metadata Files
Readme Contributing License Citation

README.md

Introduction

bayes_traj is a software package written in Python that provides routines for performing Bayesian trajectory modeling of longitudinal data. Multiple, longitudinally observed target variables -- continuous, binary, or a combination -- can be modeled simultaneously. Per-trajectory random effects can also be modeled for continuous target variables. This package also provides command-line tools that facilitate spefication of Bayesian priors, enable visualization of trajectory modeling results, and compute summary and model fit statistics.

Installation

In order to install the package, type the folowing in the terminal:

$ pip install bayes_traj

Overview

bayes_traj provides several command-line tools:

  • generate_prior -- used to speficy Bayesian priors for use the trajectory modeling
  • viz_data_prior_draws -- provides visualization of random draws from the prior
  • bayes_traj_main -- performs Bayesian trajectory modeling using a prior file
  • viz_model_trajs -- provides visualization of trajectories fit using bayes_traj_main
  • sumarize_traj_model -- prints model summary and fit statistics given a model file produce by bayes_traj_main
  • assign_trajectory -- writes a data file with appended trajectory assignment information given an input data file and a model file generated by the bayes_traj_main tool

Each of these tools can be run with the -h flag for additional usage information.

For additional documentation, see https://acil-bwh.github.io/bayes_traj/index.html

Tests

To run all unit tests, type the following in the package root directory:

$ pytest

Contribute

Please read our contribution guidelines.

Owner

  • Login: acil-bwh
  • Kind: user

JOSS Publication

bayes_traj: A Python package for Bayesian trajectory analysis
Published
April 15, 2025
DOI
Volume 10, Issue 108, Page 7323
Authors
James C. Ross ORCID
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States of America, For correspondence, contact jcross186@gmail.com
Tingting Zhao
College of Business, University of Rhode Island, Kingston, RI, United States of America
Editor
Mark A. Jensen ORCID
Tags
trajectories Bayesian
View PDF Review Thread Software Archive

Citation (CITATION.cff) 

cff-version: "1.2.0"
authors:
- family-names: Ross
  given-names: James C.
  orcid: "https://orcid.org/0000-0002-2338-3644"
- family-names: Zhao
  given-names: Tingting
doi: 10.5281/zenodo.15047374
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Ross
    given-names: James C.
    orcid: "https://orcid.org/0000-0002-2338-3644"
  - family-names: Zhao
    given-names: Tingting
  date-published: 2025-04-15
  doi: 10.21105/joss.07323
  issn: 2475-9066
  issue: 108
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 7323
  title: "bayes_traj: A Python package for Bayesian trajectory analysis"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.07323"
  volume: 10
title: "bayes_traj: A Python package for Bayesian trajectory analysis"

GitHub Events

Total
  • Issues event: 5
  • Watch event: 1
  • Issue comment event: 10
  • Push event: 27
  • Pull request review event: 1
  • Pull request event: 2
  • Fork event: 1
  • Create event: 1
Last Year
  • Issues event: 5
  • Watch event: 1
  • Issue comment event: 10
  • Push event: 27
  • Pull request review event: 1
  • Pull request event: 2
  • Fork event: 1
  • Create event: 1

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 306
  • Total Committers: 2
  • Avg Commits per committer: 153.0
  • Development Distribution Score (DDS): 0.003
Top Committers
Name Email Commits
James Ross j****s@b****u 305
acil-bwh a****h@u****m 1
Committer Domains (Top 20 + Academic)
bwh.harvard.edu: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 5
  • Total pull requests: 2
  • Average time to close issues: 6 days
  • Average time to close pull requests: 4 days
  • Total issue authors: 2
  • Total pull request authors: 2
  • Average comments per issue: 2.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 3
  • Pull requests: 1
  • Average time to close issues: 6 days
  • Average time to close pull requests: 7 days
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 3.33
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • gchure (3)
  • jcross186 (2)
Pull Request Authors
  • miaroe (2)
  • fritzo (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 171 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 31
  • Total maintainers: 1
pypi.org: bayes-traj

bayes_traj

  • Versions: 31
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 171 Last month
Rankings
Dependent packages count: 10.1%
Dependent repos count: 21.6%
Average: 22.3%
Downloads: 25.0%
Stargazers count: 25.0%
Forks count: 29.8%
Maintainers (1)
jcross186
Last synced: 4 months ago

Dependencies

setup.py pypi
  • argparse *
  • matplotlib *
  • numpy *
  • pandas *
  • provenance-tools *
  • scipy *
  • statsmodels *