Last updated: 2024-07-04
Checks: 2 0
Knit directory: MATHPOP/
This reproducible R Markdown analysis was created with workflowr (version 1.7.1). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version 24ec3c5. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for
the analysis have been committed to Git prior to generating the results
(you can use wflow_publish or
wflow_git_commit). workflowr only checks the R Markdown
file, but you know if there are other scripts or data files that it
depends on. Below is the status of the Git repository when the results
were generated:
Ignored files:
Ignored: .DS_Store
Ignored: analysis/.DS_Store
Ignored: analysis/GC_prob_cache/
Ignored: data/.DS_Store
Ignored: data/GC_prob/.DS_Store
Ignored: data/point_source_data/.DS_Store
Ignored: data/prob_GC_data/.DS_Store
Ignored: data/sim/.DS_Store
Ignored: data/v10acs/.DS_Store
Ignored: data/v10wfc3/.DS_Store
Ignored: data/v11acs/.DS_Store
Ignored: data/v11wfc3/.DS_Store
Ignored: data/v12acs/.DS_Store
Ignored: data/v12wfc3/.DS_Store
Ignored: data/v13acs/.DS_Store
Ignored: data/v13wfc3/.DS_Store
Ignored: data/v14acs/.DS_Store
Ignored: data/v14wfc3/.DS_Store
Ignored: data/v15acs/.DS_Store
Ignored: data/v15wfc3/.DS_Store
Ignored: data/v6acs/.DS_Store
Ignored: data/v6wfc3/.DS_Store
Ignored: data/v7acs/.DS_Store
Ignored: data/v8acs/.DS_Store
Ignored: data/v9acs/.DS_Store
Ignored: data/v9wfc3/.DS_Store
Unstaged changes:
Modified: analysis/GC_prob.Rmd
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were
made to the R Markdown (analysis/index.Rmd) and HTML
(docs/index.html) files. If you’ve configured a remote Git
repository (see ?wflow_git_remote), click on the hyperlinks
in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | d45548a | david.li | 2024-07-03 | data |
| html | 0b819e1 | david.li | 2024-07-03 | Build site. |
| html | 44c0586 | david.li | 2024-07-03 | Build site. |
| html | 345edbd | david.li | 2024-07-03 | Build site. |
| html | 957c2e2 | david.li | 2024-07-03 | Build site. |
| Rmd | 199856c | david.li | 2024-07-03 | wflow_publish(c("analysis/index.Rmd", "analysis/vignette.Rmd", |
| html | 3030b0c | david.li | 2024-07-03 | Build site. |
| html | 9541472 | david.li | 2024-07-03 | Build site. |
| Rmd | 6b708af | david.li | 2024-07-03 | wflow_publish("analysis/index.Rmd") |
| Rmd | db0f025 | david.li | 2024-07-03 | Initial Build |
| html | db0f025 | david.li | 2024-07-03 | Initial Build |
Welcome to MATHPOP, a R software for inferring globular
cluster (GC) counts in low-surface brightness galaxies (LSBGs) and
ultra-diffuse galaxies (UDGs). The R code in this repo is
written based on the framework of MArk-dependently THinned POint Process
(MATHPOP) proposed by Li et al. (2024), “Discovery of Two
Ultra-Diffuse Galaxies with Unusually Bright Globular Cluster Luminosity
Functions via a Mark-Dependently Thinned Point Process
(MATHPOP)”.
If you have not used R before, R is a
powerful open source language designed for statistical computing and
data analysis. Download R at The Comprehensive R Archive Network
(CRAN) and RStudio.
R is the base language environment that executes all
programs and code. RStudio is an integrated user interface
wrapper that makes the base R easy to use (similar to
Jupyter Notebook for Python).
To use the code for your own data, go to the MATHPOP Github repo and
download the repository. The R code to fit the MATHPOP
model is contained in the code/ directory. The
data/ directory contains the GC data analyzed in the
original paper.