perwin / barprofiles_paper

Files and Jupyter notebooks for paper on bar major-axis profiles

Public data, code, and notebooks for paper analyzing bar-major-axis profiles

This git repository contains data files, Python code, and Python and R Jupyter notebooks which can be used to reproduce figures and analyses from the paper "The Profiles of Bars in Barred Galaxies" (Erwin, Debattista, & Anderson 2023, Monthly Notices of the Royal Astronomical Society, 524: 3166; arXiv:2306.15739).

Logistic fits for Peak+Shoulders bar profiles (left) and B/P-bulge presence (right) for barred spirals, versus galaxy stellar mass.

Data

The full set of Spitzer 3.6-micron images for the sample galaxies can be found at, e.g., the NASA Extragalactic Database; to make it easier to reproduce Figure 1 of the paper, we include sky-subtracted versions of these images for three of the galaxies in the data/images folder.

Dependencies

The Python code and notebooks require the following external Python modules and packages, all of which are available on PyPI and can be installed via pip:

• Numpy, Scipy, matplotlib, Astropy

Jupyter Notebooks

There are two Jupyter notebooks:

• barprofiles_figures_for_paper.ipynb -- Python notebook; generates the figures for the paper

• barprofiles_R_logistic-regression.ipynb -- R notebook; computes logistic regressions

Python Code

• angle_utils.py, barprofile_utils.py, plotutils.py -- miscellaneous utility functions (including statistics).

How to Generate Figures and Analyses from the Paper

1. Download this repository.

2. Edit paths in the notebooks so they point to the correct locations, if necessary. See notes in the initial cells of the notebooks; the main variable you will probably need to edit is plotDir in the second cell of barprofiles_figures_for_paper.ipynb, which is where saved PDF figures should go. Also make sure to set savePlots = True if you want the PDF files to actually be generated (the default is False, which means the figures will appear in the notebook but won't be saved to disk).

3. Optionally: Run the notebook barprofiles_R_logistic-regression.ipynb to generate and save the various logistic fits. This is "optional" in that the output files already exist in this directory (they will be overwritten if the notebook is run).

4. Run the notebook barprofiles_figures_for_paper.ipynb to generate the figures (it will read the coefficients of the fits from the file generated by running the previous notebook).

Licensing

Code in this repository is released under the BSD 3-clause license.

Text and figures are licensed under a Creative Commons Attribution 4.0 International License.