A surface brightness analysis tool for GALFIT output.
Project description
EllipSect
EllipSect creates surface brightness profiles and extracts other photometric data from the GALFIT output peng et al. (2002).
This code is “similar” (but not substitute) to IRAF’s ellipse routine. It creates a Surface brightness profile for the galaxy, model and , optionally, individual model components.
In addition, EllipSect computes variables such as Absolute Magnitude, luminosity, Flux, total apparent magnitude, Bulge to Total Ratio, Tidal, Chinu within a radius containing 90% of total light, Bumpiness, Signal to Noise Ratio, Akaike Information criterion, Bayesian information criterion, mean surface brightness at effective radius, percentage of total light per component, radius at 90% of light (for Sersic components only), effective radius in kpc, etc.
Installation
The code is written for python 3.
The python libraries required are:
numpy
astropy
scipy
matplotlib
mgefit
Install GALFIT if you haven’t done so.
Download the latest release, and installed it via
cd ellipsect pip install .
or
cd ellipsect python setup.py install
Also, you can install it via pip:
pip install EllipSect
Run the automated tests:
tox
Note: EllipSect needs the GALFIT output files (GALFIT.XX) to work. Although GALFIT is not stricly required, it will required it to create the model components and sigma image. Make sure you can call GALFIT from the command line. Otherwise the automated tests will fail.
For Linux or Mac, just run ellipsect in the command line:
ellipsect
and that’s it!!
HOW TO USE
easy run:
Once installed, run ellipsect in the same directory that you run GALFIT. It only requires the latest GALFIT’s output file. The easiest way to run the program is:
ellipsect galfit.01
It will display images like the ones below:
for more options:
ellipsect --help
Full manual:
To see other options for EllipSect:
Script run:
If you want to use EllipSect inside your own python script, you can call it in the following way:
from ellipsect import ArgParsing from ellipsect import SectorsGalfit #put all the argument parsing in a list: args=['galfit.01','--logx', '--phot','--noplot'] parser_args = ArgParsing(args) photapi = SectorsGalfit(parser_args) print("Akaike Criterion: ",photapi.AICrit) print("Bulge to Total: ",photapi.BulgeToTotal)
To check all the output variables besides AICrit and BulgeToTotal, check:
Questions?
Do you have any questions or suggestions? Please send an email to canorve [at] gmail [dot] com or open an issue
I’m open to new ideas that can benefit the software EllipSect and the GALFIT community
License
The code is under the license of GNU
Cite as
If you find this code useful, please cite as:
Añorve, Christopher, Ríos-López, Emmanuel, Reyes-Amador, Ulises, & López-Cruz, Omar. (2022). canorve/EllipSect: EllipSect v2.7.5 (v2.7.5). Zenodo. https://doi.org/10.5281/zenodo.6975592
References
Akaike, H. (1974). A New Look at the Statistical Model Identification. IEEE Transactions on Automatic Control, 19, 716–723.
Añorve, C. (2012, July). (PhD thesis). INAOE.
Barden, M., Häußler, B., Peng, C. Y., McIntosh, D. H., & Guo, Y. (2012). GALAPAGOS: from pixels to parameters, 422(1), 449–468. doi:10.1111/j.1365-2966.2012.20619.x
Blakeslee, J. P., Holden, B. P., Franx, M., Rosati, P., Bouwens, R. J., Demarco, R., Ford, H. C., et al. (2006). Clusters at Half Hubble Time: Galaxy Structure and Colors in RX J0152.7-1357 and MS 1054-03, 644(1), 30–53. doi:10.1086/503539
Cappellari, M. (2002). Efficient multi-Gaussian expansion of galaxies, 333(2), 400–410. doi:10.1046/j.1365-8711.2002.05412.x
de Vaucouleurs, G. (1948). d’Astrophysique, 11, 247. Recherches sur les Nebuleuses Extragalactiques.Annales
Häußler, B., Bamford, S. P., Vika, M., Rojas, A. L., Barden, M., Kelvin, L. S., Alpaslan, M., et al. (2013). MegaMorph - multiwavelength measurement of galaxy structure: complete Sérsic profile information from modern surveys, 430(1), 330–369. doi:10.1093/mnras/ sts633
Jedrzejewski, R. I. (1987). CCD surface photometry of elliptical galaxies - I. Observations, reduction and results., 226, 747–768. doi:10.1093/mnras/226.4.747
Peng, C. Y., Ho, L. C., Impey, C. D., & Rix, H.-W. (2002). Detailed Structural Decomposition of Galaxy Images, 124(1), 266–293. doi:10.1086/340952
Schwarz, G. (1978). Estimating the Dimension of a Model. Annals of Statistics, 6(2), 461– 464.
Sersic, J. L. (1968). Atlas de Galaxias Australes.
Tal, T., van Dokkum, P. G., Nelan, J., & Bezanson, R. (2009). The Frequency of Tidal Fea- tures Associated with Nearby Luminous Elliptical Galaxies From a Statistically Complete Sample, 138(5), 1417–1427. doi:10.1088/0004-6256/138/5/1417
Vikram, V., Wadadekar, Y., Kembhavi, A. K., & Vijayagovindan, G. V. (2010). PYMORPH: automated galaxy structural parameter estimation using PYTHON, 409(4), 1379–1392. doi:10.1111/j.1365-2966.2010.17426.x ___
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