Metadata-Version: 2.1 Name: EllipSect Version: 3.4.4 Summary: A surface brightness analysis tool for GALFIT output. Home-page: https://github.com/canorve/EllipSect Author: Christopher Añorve Author-email: canorve@gmail.com License: GNU General Public License v3 (GPLv3) Project-URL: Documentation, https://github.com/canorve/EllipSect/blob/master/README.rst Project-URL: Source, https://github.com/canorve/EllipSect Platform: Linux Platform: Mac Classifier: Programming Language :: Python Classifier: Development Status :: 5 - Production/Stable Classifier: Framework :: Pytest Classifier: Intended Audience :: Science/Research Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3) Classifier: Natural Language :: Spanish Classifier: Natural Language :: English Classifier: Topic :: Scientific/Engineering :: Astronomy Description-Content-Type: text/x-rst; charset=UTF-8 License-File: LICENSE.txt Requires-Dist: importlib-metadata; python_version < "3.8" Requires-Dist: importlib-metadata Requires-Dist: sphinx>=3.2.1 Requires-Dist: numpy>=1.20.3 Requires-Dist: astropy>=5.1 Requires-Dist: scipy>=1.5.2 Requires-Dist: matplotlib>=3.5.2 Requires-Dist: mgefit>=5.0.13 Provides-Extra: testing Requires-Dist: setuptools; extra == "testing" Requires-Dist: pytest; extra == "testing" Requires-Dist: pytest-cov; extra == "testing" .. contents:: :depth: 3 .. ============= .. image:: https://img.shields.io/pypi/v/EllipSect.svg :alt: PyPI-Server :target: https://pypi.org/project/EllipSect/ .. image:: https://img.shields.io/badge/-PyScaffold-005CA0?logo=pyscaffold :alt: Project generated with PyScaffold :target: https://pyscaffold.org/ .. image:: https://zenodo.org/badge/282223217.svg :target: https://zenodo.org/badge/latestdoi/282223217 **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: |A85a| |A85b| for more options: :: ellipsect --help **Full manual:** ^^^^^^^^^^^^^^^^ To see other options for EllipSect: `How to use `__ **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: `Output variables `__ -------------- **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, C., Reyes-Amador, U., Ríos-López, E., & López-Cruz, O. (2024). canorve/EllipSect: v3.4.3 (v3.4.3). Zenodo. https://doi.org/10.5281/zenodo.13994369 -------------- **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 \__\_ **Other Stuff** --------------- Check my other project GALFITtools `here `__ -------------- .. |A85a| image:: img/A85.cub.png .. |A85b| image:: img/A85.def.png