Coder Social home page Coder Social logo

piexpiex / cfc Goto Github PK

View Code? Open in Web Editor NEW
0.0 1.0 0.0 813 KB

CAFOS Photometry Calibrator is a pipeline designed for an automatic calibration of astronomical images of the CAFOS instrument of the 2.2m telescope of the Calar Alto observatory.

License: GNU General Public License v3.0

Python 97.38% Shell 2.62%
astronomical-images calibration photometry

cfc's Introduction

CFC (Calibrador Fotométrico de CAFOS)

Bash and Python subroutines that perform automatic photometric calibration of images from CAFOS instrument of the 2.2m telescope at the Calar Alto Observatory (CAHA).

Requirements

-SExtractor (Source-Extractor) 2.25.0 version or later.

-PSFEx (PSF Extractor) 3.17.1 version or later.

-Astroquery.

-Astropy.

Operation mode

Description of how use the program in two different modes, one adapted to the output of filabres and the other for self-calibrated images (currently works only with images of SDSS filters).

Filabres output

it is recommended to use filabres for a correct reduction and calibration of the images.

The program works by depositing the CFC.sh file, the CFC_configuration folder and a csv file with the columns: caha_id, filter_name, program and reduction_file (for example "filabres_tree.csv") and using the following command in the UNIX terminal:

sh CFC.sh filabres_tree.csv

Images with own reduction and astrometric calibration

The program works by depositing the CFC.sh file, the CFC_configuration folder and a folder with the images to calibrate (for example "files") and using the following command in the UNIX terminal:

sh CFC.sh files

The images have to be reduced and calibrated astrometrically.

Image processing

-Estimation of the image dimensions and application of a mask (if the image has been trimed in a peculiar way, it is recommended to use the mask.py program to create a custom mask.) and identification of the filter used (at the moment it only works for SDSS filters).

-Use of SExtractor and PSFEx for the identification of the objects in the image and the estimation of their parameters.

-Application of different selection criteria to identify real objects and discard artifacts.

-Selection of the objects with the highest photometric quality and calibration by a comparison with the SDSS DR12 or APASS DR9 catalogs.

-Elaboration of a catalog associated with each image with the objects calibrated in magnitudes and different quality parameters.

Merge catalogs

To merge the obtained catalogs, you can use the command:

sh CFC.sh merge

This produces a catalog with lines of all catalogs obtained previously in a new folder called catalogs_folder/merge_catalogs.

Results

-Catalogues of objects calibrated in magnitude associated with each image of CAFOS.

-Images of source selection curves and magnitude calibration.

-Elaboration of a summary table (data_table.csv) of the photometric parameters of each image and if it has been calibrated correctly.

see the official documentation at: https://readthedocs.org/projects/cafos-photometry-calibrator

see the official repository at: https://github.com/piexpiex/CFC

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.