astropop 0.9.3

Astronomical Polarimetry and Photometry Pipeline

The ASTROnomical POlarimetry and Photometry pipeline. Developed for work with IAGPOL and SPARC4 polarimeters at Observatório Pico dos Dias (Brazil), but suitable to be used in other image polarimeters around the world.

Features

This software is intended to provide a full pipeline to reduce raw polarimetry and photometry data taken with common CCD telescope cameras. It can do:

• Create calibrate frames;

• Calibrate images using bias/flat/dark frames;

• Gain correction and in-processing image binnig;

• Cosmic ray extraction (astroscrappy);

• Align image sets;

• Aperture and (planned) PSF photometry;

• Calcite polarimeters;

  • Automatic pairs of stars identification;

• Automatic photometry calibration using online catalogs.

Support and Community

We have a community of people using astropop to perform data reduction. Also, we use this community to offer support for astropop users. Join the community at astropop-users Google-Groups

Dependencies

Some of astropop dependencies (numpy, astropy, scipy, astroscrappy) need gcc to get build. Make sure gcc is installed properly in your system.

There is nothing that prevent astropop itself to run on Windows. However, due to problems that comes from dependencies, mainly numpy and astrometry.net, astropop is currently supported only on Linux and Mac.

Bellow we list all the necessary dependencies for the good working of the code. Note that this can be changed with the time.

• astroalign;

• astropy >= 4.3;

• astroquery;

• astroscrappy;

• numpy >= 1.17;

• scikit-image;

• scikit-learn;

• scipy;

• sep.

Installation

Astropop can be downloaded from gh/sparc4-dev/astropop. It follows the stadard python package install procedure. All requirements can be installed with pip or conda.

Anaconda Environment

We recomend to use a anaconda environment to use astropop. Having the anaconda installed, use the following command to install a new <environment name> with conda dependencies:

conda create -n <environment name> -c conda-forge python=3.10 astroalign astropy astroquery astroscrappy matplotlib numpy pyyaml reproject scikit-image scikit-learn scipy sep

Once the environment is created, you can activate the environment and install the astropop with pip.

conda activate <environment name>

Stable Version

The stable version of astropop is available in PyPi and can be installed directly with pip command.

pip install astropop

Development Version

The development (unstable) version can be installed from the github code. With pip, can be done in any of the 3 ways:

pip install -U git+https://github.com/sparc4-dev/astropop

or

pip install -U https://github.com/sparc4-dev/astropop/archive/refs/heads/main.zip

or

git clone https://github.com/sparc4-dev/astropop
cd astropop
pip install -U .

Citing

An article was published in Publications of the Astronomical Society of the Pacific, vol.131, n.996, pp.024501, which is the main reference to this work. If you do not have access to PASP, the preprint was uploaded to arXiv:1811.01408.

Also, for latex citation, you can use the following BibTex:

@article{Campagnolo_2018,
    doi = {10.1088/1538-3873/aaecc2},
        url = {https://doi.org/10.1088%2F1538-3873%2Faaecc2},
        year = 2018,
        month = {dec},
        publisher = {{IOP} Publishing},
        volume = {131},
        number = {996},
        pages = {024501},
        author = {Julio Cesar Neves Campagnolo},
        title = {{ASTROPOP}: the {ASTROnomical} {POlarimetry} and Photometry Pipeline},
        journal = {Publications of the Astronomical Society of the Pacific},
}

Documentation

Documentation (not complete yet) can be found at astropop.readthedocs.io