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Pisco Pipeline

This is a current version of PISCO data reduction pipeline, developed by Taweewat Somboonpanyakul at MIT in order to reduce PISCO raw images to calibrated images with calibrated photometry.

Installation:

Required softwares before using the pipeline:

  • Astrometry.net (including necessary index files for your field of interest)
  • Sextractor
  • SCAMP
  • SWARP
  • DS9 [required for pisco_combine.py in order to make an image, can comment out the last line in pisco_combine.py (save_rgb_image(fieldname)) to remove the requirement.]

Included packages:

Other Required Python Packages:

  • astropy
  • photutils (an affiliated package of Astropy) (required only for the Photometry pipeline)
  • numpy
  • matplotlib
  • subprocess, shlex, os, sys

Usage:

Running the Astrometry pipeline

python pisco_pipeline/pisco_combine.py /path/to/data/ Field024

where /path/to/data/ is the directory where the PISCO raw data Field024_A_82.fits and Field024_A_83.fits are located, and Field024 is the prefix for all the files that you want to combine together. Run python script outside pisco_pipeline/ directory next to data/ directory is located.

The main outputs (4 fits images based on 4 different bands) will be located in final/ directory.

Running the Photometry pipeline

python pisco_pipeline/pisco_photometry.py Field026

Need to run Astrometry pipeline first as the input for the photometry pipeline. The main output for the pipeline (csv file with corrected magnitude in different bands with their uncertainty) is located in slr_output/ directory.

Known bugs

  • if you got a warning "WARNING: Significant inaccuracy" from SWARP, it tells you that the astrometry solution that you use might be wrong. One way to fix this is to remove all 2MASS.cat file that astrometry.net created since it might be incorrect, then rerun it again.

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MIT

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