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Pipeline for light-curve

Calibration

Level 1

  1. Create master files
    1. $m_d$ : Dark (darkflat)
    2. $m_d^f$ : Dark for flats
    3. $m_f$ : Flat
  2. Create dead pixels maps:
    1. Hot pixels map from $m_d$ (mask, or set them to median)
    2. Dead pixels map from $m_f$ (mask, or set them to local gaussian)
  3. Calibrate images : $s=\frac{s-m_d}{m_f-m_d^f}$

Level 2

  1. Clean $s$ with dead pixels maps (local gaussian or mask)
  2. Find sources in $s$ (coarse) (photutils or SExtractor)
  3. Plate-solve and update WCS (astroquery or SCAMP)
  4. Calibrate photometry
    1. Search stars in SDSS (once for all frames)
    2. RANSAC fit to find ZP and slope
    3. Calibrate pixel values with RANSAC (to Jy)

Level 3

  1. Clean cosmic rays (local gaussian or mask)
  2. Remove sky

PSF

  1. Co-add images (reproject or SWarp)
  2. Build PSF (photutils or PSFEx)

Light-curve

  1. For all $s$:
    1. Find sources in $s$ (fine) (photutils or SExtractor)
    2. Aperture and PSF photometry (photutils or SExtractor)
  2. Match sources in different catalogs by DBSCAN clustering
  3. Find moving sources
    1. Calculate dispersion of RA/DEC (MAD + threshold)
    2. Linear regression for RA/DEC
    3. Plot RA/DEC for moving sources
  4. Find variable and stable sources
    1. Calculate dispersion of flux/mag (MAD + threshold)
    2. Plot flux/mag
  5. Identify target: Match target RA/DEC to global catalog

Metadata

Release files for astrocal 0.1.0

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Source distribution for astrocal 0.1.0
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Table of built distributions (wheels) for astrocal 0.1.0
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astrocal-0.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 51.5 kB

Release files / astrocal-0.1.0.tar.gz

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0.1.0 This release

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