Python tools for Venus Image Analysis


Keywords
venus, images, pds, data
License
MIT
Install
pip install venim==0.10.0

Documentation

Venus Imaging Analysis

Documentation Status

Python tools for Venus Image Analysis

Features

If the feature has been implemented in an importable way, it's indicated by a filled checkmark [x]

  • [x] Read FITS arrays (done via astropy.io.fits)
  • [x] FITS image stats scanner (creates CSV overview file)
  • [ ] For un-calibrated ground-based observations:
    • [ ] Standard image reduction pipeline: bias subtraction, flat field normalization, etc.
    • [ ] Other image clean-up: bad pixels, cosmic rays, detector artifacts
    • [ ] Generate estimated errors for each pixel
    • [ ] Transform detector x,y coordinates into local Lat, Lon
  • [ ] Access PDS data automatically via mission dependent interfaces
    • [x] Automatic downloads per volume orbit
    • [x] Local easy data access per data ID
    • [x] Akatsuki version implemented
    • [ ] VEX
  • [x] Annotate images and implement a point-based circle-fit
  • [ ] Take various gradients of images
  • [ ] Filter images in the spatial frequency domain
  • [ ] Sub-pixel disk registration
  • [ ] Robust stacking of co-registered images
  • [ ] Cloud tracking

Credits

The content of this package is based on summer science work by Nicolas Ardavin and Kenyon Prater, under the lead of Eliot Young and Mark Bullock. Later improvements have been implemented by the package maintainer Michael Aye.

This package was created with Cookiecutter and the forked michaelaye/cookiecutter-pypackage-conda project template.