auromat.solving.solving module

auromat.solving.solving.estimateArcSecRange(imagePath, imageSize=None)[source]
auromat.solving.solving.solveImage(imagePath, channel=None, maskingFn=<function maskStarfield at 0x865ef50>, sigma=None, solveTimeout=300, debugOutputFolder=None, noAstrometryPlots=False, arcsecRange=None, astrometryBinPath=None, useModifiedPath=False, parameters=['xy', 'xy2', 'xy4', 's'], pixelError=10, oddsToSolve=None, verbose=False)[source]

Tries different combinations to solve the image using astrometry.net.

Parameters:
  • imagePath –
  • channel – the channel to use for source extraction ‘R’,’G’,’B’, or None for combining all channels into a grayscale image
  • maskingFn – function to use for masking the given image, if None, masking is skipped
  • sigma – noise level of the image (optional)
  • solveTimeout – maximum time in seconds after which astrometry.net is killed
  • debugOutputFolder – if given, the path to which debug files are written
  • noAstrometryPlots – whether to let astrometry.net generate plots, if True, then debugOutputFolder must be given
  • arcsecRange – tuple(low,high), if not given, then it is guessed from the image file if possible
  • astrometryBinPath – path to the bin/ folder of astrometry.net; if not given, then whatever is in PATH will be used
  • useModifiedPath (bool) – invokes astrometry.net with /usr/bin/env PATH=os.environ[‘PATH’] This may be useful when the PATH was modified after launching Python.
  • pixelError (int) – size of pixel positional error, use higher values (e.g. 10) if image contains star trails (ISS images)
  • oddsToSolve – default 1e9, see astrometry.net docs
Return type:

dictionary containing FITS WCS header, or None if solving failed
auromat.solving.solving.solveImages(imagePaths, channel=None, maskingFn=<function maskStarfield at 0x865ef50>, solveTimeout=300, parallel=True, debugOutputFolder=None, noAstrometryPlots=False, pixelError=10, oddsToSolve=None, sigma=None, maxWorkers=None, astrometryBinPath=None, useModifiedPath=False, verbose=False)[source]

Solves multiple images in parallel. See solveImage() for parameter documentation.

Note: This only works because the actual solving is done in an external
process (astrometry.net), otherwise nothing would have been gained due to Pythons GIL.