StarIDOptions

giant.stellar_opnav.star_identification:

class giant.stellar_opnav.star_identification.StarIDOptions(catalog=<factory>, max_magnitude=7, min_magnitude=-10, max_combos=100, tolerance=20, ransac_tolerance=5, second_closest_check=True, unique_check=True, use_mp=False, compute_weights=False)[source]
Parameters:

  • catalog (Catalog) – The catalog object to use to query for potential stars in an image.

  • max_magnitude (float) – the maximum magnitude to return when querying the star catalog

  • min_magnitude (float) – the minimum magnitude to return when querying the star catalog

  • max_combos (int) – The maximum number of random samples to try in the RANSAC routine

  • tolerance (float) – The maximum distance between a catalog star and a image point of interest for a potential pair to be formed before the RANSAC algorithm

  • ransac_tolerance (float) – The maximum distance between a catalog star and an image point of interest after correcting the attitude for a pair to be considered an inlier in the RANSAC algorithm.

  • second_closest_check (bool) – A flag specifying whether to reject pairs where 2 catalog stars are close to an image point of interest

  • unique_check (bool) – A flag specifying whether to allow a single catalog star to be potentially paired with multiple image points of interest

  • use_mp (bool) – A flag specifying whether to use the multi-processing library to accelerate the RANSAC algorithm

  • compute_weights (bool)

catalog: Catalog

The star catalog to use when pairing image points with star locations.

This typically should be a subclass of the Catalog class. It defaults to the Gaia.

max_magnitude: float = 7

The maximum star magnitude to query from the star catalog.

This specifies how dim stars are expected to be in the extracted_image_points data set. This is typically dependent on both the detector and the exposure length of the image under consideration.

min_magnitude: float = -10

The minimum star magnitude to query from the star catalog.

This specifies how dim stars are expected to be in the extracted_image_points data set. This is typically dependent on both the detector and the exposure length of the image under consideration.

Generally this should be left alone unless you are worried about over exposed stars (in which case ImageProcessing.reject_saturation may be more useful) or you are doing some special analysis.

max_combos: int = 100

The maximum number of random combinations to try in the RANSAC algorithm.

If the total possible number of combinations is less than this attribute then an exhaustive search will be performed instead

tolerance: float = 20

The maximum distance in units of pixels between a projected catalog location and an extracted image point for a possible pairing to be made for consideration in the RANSAC algorithm.

ransac_tolerance: float = 5

The tolerance that is required after correcting for attitude errors for a pair to be considered an inlier in the RANSAC algorithm in units of pixels.

This should always be less than the tolerance attribute.

second_closest_check: bool = True

A boolean specifying whether to ignore extracted image points where multiple catalog points are within the specified tolerance.

unique_check: bool = True

A boolean specifying whether to ignore possible catalog to image point pairs where multiple image points are within the specified tolerance of a single catalog point.

use_mp: bool = False

A boolean flag specifying whether to use multi-processing to speed up the RANSAC process.

If this is set to True then all available CPU cores will be utilized to parallelize the RANSAC algorithm computations. For small combinations, the overhead associated with this can swamp any benefit that may be realized.

compute_weights: bool = False
A boolean specifying whether to compute the formal uncertainties for the unit vectors

and the pixel locations of the catalog stars.