lsst.meas.astrom gfb315b4925+aee6f2001b
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Classes | Functions
lsst.meas.astrom.pessimistic_pattern_matcher_b_3D Namespace Reference

Classes

class  PessimisticPatternMatcherB
 

Functions

 _rotation_matrix_chi_sq (flattened_rot_matrix, pattern_a, pattern_b, max_dist_rad)
 

Function Documentation

◆ _rotation_matrix_chi_sq()

lsst.meas.astrom.pessimistic_pattern_matcher_b_3D._rotation_matrix_chi_sq (   flattened_rot_matrix,
  pattern_a,
  pattern_b,
  max_dist_rad 
)
protected
Compute the squared differences for least squares fitting.

Given a flattened rotation matrix, one N point pattern and another N point
pattern to transform into to, compute the squared differences between the
points in the two patterns after the rotation.

Parameters
----------
flattened_rot_matrix : `numpy.ndarray`, (9, )
    A flattened array representing a 3x3 rotation matrix. The array is
    flattened to comply with the API of scipy.optimize.least_squares.
    Flattened elements are [[0, 0], [0, 1], [0, 2], [1, 0]...]
pattern_a : `numpy.ndarray`, (N, 3)
    A array containing N, 3 vectors representing the objects we would like
    to transform into the frame of pattern_b.
pattern_b : `numpy.ndarray`, (N, 3)
    A array containing N, 3 vectors representing the reference frame we
    would like to transform pattern_a into.
max_dist_rad : `float`
    The maximum distance allowed from the pattern matching. This value is
    used as the standard error for the resultant chi values.

Returns
-------
noralized_diff : `numpy.ndarray`, (9,)
    Array of differences between the vectors representing of the source
    pattern rotated into the reference frame and the converse. This is
    used to minimize in a least squares fitter.

Definition at line 34 of file pessimistic_pattern_matcher_b_3D.py.