Class lsst::meas::astrom::ScaledPolynomialTransformFitter

class ScaledPolynomialTransformFitter

A fitter class for scaled polynomial transforms

This class allows for iteration between actual fitting, outlier rejection, and estimation of intrinsic scatter. It also provides access to the current model for debugging via an afw::table::BaseCatalog that contains the input values, output values, and the best-fit-transformed input values.

ScaledPolynomialTransformFitter has two public construction methods:

• fromMatches fits a transform that maps intermediate world coordinates to pixel coordinates, using as inputs a match of reference coordinates to measured source positions. This sets up the fitter to do outlier rejection and intrinsic scatter estimation.

• fromGrid fits an inverse to an existing transform, using the to-be-inverted transform to populate a grid of positions. Because the to-be-inverted transform is assumed to be known exactly, fitters initialized with this method have no need for outlier rejection or scatter estimation.

In either case, the fitter creates affine transforms that map the input and output data points onto [-1, 1]. It then fits a polynomial transform that, when composed with the input scaling transform and the inverse of the output scaling transform, maps the input data points to the output data points.

The fitter can be used in an outlier-rejection loop with the following pattern (with user-defined convergence criteria):

while (true) {
    fitter.fit();
    if (converged) break;
    fitter.updateModel();
    fitter.computeIntrinsicScatter();
    fitter.rejectOutliers();
}

This pattern fits a model, uses that model to transform the input points, estimates intrinsic scatter from the differences between model-transformed points and output data points, and finally rejects outliers by sigma-clipping those differences before repeating.

ScaledPolynomialTransformFitter instances should be confined to a single thread.