Class lsst::afw::math::GaussianProcess

template<typename T>
class GaussianProcess

Stores values of a function sampled on an image and allows you to interpolate the function to unsampled points

The data will be stored in a KD Tree for easy nearest neighbor searching when interpolating.

The array _function[] will contain the values of the function being interpolated. You can provide a two dimensional array _function[][] if you wish to interpolate a vector of functions. In this case _function[i][j] is the jth function associated with the ith data point. Note: presently, the covariance matrices do not relate elements of _function[i][] to each other, so the variances returned will be identical for all functions evaluated at the same point in parameter space.

_data[i][j] will be the jth component of the ith data point.

_max and _min contain the maximum and minimum values of each dimension in parameter space (if applicable) so that data points can be normalized by _max-_min to keep distances between points reasonable. This is an option specified by calling the relevant constructor.