Interpolation

Interpolation allows to transfer data from one set of locations to another. This includes for example:

  • interpolating the data from a polar grid to a cartesian grid or irregular points

  • interpolating point observations to a grid or a set of irregular points

  • filling missing values, e.g. filling clutters

Nearest

Nearest-neighbour interpolation in N dimensions.

Idw

Inverse distance weighting interpolation in N dimensions.

Linear

Interface to the scipy.interpolate.LinearNDInterpolator class.

OrdinaryKriging

Interpolate using Ordinary Kriging

ExternalDriftKriging

ExternalDriftKriging(src, trg, cov=‘1.0 Exp(10000.)’, nnearest=12,

RectGrid

Interpolation on a 2d grid in arbitrary dimensions.

RectBin

Bin points values to regular grid cells

QuadriArea

Map values representing quadrilateral grid cells to another quadrilateral grid.

interpolate

Convenience function to use the interpolation classes in an efficient way

interpolate_polar

Convenience function to interpolate polar data

cart_to_irregular_interp

Interpolate array values defined by cartesian coordinate array cartgrid to new coordinates defined by newgrid using nearest neighbour, linear or cubic interpolation

cart_to_irregular_spline

Map array values defined by cartesian coordinate array cartgrid to new coordinates defined by newgrid using spline interpolation.