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

IpolBase	The base class for interpolation in N dimensions.
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.