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	IpolBase(src, trg)
Nearest	Nearest(src, trg)
Idw	Idw(src, trg, nnearest=4, p=2.)
Linear	Interface to the scipy.interpolate.LinearNDInterpolator class.
OrdinaryKriging	OrdinaryKriging(src, trg, cov='1.0 Exp(10000.)', nnearest=12)
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.
griddata	Interpolate array values defined by cartesian coordinate array cartgrid to new coordinates defined by newgrid using nearest neighbour, linear or cubic interpolation
map_coordinates	Map array values defined by cartesian coordinate array cartgrid to new coordinates defined by newgrid using spline interpolation.
interpolate	Convenience function to use the interpolation classes in an efficient way.
interpolate_polar	Convenience function to interpolate polar data
get_mapping	Create xarray.Dataset with KDTree indices and distances derived from src and trg.
IpolMethods	wradlib xarray SubAccessor methods for Ipol Methods.