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.