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, drift_src=None, drift_trg=None) |
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. |