compact_radial_basis

  • Interpolates data using compactly supported radial basis functions of minimal degree and sparse matrix algebra

Calling Sequence

import spatial_interpolators as spi
ZI = spi.compact_radial_basis(xs, ys, zs, XI, YI, dimension, order, method='wendland')

Source code

spatial_interpolators.compact_radial_basis(xs, ys, zs, XI, YI, dimension, order, smooth=0.0, radius=None, method='wendland')[source]

Interpolates a sparse grid using compactly supported radial basis functions of minimal degree and sparse matrix algebra

Parameters
xs: float

scaled input x-coordinates

ys: float

scaled input y-coordinates

zs: float

input data

XI: float

scaled output x-coordinates for data grid

YI: float

scaled output y-coordinates for data grid

dimension: int

spatial dimension of Wendland function (d)

order: int

smoothness order of Wendland function (k)

smooth: float, default 0.0

smoothing weights

radius: float or NoneType, default None

scaling factor for the basis function

method: str, default `wendland`

compactly supported radial basis function

  • 'wendland'

Returns
ZI: float

interpolated data grid

References

Buhmann2003

M. Buhmann, “Radial Basis Functions”, Cambridge Monographs on Applied and Computational Mathematics, (2003).

Wendland1995

H. Wendland, “Piecewise polynomial, positive definite and compactly supported radial functions of minimal degree,” Advances in Computational Mathematics, 4, 389–396, (1995). doi: 10.1007/BF02123482

Wendland2005

H. Wendland, “Scattered Data Approximation”, Cambridge Monographs on Applied and Computational Mathematics, (2005).