rbf
gma.smc.interp.rbf
[function] rbf(points, values, bounds = None, resolution = None, crs = None, kernel = "thin_plate_spline", search_radius = 12, **kwargs):Use Radial Basis Function method to interpolate points into a 2D array.
Parameters:
points: list||tuple||array.
Interpolate point X (longitude), Y (latitude) coordinates. There must be at least 4 coordinate points.
values: array.
The data value corresponding to the coordinate point, which is the same as the number of points.
**Optional:
bounds = tuple. Default None.
The four boundaries of the interpolation result are the minimum longitude (left), the minimum latitude (bottom), the maximum longitude (right), and the maximum latitude (top). The default (None) is to extract the range from the input coordinate points.
resolution = float. Default None.
The resolution of the interpolation result. The default (None) is 1/10 of the minimum bounds X and Y difference.
crs = str||int||CoordinateReferenceSystem. Default None.
Coordinate system. Can be EPSG, WKT, Proj4, and other types of coordinate characters or CoordinateReferenceSystem.
kernel = str. Default 'thin_plate_spline'.
Type of RBF. This should be one of:
'linear' : -r.
'thin_plate_spline' : r**2 * log(r).
'cubic' : r**3.
'quintic' : -r**5.
'multiquadric' : -sqrt(1 + r**2).
'inverse_multiquadric' : 1/sqrt(1 + r**2).
'inverse_quadratic' : 1/(1 + r**2).
'gaussian' : exp(-r**2).
search_radius = int. Default 12.
The value of the interpolant at each evaluation point will be computed using only this many nearest data points.
Returns:
Type: namedtuple.
Contains data (data) and affine transformation (geo_transform).
References:
[1] Fasshauer, G., 2007. Meshfree Approximation Methods with Matlab. World Scientific Publishing Co.
[2] http://amadeus.math.iit.edu/~fass/603_ch3.pdf
[3] Wahba, G., 1990. Spline Models for Observational Data. SIAM.
[4] http://pages.stat.wisc.edu/~wahba/stat860public/lect/lect8/lect8.pdf