Interpolate an S2FunHarmonic by given function values at given points on the sphere.
Let M spherical points vi and corresponding function values yi be given. We compute the S2FunHarmonic f of an specific bandwidth which minimizes the least squares problem
M∑i=1|f(vi)−yi|2.
Syntax
sF = S2FunHarmonic.interpolate(nodes, val)
sF = S2FunHarmonic.interpolate(nodes, val, 'bandwidth', bandwidth, 'tol', TOL, 'maxit', MAXIT, 'weights', W)
Input
nodes | vector3d (grid on sphere) |
val | function values on the grid (may be multidimensional) |
Options
bandwidth | maximum degree of the spherical harmonics used to approximate the function |
tol | tolerance for lsqr |
maxit | maximum number of iterations for lsqr |
weights | weight w_n for the node nodes (default: Voronoi weights) |