Expand a set of irregularly sampled data points into spherical harmonics using a weighted least squares inversion.

Usage

cilm, chi2 = SHExpandLSQ (d, w, lat, lon, lmax, [norm, csphase])

Returns

cilm : float, dimension (2, lmax+1, lmax+1)
The real spherical harmonic coefficients of the function. The coefficients C0lm and C1lm refer to the cosine (Clm) and sine (Slm) coefficients, respectively, with Clm=cilm[0,l,m] and Slm=cilm[1,l,m].
chi2 : float
The residual sum of squares misfit for an overdetermined inversion.

Parameters

d : float, dimension (nmax)
The value of the function at the coordinates (lat, lon).
w : float, dimension (nmax)
The weights used in the weighted least squares inversion.
lat : float, dimension (nmax)
The latitude in DEGREES corresponding to the value in d.
lon : float, dimension (nmax)
The longitude in DEGREES corresponding to the value in d.
lmax : integer
The maximum spherical harmonic degree of the output coefficients cilm.
norm : optional, integer, default = 1
1 (default) = Geodesy 4-pi normalized harmonics; 2 = Schmidt semi-normalized harmonics; 3 = unnormalized harmonics; 4 = orthonormal harmonics.
csphase : optional, integer, default = 1
1 (default) = do not apply the Condon-Shortley phase factor to the associated Legendre functions; -1 = append the Condon-Shortley phase factor of (-1)^m to the associated Legendre functions.

Description

SHExpandLSQ will expand a set of irregularly sampled data points into spherical harmonics by a least squares inversion. When there are more data points than spherical harmonic coefficients (i.e., nmax>(lmax+1)**2), the solution of the overdetermined system will be determined. If there are more coefficients than data points, then the solution of the underdetermined system that minimizes the solution norm will be determined. See the LAPACK documentation concerning DGELS for further information.

A weighted least squares inversion will be performed if the optional vector weights is specified. In this case, the problem must be overdetermined, and it is assumed that each measurement is statistically independent (i.e., the weighting matrix is diagonal). The inversion is performed using the LAPACK routine DGGGLM.

The employed spherical harmonic normalization and Condon-Shortley phase convention can be set by the optional arguments norm and csphase; if not set, the default is to use geodesy 4-pi normalized harmonics that exclude the Condon-Shortley phase of (-1)^m.

See also

makegriddh, shexpanddh, makegriddhc, shexpanddhc, makegridglq, shexpandglq, makegridglqc, shexpandglqc, dgels(1), dggglm(1)

Tags: python
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