gen_averaging_kernel

  • Generates averaging kernel coefficients which minimize the total error

Calling Sequence

from gravity_toolkit.gen_averaging_kernel import gen_averaging_kernel
Wlms = gen_averaging_kernel(gclm,gslm,eclm,eslm,sigma,hw,UNITS=0,LOVE=(hl,kl,ll))

Source code

gravity_toolkit.gen_averaging_kernel(gclm, gslm, eclm, eslm, sigma, hw, LMAX=60, MMAX=None, CUTOFF=1e-15, UNITS=0, LOVE=None)[source]

Generates averaging kernel coefficients which minimize the total error following Swenson and Wahr [63]

Uses a normalized form of the Gaussian averaging function from [33]

Parameters:
gclm: np.ndarray

cosine spherical harmonics of exact averaging kernel

gslm: np.ndarray

sine spherical harmonics of exact averaging kernel

eclm: np.ndarray

measurement error in the cosine harmonics

eslm: np.ndarray

measurement error in the sine harmonics

sigma: float

variance of the surface mass signal

hw: float

Gaussian radius of the kernel in kilometers

LMAX: int, default 60

Upper bound of Spherical Harmonic Degrees

MMAX: int or NoneType, default None

Upper bound of Spherical Harmonic Orders

CUTOFF: float, default 1e-15

minimum value for tail of Gaussian averaging function

UNITS: int, default 0

Input data units

  • 0: fully-normalized

  • 1: mass coefficients (cm w.e., g/cm2)

LOVE: tuple or NoneType, default None

Load Love numbers up to degree LMAX (hl, kl, ll)

Returns:
clm: np.ndarray

cosine coefficients of the averaging kernel

slm: np.ndarray

sine coefficients of the averaging kernel