dash.math.gaspariCohn

Implements a Gaspari-Cohn 5th order polynomial

Syntax



weights = dash.math.gaspariCohn(distances, R)


weights = dash.math.gaspariCohn(distances, R, scale)


weights = dash.math.gaspariCohn(distances, R, ‘optimal’)

Description



weights = dash.math.gaspariCohn(distances, R)

Calculates covariance localization weights for a set of distances given a specified cutoff radius. Uses a length scale of 0.5.



weights = dash.math.gaspariCohn(distances, R, scale)

Specify the length scale to use for the Gaspari-Cohn polynomial.



weights = dash.math.gaspariCohn(distances, R, ‘optimal’)

Uses a length scale of sqrt(10/3), which was described as optimal by Lorenc (2003).

Input Arguments

distances

numeric array
A set of distances. The distances may be in any units, and should not contain negative values. NaN values are permitted.

R

positive numeric scalar
The cutoff radius. Must use the same units as the distances.

scale

numeric scalar | ‘optimal’
The length scale for the polynomial. Must be a value on the interval 0 < scale <= 0.5. By default, uses a length scale of 0.5, which sets the localization radius equal to R.

Output Arguments

weights

numeric array
Covariance localization weights. Will have the same size as the distances input.