Documentation for module pao_ml_gaussprocess

Gaussian Process implementation

source: pao_ml_gaussprocess.F
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public Subroutines/Functions:

Calculate gradient of Gaussian process
Uses covariance matrix to make prediction
SUBROUTINE
pao_ml_gp_train (pao)
Builds the covariance matrix

SUBROUTINEpao_ml_gp_gradient(pao, ikind, descriptor, outer_deriv, gradient)

Calculate gradient of Gaussian process

Arguments:
POINTER
:: pao ...
INTEGER,
INTENT(in)
:: ikind ...
REAL(dp),
INTENT(in),
TARGET
:: descriptor(:) ...
REAL(dp),
INTENT(in)
:: outer_deriv(:) ...
REAL(dp),
INTENT(out)
:: gradient(:) ...

SUBROUTINEpao_ml_gp_predict(pao, ikind, descriptor, output, variance)

Uses covariance matrix to make prediction

Arguments:
POINTER
:: pao ...
INTEGER,
INTENT(in)
:: ikind ...
REAL(dp),
INTENT(in)
:: descriptor(:) ...
REAL(dp),
INTENT(out)
:: output(:) ...
REAL(dp),
INTENT(out)
:: variance ...

SUBROUTINEpao_ml_gp_train(pao)

Builds the covariance matrix

Arguments:
POINTER
:: pao ...