ML IERR: Difference between revisions

Revision as of 11:45, 21 November 2022

Default: ML_IERR	= 0	if ML_ISTART=2
	= 1	otherwise

Description: Calculation and output frequency of Bayesian error estimate.

This tag sets the distance of molecular-dynamics steps for which the Bayesian error estimates are calculated and written to the ML_LOGFILE. This means that every ML_IERR steps an entry corresponding to the keyword BEE and/or BEEF is written. If learning is activated (ML_ISTART=0,1 or 2) Bayesian error estimation must be "on" at every molecular-dynamics step (ML_IERR=1 is required).

Only for ML_ISTART=2 can ML_IERR be freely chosen. For ML_IERR=0 the Bayesian error is never calculated (and also no line is written out). This is the default since for ML_ISTART=2 the Bayesian error estimation takes up a significant amount of the total calculation time.

ML_IERR>0 can be also used with the fast execution mode ML_LFAST=.TRUE., but at each step where the Bayesian error estimation is carried out, the code has to switch to the slow version. So choosing a too narrow distance for ML_IERR will result in a huge slowdown of the code.

@@ Line 8: / Line 8: @@
 Only for {{TAG|ML_ISTART}}=2 can {{TAG|ML_IERR}} be freely chosen. For {{TAG|ML_IERR}}=0 the Bayesian error is never calculated (and also no line is written out). This is the default since for {{TAG|ML_ISTART}}=2 the Bayesian error estimation takes up a significant amount of the total calculation time.
-{{TAG|ML_IERR}}>0 can be also used with the fast execution mode {{TAG|ML_LFAST}}=.TRUE., but at each step where the Bayesian error estimation is carried out, the code has to switch to the slow version.
+{{TAG|ML_IERR}}>0 can be also used with the fast execution mode {{TAG|ML_LFAST}}=.TRUE., but at each step where the Bayesian error estimation is carried out, the code has to switch to the slow version. So choosing a too narrow distance for {{TAG|ML_IERR}} will result in a huge slowdown of the code.
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