ML FFN: Difference between revisions

From VASP Wiki
m (Karsai moved page FFNCAR to ML FFNCAR)
No edit summary
 
(9 intermediate revisions by one other user not shown)
Line 1: Line 1:
{{DISPLAYTITLE:ML_FFN}}
This binary file contains a knewly created force field from machine learning runs with the options {{TAG|ML_MODE}}=<code>train</code>, <code>refit</code> or <code>select</code>. It's structure is identical to the {{TAG|ML_FF}} file. To be able to use the new force field from {{FILE|ML_FFN}} file it has to be simply copied to {{FILE|ML_FF}} and the {{FILE|INCAR}} tag {{TAG|ML_MODE}}=<code>run</code> has to be set.
Since VASP 6.4.0 the {{FILE|ML_FFN}} file starts with an ASCII header containing the most important INCAR tags in effect during generation of this force field. In Linux shells this can be easily extracted issuing the following command:
head -n 1 ML_FFN
The output may look like this:
ML_FF 0.2.1 binary { "date" : "2023-03-16T13:49:44.829", "ML_LFAST" : False, "ML_DESC_TYPE" :  0, "types" : [ "Si" ], "training_structures" : 984, "local_reference_cfgs" : [ 110 ], "descriptors" : [ 142 ], "ML_IALGO_LINREG" : 3, "ML_RCUT1" :  6.0000E+00, "ML_RCUT2" :  6.0000E+00, "ML_W1" :  1.0000E-01, "ML_SION1" :  5.0000E-01, "ML_SION2" :  5.0000E-01, "ML_LMAX2" : 4, "ML_MRB1" : 8, "ML_MRB2" : 8, "ML_IWEIGHT" : 3, "ML_WTOTEN" :  1.0000E+00, "ML_WTIFOR" :  1.0000E+00, "ML_WTSIF" :  1.0000E-10 }
followed by some extra spaces (because the header is always 4096 characters long). The timestamp following <code>"date"</code> is also written to the <code>FFOUT</code> lines in {{FILE|ML_LOGFILE}}. The <code>"ML_LFAST"</code> item allows you to check whether this force field is ready for fast prediction mode.
----
----


[[Category:Files]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category:Output Files]][[Category:VASP6]]
[[Category:Files]][[Category:Machine-learned force fields]][[Category:Output Files]]

Latest revision as of 13:38, 5 May 2023

This binary file contains a knewly created force field from machine learning runs with the options ML_MODE=train, refit or select. It's structure is identical to the ML_FF file. To be able to use the new force field from ML_FFN file it has to be simply copied to ML_FF and the INCAR tag ML_MODE=run has to be set.

Since VASP 6.4.0 the ML_FFN file starts with an ASCII header containing the most important INCAR tags in effect during generation of this force field. In Linux shells this can be easily extracted issuing the following command:

head -n 1 ML_FFN

The output may look like this:

ML_FF 0.2.1 binary { "date" : "2023-03-16T13:49:44.829", "ML_LFAST" : False, "ML_DESC_TYPE" :   0, "types" : [ "Si" ], "training_structures" : 984, "local_reference_cfgs" : [ 110 ], "descriptors" : [ 142 ], "ML_IALGO_LINREG" : 3, "ML_RCUT1" :  6.0000E+00, "ML_RCUT2" :  6.0000E+00, "ML_W1" :  1.0000E-01, "ML_SION1" :  5.0000E-01, "ML_SION2" :  5.0000E-01, "ML_LMAX2" : 4, "ML_MRB1" : 8, "ML_MRB2" : 8, "ML_IWEIGHT" : 3, "ML_WTOTEN" :  1.0000E+00, "ML_WTIFOR" :  1.0000E+00, "ML_WTSIF" :  1.0000E-10 }

followed by some extra spaces (because the header is always 4096 characters long). The timestamp following "date" is also written to the FFOUT lines in ML_LOGFILE. The "ML_LFAST" item allows you to check whether this force field is ready for fast prediction mode.