ML_LOGFILE version 0.1.0
 
 
* MEMORY INFORMATION ***********************************************************************************************************************
 
Estimated memory consumption for ML force field generation (MB):
 
Persistent allocations for force field        :   2368.2
|
|-- CMAT for basis                            :     34.4
|-- FMAT for basis                            :   2253.3
|-- DESC for basis                            :     25.2
|-- DESC product matrix                       :      3.5
 
Persistent allocations for ab initio data     :     26.2
|
|-- Ab initio data                            :     25.2
|-- Ab initio data (new)                      :      1.1
 
Temporary allocations for sparsification      :    376.3
|
|-- SVD matrices                              :    376.1
 
Other temporary allocations                   :     41.4
|
|-- Descriptors                               :      9.7
|-- Regression                                :     20.6
|-- Prediction                                :     11.1
 
Total memory consumption                      :   2812.2
 
********************************************************************************************************************************************
 
 
* MACHINE LEARNING SETTINGS ****************************************************************************************************************
 
This section lists the available machine-learning related settings with a short description, their
selected values and the INCAR tags. The column between the value and the INCAR tag may contain a
"state indicator" highlighting the origin of the value. Here is a list of possible indicators:
 
 *     : (empty) Tag was not provided in the INCAR file, a default value was chosen automatically.
 * (I) : Value was provided in the INCAR file.
 * (i) : Value was provided in the INCAR file, deprecated tag.
 * (!) : A value found in the INCAR file was overwritten by the contents of the ML_FF or ML_AB file.
 * (?) : The value for this tag was never set (please report this to the VASP developers).
 
Tag values with associated units are given here in Angstrom/eV, if not specified otherwise.
 
Please refer to the VASP online manual for a detailed description of available INCAR tags.
 
 
General settings
--------------------------------------------------------------------------------------------------------------------------------------------
Machine learning operation mode                                                                       :             0 (I) ML_ISTART               
 
 
Descriptor settings
--------------------------------------------------------------------------------------------------------------------------------------------
Radial descriptors:
-------------------
Cutoff radius of radial descriptors                                                                   :   5.00000E+00     ML_RCUT1                
Gaussian width for broadening the atomic distribution for radial descriptors                          :   5.00000E-01     ML_SION1                
Number of radial basis functions for atomic distribution for radial descriptors                       :             8     ML_MRB1                 
 
Angular descriptors:
--------------------
Cutoff radius of angular descriptors                                                                  :   5.00000E+00     ML_RCUT2                
Gaussian width for broadening the atomic distribution for angular descriptors                         :   5.00000E-01     ML_SION2                
Number of radial basis functions for atomic distribution for angular descriptors                      :             8     ML_MRB2                 
Maximum angular momentum quantum number of spherical harmonics used to expand atomic distributions    :             4     ML_LMAX2                
Angular filtering enabled                                                                             :             T     ML_LAFILT2              
Angular filtering parameter a_FILT                                                                    :   2.00000E-03     ML_AFILT2               
Angular filtering function type                                                                       :             2     ML_IAFILT2              
Enable sparsification of angular descriptors                                                          :             F     ML_LSPARSDES            
Number of highest eigenvalues relevant in the sparsification algorithm of the angular descriptors     :             5     ML_NRANK_SPARSDES       
Desired ratio of selected to all descriptors resulting from the angular descriptor sparsification     :   5.00000E-01     ML_RDES_SPARSDES        
 
 
Kernel settings
--------------------------------------------------------------------------------------------------------------------------------------------
Weight of radial descriptors in the kernel (the angular counterpart is chosen so that the sum is 1.0) :   1.00000E-01     ML_W1                   
Power of the polynomial kernel                                                                        :             4     ML_NHYP                 
 
 
Bayesian error estimation
--------------------------------------------------------------------------------------------------------------------------------------------
Enable automatic updating of the Bayesian error estimation threshold during on-the-fly training       :             1     ML_ICRITERIA            
Decides whether update of threshold is done in the same MD step or the next MD step                   :             1     ML_IUPDATE_CRITERIA     
Read Bayesian error estimation threshold from ML_AB file                                              :             T     ML_LCTIFOR_USE_FROM_FILE
Bayesian error estimation threshold (initial or static value depending on other settings)             :   2.00000E-03     ML_CTIFOR               
Scaling factor for ML_CTIFOR. The interval 0