megmcca
commented
12 months ago ace_test.in
[ACE]
numTypes = 4
rcutfac = 6.026 6.026 6.026 5.922 6.026 6.026 6.026 5.922 6.026 6.026 6.026 5.922 5.922 5.922 5.922 5.818
lambda = 1.808 1.808 1.808 1.776 1.808 1.808 1.808 1.776 1.808 1.808 1.808 1.776 1.776 1.776 1.776 1.745
rcinner = 0.580 0.580 0.580 0.570 0.580 0.580 0.580 0.570 0.580 0.580 0.580 0.570 0.570 0.570 0.570 0.560
drcinner = 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
ranks = 1 2
lmax = 0 1
nmax = 6 2
mumax = 4
lmin = 0 1
nmaxbase = 6
type = Mo Nb Ta Ti
bzeroflag = 0
[CALCULATOR]
calculator = LAMMPSPACE
energy = 1
force = 1
stress = 0
[ESHIFT]
Mo = 4.0984
Nb = 2.521626
Ta = 3.762075
Ti = 2.912304
[SOLVER]
solver = RIDGE
#compute_testerrs = 1
#detailed_errors = 1
[RIDGE]
local_solver = 0
alpha = 1.E-4
[SCRAPER]
scraper = JSON
[MEMORY]
override = 1
[PATH]
#dataPath = /ascldap/users/megmcca/training_data/JSON_MoNbTaTi_fs3lib_csvs/sym_MoNbTaTi_bcc-bundled_ngroups6_nconfigs15489_nevery20
# FOR TESTING
dataPath = /ascldap/users/megmcca/training_data/JSON_MoNbTaTi_fs3lib_csvs/sym_MoNbTaTi_ngroups10_nconfigs1395_nevery1000
[OUTFILE]
output_style = PACE
metrics = metrics.md
potential = pot_HEA
[REFERENCE]
units = metal
# with no ZBL
#atom_style = atomic
#pair_style = zero 6.5
#pair_coeff = * *
pair_style = hybrid/overlay zero 6.5 zbl 0.580000 2.320000 zbl 0.580000 2.320000 zbl 0.580000 2.320000 zbl 0.570000 2.280000 zbl 0.580000 2.320000 zbl 0.580000 2.320000 zbl 0.570000 2.280000 zbl 0.580000 2.320000 zbl 0.570000 2.280000 zbl 0.560000 2.240000
pair_coeff1 = * * zero
pair_coeff2 = 1 1 zbl 1 42 42
pair_coeff3 = 1 2 zbl 2 42 41
pair_coeff4 = 1 3 zbl 3 42 73
pair_coeff5 = 1 4 zbl 4 42 22
pair_coeff6 = 2 2 zbl 5 41 41
pair_coeff7 = 2 3 zbl 6 41 73
pair_coeff8 = 2 4 zbl 7 41 22
pair_coeff9 = 3 3 zbl 8 73 73
pair_coeff10 = 3 4 zbl 9 73 22
pair_coeff11 = 4 4 zbl 10 22 22
[GROUPS]
group_sections = name training_size testing_size eweight fweight
group_types = str float float float float
smartweights = 0
random_sampling = 0
# Pures and concentrated elements extracted
#dft_loT_eq_ternary = 1.0 1 10
dft_loT_Nb = 0.13 0.0 1 10
dft_loT_Mo = 0.12 0.0 1 10
#dft_loT_Ta = 1.0 1 10
#dft_loT_Ti = 1.0 1 10
#aimd_eq_ternary = 1.0 1 10
#aimd_Nb = 1.0 1 10
#aimd_Mo = 1.0 1 10
#aimd_Ta = 1.0 1 10
#aimd_Ti = 1.0 1 10
# BCC-bundled
#dft_loT_eq_ternary = 1.0 1 10
#dft_loT_Ti_bcc_hcp = 1.0 1 10
#dft_loT_MoNbTa_bcc = 1.0 1 10
#aimd_eq_ternary = 1.0 1 10
#aimd_Ti_bcc_hcp = 1.0 1 10
#aimd_MoNbTa_bcc = 1.0 1 10
[EXTRAS]
dump_descriptors = 0
dump_truth = 0
dump_weights = 0
dump_dataframe = 0
multinode_testing = 1
LOCAL SOLVER FOR RIDGE: Getting very bad errors on local solver ACE compared to scikit learn for below setup: in transpose_trick_new_test_err.py
LOCAL SOLVER DEFAULT: if local_solver is commented out, it is automatically enabled. this is a problem due to the above problem... probably need to set it to 0 for now, or figure out why we have it toggled on.
ERROR CALCS: Copying traditional error calcs in the transpose_trick error stuff, SNAP is identical between standard fit and re-calculated fits, ACE is not.
Example (see input files below): SNAP, MAE all unweighted training E: trad 7.07261, new 7.07261 SNAP, MAE all unweighted training F: trad 0.161032, new 0.161032 SNAP, RMSE all unweighted training E: trad 7.07593, new 7.07593 SNAP, RMSE all unweighted training F: trad 0.232894, new 0.232895 (same pattern with bzeroflag = 0)
ACE, MAE all unweighted training E: trad 0.108551, new 0.041707 ACE, MAE all unweighted training F: trad 0.138716, new 0.055821 ACE, RMSE all unweighted training E: trad 0.134556, new 0.142111 ACE, RMSE all unweighted training F: trad 0.195827, new 0.199452