lammps/examples/snap/compute_snap_dgrad.py

"""
compute_snap_dgrad.py
Purpose: Demonstrate extraction of descriptor gradient (dB/dR) array from compute snap.
         Show that dBi/dRj components summed over neighbors i yields same output as regular compute snap with dgradflag = 0.
         This shows that the dBi/dRj components extracted with dgradflag = 1 are correct.
Serial syntax:
    python compute_snap_dgrad.py
Parallel syntax:
    mpirun -np 4 python compute_snap_dgrad.py
"""

from __future__ import print_function
import sys
import ctypes
import numpy as np
from lammps import lammps, LMP_TYPE_ARRAY, LMP_STYLE_GLOBAL

# get MPI settings from LAMMPS

lmp = lammps()
me = lmp.extract_setting("world_rank")
nprocs = lmp.extract_setting("world_size")

cmds = ["-screen", "none", "-log", "none"]
lmp = lammps(cmdargs = cmds)

def run_lammps(dgradflag):

    # simulation settings

    lmp.command("clear")
    lmp.command("units metal")
    lmp.command("boundary	p p p")
    lmp.command("atom_modify	map hash")
    lmp.command(f"lattice         bcc {latparam}")
    lmp.command(f"region		box block 0 {nx} 0 {ny} 0 {nz}")
    lmp.command(f"create_box	{ntypes} box")
    lmp.command(f"create_atoms	{ntypes} box")
    lmp.command("mass 		* 180.88")
    lmp.command("displace_atoms 	all random 0.01 0.01 0.01 123456")

    # potential settings

    snap_options = f'{rcutfac} {rfac0} {twojmax} {radelem1} {radelem2} {wj1} {wj2} rmin0 {rmin0} quadraticflag {quadratic} bzeroflag {bzero} switchflag {switch} bikflag {bikflag} dgradflag {dgradflag}'
    lmp.command(f"pair_style 	zero {rcutfac}")
    lmp.command(f"pair_coeff 	* *")
    lmp.command(f"pair_style 	zbl {zblcutinner} {zblcutouter}")
    lmp.command(f"pair_coeff 	* * {zblz} {zblz}")

    # define compute snap

    lmp.command(f"compute 	snap all snap {snap_options}")

    # run

    lmp.command(f"thermo 		100")
    lmp.command(f"run {nsteps}")

# declare simulation/structure variables

nsteps = 0
nrep = 2
latparam = 2.0
ntypes = 2
nx = nrep
ny = nrep
nz = nrep

# declare compute snap variables

twojmax = 8
rcutfac = 1.0
rfac0 = 0.99363
rmin0 = 0
radelem1 = 2.3
radelem2 = 2.0
wj1 = 1.0
wj2 = 0.96
quadratic = 0
bzero = 0
switch = 0
bikflag = 1

# define reference potential

zblcutinner = 4.0
zblcutouter = 4.8
zblz = 73

# number of descriptors

if (twojmax % 2 == 0):
    m  =  twojmax / 2 + 1
    nd = int(m*(m+1)*(2*m+1)/6)
else:
    m  =  (twojmax + 1) / 2
    nd = int(m*(m+1)*(m+2)/3)

if me == 0:
    print(f"Number of descriptors based on twojmax : {nd}")

# run lammps with dgradflag on

if me == 0:
    print("Running with dgradflag on")

dgradflag = 1
run_lammps(dgradflag)

# get global snap array

lmp_snap = lmp.numpy.extract_compute("snap", LMP_STYLE_GLOBAL, LMP_TYPE_ARRAY)

# print snap array to observe
#if (me==0):
#    np.savetxt("test_snap.dat", lmp_snap, fmt="%d %d %d %f %f %f %f %f")

# take out rows with zero column

# extract dBj/dRi (includes dBi/dRi)

natoms = lmp.get_natoms()
fref1 = lmp_snap[0:natoms,0:3].flatten()
eref1 = lmp_snap[-1,0]
dbdr_length = np.shape(lmp_snap)[0]-(natoms) - 1
dBdR = lmp_snap[natoms:(natoms+dbdr_length),3:(nd+3)]
force_indices = lmp_snap[natoms:(natoms+dbdr_length),0:3].astype(np.int32)

# strip rows with all zero descriptor gradients to demonstrate how to save memory

nonzero_rows = lmp_snap[natoms:(natoms+dbdr_length),3:(nd+3)] != 0.0
nonzero_rows = np.any(nonzero_rows, axis=1)
dBdR = dBdR[nonzero_rows, :]
force_indices = force_indices[nonzero_rows,:]
dbdr_length = np.shape(dBdR)[0]

# sum over atoms i that j is a neighbor of, like dgradflag = 0 does.

array1 = np.zeros((3*natoms,nd))
for k in range(0,nd):
    for l in range(0,dbdr_length):
        i = force_indices[l,0]
        j = force_indices[l,1]
        a = force_indices[l,2]
        #print(f"{i} {j} {a}")
        array1[3 * j + a, k] += dBdR[l,k]

# run lammps with dgradflag off

if me == 0:
    print("Running with dgradflag off")

dgradflag = 0
run_lammps(dgradflag)

# get global snap array

lmp_snap = lmp.numpy.extract_compute("snap", LMP_STYLE_GLOBAL, LMP_TYPE_ARRAY)
natoms = lmp.get_natoms()
fref2 = lmp_snap[natoms:(natoms+3*natoms),-1]
eref2 = lmp_snap[0,-1]
array2 = lmp_snap[natoms:natoms+(3*natoms), nd:-1]

# take difference of arrays obtained from dgradflag on and off.

diffm = array1 - array2
difff = fref1 - fref2
diffe = eref1 - eref2

if me == 0:
    print(f"Max/min difference in dSum(Bi)/dRj: {np.max(diffm)} {np.min(diffm)}")
    print(f"Max/min difference in reference forces: {np.max(difff)} {np.min(difff)}")
    print(f"Difference in reference energy: {diffe}")