forked from lijiext/lammps
108 lines
3.1 KiB
Python
108 lines
3.1 KiB
Python
from __future__ import print_function
|
|
from lammps import lammps
|
|
import numpy as np
|
|
|
|
class LAMMPSFix(object):
|
|
def __init__(self, ptr, group_name="all"):
|
|
self.lmp = lammps(ptr=ptr)
|
|
self.group_name = group_name
|
|
|
|
class LAMMPSFixMove(LAMMPSFix):
|
|
def __init__(self, ptr, group_name="all"):
|
|
super(LAMMPSFixMove, self).__init__(ptr, group_name)
|
|
|
|
def init(self):
|
|
pass
|
|
|
|
def initial_integrate(self, vflag):
|
|
pass
|
|
|
|
def final_integrate(self):
|
|
pass
|
|
|
|
def initial_integrate_respa(self, vflag, ilevel, iloop):
|
|
pass
|
|
|
|
def final_integrate_respa(self, ilevel, iloop):
|
|
pass
|
|
|
|
def reset_dt(self):
|
|
pass
|
|
|
|
|
|
class NVE(LAMMPSFixMove):
|
|
""" Python implementation of fix/nve """
|
|
def __init__(self, ptr, group_name="all"):
|
|
super(NVE, self).__init__(ptr)
|
|
assert(self.group_name == "all")
|
|
|
|
def init(self):
|
|
dt = self.lmp.extract_global("dt")
|
|
ftm2v = self.lmp.extract_global("ftm2v")
|
|
self.ntypes = self.lmp.extract_global("ntypes")
|
|
self.dtv = dt
|
|
self.dtf = 0.5 * dt * ftm2v
|
|
|
|
def initial_integrate(self, vflag):
|
|
mass = self.lmp.numpy.extract_atom("mass")
|
|
atype = self.lmp.numpy.extract_atom("type")
|
|
x = self.lmp.numpy.extract_atom("x")
|
|
v = self.lmp.numpy.extract_atom("v")
|
|
f = self.lmp.numpy.extract_atom("f")
|
|
|
|
for i in range(x.shape[0]):
|
|
dtfm = self.dtf / mass[int(atype[i])]
|
|
v[i,:]+= dtfm * f[i,:]
|
|
x[i,:] += self.dtv * v[i,:]
|
|
|
|
def final_integrate(self):
|
|
mass = self.lmp.numpy.extract_atom("mass")
|
|
atype = self.lmp.numpy.extract_atom("type")
|
|
v = self.lmp.numpy.extract_atom("v")
|
|
f = self.lmp.numpy.extract_atom("f")
|
|
|
|
for i in range(v.shape[0]):
|
|
dtfm = self.dtf / mass[int(atype[i])]
|
|
v[i,:] += dtfm * f[i,:]
|
|
|
|
|
|
class NVE_Opt(LAMMPSFixMove):
|
|
""" Performance-optimized Python implementation of fix/nve """
|
|
def __init__(self, ptr, group_name="all"):
|
|
super(NVE_Opt, self).__init__(ptr)
|
|
assert(self.group_name == "all")
|
|
|
|
def init(self):
|
|
dt = self.lmp.extract_global("dt")
|
|
ftm2v = self.lmp.extract_global("ftm2v")
|
|
self.ntypes = self.lmp.extract_global("ntypes")
|
|
self.dtv = dt
|
|
self.dtf = 0.5 * dt * ftm2v
|
|
|
|
def initial_integrate(self, vflag):
|
|
mass = self.lmp.numpy.extract_atom("mass")
|
|
atype = self.lmp.numpy.extract_atom("type")
|
|
x = self.lmp.numpy.extract_atom("x")
|
|
v = self.lmp.numpy.extract_atom("v")
|
|
f = self.lmp.numpy.extract_atom("f")
|
|
dtf = self.dtf
|
|
dtv = self.dtv
|
|
|
|
dtfm = dtf / np.take(mass, atype)
|
|
|
|
for d in range(x.shape[1]):
|
|
v[:,d] += dtfm * f[:,d]
|
|
x[:,d] += dtv * v[:,d]
|
|
|
|
def final_integrate(self):
|
|
mass = self.lmp.numpy.extract_atom("mass")
|
|
atype = self.lmp.numpy.extract_atom("type")
|
|
v = self.lmp.numpy.extract_atom("v")
|
|
f = self.lmp.numpy.extract_atom("f")
|
|
dtf = self.dtf
|
|
|
|
dtfm = dtf / np.take(mass, atype)
|
|
|
|
for d in range(v.shape[1]):
|
|
v[:,d] += dtfm * f[:,d]
|