forked from lijiext/lammps
completed lj parameter set and compute functions for melt example
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@ -4,25 +4,32 @@ class LAMMPSLJCutPotential(object):
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def __init__(self):
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self.pmap=dict()
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# coefficients: epsilon, sigma
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self.coeff = {'lj' : {'lj' : (1.0,1.0),
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'NULL': (0.0,1.0)},
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'NULL': {'lj' : (0.0,1.0),
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'NULL': (0.0,1.0)}}
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# set coeffs: eps, sig, 48*eps*sig**12, 24*eps*sig**6,
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# 4*eps*sig**12, 4*eps*sig**6
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self.coeff = {'lj' : {'lj' : (1.0,1.0,48.0,24.0,4.0,4.0),
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'NULL': (0.0,1.0, 0.0, 0.0,0.0,0.0)},
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'NULL': {'lj' : (0.0,1.0, 0.0, 0.0,0.0,0.0),
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'NULL': (0.0,1.0, 0.0, 0.0,0.0,0.0)}}
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def map_coeff(self,type,name):
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def map_coeff(self,name,type):
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if self.coeff.has_key(name):
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print("map type %d to name %s" % (type,name))
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self.pmap[type] = name
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else:
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print("cannot match atom type",name)
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raise Exception("cannot match atom type %s" % name)
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def compute_force(self,r,itype,jtype,factor_lj):
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return 0.0
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def compute_force(self,rsq,itype,jtype):
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r2inv = 1.0/rsq
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r6inv = r2inv*r2inv*r2inv
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lj1 = self.coeff[self.pmap[itype]][self.pmap[jtype]][2]
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lj2 = self.coeff[self.pmap[itype]][self.pmap[jtype]][3]
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return (r6inv * (lj1*r6inv - lj2))
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def compute_energy(self,r,itype,jtype,factor_lj):
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return 0.0
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def compute_energy(self,rsq,itype,jtype):
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r2inv = 1.0/rsq
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r6inv = r2inv*r2inv*r2inv
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lj3 = self.coeff[self.pmap[itype]][self.pmap[jtype]][4]
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lj4 = self.coeff[self.pmap[itype]][self.pmap[jtype]][5]
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return (r6inv * (lj3*r6inv - lj4))
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lammps_pair_style = LAMMPSLJCutPotential()
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print ("lj-melt potential file loaded")
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