def plot_pos_rad_ang(atoms, types, basis, dup=0):
Ntypes = len(set(types))
N = len(atoms)
cs = ["yellow", "green", "blue", "red", "purple", "orange", "black"]
#Periodic Atoms (duplicated, needed for distributions)
datoms, dtypes = duplicate26(atoms, types, basis)
#Neighbors needed for angular distribution
dneighbs = neighbors(datoms, 5.0, style="full")
#Radial Distribution
[rbins, rdist] = rdf(datoms, inloop=N, cutoff=12.0)
#Correlation of Angles
[abins, adist] = adf(datoms, dneighbs, inloop=N)
#Type sorted atoms lists
tatoms = [list() for i in range(Ntypes)]
if (dup == 1):
for i, j in enumerate(dtypes):
tatoms[j].append(datoms[i])
else:
for i, j in enumerate(types):
tatoms[j].append(atoms[i])
v1, v2, v3 = zip(*basis)
#findsymmetry([v1,v2,v3],types,zip(xs,ys,zs))
fig = pl.figure(figsize=(12, 6))
aa = fig.add_subplot(311, projection='3d')
aa.set_position([0, 0, 0.5, 1.0])
for i in range(Ntypes):
ax, ay, az = zip(*tatoms[i])
aa.scatter(ax, ay, az, c=cs.pop(0), marker="o")
aa.plot([0, v1[0]], [0, v1[1]], [0, v1[2]])
aa.plot([0, v2[0]], [0, v2[1]], [0, v2[2]])
aa.plot([0, v3[0]], [0, v3[1]], [0, v3[2]])
bb = fig.add_subplot(312)
bb.set_position([0.56, 0.55, 0.4, 0.4])
bb.plot(rbins, rdist)
pl.xlabel("Radius (A)")
pl.ylabel("Count")
cc = fig.add_subplot(313)
cc.set_position([0.56, 0.08, 0.4, 0.36])
cc.plot(abins, adist)
pl.xlabel("Angle (deg)")
pl.ylabel("Count")
pl.show()
def plot_pos_rad_ang(atoms,types,basis,dup=0):
Ntypes=len(set(types))
N=len(atoms)
cs=["yellow","green","blue","red","purple","orange","black"]
#Periodic Atoms (duplicated, needed for distributions)
datoms,dtypes=duplicate26(atoms,types,basis)
#Neighbors needed for angular distribution
dneighbs=neighbors(datoms,5.0,style="full")
#Radial Distribution
[rbins,rdist]=rdf(datoms,inloop=N,cutoff=12.0)
#Correlation of Angles
[abins,adist]=adf(datoms,dneighbs,inloop=N)
#Type sorted atoms lists
tatoms=[list() for i in range(Ntypes)]
if(dup==1):
for i,j in enumerate(dtypes):
tatoms[j].append(datoms[i])
else:
for i,j in enumerate(types):
tatoms[j].append(atoms[i])
v1,v2,v3=zip(*basis)
#findsymmetry([v1,v2,v3],types,zip(xs,ys,zs))
fig=pl.figure(figsize=(12,6))
aa = fig.add_subplot(311,projection='3d')
aa.set_position([0,0,0.5,1.0])
for i in range(Ntypes):
ax,ay,az=zip(*tatoms[i])
aa.scatter(ax,ay,az,c=cs.pop(0),marker="o")
aa.plot([0,v1[0]],[0,v1[1]],[0,v1[2]])
aa.plot([0,v2[0]],[0,v2[1]],[0,v2[2]])
aa.plot([0,v3[0]],[0,v3[1]],[0,v3[2]])
bb = fig.add_subplot(312)
bb.set_position([0.56,0.55,0.4,0.4])
bb.plot(rbins,rdist)
pl.xlabel("Radius (A)")
pl.ylabel("Count")
cc = fig.add_subplot(313)
cc.set_position([0.56,0.08,0.4,0.36])
cc.plot(abins,adist)
pl.xlabel("Angle (deg)")
pl.ylabel("Count")
pl.show()
def make_rdf(system, rdfOutputFile, ion=False, bulk=False, force=False):
if not path.exists(system):
print("no system exists:", system)
return []
if path.exists(system + "/" + rdfOutputFile + ".dat"):
print("coord exists:", system, rdfOutputFile)
if force:
print("overwriting")
else:
return []
topology = system + "/md_nvt_prod_start_drudes.pdb"
trajectory = system + "/md_nvt_prod.dcd"
output_log = system + "/output.log"
diff_sys = DiffusionSystem(system)
ion_atom = {"BF4": "B", "TMA": "N", "TMEA": "N"}[diff_sys.diffusingIon]
if ion:
solvent_resname = {
"BF4": ("TME or resname TMA", "N"),
"TMA": ("BF4", "B"),
"TMEA": ("BF4", "B")
}[diff_sys.diffusingIon]
if diff_sys.ion_pair == "bmim":
solvent_resname = ("BMI", "N1")
else:
solvent_resname = {
"dce": ("dch", "CT CT1"),
"acn": ("acn", "CT"),
"h2o": ("HOH", "O"),
}[diff_sys.solvent]
ion_atomselection = "((resname %s) and name %s)" % (
diff_sys.diffusingIon[:3], ion_atom)
solvent_atomselection = "((resname %s) and name %s)" % (
solvent_resname[0][:3], solvent_resname[1])
smooth_coords = rdf(topology,
trajectory,
output_log,
ion_atomselection,
solvent_atomselection,
bulk=bulk)
with open(system + "/" + rdfOutputFile + ".dat", "w") as f:
for i in smooth_coords:
f.write(str(i) + "\n")
return smooth_coords
def do_rdf_RDF(self):
from rdf import rdf
validatorBase.defaultNamespaces.append(purl1_namespace)
return rdf()
def do_rdf_RDF(self): from rdf import rdf self.dispatcher.defaultNamespaces.append(purl1_namespace) return rdf()
def do_rdf_RDF(self): from rdf import rdf self.dispatcher.defaultNamespaces.append(purl1_namespace) return rdf()
def do_rdf_RDF(self): from rdf import rdf validatorBase.defaultNamespaces.append(purl1_namespace) return rdf()
print "="*80
print "Generation %d, EA#%d"%(gencnt,eanum)
a=fitness.pop(0).strip()
print "Fitness= %s eV PerAtom Energy= %s eV\nkpoints= %sVolume= %sEnthalpy= %s"%(a,round(float(a)/N,3),kpoints.pop(0),volumes.pop(0),enthalpy.pop(0).strip())
if gencnt >= start:
#plot_pos_rad_ang(atoms,types,pdup=pdup)
#Periodic Atoms (duplicated)
datoms,dtypes,dbasis=duplicate26(atoms,types,basis)
#Neighbors needed for angular distribution
dneighbs=neighbors(datoms,5.0,style="full")
#Radial Distribution
[rbins,rdist]=rdf(datoms,inloop=N,cutoff=12.0)
#Correlation of Angles
[abins,adist]=adf(datoms,dneighbs,inloop=N)
#Type sorted atoms lists
tatoms=[list() for i in range(Ntypes)]
if(pdup==1):
for i,j in enumerate(dtypes):
tatoms[j].append(datoms[i])
else:
for i,j in enumerate(types):
tatoms[j].append(atoms[i])
fig=pl.figure(figsize=(12,6))
aa = fig.add_subplot(311,projection='3d')
a = fitness.pop(0).strip()
print "Fitness= %s eV PerAtom Energy= %s eV\nkpoints= %sVolume= %sEnthalpy= %s" % (
a, round(float(a) / N,
3), kpoints.pop(0), volumes.pop(0), enthalpy.pop(0).strip())
if gencnt >= start:
#plot_pos_rad_ang(atoms,types,pdup=pdup)
#Periodic Atoms (duplicated)
datoms, dtypes, dbasis = duplicate26(atoms, types, basis)
#Neighbors needed for angular distribution
dneighbs = neighbors(datoms, 5.0, style="full")
#Radial Distribution
[rbins, rdist] = rdf(datoms, inloop=N, cutoff=12.0)
#Correlation of Angles
[abins, adist] = adf(datoms, dneighbs, inloop=N)
#Type sorted atoms lists
tatoms = [list() for i in range(Ntypes)]
if (pdup == 1):
for i, j in enumerate(dtypes):
tatoms[j].append(datoms[i])
else:
for i, j in enumerate(types):
tatoms[j].append(atoms[i])
fig = pl.figure(figsize=(12, 6))
aa = fig.add_subplot(311, projection='3d')
