def plot_atoms(atoms,types,basis=[],dup=0):
Ntypes=len(set(types))
N=len(atoms)
cs=["yellow","green","blue","red","purple","orange","black"]
#Periodic Atoms (duplicated)
if dup==1:
atoms,types=duplicate26(atoms,types,zip(v1,v2,v3))
#Type sorted atoms lists
tatoms=[list() for i in range(Ntypes)]
for i,j in enumerate(types):
tatoms[j-1].append(atoms[i])
fig=pl.figure()
aa = fig.add_subplot(111,projection='3d')
for i in range(Ntypes):
ax,ay,az=zip(*tatoms[i])
aa.scatter(ax,ay,az,c=cs.pop(0),marker="o")
if len(basis)>0:
v1,v2,v3=zip(*basis)
aa.plot([0,v1[0]],[0,v1[1]],[0,v1[2]],c="red")
aa.plot([0,v2[0]],[0,v2[1]],[0,v2[2]],c="blue")
aa.plot([0,v3[0]],[0,v3[1]],[0,v3[2]],c="green")
def plot_atoms(atoms, types, basis=[], dup=0):
Ntypes = len(set(types))
N = len(atoms)
cs = ["yellow", "green", "blue", "red", "purple", "orange", "black"]
#Periodic Atoms (duplicated)
if dup == 1:
atoms, types = duplicate26(atoms, types, zip(v1, v2, v3))
#Type sorted atoms lists
tatoms = [list() for i in range(Ntypes)]
for i, j in enumerate(types):
tatoms[j - 1].append(atoms[i])
fig = pl.figure()
aa = fig.add_subplot(111, projection='3d')
for i in range(Ntypes):
ax, ay, az = zip(*tatoms[i])
aa.scatter(ax, ay, az, c=cs.pop(0), marker="o")
if len(basis) > 0:
v1, v2, v3 = zip(*basis)
aa.plot([0, v1[0]], [0, v1[1]], [0, v1[2]], c="red")
aa.plot([0, v2[0]], [0, v2[1]], [0, v2[2]], c="blue")
aa.plot([0, v3[0]], [0, v3[1]], [0, v3[2]], c="green")
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 poscar2qvoronoi(atoms,basis,atypes,qvfile="QV_input"):
qvfp=open(qvfile,"w")
NRealAtoms=len(atoms)
#Ensure simulation bx is sufficiently orthorhombic
if sum(map(fabs,basis[0]))-fabs(basis[0][0]) > 1e-10 or \
sum(map(fabs,basis[1]))-fabs(basis[1][1]) > 1e-10 or \
sum(map(fabs,basis[2]))-fabs(basis[2][2]) > 1e-10:
print "Error: simulation axes are not sufficiently orthogonal. Use script poscarRectify.py and regenerate doscar"
exit(0)
types=list()
j=1
for i in atypes:
types+=[j]*i
j+=1
datoms,dtypes,dbasis=duplicate26(atoms,types,basis)
bounds=[[-i/2.0,i*3.0/2] for i in [basis[0][0],basis[1][1],basis[2][2]]]
def inBounds(point,bounds):
for a,[b,c] in zip(point,bounds):
if a>=c or a<b:
return False
return True
datoms=[atom for atom in datoms if inBounds(atom,bounds)]
Natoms=len(datoms)
qvfp.write("3\n")
qvfp.write("%d\n"%Natoms)
for atom in datoms:
qvfp.write("% 6.6f % 6.6f % 6.6f\n"%(atom[0],atom[1],atom[2]))
qvfp.flush()
qvfp.close()
return qvfile,basis,datoms,NRealAtoms
print "If duplicate==1, copies the structure (translated by lattice vecs) and then plots."
exit(0)
poscar = open(sys.argv[1],"r").readlines()
dupl=0
if len(sys.argv)==3:
dupl=int(sys.argv[2])
while True:
if len(poscar)<=1:
break
[basis,atypes,atoms,head,poscar] = poscarIO.read(poscar)
types=list()
#cs=list()
j=1
for i in atypes:
types+=[j]*i
#cs.append(colors[j-1])
j+=1
Ntypes=len(types)
if dupl==1:
atoms,types,basis = duplicate26(atoms,types,basis)
atoms,types = zip(*sorted(zip(atoms,types),key=lambda x:x[1])) #sort based on type
atypes = [i*26 for i in atypes]
plotsimulation(basis,atoms,atypes)
pl.show()
mlab.points3d(ax,
ay,
az,
types,
colormap="gist_heat",
scale_factor=0.7)
mlab.quiver3d(ax,
ay,
az,
afx,
afy,
afz,
line_width=3,
scale_factor=1)
else:
datoms, dtypes = duplicate26(zip(ax, ay, az), types,
zip(v1, v2, v3))
axd, ayd, azd = zip(*datoms)
mlab.points3d(axd,
ayd,
azd,
dtypes,
colormap="gist_heat",
scale_factor=0.7)
mlab.plot3d([0, v1[0]], [0, v1[1]], [0, v1[2]],
color=(0, 1, 0))
mlab.plot3d([v1[0], v1[0] + v2[0]], [v1[1], v1[1] + v2[1]],
[v1[2], v1[2] + v2[2]],
color=(0, 1, 0))
mlab.plot3d([v1[0], v1[0] + v3[0]], [v1[1], v1[1] + v3[1]],
[v1[2], v1[2] + v3[2]],
color=(0, 1, 0))
print count
print "Stress (in kB) XX YY ZZ XY YZ XZ:"
print stresskb
if md==True:
print "T=%g, PE=%g, TE=%g" % (T,PE,KE)
else:
print "PE=%g" % (PE)
print "="*50
print ""
if not(disabled):
mlab.clf()
if md==True:
mlab.points3d(ax,ay,az,types,colormap="gist_heat",scale_factor=0.7)
mlab.quiver3d(ax,ay,az,afx,afy,afz,line_width=3,scale_factor=1)
else:
datoms,dtypes=duplicate26(zip(ax,ay,az),types,zip(v1,v2,v3))
axd,ayd,azd=zip(*datoms)
mlab.points3d(axd,ayd,azd,dtypes,colormap="gist_heat",scale_factor=0.7)
mlab.plot3d([0,v1[0]],[0,v1[1]],[0,v1[2]],color=(0,1,0))
mlab.plot3d([v1[0],v1[0]+v2[0]],[v1[1],v1[1]+v2[1]],[v1[2],v1[2]+v2[2]],color=(0,1,0))
mlab.plot3d([v1[0],v1[0]+v3[0]],[v1[1],v1[1]+v3[1]],[v1[2],v1[2]+v3[2]],color=(0,1,0))
mlab.plot3d([v1[0]+v2[0],v1[0]+v2[0]+v3[0]],[v1[1]+v2[1],v1[1]+v2[1]+v3[1]],[v1[2]+v2[2],v1[2]+v2[2]+v3[2]],color=(0,1,0))
mlab.plot3d([0,v2[0]],[0,v2[1]],[0,v2[2]],color=(0,1,0))
mlab.plot3d([v2[0],v2[0]+v1[0]],[v2[1],v2[1]+v1[1]],[v2[2],v2[2]+v1[2]],color=(0,1,0))
mlab.plot3d([v2[0],v2[0]+v3[0]],[v2[1],v2[1]+v3[1]],[v2[2],v2[2]+v3[2]],color=(0,1,0))
mlab.plot3d([v2[0]+v3[0],v1[0]+v2[0]+v3[0]],[v2[1]+v3[1],v1[1]+v2[1]+v3[1]],[v2[2]+v3[2],v1[2]+v2[2]+v3[2]],color=(0,1,0))
mlab.plot3d([0,v3[0]],[0,v3[1]],[0,v3[2]],color=(0,1,0))
mlab.plot3d([v3[0],v3[0]+v1[0]],[v3[1],v3[1]+v1[1]],[v3[2],v3[2]+v1[2]],color=(0,1,0))
mlab.plot3d([v3[0],v3[0]+v2[0]],[v3[1],v3[1]+v2[1]],[v3[2],v3[2]+v2[2]],color=(0,1,0))
