coords = db.minima()[0].coords
#coords = db.transition_states()[0].coords
energy = pot.getEnergy(coords)
#coords = np.loadtxt("2.txt").flatten()
print "global minimum energy"
print energy
match = ExactMatchAACluster(system.aasystem)
get_pgorder = PointGroupOrderCluster(match)
coords = db.minima()[0].coords
hess = pot.NumericalHessian(coords, eps=1e-4)
metric = system.aasystem.metric_tensor(coords)
print get_pgorder(coords)
frq = normalmode_frequencies(hess, metric)
print "Frequencies"
print frq
fvib = logproduct_freq2(frq, 6)[1]
print "Log product of positive frequencies"
print fvib
beta = 1./2.479
print "log products and temperature-weighted log products for other minima in the database"
for m in db.minima():
hess = pot.NumericalHessian(m.coords, eps=1e-5)
metric = system.aasystem.metric_tensor(m.coords)
pgorder = get_pgorder(m.coords)
frq = normalmode_frequencies(hess, metric, eps=1e-3)
fvib = logproduct_freq2(frq, 6, eps=1e-3)[1]
print("Done with basinghopping, performing frequency analysis")
print()
#min1 = db.transition_states()[0]
# determine point group order of system
determine_pgorder = PointGroupOrderCluster(system.get_compare_exact())
pgorder = determine_pgorder(min1.coords)
# free energy from symmetry
Fpg = old_div(np.log(pgorder), beta)
# get the hession
e, g, hess = pot.getEnergyGradientHessian(min1.coords)
# TODO: go to reduced coordinates here
# get the eigenvalues
freqs2 = normalmode_frequencies(hess)
# analyze eigenvalues
n, lnf = logproduct_freq2(freqs2, 6)
Ffrq = (n * np.log(beta) + 0.5 * lnf / beta)
# print a short summary
E = pot.getEnergy(coords)
print("point group order:", pgorder)
print("number of zero eigenvalues:", (np.abs(freqs2) < 1e-4).sum())
print("number of negative eigenvalues:", (freqs2 < -1e-4).sum())
print("free energy at beta=%f:" % beta, E + Ffrq + Fpg)
print("contributions from")
print("potential energy", E)
print("frequencies", Ffrq)
transform = TransformAngleAxisCluster(system.aasystem)
coords = db.minima()[0].coords
#coords = db.transition_states()[0].coords
energy = pot.getEnergy(coords)
#coords = np.loadtxt("2.txt").flatten()
print energy
match = ExactMatchAACluster(system.aasystem)
get_pgorder = PointGroupOrderCluster(match)
coords = db.minima()[0].coords
hess = pot.NumericalHessian(coords, eps=1e-4)
metric = system.aasystem.metric_tensor(coords)
print get_pgorder(coords)
frq = normalmode_frequencies(hess, metric)
print frq
fvib = logproduct_freq2(frq, 6)[1]
print fvib
beta = 1. / 2.479
for m in db.minima():
hess = pot.NumericalHessian(m.coords, eps=1e-5)
metric = system.aasystem.metric_tensor(m.coords)
pgorder = get_pgorder(m.coords)
frq = normalmode_frequencies(hess, metric, eps=1e-3)
fvib = logproduct_freq2(frq, 6, eps=1e-3)[1]
print fvib, 0.5 * fvib / beta
m.pgorder = pgorder
m.fvib = fvib
print #min1 = db.transition_states()[0] # determine point group order of system determine_pgorder = PointGroupOrderCluster(system.get_compare_exact()) pgorder = determine_pgorder(min1.coords) # free energy from symmetry Fpg = np.log(pgorder)/beta # get the hession e, g, hess = pot.getEnergyGradientHessian(min1.coords) # TODO: go to reduced coordinates here # get the eigenvalues freqs2 = normalmode_frequencies(hess) # analyze eigenvalues n, lnf = logproduct_freq2(freqs2, 6) Ffrq = (n*np.log(beta) + 0.5*lnf /beta) # print a short summary E = pot.getEnergy(coords) print "point group order:", pgorder print "number of zero eigenvalues:", (np.abs(freqs2) < 1e-4).sum() print "number of negative eigenvalues:", (freqs2 < -1e-4).sum() print "free energy at beta=%f:"%beta, E + Ffrq + Fpg print "contributions from" print "potential energy", E print "frequencies", Ffrq
