def setUp(self):
np.random.seed(0)
self.npar = 1
self.system = SamplerSystem()
self.nreplicas = 500
replicas = [Replica(x, energy) for energy, x in
[self.system.sample_configuration(10.) for i in range(self.nreplicas)]]
mc_walker = self.system
ns = NestedSampling(replicas,
mc_walker=mc_walker, nproc=1, verbose=False,
iprint=100)
run_nested_sampling(ns, label="test")
self.energies = np.array(ns.max_energies)
self.T = np.linspace(0.1, 1.0, 10)
# compute the heat capacity and internal energy from the results of the NS run
self.cvNS = compute_heat_capacity(self.energies, self.nreplicas, npar=self.npar,
ndof=self.system.ndof,
Tmin=min(self.T), Tmax=max(self.T), nT=len(self.T),
live_replicas=False)
# compute the same directly from the HSA
self.cvHSA = minima_to_cv(self.system.database.minima(), kT=self.T, k=self.system.ndof)
def _compute_cv(self):
Tlist = self._get_T_range()
lZ, U, U2, Cv = minima_to_cv(self.minima, Tlist, self._get_ndof())
self.Tlist = Tlist
self.Cv = Cv
minima = db.minima()
else:
dbfname = args.fname
db = Database(dbfname, createdb=False)
minima = [m for m in db.minima() if m.fvib is not None and m.pgorder is not None]
if len(minima) == 0:
print "There are not minima with the necessary thermodynamic information in the database. Have you computed the normal mode"\
" frequencies and point group order for all the minima? See pele.thermodynamics "\
" for more information"
exit(1)
print "computing heat capacity from", len(minima), "minima"
Tmin = args.Tmin
Tmax = args.Tmax
nT = args.Tcount
dT = (Tmax-Tmin) / nT
T = np.array([Tmin + dT*i for i in range(nT)])
Z, U, U2, Cv = minima_to_cv(minima, T, k)
with open(args.o, "w") as fout:
fout.write("#T Cv <E> <E**2>\n")
for vals in zip(T, Cv, U, U2):
fout.write("%g %g %g %g\n" % vals)
plt.plot(T, Cv, '-')
plt.xlabel("T")
plt.ylabel("Cv")
plt.savefig(args.o + ".pdf")
def _compute_cv(self):
Tlist = self._get_T_range()
lZ, U, U2, Cv = minima_to_cv(self.minima, Tlist, self._get_ndof())
self.Tlist = Tlist
self.Cv = Cv
