def wigner_distribution(fname_output,nsample, make_file=True):
# read the hessian from output file
outp = OutputMOLPRO(fname_output)
mol = outp.get_mol_info()
hess_mw, q_eq = outp.get_hessian_and_eqcoord()
q_eq = np.ravel(q_eq)
# diagonalization
eig, trs_mw = linalg.eigh(hess_mw)
eig = eig/amu2me
hess_mw = hess_mw/amu2me
eig = np.sqrt(eig[6:])
print np.sum(eig*au2cm) # print the frequency in cm-1
# sampling mass-weighted normal-mode coordinates and momenta
q_rand = np.sqrt(0.5/eig)[:,np.newaxis]*np.random.randn(len(eig),nsample)
p_rand = np.sqrt(0.5*eig)[:,np.newaxis]*np.random.randn(len(eig),nsample)
# translate to mass-weighted Cartesian coordinates and momenta
trs_mw = trs_mw[:,6:]
q_mw = np.dot(trs_mw,q_rand)
p_mw = np.dot(trs_mw,p_rand)
# translate to mass-weighted Cartesian coordinates and momenta
#mass_3row = np.ravel(np.ones((len(mol),3))*mol.get_atomic_masses()[:,np.newaxis])
mass_3row = np.ravel(np.ones((len(mol),3))*mol.get_masses()[:,np.newaxis])
q = q_mw/np.sqrt(mass_3row)[:,np.newaxis] + q_eq[:,np.newaxis]
p = p_mw*np.sqrt(mass_3row)[:,np.newaxis]
v = p/mass_3row[:,np.newaxis]
#if as_instance:
# return q.T.reshape(nsample, len(mol),3),\
# v.T.reshape(nsample, len(mol),3)
# print coordinates and velocities
if make_file:
for i in xrange(nsample):
fq_name = "coord" + str(i+1)
fv_name = "velocity" + str(i+1)
fq = open(fq_name,"w")
fv = open(fv_name,"w")
for j in xrange(len(mol)):
fq.write("{0: 10.8f} {1: 10.8f} {2: 10.8f}\n".format(*q.T[i].reshape(len(mol),3)[j]))
fv.write("{0: 10.8f} {1: 10.8f} {2: 10.8f}\n".format(*v.T[i].reshape(len(mol),3)[j]))
fq.close()
fv.close()
# obtain the kintic and potential energy
ene_kin = 0.5*np.sum(p_mw*p_mw,axis=0)
ene_pot = 0.5*np.sum(q_mw*np.dot(hess_mw,q_mw),axis=0)
ene_tot = ene_kin + ene_pot
print 0.5*np.sum(eig)
print np.average(ene_kin)
print np.average(ene_pot)
print np.average(ene_tot)
def set_zero_energy_velocities(fname_output,nsample, make_file=True):
# This method is modified such that the kinetic energy is
# set to zero point energy and the structure is the eq coordinate
# read the hessian from output file
outp = OutputMOLPRO(fname_output)
mol = outp.get_mol_info()
hess_mw, q_eq = outp.get_hessian_and_eqcoord()
q_eq = np.ravel(q_eq)
# diagonalization
eig, trs_mw = linalg.eigh(hess_mw)
eig = eig/amu2me
hess_mw = hess_mw/amu2me
eig = np.sqrt(eig[6:])
print np.sum(eig*au2cm) # print the frequency in cm-1
# sampling mass-weighted normal-mode coordinates and momenta
#p_rand = np.sqrt(1.0*eig)[:,np.newaxis]*np.random.randn(len(eig),nsample)
p_rand = np.sqrt(1.0*eig)[:,np.newaxis]*np.ones((len(eig),nsample))
# translate to mass-weighted Cartesian coordinates and momenta
trs_mw = trs_mw[:,6:]
p_mw = np.dot(trs_mw,p_rand)
# translate to mass-weighted Cartesian coordinates and momenta
#mass_3row = np.ravel(np.ones((len(mol),3))*mol.get_atomic_masses()[:,np.newaxis])
mass_3row = np.ravel(np.ones((len(mol),3))*mol.get_masses()[:,np.newaxis])
p = p_mw*np.sqrt(mass_3row)[:,np.newaxis]
v = p/mass_3row[:,np.newaxis]
#if as_instance:
# return q.T.reshape(nsample, len(mol),3),\
# v.T.reshape(nsample, len(mol),3)
# print coordinates and velocities
if make_file:
for i in xrange(nsample):
fv_name = "velocity" + str(i+1)
fv = open(fv_name,"w")
for j in xrange(len(mol)):
fv.write("{0: 10.8f} {1: 10.8f} {2: 10.8f}\n".format(*v.T[i].reshape(len(mol),3)[j]))
fv.close()
# obtain the kintic and potential energy
ene_kin = 0.5*np.sum(p_mw*p_mw,axis=0)
print ene_kin
print 0.5*np.sum(eig)
print np.average(ene_kin)
