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 setup(self):
self.eps = 0.01
dinp = deepcopy(self.inp)
dinp.set_inputname("tmp2.com")
s = dinp.get_method_save().replace("<force>\n","")
s = s.replace("<cpmcscf>\n","").replace("force\n","")
dinp.set_method_save(s)
dinp.set_caspt2_istate(self.now_state, self.nrange)
self.dinp = dinp
if str(self.dinp) == "InputMOLPRO":
root, ext = os.path.splitext(self.dinp.get_inputname())
self.doutp = OutputMOLPRO(root + ".out",self.mol)
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)
class Potential_TSH_CASPT2(Potential_TSH):
def __init__(self, mol, inp, now_state, nrange):
Potential_TSH.__init__(self, mol, inp, now_state, nrange)
#super(Potential_TSH_CASPT2, self).__init__(mol, inp, now_state, nrange)
self.setup()
def set_now_state(self,now_state):
self.now_state = now_state
self.inp.set_caspt2_istate(self.now_state,self.nrange)
def setup(self):
self.eps = 0.01
dinp = deepcopy(self.inp)
dinp.set_inputname("tmp2.com")
s = dinp.get_method_save().replace("<force>\n","")
s = s.replace("<cpmcscf>\n","").replace("force\n","")
dinp.set_method_save(s)
dinp.set_caspt2_istate(self.now_state, self.nrange)
self.dinp = dinp
if str(self.dinp) == "InputMOLPRO":
root, ext = os.path.splitext(self.dinp.get_inputname())
self.doutp = OutputMOLPRO(root + ".out",self.mol)
def get_potential_energy_multi(self):
self.ene, self.co, self.s = self.outp.get_data_caspt2_multi(self.nrange)
return self.ene
def get_inner_v_d(self):
# the sign of nacv must be checked befor it is used
# refert to eq.13
pos_save,vel_save = self.mol.get_positions(), self.mol.get_velocities()
len_vel = sqrt(np.sum(vel_save)**2)
self.mol.set_positions(pos_save + self.eps * vel_save / len_vel)
self.dinp.set_molecule(self.mol)
self.dinp.make_input()
self.dinp.write()
os.system(self.dinp.get_command())
self.mol.set_positions(pos_save)
ene2, co2, s2 = self.doutp.get_data_caspt2_multi(self.nrange)
dco = (co2 - self.co) / self.eps
# refert to eq.9
v_d1 = np.einsum("ip, jq, pq -> ij",self.co,dco,self.s)
v_d2 = np.einsum("ip,pqlm,jq -> ijlm",self.co,self.d_multi,self.co)
return len_vel * v_d1 + np.einsum("pq,ijpq -> ij",vel_save,v_d2)
def get_velocity_adjustment_vecotr(self):
return self.mol.get_forces()
def __init__(self, mol, inp):
self.mol = mol
self.inp = inp
if str(self.inp) == "InputMOLPRO":
root, ext = os.path.splitext(self.inp.get_inputname())
self.outp = OutputMOLPRO(root + ".out",self.mol)
def override_output(self, wfile,mol=None):
if mol is None: mol = self.mol
self.outp = OutputMOLPRO(wfile,self.mol)
