def meA(self, omega, gamma=0.1):
"""Evaluate Albrecht A term.
Returns
-------
Full Albrecht A matrix element. Unit: e^2 Angstrom^2 / eV
"""
self.read()
self.timer.start('AlbrechtA')
if not hasattr(self, 'fcr'):
self.fcr = FranckCondonRecursive()
omL = omega + 1j * gamma
omS_Q = omL - self.om_Q
n_p, myp, exF_pr = self.init_parallel_excitations()
exF_pr = np.where(np.abs(exF_pr) > 1e-2, exF_pr, 0)
m_Qcc = np.zeros((self.ndof, 3, 3), dtype=complex)
for p in myp:
energy = self.ex0E_p[p]
d_Q = self.unitless_displacements(exF_pr[p])
energy_Q = energy - self.om_Q * d_Q**2 / 2.
me_cc = np.outer(self.ex0m_pc[p], self.ex0m_pc[p].conj())
wm_Q = np.zeros((self.ndof), dtype=complex)
wp_Q = np.zeros((self.ndof), dtype=complex)
for m in range(self.nm):
self.timer.start('0mm1')
fco_Q = self.fcr.direct0mm1(m, d_Q)
self.timer.stop('0mm1')
self.timer.start('weight_Q')
e_Q = energy_Q + m * self.om_Q
wm_Q += fco_Q / (e_Q - omL)
wp_Q += fco_Q / (e_Q + omS_Q)
self.timer.stop('weight_Q')
self.timer.start('einsum')
m_Qcc += np.einsum('a,bc->abc', wm_Q, me_cc)
m_Qcc += np.einsum('a,bc->abc', wp_Q, me_cc.conj())
self.timer.stop('einsum')
self.comm.sum(m_Qcc)
self.timer.stop('AlbrechtA')
return m_Qcc # e^2 Angstrom^2 / eV
def test_franck_condon():
import sys
import numpy as np
from ase.vibrations.franck_condon import FranckCondonOverlap, FranckCondonRecursive
from math import factorial
def equal(x, y, tolerance=0, fail=True, msg=''):
"""Compare x and y."""
if not np.isfinite(x - y).any() or (np.abs(x - y) > tolerance).any():
msg = (msg + '%s != %s (error: |%s| > %.9g)' %
(x, y, x - y, tolerance))
if fail:
raise AssertionError(msg)
else:
sys.stderr.write('WARNING: %s\n' % msg)
# FCOverlap
fco = FranckCondonOverlap()
fcr = FranckCondonRecursive()
# check factorial
assert(fco.factorial(8) == factorial(8))
# the second test is useful according to the implementation
assert(fco.factorial(5) == factorial(5))
assert(fco.factorial.inv(5) == 1. / factorial(5))
# check T=0 and n=0 equality
S = np.array([1, 2.1, 34])
m = 5
assert(((fco.directT0(m, S) - fco.direct(0, m, S)) / fco.directT0(m, S) <
1e-15).all())
# check symmetry
S = 2
n = 3
assert(fco.direct(n, m, S) == fco.direct(m, n, S))
# ---------------------------
# specials
S = np.array([0, 1.5])
delta = np.sqrt(2 * S)
for m in [2, 7]:
equal(fco.direct0mm1(m, S)**2,
fco.direct(1, m, S) * fco.direct(m, 0, S), 1.e-17)
equal(fco.direct0mm1(m, S), fcr.ov0mm1(m, delta), 1.e-15)
equal(fcr.ov0mm1(m, delta),
fcr.ov0m(m, delta) * fcr.ov1m(m, delta), 1.e-15)
equal(fcr.ov0mm1(m, -delta), fcr.direct0mm1(m, -delta), 1.e-15)
equal(fcr.ov0mm1(m, delta), - fcr.direct0mm1(m, -delta), 1.e-15)
equal(fco.direct0mm2(m, S)**2,
fco.direct(2, m, S) * fco.direct(m, 0, S), 1.e-17)
equal(fco.direct0mm2(m, S), fcr.ov0mm2(m, delta), 1.e-15)
equal(fcr.ov0mm2(m, delta),
fcr.ov0m(m, delta) * fcr.ov2m(m, delta), 1.e-15)
equal(fco.direct0mm2(m, S), fcr.direct0mm2(m, delta), 1.e-15)
equal(fcr.direct0mm3(m, delta),
fcr.ov0m(m, delta) * fcr.ov3m(m, delta), 1.e-15)
equal(fcr.ov1mm2(m, delta),
fcr.ov1m(m, delta) * fcr.ov2m(m, delta), 1.e-15)
equal(fcr.direct1mm2(m, delta), fcr.ov1mm2(m, delta), 1.e-15)
def meAmult(self, omega, gamma=0.1):
"""Evaluate Albrecht A term.
Returns
-------
Full Albrecht A matrix element. Unit: e^2 Angstrom^2 / eV
"""
self.read()
if not hasattr(self, 'fcr'):
self.fcr = FranckCondonRecursive()
omL = omega + 1j * gamma
omS_v = omL - self.om_v
nv = len(self.om_v)
om_Q = self.om_Q[self.skip:]
nQ = len(om_Q)
# n_v:
# how many FC factors are involved
# nvib_ov:
# delta functions to switch contributions depending on order o
# ind_ov:
# Q indicees
# n_ov:
# # of vibrational excitations
n_v = self.d_vQ.sum(axis=1) # multiplicity
nvib_ov = np.empty((self.combinations, nv), dtype=int)
om_ov = np.zeros((self.combinations, nv), dtype=float)
n_ov = np.zeros((self.combinations, nv), dtype=int)
d_ovQ = np.zeros((self.combinations, nv, nQ), dtype=int)
for o in range(self.combinations):
nvib_ov[o] = np.array(n_v == (o + 1))
for v in range(nv):
try:
om_ov[o, v] = om_Q[self.ind_v[v][o]]
d_ovQ[o, v, self.ind_v[v][o]] = 1
except IndexError:
pass
# XXXX change ????
n_ov[0] = self.n_vQ.max(axis=1)
n_ov[1] = nvib_ov[1]
n_p, myp, exF_pr = self.init_parallel_excitations()
m_vcc = np.zeros((nv, 3, 3), dtype=complex)
for p in myp:
energy = self.ex0E_p[p]
d_Q = self.unitless_displacements(exF_pr[p])[self.skip:]
S_Q = d_Q**2 / 2.
energy_v = energy - self.d_vQ.dot(om_Q * S_Q)
me_cc = np.outer(self.ex0m_pc[p], self.ex0m_pc[p].conj())
fco1_mQ = np.empty((self.nm, nQ), dtype=float)
fco2_mQ = np.empty((self.nm, nQ), dtype=float)
for m in range(self.nm):
fco1_mQ[m] = self.fcr.direct0mm1(m, d_Q)
fco2_mQ[m] = self.fcr.direct0mm2(m, d_Q)
wm_v = np.zeros((nv), dtype=complex)
wp_v = np.zeros((nv), dtype=complex)
for m in range(self.nm):
fco1_v = np.where(n_ov[0] == 2, d_ovQ[0].dot(fco2_mQ[m]),
d_ovQ[0].dot(fco1_mQ[m]))
em_v = energy_v + m * om_ov[0]
# multiples of same kind
fco_v = nvib_ov[0] * fco1_v
wm_v += fco_v / (em_v - omL)
wp_v += fco_v / (em_v + omS_v)
if nvib_ov[1].any():
# multiples of mixed type
for n in range(self.nm):
fco2_v = d_ovQ[1].dot(fco1_mQ[n])
e_v = em_v + n * om_ov[1]
fco_v = nvib_ov[1] * fco1_v * fco2_v
wm_v += fco_v / (e_v - omL)
wp_v += fco_v / (e_v + omS_v)
m_vcc += np.einsum('a,bc->abc', wm_v, me_cc)
m_vcc += np.einsum('a,bc->abc', wp_v, me_cc.conj())
self.comm.sum(m_vcc)
return m_vcc # e^2 Angstrom^2 / eV
class Albrecht(ResonantRaman):
def __init__(self, *args, **kwargs):
"""
Parameters
----------
all from ResonantRaman.__init__
combinations: int
Combinations to consider for multiple excitations.
Default is 1, possible 2
skip: int
Number of first transitions to exclude. Default 0,
recommended: 5 for linear molecules, 6 for other molecules
nm: int
Number of intermediate m levels to consider, default 20
"""
self.combinations = kwargs.pop('combinations', 1)
self.skip = kwargs.pop('skip', 0)
self.nm = kwargs.pop('nm', 20)
approximation = kwargs.pop('approximation', 'Albrecht')
ResonantRaman.__init__(self, *args, **kwargs)
self.set_approximation(approximation)
def set_approximation(self, value):
approx = value.lower()
if approx in ['albrecht', 'albrecht b', 'albrecht c', 'albrecht bc']:
if not self.overlap:
raise ValueError('Overlaps are needed')
elif not approx == 'albrecht a':
raise ValueError('Please use "Albrecht" or "Albrecht A/B/C/BC"')
self._approx = value
def calculate_energies_and_modes(self):
if hasattr(self, 'im_r'):
return
ResonantRaman.calculate_energies_and_modes(self)
# single transitions and their occupation
om_Q = self.om_Q[self.skip:]
om_v = om_Q
ndof = len(om_Q)
n_vQ = np.eye(ndof, dtype=int)
l_Q = range(ndof)
ind_v = list(combinations_with_replacement(l_Q, 1))
if self.combinations > 1:
if not self.combinations == 2:
raise NotImplementedError
for c in range(2, self.combinations + 1):
ind_v += list(combinations_with_replacement(l_Q, c))
nv = len(ind_v)
n_vQ = np.zeros((nv, ndof), dtype=int)
om_v = np.zeros((nv), dtype=float)
for j, wt in enumerate(ind_v):
for i in wt:
n_vQ[j, i] += 1
om_v = n_vQ.dot(om_Q)
self.ind_v = ind_v
self.om_v = om_v
self.n_vQ = n_vQ # how many of each
self.d_vQ = np.where(n_vQ > 0, 1, 0) # do we have them ?
def get_energies(self):
self.calculate_energies_and_modes()
return self.om_v
def _collect_r(self, arr_ro, oshape, dtype):
"""Collect an array that is distributed."""
if len(self.myr) == self.ndof: # serial
return arr_ro
data_ro = np.zeros([self.ndof] + oshape, dtype)
if len(arr_ro):
data_ro[self.slize] = arr_ro
self.comm.sum(data_ro)
return data_ro
def Huang_Rhys_factors(self, forces_r):
"""Evaluate Huang-Rhys factors derived from forces."""
return 0.5 * self.unitless_displacements(forces_r)**2
def unitless_displacements(self, forces_r, mineigv=1e-12):
"""Evaluate unitless displacements from forces
Parameters
----------
forces_r: array
Forces in cartesian coordinates
mineigv: float
Minimal Eigenvalue to consider in matrix inversion to handle
numerical noise. Default 1e-12
Returns
-------
Unitless displacements in Eigenmode coordinates
"""
assert (len(forces_r.flat) == self.ndof)
if not hasattr(self, 'Dm1_q'):
self.eigv_q, self.eigw_rq = np.linalg.eigh(self.im_r[:, None] *
self.H * self.im_r)
# there might be zero or nearly zero eigenvalues
self.Dm1_q = np.divide(1,
self.eigv_q,
out=np.zeros_like(self.eigv_q),
where=np.abs(self.eigv_q) > mineigv)
X_r = self.eigw_rq @ np.diag(
self.Dm1_q) @ self.eigw_rq.T @ (forces_r.flat * self.im_r)
d_Q = np.dot(self.modes_Qq, X_r)
s = 1.e-20 / u.kg / u.C / u._hbar**2
d_Q *= np.sqrt(s * self.om_Q)
return d_Q
def omegaLS(self, omega, gamma):
omL = omega + 1j * gamma
omS_Q = omL - self.om_Q
return omL, omS_Q
def init_parallel_excitations(self):
"""Init for paralellization over excitations."""
n_p = len(self.ex0E_p)
# collect excited state forces
exF_pr = self._collect_r(self.exF_rp, [n_p], self.ex0E_p.dtype).T
# select your work load
myn = -(-n_p // self.comm.size) # ceil divide
rank = self.comm.rank
s = slice(myn * rank, myn * (rank + 1))
return n_p, range(n_p)[s], exF_pr
def meA(self, omega, gamma=0.1):
"""Evaluate Albrecht A term.
Returns
-------
Full Albrecht A matrix element. Unit: e^2 Angstrom^2 / eV
"""
self.read()
if not hasattr(self, 'fcr'):
self.fcr = FranckCondonRecursive()
omL = omega + 1j * gamma
omS_Q = omL - self.om_Q
n_p, myp, exF_pr = self.init_parallel_excitations()
exF_pr = np.where(np.abs(exF_pr) > 1e-2, exF_pr, 0)
m_Qcc = np.zeros((self.ndof, 3, 3), dtype=complex)
for p in myp:
energy = self.ex0E_p[p]
d_Q = self.unitless_displacements(exF_pr[p])
energy_Q = energy - self.om_Q * d_Q**2 / 2.
me_cc = np.outer(self.ex0m_pc[p], self.ex0m_pc[p].conj())
wm_Q = np.zeros((self.ndof), dtype=complex)
wp_Q = np.zeros((self.ndof), dtype=complex)
for m in range(self.nm):
fco_Q = self.fcr.direct0mm1(m, d_Q)
e_Q = energy_Q + m * self.om_Q
wm_Q += fco_Q / (e_Q - omL)
wp_Q += fco_Q / (e_Q + omS_Q)
m_Qcc += np.einsum('a,bc->abc', wm_Q, me_cc)
m_Qcc += np.einsum('a,bc->abc', wp_Q, me_cc.conj())
self.comm.sum(m_Qcc)
return m_Qcc # e^2 Angstrom^2 / eV
def meAmult(self, omega, gamma=0.1):
"""Evaluate Albrecht A term.
Returns
-------
Full Albrecht A matrix element. Unit: e^2 Angstrom^2 / eV
"""
self.read()
if not hasattr(self, 'fcr'):
self.fcr = FranckCondonRecursive()
omL = omega + 1j * gamma
omS_v = omL - self.om_v
nv = len(self.om_v)
om_Q = self.om_Q[self.skip:]
nQ = len(om_Q)
# n_v:
# how many FC factors are involved
# nvib_ov:
# delta functions to switch contributions depending on order o
# ind_ov:
# Q indicees
# n_ov:
# # of vibrational excitations
n_v = self.d_vQ.sum(axis=1) # multiplicity
nvib_ov = np.empty((self.combinations, nv), dtype=int)
om_ov = np.zeros((self.combinations, nv), dtype=float)
n_ov = np.zeros((self.combinations, nv), dtype=int)
d_ovQ = np.zeros((self.combinations, nv, nQ), dtype=int)
for o in range(self.combinations):
nvib_ov[o] = np.array(n_v == (o + 1))
for v in range(nv):
try:
om_ov[o, v] = om_Q[self.ind_v[v][o]]
d_ovQ[o, v, self.ind_v[v][o]] = 1
except IndexError:
pass
# XXXX change ????
n_ov[0] = self.n_vQ.max(axis=1)
n_ov[1] = nvib_ov[1]
n_p, myp, exF_pr = self.init_parallel_excitations()
m_vcc = np.zeros((nv, 3, 3), dtype=complex)
for p in myp:
energy = self.ex0E_p[p]
d_Q = self.unitless_displacements(exF_pr[p])[self.skip:]
S_Q = d_Q**2 / 2.
energy_v = energy - self.d_vQ.dot(om_Q * S_Q)
me_cc = np.outer(self.ex0m_pc[p], self.ex0m_pc[p].conj())
fco1_mQ = np.empty((self.nm, nQ), dtype=float)
fco2_mQ = np.empty((self.nm, nQ), dtype=float)
for m in range(self.nm):
fco1_mQ[m] = self.fcr.direct0mm1(m, d_Q)
fco2_mQ[m] = self.fcr.direct0mm2(m, d_Q)
wm_v = np.zeros((nv), dtype=complex)
wp_v = np.zeros((nv), dtype=complex)
for m in range(self.nm):
fco1_v = np.where(n_ov[0] == 2, d_ovQ[0].dot(fco2_mQ[m]),
d_ovQ[0].dot(fco1_mQ[m]))
em_v = energy_v + m * om_ov[0]
# multiples of same kind
fco_v = nvib_ov[0] * fco1_v
wm_v += fco_v / (em_v - omL)
wp_v += fco_v / (em_v + omS_v)
if nvib_ov[1].any():
# multiples of mixed type
for n in range(self.nm):
fco2_v = d_ovQ[1].dot(fco1_mQ[n])
e_v = em_v + n * om_ov[1]
fco_v = nvib_ov[1] * fco1_v * fco2_v
wm_v += fco_v / (e_v - omL)
wp_v += fco_v / (e_v + omS_v)
m_vcc += np.einsum('a,bc->abc', wm_v, me_cc)
m_vcc += np.einsum('a,bc->abc', wp_v, me_cc.conj())
self.comm.sum(m_vcc)
return m_vcc # e^2 Angstrom^2 / eV
def meBC(self, omega, gamma=0.1, term='BC'):
"""Evaluate Albrecht BC term.
Returns
-------
Full Albrecht BC matrix element.
Unit: e^2 Angstrom / eV / sqrt(amu)
"""
self.read()
if not hasattr(self, 'fco'):
self.fco = FranckCondonOverlap()
omL = omega + 1j * gamma
omS_Q = omL - self.om_Q
# excited state forces
n_p, myp, exF_pr = self.init_parallel_excitations()
# derivatives after normal coordinates
exdmdr_rpc = self._collect_r(self.exdmdr_rpc, [n_p, 3],
self.ex0m_pc.dtype)
dmdq_qpc = (exdmdr_rpc.T * self.im_r).T # unit e / sqrt(amu)
dmdQ_Qpc = np.dot(dmdq_qpc.T, self.modes_Qq.T).T # unit e / sqrt(amu)
me_Qcc = np.zeros((self.ndof, 3, 3), dtype=complex)
for p in myp:
energy = self.ex0E_p[p]
S_Q = self.Huang_Rhys_factors(exF_pr[p])
# relaxed excited state energy
# # n_vQ = np.where(self.n_vQ > 0, 1, 0)
# # energy_v = energy - n_vQ.dot(self.om_Q * S_Q)
energy_Q = energy - self.om_Q * S_Q
# # me_cc = np.outer(self.ex0m_pc[p], self.ex0m_pc[p].conj())
m_c = self.ex0m_pc[p] # e Angstrom
dmdQ_Qc = dmdQ_Qpc[:, p] # e / sqrt(amu)
wBLS_Q = np.zeros((self.ndof), dtype=complex)
wBSL_Q = np.zeros((self.ndof), dtype=complex)
wCLS_Q = np.zeros((self.ndof), dtype=complex)
wCSL_Q = np.zeros((self.ndof), dtype=complex)
for m in range(self.nm):
f0mmQ1_Q = (self.fco.directT0(m, S_Q) +
np.sqrt(2) * self.fco.direct0mm2(m, S_Q))
f0Qmm1_Q = self.fco.direct(1, m, S_Q)
em_Q = energy_Q + m * self.om_Q
wBLS_Q += f0mmQ1_Q / (em_Q - omL)
wBSL_Q += f0Qmm1_Q / (em_Q - omL)
wCLS_Q += f0mmQ1_Q / (em_Q + omS_Q)
wCSL_Q += f0Qmm1_Q / (em_Q + omS_Q)
# unit e^2 Angstrom / sqrt(amu)
mdmdQ_Qcc = np.einsum('a,bc->bac', m_c, dmdQ_Qc.conj())
dmdQm_Qcc = np.einsum('ab,c->abc', dmdQ_Qc, m_c.conj())
if 'B' in term:
me_Qcc += np.multiply(wBLS_Q, mdmdQ_Qcc.T).T
me_Qcc += np.multiply(wBSL_Q, dmdQm_Qcc.T).T
if 'C' in term:
me_Qcc += np.multiply(wCLS_Q, mdmdQ_Qcc.T).T
me_Qcc += np.multiply(wCSL_Q, dmdQm_Qcc.T).T
self.comm.sum(me_Qcc)
return me_Qcc # unit e^2 Angstrom / eV / sqrt(amu)
def electronic_me_Qcc(self, omega, gamma):
self.calculate_energies_and_modes()
approx = self.approximation.lower()
assert (self.combinations == 1)
Vel_Qcc = np.zeros((len(self.om_Q), 3, 3), dtype=complex)
if approx == 'albrecht a' or approx == 'albrecht':
Vel_Qcc += self.meA(omega, gamma) # e^2 Angstrom^2 / eV
# divide through pre-factor
with np.errstate(divide='ignore'):
Vel_Qcc *= np.where(self.vib01_Q > 0, 1. / self.vib01_Q,
0)[:, None, None]
# -> e^2 Angstrom / eV / sqrt(amu)
if approx == 'albrecht bc' or approx == 'albrecht':
Vel_Qcc += self.meBC(omega, gamma) # e^2 Angstrom / eV / sqrt(amu)
if approx == 'albrecht b':
Vel_Qcc += self.meBC(omega, gamma, term='B')
if approx == 'albrecht c':
Vel_Qcc = self.meBC(omega, gamma, term='C')
Vel_Qcc *= u.Hartree * u.Bohr # e^2 Angstrom^2 / eV -> Angstrom^3
return Vel_Qcc # Angstrom^2 / sqrt(amu)
def me_Qcc(self, omega, gamma):
"""Full matrix element"""
self.read()
approx = self.approximation.lower()
nv = len(self.om_v)
V_vcc = np.zeros((nv, 3, 3), dtype=complex)
if approx == 'albrecht a' or approx == 'albrecht':
if self.combinations == 1:
# e^2 Angstrom^2 / eV
V_vcc += self.meA(omega, gamma)[self.skip:]
else:
V_vcc += self.meAmult(omega, gamma)
if approx == 'albrecht bc' or approx == 'albrecht':
if self.combinations == 1:
vel_vcc = self.meBC(omega, gamma)
V_vcc += vel_vcc * self.vib01_Q[:, None, None]
else:
vel_vcc = self.meBCmult(omega, gamma)
V_vcc = 0
elif approx == 'albrecht b':
assert (self.combinations == 1)
vel_vcc = self.meBC(omega, gamma, term='B')
V_vcc = vel_vcc * self.vib01_Q[:, None, None]
if approx == 'albrecht c':
assert (self.combinations == 1)
vel_vcc = self.meBC(omega, gamma, term='C')
V_vcc = vel_vcc * self.vib01_Q[:, None, None]
return V_vcc # e^2 Angstrom^2 / eV
def summary(self,
omega=0,
gamma=0,
method='standard',
direction='central',
log=sys.stdout):
"""Print summary for given omega [eV]"""
if self.combinations > 1:
return self.extended_summary()
om_v = self.get_energies()
intensities = self.get_absolute_intensities(omega, gamma)[self.skip:]
if isinstance(log, str):
log = paropen(log, 'a')
parprint('-------------------------------------', file=log)
parprint(' excitation at ' + str(omega) + ' eV', file=log)
parprint(' gamma ' + str(gamma) + ' eV', file=log)
parprint(' approximation:', self.approximation, file=log)
parprint(' Mode Frequency Intensity', file=log)
parprint(' # meV cm^-1 [A^4/amu]', file=log)
parprint('-------------------------------------', file=log)
for n, e in enumerate(om_v):
if e.imag != 0:
c = 'i'
e = e.imag
else:
c = ' '
e = e.real
parprint('%3d %6.1f %7.1f%s %9.1f' %
(n, 1000 * e, e / u.invcm, c, intensities[n]),
file=log)
parprint('-------------------------------------', file=log)
parprint('Zero-point energy: %.3f eV' %
self.vibrations.get_zero_point_energy(),
file=log)
def extended_summary(self,
omega=0,
gamma=0,
method='standard',
direction='central',
log=sys.stdout):
"""Print summary for given omega [eV]"""
self.read(method, direction)
om_v = self.get_energies()
intens_v = self.intensity(omega, gamma)
if isinstance(log, str):
log = paropen(log, 'a')
parprint('-------------------------------------', file=log)
parprint(' excitation at ' + str(omega) + ' eV', file=log)
parprint(' gamma ' + str(gamma) + ' eV', file=log)
parprint(' approximation:', self.approximation, file=log)
parprint(' observation:', self.observation, file=log)
parprint(' Mode Frequency Intensity', file=log)
parprint(' # meV cm^-1 [e^4A^4/eV^2]', file=log)
parprint('-------------------------------------', file=log)
for v, e in enumerate(om_v):
parprint(self.ind_v[v],
'{0:6.1f} {1:7.1f} {2:9.1f}'.format(
1000 * e, e / u.invcm, 1e9 * intens_v[v]),
file=log)
parprint('-------------------------------------', file=log)
parprint('Zero-point energy: %.3f eV' %
self.vibrations.get_zero_point_energy(),
file=log)
def equal(x, y, tolerance=0, fail=True, msg=''):
"""Compare x and y."""
if not np.isfinite(x - y).any() or (np.abs(x - y) > tolerance).any():
msg = (msg + '%s != %s (error: |%s| > %.9g)' %
(x, y, x - y, tolerance))
if fail:
raise AssertionError(msg)
else:
sys.stderr.write('WARNING: %s\n' % msg)
# FCOverlap
fco = FranckCondonOverlap()
fcr = FranckCondonRecursive()
# check factorial
assert (fco.factorial(8) == factorial(8))
# the second test is useful according to the implementation
assert (fco.factorial(5) == factorial(5))
assert (fco.factorial.inv(5) == 1. / factorial(5))
# check T=0 and n=0 equality
S = np.array([1, 2.1, 34])
m = 5
assert (((fco.directT0(m, S) - fco.direct(0, m, S)) / fco.directT0(m, S) <
1e-15).all())
# check symmetry
S = 2
def test_franck_condon(testdir):
# FCOverlap
fco = FranckCondonOverlap()
fcr = FranckCondonRecursive()
# check factorial
assert (fco.factorial(8) == factorial(8))
# the second test is useful according to the implementation
assert (fco.factorial(5) == factorial(5))
assert (fco.factorial.inv(5) == 1. / factorial(5))
# check T=0 and n=0 equality
S = np.array([1, 2.1, 34])
m = 5
assert (((fco.directT0(m, S) - fco.direct(0, m, S)) / fco.directT0(m, S) <
1e-15).all())
# check symmetry
S = 2
n = 3
assert (fco.direct(n, m, S) == fco.direct(m, n, S))
# ---------------------------
# specials
S = np.array([0, 1.5])
delta = np.sqrt(2 * S)
for m in [2, 7]:
equal(
fco.direct0mm1(m, S)**2,
fco.direct(1, m, S) * fco.direct(m, 0, S), 1.e-17)
equal(fco.direct0mm1(m, S), fcr.ov0mm1(m, delta), 1.e-15)
equal(fcr.ov0mm1(m, delta),
fcr.ov0m(m, delta) * fcr.ov1m(m, delta), 1.e-15)
equal(fcr.ov0mm1(m, -delta), fcr.direct0mm1(m, -delta), 1.e-15)
equal(fcr.ov0mm1(m, delta), -fcr.direct0mm1(m, -delta), 1.e-15)
equal(
fco.direct0mm2(m, S)**2,
fco.direct(2, m, S) * fco.direct(m, 0, S), 1.e-17)
equal(fco.direct0mm2(m, S), fcr.ov0mm2(m, delta), 1.e-15)
equal(fcr.ov0mm2(m, delta),
fcr.ov0m(m, delta) * fcr.ov2m(m, delta), 1.e-15)
equal(fco.direct0mm2(m, S), fcr.direct0mm2(m, delta), 1.e-15)
equal(fcr.direct0mm3(m, delta),
fcr.ov0m(m, delta) * fcr.ov3m(m, delta), 1.e-15)
equal(fcr.ov1mm2(m, delta),
fcr.ov1m(m, delta) * fcr.ov2m(m, delta), 1.e-15)
equal(fcr.direct1mm2(m, delta), fcr.ov1mm2(m, delta), 1.e-15)