def spectral_dens_from_corrfce(self):
#params = world.params
params = {"ftype": world.ctype,
"reorg": world.reorg,
"cortime": world.ctime,
"T": world.temp,
"matsubara":world.mats}
ta = world.ta
with energy_units(world.e_units):
cf = CorrelationFunction(ta,params)
world.sd = cf.get_SpectralDensity()
vals = numpy.zeros(2000, dtype=numpy.complex)
l = 1
while k > 0:
vals[l] = cF.data[k] * numpy.exp(-wa.data[k] / (kB_int * temperature))
l += 1
k -= 1
tf = DFunction(wa, vals)
tf.plot(ylabel=r'$\tilde{C}(\omega)$ [rad$\cdot$fs$^{-1}$]',
axis=[-0.1, 0.1, -0.005,
numpy.max(numpy.real(cF.data)) * 1.1],
real_only=False)
# Get spectral density
sd = cf.get_SpectralDensity()
with energy_units("1/cm"):
sd1 = SpectralDensity(ta, params)
cf1 = CorrelationFunction(ta, params)
cf1n = sd1.get_CorrelationFunction()
sd1n = cf1.get_SpectralDensity()
cf1.plot(real_only=False, show=False)
cf1n.plot()
lamb_cfm = cf1.measure_reorganization_energy()
lamb_def = cf1.get_reorganization_energy()
lamb_sdm = sd1.measure_reorganization_energy()
print(lamb_cfm, lamb_def, lamb_sdm)
print(numpy.allclose(lamb_cfm, lamb_def, rtol=1.0e-3))
l = 1
while k > 0:
vals[l] = cF.data[k]*numpy.exp(-wa.data[k]/(kB_int*temperature))
l += 1
k -= 1
tf = DFunction(wa,vals)
if _show_plots_:
tf.plot(ylabel=r'$\tilde{C}(\omega)$ [rad$\cdot$fs$^{-1}$]',
axis=[-0.1,0.1,-0.005,numpy.max(numpy.real(cF.data))*1.1],
real_only=False)
# Get spectral density
sd = cf.get_SpectralDensity()
with energy_units("1/cm"):
sd1 = SpectralDensity(ta,params)
cf1 = CorrelationFunction(ta, params)
cf1n = sd1.get_CorrelationFunction()
sd1n = cf1.get_SpectralDensity()
if _show_plots_:
cf1.plot(real_only=False,show=False)
cf1n.plot()
lamb_cfm = cf1.measure_reorganization_energy()
lamb_def = cf1.get_reorganization_energy()
lamb_sdm = sd1.measure_reorganization_energy()
print(lamb_cfm, lamb_def, lamb_sdm)