def calc_intraComponentFZ(Q, fe_Q, Ztot, QmaxIntegrate, maxQ, elementList, element, \
x, y, z, elementParameters, damping_factor, aff_mean_squared):
"""Function to calculate the intra-molecular components.
Parameters
----------
Q : numpy array
momentum transfer (nm^-1)
fe_Q : numpy array
effective electric form factor
Ztot : int
total Z number
QmaxIntegrate : float
maximum Q value for the intagrations
maxQ : float
maximum Q value
elementList : dictionary("element": multiplicity)
chemical elements of the sample with their multiplicity
element : string
chemical element
multiplicity : int
chemical element multiplicity
element : string array
array with the elements in the xyz_file
x, y, z : float array
atomic coordinate in the xyz_file (nm)
elementParameters : dictionary("element": parameters)
chemical elements of the sample with their parameters
element : string
chemical element
parameters : list
list of the parameters
(Z, a1, b1, a2, b2, a3, b3, a4, b4, c, M, K, L)
damping_factor : float
damp factor
Returns
-------
r : numpy array
atomic distance (nm)
Fintra_r : numpy array
intramolecular contribution of F(r)
"""
iintra_Q = calc_iintraFZ(Q, QmaxIntegrate, maxQ, elementList, element, x,
y, z, elementParameters, aff_mean_squared)
iintradamp_Q = UtilityAnalysis.calc_iintradamp(iintra_Q, Q, QmaxIntegrate,
damping_factor)
r = MainFunctions.calc_r(Q)
Fintra_r = MainFunctions.calc_Fr(r, Q[Q <= QmaxIntegrate],
iintradamp_Q[Q <= QmaxIntegrate])
return (r, iintradamp_Q, Fintra_r)
def calc_FFT_QiQ(Q, Qi_Q, QmaxIntegrate):
"""Function to calculate the FFT following the Igor Pro procedure.
I do not agree with this procedure, but I follow it to compare my results
with Igor Pro's ones.
Parameters
----------
Q : numpy array
momentum transfer (nm^-1)
Qi_Q : numpy array
Q*i(Q)
QmaxIntegrate : float
maximum Q value for the integrations
Returns
-------
r : numpy array
atomic distance (nm)
F_r : numpy array
F(r)
"""
pMax, elem = UtilityAnalysis.find_nearest(Q, QmaxIntegrate)
NumPoints = 2*2*2**math.ceil(math.log(5*(pMax+1))/math.log(2))
DelR = 2*np.pi/(np.mean(np.diff(Q))*NumPoints)
Qi_Q = Utility.resize_zero(Qi_Q[Q<=QmaxIntegrate], NumPoints)
Qi_Q[pMax+1:] = 0.0
Q = np.arange(np.amin(Q), np.amin(Q)+np.mean(np.diff(Q))*NumPoints, np.mean(np.diff(Q)))
r = MainFunctions.calc_r(Q)
F_r = fftpack.fft(Qi_Q)
F_r = F_r[np.where(r>=0.0)]
F_r = -np.imag(F_r)*np.mean(np.diff(Q))*2/np.pi
r = np.arange(0.0, 0.0+DelR*len(F_r), DelR)
return (r, F_r)