x = xtemp
else:
x = np.concatenate((x, xtemp), axis=1)
else:
continue
params = dict(Fs=4096.0, fpass=[5, 600], tapers=[1, 1], pad=1,
Npairs=2000, itc=1)
nPerDraw = 400
nDraws = 100
print 'Running Pairwise Spectrum Estimation'
(pS, f) = spectral.mtpspec(x, params, verbose='DEBUG')
print 'Running Raw Spectrum Estimation'
(Sraw, f) = spectral.mtspecraw(x, params, verbose=True)
print 'Running Mean Spectrum Estimation'
(S, N, f) = spectral.mtspec(x, params, verbose=True)
print 'Running CPCA PLV Estimation'
(cplv, f) = spectral.mtcpca(x, params, verbose=True)
# print 'Running CPCA Power Estimation'
# (cpow, f) = spectral.mtcspec(x, params, verbose=True)
# Saving Results
res = dict(pS=pS, cplv=cplv, Sraw=Sraw, f=f, S=S, N=N)
# res = dict(cpow = cpow, f = f)
save_name = subj + condstem + '.mat'
# plt.figure()
# plt.plot(t,ITD_nfs.T,color= mcolors.CSS4_COLORS['grey'])
# plt.plot(t,ITD_Ht,color='k')
# plt.xlim([0,Keep_H])
# plt.title('Ht ITD')
#%% Calculate Hf
params = {'Fs': fs, 'tapers': [1.5, 2], 'fpass': [0, 40]}
IAC_getHf = IAC_Ht[:int(np.round(Keep_H * fs))]
IAC_getHf = IAC_getHf.reshape([1, IAC_getHf.size])
ITD_getHF = ITD_Ht[:int(np.round(Keep_H * fs))]
ITD_getHF = ITD_getHF.reshape([1, ITD_getHF.size])
out_IAC = mtspecraw(IAC_getHf, params)
out_ITD = mtspecraw(ITD_getHF, params)
IAC_Hf = out_IAC[0]
ITD_Hf = out_ITD[0]
f1 = out_IAC[1]
#%% Compute Hf noise floors
#!!!!!!!!!!!!!!!!!!!!!!!!!! Commenting out for now - 02/02/20201
# NF_Hfs_IAC = np.zeros([Num_noiseFloors,IAC_Hf.size])
# NF_Hfs_ITD = np.zeros([Num_noiseFloors,ITD_Hf.size])
# for j in range(0,Num_noiseFloors):
# NF_getHf_IAC = IAC_nfs[j,:int(np.round(Keep_H*fs))]
# NF_getHf_IAC = NF_getHf_IAC.reshape([1,NF_getHf_IAC.size])
# NF_getHf_ITD = ITD_nfs[j,:int(np.round(Keep_H*fs))]