I changed the No.101 line of the origin mtm-svd-python.py file from
to
The upper pic is the output plot of the spectrum and the confidence level. The lines of confidence intersected.
Here is part 2 of the script
# 2) Compute the LVF
print('Apply the MTM-SVD...')
# Slepian tapers
nw = 2; # bandwidth
kk = 3; # number of orthogonal windows
o2 = var.copy().values
# Reshape the 2d array to a 1d array
o2ts = o2.reshape((o2.shape[0],o2.shape[1]*o2.shape[2]), order='F')
p, n = o2ts.shape
# Compute the LFV
[freq, lfv] = mtm_svd_lfv(o2ts,nw,kk,dt)
# Compute the confidence intervals
niter = 10000 # minimum of 1000 iterations
sl = [0.99,0.95,0.9]
[conffreq, conflevel] = mtm_svd_conf(o2ts,nw,kk,dt,niter,sl)
# Display the plot to allow the user to choose the frequencies associated with peaks
plt.plot(freq, lfv, '-', c='k')
plt.plot(conffreq, conflevel[0,:], '--', c='tab:red', label=str(sl[0]))
plt.plot(conffreq, conflevel[1,:], '--', c='tab:orange', label=str(sl[1]))
plt.plot(conffreq, conflevel[2,:], '--', c='tab:blue', label=str(sl[2]))
plt.xlim([0.01,.1])
plt.legend()
plt.savefig(f'./spectrum_{model}{niter}.png')
# plt.show()
plt.clf()
I changed the No.101 line of the origin mtm-svd-python.py file from
to
The upper pic is the output plot of the spectrum and the confidence level. The lines of confidence intersected.
Here is part 2 of the script