def freqs_lorentzian(freq, fq, network, Oorb=False, rtol=1e-8, max_iters=100, bw=0, n_lowpass=False, mode_nums=None):
"""
selects modes using the frequency data (freq, fq) and returns a list of modes
modes = [(f, (n,l,m,w,y,U)), ...]
if Oorb, we assume that freq contains (O/Oorb) data, and we convert it back to O [rad/sec] by multiplying by Oorb
"""
if not mode_nums:
mode_nums = range(len(network))
fit_params, fit_params_covar = nm_s.fit_peaks_lorentzian(freq, fq, max_iters=50, verbose=True)
modes = {}
for modeNo in mode_nums:
fit = fit_params[modeNo]
if len(fit) == 0:
raise StandardError, "No frequency peak detected for modeNo=%d" % modeNo
f,_,_ = fit[0]
if Oorb:
f = f*Oorb
if (min_w <= f) and (f <= max_w):
modes[modeNo] = f
return modes
if not len(freq):
raise ValueError, "no data loaded from ", opts.freqfilename
if opts.freq_peaks:
if opts.verbose: print "finding peak frequencies by closest point in the FFT"
x, _ = nm_s.find_freq_peaks(freq, fq, delta=0, __sort=True)
freq_maxs=[]
for A in x:
try:
freq_maxs.append( [A[0]] )
except IndexError:
freq_maxs.append( [] )
if opts.freq_peaks_fit:
if opts.verbose: print "fitting lorentizians to the peak frequencies in the FFT"
fit_params, fit_params_covar = nm_s.fit_peaks_lorentzian(freq, fq, max_iters=opts.max_freqfit_iters, delta=0, rtol=opts.freqfit_rtol, verbose=opts.freq_peaks_verbose)
####################################################################################################
#
#
# analytics
#
#
####################################################################################################
if opts.analytics:
if not opts.freq_peaks:
if opts.verbose: print "finding peak freuqencies by closest point in the FFT"
freq_maxs, freq_mins = nm_s.find_freq_peaks(freq, fq, delta=0, __sort=True)
if opts.verbose: print "computing the most unstable pairings using observed frequencies"
freqs = []
