fast_chans_list[ix])) ax[0].grid(True) ax[1].semilogy(f, np.ones_like(f), ls='--') ax[1].semilogy(f, clean_psd / darm_psd) ax[1].set_ylim([0.01, 10]) ax[1].set_xlabel('Frequency [Hz]') ax[1].set_ylabel('Clean/Dirty ASD Ratio') ax[1].grid(True) plt.tight_layout() plt.savefig('ns/ns_subtraction_{}.png'.format(ix)) plt.close() cln = TimeSeries(clean, sample_rate=fs_fast, t0=st) specgram = cln.spectrogram(2, fftlength=1, overlap=.9)**(1 / 2.) plot = specgram.imshow(norm='log') ax = plot.gca() ax.set_yscale('log') ax.set_ylim(10, 100) ax.set_title('Witness: {}'.format(fast_chans_list[ix])) ax.colorbar( label=r'Gravitational-wave amplitude [strain/$\sqrt{\mathrm{Hz}}$]') plt.savefig('ns/ns_sub_spec_{}.png'.format(fast_chans_list[ix])) plt.close() dts = TimeSeries(darm_copy, sample_rate=fs_fast, t0=st) specgram = dts.spectrogram(2, fftlength=1, overlap=.9)**(1 / 2.) plot = specgram.imshow(norm='log') ax = plot.gca() ax.set_yscale('log')
data = TimeSeries.get(chan1, st, st+dur, nproc=4) if data.sample_rate.value != fs: data = data.resample(fs) wit = data.value wit = butter_filter(wit, low=low, high=high, fs=fs) wit = wit.reshape(dur*fs) clean = darm_copy - nlms(darm, wit, M=1, leak=0.0, psi=1e-6, mu=0.5) #------------------------------------------------------------------------------- # Plot if Good Results #------------------------------------------------------------------------------- clean = clean[fs*10:] darm = darm[fs*10:] ts = TimeSeries(clean, sample_rate=fs) specgram = ts.spectrogram(2, fftlength=1, overlap=.5)**(1/2.) mn, mx = np.min(specgram.value), np.max(specgram.value) plot = specgram.imshow(norm='log', vmin=mn/10, vmax=mx*10) ax = plot.gca() ax.set_yscale('log') ax.set_ylim(10, 200) ax.colorbar(label=r'Gravitational-wave amplitude [strain/$\sqrt{\mathrm{Hz}}$]') plt.savefig('wandering.png') plt.close() dts = TimeSeries(darm_copy, sample_rate=fs) specgram = dts.spectrogram(2, fftlength=1, overlap=.5)**(1/2.) plot = specgram.imshow(norm='log', vmin=mn/10, vmax=mx*10) ax = plot.gca() ax.set_yscale('log') ax.set_ylim(10, 200)