for iSeg in range(0, len(oDataSegs)): t = oDataSegs[iSeg]['time_s'] y = outList[iSeg][iSgnl] # Number of time segments and length of overlap, units of samples #lenSeg = 2**6 - 1 lenSeg = int(1 * optSpec.freqRate * rps2hz) lenOverlap = 5 # Compute Spectrum over time tSpec_s, freqSpec_rps, P_mag = FreqTrans.SpectTime( t, y, lenSeg, lenOverlap, optSpec) # Plot the Spectrogram fig = FreqTrans.Spectogram(tSpec_s, freqSpec_rps * rps2hz, 20 * np.log10(P_mag)) fig.suptitle(oDataSegs[iSeg]['Desc'] + ': Spectrogram - ' + sigOutList[iSgnl]) #%% Nyquist Plots inPlot = sigInList # Elements of sigInList outPlot = sigOutList # Elements of sigOutList if False: for iIn, inName in enumerate(inPlot): for iOut, outName in enumerate(outPlot): fig = None for iSeg in range(0, len(oDataSegs)): fig = FreqTrans.PlotNyquist(T[iSeg][iOut, iIn], TUnc[iSeg][iOut, iIn],
x = vExcList[iSeg][iSgnlExc] y = vFbList[iSeg][iSgnlOut] # Number of time segments and length of overlap, units of samples #lenSeg = 2**6 - 1 lenSeg = int(1.0 * optSpec.freqRate * rps2hz) lenOverlap = 1 # Compute Spectrum over time tSpecY_s, freqSpecY_rps, P_Y_mag = FreqTrans.SpectTime( t, y, lenSeg, lenOverlap, optSpec) tSpecN_s, freqSpecN_rps, P_N_mag = FreqTrans.SpectTime( t, y, lenSeg, lenOverlap, optSpecN) # Plot the Spectrogram fig = FreqTrans.Spectogram(tSpecY_s, freqSpecY_rps * rps2hz, 20 * np.log10(P_Y_mag)) fig.suptitle(oDataSegs[iSeg]['Desc'] + ': Spectrogram - ' + sigFbList[iSgnlOut]) fig = FreqTrans.Spectogram(tSpecN_s, freqSpecN_rps * rps2hz, 20 * np.log10(P_N_mag)) fig.suptitle(oDataSegs[iSeg]['Desc'] + ': Spectrogram Null - ' + sigFbList[iSgnlOut]) #%% Sigma Plot fig = None for iSeg in range(0, len(oDataSegs)): Cmin = np.min(np.min(C[iSeg], axis=0), axis=0) sNomMin = np.min(sNom[iSeg], axis=0) sCritMin = np.min(sUnc[iSeg], axis=0) sNomMinErr = sNomMin - sCritMin