Function cumulative_integration

pytta/classes/analysis.py:1443–1494

Cumulative integration with proper corrections.

(inputSignal,
                           bypassLundeby,
                           plotLundebyResults,
                           suppressWarnings=True,
                           **kwargs)

def cumulative_integration(inputSignal,
                           bypassLundeby,
                           plotLundebyResults,
                           suppressWarnings=True,
                           **kwargs):
    """Cumulative integration with proper corrections."""

    def plot_lundeby():
        c0, c1, interIdx, BGL = lundebyParams
        fig = plt.figure(figsize=(10, 5))
        ax = fig.add_axes([0.08, 0.15, 0.75, 0.8], polar=False,
                          projection='rectilinear', xscale='linear')
        line = c1*inputSignal.timeVector + c0
        ax.plot(inputSignal.timeVector, 10*np.log10(inputSignal.timeSignal**2), label='IR')
        ax.axhline(y=10*np.log10(BGL), color='#1f77b4', label='BG Noise', c='red')
        ax.plot(inputSignal.timeVector, line, label='Late slope', c='black')
        ax.axvline(x=interIdx/inputSignal.samplingRate, label='Truncation point', c='green')
        ax.grid()
        ax.set_xlabel('Time [s]')
        ax.set_ylabel('Amplitude [dBFS]')
        plt.title('{0:.0f} [Hz]'.format(band))
        ax.legend(loc='best', shadow=True, fontsize='x-large')

    # timeSignal = inputSignal.timeSignal[:]
    # Substituted by SignalObj.crop in analyse function
    # timeSignal, sampleShift = _circular_time_shift(timeSignal)
    # del sampleShift
    # hSignal = SignalObj(timeSignal, inputSignal.lengthDomain, inputSignal.samplingRate)
    hSignal = _filter(inputSignal, **kwargs)
    bands = FOF(nthOct=kwargs['nthOct'],
                freqRange=[kwargs['minFreq'],
                           kwargs['maxFreq']])[:, 1]
    listEDC = []
    for ch in range(hSignal.numChannels):
        signal = hSignal[ch]
        band = bands[ch]
        energyDecay, energyVector, lundebyParams = \
            energy_decay_calculation(band,
                                     signal.timeSignal,
                                     signal.timeVector,
                                     signal.samplingRate,
                                     signal.numSamples,
                                     signal.numChannels,
                                     signal.timeLength,
                                     bypassLundeby,
                                     suppressWarnings=suppressWarnings)
        listEDC.append((energyDecay, energyVector))
        if plotLundebyResults:  # Placed here because Numba can't handle plots.
            # plot_lundeby(band, timeVector, timeSignal,  samplingRate,
            #             lundebyParams)
            plot_lundeby()
    return listEDC, hSignal

# @njit
def reverb_time_regression(energyDecay, energyVector, upperLim, lowerLim):