preprocessing.py 文件源码

def compute_power_spectral_density(self, windowed_signal):

        # Windowed signal of shape [channel][sample] [16 x 12000]
        ret = []

        # Welch parameters
        sliding_window = 512
        overlap = 0.25
        n_overlap = int(sliding_window * overlap)

        # compute psd using Welch method
        freqs, power = signal.welch(windowed_signal, fs=SAMPLING_FREQUENCY,
                                    nperseg=sliding_window, noverlap=n_overlap)

        for psd_freq in PSD_FREQ:
            tmp = (freqs >= psd_freq[0]) & (freqs < psd_freq[1])
            ret.append(power[:,tmp].mean(1))

        return(np.log(np.array(ret) / np.sum(ret, axis=0)))