Apply moving wave integration (mwi) with a ricker (Mexican hat)
        wavelet onto the filtered signal, and save the square of the
        integrated signal.

        The width of the hat is equal to the qrs width

        After integration, find all local peaks in the mwi signal.

def _mwi(self):
        """
        Apply moving wave integration (mwi) with a ricker (Mexican hat)
        wavelet onto the filtered signal, and save the square of the
        integrated signal.

        The width of the hat is equal to the qrs width

        After integration, find all local peaks in the mwi signal.
        """
        wavelet_filter = signal.ricker(self.qrs_width, 4)

        self.sig_i = signal.filtfilt(wavelet_filter, [1], self.sig_f,
                                     axis=0) ** 2

        # Save the mwi gain (x2 due to double filtering) and the total
        # gain from raw to mwi
        self.mwi_gain = get_filter_gain(wavelet_filter, [1],
                         np.mean([self.fc_low, self.fc_high]), self.fs) * 2
        self.transform_gain = self.filter_gain * self.mwi_gain
        self.peak_inds_i = find_local_peaks(self.sig_i, radius=self.qrs_radius)
        self.n_peaks_i = len(self.peak_inds_i)