def METHOD_NAME(self, data):
    # Calculate the low, mids, and high indexes scaling based on the pixel
    # count
    intensities = np.fromiter(
        (i.max() for i in self.melbank_thirds()), float
    )
    self.update_drop_frames()
    if (
        intensities[0] - self.filtered_intensities[0]
        > self._config["lows_sensitivity"]
    ):
        self.new_drop(
            randint(0, self.pixel_count - 1),
            parse_color(self._config["lows_color"]),
        )
    if (
        intensities[1] - self.filtered_intensities[1]
        > self._config["mids_sensitivity"]
    ):
        self.new_drop(
            randint(0, self.pixel_count - 1),
            parse_color(self._config["mids_color"]),
        )
    if (
        intensities[2] - self.filtered_intensities[2]
        > self._config["high_sensitivity"]
    ):
        self.new_drop(
            randint(0, self.pixel_count - 1),
            parse_color(self._config["high_color"]),
        )
    self.filtered_intensities = self.intensity_filter.update(intensities)