def METHOD_NAME(self):
    """Create image data for visualiation
    Using caiman code here
    -- easier way to compute this?
    """
    mn = self.onAc.M - self.onAc.N
    image = self.frame.copy()
    try:
        components = (self.onAc.estimates.Ab[:, mn:]
                      .dot(self.onAc.estimates.C_on[mn : self.onAc.M, (self.frame_number - 1)])
                      .reshape(self.onAc.estimates.dims, order="F"))
        ssub_B = self.onAc.params.get("init", "ssub_B") * self.onAc.params.get("init", "ssub")
        if ssub_B == 1:
            B = (self.onAc.estimates.W.dot((image - components).flatten(order="F") 
                                           - self.onAc.estimates.b0) + self.onAc.estimates.b0)
            background = B.reshape(self.onAc.estimates.dims, order="F")
        else:
            bc2 = self.onAc.estimates.downscale_matrix.dot(
                (image - components).flatten(order="F") - self.onAc.estimates.b0)
            background = (self.onAc.estimates.b0 + self.onAc.estimates.upscale_matrix.dot(
                    self.onAc.estimates.W.dot(bc2))).reshape(self.onAc.estimates.dims, order="F")
        image = ((components + background) - self.onAc.bnd_Y[0]) / np.diff(self.onAc.bnd_Y)
        image = np.minimum((image * 255.0), 255).astype("u1")
    except ValueError as ve:
        logger.info("ValueError: {0}".format(ve))
    # cor_frame = (self.frame - self.onAc.bnd_Y[0])/np.diff(self.onAc.bnd_Y)
    return image