def METHOD_NAME(self, data, lamb, clip = False):
    """This is what you actually call to do the deconvolution.
    parameters are:
    data - the raw data
    lamb - the regularisation parameter
    """
    #test to see if we need to recalculate filter factor        
    if not lamb == self.lamb: 
        self.WF = self.Ht/(self.H2 + lamb**2)
    self._r[:] = data
    #F = fftn(fs)
    #d = ifftshift(ifftn(F*self.H));
    self._plan_r_F()
    self._F *= self.WF
    #self._F /= (self.H2 + lamb**2)
    self._plan_F_r()
    res = ifftshift(self._r)
    if clip:
        res = numpy.maximum(res, 0)
    return res