How to use the identify.FF_WEIGHTED_VARIANCE function in identify

def get_measurement_columns(self, pipeline):
        '''Column definitions for measurements made by IdentifyPrimAutomatic'''
        columns = cpmi.get_object_measurement_columns(self.object_name.value)
        columns += [(cpmeas.IMAGE, 
                     format%self.object_name.value,
                     cpmeas.COLTYPE_FLOAT)
                    for format in (FF_FINAL_THRESHOLD, FF_ORIG_THRESHOLD,
                                   FF_WEIGHTED_VARIANCE, FF_SUM_OF_ENTROPIES)]
        return columns

if isinstance(local_threshold,np.ndarray):
                ave_threshold = np.mean(local_threshold)
            else:
                ave_threshold = local_threshold
            
            measurements.add_measurement(cpmeas.IMAGE,
                                         cpmi.FF_FINAL_THRESHOLD%(objname),
                                         np.array([ave_threshold],
                                                     dtype=float))
            measurements.add_measurement(cpmeas.IMAGE,
                                         cpmi.FF_ORIG_THRESHOLD%(objname),
                                         np.array([global_threshold],
                                                      dtype=float))
            wv = cpthresh.weighted_variance(img, mask, local_threshold)
            measurements.add_measurement(cpmeas.IMAGE,
                                         cpmi.FF_WEIGHTED_VARIANCE%(objname),
                                         np.array([wv],dtype=float))
            entropies = cpthresh.sum_of_entropies(img, mask, local_threshold)
            measurements.add_measurement(cpmeas.IMAGE,
                                         cpmi.FF_SUM_OF_ENTROPIES%(objname),
                                         np.array([entropies],dtype=float))
        cpmi.add_object_count_measurements(measurements, objname, object_count)
        cpmi.add_object_location_measurements(measurements, objname,
                                              segmented_out)
        #
        # Relate the secondary objects to the primary ones and record
        # the relationship.
        #
        children_per_parent, parents_of_children = \
            objects.relate_children(objects_out)
        measurements.add_measurement(self.primary_objects.value,
                                     cpmi.FF_CHILDREN_COUNT%objname,