def get_stats_result(self, request):
        """Return the StatsResult object for this statistic"""
        stats_datasets = StatsMakerDataverses(**request.GET.dict())

        pub_state = self.get_pub_state(request)

        if pub_state == self.PUB_STATE_ALL:
            stats_result = stats_datasets.get_dataverse_affiliation_counts()
        elif pub_state == self.PUB_STATE_UNPUBLISHED:
            stats_result = stats_datasets.get_dataverse_affiliation_counts_unpublished()
        else:
            stats_result = stats_datasets.get_dataverse_affiliation_counts_published()

        return stats_result
def main():
    # Contingency Table from Wilks (2011) Table 8.3
    table = np.array([[50, 91, 71],
                      [47, 2364, 170],
                      [54, 205, 3288]])
    mct = MulticlassContingencyTable(table, n_classes=table.shape[0],
                                     class_names=np.arange(table.shape[0]).astype(str))
    print(mct.peirce_skill_score())
    print(mct.gerrity_score())