model.py 文件源码

def _choose_cov(self, cov_type, **cov_config):
        """Return covariance estimator reformat clusters"""
        cov_est = self._cov_estimators[cov_type]
        if cov_type != 'clustered':
            return cov_est, cov_config
        cov_config_upd = {k: v for k, v in cov_config.items()}

        clusters = cov_config.get('clusters', None)
        if clusters is not None:
            clusters = self.reformat_clusters(clusters).copy()
            cluster_max = np.nanmax(clusters.values3d, axis=1)
            delta = cluster_max - np.nanmin(clusters.values3d, axis=1)
            if np.any(delta != 0):
                raise ValueError('clusters must not vary within an entity')

            index = clusters.panel.minor_axis
            reindex = clusters.entities
            clusters = pd.DataFrame(cluster_max.T, index=index, columns=clusters.vars)
            clusters = clusters.loc[reindex].astype(np.int64)
            cov_config_upd['clusters'] = clusters

        return cov_est, cov_config_upd