def _cluster_and_decide()

in graspologic/cluster/divisive_cluster.py [0:0]

• 34 lines of code
• 8 McCabe index (conditional complexity)

    def _cluster_and_decide(self, X: np.ndarray) -> np.ndarray:
        if self.is_root:
            min_components = self.min_components
        else:
            min_components = 1

        if self.cluster_method == "gmm":
            cluster = AutoGMMCluster(
                min_components=min_components,
                max_components=self.max_components,
                **self.cluster_kws
            )
            cluster.fit(X)
            model = cluster.model_
            criter = cluster.criter_
            k = cluster.n_components_
            pred = cluster.predict(X)

            if self.delta_criter > 0:
                single_cluster = AutoGMMCluster(
                    min_components=1, max_components=1, **self.cluster_kws
                )
                single_cluster.fit(X)
                criter_single_cluster = single_cluster.criter_

                if k > 1:
                    # check whether the difference between the criterion
                    # of "split" and "not split" is greater than
                    # the threshold, delta_criter
                    if criter_single_cluster - criter < self.delta_criter:
                        pred = np.zeros((len(X), 1), dtype=int)

        elif self.cluster_method == "kmeans":
            cluster = KMeansCluster(
                max_clusters=self.max_components, **self.cluster_kws
            )
            cluster.fit(X)
            model = cluster.model_
            pred = cluster.predict(X)

        self.model_ = model
        return pred