def azp(X, w, n_clusters=5, **kwargs): """AZP clustering algorithm. Parameters ---------- X : array-like n x k attribute data w : libpysal.weights.W instance spatial weights matrix n_clusters : int, optional, default: 5 The number of clusters to form. Returns ------- fitted cluster instance: region.p_regions.azp.AZP """ model = AZP() model.fit_from_w(attr=X.values, w=w, n_regions=n_clusters) return model
def test_w_basic(): cluster_object = AZP(random_state=0) cluster_object.fit_from_w(w, attr, n_regions=2) result = region_list_from_array(cluster_object.labels_) compare_region_lists(result, optimal_clustering)