feat: add cal_external_cluster_validation_metrics();

pypots/utils/metrics.py

@@ -599,6 +599,37 @@ def cal_cluster_purity(
     return cluster_purity
 
 
+def cal_external_cluster_validation_metrics(class_predictions, targets):
+    """Computer all external cluster validation metrics available in PyPOTS and return as a dictionary.
+
+    Parameters
+    ----------
+    class_predictions :
+        Clustering results returned by a clusterer.
+
+    targets :
+        Ground truth (correct) clustering results.
+
+    Returns
+    -------
+    external_cluster_validation_metrics : dict
+        A dictionary contains all external cluster validation metrics available in PyPOTS.
+    """
+
+    ri = cal_rand_index(class_predictions, targets)
+    ari = cal_adjusted_rand_index(class_predictions, targets)
+    nmi = cal_nmi(class_predictions, targets)
+    cp = cal_cluster_purity(class_predictions, targets)
+
+    external_cluster_validation_metrics = {
+        "rand_index": ri,
+        "adjusted_rand_index": ari,
+        "nmi": nmi,
+        "cluster_purity": cp,
+    }
+    return external_cluster_validation_metrics
+
+
 def cal_silhouette(X: np.ndarray, predicted_labels: np.ndarray) -> float:
     """Compute the mean Silhouette Coefficient of all samples.