add metric argument to allow for other linkages in clusterer (#222)

* add `metric` argument to allow for other linkages * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * add docstring --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Jan Kwakkel <[email protected]>
quaquel · Mar 6, 2023 · f3e10d6 · f3e10d6
1 parent b003ee1
commit f3e10d6
Showing 1 changed file with 3 additions and 4 deletions.
diff --git a/ema_workbench/analysis/clusterer.py b/ema_workbench/analysis/clusterer.py
@@ -84,13 +84,14 @@ def plot_dendrogram(distances):
     return fig
 
 
-def apply_agglomerative_clustering(distances, n_clusters, linkage="average"):
+def apply_agglomerative_clustering(distances, n_clusters, metric="precomputed", linkage="average"):
     """apply agglomerative clustering to the distances
 
     Parameters
     ----------
     distances : ndarray
     n_clusters : int
+    metric : str, optional. The distance metric to use. The default is 'precomputed'. For a list of available metrics, see the documentation of scipy.spatial.distance.pdist.
     linkage : {'average', 'complete', 'single'}
 
     Returns
@@ -99,8 +100,6 @@ def apply_agglomerative_clustering(distances, n_clusters, linkage="average"):
 
     """
 
-    c = cluster.AgglomerativeClustering(
-        n_clusters=n_clusters, metric="precomputed", linkage=linkage
-    )
+    c = cluster.AgglomerativeClustering(n_clusters=n_clusters, metric=metric, linkage=linkage)
     clusters = c.fit_predict(distances)
     return clusters