diff --git a/solventmapcreator/clusteringanalysis/clustercalculation.py b/solventmapcreator/clusteringanalysis/clustercalculation.py
index c12915c2bb3ffd9d268669365cdb1c3454a71b35..30dc5c06578b786acd185d0d8c41446291f71bd2 100644
--- a/solventmapcreator/clusteringanalysis/clustercalculation.py
+++ b/solventmapcreator/clusteringanalysis/clustercalculation.py
@@ -13,17 +13,17 @@ logging.basicConfig()
 LOGGER = logging.getLogger(__name__)
 LOGGER.setLevel(logging.WARN)
 
-def clustering_by_all_methods(triangular_distance_matrix):
+def clustering_by_all_methods(condensed_distance_matrix):
     """This carries out the clustering using all the clustering methods.
     A dictionary is returned where the key is the clustering approach used.
     """
-    ward_linkage = ward_clustering(triangular_distance_matrix)
-    wpgmc_linkage = wpgmc_clustering(triangular_distance_matrix)
-    upgmc_linkage = upgmc_clustering(triangular_distance_matrix)
-    wpgma_linkage = wpgma_clustering(triangular_distance_matrix)
-    upgma_linkage = upgma_clustering(triangular_distance_matrix)
-    max_linkage = max_clustering(triangular_distance_matrix)
-    min_linkage = min_clustering(triangular_distance_matrix)
+    ward_linkage = ward_clustering(condensed_distance_matrix)
+    wpgmc_linkage = wpgmc_clustering(condensed_distance_matrix)
+    upgmc_linkage = upgmc_clustering(condensed_distance_matrix)
+    wpgma_linkage = wpgma_clustering(condensed_distance_matrix)
+    upgma_linkage = upgma_clustering(condensed_distance_matrix)
+    max_linkage = max_clustering(condensed_distance_matrix)
+    min_linkage = min_clustering(condensed_distance_matrix)
     return {"ward_clustering":ward_linkage,
             "wpgmc_clustering":wpgmc_linkage,
             "upgmc_clustering":upgmc_linkage,
@@ -32,42 +32,42 @@ def clustering_by_all_methods(triangular_distance_matrix):
             "max_clustering": max_linkage,
             "min_clustering":min_linkage}
 
-def ward_clustering(triangular_distance_matrix):
+def ward_clustering(condensed_distance_matrix):
     """This calculates the ward linkage for clustering.
     """
-    return calculate_clustering(triangular_distance_matrix, "ward")
+    return calculate_clustering(condensed_distance_matrix, "ward")
 
-def wpgmc_clustering(triangular_distance_matrix):
+def wpgmc_clustering(condensed_distance_matrix):
     """This calculates the median/WPGMC linkage for clustering.
     """
-    return calculate_clustering(triangular_distance_matrix, "median")
+    return calculate_clustering(condensed_distance_matrix, "median")
 
-def upgmc_clustering(triangular_distance_matrix):
+def upgmc_clustering(condensed_distance_matrix):
     """This calculates the centroid/UPGMC linkage for clustering.
     """
-    return calculate_clustering(triangular_distance_matrix, "centroid")
+    return calculate_clustering(condensed_distance_matrix, "centroid")
 
-def wpgma_clustering(triangular_distance_matrix):
+def wpgma_clustering(condensed_distance_matrix):
     """This calculates the weighted/WPGMA linkage for clustering.
     """
-    return calculate_clustering(triangular_distance_matrix,"weighted")
+    return calculate_clustering(condensed_distance_matrix,"weighted")
 
-def upgma_clustering(triangular_distance_matrix):
+def upgma_clustering(condensed_distance_matrix):
     """This calculates the average/UPGMA linkage for clustering.
     """
-    return calculate_clustering(triangular_distance_matrix, "average")
+    return calculate_clustering(condensed_distance_matrix, "average")
 
-def max_clustering(triangular_distance_matrix):
+def max_clustering(condensed_distance_matrix):
     """This calculates the complete/max/farthest linkage for clustering.
     """
-    return calculate_clustering(triangular_distance_matrix, "complete")
+    return calculate_clustering(condensed_distance_matrix, "complete")
 
-def min_clustering(triangular_distance_matrix):
+def min_clustering(condensed_distance_matrix):
     """This calculates the single/min/nearest linkage for clustering
     """
-    return calculate_clustering(triangular_distance_matrix, "single")
+    return calculate_clustering(condensed_distance_matrix, "single")
 
-def calculate_clustering(triangular_distance_matrix, method):
+def calculate_clustering(condensed_distance_matrix, method):
     """This calculates the clustering for the given input method.
     """
-    return cluster.linkage(triangular_distance_matrix, method=method)
+    return cluster.linkage(condensed_distance_matrix, method=method)