diff --git a/docs/source/pecuzal_embedding.py b/docs/source/pecuzal_embedding.py
index bd34bfe..f647716 100644
--- a/docs/source/pecuzal_embedding.py
+++ b/docs/source/pecuzal_embedding.py
@@ -952,6 +952,9 @@ def uzal_cost_pecuzal(Y, Y_trial, Tw, K = 3, theiler = 1, norm = 'euclidean', ec
         # increased
 
         dist = compute_L_decrease(E2, E2_trial, eps2, eps2_trial, cnt+1, NN)
+        if math.isnan(dist):
+            raise Exception('Computed 0-distances. You might use model-data, thus try to add minimal additive noise to the signal you wish to embed and try again.')
+
         if dist > dist_former and dist_former<0:
             break
         else:
diff --git a/setup.py b/setup.py
index a301d37..210891b 100644
--- a/setup.py
+++ b/setup.py
@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="pecuzal_embedding", 
-    version="1.3.0",
+    version="1.3.1",
     author="K.H.Kraemer",
     author_email="hkraemer@pik-potsdam.de",
     description="PECUZAL automatic embedding of uni- and multivariate time series",
diff --git a/src/pecuzal_embedding.py b/src/pecuzal_embedding.py
index bd34bfe..f647716 100644
--- a/src/pecuzal_embedding.py
+++ b/src/pecuzal_embedding.py
@@ -952,6 +952,9 @@ def uzal_cost_pecuzal(Y, Y_trial, Tw, K = 3, theiler = 1, norm = 'euclidean', ec
         # increased
 
         dist = compute_L_decrease(E2, E2_trial, eps2, eps2_trial, cnt+1, NN)
+        if math.isnan(dist):
+            raise Exception('Computed 0-distances. You might use model-data, thus try to add minimal additive noise to the signal you wish to embed and try again.')
+
         if dist > dist_former and dist_former<0:
             break
         else:
diff --git a/tests/pecuzal_embedding.py b/tests/pecuzal_embedding.py
index bd34bfe..f647716 100644
--- a/tests/pecuzal_embedding.py
+++ b/tests/pecuzal_embedding.py
@@ -952,6 +952,9 @@ def uzal_cost_pecuzal(Y, Y_trial, Tw, K = 3, theiler = 1, norm = 'euclidean', ec
         # increased
 
         dist = compute_L_decrease(E2, E2_trial, eps2, eps2_trial, cnt+1, NN)
+        if math.isnan(dist):
+            raise Exception('Computed 0-distances. You might use model-data, thus try to add minimal additive noise to the signal you wish to embed and try again.')
+
         if dist > dist_former and dist_former<0:
             break
         else: