diff --git a/Fred/__init__.py b/Fred/__init__.py
index 517d82e..035b227 100644
--- a/Fred/__init__.py
+++ b/Fred/__init__.py
@@ -4,31 +4,40 @@
 
 def plot_curve(*curves, savename=None, saveextension=None):
     import matplotlib.pyplot as plt
+    max_compl = 1
+    for curve in curves:
+        if isinstance(curve, backend.Curve):
+            max_compl = max(max_compl, curve.complexity)
+        elif isinstance(curve, backend.Curves):
+            for curv in curve:
+                max_compl = max(max_compl, curv.complexity)
+        elif isinstance(curve, backend.Clustering_Result):
+            for curv in curve:
+                max_compl = max(max_compl, curv.complexity)
     for curve in curves:
         if isinstance(curve, backend.Curve):
             if curve.dimensions >= 2:
                 p = plt.plot(curve.values[:, 0], curve.values[:, 1], '--o', label = curve.name, markersize = 7, markevery = curve.complexity)
                 plt.plot(curve.values[1:, 0], curve.values[1:, 1], 'x', label = None, color = p[0].get_color(), markersize = 7)
             else:
-                p = plt.plot(range(0, len(curve)), curve.values, '--o', label = curve.name, markersize = 7, markevery = curve.complexity)
-                plt.plot(range(1, len(curve)), curve.values[1:], 'x', label = None, color = p[0].get_color(), markersize = 7)
+                p = plt.plot([i * max_compl / len(curve) for i in range(len(curve))], curve.values, '--o', label = curve.name, markersize = 7, markevery = curve.complexity)
+                plt.plot([i * max_compl / len(curve) for i in range(1, len(curve))], curve.values[1:], 'x', label = None, color = p[0].get_color(), markersize = 7)
         elif isinstance(curve, backend.Curves):
             for curv in curve:
                 if curv.dimensions >= 2:
                     p = plt.plot(curv.values[:, 0], curv.values[:, 1], '--o', label = curv.name, markersize = 7, markevery = curv.complexity)
                     plt.plot(curv.values[1:, 0], curv.values[1:, 1], 'x', label = None, color = p[0].get_color(), markersize = 7)
                 else:
-                    p = plt.plot(range(0, len(curv)), curv.values, '--o', label = curv.name, markersize = 7, markevery = curv.complexity)
-                    plt.plot(range(1, len(curv)), curv.values[1:], 'x', label = None, color = p[0].get_color(), markersize = 7)
+                    p = plt.plot([i * max_compl / len(curv) for i in range(len(curv))], curv.values, '--o', label = curv.name, markersize = 7, markevery = curv.complexity)
+                    plt.plot([i * max_compl / len(curv) for i in range(1, len(curv))], curv.values[1:], 'x', label = None, color = p[0].get_color(), markersize = 7)
         elif isinstance(curve, backend.Clustering_Result):
             for curv in curve:
                 if curv.dimensions >= 2:
                     p = plt.plot(curv.values[:, 0], curv.values[:, 1], '-o', label = curv.name, markersize = 7, markevery = curv.complexity)
                     plt.plot(curv.values[1:, 0], curv.values[1:, 1], 'x', label = None, color = p[0].get_color(), markersize = 7)
                 else:
-                    p = plt.plot(range(0, len(curv)), curv.values, '-o', label = curv.name, markersize = 7, markevery = curv.complexity)
-                    plt.plot(range(0, len(curv)), curv.values[1:], 'x', label = None, color = p[0].get_color(), markersize = 7)
-                
+                    p = plt.plot([i * max_compl / len(curv) for i in range(len(curv))], curv.values, '-o', label = curv.name, markersize = 7, markevery = curv.complexity)
+                    plt.plot([i * max_compl / len(curv) for i in range(1, len(curv))], curv.values[1:], 'x', label = None, color = p[0].get_color(), markersize = 7)
     plt.legend(title='Curve names:')
     plt.title('Fred Curves')
     if savename is None:
diff --git a/setup.py b/setup.py
index eca1535..b89cc8d 100644
--- a/setup.py
+++ b/setup.py
@@ -74,7 +74,7 @@ def build_extension(self, ext):
 
 setup(
     name='Fred-Frechet',
-    version='1.9.10',
+    version='1.9.11',
     author='Dennis Rohde',
     author_email='dennis.rohde@tu-dortmund.de',
     description='A fast, scalable and light-weight C++ Fréchet distance library, exposed to python and focused on (k,l)-clustering of polygonal curves.',