diff --git a/examples/LEMS_SimExample3.xml b/examples/LEMS_SimExample3.xml
index 2b1e0a9..5204c5b 100644
--- a/examples/LEMS_SimExample3.xml
+++ b/examples/LEMS_SimExample3.xml
@@ -2,7 +2,7 @@
 
     <!-- 
 
-        This LEMS file has been automatically generated using PyNeuroML v1.2.3 (libNeuroML v0.5.8)
+        This LEMS file has been automatically generated using PyNeuroML v1.2.13 (libNeuroML v0.5.9)
 
      -->
 
diff --git a/examples/LEMS_SimExample4.xml b/examples/LEMS_SimExample4.xml
index b861b73..e584554 100644
--- a/examples/LEMS_SimExample4.xml
+++ b/examples/LEMS_SimExample4.xml
@@ -2,7 +2,7 @@
 
     <!-- 
 
-        This LEMS file has been automatically generated using PyNeuroML v1.2.3 (libNeuroML v0.5.8)
+        This LEMS file has been automatically generated using PyNeuroML v1.2.13 (libNeuroML v0.5.9)
 
      -->
 
diff --git a/examples/test_files/.test.ex4.jnmleden.omt b/examples/test_files/.test.ex4.jnmleden.omt
index a013434..3046d31 100644
--- a/examples/test_files/.test.ex4.jnmleden.omt
+++ b/examples/test_files/.test.ex4.jnmleden.omt
@@ -14,7 +14,7 @@ experiments:
         spike detection:
           method: threshold
           threshold: -64
-        tolerance: 0.0002527679474217274
+        tolerance: 0.00025278058645101804
 
   v1:
     observables:
@@ -26,4 +26,4 @@ experiments:
         spike detection:
           method: threshold
           threshold: -69
-        tolerance: 0.0002327287423609406
+        tolerance: 0.00023269200151868833
diff --git a/neuromllite/MatrixHandler.py b/neuromllite/MatrixHandler.py
index 8cf05de..3d1fa3b 100644
--- a/neuromllite/MatrixHandler.py
+++ b/neuromllite/MatrixHandler.py
@@ -18,6 +18,7 @@ class MatrixHandler(ConnectivityHandler):
     colormaps_used = []
 
     weight_arrays_to_show = {}
+    weight_array_figures = {}
 
     def __init__(self, level=10, nl_network=None, show_already=True, save_figs_to_dir=None):
         self.nl_network = nl_network
@@ -382,6 +383,9 @@ def finalise_document(self):
                     save_figure_to = os.path.join(self.save_figs_to_dir, '%s_%s.png'%(self.network_id, safe))
                     plt.savefig(save_figure_to, bbox_inches="tight")
                     print_v("Saved image to %s of plot: %s" % (save_figure_to, title))
+                    self.weight_array_figures[title] = save_figure_to
+
+
 
         print_v("Generating matrix for: %s" % self.network_id)