diff --git a/examples/example_16/ulens_model_fit.py b/examples/example_16/ulens_model_fit.py
index c409787d..f45fb353 100644
--- a/examples/example_16/ulens_model_fit.py
+++ b/examples/example_16/ulens_model_fit.py
@@ -38,7 +38,7 @@
 except Exception:
     raise ImportError('\nYou have to install MulensModel first!\n')
 
-__version__ = '0.34.0'
+__version__ = '0.34.1'
 
 
 class UlensModelFit(object):
@@ -3131,10 +3131,7 @@ def _second_Y_axis_get_fluxes(self, ylim):
         flux_max = mm.Utils.get_flux_from_mag(ylim[1])
         (source_flux, blend_flux) = self._event.get_ref_fluxes()
 
-        if self._model.n_sources == 1:
-            total_source_flux = source_flux
-        else:
-            total_source_flux = sum(source_flux)
+        total_source_flux = sum(source_flux)
         A_min = (flux_min - blend_flux) / total_source_flux
         A_max = (flux_max - blend_flux) / total_source_flux
 
@@ -3146,11 +3143,11 @@ def _second_Y_axis_optimal(self, ax2, A_min, A_max):
         """
         ax2.set_ylim(A_min, A_max)
         A_values = ax2.yaxis.get_ticklocs().round(7)
-        A_values = A_values[(A_values >= 1.) & (A_values < A_max)]
+        A_values = A_values[(A_values >= max(1, A_min)) & (A_values < A_max)]
         is_integer = [mag.is_integer() for mag in A_values]
         if all(is_integer):
             labels = [f"{int(x):d}" for x in A_values]
-            return (A_values.tolist(), labels, False)
+            return (A_values, labels, False)
 
         fnum = np.array([str(x)[::-1].find(".") for x in A_values])
         labels = np.array([f"%0.{max(fnum)}f" % x for x in A_values])
@@ -3158,11 +3155,11 @@ def _second_Y_axis_optimal(self, ax2, A_min, A_max):
             msg = ("The computed magnifications for the second Y scale cover"
                    " a range too small to be shown: {:}")
             warnings.warn(msg.format(A_values))
-            return (A_values.tolist(), labels.tolist(), True)
+            return (A_values, labels.tolist(), True)
         if max(fnum) >= 4:
             labels = np.array([f"{x:0.3f}" for x in A_values])
 
-        return (A_values[fnum < 4].tolist(), labels[fnum < 4].tolist(), False)
+        return (A_values[fnum < 4], labels[fnum < 4].tolist(), False)
 
     def _second_Y_axis_warnings(self, flux, labels, A_values, A_min, A_max):
         """
@@ -3183,7 +3180,7 @@ def _second_Y_axis_warnings(self, flux, labels, A_values, A_min, A_max):
                    "side) Y-axis scale are from {:} to {:},\nbut the range "
                    "of plotted magnifications is from {:} to {:}, hence, "
                    "the second scale is not plotted")
-            args = [min(A_values), max(A_values), A_min[0], A_max[0]]
+            args = [np.min(A_values), np.max(A_values), A_min[0], A_max[0]]
             warnings.warn(msg.format(*args))
             return True