diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py
index 2a319e8a..a216eec6 100644
--- a/GPy/examples/dimensionality_reduction.py
+++ b/GPy/examples/dimensionality_reduction.py
@@ -518,21 +518,21 @@ def stick_bgplvm(model=None, optimize=True, verbose=True, plot=True):
     Q = 6
     kernel = GPy.kern.RBF(Q, lengthscale=np.repeat(.5, Q), ARD=True) 
     m = BayesianGPLVM(data['Y'], Q, init="PCA", num_inducing=20, kernel=kernel)
-    
+
     m.data = data
     m.likelihood.variance = 0.001
-    
+
     # optimize
-    if optimize: m.optimize('bfgs', messages=verbose, max_iters=800, xtol=1e-300, ftol=1e-300)
+    if optimize: m.optimize('bfgs', messages=verbose, max_iters=5e3, bfgs_factor=10)
     if plot:
-        plt.clf, (latent_axes, sense_axes) = plt.subplots(1, 2)
+        fig, (latent_axes, sense_axes) = plt.subplots(1, 2)
         plt.sca(latent_axes)
         m.plot_latent(ax=latent_axes)
         y = m.Y[:1, :].copy()
         data_show = GPy.plotting.matplot_dep.visualize.stick_show(y, connect=data['connect'])
-        GPy.plotting.matplot_dep.visualize.lvm_dimselect(m.X.mean[:1, :].copy(), m, data_show, latent_axes=latent_axes, sense_axes=sense_axes)
-        plt.draw()
-        plt.show()
+        dim_select = GPy.plotting.matplot_dep.visualize.lvm_dimselect(m.X.mean[:1, :].copy(), m, data_show, latent_axes=latent_axes, sense_axes=sense_axes)
+        fig.canvas.draw()
+        fig.canvas.show()
         raw_input('Press enter to finish')
 
     return m
diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py
index d7884730..3ba120aa 100644
--- a/GPy/plotting/matplot_dep/visualize.py
+++ b/GPy/plotting/matplot_dep/visualize.py
@@ -88,7 +88,6 @@ class vector_show(matplotlib_show):
 
 
 class lvm(matplotlib_show):
-    
     def __init__(self, vals, model, data_visualize, latent_axes=None, sense_axes=None, latent_index=[0,1]):
         """Visualize a latent variable model
 
@@ -147,7 +146,6 @@ class lvm(matplotlib_show):
         pass
 
     def on_click(self, event):
-        print 'click!'
         if event.inaxes!=self.latent_axes: return
         self.move_on = not self.move_on
         self.called = True
@@ -220,11 +218,10 @@ class lvm_dimselect(lvm):
         self.labels = labels
         lvm.__init__(self,vals,model,data_visualize,latent_axes,sense_axes,latent_index)
         self.show_sensitivities()
-        print "use left and right mouse butons to select dimensions"
+        print "use left and right mouse buttons to select dimensions"
 
 
     def on_click(self, event):
-
         if event.inaxes==self.sense_axes:
             new_index = max(0,min(int(np.round(event.xdata-0.5)),self.model.input_dim-1))
             if event.button == 1: