diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py
index df9093a2..c14d6db5 100644
--- a/GPy/examples/dimensionality_reduction.py
+++ b/GPy/examples/dimensionality_reduction.py
@@ -215,6 +215,7 @@ def ssgplvm_oil(optimize=True, verbose=1, plot=True, N=200, Q=7, num_inducing=40
     return m
 
 def _simulate_matern(D1, D2, D3, N, num_inducing, plot_sim=False):
+    """Simulate some data drawn from a matern covariance and a periodic exponential for use in MRD demos."""
     Q_signal = 4
     import GPy
     import numpy as np
@@ -254,6 +255,7 @@ def _simulate_matern(D1, D2, D3, N, num_inducing, plot_sim=False):
     return slist, [S1, S2, S3], Ylist
 
 def _simulate_sincos(D1, D2, D3, N, num_inducing, plot_sim=False):
+    """Simulate some data drawn from sine and cosine for use in demos of MRD"""
     _np.random.seed(1234)
 
     x = _np.linspace(0, 4 * _np.pi, N)[:, None]
@@ -402,7 +404,8 @@ def mrd_simulation(optimize=True, verbose=True, plot=True, plot_sim=True, **kw):
     from GPy.models import MRD
 
     D1, D2, D3, N, num_inducing, Q = 60, 20, 36, 60, 6, 5
-    _, _, Ylist = _simulate_matern(D1, D2, D3, N, num_inducing, plot_sim)
+    _, _, Ylist = _simulate_sincos(D1, D2, D3, N, num_inducing, plot_sim)
+    
 
     # Ylist = [Ylist[0]]
     k = kern.Linear(Q, ARD=True)
@@ -585,6 +588,7 @@ def robot_wireless(optimize=True, verbose=True, plot=True):
     return m
 
 def stick_bgplvm(model=None, optimize=True, verbose=True, plot=True):
+    """Interactive visualisation of the Stick Man data from Ohio State University with the Bayesian GPLVM."""
     from GPy.models import BayesianGPLVM
     from matplotlib import pyplot as plt
     import numpy as np
@@ -613,7 +617,8 @@ def stick_bgplvm(model=None, optimize=True, verbose=True, plot=True):
         data_show = GPy.plotting.matplot_dep.visualize.stick_show(y, connect=data['connect'])
         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()
+        # Canvas.show doesn't work on OSX.
+        #fig.canvas.show()
         raw_input('Press enter to finish')
 
     return m