--- a/python/ml.py	Tue Jul 04 17:36:24 2017 -0400
+++ b/python/ml.py	Tue Jul 04 18:00:01 2017 -0400
@@ -266,7 +266,7 @@
             print('Mean overall similarity: {}'.format((similarities[cluster][:,cluster].sum()+n)/(n*(n-1))))
 
 # Gaussian Mixture Models
-def plotGMM(mean, covariance, num, fig, color, alpha = 0.3):
+def plotGMM(mean, covariance, gmmId, fig, color, alpha = 0.3):
     v, w = np.linalg.eigh(covariance)
     angle = 180*np.arctan2(w[0][1], w[0][0])/np.pi
     v *= 4
@@ -275,7 +275,7 @@
     ell.set_alpha(alpha)
     fig.axes[0].add_artist(ell)
     plt.plot([mean[0]], [mean[1]], 'x'+color)
-    plt.annotate(str(num), xy=(mean[0]+1, mean[1]+1))
+    plt.annotate(str(gmmId), xy=(mean[0]+1, mean[1]+1))
 
 def plotGMMClusters(model, labels = None, dataset = None, fig = None, colors = utils.colors, nUnitsPerPixel = 1., alpha = 0.3):
     '''plot the ellipse corresponding to the Gaussians