Finish assignment 4

1 files changed, 4 insertions, 5 deletions

diff --git a/Assignment 4/packages/clusterPlot.py b/Assignment 4/packages/clusterPlot.py
index 2f37a3d..4abc2c0 100644
--- a/Assignment 4/packages/clusterPlot.py
+++ b/Assignment 4/packages/clusterPlot.py
@@ -4,7 +4,7 @@ Created on Mon Apr 14 09:01:18 2014
 

 """

 

-def clusterPlot(X, clusterid, centroids='None', y='None', covars='None', figsize=(16,10)):

+def clusterPlot(X, clusterid, centroids='None', y='None', covars='None', figsize=None):

     '''

     CLUSTERPLOT Plots a clustering of a data set as well as the true class

     labels. If data is more than 2-dimensional it should be first projected

@@ -27,7 +27,7 @@ def clusterPlot(X, clusterid, centroids='None', y='None', covars='None', figsize
     covars      M-by-M-by-K tensor of covariance matrices (optional)

     '''

     import numpy as np

-    from matplotlib.pyplot import figure, cm, plot, hold, legend, xlim, show

+    from matplotlib.pyplot import figure, cm, plot, hold, legend, xlim

 

 

     X = np.asarray(X)

@@ -43,7 +43,8 @@ def clusterPlot(X, clusterid, centroids='None', y='None', covars='None', figsize
     ncolors = np.max([C,K])

     

     # plot data points color-coded by class, cluster markers and centroids

-    figure(figsize=figsize)        

+    if figsize != None:

+        figure(figsize=figsize)        

     hold(True)

     colors = [0]*ncolors

     for color in range(ncolors):

@@ -71,5 +72,3 @@ def clusterPlot(X, clusterid, centroids='None', y='None', covars='None', figsize
     legend(legend_items, numpoints=1, markerscale=.75, prop={'size': 9})

     

     xlim(X[:,0].min()*1.1, X[:,0].max()*1.2)

-    

-    show()