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    # Exercise 4.2.5
    
    from matplotlib.pyplot import (figure, subplot, plot, xlabel, ylabel, 
                                   xticks, yticks,legend,show)
    
    # requires data from exercise 4.2.1
    from ex4_2_1 import *
    
    figure(figsize=(12,10))
    for m1 in range(M):
        for m2 in range(M):
            subplot(M, M, m1*M + m2 + 1)
            for c in range(C):
                class_mask = (y==c)
                plot(np.array(X[class_mask,m2]), np.array(X[class_mask,m1]), '.')
                if m1==M-1:
                    xlabel(attributeNames[m2])
                else:
                    xticks([])
                if m2==0:
                    ylabel(attributeNames[m1])
                else:
                    yticks([])
                #ylim(0,X.max()*1.1)
                #xlim(0,X.max()*1.1)
    legend(classNames)
    
    show()
    
    print('Ran Exercise 4.2.5')