Calinski Harabasz Index function

gistfile1.py

def CH_index(X, labels, centroids):
    #X being a pandas dataframe, so X = dataframe.values
    #labels being the (KMeans(n_clusters=i).fit(X)).labels_
    #centroids being the KMeans centroid values of a fitted kmeans model
    '''
    https://github.com/scampion/scikit-learn/blob/master/scikits/learn/cluster/__init__.py
    '''
    mean = np.mean(X,axis=0) 
    B = np.sum([ np.sum(labels==i)*(c - mean)**2 for i,c in enumerate(centroids)])
    W = np.sum([ (x-centroids[labels[i]])**2 for i, x in enumerate(X)])
    c = len(centroids)
    n = len(X)
    return ((n-c)*B )/1.0/((c-1)*W)