dls_funct.py 文件源码

def compute_clustering_accuracy(label1, label2):
    """
    From clustering_on_transcript_compatibility_counts, see github for MIT license
    """
    uniq1,uniq2 = np.unique(label1),np.unique(label2)
    # Create two dictionaries. Each will store the indices of each label
    entries1,entries2 = {},{}
    for label in uniq1: entries1[label] = set(np.flatnonzero((label1==label)))
    for label in uniq2: entries2[label] = set(np.flatnonzero((label2==label)))
    # Create an intersection matrix which counts the number of entries that overlap for each label combination        
    W = np.zeros((len(uniq1),len(uniq2)))
    for i,j in itertools.product(range(len(uniq1)),range(len(uniq2))):
        W[i,j]=len(entries1[uniq1[i]].intersection(entries2[uniq2[j]]))
    # find the max weight matching
    match_val = get_max_wt_matching(uniq1,uniq2,W)
    # return the error rate
    return (1-match_val/float(len(label1)))*100