evaluate.py 文件源码

def getCorrelation(model,words,f):
    f = open(f,'r')
    lines = f.readlines()
    preds = []
    golds = []
    seq1 = []
    seq2 = []
    for i in lines:
        i = i.split("\t")
        p1 = i[1]; p2 = i[2]; score = float(i[0])
    if len(p1.split()[0].split('_')) == 2:
        X1, X2, SX1, SX2 = getSeqs2(p1,p2,words)
    else:
            X1, X2 = getSeqs(p1,p2,words)
        seq1.append(X1)
        seq2.append(X2)
        golds.append(score)
    x1,m1 = utils.prepare_data(seq1)
    x2,m2 = utils.prepare_data(seq2)
    scores = model.scoring_function(x1,x2,m1,m2)
    preds = np.squeeze(scores)
    return pearsonr(preds,golds)[0], spearmanr(preds,golds)[0]