eval.py 文件源码

def getCorrelation(model,words,f, params=[]):
    f = open(f,'r')
    lines = f.readlines()
    preds = []
    golds = []
    seq1 = []
    seq2 = []
    for i in lines:
        i = i.split("\t")
        p1 = i[0]; p2 = i[1]; score = float(i[2])
        X1, X2 = data_io.getSeqs(p1,p2,words)
        seq1.append(X1)
        seq2.append(X2)
        golds.append(score)
    x1,m1 = data_io.prepare_data(seq1)
    x2,m2 = data_io.prepare_data(seq2)
    if params and params.weightfile:
        m1 = data_io.seq2weight(x1, m1, params.weight4ind)
        m2 = data_io.seq2weight(x2, m2, params.weight4ind)
    scores = model.scoring_function(x1,x2,m1,m2)
    preds = np.squeeze(scores)
    return pearsonr(preds,golds)[0], spearmanr(preds,golds)[0]