fresult.py 文件源码

 复制代码def auc_score(res_list):
    gp_list = np.array([])
    anno_list = np.array([])
    for res in res_list:
        g_pred = res.g_pred
        anno = res.annotation
        if g_pred.shape[-1] < anno.shape[-1]:
            anno = np.delete(anno, range(g_pred.shape[-1], anno.shape[-1]), axis=-1)
        elif g_pred.shape[-1] > anno.shape[-1]:
            g_pred = np.delete(g_pred, range(anno.shape[-1], g_pred.shape[-1]), axis=-1)
        gp_list = g_pred.T if len(gp_list) == 0 else np.append(gp_list, g_pred.T, axis=0)
        anno_list = anno.T if len(anno_list) == 0 else np.append(anno_list, anno.T, axis=0)

    assert(gp_list.shape == anno_list.shape)

    from sklearn.metrics import roc_auc_score
    class_auc = roc_auc_score(anno_list, gp_list, average=None)
    print('AUC of Classes:')
    print(class_auc)
    all_micro_auc = roc_auc_score(anno_list, gp_list, average='micro')
    print('Total micro AUC: {}'.format(all_micro_auc))

    all_macro_auc = roc_auc_score(anno_list, gp_list, average='macro')
    print('Total macro AUC: {}'.format(all_macro_auc))