def xu_et_al_on_fold(feature_sets, train, test, y, y_all, X, dim, dimsum, learn_options):
    coef = pandas.read_csv(learn_options['xu_matrix_file'], skiprows=1, delimiter='\t')
    coef = coef[['A', 'T', 'C', 'G']] # swap columns so that they are in correct order
    coef = coef.values.flatten()[:, None]
    X = X.copy()
    X = np.append(X, np.zeros((X.shape[0], 3*4)), axis=1)
    X = X[:, 3*4:]
    y_pred = 1./(1+np.exp(-np.dot(X[test], coef)))

    return y_pred, coef
dataset/ETHPy150Open MicrosoftResearch/Azimuth/azimuth/models/baselines.py/xu_et_al_on_fold/original