95ee3130ab91b46eee8e931fd73d20a9cc81f4f4,pyglmnet/pyglmnet.py,,simulate_glm,#Any#Any#Any#Any#Any#Any#Any#,325

Before Change

        return _lmb(distr, beta0, beta, X, eta)

    if random_state is not None:
        np.random.RandomState(random_state)
    if distr == "softplus" or distr == "poisson":
        y = np.random.poisson(_lmb(distr, beta0, beta, X, eta))
    if distr == "gaussian":
        y = np.random.normal(_lmb(distr, beta0, beta, X, eta))

After Change

    if not sample:
        return _lmb(distr, beta0, beta, X, eta)

    _random_state = np.random.RandomState(random_state)
    if distr == "softplus" or distr == "poisson":
        y = _random_state.poisson(_lmb(distr, beta0, beta, X, eta))
    if distr == "gaussian":
        y = _random_state.normal(_lmb(distr, beta0, beta, X, eta))

Instances