def mc_bar_call_pv_with_paths(S0, K, B, T, r, sigma, M, I):
    # Simulating I paths with M time steps
    S = np.zeros((M + 1, I))
    S[0] = S0
    isChange = np.ones(I)
    dt = float(T) / M
    for t in range(1, M + 1):
        z = standard_normal(I)

        S_next = S[t - 1] * np.exp((r - 0.5 * sigma ** 2) * dt + sigma * m.sqrt(dt) * z)
        for i in range(I):
            if (S_next[i] >= B) :
                isChange[i] = 0
        for i in range(I):
            if (isChange[i] == 0) :
                S_next[i] = 0;
        S[t] = S_next

    # PV is extected discounted payoff
    C = np.sum(m.exp(-r * T) * np.maximum(S[-1] - K, 0)) / I
    return C, S