'generate sample of Wiener Process'

def simulateW(self, nobs=100, T=1, dt=None, nrepl=1):

    dt = ((T * 1.0) / nobs)
    t = np.linspace(dt, 1, nobs)
    dW = (np.sqrt(dt) * np.random.normal(size=(nrepl, nobs)))
    W = np.cumsum(dW, 1)
    self.dW = dW
    return (W, t)
