b2566d099e6b0b4cc8c3958638d06ad3c87eee41,pymc/tests/test_graph.py,,mymodel,#,7

Before Change

    def C(value=0, mom = A, dad = B):
        return 0.

    F = []

    @stochastic
    def x_0(value=0, mod = C):
        return 0.

After Change

def mymodel():
    mu=pm.Normal("mu",0,1)
    N= [pm.Normal("N_%i"%i,mu,1) for i in xrange(10)]
    z = pm.Lambda("z",lambda n=N: np.sum(n))
    @pm.potential
    def y(z=z):
        return -z**2
    return mu,N,z,y

Instances