225ae82fa59eebcb13d322a4f7642afdbc534fd5,pymc3/tests/test_ode.py,,test_logp_scalar_ode,#,184

Before Change

    y0 = 0.0
    times = np.arange(0.5, 8, 0.5)

    yobs = np.array(
        [
            0.30,
            0.56,
            0.51,
            0.55,
            0.47,
            0.42,
            0.38,
            0.30,
            0.26,
            0.21,
            0.22,
            0.13,
            0.13,
            0.09,
            0.09,
        ]
    ).reshape(-1, 1)

    ode_model = DifferentialEquation(
        func=system_1, t0=0, times=times, n_odeparams=1, n_states=1
    )

    integrated_solution, *_ = ode_model._simulate([alpha, y0])
    manual_logp = norm.logpdf(
        x=np.ravel(yobs), loc=np.ravel(integrated_solution), scale=1
    ).sum()
    with pm.Model() as model_1:
        forward = ode_model(odeparams=[alpha], y0=[y0]).reshape(yobs.shape)
        y = pm.Normal("y", mu=forward, sd=1, observed=yobs)
    pymc3_logp = model_1.logp()

    np.testing.assert_allclose(manual_logp, pymc3_logp)

After Change

        scale=1
    ).sum()
    with pm.Model() as model_1:
        forward = ode_model(theta=[alpha], y0=[y0])
        y = pm.Normal("y", mu=forward, sd=1, observed=yobs)
    pymc3_logp = model_1.logp()

    np.testing.assert_allclose(manual_logp, pymc3_logp)

Instances