Raise NotImplementedError in not yet refactored timeseries distributions

Co-authored-by: Thomas Wiecki <[email protected]>

Author: 2 people

pymc/distributions/timeseries.py

@@ -648,6 +648,13 @@ class GARCH11(distribution.Continuous):
         initial_vol >= 0, initial volatility, sigma_0
     """
 
+    def __new__(cls, *args, **kwargs):
+        raise NotImplementedError(f"{cls.__name__} has not yet been ported to PyMC 4.0.")
+
+    @classmethod
+    def dist(cls, *args, **kwargs):
+        raise NotImplementedError(f"{cls.__name__} has not yet been ported to PyMC 4.0.")
+
     def __init__(self, omega, alpha_1, beta_1, initial_vol, *args, **kwargs):
         super().__init__(*args, **kwargs)
 
@@ -705,6 +712,13 @@ class EulerMaruyama(distribution.Continuous):
         parameters of the SDE, passed as ``*args`` to ``sde_fn``
     """
 
+    def __new__(cls, *args, **kwargs):
+        raise NotImplementedError(f"{cls.__name__} has not yet been ported to PyMC 4.0.")
+
+    @classmethod
+    def dist(cls, *args, **kwargs):
+        raise NotImplementedError(f"{cls.__name__} has not yet been ported to PyMC 4.0.")
+
     def __init__(self, dt, sde_fn, sde_pars, *args, **kwds):
         super().__init__(*args, **kwds)
         self.dt = dt = at.as_tensor_variable(dt)
@@ -757,6 +771,13 @@ class MvGaussianRandomWalk(distribution.Continuous):
 
     """
 
+    def __new__(cls, *args, **kwargs):
+        raise NotImplementedError(f"{cls.__name__} has not yet been ported to PyMC 4.0.")
+
+    @classmethod
+    def dist(cls, *args, **kwargs):
+        raise NotImplementedError(f"{cls.__name__} has not yet been ported to PyMC 4.0.")
+
     def __init__(
         self, mu=0.0, cov=None, tau=None, chol=None, lower=True, init=None, *args, **kwargs
     ):
@@ -879,6 +900,13 @@ class MvStudentTRandomWalk(MvGaussianRandomWalk):
         distribution for initial value (Defaults to Flat())
     """
 
+    def __new__(cls, *args, **kwargs):
+        raise NotImplementedError(f"{cls.__name__} has not yet been ported to PyMC 4.0.")
+
+    @classmethod
+    def dist(cls, *args, **kwargs):
+        raise NotImplementedError(f"{cls.__name__} has not yet been ported to PyMC 4.0.")
+
     def __init__(self, nu, *args, **kwargs):
         super().__init__(*args, **kwargs)
         self.nu = at.as_tensor_variable(nu)

pymc/tests/test_distributions_timeseries.py

@@ -435,7 +435,7 @@ def test_moment(self, size, expected):
         assert_moment_is_expected(model, expected, check_finite_logp=False)
 
 
-@pytest.mark.xfail(reason="Timeseries not refactored")
+@pytest.mark.xfail(reason="Timeseries not refactored", raises=NotImplementedError)
 def test_GARCH11():
     # test data ~ N(0, 1)
     data = np.array(
@@ -496,7 +496,7 @@ def _gen_sde_path(sde, pars, dt, n, x0):
     return np.array(xs)
 
 
-@pytest.mark.xfail(reason="Timeseries not refactored")
+@pytest.mark.xfail(reason="Timeseries not refactored", raises=NotImplementedError)
 def test_linear():
     lam = -0.78
     sig2 = 5e-3