remove tests

Author: williambdean

pymc/gp/gp.py

@@ -458,8 +458,7 @@ def marginal_likelihood(
         name,
         X,
         y,
-        sigma=None,
-        noise=None,
+        sigma,
         jitter=JITTER_DEFAULT,
         is_observed=True,
         **kwargs,
@@ -777,7 +776,7 @@ def _build_marginal_likelihood_loglik(self, y, X, Xu, sigma, jitter):
         quadratic = 0.5 * (pt.dot(r, r_l) - pt.dot(c, c))
         return -1.0 * (constant + logdet + quadratic + trace)
 
-    def marginal_likelihood(self, name, X, Xu, y, sigma=None, jitter=JITTER_DEFAULT, **kwargs):
+    def marginal_likelihood(self, name, X, Xu, y, sigma, jitter=JITTER_DEFAULT, **kwargs):
         R"""
         Return the approximate marginal likelihood distribution.
 

tests/gp/test_gp.py

@@ -25,84 +25,6 @@
 from pymc.math import cartesian
 
 
-class TestSigmaParams:
-    def setup_method(self):
-        """Common setup."""
-        self.x = np.linspace(-5, 5, 30)[:, None]
-        self.xu = np.linspace(-5, 5, 10)[:, None]
-        self.y = np.random.normal(0.25 * self.x, 0.1)
-
-        with pm.Model() as self.model:
-            cov_func = pm.gp.cov.Linear(1, c=0.0)
-            c = pm.Normal("c", mu=20.0, sigma=100.0)
-            mean_func = pm.gp.mean.Constant(c)
-            self.gp = self.gp_implementation(mean_func=mean_func, cov_func=cov_func)
-            self.sigma = pm.HalfNormal("sigma", sigma=100)
-
-
-class TestMarginalSigmaParams(TestSigmaParams):
-    R"""Tests for the deprecation warnings and raising ValueError."""
-
-    gp_implementation = pm.gp.Marginal
-
-    def test_catch_warnings(self):
-        """Warning from using the old noise parameter."""
-        with self.model:
-            with pytest.warns(FutureWarning):
-                self.gp.marginal_likelihood("lik_noise", X=self.x, y=self.y, noise=self.sigma)
-
-            with pytest.warns(FutureWarning):
-                self.gp.conditional(
-                    "cond_noise",
-                    Xnew=self.x,
-                    given={
-                        "noise": self.sigma,
-                    },
-                )
-
-    def test_raise_value_error(self):
-        """Either both or neither parameter is specified."""
-        with self.model:
-            with pytest.raises(ValueError):
-                self.gp.marginal_likelihood(
-                    "like_both", X=self.x, y=self.y, noise=self.sigma, sigma=self.sigma
-                )
-
-            with pytest.raises(ValueError):
-                self.gp.marginal_likelihood("like_neither", X=self.x, y=self.y)
-
-
-class TestMarginalApproxSigmaParams(TestSigmaParams):
-    R"""Tests for the deprecation warnings and raising ValueError"""
-
-    gp_implementation = pm.gp.MarginalApprox
-
-    @pytest.mark.xfail(reason="Possible shape problem, see #6366")
-    def test_catch_warnings(self):
-        """Warning from using the old noise parameter."""
-        with self.model:
-            with pytest.warns(FutureWarning):
-                self.gp.marginal_likelihood(
-                    "lik_noise", X=self.x, Xu=self.xu, y=self.y, noise=self.sigma
-                )
-
-    def test_raise_value_error(self):
-        """Either both or neither parameter is specified."""
-        with self.model:
-            with pytest.raises(ValueError):
-                self.gp.marginal_likelihood(
-                    "like_both",
-                    X=self.x,
-                    Xu=self.xu,
-                    y=self.y,
-                    noise=self.sigma,
-                    sigma=self.sigma,
-                )
-
-            with pytest.raises(ValueError):
-                self.gp.marginal_likelihood("like_neither", X=self.x, Xu=self.xu, y=self.y)
-
-
 class TestMarginalVsMarginalApprox:
     R"""
     Compare test fits of models Marginal and MarginalApprox.