add test to check for inference method names

tests/test_alternative_samplers.py

@@ -30,6 +30,17 @@ def data_n100():
     return data
 
 
+def test_inference_method_names():
+    names = bmb.inference_methods.names
+
+    # Check PyMC inference method family
+    assert "mcmc" in names["pymc"].keys()
+    assert "vi" in names["pymc"].keys()
+
+    # Check bayeu inference method family. Currently, only MCMC methods are supported
+    assert "mcmc" in names["bayeux"].keys()
+
+
 def test_laplace():
     data = pd.DataFrame(np.repeat((0, 1), (30, 60)), columns=["w"])
     priors = {"Intercept": bmb.Prior("Uniform", lower=0, upper=1)}
@@ -56,7 +67,7 @@ def test_vi():
         (mode_n.item(), std_n.item()), (mode_a.item(), std_a.item()), decimal=2
     )
 
-# 
+
 @pytest.mark.parametrize("sampler", MCMC_METHODS_FILTERED)
 def test_logistic_regression_categoric_alternative_samplers(data_n100, sampler):
     model = bmb.Model("b1 ~ n1", data_n100, family="bernoulli")