Make TestBoundedContinuous more readable

pymc3/tests/test_distributions.py

@@ -2737,27 +2737,35 @@ def get_dist_params_and_interval_bounds(self, model, rv_name):
             upper_interval,
         )
 
-    def test_missing_lower_bound(self):
+    def test_upper_bounded(self):
         bounded_rv_name = "lower_bounded"
         with Model() as model:
             TruncatedNormal(bounded_rv_name, mu=1, sigma=2, lower=None, upper=3)
-        dist_params, lower, upper = self.get_dist_params_and_interval_bounds(model, bounded_rv_name)
-        assert dist_params[2].value == -np.inf
-        assert dist_params[3].value == 3
-        assert lower is None
+        (
+            (_, _, lower, upper),
+            lower_interval,
+            upper_interval,
+        ) = self.get_dist_params_and_interval_bounds(model, bounded_rv_name)
+        assert lower.value == -np.inf
         assert upper.value == 3
+        assert lower_interval is None
+        assert upper_interval.value == 3
 
-    def test_missing_upper_bound(self):
+    def test_lower_bounded(self):
         bounded_rv_name = "upper_bounded"
         with Model() as model:
             TruncatedNormal(bounded_rv_name, mu=1, sigma=2, lower=-2, upper=None)
-        dist_params, lower, upper = self.get_dist_params_and_interval_bounds(model, bounded_rv_name)
-        assert dist_params[2].value == -2
-        assert dist_params[3].value == np.inf
+        (
+            (_, _, lower, upper),
+            lower_interval,
+            upper_interval,
+        ) = self.get_dist_params_and_interval_bounds(model, bounded_rv_name)
         assert lower.value == -2
-        assert upper is None
+        assert upper.value == np.inf
+        assert lower_interval.value == -2
+        assert upper_interval is None
 
-    def test_missing_upper_bound_array(self):
+    def test_vector_lower_bounded(self):
         bounded_rv_name = "upper_bounded"
         with Model() as model:
             TruncatedNormal(
@@ -2767,40 +2775,52 @@ def test_missing_upper_bound_array(self):
                 lower=np.array([-1.0, 0]),
                 upper=None,
             )
-        dist_params, lower, upper = self.get_dist_params_and_interval_bounds(model, bounded_rv_name)
+        (
+            (_, _, lower, upper),
+            lower_interval,
+            upper_interval,
+        ) = self.get_dist_params_and_interval_bounds(model, bounded_rv_name)
 
-        assert np.array_equal(dist_params[2].value, [-1, 0])
-        assert dist_params[3].value == np.inf
         assert np.array_equal(lower.value, [-1, 0])
-        assert upper is None
+        assert upper.value == np.inf
+        assert np.array_equal(lower_interval.value, [-1, 0])
+        assert upper_interval is None
 
-    def test_missing_partial_upper_bound_array(self):
+    def test_lower_bounded_broadcasted(self):
         bounded_rv_name = "upper_bounded"
         with Model() as model:
             TruncatedNormal(
                 bounded_rv_name,
                 mu=np.array([1, 1]),
                 sigma=np.array([2, 3]),
-                lower=np.array([-1.0, -np.inf]),
-                upper=None,
+                lower=-1,
+                upper=np.array([np.inf, np.inf]),
             )
-        dist_params, lower, upper = self.get_dist_params_and_interval_bounds(model, bounded_rv_name)
+        (
+            (_, _, lower, upper),
+            lower_interval,
+            upper_interval,
+        ) = self.get_dist_params_and_interval_bounds(model, bounded_rv_name)
 
-        assert np.array_equal(dist_params[2].value, [-1, -np.inf])
-        assert dist_params[3].value == np.inf
-        assert np.array_equal(lower.value, [-1, -np.inf])
-        assert upper is None
+        assert lower.value == -1
+        assert np.array_equal(upper.value, [np.inf, np.inf])
+        assert lower_interval.value == -1
+        assert upper_interval is None
 
-    def test_missing_upper_bound_with_richer_context(self):
+    def test_hierarchical(self):
         with Model() as model:
             sigma = TruncatedNormal("lower_bounded", mu=2, sigma=1.5, lower=0, upper=None)
             mu = TruncatedNormal("upper_bounded", mu=0, sigma=2, lower=None, upper=3)
             Normal("normal", mu=mu, sigma=sigma, observed=[1.3, -1.4, 2.0])
-        dist_params, lower, upper = self.get_dist_params_and_interval_bounds(model, "upper_bounded")
-        assert dist_params[2].value == -np.inf
-        assert dist_params[3].value == 3
-        assert lower is None
+        (
+            (_, _, lower, upper),
+            lower_interval,
+            upper_interval,
+        ) = self.get_dist_params_and_interval_bounds(model, "upper_bounded")
+        assert lower.value == -np.inf
         assert upper.value == 3
+        assert lower_interval is None
+        assert upper_interval.value == 3
 
 
 @pytest.mark.xfail(reason="LaTeX repr and str no longer applicable")