update cls.sd in tests

Author: MarcoGorelli

pymc3/tests/test_glm.py

@@ -46,9 +46,9 @@ def setup_class(cls):
         super().setup_class()
         cls.intercept = 1
         cls.slope = 3
-        cls.sd = 0.05
+        cls.sigma = 0.05
         x_linear, cls.y_linear = generate_data(cls.intercept, cls.slope, size=1000)
-        cls.y_linear += np.random.normal(size=1000, scale=cls.sd)
+        cls.y_linear += np.random.normal(size=1000, scale=cls.sigma)
         cls.data_linear = pd.DataFrame(dict(x=x_linear, y=cls.y_linear))
 
         x_logistic, y_logistic = generate_data(cls.intercept, cls.slope, size=3000)

pymc3/tests/test_models_linear.py

@@ -35,7 +35,7 @@ def setup_class(cls):
         cls.slope = 3
         cls.sigma = 0.05
         x_linear, cls.y_linear = generate_data(cls.intercept, cls.slope, size=1000)
-        cls.y_linear += np.random.normal(size=1000, scale=cls.sd)
+        cls.y_linear += np.random.normal(size=1000, scale=cls.sigma)
         cls.data_linear = dict(x=x_linear, y=cls.y_linear)
 
         x_logistic, y_logistic = generate_data(cls.intercept, cls.slope, size=3000)