REF: Use pytest warns to capture warning

Use pytest's infrastructure

statsmodels/genmod/tests/test_glm_weights.py

@@ -272,8 +272,7 @@ def setup_class(cls):
         # no wnobs yet in sandwich covariance calcualtion
         cls.corr_fact = 1 / np.sqrt(n_groups / (n_groups - 1))   #np.sqrt((wsum - 1.) / wsum)
         cov_kwds = {'groups': gid, 'use_correction':False}
-        with warnings.catch_warnings():
-            warnings.simplefilter("ignore", category=SpecificationWarning)
+        with pytest.warns(SpecificationWarning):
             cls.res1 = GLM(cpunish_data.endog, cpunish_data.exog,
                             family=sm.families.Poisson(), freq_weights=fweights
                             ).fit(cov_type='cluster', cov_kwds=cov_kwds)
@@ -774,19 +773,17 @@ def test_warnings_raised():
     gid = np.arange(1, 17 + 1) // 2
 
     cov_kwds = {'groups': gid, 'use_correction': False}
-    with warnings.catch_warnings(record=True) as w:
+    with pytest.warns(SpecificationWarning):
         res1 = GLM(cpunish_data.endog, cpunish_data.exog,
                    family=sm.families.Poisson(), freq_weights=weights
                    ).fit(cov_type='cluster', cov_kwds=cov_kwds)
         res1.summary()
-        assert len(w) >= 1
 
-    with warnings.catch_warnings(record=True) as w:
+    with pytest.warns(SpecificationWarning):
         res1 = GLM(cpunish_data.endog, cpunish_data.exog,
                    family=sm.families.Poisson(), var_weights=weights
                    ).fit(cov_type='cluster', cov_kwds=cov_kwds)
         res1.summary()
-        assert len(w) >= 1
 
 
 weights = [1, 1, 1, 2, 2, 2, 3, 3, 3, 1, 1, 1, 2, 2, 2, 3, 3]