CLN: Switch to pytest.mark.slow

Consistently use pytest.mark.slow to indicate slow tests

Author: bashtage

statsmodels/emplike/tests/test_regression.py

@@ -1,7 +1,9 @@
 from __future__ import division
 
 from numpy.testing import assert_almost_equal
-from numpy.testing.decorators import slow
+
+import pytest
+
 from statsmodels.regression.linear_model import OLS
 from statsmodels.tools import add_constant
 from .results.el_results import RegressionResults
@@ -33,14 +35,14 @@ class TestRegressionPowell(GenRes):
 
     """
 
-    @slow
+    @pytest.mark.slow
     def test_hypothesis_beta0(self):
         beta0res = self.res1.el_test([-30], [0], return_weights=1,
                                      method='powell')
         assert_almost_equal(beta0res[:2], self.res2.test_beta0[:2], 4)
         assert_almost_equal(beta0res[2], self.res2.test_beta0[2], 4)
 
-    @slow
+    @pytest.mark.slow
     def test_hypothesis_beta1(self):
         beta1res = self.res1.el_test([.5], [1], return_weights=1,
                                      method='powell')
@@ -106,14 +108,14 @@ def test_hypothesis_beta1(self):
         assert_almost_equal(beta1res[:2], self.res2.test_beta1[:2], 4)
         assert_almost_equal(beta1res[2], self.res2.test_beta1[2], 4)
 
-    @slow
+    @pytest.mark.slow
     def test_hypothesis_beta2(self):
         beta2res = self.res1.el_test([1], [2], return_weights=1,
                                           method='nm')
         assert_almost_equal(beta2res[:2], self.res2.test_beta2[:2], 4)
         assert_almost_equal(beta2res[2], self.res2.test_beta2[2], 4)
 
-    @slow
+    @pytest.mark.slow
     def test_hypothesis_beta3(self):
         beta3res = self.res1.el_test([0], [3], return_weights=1,
                                           method='nm')
@@ -122,7 +124,7 @@ def test_hypothesis_beta3(self):
 
     #  Confidence interval results obtained through hyp testing in Matlab
 
-    @slow
+    @pytest.mark.slow
     def test_ci_beta0(self):
         # All confidence intervals are tested by conducting a hypothesis
         # tests at the confidence interval values since el_test
@@ -136,17 +138,17 @@ def test_ci_beta0(self):
         beta0ci = self.res1.conf_int_el(0, method='nm')
         assert_almost_equal(beta0ci, self.res2.test_ci_beta0, 6)
 
-    @slow
+    @pytest.mark.slow
     def test_ci_beta1(self):
         beta1ci = self.res1.conf_int_el(1, method='nm')
         assert_almost_equal(beta1ci, self.res2.test_ci_beta1, 6)
 
-    @slow
+    @pytest.mark.slow
     def test_ci_beta2(self):
         beta2ci = self.res1.conf_int_el(2, lower_bound=.59, upper_bound=2.2,  method='nm')
         assert_almost_equal(beta2ci, self.res2.test_ci_beta2, 6)
 
-    @slow
+    @pytest.mark.slow
     def test_ci_beta3(self):
         beta3ci = self.res1.conf_int_el(3, method='nm')
         assert_almost_equal(beta3ci, self.res2.test_ci_beta3, 6)

statsmodels/stats/tests/test_knockoff.py

@@ -1,10 +1,11 @@
 import numpy as np
+from numpy.testing import assert_allclose, assert_array_equal
+import pytest
+
 from statsmodels.stats import knockoff_regeffects as kr
 from statsmodels.stats._knockoff import (RegressionFDR,
                                          _design_knockoff_equi,
                                          _design_knockoff_sdp)
-from numpy.testing import assert_allclose, assert_array_equal
-from numpy.testing.decorators import slow
 
 try:
     import cvxopt
@@ -81,7 +82,7 @@ def test_testers():
             RegressionFDR(y, x, tv, design_method=method)
 
 
-@slow
+@pytest.mark.slow
 def test_sim():
     # This function assesses the performance of the knockoff approach
     # relative to its theoretical claims.