TST: Update for pytest 7

Remove 36 PytestRemovedIn8Warning and PytestReturnNotNoneWarning warnings.

probscale/tests/test_algo.py

@@ -121,7 +121,7 @@ def test__bs_fit(plot_data, fitlogs, known_lo, known_hi):
 
 
 class Test__estimate_from_fit(object):
-    def setup(self):
+    def setup_method(self):
         self.x = numpy.arange(1, 11, 0.5)
         self.slope = 2
         self.intercept = 3.5

probscale/tests/test_probscale.py

@@ -1,4 +1,5 @@
 import os
+import warnings
 
 import numpy
 import matplotlib.pyplot as plt
@@ -120,16 +121,16 @@ def test_minimal_norm_cdf(mn, mn_input):
 
 
 def test_sign_with_nan_no_warning(mn):
-    with pytest.warns(None) as record:
+    with warnings.catch_warnings():
+        warnings.simplefilter("error")
         res = mn._approx_erf(numpy.nan)
-    assert not record
     assert numpy.isnan(res)
 
 
 def test_sign_with_nan_no_warning_inv(mn):
-    with pytest.warns(None) as record:
+    with warnings.catch_warnings():
+        warnings.simplefilter("error")
         res = mn._approx_inv_erf(numpy.nan)
-    assert not record
     assert numpy.isnan(res)
 
 

probscale/tests/test_viz.py

@@ -72,7 +72,7 @@ def plot_data():
 
 
 class Test_fit_line(object):
-    def setup(self):
+    def setup_method(self):
         self.data = numpy.array(
             [
                 2.00,
@@ -454,7 +454,7 @@ def test_custom_xhat(self):
 
 
 class Test_plot_pos(object):
-    def setup(self):
+    def setup_method(self):
         self.data = numpy.arange(16)
 
         self.known_type4 = numpy.array(
@@ -740,7 +740,6 @@ def test_probplot_prob(plot_data):
     fig, ax = plt.subplots()
     fig = viz.probplot(plot_data, ax=ax, problabel="Test xlabel", datascale="log")
     assert isinstance(fig, plt.Figure)
-    return fig
 
 
 @pytest.mark.mpl_image_compare(baseline_dir=BASELINE_DIR, tolerance=TIGHT_TOLERANCE)
@@ -1026,7 +1025,6 @@ def test_probplot_test_results(plot_data):
     assert isinstance(results, dict)
     known_keys = sorted(["q", "x", "y", "xhat", "yhat", "res"])
     assert sorted(list(results.keys())) == known_keys
-    return fig
 
 
 @pytest.mark.parametrize("probax", ["x", "y"])