Fix hypothesis error in Python 3.10 for extremely small ("subnormal")…

… histogram weights. Disable deprecations of deprecated Graph in its tests.

tests/structures/test_graph.py

@@ -15,7 +15,7 @@
 # from histogram_strategy import generate_increasing_list, generate_data_in_range
 
 
-def test_graph_structure():
+def test_graph():
     xs = [0, 1]
     ys = [2, 3]
 
@@ -84,7 +84,9 @@ def test_graph_structure():
     assert gr4._points == [xs, [1, 1.5], [0.5, 1]]
 
 
-def test_graph():
+# Graph is deprecated, but we keep its tests at the moment.
+@pytest.mark.filterwarnings('ignore::DeprecationWarning')
+def test_Graph():
     # sorts well
     coords = range(0, 10)
     values = map(math.sin, coords)
@@ -171,6 +173,7 @@ def test_graph():
     assert gr1 == Graph()
 
 
+@pytest.mark.filterwarnings('ignore::DeprecationWarning')
 def test_graph_equal():
     # test equality
     gr1 = Graph([(0, 1)])
@@ -194,6 +197,7 @@ def test_graph_equal():
     assert not gr2 == gr3
 
 
+@pytest.mark.filterwarnings('ignore::DeprecationWarning')
 def test_graph_to_csv():
     # to_csv works
     gr2 = Graph([(0, 1)])

tests/structures/test_histogram.py

@@ -4,11 +4,12 @@
 - scale (if filled with a non-negative weight) is always non-negative.
 - scale of a histogram filled with *weight* is *weight* times scale.
 - if all data fills into the histogram with bins size 1,
-its scale is number of data points.
-- if histogram bins are divided by N, its scale will be divided by N.
+  its scale is the number of data points.
+- if histogram bins are divided by N, its scale is divided by N.
 - Histogram and NumpyHistogram should be almost same (except for the upper edge).
 """
 import math
+import sys
 
 import hypothesis
 import pytest
@@ -30,7 +31,17 @@ def test_init_scale_zero(edges):
     assert hist.scale() == 0
 
 
-@given(edges=Edges1dStrategy, weight=s.floats(),
+# we disable subnormals, because in Python 3.10 sometimes (!)
+# the test failed with an error,
+#     where False = isclose((2.2216311086621543 * 5e-324), 1.5e-323)
+# https://hypothesis.readthedocs.io/en/latest/data.html#hypothesis.strategies.floats
+if sys.version_info.major > 2:
+    floats_ = s.floats(allow_subnormal=False)
+else:
+    # in Python 2 allow_subnormal is not recognised
+    floats_ = s.floats()
+
+@given(edges=Edges1dStrategy, weight=floats_,
        refinement=s.integers(min_value=1, max_value=20),
        data_samples=s.integers(min_value=1, max_value=50)
 )