Fixes for numpy 1.14.0 compatibility
- UPDATEIFCOPY is deprecated, replaced with similar (but not identical)
WRITEBACKIFCOPY; trying to access the flag causes a deprecation
warning under numpy 1.14, so just check the new flag there.
- Numpy `repr` formatting of floats changed in 1.14.0 to `[1., 2., 3.]`
instead of the pre-1.14 `[ 1., 2., 3.]`. Updated the tests to
check for equality with the `repr(...)` value rather than the
hard-coded (and now version-dependent) string representation.
diff --git a/tests/test_numpy_array.py b/tests/test_numpy_array.py
index 2743393..5084898 100644
--- a/tests/test_numpy_array.py
+++ b/tests/test_numpy_array.py
@@ -137,6 +137,7 @@
def test_wrap():
def assert_references(a, b, base=None):
+ from distutils.version import LooseVersion
if base is None:
base = a
assert a is not b
@@ -147,7 +148,10 @@
assert a.flags.f_contiguous == b.flags.f_contiguous
assert a.flags.writeable == b.flags.writeable
assert a.flags.aligned == b.flags.aligned
- assert a.flags.updateifcopy == b.flags.updateifcopy
+ if LooseVersion(np.__version__) >= LooseVersion("1.14.0"):
+ assert a.flags.writebackifcopy == b.flags.writebackifcopy
+ else:
+ assert a.flags.updateifcopy == b.flags.updateifcopy
assert np.all(a == b)
assert not b.flags.owndata
assert b.base is base
@@ -282,17 +286,17 @@
1. (arg0: numpy.ndarray[int32]) -> str
2. (arg0: numpy.ndarray[float64]) -> str
- Invoked with:"""
+ Invoked with: """
with pytest.raises(TypeError) as excinfo:
m.overloaded3(np.array([1], dtype='uintc'))
- assert msg(excinfo.value) == expected_exc + " array([1], dtype=uint32)"
+ assert msg(excinfo.value) == expected_exc + repr(np.array([1], dtype='uint32'))
with pytest.raises(TypeError) as excinfo:
m.overloaded3(np.array([1], dtype='float32'))
- assert msg(excinfo.value) == expected_exc + " array([ 1.], dtype=float32)"
+ assert msg(excinfo.value) == expected_exc + repr(np.array([1.], dtype='float32'))
with pytest.raises(TypeError) as excinfo:
m.overloaded3(np.array([1], dtype='complex'))
- assert msg(excinfo.value) == expected_exc + " array([ 1.+0.j])"
+ assert msg(excinfo.value) == expected_exc + repr(np.array([1. + 0.j]))
# Exact matches:
assert m.overloaded4(np.array([1], dtype='double')) == 'double'