67 lines
1.8 KiB
Python
67 lines
1.8 KiB
Python
|
"""Test how the ufuncs in special handle nan inputs.
|
||
|
|
|
||
|
|
"""
|
||
|
|
from __future__ import division, print_function, absolute_import
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
from numpy.testing import assert_array_equal, assert_
|
||
|
|
import pytest
|
||
|
|
|
||
|
|
import scipy.special as sc
|
||
|
|
from scipy._lib._numpy_compat import suppress_warnings
|
||
|
|
|
||
|
|
|
||
|
|
KNOWNFAILURES = {}
|
||
|
|
|
||
|
|
POSTPROCESSING = {
|
||
|
|
sc.hyp2f0: lambda x, y: x # Second argument is an error estimate
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
def _get_ufuncs():
|
||
|
|
ufuncs = []
|
||
|
|
ufunc_names = []
|
||
|
|
for name in sorted(sc.__dict__):
|
||
|
|
obj = sc.__dict__[name]
|
||
|
|
if not isinstance(obj, np.ufunc):
|
||
|
|
continue
|
||
|
|
msg = KNOWNFAILURES.get(obj)
|
||
|
|
if msg is None:
|
||
|
|
ufuncs.append(obj)
|
||
|
|
ufunc_names.append(name)
|
||
|
|
else:
|
||
|
|
fail = pytest.mark.xfail(run=False, reason=msg)
|
||
|
|
ufuncs.append(pytest.param(obj, marks=fail))
|
||
|
|
ufunc_names.append(name)
|
||
|
|
return ufuncs, ufunc_names
|
||
|
|
|
||
|
|
|
||
|
|
UFUNCS, UFUNC_NAMES = _get_ufuncs()
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("func", UFUNCS, ids=UFUNC_NAMES)
|
||
|
|
def test_nan_inputs(func):
|
||
|
|
args = (np.nan,)*func.nin
|
||
|
|
with suppress_warnings() as sup:
|
||
|
|
# Ignore warnings about unsafe casts from legacy wrappers
|
||
|
|
sup.filter(RuntimeWarning,
|
||
|
|
"floating point number truncated to an integer")
|
||
|
|
try:
|
||
|
|
res = func(*args)
|
||
|
|
except TypeError:
|
||
|
|
# One of the arguments doesn't take real inputs
|
||
|
|
return
|
||
|
|
if func in POSTPROCESSING:
|
||
|
|
res = POSTPROCESSING[func](*res)
|
||
|
|
|
||
|
|
msg = "got {} instead of nan".format(res)
|
||
|
|
assert_array_equal(np.isnan(res), True, err_msg=msg)
|
||
|
|
|
||
|
|
|
||
|
|
def test_legacy_cast():
|
||
|
|
with suppress_warnings() as sup:
|
||
|
|
sup.filter(RuntimeWarning,
|
||
|
|
"floating point number truncated to an integer")
|
||
|
|
res = sc.bdtrc(np.nan, 1, 0.5)
|
||
|
|
assert_(np.isnan(res))
|