[SciPy-Dev] Why does forcing Numpy to compile with "sizeof(long double) == 8" fails tests?

[Gustavo Serra Scalet]

Hi,

I'm checking how Numpy performs on a POWER8 machine and I noticed that some tests related to machar.py are failing:
======================================================================
ERROR: test_singleton (test_getlimits.TestLongdouble)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/gut/python/venv3.5-b/lib/python3.4/site-packages/numpy-1.12.0.dev0+33d850d-py3.4-linux-ppc64le.egg/numpy/core/tests/test_getlimits.py", line 41, in test_singleton
    ftype = finfo(longdouble)
  File "/home/gut/python/venv3.5-b/lib/python3.4/site-packages/numpy-1.12.0.dev0+33d850d-py3.4-linux-ppc64le.egg/numpy/core/getlimits.py", line 124, in __new__
    obj = object.__new__(cls)._init(dtype)
  File "/home/gut/python/venv3.5-b/lib/python3.4/site-packages/numpy-1.12.0.dev0+33d850d-py3.4-linux-ppc64le.egg/numpy/core/getlimits.py", line 154, in _init
    'numpy %s precision floating point number' % precname)
  File "/home/gut/python/venv3.5-b/lib/python3.4/site-packages/numpy-1.12.0.dev0+33d850d-py3.4-linux-ppc64le.egg/numpy/core/machar.py", line 114, in __init__
    self._do_init(float_conv, int_conv, float_to_float, float_to_str, title)
  File "/home/gut/python/venv3.5-b/lib/python3.4/site-packages/numpy-1.12.0.dev0+33d850d-py3.4-linux-ppc64le.egg/numpy/core/machar.py", line 127, in _do_init
    a = a + a
RuntimeWarning: overflow encountered in add 

FAILED (KNOWNFAIL=4, SKIP=10, errors=4)


That happened because native long double actually uses 2 doubles[1] (that method is called IBM Extended double[2]).

To avoid that, I changed the compile flags to use -mlong-double-64 [3] and despite solving those errors, now I have some of these failures:
======================================================================
FAIL: test_in_from_2casttype (test_array_from_pyobj.test_LONGDOUBLE_gen)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/gut/python/venv3.5/lib/python3.4/site-packages/numpy-1.12.0.dev0+7a962d1-py3.4-linux-ppc64le.egg/numpy/f2py/tests/test_array_from_pyobj.py", line 319, in test_in_from_2casttype
    a = self.array([len(self.num2seq)], intent.in_, obj)
  File "<string>", line 6, in <lambda>
  File "/home/gut/python/venv3.5/lib/python3.4/site-packages/numpy-1.12.0.dev0+7a962d1-py3.4-linux-ppc64le.egg/numpy/f2py/tests/test_array_from_pyobj.py", line 275, in __init__
    assert_(self.has_shared_memory())
  File "/home/gut/python/venv3.5/lib/python3.4/site-packages/numpy-1.12.0.dev0+7a962d1-py3.4-linux-ppc64le.egg/numpy/testing/utils.py", line 90, in assert_
    raise AssertionError(smsg)
AssertionError

FAILED (KNOWNFAIL=6, SKIP=16, failures=3)


I wanted to know if there is a better approach to solve this issue. I guess it supports 'long double == double', right?

Thanks in advance!


Environment:
Repository head at 33d850d522b3a1940c3ad06b63c79a466def11e9 (from git://github.com/numpy/numpy.git) + patch on [3]
Python-3.5.2 


[1] https://github.com/gcc-mirror/gcc/blob/3ff1ad36ed4ee3cc490e6178db87b1b8f2326c61/libgcc/config/rs6000/ibm-ldouble.c#L36-L43
[2] https://gcc.gnu.org/wiki/Ieee128PowerPC
[3] https://github.com/PPC64/numpy/commit/be15f1073802ab127162c5dcdd995de7f6452c78