from __future__ import division, absolute_import, print_function # To get sub-classes from .info import __doc__ from .fftpack import * from .helper import * from numpy.testing import _numpy_tester test = _numpy_tester().test bench = _numpy_tester().bench
from .numeric import absolute as abs
__all__ = ['char', 'rec', 'memmap']
__all__ += numeric.__all__
__all__ += fromnumeric.__all__
__all__ += rec.__all__
__all__ += ['chararray']
__all__ += function_base.__all__
__all__ += machar.__all__
__all__ += getlimits.__all__
__all__ += shape_base.__all__
__all__ += einsumfunc.__all__
from numpy.testing import _numpy_tester
test = _numpy_tester().test
# Make it possible so that ufuncs can be pickled
# Here are the loading and unloading functions
# The name numpy.core._ufunc_reconstruct must be
# available for unpickling to work.
def _ufunc_reconstruct(module, name):
# The `fromlist` kwarg is required to ensure that `mod` points to the
# inner-most module rather than the parent package when module name is
# nested. This makes it possible to pickle non-toplevel ufuncs such as
# scipy.special.expit for instance.
mod = __import__(module, fromlist=[name])
return getattr(mod, name)
The extension tells which fortran standard is used.
The default is `.f`, which implies F77 standard.
.. versionadded:: 1.11.0
"""
from numpy.distutils.exec_command import exec_command
import tempfile
if source_fn is None:
f = tempfile.NamedTemporaryFile(suffix=extension)
else:
f = open(source_fn, 'w')
try:
f.write(source)
f.flush()
args = ' -c -m {} {} {}'.format(modulename, f.name, extra_args)
c = '{} -c "import numpy.f2py as f2py2e;f2py2e.main()" {}'
c = c.format(sys.executable, args)
status, output = exec_command(c)
if verbose:
print(output)
finally:
f.close()
return status
from numpy.testing import _numpy_tester
test = _numpy_tester().test
bench = _numpy_tester().bench
