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