from __future__ import division, absolute_import, print_function from .info import __doc__ from numpy.version import version as __version__ # disables OpenBLAS affinity setting of the main thread that limits # python threads or processes to one core import os env_added = [] for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: if envkey not in os.environ: os.environ[envkey] = '1' env_added.append(envkey) try: from . import multiarray except ImportError as exc: import sys msg = """ IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! Importing the multiarray numpy extension module failed. Most likely you are trying to import a failed build of numpy. Here is how to proceed: - If you're working with a numpy git repository, try `git clean -xdf` (removes all files not under version control) and rebuild numpy. - If you are simply trying to use the numpy version that you have installed: your installation is broken - please reinstall numpy. - If you have already reinstalled and that did not fix the problem, then: 1. Check that you are using the Python you expect (you're using %s), and that you have no directories in your PATH or PYTHONPATH that can interfere with the Python and numpy versions you're trying to use. 2. If (1) looks fine, you can open a new issue at https://github.com/numpy/numpy/issues. Please include details on: - how you installed Python - how you installed numpy - your operating system - whether or not you have multiple versions of Python installed - if you built from source, your compiler versions and ideally a build log Note: this error has many possible causes, so please don't comment on an existing issue about this - open a new one instead. Original error was: %s """ % (sys.executable, exc) raise ImportError(msg) finally: for envkey in env_added: del os.environ[envkey] del envkey del env_added del os from . import umath from . import _internal # for freeze programs from . import numerictypes as nt multiarray.set_typeDict(nt.sctypeDict) from . import numeric from .numeric import * from . import fromnumeric from .fromnumeric import * from . import defchararray as char from . import records as rec from .records import * from .memmap import * from .defchararray import chararray from . import function_base from .function_base import * from . import machar from .machar import * from . import getlimits from .getlimits import * from . import shape_base from .shape_base import * from . import einsumfunc from .einsumfunc import * del nt from .fromnumeric import amax as max, amin as min, round_ as round from .numeric import absolute as abs # do this after everything else, to minimize the chance of this misleadingly # appearing in an import-time traceback from . import _add_newdocs __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__ # 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) def _ufunc_reduce(func): from pickle import whichmodule name = func.__name__ return _ufunc_reconstruct, (whichmodule(func, name), name) import sys if sys.version_info[0] >= 3: import copyreg else: import copy_reg as copyreg copyreg.pickle(ufunc, _ufunc_reduce, _ufunc_reconstruct) # Unclutter namespace (must keep _ufunc_reconstruct for unpickling) del copyreg del sys del _ufunc_reduce from numpy._pytesttester import PytestTester test = PytestTester(__name__) del PytestTester