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/opt/imh-python/lib/python3.9/site-packages/numpy/core/

/opt/imh-python/lib/python3.9/site-packages/numpy/core

Name	Size	Mode	Actions
include/	-	0755	rm
lib/	-	0755	rm
tests/	-	0755	rm
__pycache__/	-	0755	rm
arrayprint.py	63608	0644	edit dl rm
arrayprint.pyi	4428	0644	edit dl rm
cversions.py	347	0644	edit dl rm
defchararray.py	73617	0644	edit dl rm
defchararray.pyi	9216	0644	edit dl rm
einsumfunc.py	51868	0644	edit dl rm
einsumfunc.pyi	4860	0644	edit dl rm
fromnumeric.py	128821	0644	edit dl rm
fromnumeric.pyi	23726	0644	edit dl rm
function_base.py	19836	0644	edit dl rm
function_base.pyi	4725	0644	edit dl rm
getlimits.py	25865	0644	edit dl rm
getlimits.pyi	82	0644	edit dl rm
memmap.py	11771	0644	edit dl rm
memmap.pyi	55	0644	edit dl rm
multiarray.py	56097	0644	edit dl rm
multiarray.pyi	24768	0644	edit dl rm
numeric.py	77014	0644	edit dl rm
numeric.pyi	14315	0644	edit dl rm
numerictypes.py	18098	0644	edit dl rm
numerictypes.pyi	3267	0644	edit dl rm
overrides.py	7093	0644	edit dl rm
records.py	37533	0644	edit dl rm
records.pyi	5692	0644	edit dl rm
shape_base.py	29743	0644	edit dl rm
shape_base.pyi	2774	0644	edit dl rm
umath.py	2040	0644	edit dl rm
umath_tests.py	389	0644	edit dl rm
_add_newdocs.py	208972	0644	edit dl rm
_add_newdocs_scalars.py	12106	0644	edit dl rm
_asarray.py	3884	0644	edit dl rm
_asarray.pyi	1086	0644	edit dl rm
_dtype.py	10606	0644	edit dl rm
_dtype_ctypes.py	3673	0644	edit dl rm
_exceptions.py	5379	0644	edit dl rm
_internal.py	28348	0644	edit dl rm
_internal.pyi	1032	0644	edit dl rm
_machar.py	11565	0644	edit dl rm
_methods.py	8613	0644	edit dl rm
_multiarray_tests.cpython-39-x86_64-linux-gnu.so	151008	0755	edit dl rm
_multiarray_umath.cpython-39-x86_64-linux-gnu.so	7382112	0755	edit dl rm
_operand_flag_tests.cpython-39-x86_64-linux-gnu.so	16728	0755	edit dl rm
_rational_tests.cpython-39-x86_64-linux-gnu.so	59640	0755	edit dl rm
_simd.cpython-39-x86_64-linux-gnu.so	3526664	0755	edit dl rm
_string_helpers.py	2852	0644	edit dl rm
_struct_ufunc_tests.cpython-39-x86_64-linux-gnu.so	16832	0755	edit dl rm
_type_aliases.py	7534	0644	edit dl rm
_type_aliases.pyi	404	0644	edit dl rm
_ufunc_config.py	13944	0644	edit dl rm
_ufunc_config.pyi	1066	0644	edit dl rm
_umath_tests.cpython-39-x86_64-linux-gnu.so	42008	0755	edit dl rm
__init__.py	5780	0644	edit dl rm
__init__.pyi	126	0644	edit dl rm

Edit: /opt/imh-python/lib/python3.9/site-packages/numpy/core/__init__.py (5780B)

"""
Contains the core of NumPy: ndarray, ufuncs, dtypes, etc.

Please note that this module is private.  All functions and objects
are available in the main ``numpy`` namespace - use that instead.

"""

import os
import warnings

from numpy.version import version as __version__

# disables OpenBLAS affinity setting of the main thread that limits
# python threads or processes to one core
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 numpy C-extensions failed. This error can happen for
many reasons, often due to issues with your setup or how NumPy was
installed.

We have compiled some common reasons and troubleshooting tips at:

https://numpy.org/devdocs/user/troubleshooting-importerror.html

Please note and check the following:

* The Python version is: Python%d.%d from "%s"
  * The NumPy version is: "%s"

and make sure that they are the versions you expect.
Please carefully study the documentation linked above for further help.

Original error was: %s
""" % (sys.version_info[0], sys.version_info[1], sys.executable,
        __version__, exc)
    raise ImportError(msg)
finally:
    for envkey in env_added:
        del os.environ[envkey]
del envkey
del env_added
del os

from . import umath

# Check that multiarray,umath are pure python modules wrapping
# _multiarray_umath and not either of the old c-extension modules
if not (hasattr(multiarray, '_multiarray_umath') and
        hasattr(umath, '_multiarray_umath')):
    import sys
    path = sys.modules['numpy'].__path__
    msg = ("Something is wrong with the numpy installation. "
        "While importing we detected an older version of "
        "numpy in {}. One method of fixing this is to repeatedly uninstall "
        "numpy until none is found, then reinstall this version.")
    raise ImportError(msg.format(path))

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
from . import records as rec
from .records import record, recarray, format_parser
# Note: module name memmap is overwritten by a class with same name
from .memmap import *
from .defchararray import chararray
from . import function_base
from .function_base import *
from . import _machar
from . import getlimits
from .getlimits import *
from . import shape_base
from .shape_base import *
from . import einsumfunc
from .einsumfunc import *
del nt

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
from . import _add_newdocs_scalars
# add these for module-freeze analysis (like PyInstaller)
from . import _dtype_ctypes
from . import _internal
from . import _dtype
from . import _methods

__all__ = ['char', 'rec', 'memmap']
__all__ += numeric.__all__
__all__ += ['record', 'recarray', 'format_parser']
__all__ += ['chararray']
__all__ += function_base.__all__
__all__ += getlimits.__all__
__all__ += shape_base.__all__
__all__ += einsumfunc.__all__

# We used to use `np.core._ufunc_reconstruct` to unpickle. This is unnecessary,
# but old pickles saved before 1.20 will be using it, and there is no reason
# to break loading them.
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):
    # Report the `__name__`. pickle will try to find the module. Note that
    # pickle supports for this `__name__` to be a `__qualname__`. It may
    # make sense to add a `__qualname__` to ufuncs, to allow this more
    # explicitly (Numba has ufuncs as attributes).
    # See also: https://github.com/dask/distributed/issues/3450
    return func.__name__

def _DType_reconstruct(scalar_type):
    # This is a work-around to pickle type(np.dtype(np.float64)), etc.
    # and it should eventually be replaced with a better solution, e.g. when
    # DTypes become HeapTypes.
    return type(dtype(scalar_type))

def _DType_reduce(DType):
    # As types/classes, most DTypes can simply be pickled by their name:
    if not DType._legacy or DType.__module__ == "numpy.dtypes":
        return DType.__name__

# However, user defined legacy dtypes (like rational) do not end up in
    # `numpy.dtypes` as module and do not have a public class at all.
    # For these, we pickle them by reconstructing them from the scalar type:
    scalar_type = DType.type
    return _DType_reconstruct, (scalar_type,)

def __getattr__(name):
    # Deprecated 2022-11-22, NumPy 1.25.
    if name == "MachAr":
        warnings.warn(
            "The `np.core.MachAr` is considered private API (NumPy 1.24)",
            DeprecationWarning, stacklevel=2,
        )
        return _machar.MachAr
    raise AttributeError(f"Module {__name__!r} has no attribute {name!r}")

import copyreg

copyreg.pickle(ufunc, _ufunc_reduce)
copyreg.pickle(type(dtype), _DType_reduce, _DType_reconstruct)

# Unclutter namespace (must keep _*_reconstruct for unpickling)
del copyreg
del _ufunc_reduce
del _DType_reduce

from numpy._pytesttester import PytestTester
test = PytestTester(__name__)
del PytestTester

cmd: