AR_LIKE_c: List[complex]
AR_LIKE_U: List[str]

OUT_f: np.ndarray[Any, np.dtype[np.float64]]

reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_b))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_u, AR_LIKE_u))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_i, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f))  # E: Any

            

Reported by Pylint.

              
OUT_f: np.ndarray[Any, np.dtype[np.float64]]

reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_b))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_u, AR_LIKE_u))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_i, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i))  # E: Any

            

Reported by Pylint.

              OUT_f: np.ndarray[Any, np.dtype[np.float64]]

reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_b))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_u, AR_LIKE_u))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_i, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c))  # E: Any

            

Reported by Pylint.

              
reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_b))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_u, AR_LIKE_u))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_i, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c))  # E: Any


            

Reported by Pylint.

              reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_b))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_u, AR_LIKE_u))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_i, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c))  # E: Any

reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c, out=OUT_f))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]

            

Reported by Pylint.

              reveal_type(np.einsum("i,i->i", AR_LIKE_u, AR_LIKE_u))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_i, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c))  # E: Any

reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c, out=OUT_f))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]
reveal_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe", out=OUT_f))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]

            

Reported by Pylint.

              reveal_type(np.einsum("i,i->i", AR_LIKE_i, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c))  # E: Any

reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c, out=OUT_f))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]
reveal_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe", out=OUT_f))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]
reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f, dtype="c16"))  # E: Any

            

Reported by Pylint.

              reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c))  # E: Any

reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c, out=OUT_f))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]
reveal_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe", out=OUT_f))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]
reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f, dtype="c16"))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe"))  # E: Any

            

Reported by Pylint.

              reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i))  # E: Any
reveal_type(np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c))  # E: Any

reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c, out=OUT_f))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]
reveal_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe", out=OUT_f))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]
reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f, dtype="c16"))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe"))  # E: Any

reveal_type(np.einsum_path("i,i->i", AR_LIKE_b, AR_LIKE_b))  # E: Tuple[builtins.list[Any], builtins.str]

            

Reported by Pylint.

              reveal_type(np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c))  # E: Any

reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c, out=OUT_f))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]
reveal_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe", out=OUT_f))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]
reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f, dtype="c16"))  # E: Any
reveal_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe"))  # E: Any

reveal_type(np.einsum_path("i,i->i", AR_LIKE_b, AR_LIKE_b))  # E: Tuple[builtins.list[Any], builtins.str]
reveal_type(np.einsum_path("i,i->i", AR_LIKE_u, AR_LIKE_u))  # E: Tuple[builtins.list[Any], builtins.str]

            

Reported by Pylint.

                  import numpy as np
    import numpy._globals

    _NoValue = np._NoValue
    VisibleDeprecationWarning = np.VisibleDeprecationWarning
    ModuleDeprecationWarning = np.ModuleDeprecationWarning

    with assert_warns(UserWarning):
        reload(np)

            

Reported by Pylint.

              
    with assert_warns(UserWarning):
        reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    with assert_warns(UserWarning):

            

Reported by Pylint.

              
    with assert_warns(UserWarning):
        reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    with assert_warns(UserWarning):

            

Reported by Pylint.

                  with assert_warns(UserWarning):
        reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    with assert_warns(UserWarning):
        reload(np)

            

Reported by Pylint.

                      reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    with assert_warns(UserWarning):
        reload(np)
    assert_(_NoValue is np._NoValue)

            

Reported by Pylint.

                  assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    with assert_warns(UserWarning):
        reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

            

Reported by Pylint.

                  assert_raises(RuntimeError, reload, numpy._globals)
    with assert_warns(UserWarning):
        reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

def test_novalue():
    import numpy as np

            

Reported by Pylint.

                  assert_raises(RuntimeError, reload, numpy._globals)
    with assert_warns(UserWarning):
        reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

def test_novalue():
    import numpy as np

            

Reported by Pylint.

                  with assert_warns(UserWarning):
        reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

def test_novalue():
    import numpy as np
    for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):

            

Reported by Pylint.

                      reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

def test_novalue():
    import numpy as np
    for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
        assert_equal(repr(np._NoValue), '<no value>')

            

Reported by Pylint.

              

def test_main_versions():
    assert_(NumpyVersion('1.8.0') == '1.8.0')
    for ver in ['1.9.0', '2.0.0', '1.8.1', '10.0.1']:
        assert_(NumpyVersion('1.8.0') < ver)

    for ver in ['1.7.0', '1.7.1', '0.9.9']:
        assert_(NumpyVersion('1.8.0') > ver)

            

Reported by Pylint.

              def test_main_versions():
    assert_(NumpyVersion('1.8.0') == '1.8.0')
    for ver in ['1.9.0', '2.0.0', '1.8.1', '10.0.1']:
        assert_(NumpyVersion('1.8.0') < ver)

    for ver in ['1.7.0', '1.7.1', '0.9.9']:
        assert_(NumpyVersion('1.8.0') > ver)



            

Reported by Pylint.

                      assert_(NumpyVersion('1.8.0') < ver)

    for ver in ['1.7.0', '1.7.1', '0.9.9']:
        assert_(NumpyVersion('1.8.0') > ver)


def test_version_1_point_10():
    # regression test for gh-2998.
    assert_(NumpyVersion('1.9.0') < '1.10.0')

            

Reported by Pylint.

              
def test_version_1_point_10():
    # regression test for gh-2998.
    assert_(NumpyVersion('1.9.0') < '1.10.0')
    assert_(NumpyVersion('1.11.0') < '1.11.1')
    assert_(NumpyVersion('1.11.0') == '1.11.0')
    assert_(NumpyVersion('1.99.11') < '1.99.12')



            

Reported by Pylint.

              def test_version_1_point_10():
    # regression test for gh-2998.
    assert_(NumpyVersion('1.9.0') < '1.10.0')
    assert_(NumpyVersion('1.11.0') < '1.11.1')
    assert_(NumpyVersion('1.11.0') == '1.11.0')
    assert_(NumpyVersion('1.99.11') < '1.99.12')


def test_alpha_beta_rc():

            

Reported by Pylint.

                  # regression test for gh-2998.
    assert_(NumpyVersion('1.9.0') < '1.10.0')
    assert_(NumpyVersion('1.11.0') < '1.11.1')
    assert_(NumpyVersion('1.11.0') == '1.11.0')
    assert_(NumpyVersion('1.99.11') < '1.99.12')


def test_alpha_beta_rc():
    assert_(NumpyVersion('1.8.0rc1') == '1.8.0rc1')

            

Reported by Pylint.

                  assert_(NumpyVersion('1.9.0') < '1.10.0')
    assert_(NumpyVersion('1.11.0') < '1.11.1')
    assert_(NumpyVersion('1.11.0') == '1.11.0')
    assert_(NumpyVersion('1.99.11') < '1.99.12')


def test_alpha_beta_rc():
    assert_(NumpyVersion('1.8.0rc1') == '1.8.0rc1')
    for ver in ['1.8.0', '1.8.0rc2']:

            

Reported by Pylint.

              

def test_alpha_beta_rc():
    assert_(NumpyVersion('1.8.0rc1') == '1.8.0rc1')
    for ver in ['1.8.0', '1.8.0rc2']:
        assert_(NumpyVersion('1.8.0rc1') < ver)

    for ver in ['1.8.0a2', '1.8.0b3', '1.7.2rc4']:
        assert_(NumpyVersion('1.8.0rc1') > ver)

            

Reported by Pylint.

              def test_alpha_beta_rc():
    assert_(NumpyVersion('1.8.0rc1') == '1.8.0rc1')
    for ver in ['1.8.0', '1.8.0rc2']:
        assert_(NumpyVersion('1.8.0rc1') < ver)

    for ver in ['1.8.0a2', '1.8.0b3', '1.7.2rc4']:
        assert_(NumpyVersion('1.8.0rc1') > ver)

    assert_(NumpyVersion('1.8.0b1') > '1.8.0a2')

            

Reported by Pylint.

                      assert_(NumpyVersion('1.8.0rc1') < ver)

    for ver in ['1.8.0a2', '1.8.0b3', '1.7.2rc4']:
        assert_(NumpyVersion('1.8.0rc1') > ver)

    assert_(NumpyVersion('1.8.0b1') > '1.8.0a2')


def test_dev_version():

            

Reported by Pylint.

              
def run_command(cmd):
    print('Running %r:' % (cmd))
    os.system(cmd)
    print('------')


def run():
    _path = os.getcwd()

            

Reported by Bandit.

                      try:
            if has_numpy_distutils == 2:
                print('Found numpy.distutils version %r in %r' % (
                    numpy.distutils.__version__,
                    numpy.distutils.__file__))
            else:
                print('Found numpy_distutils version %r in %r' % (
                    numpy_distutils.numpy_distutils_version.numpy_distutils_version,
                    numpy_distutils.__file__))

            

Reported by Pylint.

                          if has_numpy_distutils == 1:
                print(
                    'Importing numpy_distutils.command.build_flib ...', end=' ')
                import numpy_distutils.command.build_flib as build_flib
                print('ok')
                print('------')
                try:
                    print(
                        'Checking availability of supported Fortran compilers:')

            

Reported by Pylint.

                              import numpy.distutils.fcompiler as fcompiler
            else:
                print('Importing numpy_distutils.fcompiler ...', end=' ')
                import numpy_distutils.fcompiler as fcompiler
            print('ok')
            print('------')
            try:
                print('Checking availability of supported Fortran compilers:')
                fcompiler.show_fcompilers()

            

Reported by Pylint.

                      try:
            print('Found new numpy version %r in %s' %
                  (numpy.__version__, numpy.__file__))
        except Exception as msg:
            print('error:', msg)
            print('------')

    if has_f2py2e:
        try:

            

Reported by Pylint.

                      try:
            print('Found f2py2e version %r in %s' %
                  (f2py2e.__version__.version, f2py2e.__file__))
        except Exception as msg:
            print('error:', msg)
            print('------')

    if has_numpy_distutils:
        try:

            

Reported by Pylint.

                                  numpy_distutils.numpy_distutils_version.numpy_distutils_version,
                    numpy_distutils.__file__))
            print('------')
        except Exception as msg:
            print('error:', msg)
            print('------')
        try:
            if has_numpy_distutils == 1:
                print(

            

Reported by Pylint.

                                  for compiler_class in build_flib.all_compilers:
                        compiler_class(verbose=1).is_available()
                        print('------')
                except Exception as msg:
                    print('error:', msg)
                    print('------')
        except Exception as msg:
            print(
                'error:', msg, '(ignore it, build_flib is obsolute for numpy.distutils 0.2.2 and up)')

            

Reported by Pylint.

                              except Exception as msg:
                    print('error:', msg)
                    print('------')
        except Exception as msg:
            print(
                'error:', msg, '(ignore it, build_flib is obsolute for numpy.distutils 0.2.2 and up)')
            print('------')
        try:
            if has_numpy_distutils == 2:

            

Reported by Pylint.

                              print('Checking availability of supported Fortran compilers:')
                fcompiler.show_fcompilers()
                print('------')
            except Exception as msg:
                print('error:', msg)
                print('------')
        except Exception as msg:
            print('error:', msg)
            print('------')

            

Reported by Pylint.

              
import warnings

from .machar import MachAr
from .overrides import set_module
from . import numeric
from . import numerictypes as ntypes
from .numeric import array, inf, NaN
from .umath import log10, exp2, nextafter, isnan

            

Reported by Pylint.

              import warnings

from .machar import MachAr
from .overrides import set_module
from . import numeric
from . import numerictypes as ntypes
from .numeric import array, inf, NaN
from .umath import log10, exp2, nextafter, isnan
from . import umath

            

Reported by Pylint.

              
from .machar import MachAr
from .overrides import set_module
from . import numeric
from . import numerictypes as ntypes
from .numeric import array, inf, NaN
from .umath import log10, exp2, nextafter, isnan
from . import umath


            

Reported by Pylint.

              from .machar import MachAr
from .overrides import set_module
from . import numeric
from . import numerictypes as ntypes
from .numeric import array, inf, NaN
from .umath import log10, exp2, nextafter, isnan
from . import umath



            

Reported by Pylint.

              from .overrides import set_module
from . import numeric
from . import numerictypes as ntypes
from .numeric import array, inf, NaN
from .umath import log10, exp2, nextafter, isnan
from . import umath


def _fr0(a):

            

Reported by Pylint.

              from . import numeric
from . import numerictypes as ntypes
from .numeric import array, inf, NaN
from .umath import log10, exp2, nextafter, isnan
from . import umath


def _fr0(a):
    """fix rank-0 --> rank-1"""

            

Reported by Pylint.

              from . import numerictypes as ntypes
from .numeric import array, inf, NaN
from .umath import log10, exp2, nextafter, isnan
from . import umath


def _fr0(a):
    """fix rank-0 --> rank-1"""
    if a.ndim == 0:

            

Reported by Pylint.

              from . import numerictypes as ntypes
from .numeric import array, inf, NaN
from .umath import log10, exp2, nextafter, isnan
from . import umath


def _fr0(a):
    """fix rank-0 --> rank-1"""
    if a.ndim == 0:

            

Reported by Pylint.

                      self.nexp = machar.iexp
        self.nmant = machar.it
        self.machar = machar
        self._str_tiny = machar._str_xmin.strip()
        self._str_max = machar._str_xmax.strip()
        self._str_epsneg = machar._str_epsneg.strip()
        self._str_eps = machar._str_eps.strip()
        self._str_resolution = machar._str_resolution.strip()
        self._str_smallest_normal = machar._str_smallest_normal.strip()

            

Reported by Pylint.

                      self.nmant = machar.it
        self.machar = machar
        self._str_tiny = machar._str_xmin.strip()
        self._str_max = machar._str_xmax.strip()
        self._str_epsneg = machar._str_epsneg.strip()
        self._str_eps = machar._str_eps.strip()
        self._str_resolution = machar._str_resolution.strip()
        self._str_smallest_normal = machar._str_smallest_normal.strip()
        self._str_smallest_subnormal = machar._str_smallest_subnormal.strip()

            

Reported by Pylint.

              # add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#
import os
# import sys
# sys.path.insert(0, os.path.abspath('.'))


# -- General configuration ------------------------------------------------

            

Reported by Pylint.

              
# General information about the project.
project = u'NumPy Enhancement Proposals'
copyright = u'2017-2018, NumPy Developers'
author = u'NumPy Developers'

# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.

            

Reported by Pylint.

              # -*- coding: utf-8 -*-
#
# NumPy Enhancement Proposals documentation build configuration file, created by
# sphinx-quickstart on Mon Dec 11 12:45:09 2017.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this

            

Reported by Pylint.

              # You can specify multiple suffix as a list of string:
#
# source_suffix = ['.rst', '.md']
source_suffix = '.rst'

# The master toctree document.
master_doc = 'content'

# General information about the project.

            

Reported by Pylint.

              source_suffix = '.rst'

# The master toctree document.
master_doc = 'content'

# General information about the project.
project = u'NumPy Enhancement Proposals'
copyright = u'2017-2018, NumPy Developers'
author = u'NumPy Developers'

            

Reported by Pylint.

              master_doc = 'content'

# General information about the project.
project = u'NumPy Enhancement Proposals'
copyright = u'2017-2018, NumPy Developers'
author = u'NumPy Developers'

# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the

            

Reported by Pylint.

              
# General information about the project.
project = u'NumPy Enhancement Proposals'
copyright = u'2017-2018, NumPy Developers'
author = u'NumPy Developers'

# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.

            

Reported by Pylint.

              # General information about the project.
project = u'NumPy Enhancement Proposals'
copyright = u'2017-2018, NumPy Developers'
author = u'NumPy Developers'

# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#

            

Reported by Pylint.

              # built documents.
#
# The short X.Y version.
version = u''
# The full version, including alpha/beta/rc tags.
release = u''

# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.

            

Reported by Pylint.

              # The short X.Y version.
version = u''
# The full version, including alpha/beta/rc tags.
release = u''

# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#
# This is also used if you do content translation via gettext catalogs.

            

Reported by Pylint.

              import numpy as np
import numpy.typing as npt

nd: npt.NDArray[np.int_] = np.array([[1, 2], [3, 4]])

# item
reveal_type(nd.item())  # E: int
reveal_type(nd.item(1))  # E: int
reveal_type(nd.item(0, 1))  # E: int

            

Reported by Pylint.

              nd: npt.NDArray[np.int_] = np.array([[1, 2], [3, 4]])

# item
reveal_type(nd.item())  # E: int
reveal_type(nd.item(1))  # E: int
reveal_type(nd.item(0, 1))  # E: int
reveal_type(nd.item((0, 1)))  # E: int

# tolist

            

Reported by Pylint.

              
# item
reveal_type(nd.item())  # E: int
reveal_type(nd.item(1))  # E: int
reveal_type(nd.item(0, 1))  # E: int
reveal_type(nd.item((0, 1)))  # E: int

# tolist
reveal_type(nd.tolist())  # E: Any

            

Reported by Pylint.

              # item
reveal_type(nd.item())  # E: int
reveal_type(nd.item(1))  # E: int
reveal_type(nd.item(0, 1))  # E: int
reveal_type(nd.item((0, 1)))  # E: int

# tolist
reveal_type(nd.tolist())  # E: Any


            

Reported by Pylint.

              reveal_type(nd.item())  # E: int
reveal_type(nd.item(1))  # E: int
reveal_type(nd.item(0, 1))  # E: int
reveal_type(nd.item((0, 1)))  # E: int

# tolist
reveal_type(nd.tolist())  # E: Any

# itemset does not return a value

            

Reported by Pylint.

              reveal_type(nd.item((0, 1)))  # E: int

# tolist
reveal_type(nd.tolist())  # E: Any

# itemset does not return a value
# tostring is pretty simple
# tobytes is pretty simple
# tofile does not return a value

            

Reported by Pylint.

              # dumps is pretty simple

# astype
reveal_type(nd.astype("float"))  # E: numpy.ndarray[Any, numpy.dtype[Any]]
reveal_type(nd.astype(float))  # E: numpy.ndarray[Any, numpy.dtype[Any]]
reveal_type(nd.astype(np.float64))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K"))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K", "unsafe"))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K", "unsafe", True))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]

            

Reported by Pylint.

              
# astype
reveal_type(nd.astype("float"))  # E: numpy.ndarray[Any, numpy.dtype[Any]]
reveal_type(nd.astype(float))  # E: numpy.ndarray[Any, numpy.dtype[Any]]
reveal_type(nd.astype(np.float64))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K"))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K", "unsafe"))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K", "unsafe", True))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K", "unsafe", True, True))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]

            

Reported by Pylint.

              # astype
reveal_type(nd.astype("float"))  # E: numpy.ndarray[Any, numpy.dtype[Any]]
reveal_type(nd.astype(float))  # E: numpy.ndarray[Any, numpy.dtype[Any]]
reveal_type(nd.astype(np.float64))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K"))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K", "unsafe"))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K", "unsafe", True))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K", "unsafe", True, True))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]


            

Reported by Pylint.

              reveal_type(nd.astype("float"))  # E: numpy.ndarray[Any, numpy.dtype[Any]]
reveal_type(nd.astype(float))  # E: numpy.ndarray[Any, numpy.dtype[Any]]
reveal_type(nd.astype(np.float64))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K"))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K", "unsafe"))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K", "unsafe", True))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]
reveal_type(nd.astype(np.float64, "K", "unsafe", True, True))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]

# byteswap

            

Reported by Pylint.

              import os
from os import path
import sys
import pytest
from ctypes import c_longlong, c_double, c_float, c_int, cast, pointer, POINTER
from numpy.testing import assert_array_max_ulp
from numpy.core._multiarray_umath import __cpu_features__

IS_AVX = __cpu_features__.get('AVX512F', False) or \

            

Reported by Pylint.

              import pytest
from ctypes import c_longlong, c_double, c_float, c_int, cast, pointer, POINTER
from numpy.testing import assert_array_max_ulp
from numpy.core._multiarray_umath import __cpu_features__

IS_AVX = __cpu_features__.get('AVX512F', False) or \
        (__cpu_features__.get('FMA3', False) and __cpu_features__.get('AVX2', False))
runtest = sys.platform.startswith('linux') and IS_AVX
platform_skip = pytest.mark.skipif(not runtest,

            

Reported by Pylint.

                                      data_subset = data[data['type'] == datatype]
                        inval  = np.array(str_to_float(data_subset['input'].astype(str), data_subset['type'].astype(str)), dtype=eval(datatype))
                        outval = np.array(str_to_float(data_subset['output'].astype(str), data_subset['type'].astype(str)), dtype=eval(datatype))
                        perm = np.random.permutation(len(inval))
                        inval = inval[perm]
                        outval = outval[perm]
                        maxulperr = data_subset['ulperr'].max()
                        assert_array_max_ulp(npfunc(inval), outval, maxulperr)

            

Reported by Pylint.

              import numpy as np
import platform
import os
from os import path
import sys
import pytest
from ctypes import c_longlong, c_double, c_float, c_int, cast, pointer, POINTER
from numpy.testing import assert_array_max_ulp
from numpy.core._multiarray_umath import __cpu_features__

            

Reported by Pylint.

                                  npfunc = getattr(np, npname)
                    for datatype in np.unique(data['type']):
                        data_subset = data[data['type'] == datatype]
                        inval  = np.array(str_to_float(data_subset['input'].astype(str), data_subset['type'].astype(str)), dtype=eval(datatype))
                        outval = np.array(str_to_float(data_subset['output'].astype(str), data_subset['type'].astype(str)), dtype=eval(datatype))
                        perm = np.random.permutation(len(inval))
                        inval = inval[perm]
                        outval = outval[perm]
                        maxulperr = data_subset['ulperr'].max()

            

Reported by Bandit.

                                  npfunc = getattr(np, npname)
                    for datatype in np.unique(data['type']):
                        data_subset = data[data['type'] == datatype]
                        inval  = np.array(str_to_float(data_subset['input'].astype(str), data_subset['type'].astype(str)), dtype=eval(datatype))
                        outval = np.array(str_to_float(data_subset['output'].astype(str), data_subset['type'].astype(str)), dtype=eval(datatype))
                        perm = np.random.permutation(len(inval))
                        inval = inval[perm]
                        outval = outval[perm]
                        maxulperr = data_subset['ulperr'].max()

            

Reported by Pylint.

                                  for datatype in np.unique(data['type']):
                        data_subset = data[data['type'] == datatype]
                        inval  = np.array(str_to_float(data_subset['input'].astype(str), data_subset['type'].astype(str)), dtype=eval(datatype))
                        outval = np.array(str_to_float(data_subset['output'].astype(str), data_subset['type'].astype(str)), dtype=eval(datatype))
                        perm = np.random.permutation(len(inval))
                        inval = inval[perm]
                        outval = outval[perm]
                        maxulperr = data_subset['ulperr'].max()
                        assert_array_max_ulp(npfunc(inval), outval, maxulperr)

            

Reported by Pylint.

                                  for datatype in np.unique(data['type']):
                        data_subset = data[data['type'] == datatype]
                        inval  = np.array(str_to_float(data_subset['input'].astype(str), data_subset['type'].astype(str)), dtype=eval(datatype))
                        outval = np.array(str_to_float(data_subset['output'].astype(str), data_subset['type'].astype(str)), dtype=eval(datatype))
                        perm = np.random.permutation(len(inval))
                        inval = inval[perm]
                        outval = outval[perm]
                        maxulperr = data_subset['ulperr'].max()
                        assert_array_max_ulp(npfunc(inval), outval, maxulperr)

            

Reported by Bandit.

              import numpy as np
import platform
import os
from os import path
import sys
import pytest
from ctypes import c_longlong, c_double, c_float, c_int, cast, pointer, POINTER
from numpy.testing import assert_array_max_ulp
from numpy.core._multiarray_umath import __cpu_features__

            

Reported by Pylint.

              import numpy as np
import platform
import os
from os import path
import sys
import pytest
from ctypes import c_longlong, c_double, c_float, c_int, cast, pointer, POINTER
from numpy.testing import assert_array_max_ulp
from numpy.core._multiarray_umath import __cpu_features__

            

Reported by Pylint.

              import sys

import pytest

import numpy as np
from numpy.testing import assert_, assert_equal
from numpy.core.tests._locales import CommaDecimalPointLocale



            

Reported by Pylint.

                          assert_equal(fmat.format(val), fmat.format(valtype(val)),
                    "failed with val %s, type %s" % (val, valtype))
        except ValueError as e:
            assert_(False,
               "format raised exception (fmt='%s', val=%s, type=%s, exc='%s')" %
                            (fmat, repr(val), repr(valtype), str(e)))


#

            

Reported by Pylint.

              import sys

import pytest

import numpy as np
from numpy.testing import assert_, assert_equal
from numpy.core.tests._locales import CommaDecimalPointLocale



            

Reported by Pylint.

              from numpy.core.tests._locales import CommaDecimalPointLocale


from io import StringIO

_REF = {np.inf: 'inf', -np.inf: '-inf', np.nan: 'nan'}


@pytest.mark.parametrize('tp', [np.float32, np.double, np.longdouble])

            

Reported by Pylint.

              

@pytest.mark.parametrize('tp', [np.float32, np.double, np.longdouble])
def test_float_types(tp):
    """ Check formatting.

        This is only for the str function, and only for simple types.
        The precision of np.float32 and np.longdouble aren't the same as the
        python float precision.

            

Reported by Pylint.

                      python float precision.

    """
    for x in [0, 1, -1, 1e20]:
        assert_equal(str(tp(x)), str(float(x)),
                     err_msg='Failed str formatting for type %s' % tp)

    if tp(1e16).itemsize > 4:
        assert_equal(str(tp(1e16)), str(float('1e16')),

            

Reported by Pylint.

              

@pytest.mark.parametrize('tp', [np.float32, np.double, np.longdouble])
def test_nan_inf_float(tp):
    """ Check formatting of nan & inf.

        This is only for the str function, and only for simple types.
        The precision of np.float32 and np.longdouble aren't the same as the
        python float precision.

            

Reported by Pylint.

                      python float precision.

    """
    for x in [np.inf, -np.inf, np.nan]:
        assert_equal(str(tp(x)), _REF[x],
                     err_msg='Failed str formatting for type %s' % tp)


@pytest.mark.parametrize('tp', [np.complex64, np.cdouble, np.clongdouble])

            

Reported by Pylint.

              

@pytest.mark.parametrize('tp', [np.complex64, np.cdouble, np.clongdouble])
def test_complex_types(tp):
    """Check formatting of complex types.

        This is only for the str function, and only for simple types.
        The precision of np.float32 and np.longdouble aren't the same as the
        python float precision.

            

Reported by Pylint.

                      python float precision.

    """
    for x in [0, 1, -1, 1e20]:
        assert_equal(str(tp(x)), str(complex(x)),
                     err_msg='Failed str formatting for type %s' % tp)
        assert_equal(str(tp(x*1j)), str(complex(x*1j)),
                     err_msg='Failed str formatting for type %s' % tp)
        assert_equal(str(tp(x + x*1j)), str(complex(x + x*1j)),

            

Reported by Pylint.

              from contextlib import nullcontext

import numpy as np
from .numeric import uint8, ndarray, dtype
from numpy.compat import os_fspath, is_pathlib_path
from numpy.core.overrides import set_module

__all__ = ['memmap']


            

Reported by Pylint.

              
    __array_priority__ = -100.0

    def __new__(subtype, filename, dtype=uint8, mode='r+', offset=0,
                shape=None, order='C'):
        # Import here to minimize 'import numpy' overhead
        import mmap
        import os.path
        try:

            

Reported by Pylint.

                      import os.path
        try:
            mode = mode_equivalents[mode]
        except KeyError as e:
            if mode not in valid_filemodes:
                raise ValueError(
                    "mode must be one of {!r} (got {!r})"
                    .format(valid_filemodes + list(mode_equivalents.keys()), mode)
                ) from None

            

Reported by Pylint.

                          _dbytes = descr.itemsize

            if shape is None:
                bytes = flen - offset
                if bytes % _dbytes:
                    raise ValueError("Size of available data is not a "
                            "multiple of the data-type size.")
                size = bytes // _dbytes
                shape = (size,)

            

Reported by Pylint.

              
    def __array_finalize__(self, obj):
        if hasattr(obj, '_mmap') and np.may_share_memory(self, obj):
            self._mmap = obj._mmap
            self.filename = obj.filename
            self.offset = obj.offset
            self.mode = obj.mode
        else:
            self._mmap = None

            

Reported by Pylint.

              
    def __array_finalize__(self, obj):
        if hasattr(obj, '_mmap') and np.may_share_memory(self, obj):
            self._mmap = obj._mmap
            self.filename = obj.filename
            self.offset = obj.offset
            self.mode = obj.mode
        else:
            self._mmap = None

            

Reported by Pylint.

                  def __array_finalize__(self, obj):
        if hasattr(obj, '_mmap') and np.may_share_memory(self, obj):
            self._mmap = obj._mmap
            self.filename = obj.filename
            self.offset = obj.offset
            self.mode = obj.mode
        else:
            self._mmap = None
            self.filename = None

            

Reported by Pylint.

                      if hasattr(obj, '_mmap') and np.may_share_memory(self, obj):
            self._mmap = obj._mmap
            self.filename = obj.filename
            self.offset = obj.offset
            self.mode = obj.mode
        else:
            self._mmap = None
            self.filename = None
            self.offset = None

            

Reported by Pylint.

                          self._mmap = obj._mmap
            self.filename = obj.filename
            self.offset = obj.offset
            self.mode = obj.mode
        else:
            self._mmap = None
            self.filename = None
            self.offset = None
            self.mode = None

            

Reported by Pylint.

                          self.offset = obj.offset
            self.mode = obj.mode
        else:
            self._mmap = None
            self.filename = None
            self.offset = None
            self.mode = None

    def flush(self):

            

Reported by Pylint.