assert_, assert_allclose, assert_array_almost_equal_nulp,
    assert_raises, build_err_msg
    )
from .core import mask_or, getmask, masked_array, nomask, masked, filled

__all__masked = [
    'almost', 'approx', 'assert_almost_equal', 'assert_array_almost_equal',
    'assert_array_approx_equal', 'assert_array_compare',
    'assert_array_equal', 'assert_array_less', 'assert_close',

            

Reported by Pylint.

                      return np.equal(d1, d2).ravel()
    x = filled(masked_array(d1, copy=False, mask=m), fill_value).astype(float_)
    y = filled(masked_array(d2, copy=False, mask=m), 1).astype(float_)
    d = np.less_equal(umath.absolute(x - y), atol + rtol * umath.absolute(y))
    return d.ravel()


def almost(a, b, decimal=6, fill_value=True):
    """

            

Reported by Pylint.

                      return np.equal(d1, d2).ravel()
    x = filled(masked_array(d1, copy=False, mask=m), fill_value).astype(float_)
    y = filled(masked_array(d2, copy=False, mask=m), 1).astype(float_)
    d = np.less_equal(umath.absolute(x - y), atol + rtol * umath.absolute(y))
    return d.ravel()


def almost(a, b, decimal=6, fill_value=True):
    """

            

Reported by Pylint.

              import numpy as np
from numpy import ndarray, float_
import numpy.core.umath as umath
import numpy.testing
from numpy.testing import (
    assert_, assert_allclose, assert_array_almost_equal_nulp,
    assert_raises, build_err_msg
    )
from .core import mask_or, getmask, masked_array, nomask, masked, filled

            

Reported by Pylint.

                      if not isinstance(actual, dict):
            raise AssertionError(repr(type(actual)))
        assert_equal(len(actual), len(desired), err_msg)
        for k, i in desired.items():
            if k not in actual:
                raise AssertionError(f"{k} not in {actual}")
            assert_equal(actual[k], desired[k], f'key={k!r}\n{err_msg}')
        return
    # Case #2: lists .....

            

Reported by Pylint.

                      if not isinstance(actual, dict):
            raise AssertionError(repr(type(actual)))
        fail_if_equal(len(actual), len(desired), err_msg)
        for k, i in desired.items():
            if k not in actual:
                raise AssertionError(repr(k))
            fail_if_equal(actual[k], desired[k], f'key={k!r}\n{err_msg}')
        return
    if isinstance(desired, (list, tuple)) and isinstance(actual, (list, tuple)):

            

Reported by Pylint.

              
    """
    if m1 is nomask:
        assert_(m2 is nomask)
    if m2 is nomask:
        assert_(m1 is nomask)
    assert_array_equal(m1, m2, err_msg=err_msg)

            

Reported by Pylint.

                  if m1 is nomask:
        assert_(m2 is nomask)
    if m2 is nomask:
        assert_(m1 is nomask)
    assert_array_equal(m1, m2, err_msg=err_msg)

            

Reported by Pylint.

              # have mistakenly included them from this file. SciPy is one. That is
# unfortunate, as some of these functions are not intended to work with
# masked arrays. But there was no way to tell before.
from unittest import TestCase
__some__from_testing = [
    'TestCase', 'assert_', 'assert_allclose', 'assert_array_almost_equal_nulp',
    'assert_raises'
    ]


            

Reported by Pylint.

              # have mistakenly included them from this file. SciPy is one. That is
# unfortunate, as some of these functions are not intended to work with
# masked arrays. But there was no way to tell before.
from unittest import TestCase
__some__from_testing = [
    'TestCase', 'assert_', 'assert_allclose', 'assert_array_almost_equal_nulp',
    'assert_raises'
    ]


            

Reported by Pylint.

                  return VariableSet(d)

def parse_sections(config):
    return meta_d, r

def pkg_to_filename(pkg_name):
    return "%s.ini" % pkg_name

def parse_config(filename, dirs=None):

            

Reported by Pylint.

                  return VariableSet(d)

def parse_sections(config):
    return meta_d, r

def pkg_to_filename(pkg_name):
    return "%s.ini" % pkg_name

def parse_config(filename, dirs=None):

            

Reported by Pylint.

                  Exception thrown when there is a problem parsing a configuration file.

    """
    def __init__(self, msg):
        self.msg = msg

    def __str__(self):
        return self.msg


            

Reported by Pylint.

              
class PkgNotFound(IOError):
    """Exception raised when a package can not be located."""
    def __init__(self, msg):
        self.msg = msg

    def __str__(self):
        return self.msg


            

Reported by Pylint.

                      * 'ignored'

    """
    d = {'include_dirs': [], 'library_dirs': [], 'libraries': [],
         'macros': [], 'ignored': []}

    flags = (' ' + line).split(' -')
    for flag in flags:
        flag = '-' + flag

            

Reported by Pylint.

                  attributes of the same name.

    """
    def __init__(self, name, description, version, sections, vars, requires=None):
        self.name = name
        self.description = description
        if requires:
            self.requires = requires
        else:

            

Reported by Pylint.

                  attributes of the same name.

    """
    def __init__(self, name, description, version, sections, vars, requires=None):
        self.name = name
        self.description = description
        if requires:
            self.requires = requires
        else:

            

Reported by Pylint.

                      """
        return list(self._sections.keys())

    def cflags(self, section="default"):
        val = self.vars.interpolate(self._sections[section]['cflags'])
        return _escape_backslash(val)

    def libs(self, section="default"):
        val = self.vars.interpolate(self._sections[section]['libs'])

            

Reported by Pylint.

                      val = self.vars.interpolate(self._sections[section]['cflags'])
        return _escape_backslash(val)

    def libs(self, section="default"):
        val = self.vars.interpolate(self._sections[section]['libs'])
        return _escape_backslash(val)

    def __str__(self):
        m = ['Name: %s' % self.name, 'Description: %s' % self.description]

            

Reported by Pylint.

                      return _escape_backslash(val)

    def __str__(self):
        m = ['Name: %s' % self.name, 'Description: %s' % self.description]
        if self.requires:
            m.append('Requires:')
        else:
            m.append('Requires: %s' % ",".join(self.requires))
        m.append('Version: %s' % self.version)

            

Reported by Pylint.

              

# Small arrays
xs = numpy.random.uniform(-1, 1, 6).reshape(2, 3)
ys = numpy.random.uniform(-1, 1, 6).reshape(2, 3)
zs = xs + 1j * ys
m1 = [[True, False, False], [False, False, True]]
m2 = [[True, False, True], [False, False, True]]
nmxs = numpy.ma.array(xs, mask=m1)

            

Reported by Pylint.

              
# Small arrays
xs = numpy.random.uniform(-1, 1, 6).reshape(2, 3)
ys = numpy.random.uniform(-1, 1, 6).reshape(2, 3)
zs = xs + 1j * ys
m1 = [[True, False, False], [False, False, True]]
m2 = [[True, False, True], [False, False, True]]
nmxs = numpy.ma.array(xs, mask=m1)
nmys = numpy.ma.array(ys, mask=m2)

            

Reported by Pylint.

              nmzs = numpy.ma.array(zs, mask=m1)

# Big arrays
xl = numpy.random.uniform(-1, 1, 100*100).reshape(100, 100)
yl = numpy.random.uniform(-1, 1, 100*100).reshape(100, 100)
zl = xl + 1j * yl
maskx = xl > 0.8
masky = yl < -0.8
nmxl = numpy.ma.array(xl, mask=maskx)

            

Reported by Pylint.

              
# Big arrays
xl = numpy.random.uniform(-1, 1, 100*100).reshape(100, 100)
yl = numpy.random.uniform(-1, 1, 100*100).reshape(100, 100)
zl = xl + 1j * yl
maskx = xl > 0.8
masky = yl < -0.8
nmxl = numpy.ma.array(xl, mask=maskx)
nmyl = numpy.ma.array(yl, mask=masky)

            

Reported by Pylint.

              

def compare_functions_1v(func, nloop=500,
                       xs=xs, nmxs=nmxs, xl=xl, nmxl=nmxl):
    funcname = func.__name__
    print("-"*50)
    print(f'{funcname} on small arrays')
    module, data = "numpy.ma", "nmxs"
    timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)

            

Reported by Pylint.

              

def compare_functions_1v(func, nloop=500,
                       xs=xs, nmxs=nmxs, xl=xl, nmxl=nmxl):
    funcname = func.__name__
    print("-"*50)
    print(f'{funcname} on small arrays')
    module, data = "numpy.ma", "nmxs"
    timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)

            

Reported by Pylint.

              

def compare_functions_1v(func, nloop=500,
                       xs=xs, nmxs=nmxs, xl=xl, nmxl=nmxl):
    funcname = func.__name__
    print("-"*50)
    print(f'{funcname} on small arrays')
    module, data = "numpy.ma", "nmxs"
    timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)

            

Reported by Pylint.

              

def compare_functions_1v(func, nloop=500,
                       xs=xs, nmxs=nmxs, xl=xl, nmxl=nmxl):
    funcname = func.__name__
    print("-"*50)
    print(f'{funcname} on small arrays')
    module, data = "numpy.ma", "nmxs"
    timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)

            

Reported by Pylint.

              

def compare_functions_1v(func, nloop=500,
                       xs=xs, nmxs=nmxs, xl=xl, nmxl=nmxl):
    funcname = func.__name__
    print("-"*50)
    print(f'{funcname} on small arrays')
    module, data = "numpy.ma", "nmxs"
    timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)

            

Reported by Pylint.

              

def compare_functions_1v(func, nloop=500,
                       xs=xs, nmxs=nmxs, xl=xl, nmxl=nmxl):
    funcname = func.__name__
    print("-"*50)
    print(f'{funcname} on small arrays')
    module, data = "numpy.ma", "nmxs"
    timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)

            

Reported by Pylint.

              

ndarray_func(np.array([1, 2]))
array == 1
array.dtype == float

# Dtype construction
np.dtype(float)
np.dtype(np.float64)

            

Reported by Pylint.

              
ndarray_func(np.array([1, 2]))
array == 1
array.dtype == float

# Dtype construction
np.dtype(float)
np.dtype(np.float64)
np.dtype(None)

            

Reported by Pylint.

              np.dtype((np.int32, (np.int8, 4)))

# Dtype comparision
np.dtype(float) == float
np.dtype(float) != np.float64
np.dtype(float) < None
np.dtype(float) <= "float64"
np.dtype(float) > np.dtype(float)
np.dtype(float) >= np.dtype(("U", 10))

            

Reported by Pylint.

              
# Dtype comparision
np.dtype(float) == float
np.dtype(float) != np.float64
np.dtype(float) < None
np.dtype(float) <= "float64"
np.dtype(float) > np.dtype(float)
np.dtype(float) >= np.dtype(("U", 10))


            

Reported by Pylint.

              # Dtype comparision
np.dtype(float) == float
np.dtype(float) != np.float64
np.dtype(float) < None
np.dtype(float) <= "float64"
np.dtype(float) > np.dtype(float)
np.dtype(float) >= np.dtype(("U", 10))

# Iteration and indexing

            

Reported by Pylint.

              np.dtype(float) == float
np.dtype(float) != np.float64
np.dtype(float) < None
np.dtype(float) <= "float64"
np.dtype(float) > np.dtype(float)
np.dtype(float) >= np.dtype(("U", 10))

# Iteration and indexing
def iterable_func(x):

            

Reported by Pylint.

              np.dtype(float) != np.float64
np.dtype(float) < None
np.dtype(float) <= "float64"
np.dtype(float) > np.dtype(float)
np.dtype(float) >= np.dtype(("U", 10))

# Iteration and indexing
def iterable_func(x):
    # type: (Iterable) -> Iterable

            

Reported by Pylint.

              np.dtype(float) < None
np.dtype(float) <= "float64"
np.dtype(float) > np.dtype(float)
np.dtype(float) >= np.dtype(("U", 10))

# Iteration and indexing
def iterable_func(x):
    # type: (Iterable) -> Iterable
    return x

            

Reported by Pylint.

              

iterable_func(array)
[element for element in array]
iter(array)
zip(array, array)
array[1]
array[:]
array[...]

            

Reported by Pylint.

              [element for element in array]
iter(array)
zip(array, array)
array[1]
array[:]
array[...]
array[:] = 0

array_2d = np.ones((3, 3))

            

Reported by Pylint.

                  def __init__(self, name=None, filename=None):
        self.filename = filename
        if name is None:
            root, ext = os.path.splitext(filename)
            name = root
        self.name = name
        self._dependencies = None

    def dependencies(self):

            

Reported by Pylint.

              
    try:
        shutil.rmtree(output_dir)
    except:
        pass
    os.makedirs(output_dir)

    wrapped_routines, ignores = getWrappedRoutineNames(wrapped_routines_file)
    library = getLapackRoutines(wrapped_routines, ignores, lapack_src_dir)

            

Reported by Pylint.

              import sys
import os
import re
import subprocess
import shutil

import fortran
import clapack_scrub


            

Reported by Bandit.

              import fortran
import clapack_scrub

from shutil import which

# Arguments to pass to f2c. You'll always want -A for ANSI C prototypes
# Others of interest: -a to not make variables static by default
#                     -C to check array subscripts
F2C_ARGS = ['-A', '-Nx800']

            

Reported by Pylint.

                      self.name = name
        self._dependencies = None

    def dependencies(self):
        if self._dependencies is None:
            deps = fortran.getDependencies(self.filename)
            self._dependencies = [d.lower() for d in deps]
        return self._dependencies


            

Reported by Pylint.

                  def __repr__(self):
        return f'FortranRoutine({self.name!r}, filename={self.filename!r})'

class UnknownFortranRoutine(FortranRoutine):
    """Wrapper for a Fortran routine for which the corresponding file
    is not known.
    """
    type = 'unknown'
    def __init__(self, name):

            

Reported by Pylint.

                      self._src_dirs = src_dirs
        self.names_to_routines = {}

    def _findRoutine(self, rname):
        rname = rname.lower()
        for s in self._src_dirs:
            ffilename = os.path.join(s, rname + '.f')
            if os.path.exists(ffilename):
                return self._newFortranRoutine(rname, ffilename)

            

Reported by Pylint.

              
    def _findRoutine(self, rname):
        rname = rname.lower()
        for s in self._src_dirs:
            ffilename = os.path.join(s, rname + '.f')
            if os.path.exists(ffilename):
                return self._newFortranRoutine(rname, ffilename)
        return UnknownFortranRoutine(rname)


            

Reported by Pylint.

                              return self._newFortranRoutine(rname, ffilename)
        return UnknownFortranRoutine(rname)

    def _newFortranRoutine(self, rname, filename):
        return FortranRoutine(rname, filename)

    def addIgnorableRoutine(self, rname):
        """Add a routine that we don't want to consider when looking at
        dependencies.

            

Reported by Pylint.

                              return self._newFortranRoutine(rname, ffilename)
        return UnknownFortranRoutine(rname)

    def _newFortranRoutine(self, rname, filename):
        return FortranRoutine(rname, filename)

    def addIgnorableRoutine(self, rname):
        """Add a routine that we don't want to consider when looking at
        dependencies.

            

Reported by Pylint.

              _SCT = TypeVar("_SCT", bound=np.generic)


def func1(ar: npt.NDArray[_SCT], a: int) -> npt.NDArray[_SCT]:
    pass


def func2(ar: npt.NDArray[np.number[Any]], a: str) -> npt.NDArray[np.float64]:
    pass

            

Reported by Pylint.

              _SCT = TypeVar("_SCT", bound=np.generic)


def func1(ar: npt.NDArray[_SCT], a: int) -> npt.NDArray[_SCT]:
    pass


def func2(ar: npt.NDArray[np.number[Any]], a: str) -> npt.NDArray[np.float64]:
    pass

            

Reported by Pylint.

                  pass


def func2(ar: npt.NDArray[np.number[Any]], a: str) -> npt.NDArray[np.float64]:
    pass


AR_b: npt.NDArray[np.bool_]
AR_u: npt.NDArray[np.uint64]

            

Reported by Pylint.

                  pass


def func2(ar: npt.NDArray[np.number[Any]], a: str) -> npt.NDArray[np.float64]:
    pass


AR_b: npt.NDArray[np.bool_]
AR_u: npt.NDArray[np.uint64]

            

Reported by Pylint.

                  pass


def func2(ar: npt.NDArray[np.number[Any]], a: str) -> npt.NDArray[np.float64]:
    pass


AR_b: npt.NDArray[np.bool_]
AR_u: npt.NDArray[np.uint64]

            

Reported by Pylint.

                  pass


AR_b: npt.NDArray[np.bool_]
AR_u: npt.NDArray[np.uint64]
AR_i: npt.NDArray[np.int64]
AR_f: npt.NDArray[np.float64]
AR_c: npt.NDArray[np.complex128]
AR_O: npt.NDArray[np.object_]

            

Reported by Pylint.

              

AR_b: npt.NDArray[np.bool_]
AR_u: npt.NDArray[np.uint64]
AR_i: npt.NDArray[np.int64]
AR_f: npt.NDArray[np.float64]
AR_c: npt.NDArray[np.complex128]
AR_O: npt.NDArray[np.object_]


            

Reported by Pylint.

              
AR_b: npt.NDArray[np.bool_]
AR_u: npt.NDArray[np.uint64]
AR_i: npt.NDArray[np.int64]
AR_f: npt.NDArray[np.float64]
AR_c: npt.NDArray[np.complex128]
AR_O: npt.NDArray[np.object_]

AR_LIKE_b: List[bool]

            

Reported by Pylint.

              AR_b: npt.NDArray[np.bool_]
AR_u: npt.NDArray[np.uint64]
AR_i: npt.NDArray[np.int64]
AR_f: npt.NDArray[np.float64]
AR_c: npt.NDArray[np.complex128]
AR_O: npt.NDArray[np.object_]

AR_LIKE_b: List[bool]


            

Reported by Pylint.

              AR_u: npt.NDArray[np.uint64]
AR_i: npt.NDArray[np.int64]
AR_f: npt.NDArray[np.float64]
AR_c: npt.NDArray[np.complex128]
AR_O: npt.NDArray[np.object_]

AR_LIKE_b: List[bool]

reveal_type(np.fliplr(AR_b))  # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]]

            

Reported by Pylint.

              import sys
import warnings

from ._globals import (
    ModuleDeprecationWarning, VisibleDeprecationWarning, _NoValue
)

# We first need to detect if we're being called as part of the numpy setup
# procedure itself in a reliable manner.

            

Reported by Pylint.

                             'VisibleDeprecationWarning']

    # get the version using versioneer
    from ._version import get_versions
    vinfo = get_versions()
    __version__ = vinfo.get("closest-tag", vinfo["version"])
    __git_version__ = vinfo.get("full-revisionid")
    del get_versions, vinfo


            

Reported by Pylint.

                  from . import _distributor_init

    from . import core
    from .core import *
    from . import compat
    from . import lib
    # NOTE: to be revisited following future namespace cleanup.
    # See gh-14454 and gh-15672 for discussion.
    from .lib import *

            

Reported by Pylint.

                  from . import lib
    # NOTE: to be revisited following future namespace cleanup.
    # See gh-14454 and gh-15672 for discussion.
    from .lib import *

    from . import linalg
    from . import fft
    from . import polynomial
    from . import random

            

Reported by Pylint.

                  from . import random
    from . import ctypeslib
    from . import ma
    from . import matrixlib as _mat
    from .matrixlib import *

    # Deprecations introduced in NumPy 1.20.0, 2020-06-06
    import builtins as _builtins


            

Reported by Pylint.

                  from . import ctypeslib
    from . import ma
    from . import matrixlib as _mat
    from .matrixlib import *

    # Deprecations introduced in NumPy 1.20.0, 2020-06-06
    import builtins as _builtins

    _msg = (

            

Reported by Pylint.

              
    del _msg, _specific_msg, _int_extended_msg, _type_info, _builtins

    from .core import round, abs, max, min
    # now that numpy modules are imported, can initialize limits
    core.getlimits._register_known_types()

    __all__.extend(['__version__', 'show_config'])
    __all__.extend(core.__all__)

            

Reported by Pylint.

                  # These are exported by np.core, but are replaced by the builtins below
    # remove them to ensure that we don't end up with `np.long == np.int_`,
    # which would be a breaking change.
    del long, unicode
    __all__.remove('long')
    __all__.remove('unicode')

    # Remove things that are in the numpy.lib but not in the numpy namespace
    # Note that there is a test (numpy/tests/test_public_api.py:test_numpy_namespace)

            

Reported by Pylint.

                  # These are exported by np.core, but are replaced by the builtins below
    # remove them to ensure that we don't end up with `np.long == np.int_`,
    # which would be a breaking change.
    del long, unicode
    __all__.remove('long')
    __all__.remove('unicode')

    # Remove things that are in the numpy.lib but not in the numpy namespace
    # Note that there is a test (numpy/tests/test_public_api.py:test_numpy_namespace)

            

Reported by Pylint.

                  # The list below will grow until the `from .lib import *` fixme above is
    # taken care of
    __all__.remove('Arrayterator')
    del Arrayterator

    # These names were removed in NumPy 1.20.  For at least one release,
    # attempts to access these names in the numpy namespace will trigger
    # a warning, and calling the function will raise an exception.
    _financial_names = ['fv', 'ipmt', 'irr', 'mirr', 'nper', 'npv', 'pmt',

            

Reported by Pylint.

                  # Handle order kwarg for output array, c_einsum allows mixed case
    output_order = kwargs.pop('order', 'K')
    if output_order.upper() == 'A':
        if all(arr.flags.f_contiguous for arr in operands):
            output_order = 'F'
        else:
            output_order = 'C'

    # Start contraction loop

            

Reported by Pylint.

                  # Handle order kwarg for output array, c_einsum allows mixed case
    output_order = kwargs.pop('order', 'K')
    if output_order.upper() == 'A':
        if all(arr.flags.f_contiguous for arr in operands):
            output_order = 'F'
        else:
            output_order = 'C'

    # Start contraction loop

            

Reported by Pylint.

              
    # Build up a naive cost
    contract = _find_contraction(range(len(input_sets)), input_sets, output_set)
    idx_result, new_input_sets, idx_removed, idx_contract = contract
    naive_cost = _flop_count(idx_contract, idx_removed, len(input_sets), idx_dict)

    # Initially iterate over all pairs
    comb_iter = itertools.combinations(range(len(input_sets)), 2)
    known_contractions = []

            

Reported by Pylint.

              
    # Build up a naive cost
    contract = _find_contraction(range(len(input_sets)), input_sets, output_set)
    idx_result, new_input_sets, idx_removed, idx_contract = contract
    naive_cost = _flop_count(idx_contract, idx_removed, len(input_sets), idx_dict)

    # Initially iterate over all pairs
    comb_iter = itertools.combinations(range(len(input_sets)), 2)
    known_contractions = []

            

Reported by Pylint.

                  path_cost = 0
    path = []

    for iteration in range(len(input_sets) - 1):

        # Iterate over all pairs on first step, only previously found pairs on subsequent steps
        for positions in comb_iter:

            # Always initially ignore outer products

            

Reported by Pylint.

                      tmp_operands = list(operands)
        operand_list = []
        subscript_list = []
        for p in range(len(operands) // 2):
            operand_list.append(tmp_operands.pop(0))
            subscript_list.append(tmp_operands.pop(0))

        output_list = tmp_operands[-1] if len(tmp_operands) else None
        operands = [asanyarray(v) for v in operand_list]

            

Reported by Pylint.

                  return (input_subscripts, output_subscript, operands)


def _einsum_path_dispatcher(*operands, optimize=None, einsum_call=None):
    # NOTE: technically, we should only dispatch on array-like arguments, not
    # subscripts (given as strings). But separating operands into
    # arrays/subscripts is a little tricky/slow (given einsum's two supported
    # signatures), so as a practical shortcut we dispatch on everything.
    # Strings will be ignored for dispatching since they don't define

            

Reported by Pylint.

                  return (input_subscripts, output_subscript, operands)


def _einsum_path_dispatcher(*operands, optimize=None, einsum_call=None):
    # NOTE: technically, we should only dispatch on array-like arguments, not
    # subscripts (given as strings). But separating operands into
    # arrays/subscripts is a little tricky/slow (given einsum's two supported
    # signatures), so as a practical shortcut we dispatch on everything.
    # Strings will be ignored for dispatching since they don't define

            

Reported by Pylint.

                  elif path_type[0] == 'einsum_path':
        path = path_type[1:]
    else:
        raise KeyError("Path name %s not found", path_type)

    cost_list, scale_list, size_list, contraction_list = [], [], [], []

    # Build contraction tuple (positions, gemm, einsum_str, remaining)
    for cnum, contract_inds in enumerate(path):

            

Reported by Pylint.

                  path_print += "-" * 74

    for n, contraction in enumerate(contraction_list):
        inds, idx_rm, einsum_str, remaining, blas = contraction
        remaining_str = ",".join(remaining) + "->" + output_subscript
        path_run = (scale_list[n], einsum_str, remaining_str)
        path_print += "\n%4d    %24s %40s" % path_run

    path = ['einsum_path'] + path

            

Reported by Pylint.

              
import numpy as np

from . import capi_maps
from . import func2subr
from .crackfortran import undo_rmbadname, undo_rmbadname1

# The environment provided by auxfuncs.py is needed for some calls to eval.
# As the needed functions cannot be determined by static inspection of the

            

Reported by Pylint.

              import numpy as np

from . import capi_maps
from . import func2subr
from .crackfortran import undo_rmbadname, undo_rmbadname1

# The environment provided by auxfuncs.py is needed for some calls to eval.
# As the needed functions cannot be determined by static inspection of the
# code, it is safest to use import * pending a major refactoring of f2py.

            

Reported by Pylint.

              
from . import capi_maps
from . import func2subr
from .crackfortran import undo_rmbadname, undo_rmbadname1

# The environment provided by auxfuncs.py is needed for some calls to eval.
# As the needed functions cannot be determined by static inspection of the
# code, it is safest to use import * pending a major refactoring of f2py.
from .auxfuncs import *

            

Reported by Pylint.

              # The environment provided by auxfuncs.py is needed for some calls to eval.
# As the needed functions cannot be determined by static inspection of the
# code, it is safest to use import * pending a major refactoring of f2py.
from .auxfuncs import *

options = {}


def findf90modules(m):

            

Reported by Pylint.

              

def findf90modules(m):
    if ismodule(m):
        return [m]
    if not hasbody(m):
        return []
    ret = []
    for b in m['body']:

            

Reported by Pylint.

              def findf90modules(m):
    if ismodule(m):
        return [m]
    if not hasbody(m):
        return []
    ret = []
    for b in m['body']:
        if ismodule(b):
            ret.append(b)

            

Reported by Pylint.

                      return []
    ret = []
    for b in m['body']:
        if ismodule(b):
            ret.append(b)
        else:
            ret = ret + findf90modules(b)
    return ret


            

Reported by Pylint.

              

def buildhooks(pymod):
    from . import rules
    ret = {'f90modhooks': [], 'initf90modhooks': [], 'body': [],
           'need': ['F_FUNC', 'arrayobject.h'],
           'separatorsfor': {'includes0': '\n', 'includes': '\n'},
           'docs': ['"Fortran 90/95 modules:\\n"'],
           'latexdoc': []}

            

Reported by Pylint.

                      sargsp = []
        ifargs = []
        mfargs = []
        if hasbody(m):
            for b in m['body']:
                notvars.append(b['name'])
        for n in m['vars'].keys():
            var = m['vars'][n]
            if (n not in notvars) and (not l_or(isintent_hide, isprivate)(var)):

            

Reported by Pylint.

                              notvars.append(b['name'])
        for n in m['vars'].keys():
            var = m['vars'][n]
            if (n not in notvars) and (not l_or(isintent_hide, isprivate)(var)):
                onlyvars.append(n)
                mfargs.append(n)
        outmess('\t\tConstructing F90 module support for "%s"...\n' %
                (m['name']))
        if onlyvars:

            

Reported by Pylint.

              
"""
__all__ = [
    'beta',
    'binomial',
    'bytes',
    'chisquare',
    'choice',
    'dirichlet',

            

Reported by Pylint.

              """
__all__ = [
    'beta',
    'binomial',
    'bytes',
    'chisquare',
    'choice',
    'dirichlet',
    'exponential',

            

Reported by Pylint.

              __all__ = [
    'beta',
    'binomial',
    'bytes',
    'chisquare',
    'choice',
    'dirichlet',
    'exponential',
    'f',

            

Reported by Pylint.

                  'beta',
    'binomial',
    'bytes',
    'chisquare',
    'choice',
    'dirichlet',
    'exponential',
    'f',
    'gamma',

            

Reported by Pylint.

                  'binomial',
    'bytes',
    'chisquare',
    'choice',
    'dirichlet',
    'exponential',
    'f',
    'gamma',
    'geometric',

            

Reported by Pylint.

                  'bytes',
    'chisquare',
    'choice',
    'dirichlet',
    'exponential',
    'f',
    'gamma',
    'geometric',
    'get_state',

            

Reported by Pylint.

                  'chisquare',
    'choice',
    'dirichlet',
    'exponential',
    'f',
    'gamma',
    'geometric',
    'get_state',
    'gumbel',

            

Reported by Pylint.

                  'choice',
    'dirichlet',
    'exponential',
    'f',
    'gamma',
    'geometric',
    'get_state',
    'gumbel',
    'hypergeometric',

            

Reported by Pylint.

                  'dirichlet',
    'exponential',
    'f',
    'gamma',
    'geometric',
    'get_state',
    'gumbel',
    'hypergeometric',
    'laplace',

            

Reported by Pylint.

                  'exponential',
    'f',
    'gamma',
    'geometric',
    'get_state',
    'gumbel',
    'hypergeometric',
    'laplace',
    'logistic',

            

Reported by Pylint.