"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 *

            

Reported by Pylint.

              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 record, recarray, format_parser

            

Reported by Pylint.

              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 record, recarray, format_parser
from .memmap import *
from .defchararray import chararray

            

Reported by Pylint.

              from .numeric import *
from . import fromnumeric
from .fromnumeric import *
from . import defchararray as char
from . import records as rec
from .records import record, recarray, format_parser
from .memmap import *
from .defchararray import chararray
from . import function_base

            

Reported by Pylint.

              from . import fromnumeric
from .fromnumeric import *
from . import defchararray as char
from . import records as rec
from .records import record, recarray, format_parser
from .memmap import *
from .defchararray import chararray
from . import function_base
from .function_base import *

            

Reported by Pylint.

              from .fromnumeric import *
from . import defchararray as char
from . import records as rec
from .records import record, recarray, format_parser
from .memmap import *
from .defchararray import chararray
from . import function_base
from .function_base import *
from . import machar

            

Reported by Pylint.

              from . import defchararray as char
from . import records as rec
from .records import record, recarray, format_parser
from .memmap import *
from .defchararray import chararray
from . import function_base
from .function_base import *
from . import machar
from .machar import *

            

Reported by Pylint.

              from . import records as rec
from .records import record, recarray, format_parser
from .memmap import *
from .defchararray import chararray
from . import function_base
from .function_base import *
from . import machar
from .machar import *
from . import getlimits

            

Reported by Pylint.

              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

            

Reported by Pylint.

              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

            

Reported by Pylint.

              import numpy.linalg as la
from numpy.core.multiarray import normalize_axis_index

from . import polyutils as pu
from ._polybase import ABCPolyBase

polytrim = pu.trimcoef

#

            

Reported by Pylint.

              from numpy.core.multiarray import normalize_axis_index

from . import polyutils as pu
from ._polybase import ABCPolyBase

polytrim = pu.trimcoef

#
# These are constant arrays are of integer type so as to be compatible

            

Reported by Pylint.

                  array([1.+0.j,  0.+0.j,  1.+0.j])

    """
    return pu._fromroots(polyline, polymul, roots)


def polyadd(c1, c2):
    """
    Add one polynomial to another.

            

Reported by Pylint.

                  28.0

    """
    return pu._add(c1, c2)


def polysub(c1, c2):
    """
    Subtract one polynomial from another.

            

Reported by Pylint.

                  array([ 2.,  0., -2.])

    """
    return pu._sub(c1, c2)


def polymulx(c):
    """Multiply a polynomial by x.


            

Reported by Pylint.

                      return c1[j+1:]/scl, pu.trimseq(c1[:j+1])


def polypow(c, pow, maxpower=None):
    """Raise a polynomial to a power.

    Returns the polynomial `c` raised to the power `pow`. The argument
    `c` is a sequence of coefficients ordered from low to high. i.e.,
    [1,2,3] is the series  ``1 + 2*x + 3*x**2.``

            

Reported by Pylint.

                  """
    # note: this is more efficient than `pu._pow(polymul, c1, c2)`, as it
    # avoids calling `as_series` repeatedly
    return pu._pow(np.convolve, c, pow, maxpower)


def polyder(c, m=1, scl=1, axis=0):
    """
    Differentiate a polynomial.

            

Reported by Pylint.

                      # astype fails with NA
        c = c + 0.0
    cdt = c.dtype
    cnt = pu._deprecate_as_int(m, "the order of derivation")
    iaxis = pu._deprecate_as_int(axis, "the axis")
    if cnt < 0:
        raise ValueError("The order of derivation must be non-negative")
    iaxis = normalize_axis_index(iaxis, c.ndim)


            

Reported by Pylint.

                      c = c + 0.0
    cdt = c.dtype
    cnt = pu._deprecate_as_int(m, "the order of derivation")
    iaxis = pu._deprecate_as_int(axis, "the axis")
    if cnt < 0:
        raise ValueError("The order of derivation must be non-negative")
    iaxis = normalize_axis_index(iaxis, c.ndim)

    if cnt == 0:

            

Reported by Pylint.

                  if cnt >= n:
        c = c[:1]*0
    else:
        for i in range(cnt):
            n = n - 1
            c *= scl
            der = np.empty((n,) + c.shape[1:], dtype=cdt)
            for j in range(n, 0, -1):
                der[j - 1] = j*c[j]

            

Reported by Pylint.

                        end with `?`.
        - remained features are representing the baseline.
    """
    from numpy.core._multiarray_umath import (
        __cpu_features__, __cpu_baseline__, __cpu_dispatch__
    )

    if len(__cpu_baseline__) == 0 and len(__cpu_dispatch__) == 0:
        return ''

            

Reported by Pylint.

                      ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers

            

Reported by Pylint.

              
    """
    if vardict is None:
        frame = sys._getframe().f_back
        vardict = frame.f_globals
    sta = []
    cache = {}
    for name in vardict.keys():
        if isinstance(vardict[name], ndarray):

            

Reported by Pylint.

                  print("contiguous: ", bp(obj.flags.contiguous), file=output)
    print("fortran: ", obj.flags.fortran, file=output)
    print(
        "data pointer: %s%s" % (hex(obj.ctypes._as_parameter_.value), extra),
        file=output
        )
    print("byteorder: ", end=' ', file=output)
    if endian in ['|', '=']:
        print("%s%s%s" % (tic, sys.byteorder, tic), file=output)

            

Reported by Pylint.

              

@set_module('numpy')
def info(object=None, maxwidth=76, output=sys.stdout, toplevel='numpy'):
    """
    Get help information for a function, class, or module.

    Parameters
    ----------

            

Reported by Pylint.

                       *** Total of 3 references found. ***

    """
    global _namedict, _dictlist
    # Local import to speed up numpy's import time.
    import pydoc
    import inspect

    if (hasattr(object, '_ppimport_importer') or

            

Reported by Pylint.

              
    if (hasattr(object, '_ppimport_importer') or
           hasattr(object, '_ppimport_module')):
        object = object._ppimport_module
    elif hasattr(object, '_ppimport_attr'):
        object = object._ppimport_attr

    if object is None:
        info(info)

            

Reported by Pylint.

                         hasattr(object, '_ppimport_module')):
        object = object._ppimport_module
    elif hasattr(object, '_ppimport_attr'):
        object = object._ppimport_attr

    if object is None:
        info(info)
    elif isinstance(object, ndarray):
        _info(object, output=output)

            

Reported by Pylint.

                      name = object.__name__
        try:
            arguments = str(inspect.signature(object))
        except Exception:
            arguments = "()"

        if len(name+arguments) > maxwidth:
            argstr = _split_line(name, arguments, maxwidth)
        else:

            

Reported by Pylint.

                      name = object.__name__
        try:
            arguments = str(inspect.signature(object))
        except Exception:
            arguments = "()"

        if len(name+arguments) > maxwidth:
            argstr = _split_line(name, arguments, maxwidth)
        else:

            

Reported by Pylint.

              from .common import Benchmark

import numpy as np

try:
    from numpy.random import Generator
except ImportError:
    pass


            

Reported by Pylint.

              
    def setup(self, bitgen):
        if bitgen == 'numpy':
            self.rg = np.random.RandomState()
        else:
            self.rg = Generator(getattr(np.random, bitgen)())
        self.rg.random()
        self.int32info = np.iinfo(np.int32)
        self.uint32info = np.iinfo(np.uint32)

            

Reported by Pylint.

              
    def setup(self, bitgen, args):
        if bitgen == 'numpy':
            self.rg = np.random.RandomState()
        else:
            self.rg = Generator(getattr(np.random, bitgen)())
        self.rg.random()

    def time_bounded(self, bitgen, args):

            

Reported by Pylint.

                      name = items.pop(0)
        params = [float(x) for x in items]

        self.func = getattr(np.random, name)
        self.params = tuple(params) + ((100, 100),)

    def time_rng(self, name):
        self.func(*self.params)


            

Reported by Pylint.

                      self.func = getattr(np.random, name)
        self.params = tuple(params) + ((100, 100),)

    def time_rng(self, name):
        self.func(*self.params)


class Shuffle(Benchmark):
    def setup(self):

            

Reported by Pylint.

              
class Shuffle(Benchmark):
    def setup(self):
        self.a = np.arange(100000)

    def time_100000(self):
        np.random.shuffle(self.a)



            

Reported by Pylint.

                  param_names = ['dtype']
    params = ['bool', 'uint8', 'uint16', 'uint32', 'uint64']

    def setup(self, name):
        from numpy.lib import NumpyVersion
        if NumpyVersion(np.__version__) < '1.11.0.dev0':
            raise NotImplementedError

    def time_randint_fast(self, name):

            

Reported by Pylint.

              
class Permutation(Benchmark):
    def setup(self):
        self.n = 10000
        self.a_1d = np.random.random(self.n)
        self.a_2d = np.random.random((self.n, 2))

    def time_permutation_1d(self):
        np.random.permutation(self.a_1d)

            

Reported by Pylint.

              class Permutation(Benchmark):
    def setup(self):
        self.n = 10000
        self.a_1d = np.random.random(self.n)
        self.a_2d = np.random.random((self.n, 2))

    def time_permutation_1d(self):
        np.random.permutation(self.a_1d)


            

Reported by Pylint.

                  def setup(self):
        self.n = 10000
        self.a_1d = np.random.random(self.n)
        self.a_2d = np.random.random((self.n, 2))

    def time_permutation_1d(self):
        np.random.permutation(self.a_1d)

    def time_permutation_2d(self):

            

Reported by Pylint.

              import sys
import datetime as dt

import pytest
import numpy as np

b =  np.bool_()
u8 = np.uint64()
i8 = np.int64()

            

Reported by Pylint.

              import pytest
import numpy as np

b =  np.bool_()
u8 = np.uint64()
i8 = np.int64()
f8 = np.float64()
c16 = np.complex128()
U = np.str_()

            

Reported by Pylint.

              import numpy as np

b =  np.bool_()
u8 = np.uint64()
i8 = np.int64()
f8 = np.float64()
c16 = np.complex128()
U = np.str_()
S = np.bytes_()

            

Reported by Pylint.

              b =  np.bool_()
u8 = np.uint64()
i8 = np.int64()
f8 = np.float64()
c16 = np.complex128()
U = np.str_()
S = np.bytes_()



            

Reported by Pylint.

              u8 = np.uint64()
i8 = np.int64()
f8 = np.float64()
c16 = np.complex128()
U = np.str_()
S = np.bytes_()


# Construction

            

Reported by Pylint.

              np.int32(4)
np.int64(-1)
np.uint8(B())
np.uint32()
np.int32("1")
np.int64(b"2")

np.float16(A())
np.float32(16)

            

Reported by Pylint.

              np.int64().flags

np.uint8().itemsize * 2
np.uint16().ndim + 1
np.uint32().strides
np.uint64().shape

# Time structures
np.datetime64()

            

Reported by Pylint.

              
np.uint8().itemsize * 2
np.uint16().ndim + 1
np.uint32().strides
np.uint64().shape

# Time structures
np.datetime64()
np.datetime64(0, "D")

            

Reported by Pylint.

              np.uint8().itemsize * 2
np.uint16().ndim + 1
np.uint32().strides
np.uint64().shape

# Time structures
np.datetime64()
np.datetime64(0, "D")
np.datetime64(0, b"D")

            

Reported by Pylint.

              np.uint64().shape

# Time structures
np.datetime64()
np.datetime64(0, "D")
np.datetime64(0, b"D")
np.datetime64(0, ('ms', 3))
np.datetime64("2019")
np.datetime64(b"2019")

            

Reported by Pylint.

                              [7.]])

        """
        return N.ndarray.sum(self, axis, dtype, out, keepdims=True)._collapse(axis)


    # To update docstring from array to matrix...
    def squeeze(self, axis=None):
        """

            

Reported by Pylint.

                              [ 9.5]])

        """
        return N.ndarray.mean(self, axis, dtype, out, keepdims=True)._collapse(axis)

    def std(self, axis=None, dtype=None, out=None, ddof=0):
        """
        Return the standard deviation of the array elements along the given axis.


            

Reported by Pylint.

                              [ 1.11803399]])

        """
        return N.ndarray.std(self, axis, dtype, out, ddof, keepdims=True)._collapse(axis)

    def var(self, axis=None, dtype=None, out=None, ddof=0):
        """
        Returns the variance of the matrix elements, along the given axis.


            

Reported by Pylint.

                              [1.25]])

        """
        return N.ndarray.var(self, axis, dtype, out, ddof, keepdims=True)._collapse(axis)

    def prod(self, axis=None, dtype=None, out=None):
        """
        Return the product of the array elements over the given axis.


            

Reported by Pylint.

                              [7920]])

        """
        return N.ndarray.prod(self, axis, dtype, out, keepdims=True)._collapse(axis)

    def any(self, axis=None, out=None):
        """
        Test whether any array element along a given axis evaluates to True.


            

Reported by Pylint.

                              returns `ndarray`

        """
        return N.ndarray.any(self, axis, out, keepdims=True)._collapse(axis)

    def all(self, axis=None, out=None):
        """
        Test whether all matrix elements along a given axis evaluate to True.


            

Reported by Pylint.

                              [False]])

        """
        return N.ndarray.all(self, axis, out, keepdims=True)._collapse(axis)

    def max(self, axis=None, out=None):
        """
        Return the maximum value along an axis.


            

Reported by Pylint.

                              [11]])

        """
        return N.ndarray.max(self, axis, out, keepdims=True)._collapse(axis)

    def argmax(self, axis=None, out=None):
        """
        Indexes of the maximum values along an axis.


            

Reported by Pylint.

                              [11]])

        """
        return N.ndarray.max(self, axis, out, keepdims=True)._collapse(axis)

    def argmax(self, axis=None, out=None):
        """
        Indexes of the maximum values along an axis.


            

Reported by Pylint.

                              [3]])

        """
        return N.ndarray.argmax(self, axis, out)._align(axis)

    def min(self, axis=None, out=None):
        """
        Return the minimum value along an axis.


            

Reported by Pylint.

              import os
import shutil
import pytest
from tempfile import mkstemp, mkdtemp
from subprocess import Popen, PIPE
from distutils.errors import DistutilsError

from numpy.testing import assert_, assert_equal, assert_raises
from numpy.distutils import ccompiler, customized_ccompiler

            

Reported by Pylint.

              from numpy.distutils import _shell_utils


def get_class(name, notfound_action=1):
    """
    notfound_action:
      0 - do nothing
      1 - display warning message
      2 - raise error

            

Reported by Pylint.

              
class _system_info(system_info):

    def __init__(self,
                 default_lib_dirs=default_lib_dirs,
                 default_include_dirs=default_include_dirs,
                 verbosity=1,
                 ):
        self.__class__.info = {}

            

Reported by Pylint.

              
class _system_info(system_info):

    def __init__(self,
                 default_lib_dirs=default_lib_dirs,
                 default_include_dirs=default_include_dirs,
                 verbosity=1,
                 ):
        self.__class__.info = {}

            

Reported by Pylint.

              
class _system_info(system_info):

    def __init__(self,
                 default_lib_dirs=default_lib_dirs,
                 default_include_dirs=default_include_dirs,
                 verbosity=1,
                 ):
        self.__class__.info = {}

            

Reported by Pylint.

              class _system_info(system_info):

    def __init__(self,
                 default_lib_dirs=default_lib_dirs,
                 default_include_dirs=default_include_dirs,
                 verbosity=1,
                 ):
        self.__class__.info = {}
        self.local_prefixes = []

            

Reported by Pylint.

              
    def __init__(self,
                 default_lib_dirs=default_lib_dirs,
                 default_include_dirs=default_include_dirs,
                 verbosity=1,
                 ):
        self.__class__.info = {}
        self.local_prefixes = []
        defaults = {'library_dirs': '',

            

Reported by Pylint.

                  def __init__(self,
                 default_lib_dirs=default_lib_dirs,
                 default_include_dirs=default_include_dirs,
                 verbosity=1,
                 ):
        self.__class__.info = {}
        self.local_prefixes = []
        defaults = {'library_dirs': '',
                    'include_dirs': '',

            

Reported by Pylint.

                  def setup(self):
        """ Create the libraries """
        # Create 2 sources and 2 libraries
        self._dir1 = mkdtemp()
        self._src1 = os.path.join(self._dir1, 'foo.c')
        self._lib1 = os.path.join(self._dir1, 'libfoo.so')
        self._dir2 = mkdtemp()
        self._src2 = os.path.join(self._dir2, 'bar.c')
        self._lib2 = os.path.join(self._dir2, 'libbar.so')

            

Reported by Pylint.

                      """ Create the libraries """
        # Create 2 sources and 2 libraries
        self._dir1 = mkdtemp()
        self._src1 = os.path.join(self._dir1, 'foo.c')
        self._lib1 = os.path.join(self._dir1, 'libfoo.so')
        self._dir2 = mkdtemp()
        self._src2 = os.path.join(self._dir2, 'bar.c')
        self._lib2 = os.path.join(self._dir2, 'libbar.so')
        # Update local site.cfg

            

Reported by Pylint.

                      # Make sure generated random variables are in [-pi, pi].
        # Regression test for ticket #986.
        for mu in np.linspace(-7., 7., 5):
            r = random.mtrand.vonmises(mu, 1, 50)
            assert_(np.all(r > -np.pi) and np.all(r <= np.pi))

    def test_hypergeometric_range(self):
        # Test for ticket #921
        assert_(np.all(np.random.hypergeometric(3, 18, 11, size=10) < 4))

            

Reported by Pylint.

              
    def test_hypergeometric_range(self):
        # Test for ticket #921
        assert_(np.all(np.random.hypergeometric(3, 18, 11, size=10) < 4))
        assert_(np.all(np.random.hypergeometric(18, 3, 11, size=10) > 0))

        # Test for ticket #5623
        args = [
            (2**20 - 2, 2**20 - 2, 2**20 - 2),  # Check for 32-bit systems

            

Reported by Pylint.

                  def test_hypergeometric_range(self):
        # Test for ticket #921
        assert_(np.all(np.random.hypergeometric(3, 18, 11, size=10) < 4))
        assert_(np.all(np.random.hypergeometric(18, 3, 11, size=10) > 0))

        # Test for ticket #5623
        args = [
            (2**20 - 2, 2**20 - 2, 2**20 - 2),  # Check for 32-bit systems
        ]

            

Reported by Pylint.

                          # Check for 64-bit systems
            args.append((2**40 - 2, 2**40 - 2, 2**40 - 2))
        for arg in args:
            assert_(np.random.hypergeometric(*arg) > 0)

    def test_logseries_convergence(self):
        # Test for ticket #923
        N = 1000
        np.random.seed(0)

            

Reported by Pylint.

                  def test_logseries_convergence(self):
        # Test for ticket #923
        N = 1000
        np.random.seed(0)
        rvsn = np.random.logseries(0.8, size=N)
        # these two frequency counts should be close to theoretical
        # numbers with this large sample
        # theoretical large N result is 0.49706795
        freq = np.sum(rvsn == 1) / N

            

Reported by Pylint.

                      # Test for ticket #923
        N = 1000
        np.random.seed(0)
        rvsn = np.random.logseries(0.8, size=N)
        # these two frequency counts should be close to theoretical
        # numbers with this large sample
        # theoretical large N result is 0.49706795
        freq = np.sum(rvsn == 1) / N
        msg = f'Frequency was {freq:f}, should be > 0.45'

            

Reported by Pylint.

                                [(1, 1), (2, 2), (3, 3), None],
                  [1, (2, 2), (3, 3), None],
                  [(1, 1), 2, 3, None]]:
            np.random.seed(12345)
            shuffled = list(t)
            random.shuffle(shuffled)
            expected = np.array([t[0], t[3], t[1], t[2]], dtype=object)
            assert_array_equal(np.array(shuffled, dtype=object), expected)


            

Reported by Pylint.

                                [(1, 1), 2, 3, None]]:
            np.random.seed(12345)
            shuffled = list(t)
            random.shuffle(shuffled)
            expected = np.array([t[0], t[3], t[1], t[2]], dtype=object)
            assert_array_equal(np.array(shuffled, dtype=object), expected)

    def test_call_within_randomstate(self):
        # Check that custom RandomState does not call into global state

            

Reported by Pylint.

              
    def test_call_within_randomstate(self):
        # Check that custom RandomState does not call into global state
        m = np.random.RandomState()
        res = np.array([0, 8, 7, 2, 1, 9, 4, 7, 0, 3])
        for i in range(3):
            np.random.seed(i)
            m.seed(4321)
            # If m.state is not honored, the result will change

            

Reported by Pylint.

                      m = np.random.RandomState()
        res = np.array([0, 8, 7, 2, 1, 9, 4, 7, 0, 3])
        for i in range(3):
            np.random.seed(i)
            m.seed(4321)
            # If m.state is not honored, the result will change
            assert_array_equal(m.choice(10, size=10, p=np.ones(10)/10.), res)

    def test_multivariate_normal_size_types(self):

            

Reported by Pylint.

                      return "https://github.com/numpy/numpy/blob/v%s/numpy/%s%s" % (
           numpy.__version__, fn, linespec)

from pygments.lexers import CLexer
from pygments.lexer import inherit, bygroups
from pygments.token import Comment

class NumPyLexer(CLexer):
    name = 'NUMPYLEXER'

            

Reported by Pylint.

                  class PyTypeObject(ctypes.Structure):
        pass

    PyObject._fields_ = [
        ('ob_refcnt', Py_ssize_t),
        ('ob_type', ctypes.POINTER(PyTypeObject)),
    ]



            

Reported by Pylint.

                  ]


    PyTypeObject._fields_ = [
        # varhead
        ('ob_base', PyObject),
        ('ob_size', Py_ssize_t),
        # declaration
        ('tp_name', ctypes.c_char_p),

            

Reported by Pylint.

                  assert 'numpy.core._add_newdocs_scalars' not in sys.modules
    sys.modules['numpy.core._add_newdocs_scalars'] = object()

    import numpy

    # change the __name__ of the scalar types
    for name in [
        'byte', 'short', 'intc', 'int_', 'longlong',
        'ubyte', 'ushort', 'uintc', 'uint', 'ulonglong',

            

Reported by Pylint.

                  assert 'numpy.core._add_newdocs_scalars' not in sys.modules
    sys.modules['numpy.core._add_newdocs_scalars'] = object()

    import numpy

    # change the __name__ of the scalar types
    for name in [
        'byte', 'short', 'intc', 'int_', 'longlong',
        'ubyte', 'ushort', 'uintc', 'uint', 'ulonglong',

            

Reported by Pylint.

                  import numpy

    # change the __name__ of the scalar types
    for name in [
        'byte', 'short', 'intc', 'int_', 'longlong',
        'ubyte', 'ushort', 'uintc', 'uint', 'ulonglong',
        'half', 'single', 'double', 'longdouble',
        'half', 'csingle', 'cdouble', 'clongdouble',
    ]:

            

Reported by Pylint.

              
# General substitutions.
project = 'NumPy'
copyright = '2008-2021, The NumPy community'

# The default replacements for |version| and |release|, also used in various
# other places throughout the built documents.
#
import numpy

            

Reported by Pylint.

                  elif obj is numpy.ndarray:
        return r"core/src/multiarray/arrayobject.c"
    else:
        # todo: come up with a better way to generate these
        return None


def linkcode_resolve(domain, info):
    """

            

Reported by Pylint.

                  for part in fullname.split('.'):
        try:
            obj = getattr(obj, part)
        except Exception:
            return None

    # strip decorators, which would resolve to the source of the decorator
    # possibly an upstream bug in getsourcefile, bpo-1764286
    try:

            

Reported by Pylint.

                  if fn is None:
        try:
            fn = inspect.getsourcefile(obj)
        except Exception:
            fn = None
        if not fn:
            return None

        # Ignore re-exports as their source files are not within the numpy repo

            

Reported by Pylint.

              import sys
from io import StringIO

from plex import Scanner, Str, Lexicon, Opt, Bol, State, AnyChar, TEXT, IGNORE
from plex.traditional import re as Re


class MyScanner(Scanner):
    def __init__(self, info, name='<default>'):

            

Reported by Pylint.

              from io import StringIO

from plex import Scanner, Str, Lexicon, Opt, Bol, State, AnyChar, TEXT, IGNORE
from plex.traditional import re as Re


class MyScanner(Scanner):
    def __init__(self, info, name='<default>'):
        Scanner.__init__(self, self.lexicon, info, name)

            

Reported by Pylint.

                  else:
        nsteps = None

    source = scrub_source(source, nsteps, verbose=True)

    writefo = open(outfilename, 'w')
    writefo.write(source)
    writefo.close()

            

Reported by Pylint.

                  else:
        scanner = scanner_class(info)
    while True:
        value, text = scanner.read()
        if value is None:
            break
        elif value is IGNORE:
            pass
        else:

            

Reported by Pylint.

                      (AnyChar,                               TEXT),
    ])

def scrubFtnlen(source):
    return runScanner(source, LenSubsScanner)[0]

def cleanSource(source):
    # remove whitespace at end of lines
    source = re.sub(r'[\t ]+\n', '\n', source)

            

Reported by Pylint.

              def scrubFtnlen(source):
    return runScanner(source, LenSubsScanner)[0]

def cleanSource(source):
    # remove whitespace at end of lines
    source = re.sub(r'[\t ]+\n', '\n', source)
    # remove comments like .. Scalar Arguments ..
    source = re.sub(r'(?m)^[\t ]*/\* *\.\. .*?\n', '', source)
    # collapse blanks of more than two in-a-row to two

            

Reported by Pylint.

                  def getValue(self):
        q = LineQueue()
        self.flushTo(q)
        s = ''.join(q._queue)
        self.clear()
        return s

class CommentQueue(LineQueue):
    def __init__(self):

            

Reported by Pylint.

                      self.clear()

# This really seems to be about 4x longer than it needs to be
def cleanComments(source):
    lines = LineQueue()
    comments = CommentQueue()
    def isCommentLine(line):
        return line.startswith('/*') and line.endswith('*/\n')


            

Reported by Pylint.

                  comments.flushTo(lines)
    return lines.getValue()

def removeHeader(source):
    lines = LineQueue()

    def LookingForHeader(line):
        m = re.match(r'/\*[^\n]*-- translated', line)
        if m:

            

Reported by Pylint.

                      state = state(line)
    return lines.getValue()

def removeSubroutinePrototypes(source):
    expression = re.compile(
        r'/\* Subroutine \*/^\s*(?:(?:inline|static)\s+){0,2}(?!else|typedef|return)\w+\s+\*?\s*(\w+)\s*\([^0]+\)\s*;?'
    )
    lines = LineQueue()
    for line in StringIO(source):

            

Reported by Pylint.