class RankWarning(UserWarning):
    """Issued by chebfit when the design matrix is rank deficient."""
    pass

#
# Helper functions to convert inputs to 1-D arrays
#
def trimseq(seq):

            

Reported by Pylint.

                      return c


def _pow(mul_f, c, pow, maxpower):
    """
    Helper function used to implement the ``<type>pow`` functions.

    Parameters
    ----------

            

Reported by Pylint.

                      # This can be made more efficient by using powers of two
        # in the usual way.
        prd = c
        for i in range(2, power + 1):
            prd = mul_f(prd, c)
        return prd


def _deprecate_as_int(x, desc):

            

Reported by Pylint.

                  Do not lose the type info if the sequence contains unknown objects.

    """
    if len(seq) == 0:
        return seq
    else:
        for i in range(len(seq) - 1, -1, -1):
            if seq[i] != 0:
                break

            

Reported by Pylint.

              
    if any(a.dtype == np.dtype(object) for a in arrays):
        ret = []
        for a in arrays:
            if a.dtype != np.dtype(object):
                tmp = np.empty(len(a), dtype=np.dtype(object))
                tmp[:] = a[:]
                ret.append(tmp)
            else:

            

Reported by Pylint.

                  else:
        try:
            dtype = np.common_type(*arrays)
        except Exception as e:
            raise ValueError("Coefficient arrays have no common type") from e
        ret = [np.array(a, copy=True, dtype=dtype) for a in arrays]
    return ret



            

Reported by Pylint.

                  return ret


def trimcoef(c, tol=0):
    """
    Remove "small" "trailing" coefficients from a polynomial.

    "Small" means "small in absolute value" and is controlled by the
    parameter `tol`; "trailing" means highest order coefficient(s), e.g., in

            

Reported by Pylint.

              
    [c] = as_series([c])
    [ind] = np.nonzero(np.abs(c) > tol)
    if len(ind) == 0:
        return c[:1]*0
    else:
        return c[:ind[-1] + 1].copy()

def getdomain(x):

            

Reported by Pylint.

                  else:
        return c[:ind[-1] + 1].copy()

def getdomain(x):
    """
    Return a domain suitable for given abscissae.

    Find a domain suitable for a polynomial or Chebyshev series
    defined at the values supplied.

            

Reported by Pylint.

              
    """
    [x] = as_series([x], trim=False)
    if x.dtype.char in np.typecodes['Complex']:
        rmin, rmax = x.real.min(), x.real.max()
        imin, imax = x.imag.min(), x.imag.max()
        return np.array((complex(rmin, imin), complex(rmax, imax)))
    else:
        return np.array((x.min(), x.max()))

            

Reported by Pylint.

              # Its presence/absence is used in subclassing setup in numpy/distutils/core.py.
# However, we need to run the distutils version of sdist, so import that first
# so that it is in sys.modules
import numpy.distutils.command.sdist
import setuptools

# Initialize cmdclass from versioneer
from numpy.distutils.core import numpy_cmdclass
cmdclass = versioneer.get_cmdclass(numpy_cmdclass)

            

Reported by Pylint.

              # However, we need to run the distutils version of sdist, so import that first
# so that it is in sys.modules
import numpy.distutils.command.sdist
import setuptools

# Initialize cmdclass from versioneer
from numpy.distutils.core import numpy_cmdclass
cmdclass = versioneer.get_cmdclass(numpy_cmdclass)


            

Reported by Pylint.

                  def __enter__(self):
        """Concatenate files and remove LICENSES_bundled.txt"""
        with open(self.f1, 'r') as f1:
            self.bsd_text = f1.read()

        with open(self.f1, 'a') as f1:
            with open(self.f2, 'r') as f2:
                self.bundled_text = f2.read()
                f1.write('\n\n')

            

Reported by Pylint.

              
        with open(self.f1, 'a') as f1:
            with open(self.f2, 'r') as f2:
                self.bundled_text = f2.read()
                f1.write('\n\n')
                f1.write(self.bundled_text)

    def __exit__(self, exception_type, exception_value, traceback):
        """Restore content of both files"""

            

Reported by Pylint.

                          return False

        # will print something like '4.2.1\n'
        out = subprocess.run([cc, '-dumpversion'], stdout=subprocess.PIPE,
                             stderr=subprocess.PIPE, universal_newlines=True)
        # -std=c99 is default from this version on
        if LooseVersion(out.stdout) >= LooseVersion('5.0'):
            return False
        return True

            

Reported by Pylint.

              """
DOCLINES = (__doc__ or '').split("\n")

import os
import sys
import subprocess
import textwrap
import warnings
import builtins

            

Reported by Pylint.

              DOCLINES = (__doc__ or '').split("\n")

import os
import sys
import subprocess
import textwrap
import warnings
import builtins
import re

            

Reported by Pylint.

              
import os
import sys
import subprocess
import textwrap
import warnings
import builtins
import re


            

Reported by Pylint.

              
import os
import sys
import subprocess
import textwrap
import warnings
import builtins
import re


            

Reported by Bandit.

              import os
import sys
import subprocess
import textwrap
import warnings
import builtins
import re



            

Reported by Pylint.

                  return tuple(fancy_index)


def _take_along_axis_dispatcher(arr, indices, axis):
    return (arr, indices)


@array_function_dispatch(_take_along_axis_dispatcher)
def take_along_axis(arr, indices, axis):

            

Reported by Pylint.

                  return arr[_make_along_axis_idx(arr_shape, indices, axis)]


def _put_along_axis_dispatcher(arr, indices, values, axis):
    return (arr, indices, values)


@array_function_dispatch(_put_along_axis_dispatcher)
def put_along_axis(arr, indices, values, axis):

            

Reported by Pylint.

                  arr[_make_along_axis_idx(arr_shape, indices, axis)] = values


def _apply_along_axis_dispatcher(func1d, axis, arr, *args, **kwargs):
    return (arr,)


@array_function_dispatch(_apply_along_axis_dispatcher)
def apply_along_axis(func1d, axis, arr, *args, **kwargs):

            

Reported by Pylint.

                  arr[_make_along_axis_idx(arr_shape, indices, axis)] = values


def _apply_along_axis_dispatcher(func1d, axis, arr, *args, **kwargs):
    return (arr,)


@array_function_dispatch(_apply_along_axis_dispatcher)
def apply_along_axis(func1d, axis, arr, *args, **kwargs):

            

Reported by Pylint.

                  arr[_make_along_axis_idx(arr_shape, indices, axis)] = values


def _apply_along_axis_dispatcher(func1d, axis, arr, *args, **kwargs):
    return (arr,)


@array_function_dispatch(_apply_along_axis_dispatcher)
def apply_along_axis(func1d, axis, arr, *args, **kwargs):

            

Reported by Pylint.

                  arr[_make_along_axis_idx(arr_shape, indices, axis)] = values


def _apply_along_axis_dispatcher(func1d, axis, arr, *args, **kwargs):
    return (arr,)


@array_function_dispatch(_apply_along_axis_dispatcher)
def apply_along_axis(func1d, axis, arr, *args, **kwargs):

            

Reported by Pylint.

                  # invoke the function on the first item
    try:
        ind0 = next(inds)
    except StopIteration as e:
        raise ValueError(
            'Cannot apply_along_axis when any iteration dimensions are 0'
        ) from None
    res = asanyarray(func1d(inarr_view[ind0], *args, **kwargs))


            

Reported by Pylint.

                      return res.__array_wrap__(out_arr)


def _apply_over_axes_dispatcher(func, a, axes):
    return (a,)


@array_function_dispatch(_apply_over_axes_dispatcher)
def apply_over_axes(func, a, axes):

            

Reported by Pylint.

                      return res.__array_wrap__(out_arr)


def _apply_over_axes_dispatcher(func, a, axes):
    return (a,)


@array_function_dispatch(_apply_over_axes_dispatcher)
def apply_over_axes(func, a, axes):

            

Reported by Pylint.

                  return val


def _expand_dims_dispatcher(a, axis):
    return (a,)


@array_function_dispatch(_expand_dims_dispatcher)
def expand_dims(a, axis):

            

Reported by Pylint.

              import sys
import copy

from . import __version__

f2py_version = __version__.version
errmess = sys.stderr.write

##################### Definitions ##################

            

Reported by Pylint.

              

def buildcfuncs():
    from .capi_maps import c2capi_map
    for k in c2capi_map.keys():
        m = 'pyarr_from_p_%s1' % k
        cppmacros[
            m] = '#define %s(v) (PyArray_SimpleNewFromData(0,NULL,%s,(char *)v))' % (m, c2capi_map[k])
    k = 'string'

            

Reported by Pylint.

              #         return 1;\\
#     }
# """
# XXX: Note that CNUMFROMARROBJ is identical with NUMFROMARROBJ
# cppmacros['CNUMFROMARROBJ']="""\
# define CNUMFROMARROBJ(typenum,ctype) \\
#     if (PyArray_Check(obj)) arr = (PyArrayObject *)obj;\\
#     else arr = (PyArrayObject *)PyArray_ContiguousFromObject(obj,typenum,0,0);\\
#     if (arr) {\\

            

Reported by Pylint.

              #!/usr/bin/env python3
"""

C declarations, CPP macros, and C functions for f2py2e.
Only required declarations/macros/functions will be used.

Copyright 1999,2000 Pearu Peterson all rights reserved,
Pearu Peterson <pearu@ioc.ee>
Permission to use, modify, and distribute this software is given under the

            

Reported by Pylint.

                  'pyobj_from_float1'] = '#define pyobj_from_float1(v) (PyFloat_FromDouble(v))'
needs['pyobj_from_complex_long_double1'] = ['complex_long_double']
cppmacros[
    'pyobj_from_complex_long_double1'] = '#define pyobj_from_complex_long_double1(v) (PyComplex_FromDoubles(v.r,v.i))'
needs['pyobj_from_complex_double1'] = ['complex_double']
cppmacros[
    'pyobj_from_complex_double1'] = '#define pyobj_from_complex_double1(v) (PyComplex_FromDoubles(v.r,v.i))'
needs['pyobj_from_complex_float1'] = ['complex_float']
cppmacros[

            

Reported by Pylint.

                  'pyobj_from_complex_long_double1'] = '#define pyobj_from_complex_long_double1(v) (PyComplex_FromDoubles(v.r,v.i))'
needs['pyobj_from_complex_double1'] = ['complex_double']
cppmacros[
    'pyobj_from_complex_double1'] = '#define pyobj_from_complex_double1(v) (PyComplex_FromDoubles(v.r,v.i))'
needs['pyobj_from_complex_float1'] = ['complex_float']
cppmacros[
    'pyobj_from_complex_float1'] = '#define pyobj_from_complex_float1(v) (PyComplex_FromDoubles(v.r,v.i))'
needs['pyobj_from_string1'] = ['string']
cppmacros[

            

Reported by Pylint.

                  'pyobj_from_complex_double1'] = '#define pyobj_from_complex_double1(v) (PyComplex_FromDoubles(v.r,v.i))'
needs['pyobj_from_complex_float1'] = ['complex_float']
cppmacros[
    'pyobj_from_complex_float1'] = '#define pyobj_from_complex_float1(v) (PyComplex_FromDoubles(v.r,v.i))'
needs['pyobj_from_string1'] = ['string']
cppmacros[
    'pyobj_from_string1'] = '#define pyobj_from_string1(v) (PyUnicode_FromString((char *)v))'
needs['pyobj_from_string1size'] = ['string']
cppmacros[

            

Reported by Pylint.

                  'pyobj_from_string1'] = '#define pyobj_from_string1(v) (PyUnicode_FromString((char *)v))'
needs['pyobj_from_string1size'] = ['string']
cppmacros[
    'pyobj_from_string1size'] = '#define pyobj_from_string1size(v,len) (PyUnicode_FromStringAndSize((char *)v, len))'
needs['TRYPYARRAYTEMPLATE'] = ['PRINTPYOBJERR']
cppmacros['TRYPYARRAYTEMPLATE'] = """\
/* New SciPy */
#define TRYPYARRAYTEMPLATECHAR case NPY_STRING: *(char *)(PyArray_DATA(arr))=*v; break;
#define TRYPYARRAYTEMPLATELONG case NPY_LONG: *(long *)(PyArray_DATA(arr))=*v; break;

            

Reported by Pylint.

              # define CHECKDIMS(dims,rank) \\
#     for (int i=0;i<(rank);i++)\\
#         if (dims[i]<0) {\\
#             fprintf(stderr,\"Unspecified array argument requires a complete dimension specification.\\n\");\\
#             goto capi_fail;\\
#         }
# """
cppmacros[
    'ARRSIZE'] = '#define ARRSIZE(dims,rank) (_PyArray_multiply_list(dims,rank))'

            

Reported by Pylint.

              
needs['try_pyarr_from_char'] = ['pyobj_from_char1', 'TRYPYARRAYTEMPLATE']
cfuncs[
    'try_pyarr_from_char'] = 'static int try_pyarr_from_char(PyObject* obj,char* v) {\n    TRYPYARRAYTEMPLATE(char,\'c\');\n}\n'
needs['try_pyarr_from_signed_char'] = ['TRYPYARRAYTEMPLATE', 'unsigned_char']
cfuncs[
    'try_pyarr_from_unsigned_char'] = 'static int try_pyarr_from_unsigned_char(PyObject* obj,unsigned_char* v) {\n    TRYPYARRAYTEMPLATE(unsigned_char,\'b\');\n}\n'
needs['try_pyarr_from_signed_char'] = ['TRYPYARRAYTEMPLATE', 'signed_char']
cfuncs[

            

Reported by Pylint.

              
SEED_NONE = None
SEED_INT = 4579435749574957634658964293569
SEED_ARR: np.ndarray[Any, np.dtype[np.int64]] = np.array([1, 2, 3, 4], dtype=np.int64)
SEED_ARRLIKE: List[int] = [1, 2, 3, 4]
SEED_SEED_SEQ: np.random.SeedSequence = np.random.SeedSequence(0)
SEED_MT19937: np.random.MT19937 = np.random.MT19937(0)
SEED_PCG64: np.random.PCG64 = np.random.PCG64(0)
SEED_PHILOX: np.random.Philox = np.random.Philox(0)

            

Reported by Pylint.

              
def_gen: np.random.Generator = np.random.default_rng()

D_arr_0p1: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.1])
D_arr_0p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.5])
D_arr_0p9: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.9])
D_arr_1p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([1.5])
I_arr_10: np.ndarray[Any, np.dtype[np.int_]] = np.array([10], dtype=np.int_)
I_arr_20: np.ndarray[Any, np.dtype[np.int_]] = np.array([20], dtype=np.int_)

            

Reported by Pylint.

              def_gen: np.random.Generator = np.random.default_rng()

D_arr_0p1: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.1])
D_arr_0p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.5])
D_arr_0p9: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.9])
D_arr_1p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([1.5])
I_arr_10: np.ndarray[Any, np.dtype[np.int_]] = np.array([10], dtype=np.int_)
I_arr_20: np.ndarray[Any, np.dtype[np.int_]] = np.array([20], dtype=np.int_)
D_arr_like_0p1: List[float] = [0.1]

            

Reported by Pylint.

              
D_arr_0p1: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.1])
D_arr_0p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.5])
D_arr_0p9: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.9])
D_arr_1p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([1.5])
I_arr_10: np.ndarray[Any, np.dtype[np.int_]] = np.array([10], dtype=np.int_)
I_arr_20: np.ndarray[Any, np.dtype[np.int_]] = np.array([20], dtype=np.int_)
D_arr_like_0p1: List[float] = [0.1]
D_arr_like_0p5: List[float] = [0.5]

            

Reported by Pylint.

              D_arr_0p1: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.1])
D_arr_0p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.5])
D_arr_0p9: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.9])
D_arr_1p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([1.5])
I_arr_10: np.ndarray[Any, np.dtype[np.int_]] = np.array([10], dtype=np.int_)
I_arr_20: np.ndarray[Any, np.dtype[np.int_]] = np.array([20], dtype=np.int_)
D_arr_like_0p1: List[float] = [0.1]
D_arr_like_0p5: List[float] = [0.5]
D_arr_like_0p9: List[float] = [0.9]

            

Reported by Pylint.

              D_arr_0p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.5])
D_arr_0p9: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.9])
D_arr_1p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([1.5])
I_arr_10: np.ndarray[Any, np.dtype[np.int_]] = np.array([10], dtype=np.int_)
I_arr_20: np.ndarray[Any, np.dtype[np.int_]] = np.array([20], dtype=np.int_)
D_arr_like_0p1: List[float] = [0.1]
D_arr_like_0p5: List[float] = [0.5]
D_arr_like_0p9: List[float] = [0.9]
D_arr_like_1p5: List[float] = [1.5]

            

Reported by Pylint.

              D_arr_0p9: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.9])
D_arr_1p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([1.5])
I_arr_10: np.ndarray[Any, np.dtype[np.int_]] = np.array([10], dtype=np.int_)
I_arr_20: np.ndarray[Any, np.dtype[np.int_]] = np.array([20], dtype=np.int_)
D_arr_like_0p1: List[float] = [0.1]
D_arr_like_0p5: List[float] = [0.5]
D_arr_like_0p9: List[float] = [0.9]
D_arr_like_1p5: List[float] = [1.5]
I_arr_like_10: List[int] = [10]

            

Reported by Pylint.

              I_arr_like_10: List[int] = [10]
I_arr_like_20: List[int] = [20]
D_2D_like: List[List[float]] = [[1, 2], [2, 3], [3, 4], [4, 5.1]]
D_2D: np.ndarray[Any, np.dtype[np.float64]] = np.array(D_2D_like)

S_out: np.ndarray[Any, np.dtype[np.float32]] = np.empty(1, dtype=np.float32)
D_out: np.ndarray[Any, np.dtype[np.float64]] = np.empty(1)

def_gen.standard_normal()

            

Reported by Pylint.

              D_2D_like: List[List[float]] = [[1, 2], [2, 3], [3, 4], [4, 5.1]]
D_2D: np.ndarray[Any, np.dtype[np.float64]] = np.array(D_2D_like)

S_out: np.ndarray[Any, np.dtype[np.float32]] = np.empty(1, dtype=np.float32)
D_out: np.ndarray[Any, np.dtype[np.float64]] = np.empty(1)

def_gen.standard_normal()
def_gen.standard_normal(dtype=np.float32)
def_gen.standard_normal(dtype="float32")

            

Reported by Pylint.

              D_2D: np.ndarray[Any, np.dtype[np.float64]] = np.array(D_2D_like)

S_out: np.ndarray[Any, np.dtype[np.float32]] = np.empty(1, dtype=np.float32)
D_out: np.ndarray[Any, np.dtype[np.float64]] = np.empty(1)

def_gen.standard_normal()
def_gen.standard_normal(dtype=np.float32)
def_gen.standard_normal(dtype="float32")
def_gen.standard_normal(dtype="double")

            

Reported by Pylint.

              
# Time structures

td % td
td % AR2
AR2 % td

divmod(td, td)
divmod(td, AR2)

            

Reported by Pylint.

              # Time structures

td % td
td % AR2
AR2 % td

divmod(td, td)
divmod(td, AR2)
divmod(AR2, td)

            

Reported by Pylint.

              
td % td
td % AR2
AR2 % td

divmod(td, td)
divmod(td, AR2)
divmod(AR2, td)


            

Reported by Pylint.

              
# Bool

b_ % b
b_ % i
b_ % f
b_ % b_
b_ % i8
b_ % u8

            

Reported by Pylint.

              # Bool

b_ % b
b_ % i
b_ % f
b_ % b_
b_ % i8
b_ % u8
b_ % f8

            

Reported by Pylint.

              
b_ % b
b_ % i
b_ % f
b_ % b_
b_ % i8
b_ % u8
b_ % f8
b_ % AR

            

Reported by Pylint.

              b_ % b
b_ % i
b_ % f
b_ % b_
b_ % i8
b_ % u8
b_ % f8
b_ % AR


            

Reported by Pylint.

              b_ % i
b_ % f
b_ % b_
b_ % i8
b_ % u8
b_ % f8
b_ % AR

divmod(b_, b)

            

Reported by Pylint.

              b_ % f
b_ % b_
b_ % i8
b_ % u8
b_ % f8
b_ % AR

divmod(b_, b)
divmod(b_, i)

            

Reported by Pylint.

              b_ % b_
b_ % i8
b_ % u8
b_ % f8
b_ % AR

divmod(b_, b)
divmod(b_, i)
divmod(b_, f)

            

Reported by Pylint.

              from numpy.core.numeric import asarray, asanyarray, isnan, zeros
from numpy.core.overrides import set_module
from numpy.core import overrides
from .ufunclike import isneginf, isposinf


array_function_dispatch = functools.partial(
    overrides.array_function_dispatch, module='numpy')


            

Reported by Pylint.

                  return min(intersection, key=_typecodes_by_elsize.index)


def _asfarray_dispatcher(a, dtype=None):
    return (a,)


@array_function_dispatch(_asfarray_dispatcher)
def asfarray(a, dtype=_nx.float_):

            

Reported by Pylint.

                  return f.max, f.min


def _nan_to_num_dispatcher(x, copy=None, nan=None, posinf=None, neginf=None):
    return (x,)


@array_function_dispatch(_nan_to_num_dispatcher)
def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None):

            

Reported by Pylint.

                  return f.max, f.min


def _nan_to_num_dispatcher(x, copy=None, nan=None, posinf=None, neginf=None):
    return (x,)


@array_function_dispatch(_nan_to_num_dispatcher)
def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None):

            

Reported by Pylint.

                  return f.max, f.min


def _nan_to_num_dispatcher(x, copy=None, nan=None, posinf=None, neginf=None):
    return (x,)


@array_function_dispatch(_nan_to_num_dispatcher)
def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None):

            

Reported by Pylint.

                  return f.max, f.min


def _nan_to_num_dispatcher(x, copy=None, nan=None, posinf=None, neginf=None):
    return (x,)


@array_function_dispatch(_nan_to_num_dispatcher)
def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None):

            

Reported by Pylint.

                  if not issubclass(xtype, _nx.inexact):
        return x[()] if isscalar else x

    iscomplex = issubclass(xtype, _nx.complexfloating)

    dest = (x.real, x.imag) if iscomplex else (x,)
    maxf, minf = _getmaxmin(x.real.dtype)
    if posinf is not None:
        maxf = posinf

            

Reported by Pylint.

              
#-----------------------------------------------------------------------------

def _real_if_close_dispatcher(a, tol=None):
    return (a,)


@array_function_dispatch(_real_if_close_dispatcher)
def real_if_close(a, tol=100):

            

Reported by Pylint.

                  overrides.array_function_dispatch, module='numpy')


_typecodes_by_elsize = 'GDFgdfQqLlIiHhBb?'


@set_module('numpy')
def mintypecode(typechars, typeset='GDFgdf', default='d'):
    """

            

Reported by Pylint.

                  return min(intersection, key=_typecodes_by_elsize.index)


def _asfarray_dispatcher(a, dtype=None):
    return (a,)


@array_function_dispatch(_asfarray_dispatcher)
def asfarray(a, dtype=_nx.float_):

            

Reported by Pylint.

              import numpy as np
from numpy.testing import assert_array_equal, assert_equal
from numpy.f2py.crackfortran import markinnerspaces
from . import util
from numpy.f2py import crackfortran
import textwrap


class TestNoSpace(util.F2PyTest):

            

Reported by Pylint.

              import numpy as np
from numpy.testing import assert_array_equal, assert_equal
from numpy.f2py.crackfortran import markinnerspaces
from . import util
from numpy.f2py import crackfortran
import textwrap


class TestNoSpace(util.F2PyTest):

            

Reported by Pylint.

              from numpy.testing import assert_array_equal, assert_equal
from numpy.f2py.crackfortran import markinnerspaces
from . import util
from numpy.f2py import crackfortran
import textwrap


class TestNoSpace(util.F2PyTest):
    # issue gh-15035: add handling for endsubroutine, endfunction with no space

            

Reported by Pylint.

              from numpy.f2py.crackfortran import markinnerspaces
from . import util
from numpy.f2py import crackfortran
import textwrap


class TestNoSpace(util.F2PyTest):
    # issue gh-15035: add handling for endsubroutine, endfunction with no space
    # between "end" and the block name

            

Reported by Pylint.

              import textwrap


class TestNoSpace(util.F2PyTest):
    # issue gh-15035: add handling for endsubroutine, endfunction with no space
    # between "end" and the block name
    code = """
        subroutine subb(k)
          real(8), intent(inout) :: k(:)

            

Reported by Pylint.

              import textwrap


class TestNoSpace(util.F2PyTest):
    # issue gh-15035: add handling for endsubroutine, endfunction with no space
    # between "end" and the block name
    code = """
        subroutine subb(k)
          real(8), intent(inout) :: k(:)

            

Reported by Pylint.

                      endfunction
    """

    def test_module(self):
        k = np.array([1, 2, 3], dtype=np.float64)
        w = np.array([1, 2, 3], dtype=np.float64)
        self.module.subb(k)
        assert_array_equal(k, w + 1)
        self.module.subc([w, k])

            

Reported by Pylint.

              
    def test_module(self):
        k = np.array([1, 2, 3], dtype=np.float64)
        w = np.array([1, 2, 3], dtype=np.float64)
        self.module.subb(k)
        assert_array_equal(k, w + 1)
        self.module.subc([w, k])
        assert_array_equal(k, w + 1)
        assert self.module.t0(23) == b'2'

            

Reported by Pylint.

                      assert_array_equal(k, w + 1)
        self.module.subc([w, k])
        assert_array_equal(k, w + 1)
        assert self.module.t0(23) == b'2'


class TestPublicPrivate():
    def test_defaultPrivate(self, tmp_path):
        f_path = tmp_path / "mod.f90"

            

Reported by Bandit.

                      assert self.module.t0(23) == b'2'


class TestPublicPrivate():
    def test_defaultPrivate(self, tmp_path):
        f_path = tmp_path / "mod.f90"
        with f_path.open('w') as ff:
            ff.write(textwrap.dedent("""\
            module foo

            

Reported by Pylint.

              
import pickle

import pytest
import numpy as np

_ArrayMemoryError = np.core._exceptions._ArrayMemoryError
_UFuncNoLoopError = np.core._exceptions._UFuncNoLoopError


            

Reported by Pylint.

              import pytest
import numpy as np

_ArrayMemoryError = np.core._exceptions._ArrayMemoryError
_UFuncNoLoopError = np.core._exceptions._UFuncNoLoopError

class TestArrayMemoryError:
    def test_pickling(self):
        """ Test that _ArrayMemoryError can be pickled """

            

Reported by Pylint.

              import pytest
import numpy as np

_ArrayMemoryError = np.core._exceptions._ArrayMemoryError
_UFuncNoLoopError = np.core._exceptions._UFuncNoLoopError

class TestArrayMemoryError:
    def test_pickling(self):
        """ Test that _ArrayMemoryError can be pickled """

            

Reported by Pylint.

              import numpy as np

_ArrayMemoryError = np.core._exceptions._ArrayMemoryError
_UFuncNoLoopError = np.core._exceptions._UFuncNoLoopError

class TestArrayMemoryError:
    def test_pickling(self):
        """ Test that _ArrayMemoryError can be pickled """
        error = _ArrayMemoryError((1023,), np.dtype(np.uint8))

            

Reported by Pylint.

              import numpy as np

_ArrayMemoryError = np.core._exceptions._ArrayMemoryError
_UFuncNoLoopError = np.core._exceptions._UFuncNoLoopError

class TestArrayMemoryError:
    def test_pickling(self):
        """ Test that _ArrayMemoryError can be pickled """
        error = _ArrayMemoryError((1023,), np.dtype(np.uint8))

            

Reported by Pylint.

                  def test_pickling(self):
        """ Test that _ArrayMemoryError can be pickled """
        error = _ArrayMemoryError((1023,), np.dtype(np.uint8))
        res = pickle.loads(pickle.dumps(error))
        assert res._total_size == error._total_size

    def test_str(self):
        e = _ArrayMemoryError((1023,), np.dtype(np.uint8))
        str(e)  # not crashing is enough

            

Reported by Bandit.

                      """ Test that _ArrayMemoryError can be pickled """
        error = _ArrayMemoryError((1023,), np.dtype(np.uint8))
        res = pickle.loads(pickle.dumps(error))
        assert res._total_size == error._total_size

    def test_str(self):
        e = _ArrayMemoryError((1023,), np.dtype(np.uint8))
        str(e)  # not crashing is enough


            

Reported by Pylint.

                      """ Test that _ArrayMemoryError can be pickled """
        error = _ArrayMemoryError((1023,), np.dtype(np.uint8))
        res = pickle.loads(pickle.dumps(error))
        assert res._total_size == error._total_size

    def test_str(self):
        e = _ArrayMemoryError((1023,), np.dtype(np.uint8))
        str(e)  # not crashing is enough


            

Reported by Pylint.

                  # testing these properties is easier than testing the full string repr
    def test__size_to_string(self):
        """ Test e._size_to_string """
        f = _ArrayMemoryError._size_to_string
        Ki = 1024
        assert f(0) == '0 bytes'
        assert f(1) == '1 bytes'
        assert f(1023) == '1023 bytes'
        assert f(Ki) == '1.00 KiB'

            

Reported by Pylint.

                  def test__total_size(self):
        """ Test e._total_size """
        e = _ArrayMemoryError((1,), np.dtype(np.uint8))
        assert e._total_size == 1

        e = _ArrayMemoryError((2, 4), np.dtype((np.uint64, 16)))
        assert e._total_size == 1024



            

Reported by Pylint.

                      "Test validate no names"
        namelist = None
        validator = NameValidator()
        assert_(validator(namelist) is None)
        assert_equal(validator(namelist, nbfields=3), ['f0', 'f1', 'f2'])

# -----------------------------------------------------------------------------



            

Reported by Pylint.

                  def test_creation(self):
        "Test creation of a StringConverter"
        converter = StringConverter(int, -99999)
        assert_equal(converter._status, 1)
        assert_equal(converter.default, -99999)

    def test_upgrade(self):
        "Tests the upgrade method."


            

Reported by Pylint.

                      "Tests the upgrade method."

        converter = StringConverter()
        assert_equal(converter._status, 0)

        # test int
        assert_equal(converter.upgrade('0'), 0)
        assert_equal(converter._status, 1)


            

Reported by Pylint.

              
        # test int
        assert_equal(converter.upgrade('0'), 0)
        assert_equal(converter._status, 1)

        # On systems where long defaults to 32-bit, the statuses will be
        # offset by one, so we check for this here.
        import numpy.core.numeric as nx
        status_offset = int(nx.dtype(nx.int_).itemsize < nx.dtype(nx.int64).itemsize)

            

Reported by Pylint.

              
        # test int > 2**32
        assert_equal(converter.upgrade('17179869184'), 17179869184)
        assert_equal(converter._status, 1 + status_offset)

        # test float
        assert_allclose(converter.upgrade('0.'), 0.0)
        assert_equal(converter._status, 2 + status_offset)


            

Reported by Pylint.

              
        # test float
        assert_allclose(converter.upgrade('0.'), 0.0)
        assert_equal(converter._status, 2 + status_offset)

        # test complex
        assert_equal(converter.upgrade('0j'), complex('0j'))
        assert_equal(converter._status, 3 + status_offset)


            

Reported by Pylint.

              
        # test complex
        assert_equal(converter.upgrade('0j'), complex('0j'))
        assert_equal(converter._status, 3 + status_offset)

        # test str
        # note that the longdouble type has been skipped, so the
        # _status increases by 2. Everything should succeed with
        # unicode conversion (8).

            

Reported by Pylint.

                      # unicode conversion (8).
        for s in ['a', b'a']:
            res = converter.upgrade(s)
            assert_(type(res) is str)
            assert_equal(res, 'a')
            assert_equal(converter._status, 8 + status_offset)

    def test_missing(self):
        "Tests the use of missing values."

            

Reported by Pylint.

                          res = converter.upgrade(s)
            assert_(type(res) is str)
            assert_equal(res, 'a')
            assert_equal(converter._status, 8 + status_offset)

    def test_missing(self):
        "Tests the use of missing values."
        converter = StringConverter(missing_values=('missing',
                                                    'missed'))

            

Reported by Pylint.

                  def test_upgrademapper(self):
        "Tests updatemapper"
        dateparser = _bytes_to_date
        _original_mapper = StringConverter._mapper[:]
        try:
            StringConverter.upgrade_mapper(dateparser, date(2000, 1, 1))
            convert = StringConverter(dateparser, date(2000, 1, 1))
            test = convert('2001-01-01')
            assert_equal(test, date(2001, 1, 1))

            

Reported by Pylint.