import os
import gc
import weakref
import pytest
from contextlib import contextmanager

from numpy.compat import pickle

import pathlib

            

Reported by Pylint.

              from decimal import Decimal

import numpy as np
import numpy.core._multiarray_tests as _multiarray_tests
from numpy.core._rational_tests import rational
from numpy.testing import (
    assert_, assert_raises, assert_warns, assert_equal, assert_almost_equal,
    assert_array_equal, assert_raises_regex, assert_array_almost_equal,
    assert_allclose, IS_PYPY, IS_PYSTON, HAS_REFCOUNT, assert_array_less,

            

Reported by Pylint.

              
import numpy as np
import numpy.core._multiarray_tests as _multiarray_tests
from numpy.core._rational_tests import rational
from numpy.testing import (
    assert_, assert_raises, assert_warns, assert_equal, assert_almost_equal,
    assert_array_equal, assert_raises_regex, assert_array_almost_equal,
    assert_allclose, IS_PYPY, IS_PYSTON, HAS_REFCOUNT, assert_array_less,
    runstring, temppath, suppress_warnings, break_cycles,

            

Reported by Pylint.

                  size = functools.reduce(operator.mul, shape) * dtype.itemsize
    buf = np.empty(size + 2*align + 1, np.uint8)

    ptr = buf.__array_interface__['data'][0]
    offset = ptr % align
    if offset != 0:
        offset = align - offset
    if (ptr % (2*align)) == 0:
        offset += align

            

Reported by Pylint.

                      # Test that the writeable flag can be changed for an array wrapping
        # low level C-data, but not owning its data.
        # Also see that this is deprecated to change from python.
        from numpy.core._multiarray_tests import get_c_wrapping_array

        arr_writeable = get_c_wrapping_array(True)
        assert not arr_writeable.flags.owndata
        assert arr_writeable.flags.writeable
        view = arr_writeable[...]

            

Reported by Pylint.

                      b = np.array([b'done'])

        class bad_sequence:
            def __getitem__(self): pass
            def __len__(self): raise RuntimeError

        assert_raises(ValueError, operator.setitem, u, 0, [])
        assert_raises(ValueError, operator.setitem, b, 0, [])


            

Reported by Pylint.

                                           [False],
                             [True]])
        for _ax in [0, None]:
            assert_equal(a.all(axis=_ax, where=wh_lower),
                        np.all(a[wh_lower[:,0],:], axis=_ax))
            assert_equal(np.all(a, axis=_ax, where=wh_lower),
                         a[wh_lower[:,0],:].all(axis=_ax))

        assert_equal(a.all(where=wh_full), True)

            

Reported by Pylint.

                          assert_equal(np.all(a, axis=_ax, where=wh_lower),
                         a[wh_lower[:,0],:].all(axis=_ax))

        assert_equal(a.all(where=wh_full), True)
        assert_equal(np.all(a, where=wh_full), True)
        assert_equal(a.all(where=False), True)
        assert_equal(np.all(a, where=False), True)

    def test_any_where(self):

            

Reported by Pylint.

              
        assert_equal(a.all(where=wh_full), True)
        assert_equal(np.all(a, where=wh_full), True)
        assert_equal(a.all(where=False), True)
        assert_equal(np.all(a, where=False), True)

    def test_any_where(self):
        a = np.array([[True, False, True],
                      [False, False, False],

            

Reported by Pylint.

                                            [True],
                              [False]])
        for _ax in [0, None]:
            assert_equal(a.any(axis=_ax, where=wh_middle),
                         np.any(a[wh_middle[:,0],:], axis=_ax))
            assert_equal(np.any(a, axis=_ax, where=wh_middle),
                         a[wh_middle[:,0],:].any(axis=_ax))
        assert_equal(a.any(where=wh_full), False)
        assert_equal(np.any(a, where=wh_full), False)

            

Reported by Pylint.

              philox = np.random.Philox()
seedless_seq = np.random.bit_generator.SeedlessSeedSequence()

reveal_type(def_rng)  # E: numpy.random._generator.Generator
reveal_type(mt19937)  # E: numpy.random._mt19937.MT19937
reveal_type(pcg64)  # E: numpy.random._pcg64.PCG64
reveal_type(sfc64)  # E: numpy.random._sfc64.SFC64
reveal_type(philox)  # E: numpy.random._philox.Philox
reveal_type(seed_seq)  # E: numpy.random.bit_generator.SeedSequence

            

Reported by Pylint.

              seedless_seq = np.random.bit_generator.SeedlessSeedSequence()

reveal_type(def_rng)  # E: numpy.random._generator.Generator
reveal_type(mt19937)  # E: numpy.random._mt19937.MT19937
reveal_type(pcg64)  # E: numpy.random._pcg64.PCG64
reveal_type(sfc64)  # E: numpy.random._sfc64.SFC64
reveal_type(philox)  # E: numpy.random._philox.Philox
reveal_type(seed_seq)  # E: numpy.random.bit_generator.SeedSequence
reveal_type(seedless_seq)  # E: numpy.random.bit_generator.SeedlessSeedSequence

            

Reported by Pylint.

              
reveal_type(def_rng)  # E: numpy.random._generator.Generator
reveal_type(mt19937)  # E: numpy.random._mt19937.MT19937
reveal_type(pcg64)  # E: numpy.random._pcg64.PCG64
reveal_type(sfc64)  # E: numpy.random._sfc64.SFC64
reveal_type(philox)  # E: numpy.random._philox.Philox
reveal_type(seed_seq)  # E: numpy.random.bit_generator.SeedSequence
reveal_type(seedless_seq)  # E: numpy.random.bit_generator.SeedlessSeedSequence


            

Reported by Pylint.

              reveal_type(def_rng)  # E: numpy.random._generator.Generator
reveal_type(mt19937)  # E: numpy.random._mt19937.MT19937
reveal_type(pcg64)  # E: numpy.random._pcg64.PCG64
reveal_type(sfc64)  # E: numpy.random._sfc64.SFC64
reveal_type(philox)  # E: numpy.random._philox.Philox
reveal_type(seed_seq)  # E: numpy.random.bit_generator.SeedSequence
reveal_type(seedless_seq)  # E: numpy.random.bit_generator.SeedlessSeedSequence

mt19937_jumped = mt19937.jumped()

            

Reported by Pylint.

              reveal_type(mt19937)  # E: numpy.random._mt19937.MT19937
reveal_type(pcg64)  # E: numpy.random._pcg64.PCG64
reveal_type(sfc64)  # E: numpy.random._sfc64.SFC64
reveal_type(philox)  # E: numpy.random._philox.Philox
reveal_type(seed_seq)  # E: numpy.random.bit_generator.SeedSequence
reveal_type(seedless_seq)  # E: numpy.random.bit_generator.SeedlessSeedSequence

mt19937_jumped = mt19937.jumped()
mt19937_jumped3 = mt19937.jumped(3)

            

Reported by Pylint.

              reveal_type(pcg64)  # E: numpy.random._pcg64.PCG64
reveal_type(sfc64)  # E: numpy.random._sfc64.SFC64
reveal_type(philox)  # E: numpy.random._philox.Philox
reveal_type(seed_seq)  # E: numpy.random.bit_generator.SeedSequence
reveal_type(seedless_seq)  # E: numpy.random.bit_generator.SeedlessSeedSequence

mt19937_jumped = mt19937.jumped()
mt19937_jumped3 = mt19937.jumped(3)
mt19937_raw = mt19937.random_raw()

            

Reported by Pylint.

              reveal_type(sfc64)  # E: numpy.random._sfc64.SFC64
reveal_type(philox)  # E: numpy.random._philox.Philox
reveal_type(seed_seq)  # E: numpy.random.bit_generator.SeedSequence
reveal_type(seedless_seq)  # E: numpy.random.bit_generator.SeedlessSeedSequence

mt19937_jumped = mt19937.jumped()
mt19937_jumped3 = mt19937.jumped(3)
mt19937_raw = mt19937.random_raw()
mt19937_raw_arr = mt19937.random_raw(5)

            

Reported by Pylint.

              mt19937_raw = mt19937.random_raw()
mt19937_raw_arr = mt19937.random_raw(5)

reveal_type(mt19937_jumped)  # E: numpy.random._mt19937.MT19937
reveal_type(mt19937_jumped3)  # E: numpy.random._mt19937.MT19937
reveal_type(mt19937_raw)  # E: int
reveal_type(mt19937_raw_arr)  # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[numpy.typing._64Bit]]]
reveal_type(mt19937.lock)  # E: threading.Lock


            

Reported by Pylint.

              mt19937_raw_arr = mt19937.random_raw(5)

reveal_type(mt19937_jumped)  # E: numpy.random._mt19937.MT19937
reveal_type(mt19937_jumped3)  # E: numpy.random._mt19937.MT19937
reveal_type(mt19937_raw)  # E: int
reveal_type(mt19937_raw_arr)  # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[numpy.typing._64Bit]]]
reveal_type(mt19937.lock)  # E: threading.Lock

pcg64_jumped = pcg64.jumped()

            

Reported by Pylint.

              
reveal_type(mt19937_jumped)  # E: numpy.random._mt19937.MT19937
reveal_type(mt19937_jumped3)  # E: numpy.random._mt19937.MT19937
reveal_type(mt19937_raw)  # E: int
reveal_type(mt19937_raw_arr)  # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[numpy.typing._64Bit]]]
reveal_type(mt19937.lock)  # E: threading.Lock

pcg64_jumped = pcg64.jumped()
pcg64_jumped3 = pcg64.jumped(3)

            

Reported by Pylint.

              # pylint: disable-msg=W0400,W0511,W0611,W0612,W0614,R0201,E1102
"""Tests suite for MaskedArray & subclassing.

:author: Pierre Gerard-Marchant
:contact: pierregm_at_uga_dot_edu
"""
__author__ = "Pierre GF Gerard-Marchant"

import sys

            

Reported by Pylint.

              import operator
import itertools
import textwrap
import pytest

from functools import reduce


import numpy as np

            

Reported by Pylint.

              
    def test_concatenate_flexible(self):
        # Tests the concatenation on flexible arrays.
        data = masked_array(list(zip(np.random.rand(10),
                                     np.arange(10))),
                            dtype=[('a', float), ('b', int)])

        test = concatenate([data[:5], data[5:]])
        assert_equal_records(test, data)

            

Reported by Pylint.

              
    def test_unknown_keyword_parameter(self):
        with pytest.raises(TypeError, match="unexpected keyword argument"):
            MaskedArray([1, 2, 3], maks=[0, 1, 0])  # `mask` is misspelled.

    def test_asarray(self):
        (x, y, a10, m1, m2, xm, ym, z, zm, xf) = self.d
        xm.fill_value = -9999
        xm._hardmask = True

            

Reported by Pylint.

                      x = array([1., 2., 3., 4., 5.])
        c = array([1, 1, 1, 0, 0])
        x[2] = masked
        z = where(c, x, -x)
        assert_equal(z, [1., 2., 0., -4., -5])
        c[0] = masked
        z = where(c, x, -x)
        assert_equal(z, [1., 2., 0., -4., -5])
        assert_(z[0] is masked)

            

Reported by Pylint.

                      z = where(c, x, -x)
        assert_equal(z, [1., 2., 0., -4., -5])
        c[0] = masked
        z = where(c, x, -x)
        assert_equal(z, [1., 2., 0., -4., -5])
        assert_(z[0] is masked)
        assert_(z[1] is not masked)
        assert_(z[2] is masked)


            

Reported by Pylint.

                      assert_equal(a._optinfo["key"], np.exp(a)._optinfo["key"])
        assert_equal(a._optinfo["key"], np.abs(a)._optinfo["key"])
        assert_equal(a._optinfo["key"], array(a, copy=True)._optinfo["key"])
        assert_equal(a._optinfo["key"], np.zeros_like(a)._optinfo["key"])

    def test_fancy_printoptions(self):
        # Test printing a masked array w/ fancy dtype.
        fancydtype = np.dtype([('x', int), ('y', [('t', int), ('s', float)])])
        test = array([(1, (2, 3.0)), (4, (5, 6.0))],

            

Reported by Pylint.

                                      mask=[[0, 1], [1, 0]], dtype=float)
        assert_equal(test, control)
        assert_equal(test.dtype, control.dtype)
        assert_equal(test.mask, control.mask)
        # On masked array with nested structure
        ndtype = [('a', int), ('b', [('ba', int), ('bb', float)])]
        a = array([(1, (1, 1.1)), (2, (2, 2.2))],
                  mask=[(0, (1, 0)), (1, (0, 1))], dtype=ndtype)
        test = flatten_structured_array(a)

            

Reported by Pylint.

                                      mask=[[0, 1], [1, 0]], dtype=float)
        assert_equal(test, control)
        assert_equal(test.dtype, control.dtype)
        assert_equal(test.mask, control.mask)
        # On masked array with nested structure
        ndtype = [('a', int), ('b', [('ba', int), ('bb', float)])]
        a = array([(1, (1, 1.1)), (2, (2, 2.2))],
                  mask=[(0, (1, 0)), (1, (0, 1))], dtype=ndtype)
        test = flatten_structured_array(a)

            

Reported by Pylint.

                                      mask=[[0, 1, 0], [1, 0, 1]], dtype=float)
        assert_equal(test, control)
        assert_equal(test.dtype, control.dtype)
        assert_equal(test.mask, control.mask)
        # Keeping the initial shape
        ndtype = [('a', int), ('b', float)]
        a = np.array([[(1, 1), ], [(2, 2), ]], dtype=ndtype)
        test = flatten_structured_array(a)
        control = np.array([[[1., 1.], ], [[2., 2.], ]], dtype=float)

            

Reported by Pylint.

              import warnings
import fnmatch
import itertools
import pytest
import sys
import os
from fractions import Fraction
from functools import reduce


            

Reported by Pylint.

              
class TestConstants:
    def test_pi(self):
        assert_allclose(ncu.pi, 3.141592653589793, 1e-15)

    def test_e(self):
        assert_allclose(ncu.e, 2.718281828459045, 1e-15)

    def test_euler_gamma(self):

            

Reported by Pylint.

                      with suppress_warnings() as sup:
            sup.filter(RuntimeWarning, "invalid value encountered in floor_divide")
            div = np.floor_divide(fnan, fone)
            assert(np.isnan(div)), "dt: %s, div: %s" % (dt, div)
            div = np.floor_divide(fone, fnan)
            assert(np.isnan(div)), "dt: %s, div: %s" % (dt, div)
            div = np.floor_divide(fnan, fzer)
            assert(np.isnan(div)), "dt: %s, div: %s" % (dt, div)
        # verify 1.0//0.0 computations return inf

            

Reported by Pylint.

                          div = np.floor_divide(fnan, fone)
            assert(np.isnan(div)), "dt: %s, div: %s" % (dt, div)
            div = np.floor_divide(fone, fnan)
            assert(np.isnan(div)), "dt: %s, div: %s" % (dt, div)
            div = np.floor_divide(fnan, fzer)
            assert(np.isnan(div)), "dt: %s, div: %s" % (dt, div)
        # verify 1.0//0.0 computations return inf
        with np.errstate(divide='ignore'):
            z = np.floor_divide(y, x)

            

Reported by Pylint.

                          div = np.floor_divide(fone, fnan)
            assert(np.isnan(div)), "dt: %s, div: %s" % (dt, div)
            div = np.floor_divide(fnan, fzer)
            assert(np.isnan(div)), "dt: %s, div: %s" % (dt, div)
        # verify 1.0//0.0 computations return inf
        with np.errstate(divide='ignore'):
            z = np.floor_divide(y, x)
            assert_(np.isinf(z).all())


            

Reported by Pylint.

                      y **= 2
        assert_equal(y, [1., 4., 9.])
        assert_almost_equal(x**(-1), [1., 0.5, 1./3])
        assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)])

        for out, inp, msg in _gen_alignment_data(dtype=np.float32,
                                                 type='unary',
                                                 max_size=11):
            exp = [ncu.sqrt(i) for i in inp]

            

Reported by Pylint.

                      y **= 2
        assert_equal(y, [1., 4., 9.])
        assert_almost_equal(x**(-1), [1., 0.5, 1./3])
        assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)])

        for out, inp, msg in _gen_alignment_data(dtype=np.float32,
                                                 type='unary',
                                                 max_size=11):
            exp = [ncu.sqrt(i) for i in inp]

            

Reported by Pylint.

                      for out, inp, msg in _gen_alignment_data(dtype=np.float32,
                                                 type='unary',
                                                 max_size=11):
            exp = [ncu.sqrt(i) for i in inp]
            assert_almost_equal(inp**(0.5), exp, err_msg=msg)
            np.sqrt(inp, out=out)
            assert_equal(out, exp, err_msg=msg)

        for out, inp, msg in _gen_alignment_data(dtype=np.float64,

            

Reported by Pylint.

                      for out, inp, msg in _gen_alignment_data(dtype=np.float64,
                                                 type='unary',
                                                 max_size=7):
            exp = [ncu.sqrt(i) for i in inp]
            assert_almost_equal(inp**(0.5), exp, err_msg=msg)
            np.sqrt(inp, out=out)
            assert_equal(out, exp, err_msg=msg)

    def test_power_complex(self):

            

Reported by Pylint.

                      assert_almost_equal(x**(-2), [1/(1+2j)**2, 1/(2+3j)**2, 1/(3+4j)**2])
        assert_almost_equal(x**(-3), [(-11+2j)/125, (-46-9j)/2197,
                                      (-117-44j)/15625])
        assert_almost_equal(x**(0.5), [ncu.sqrt(1+2j), ncu.sqrt(2+3j),
                                       ncu.sqrt(3+4j)])
        norm = 1./((x**14)[0])
        assert_almost_equal(x**14 * norm,
                [i * norm for i in [-76443+16124j, 23161315+58317492j,
                                    5583548873 + 2465133864j]])

            

Reported by Pylint.

              import warnings
import itertools
import platform
import pytest
import math
from decimal import Decimal

import numpy as np
from numpy.core import umath

            

Reported by Pylint.

                  assert_array_equal, assert_almost_equal, assert_array_almost_equal,
    assert_warns, assert_array_max_ulp, HAS_REFCOUNT
    )
from numpy.core._rational_tests import rational

from hypothesis import assume, given, strategies as st
from hypothesis.extra import numpy as hynp



            

Reported by Pylint.

                  )
from numpy.core._rational_tests import rational

from hypothesis import assume, given, strategies as st
from hypothesis.extra import numpy as hynp


class TestResize:
    def test_copies(self):

            

Reported by Pylint.

              from numpy.core._rational_tests import rational

from hypothesis import assume, given, strategies as st
from hypothesis.extra import numpy as hynp


class TestResize:
    def test_copies(self):
        A = np.array([[1, 2], [3, 4]])

            

Reported by Pylint.

                          [[np.dtype("V6"), np.dtype("V10")],
             [np.dtype([("name1", "i8")]), np.dtype([("name2", "i8")])],
             [np.dtype("i8,i8"), np.dtype("i4,i4")],
            ])
    def test_invalid_void_promotion(self, dtype1, dtype2):
        # Mainly test structured void promotion, which currently allows
        # byte-swapping, but nothing else:
        with pytest.raises(TypeError):
            np.promote_types(dtype1, dtype2)

            

Reported by Pylint.

                          [[np.dtype("V10"), np.dtype("V10")],
             [np.dtype([("name1", "<i8")]), np.dtype([("name1", ">i8")])],
             [np.dtype("i8,i8"), np.dtype("i8,>i8")],
            ])
    def test_valid_void_promotion(self, dtype1, dtype2):
        assert np.promote_types(dtype1, dtype2) is dtype1

    def test_can_cast(self):
        assert_(np.can_cast(np.int32, np.int64))

            

Reported by Pylint.

                      size = (5, 5, 5, 5)
        msg = "Mismatch for axis: %s"

        rng = np.random.RandomState(1234)
        m = rng.randint(-100, 100, size=size)
        n = m.astype(object)

        for length in range(len(axis)):
            for combo in combinations(axis, length):

            

Reported by Pylint.

                      dt = np.dtype([("", dt)])
        dt = np.dtype([("", dt)] * 2)
        # The array should be large enough to likely run into threading issues
        arr = np.random.uniform(size=(5000, 4)).view(dt)[:, 0]
        def func(arr):
            arr.nonzero()

        tpe = ThreadPoolExecutor(max_workers=8)
        futures = [tpe.submit(func, arr) for _ in range(10)]

            

Reported by Pylint.

              
class TestMoveaxis:
    def test_move_to_end(self):
        x = np.random.randn(5, 6, 7)
        for source, expected in [(0, (6, 7, 5)),
                                 (1, (5, 7, 6)),
                                 (2, (5, 6, 7)),
                                 (-1, (5, 6, 7))]:
            actual = np.moveaxis(x, source, -1).shape

            

Reported by Pylint.

                          assert_(actual, expected)

    def test_move_new_position(self):
        x = np.random.randn(1, 2, 3, 4)
        for source, destination, expected in [
                (0, 1, (2, 1, 3, 4)),
                (1, 2, (1, 3, 2, 4)),
                (1, -1, (1, 3, 4, 2)),
                ]:

            

Reported by Pylint.

              import decimal
from fractions import Fraction
import math
import pytest
import hypothesis
from hypothesis.extra.numpy import arrays
import hypothesis.strategies as st



            

Reported by Pylint.

              from fractions import Fraction
import math
import pytest
import hypothesis
from hypothesis.extra.numpy import arrays
import hypothesis.strategies as st


import numpy as np

            

Reported by Pylint.

              import math
import pytest
import hypothesis
from hypothesis.extra.numpy import arrays
import hypothesis.strategies as st


import numpy as np
from numpy import ma

            

Reported by Pylint.

              import pytest
import hypothesis
from hypothesis.extra.numpy import arrays
import hypothesis.strategies as st


import numpy as np
from numpy import ma
from numpy.testing import (

            

Reported by Pylint.

                      assert_equal(b.ptp(axis=0), [5.0, 7.0, 7.0])
        assert_equal(b.ptp(axis=-1), [6.0, 6.0, 6.0])

        assert_equal(b.ptp(axis=0, keepdims=True), [[5.0, 7.0, 7.0]])
        assert_equal(b.ptp(axis=(0,1), keepdims=True), [[8.0]])


class TestCumsum:


            

Reported by Pylint.

                      assert_equal(b.ptp(axis=-1), [6.0, 6.0, 6.0])

        assert_equal(b.ptp(axis=0, keepdims=True), [[5.0, 7.0, 7.0]])
        assert_equal(b.ptp(axis=(0,1), keepdims=True), [[8.0]])


class TestCumsum:

    def test_basic(self):

            

Reported by Pylint.

                      assert_(np.all(num_error < 0.03) == True)

        # test with unevenly spaced
        np.random.seed(0)
        x = np.sort(np.random.random(10))
        y = 2 * x ** 3 + 4 * x ** 2 + 2 * x
        analytical = 6 * x ** 2 + 8 * x + 2
        num_error = np.abs((np.gradient(y, x, edge_order=2) / analytical) - 1)
        assert_(np.all(num_error < 0.03) == True)

            

Reported by Pylint.

              
        # test with unevenly spaced
        np.random.seed(0)
        x = np.sort(np.random.random(10))
        y = 2 * x ** 3 + 4 * x ** 2 + 2 * x
        analytical = 6 * x ** 2 + 8 * x + 2
        num_error = np.abs((np.gradient(y, x, edge_order=2) / analytical) - 1)
        assert_(np.all(num_error < 0.03) == True)


            

Reported by Pylint.

                      assert_equal(b, np.array([2.5]))

    def test_extended_axis(self):
        o = np.random.normal(size=(71, 23))
        x = np.dstack([o] * 10)
        assert_equal(np.percentile(x, 30, axis=(0, 1)), np.percentile(o, 30))
        x = np.moveaxis(x, -1, 0)
        assert_equal(np.percentile(x, 30, axis=(-2, -1)), np.percentile(o, 30))
        x = x.swapaxes(0, 1).copy()

            

Reported by Pylint.

                                   np.percentile(x, [25, 60], axis=0))

        d = np.arange(3 * 5 * 7 * 11).reshape((3, 5, 7, 11))
        np.random.shuffle(d.ravel())
        assert_equal(np.percentile(d, 25,  axis=(0, 1, 2))[0],
                     np.percentile(d[:,:,:, 0].flatten(), 25))
        assert_equal(np.percentile(d, [10, 90], axis=(0, 1, 3))[:, 1],
                     np.percentile(d[:,:, 1,:].flatten(), [10, 90]))
        assert_equal(np.percentile(d, 25, axis=(3, 1, -4))[2],

            

Reported by Pylint.

              import sys
import gc
import tempfile
import pytest
from os import path
from io import BytesIO
from itertools import chain

import numpy as np

            

Reported by Pylint.

              
    def test_mem_dot(self):
        # Ticket #106
        x = np.random.randn(0, 1)
        y = np.random.randn(10, 1)
        # Dummy array to detect bad memory access:
        _z = np.ones(10)
        _dummy = np.empty((0, 10))
        z = np.lib.stride_tricks.as_strided(_z, _dummy.shape, _dummy.strides)

            

Reported by Pylint.

                  def test_mem_dot(self):
        # Ticket #106
        x = np.random.randn(0, 1)
        y = np.random.randn(10, 1)
        # Dummy array to detect bad memory access:
        _z = np.ones(10)
        _dummy = np.empty((0, 10))
        z = np.lib.stride_tricks.as_strided(_z, _dummy.shape, _dummy.strides)
        np.dot(x, np.transpose(y), out=z)

            

Reported by Pylint.

              
    def test_argmax(self):
        # Ticket #119
        a = np.random.normal(0, 1, (4, 5, 6, 7, 8))
        for i in range(a.ndim):
            a.argmax(i)  # Should succeed

    def test_mem_divmod(self):
        # Ticket #126

            

Reported by Pylint.

                  def test_tobytes_FORTRANORDER_discontiguous(self):
        # Fix in r2836
        # Create non-contiguous Fortran ordered array
        x = np.array(np.random.rand(3, 3), order='F')[:, :2]
        assert_array_almost_equal(x.ravel(), np.frombuffer(x.tobytes()))

    def test_flat_assignment(self):
        # Correct behaviour of ticket #194
        x = np.empty((3, 1))

            

Reported by Pylint.

                      funcs2 = ['compress', 'take', 'repeat']

        for func in funcs1:
            arr = np.random.rand(8, 7)
            arr2 = arr.copy()
            if isinstance(func, tuple):
                func_meth = func[1]
                func = func[0]
            else:

            

Reported by Pylint.

                              assert_(abs(res1-res2).max() < 1e-8, func)

        for func in funcs2:
            arr1 = np.random.rand(8, 7)
            arr2 = np.random.rand(8, 7)
            res1 = None
            if func == 'compress':
                arr1 = arr1.ravel()
                res1 = getattr(arr2, func)(arr1)

            

Reported by Pylint.

              
        for func in funcs2:
            arr1 = np.random.rand(8, 7)
            arr2 = np.random.rand(8, 7)
            res1 = None
            if func == 'compress':
                arr1 = arr1.ravel()
                res1 = getattr(arr2, func)(arr1)
            else:

            

Reported by Pylint.

              
    # Cannot test if NPY_RELAXED_STRIDES_CHECKING changes the strides.
    # With NPY_RELAXED_STRIDES_CHECKING the test becomes superfluous.
    @pytest.mark.skipif(np.ones(1).strides[0] == np.iinfo(np.intp).max,
                        reason="Using relaxed stride checking")
    def test_reshape_trailing_ones_strides(self):
        # GitHub issue gh-2949, bad strides for trailing ones of new shape
        a = np.zeros(12, dtype=np.int32)[::2]  # not contiguous
        strides_c = (16, 8, 8, 8)

            

Reported by Pylint.

                      # Ticket #374
        a = np.arange(5).reshape((5, 1))
        b = a.copy()
        np.random.shuffle(b)
        assert_equal(np.sort(b, axis=0), a)

    def test_refcount_vdot(self):
        # Changeset #3443
        _assert_valid_refcount(np.vdot)

            

Reported by Pylint.

              import copy
import platform

from . import __version__

# 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 *


f2py_version = __version__.version

# Global flags:

            

Reported by Pylint.

              
def rmbadname1(name):
    if name in badnames:
        errmess('rmbadname1: Replacing "%s" with "%s".\n' %
                (name, badnames[name]))
        return badnames[name]
    return name



            

Reported by Pylint.

              
def undo_rmbadname1(name):
    if name in invbadnames:
        errmess('undo_rmbadname1: Replacing "%s" with "%s".\n'
                % (name, invbadnames[name]))
        return invbadnames[name]
    return name



            

Reported by Pylint.

              

# Read fortran (77,90) code
def readfortrancode(ffile, dowithline=show, istop=1):
    """
    Read fortran codes from files and
     1) Get rid of comments, line continuations, and empty lines; lower cases.
     2) Call dowithline(line) on every line.
     3) Recursively call itself when statement \"include '<filename>'\" is met.

            

Reported by Pylint.

                              while True:
                    lc = fin.readline()
                    if not lc:
                        errmess(
                            'Unexpected end of file when reading multiline\n')
                        break
                    l = l + lc
                    if mline_mark.match(lc):
                        break

            

Reported by Pylint.

                      elif k == 'note':
            pass
        elif k in ['intent', 'check', 'dimension', 'optional', 'required']:
            errmess('appenddecl: "%s" not implemented.\n' % k)
        else:
            raise Exception('appenddecl: Unknown variable definition key:' +
                            str(k))
    return decl


            

Reported by Pylint.

                                                      ' to %s arguments\n' % (k, groupcache[groupcounter]['name']))
                                groupcache[groupcounter]['args'].append(k)
                        else:
                            errmess(
                                'analyzeline: intent(callback) %s is ignored' % (k))
                    else:
                        errmess('analyzeline: intent(callback) %s is already'
                                ' in argument list' % (k))
            if case in ['optional', 'required', 'public', 'external', 'private', 'intrinsic']:

            

Reported by Pylint.

                                          errmess(
                                'analyzeline: intent(callback) %s is ignored' % (k))
                    else:
                        errmess('analyzeline: intent(callback) %s is already'
                                ' in argument list' % (k))
            if case in ['optional', 'required', 'public', 'external', 'private', 'intrinsic']:
                ap = case
            if 'attrspec' in edecl[k]:
                edecl[k]['attrspec'].append(ap)

            

Reported by Pylint.

                          try:
                v = eval(initexpr, {}, params)
            except (SyntaxError, NameError, TypeError) as msg:
                errmess('analyzeline: Failed to evaluate %r. Ignoring: %s\n'
                        % (initexpr, msg))
                continue
            edecl[k]['='] = repr(v)
            if 'attrspec' in edecl[k]:
                edecl[k]['attrspec'].append('parameter')

            

Reported by Pylint.

              import traceback
import textwrap
import subprocess
import pytest

import numpy as np
from numpy import array, single, double, csingle, cdouble, dot, identity, matmul
from numpy.core import swapaxes
from numpy import multiply, atleast_2d, inf, asarray

            

Reported by Pylint.

              old_assert_almost_equal = assert_almost_equal


def assert_almost_equal(a, b, single_decimal=6, double_decimal=12, **kw):
    if asarray(a).dtype.type in (single, csingle):
        decimal = single_decimal
    else:
        decimal = double_decimal
    old_assert_almost_equal(a, b, decimal=decimal, **kw)

            

Reported by Pylint.

              # Base test cases
#

np.random.seed(1234)

CASES = []

# square test cases
CASES += apply_tag('square', [

            

Reported by Pylint.

                             np.empty((0,), dtype=double),
               tags={'size-0'}),
    LinalgCase("8x8",
               np.random.rand(8, 8),
               np.random.rand(8)),
    LinalgCase("1x1",
               np.random.rand(1, 1),
               np.random.rand(1)),
    LinalgCase("nonarray",

            

Reported by Pylint.

                             tags={'size-0'}),
    LinalgCase("8x8",
               np.random.rand(8, 8),
               np.random.rand(8)),
    LinalgCase("1x1",
               np.random.rand(1, 1),
               np.random.rand(1)),
    LinalgCase("nonarray",
               [[1, 2], [3, 4]],

            

Reported by Pylint.

                             np.random.rand(8, 8),
               np.random.rand(8)),
    LinalgCase("1x1",
               np.random.rand(1, 1),
               np.random.rand(1)),
    LinalgCase("nonarray",
               [[1, 2], [3, 4]],
               [2, 1]),
])

            

Reported by Pylint.

                             np.random.rand(8)),
    LinalgCase("1x1",
               np.random.rand(1, 1),
               np.random.rand(1)),
    LinalgCase("nonarray",
               [[1, 2], [3, 4]],
               [2, 1]),
])


            

Reported by Pylint.

                                 [[1. + 1j, 2. + 2j], [3. - 3j, 4. - 9j], [5. - 4j, 6. + 8j]], dtype=cdouble),
               array([[2. + 1j, 1. + 2j], [1 - 1j, 2 - 2j], [1 - 1j, 2 - 2j]], dtype=cdouble)),
    LinalgCase("8x11",
               np.random.rand(8, 11),
               np.random.rand(8)),
    LinalgCase("1x5",
               np.random.rand(1, 5),
               np.random.rand(1)),
    LinalgCase("5x1",

            

Reported by Pylint.

                             array([[2. + 1j, 1. + 2j], [1 - 1j, 2 - 2j], [1 - 1j, 2 - 2j]], dtype=cdouble)),
    LinalgCase("8x11",
               np.random.rand(8, 11),
               np.random.rand(8)),
    LinalgCase("1x5",
               np.random.rand(1, 5),
               np.random.rand(1)),
    LinalgCase("5x1",
               np.random.rand(5, 1),

            

Reported by Pylint.

                             np.random.rand(8, 11),
               np.random.rand(8)),
    LinalgCase("1x5",
               np.random.rand(1, 5),
               np.random.rand(1)),
    LinalgCase("5x1",
               np.random.rand(5, 1),
               np.random.rand(5)),
    LinalgCase("0x4",

            

Reported by Pylint.

                      x = array([1., 2., 3., 4., 5.])
        c = array([1, 1, 1, 0, 0])
        x[2] = masked
        z = where(c, x, -x)
        assert_(eq(z, [1., 2., 0., -4., -5]))
        c[0] = masked
        z = where(c, x, -x)
        assert_(eq(z, [1., 2., 0., -4., -5]))
        assert_(z[0] is masked)

            

Reported by Pylint.

                      z = where(c, x, -x)
        assert_(eq(z, [1., 2., 0., -4., -5]))
        c[0] = masked
        z = where(c, x, -x)
        assert_(eq(z, [1., 2., 0., -4., -5]))
        assert_(z[0] is masked)
        assert_(z[1] is not masked)
        assert_(z[2] is masked)
        assert_(eq(masked_where(greater(x, 2), x), masked_greater(x, 2)))

            

Reported by Pylint.

                      assert_(eq(masked_where(not_equal(x, 2), x), masked_not_equal(x, 2)))
        assert_(eq(masked_inside(list(range(5)), 1, 3), [0, 199, 199, 199, 4]))
        assert_(eq(masked_outside(list(range(5)), 1, 3), [199, 1, 2, 3, 199]))
        assert_(eq(masked_inside(array(list(range(5)),
                                       mask=[1, 0, 0, 0, 0]), 1, 3).mask,
                   [1, 1, 1, 1, 0]))
        assert_(eq(masked_outside(array(list(range(5)),
                                        mask=[0, 1, 0, 0, 0]), 1, 3).mask,
                   [1, 1, 0, 0, 1]))

            

Reported by Pylint.

                      assert_(eq(masked_inside(array(list(range(5)),
                                       mask=[1, 0, 0, 0, 0]), 1, 3).mask,
                   [1, 1, 1, 1, 0]))
        assert_(eq(masked_outside(array(list(range(5)),
                                        mask=[0, 1, 0, 0, 0]), 1, 3).mask,
                   [1, 1, 0, 0, 1]))
        assert_(eq(masked_equal(array(list(range(5)),
                                      mask=[1, 0, 0, 0, 0]), 2).mask,
                   [1, 0, 1, 0, 0]))

            

Reported by Pylint.

                      assert_(eq(masked_outside(array(list(range(5)),
                                        mask=[0, 1, 0, 0, 0]), 1, 3).mask,
                   [1, 1, 0, 0, 1]))
        assert_(eq(masked_equal(array(list(range(5)),
                                      mask=[1, 0, 0, 0, 0]), 2).mask,
                   [1, 0, 1, 0, 0]))
        assert_(eq(masked_not_equal(array([2, 2, 1, 2, 1],
                                          mask=[1, 0, 0, 0, 0]), 2).mask,
                   [1, 0, 1, 0, 1]))

            

Reported by Pylint.

                      assert_(eq(masked_equal(array(list(range(5)),
                                      mask=[1, 0, 0, 0, 0]), 2).mask,
                   [1, 0, 1, 0, 0]))
        assert_(eq(masked_not_equal(array([2, 2, 1, 2, 1],
                                          mask=[1, 0, 0, 0, 0]), 2).mask,
                   [1, 0, 1, 0, 1]))
        assert_(eq(masked_where([1, 1, 0, 0, 0], [1, 2, 3, 4, 5]),
                   [99, 99, 3, 4, 5]))
        atest = ones((10, 10, 10), dtype=np.float32)

            

Reported by Pylint.

                      btest = zeros(atest.shape, MaskType)
        ctest = masked_where(btest, atest)
        assert_(eq(atest, ctest))
        z = choose(c, (-x, x))
        assert_(eq(z, [1., 2., 0., -4., -5]))
        assert_(z[0] is masked)
        assert_(z[1] is not masked)
        assert_(z[2] is masked)
        x = arange(6)

            

Reported by Pylint.

                      with np.errstate(divide='ignore'):
            assert_((1 / array(0)).mask)
        assert_((1 + xm).mask)
        assert_((-xm).mask)
        assert_((-xm).mask)
        assert_(maximum(xm, xm).mask)
        assert_(minimum(xm, xm).mask)
        assert_(xm.filled().dtype is xm._data.dtype)
        x = array(0, mask=0)

            

Reported by Pylint.

                          assert_((1 / array(0)).mask)
        assert_((1 + xm).mask)
        assert_((-xm).mask)
        assert_((-xm).mask)
        assert_(maximum(xm, xm).mask)
        assert_(minimum(xm, xm).mask)
        assert_(xm.filled().dtype is xm._data.dtype)
        x = array(0, mask=0)
        assert_(x.filled() == x._data)

            

Reported by Pylint.

              
    def test_reduce(self):
        a = self.d[0]
        assert_(not alltrue(a, axis=0))
        assert_(sometrue(a, axis=0))
        assert_equal(sum(a[:3], axis=0), 0)
        assert_equal(product(a, axis=0), 0)

    def test_minmax(self):

            

Reported by Pylint.