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

import numpy as np
from numpy.testing import (
        assert_, assert_equal, IS_PYPY, assert_almost_equal,
        assert_array_equal, assert_array_almost_equal, assert_raises,
        assert_raises_regex, assert_warns, suppress_warnings,
        _assert_valid_refcount, HAS_REFCOUNT,
        )
from numpy.testing._private.utils import _no_tracing
from numpy.compat import asbytes, asunicode, pickle

try:
    RecursionError
except NameError:
    RecursionError = RuntimeError  # python < 3.5

class TestRegression:
    def test_invalid_round(self):
        # Ticket #3
        v = 4.7599999999999998
        assert_array_equal(np.array([v]), np.array(v))

    def test_mem_empty(self):
        # Ticket #7
        np.empty((1,), dtype=[('x', np.int64)])

    def test_pickle_transposed(self):
        # Ticket #16
        a = np.transpose(np.array([[2, 9], [7, 0], [3, 8]]))
        for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
            with BytesIO() as f:
                pickle.dump(a, f, protocol=proto)
                f.seek(0)
                b = pickle.load(f)
            assert_array_equal(a, b)

    def test_typeNA(self):
        # Issue gh-515
        with suppress_warnings() as sup:
            sup.filter(np.VisibleDeprecationWarning)
            assert_equal(np.typeNA[np.int64], 'Int64')
            assert_equal(np.typeNA[np.uint64], 'UInt64')

    def test_dtype_names(self):
        # Ticket #35
        # Should succeed
        np.dtype([(('name', 'label'), np.int32, 3)])

    def test_reduce(self):
        # Ticket #40
        assert_almost_equal(np.add.reduce([1., .5], dtype=None), 1.5)

    def test_zeros_order(self):
        # Ticket #43
        np.zeros([3], int, 'C')
        np.zeros([3], order='C')
        np.zeros([3], int, order='C')

    def test_asarray_with_order(self):
        # Check that nothing is done when order='F' and array C/F-contiguous
        a = np.ones(2)
        assert_(a is np.asarray(a, order='F'))

    def test_ravel_with_order(self):
        # Check that ravel works when order='F' and array C/F-contiguous
        a = np.ones(2)
        assert_(not a.ravel('F').flags.owndata)

    def test_sort_bigendian(self):
        # Ticket #47
        a = np.linspace(0, 10, 11)
        c = a.astype(np.dtype('<f8'))
        c.sort()
        assert_array_almost_equal(c, a)

    def test_negative_nd_indexing(self):
        # Ticket #49
        c = np.arange(125).reshape((5, 5, 5))
        origidx = np.array([-1, 0, 1])
        idx = np.array(origidx)
        c[idx]
        assert_array_equal(idx, origidx)

    def test_char_dump(self):
        # Ticket #50
        ca = np.char.array(np.arange(1000, 1010), itemsize=4)
        for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
            with BytesIO() as f:
                pickle.dump(ca, f, protocol=proto)
                f.seek(0)
                ca = np.load(f, allow_pickle=True)

    def test_noncontiguous_fill(self):
        # Ticket #58.
        a = np.zeros((5, 3))
        b = a[:, :2,]

        def rs():
            b.shape = (10,)

        assert_raises(AttributeError, rs)

    def test_bool(self):
        # Ticket #60
        np.bool_(1)  # Should succeed

    def test_indexing1(self):
        # Ticket #64
        descr = [('x', [('y', [('z', 'c16', (2,)),]),]),]
        buffer = ((([6j, 4j],),),)
        h = np.array(buffer, dtype=descr)
        h['x']['y']['z']

    def test_indexing2(self):
        # Ticket #65
        descr = [('x', 'i4', (2,))]
        buffer = ([3, 2],)
        h = np.array(buffer, dtype=descr)
        h['x']

    def test_round(self):
        # Ticket #67
        x = np.array([1+2j])
        assert_almost_equal(x**(-1), [1/(1+2j)])

    def test_scalar_compare(self):
        # Trac Ticket #72
        # https://github.com/numpy/numpy/issues/565
        a = np.array(['test', 'auto'])
        assert_array_equal(a == 'auto', np.array([False, True]))
        assert_(a[1] == 'auto')
        assert_(a[0] != 'auto')
        b = np.linspace(0, 10, 11)
        # This should return true for now, but will eventually raise an error:
        with suppress_warnings() as sup:
            sup.filter(FutureWarning)
            assert_(b != 'auto')
        assert_(b[0] != 'auto')

    def test_unicode_swapping(self):
        # Ticket #79
        ulen = 1
        ucs_value = u'\U0010FFFF'
        ua = np.array([[[ucs_value*ulen]*2]*3]*4, dtype='U%s' % ulen)
        ua.newbyteorder()  # Should succeed.

    def test_object_array_fill(self):
        # Ticket #86
        x = np.zeros(1, 'O')
        x.fill([])

    def test_mem_dtype_align(self):
        # Ticket #93
        assert_raises(TypeError, np.dtype,
                              {'names':['a'], 'formats':['foo']}, align=1)

    def test_endian_bool_indexing(self):
        # Ticket #105
        a = np.arange(10., dtype='>f8')
        b = np.arange(10., dtype='<f8')
        xa = np.where((a > 2) & (a < 6))
        xb = np.where((b > 2) & (b < 6))
        ya = ((a > 2) & (a < 6))
        yb = ((b > 2) & (b < 6))
        assert_array_almost_equal(xa, ya.nonzero())
        assert_array_almost_equal(xb, yb.nonzero())
        assert_(np.all(a[ya] > 0.5))
        assert_(np.all(b[yb] > 0.5))

    def test_endian_where(self):
        # GitHub issue #369
        net = np.zeros(3, dtype='>f4')
        net[1] = 0.00458849
        net[2] = 0.605202
        max_net = net.max()
        test = np.where(net <= 0., max_net, net)
        correct = np.array([ 0.60520202,  0.00458849,  0.60520202])
        assert_array_almost_equal(test, correct)

    def test_endian_recarray(self):
        # Ticket #2185
        dt = np.dtype([
               ('head', '>u4'),
               ('data', '>u4', 2),
            ])
        buf = np.recarray(1, dtype=dt)
        buf[0]['head'] = 1
        buf[0]['data'][:] = [1, 1]

        h = buf[0]['head']
        d = buf[0]['data'][0]
        buf[0]['head'] = h
        buf[0]['data'][0] = d
        assert_(buf[0]['head'] == 1)

    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)
        assert_equal(_z, np.ones(10))
        # Do the same for the built-in dot:
        np.core.multiarray.dot(x, np.transpose(y), out=z)
        assert_equal(_z, np.ones(10))

    def test_arange_endian(self):
        # Ticket #111
        ref = np.arange(10)
        x = np.arange(10, dtype='<f8')
        assert_array_equal(ref, x)
        x = np.arange(10, dtype='>f8')
        assert_array_equal(ref, x)

    def test_arange_inf_step(self):
        ref = np.arange(0, 1, 10)
        x = np.arange(0, 1, np.inf)
        assert_array_equal(ref, x)

        ref = np.arange(0, 1, -10)
        x = np.arange(0, 1, -np.inf)
        assert_array_equal(ref, x)

        ref = np.arange(0, -1, -10)
        x = np.arange(0, -1, -np.inf)
        assert_array_equal(ref, x)

        ref = np.arange(0, -1, 10)
        x = np.arange(0, -1, np.inf)
        assert_array_equal(ref, x)

    def test_arange_underflow_stop_and_step(self):
        finfo = np.finfo(np.float64)

        ref = np.arange(0, finfo.eps, 2 * finfo.eps)
        x = np.arange(0, finfo.eps, finfo.max)
        assert_array_equal(ref, x)

        ref = np.arange(0, finfo.eps, -2 * finfo.eps)
        x = np.arange(0, finfo.eps, -finfo.max)
        assert_array_equal(ref, x)

        ref = np.arange(0, -finfo.eps, -2 * finfo.eps)
        x = np.arange(0, -finfo.eps, -finfo.max)
        assert_array_equal(ref, x)

        ref = np.arange(0, -finfo.eps, 2 * finfo.eps)
        x = np.arange(0, -finfo.eps, finfo.max)
        assert_array_equal(ref, x)

    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
        for i in range(10):
            divmod(np.array([i])[0], 10)

    def test_hstack_invalid_dims(self):
        # Ticket #128
        x = np.arange(9).reshape((3, 3))
        y = np.array([0, 0, 0])
        assert_raises(ValueError, np.hstack, (x, y))

    def test_squeeze_type(self):
        # Ticket #133
        a = np.array([3])
        b = np.array(3)
        assert_(type(a.squeeze()) is np.ndarray)
        assert_(type(b.squeeze()) is np.ndarray)

    def test_add_identity(self):
        # Ticket #143
        assert_equal(0, np.add.identity)

    def test_numpy_float_python_long_addition(self):
        # Check that numpy float and python longs can be added correctly.
        a = np.float_(23.) + 2**135
        assert_equal(a, 23. + 2**135)

    def test_binary_repr_0(self):
        # Ticket #151
        assert_equal('0', np.binary_repr(0))

    def test_rec_iterate(self):
        # Ticket #160
        descr = np.dtype([('i', int), ('f', float), ('s', '|S3')])
        x = np.rec.array([(1, 1.1, '1.0'),
                         (2, 2.2, '2.0')], dtype=descr)
        x[0].tolist()
        [i for i in x[0]]

    def test_unicode_string_comparison(self):
        # Ticket #190
        a = np.array('hello', np.unicode_)
        b = np.array('world')
        a == b

    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))
        x.flat = np.arange(3)
        assert_array_almost_equal(x, [[0], [1], [2]])
        x.flat = np.arange(3, dtype=float)
        assert_array_almost_equal(x, [[0], [1], [2]])

    def test_broadcast_flat_assignment(self):
        # Ticket #194
        x = np.empty((3, 1))

        def bfa():
            x[:] = np.arange(3)

        def bfb():
            x[:] = np.arange(3, dtype=float)

        assert_raises(ValueError, bfa)
        assert_raises(ValueError, bfb)

    def test_nonarray_assignment(self):
        # See also Issue gh-2870, test for non-array assignment
        # and equivalent unsafe casted array assignment
        a = np.arange(10)
        b = np.ones(10, dtype=bool)
        r = np.arange(10)