import collections.abc
import tempfile
import sys
import shutil
import warnings
import operator
import io
import itertools
import functools
import ctypes
import os
import gc
import weakref
import pytest
from contextlib import contextmanager

from numpy.compat import pickle

import pathlib
import builtins
from decimal import Decimal

import numpy as np
from numpy.compat import strchar
import numpy.core._multiarray_tests as _multiarray_tests
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, HAS_REFCOUNT, assert_array_less, runstring,
    temppath, suppress_warnings, break_cycles,
    )
from numpy.testing._private.utils import _no_tracing
from numpy.core.tests._locales import CommaDecimalPointLocale

# Need to test an object that does not fully implement math interface
from datetime import timedelta, datetime


def _aligned_zeros(shape, dtype=float, order="C", align=None):
    """
    Allocate a new ndarray with aligned memory.

    The ndarray is guaranteed *not* aligned to twice the requested alignment.
    Eg, if align=4, guarantees it is not aligned to 8. If align=None uses
    dtype.alignment."""
    dtype = np.dtype(dtype)
    if dtype == np.dtype(object):
        # Can't do this, fall back to standard allocation (which
        # should always be sufficiently aligned)
        if align is not None:
            raise ValueError("object array alignment not supported")
        return np.zeros(shape, dtype=dtype, order=order)
    if align is None:
        align = dtype.alignment
    if not hasattr(shape, '__len__'):
        shape = (shape,)
    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

    # Note: slices producing 0-size arrays do not necessarily change
    # data pointer --- so we use and allocate size+1
    buf = buf[offset:offset+size+1][:-1]
    data = np.ndarray(shape, dtype, buf, order=order)
    data.fill(0)
    return data


class TestFlags:
    def setup(self):
        self.a = np.arange(10)

    def test_writeable(self):
        mydict = locals()
        self.a.flags.writeable = False
        assert_raises(ValueError, runstring, 'self.a[0] = 3', mydict)
        assert_raises(ValueError, runstring, 'self.a[0:1].itemset(3)', mydict)
        self.a.flags.writeable = True
        self.a[0] = 5
        self.a[0] = 0

    def test_writeable_any_base(self):
        # Ensure that any base being writeable is sufficient to change flag;
        # this is especially interesting for arrays from an array interface.
        arr = np.arange(10)

        class subclass(np.ndarray):
            pass

        # Create subclass so base will not be collapsed, this is OK to change
        view1 = arr.view(subclass)
        view2 = view1[...]
        arr.flags.writeable = False
        view2.flags.writeable = False
        view2.flags.writeable = True  # Can be set to True again.

        arr = np.arange(10)

        class frominterface:
            def __init__(self, arr):
                self.arr = arr
                self.__array_interface__ = arr.__array_interface__

        view1 = np.asarray(frominterface)
        view2 = view1[...]
        view2.flags.writeable = False
        view2.flags.writeable = True

        view1.flags.writeable = False
        view2.flags.writeable = False
        with assert_raises(ValueError):
            # Must assume not writeable, since only base is not:
            view2.flags.writeable = True

    def test_writeable_from_readonly(self):
        # gh-9440 - make sure fromstring, from buffer on readonly buffers
        # set writeable False
        data = b'\x00' * 100
        vals = np.frombuffer(data, 'B')
        assert_raises(ValueError, vals.setflags, write=True)
        types = np.dtype( [('vals', 'u1'), ('res3', 'S4')] )
        values = np.core.records.fromstring(data, types)
        vals = values['vals']
        assert_raises(ValueError, vals.setflags, write=True)

    def test_writeable_from_buffer(self):
        data = bytearray(b'\x00' * 100)
        vals = np.frombuffer(data, 'B')
        assert_(vals.flags.writeable)
        vals.setflags(write=False)
        assert_(vals.flags.writeable is False)
        vals.setflags(write=True)
        assert_(vals.flags.writeable)
        types = np.dtype( [('vals', 'u1'), ('res3', 'S4')] )
        values = np.core.records.fromstring(data, types)
        vals = values['vals']
        assert_(vals.flags.writeable)
        vals.setflags(write=False)
        assert_(vals.flags.writeable is False)
        vals.setflags(write=True)
        assert_(vals.flags.writeable)

    @pytest.mark.skipif(IS_PYPY, reason="PyPy always copies")
    def test_writeable_pickle(self):
        import pickle
        # Small arrays will be copied without setting base.
        # See condition for using PyArray_SetBaseObject in
        # array_setstate.
        a = np.arange(1000)
        for v in range(pickle.HIGHEST_PROTOCOL):
            vals = pickle.loads(pickle.dumps(a, v))
            assert_(vals.flags.writeable)
            assert_(isinstance(vals.base, bytes))

    def test_writeable_from_c_data(self):
        # 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[...]

        # Toggling the writeable flag works on the view:
        view.flags.writeable = False
        assert not view.flags.writeable
        view.flags.writeable = True
        assert view.flags.writeable
        # Flag can be unset on the arr_writeable:
        arr_writeable.flags.writeable = False

        arr_readonly = get_c_wrapping_array(False)
        assert not arr_readonly.flags.owndata
        assert not arr_readonly.flags.writeable

        for arr in [arr_writeable, arr_readonly]:
            view = arr[...]
            view.flags.writeable = False  # make sure it is readonly
            arr.flags.writeable = False
            assert not arr.flags.writeable

            with assert_raises(ValueError):
                view.flags.writeable = True

            with warnings.catch_warnings():
                warnings.simplefilter("error", DeprecationWarning)
                with assert_raises(DeprecationWarning):
                    arr.flags.writeable = True

            with assert_warns(DeprecationWarning):
                arr.flags.writeable = True

    def test_warnonwrite(self):
        a = np.arange(10)
        a.flags._warn_on_write = True
        with warnings.catch_warnings(record=True) as w:
            warnings.filterwarnings('always')
            a[1] = 10
            a[2] = 10
            # only warn once
            assert_(len(w) == 1)

    def test_otherflags(self):
        assert_equal(self.a.flags.carray, True)
        assert_equal(self.a.flags['C'], True)
        assert_equal(self.a.flags.farray, False)
        assert_equal(self.a.flags.behaved, True)
        assert_equal(self.a.flags.fnc, False)
        assert_equal(self.a.flags.forc, True)
        assert_equal(self.a.flags.owndata, True)
        assert_equal(self.a.flags.writeable, True)
        assert_equal(self.a.flags.aligned, True)
        with assert_warns(DeprecationWarning):
            assert_equal(self.a.flags.updateifcopy, False)
        with assert_warns(DeprecationWarning):
            assert_equal(self.a.flags['U'], False)
            assert_equal(self.a.flags['UPDATEIFCOPY'], False)
        assert_equal(self.a.flags.writebackifcopy, False)
        assert_equal(self.a.flags['X'], False)
        assert_equal(self.a.flags['WRITEBACKIFCOPY'], False)

    def test_string_align(self):
        a = np.zeros(4, dtype=np.dtype('|S4'))
        assert_(a.flags.aligned)
        # not power of two are accessed byte-wise and thus considered aligned
        a = np.zeros(5, dtype=np.dtype('|S4'))
        assert_(a.flags.aligned)

    def test_void_align(self):
        a = np.zeros(4, dtype=np.dtype([("a", "i4"), ("b", "i4")]))
        assert_(a.flags.aligned)


class TestHash:
    # see #3793
    def test_int(self):
        for st, ut, s in [(np.int8, np.uint8, 8),
                          (np.int16, np.uint16, 16),
                          (np.int32, np.uint32, 32),
                          (np.int64, np.uint64, 64)]:
            for i in range(1, s):
                assert_equal(hash(st(-2**i)), hash(-2**i),
                             err_msg="%r: -2**%d" % (st, i))
                assert_equal(hash(st(2**(i - 1))), hash(2**(i - 1)),
                             err_msg="%r: 2**%d" % (st, i - 1))
                assert_equal(hash(st(2**i - 1)), hash(2**i - 1),
                             err_msg="%r: 2**%d - 1" % (st, i))

                i = max(i - 1, 1)
                assert_equal(hash(ut(2**(i - 1))), hash(2**(i - 1)),
                             err_msg="%r: 2**%d" % (ut, i - 1))
                assert_equal(hash(ut(2**i - 1)), hash(2**i - 1),
                             err_msg="%r: 2**%d - 1" % (ut, i))


class TestAttributes:
    def setup(self):
        self.one = np.arange(10)
        self.two = np.arange(20).reshape(4, 5)
        self.three = np.arange(60, dtype=np.float64).reshape(2, 5, 6)

    def test_attributes(self):
        assert_equal(self.one.shape, (10,))
        assert_equal(self.two.shape, (4, 5))
        assert_equal(self.three.shape, (2, 5, 6))
        self.three.shape = (10, 3, 2)
        assert_equal(self.three.shape, (10, 3, 2))
        self.three.shape = (2, 5, 6)
        assert_equal(self.one.strides, (self.one.itemsize,))
        num = self.two.itemsize
        assert_equal(self.two.strides, (5*num, num))
        num = self.three.itemsize
        assert_equal(self.three.strides, (30*num, 6*num, num))
        assert_equal(self.one.ndim, 1)
        assert_equal(self.two.ndim, 2)
        assert_equal(self.three.ndim, 3)
        num = self.two.itemsize
        assert_equal(self.two.size, 20)
        assert_equal(self.two.nbytes, 20*num)
        assert_equal(self.two.itemsize, self.two.dtype.itemsize)
        assert_equal(self.two.base, np.arange(20))

    def test_dtypeattr(self):
        assert_equal(self.one.dtype, np.dtype(np.int_))
        assert_equal(self.three.dtype, np.dtype(np.float_))
        assert_equal(self.one.dtype.char, 'l')
        assert_equal(self.three.dtype.char, 'd')
        assert_(self.three.dtype.str[0] in '<>')
        assert_equal(self.one.dtype.str[1], 'i')
        assert_equal(self.three.dtype.str[1], 'f')

    def test_int_subclassing(self):
        # Regression test for https://github.com/numpy/numpy/pull/3526

        numpy_int = np.int_(0)

        # int_ doesn't inherit from Python int, because it's not fixed-width
        assert_(not isinstance(numpy_int, int))

    def test_stridesattr(self):
        x = self.one

        def make_array(size, offset, strides):
            return np.ndarray(size, buffer=x, dtype=int,
                              offset=offset*x.itemsize,
                              strides=strides*x.itemsize)

        assert_equal(make_array(4, 4, -1), np.array([4, 3, 2, 1]))
        assert_raises(ValueError, make_array, 4, 4, -2)
        assert_raises(ValueError, make_array, 4, 2, -1)
        assert_raises(ValueError, make_array, 8, 3, 1)
        assert_equal(make_array(8, 3, 0), np.array([3]*8))
        # Check behavior reported in gh-2503:
        assert_raises(ValueError, make_array, (2, 3), 5, np.array([-2, -3]))
        make_array(0, 0, 10)

    def test_set_stridesattr(self):
        x = self.one

        def make_array(size, offset, strides):
            try:
                r = np.ndarray([size], dtype=int, buffer=x,
                               offset=offset*x.itemsize)
            except Exception as e:
                raise RuntimeError(e)
            r.strides = strides = strides*x.itemsize
            return r

        assert_equal(make_array(4, 4, -1), np.array([4, 3, 2, 1]))
        assert_equal(make_array(7, 3, 1), np.array([3, 4, 5, 6, 7, 8, 9]))
        assert_raises(ValueError, make_array, 4, 4, -2)
        assert_raises(ValueError, make_array, 4, 2, -1)
        assert_raises(RuntimeError, make_array, 8, 3, 1)
        # Check that the true extent of the array is used.
        # Test relies on as_strided base not exposing a buffer.
        x = np.lib.stride_tricks.as_strided(np.arange(1), (10, 10), (0, 0))