# 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
"""
from __future__ import division, absolute_import, print_function

__author__ = "Pierre GF Gerard-Marchant"

import sys
import warnings
import operator
import itertools
import textwrap
import pytest

from functools import reduce


import numpy as np
import numpy.ma.core
import numpy.core.fromnumeric as fromnumeric
import numpy.core.umath as umath
from numpy.testing import (
    assert_raises, assert_warns, suppress_warnings
    )
from numpy import ndarray
from numpy.compat import asbytes
from numpy.ma.testutils import (
    assert_, assert_array_equal, assert_equal, assert_almost_equal,
    assert_equal_records, fail_if_equal, assert_not_equal,
    assert_mask_equal
    )
from numpy.ma.core import (
    MAError, MaskError, MaskType, MaskedArray, abs, absolute, add, all,
    allclose, allequal, alltrue, angle, anom, arange, arccos, arccosh, arctan2,
    arcsin, arctan, argsort, array, asarray, choose, concatenate,
    conjugate, cos, cosh, count, default_fill_value, diag, divide, empty,
    empty_like, equal, exp, flatten_mask, filled, fix_invalid,
    flatten_structured_array, fromflex, getmask, getmaskarray, greater,
    greater_equal, identity, inner, isMaskedArray, less, less_equal, log,
    log10, make_mask, make_mask_descr, mask_or, masked, masked_array,
    masked_equal, masked_greater, masked_greater_equal, masked_inside,
    masked_less, masked_less_equal, masked_not_equal, masked_outside,
    masked_print_option, masked_values, masked_where, max, maximum,
    maximum_fill_value, min, minimum, minimum_fill_value, mod, multiply,
    mvoid, nomask, not_equal, ones, outer, power, product, put, putmask,
    ravel, repeat, reshape, resize, shape, sin, sinh, sometrue, sort, sqrt,
    subtract, sum, take, tan, tanh, transpose, where, zeros,
    )
from numpy.core.numeric import pickle

pi = np.pi


suppress_copy_mask_on_assignment = suppress_warnings()
suppress_copy_mask_on_assignment.filter(
    numpy.ma.core.MaskedArrayFutureWarning,
    "setting an item on a masked array which has a shared mask will not copy")


# For parametrized numeric testing
num_dts = [np.dtype(dt_) for dt_ in '?bhilqBHILQefdgFD']
num_ids = [dt_.char for dt_ in num_dts]


class TestMaskedArray(object):
    # Base test class for MaskedArrays.

    def setup(self):
        # Base data definition.
        x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
        y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
        a10 = 10.
        m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
        m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
        xm = masked_array(x, mask=m1)
        ym = masked_array(y, mask=m2)
        z = np.array([-.5, 0., .5, .8])
        zm = masked_array(z, mask=[0, 1, 0, 0])
        xf = np.where(m1, 1e+20, x)
        xm.set_fill_value(1e+20)
        self.d = (x, y, a10, m1, m2, xm, ym, z, zm, xf)

    def test_basicattributes(self):
        # Tests some basic array attributes.
        a = array([1, 3, 2])
        b = array([1, 3, 2], mask=[1, 0, 1])
        assert_equal(a.ndim, 1)
        assert_equal(b.ndim, 1)
        assert_equal(a.size, 3)
        assert_equal(b.size, 3)
        assert_equal(a.shape, (3,))
        assert_equal(b.shape, (3,))

    def test_basic0d(self):
        # Checks masking a scalar
        x = masked_array(0)
        assert_equal(str(x), '0')
        x = masked_array(0, mask=True)
        assert_equal(str(x), str(masked_print_option))
        x = masked_array(0, mask=False)
        assert_equal(str(x), '0')
        x = array(0, mask=1)
        assert_(x.filled().dtype is x._data.dtype)

    def test_basic1d(self):
        # Test of basic array creation and properties in 1 dimension.
        (x, y, a10, m1, m2, xm, ym, z, zm, xf) = self.d
        assert_(not isMaskedArray(x))
        assert_(isMaskedArray(xm))
        assert_((xm - ym).filled(0).any())
        fail_if_equal(xm.mask.astype(int), ym.mask.astype(int))
        s = x.shape
        assert_equal(np.shape(xm), s)
        assert_equal(xm.shape, s)
        assert_equal(xm.dtype, x.dtype)
        assert_equal(zm.dtype, z.dtype)
        assert_equal(xm.size, reduce(lambda x, y:x * y, s))
        assert_equal(count(xm), len(m1) - reduce(lambda x, y:x + y, m1))
        assert_array_equal(xm, xf)
        assert_array_equal(filled(xm, 1.e20), xf)
        assert_array_equal(x, xm)

    def test_basic2d(self):
        # Test of basic array creation and properties in 2 dimensions.
        (x, y, a10, m1, m2, xm, ym, z, zm, xf) = self.d
        for s in [(4, 3), (6, 2)]:
            x.shape = s
            y.shape = s
            xm.shape = s
            ym.shape = s
            xf.shape = s

            assert_(not isMaskedArray(x))
            assert_(isMaskedArray(xm))
            assert_equal(shape(xm), s)
            assert_equal(xm.shape, s)
            assert_equal(xm.size, reduce(lambda x, y:x * y, s))
            assert_equal(count(xm), len(m1) - reduce(lambda x, y:x + y, m1))
            assert_equal(xm, xf)
            assert_equal(filled(xm, 1.e20), xf)
            assert_equal(x, xm)

    def test_concatenate_basic(self):
        # Tests concatenations.
        (x, y, a10, m1, m2, xm, ym, z, zm, xf) = self.d
        # basic concatenation
        assert_equal(np.concatenate((x, y)), concatenate((xm, ym)))
        assert_equal(np.concatenate((x, y)), concatenate((x, y)))
        assert_equal(np.concatenate((x, y)), concatenate((xm, y)))
        assert_equal(np.concatenate((x, y, x)), concatenate((x, ym, x)))

    def test_concatenate_alongaxis(self):
        # Tests concatenations.
        (x, y, a10, m1, m2, xm, ym, z, zm, xf) = self.d
        # Concatenation along an axis
        s = (3, 4)
        x.shape = y.shape = xm.shape = ym.shape = s
        assert_equal(xm.mask, np.reshape(m1, s))
        assert_equal(ym.mask, np.reshape(m2, s))
        xmym = concatenate((xm, ym), 1)
        assert_equal(np.concatenate((x, y), 1), xmym)
        assert_equal(np.concatenate((xm.mask, ym.mask), 1), xmym._mask)

        x = zeros(2)
        y = array(ones(2), mask=[False, True])
        z = concatenate((x, y))
        assert_array_equal(z, [0, 0, 1, 1])
        assert_array_equal(z.mask, [False, False, False, True])
        z = concatenate((y, x))
        assert_array_equal(z, [1, 1, 0, 0])
        assert_array_equal(z.mask, [False, True, False, False])

    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)

    def test_creation_ndmin(self):
        # Check the use of ndmin
        x = array([1, 2, 3], mask=[1, 0, 0], ndmin=2)
        assert_equal(x.shape, (1, 3))
        assert_equal(x._data, [[1, 2, 3]])
        assert_equal(x._mask, [[1, 0, 0]])

    def test_creation_ndmin_from_maskedarray(self):
        # Make sure we're not losing the original mask w/ ndmin
        x = array([1, 2, 3])
        x[-1] = masked
        xx = array(x, ndmin=2, dtype=float)
        assert_equal(x.shape, x._mask.shape)
        assert_equal(xx.shape, xx._mask.shape)

    def test_creation_maskcreation(self):
        # Tests how masks are initialized at the creation of Maskedarrays.
        data = arange(24, dtype=float)
        data[[3, 6, 15]] = masked
        dma_1 = MaskedArray(data)
        assert_equal(dma_1.mask, data.mask)
        dma_2 = MaskedArray(dma_1)
        assert_equal(dma_2.mask, dma_1.mask)
        dma_3 = MaskedArray(dma_1, mask=[1, 0, 0, 0] * 6)
        fail_if_equal(dma_3.mask, dma_1.mask)

        x = array([1, 2, 3], mask=True)
        assert_equal(x._mask, [True, True, True])
        x = array([1, 2, 3], mask=False)
        assert_equal(x._mask, [False, False, False])
        y = array([1, 2, 3], mask=x._mask, copy=False)
        assert_(np.may_share_memory(x.mask, y.mask))
        y = array([1, 2, 3], mask=x._mask, copy=True)
        assert_(not np.may_share_memory(x.mask, y.mask))

    def test_creation_with_list_of_maskedarrays(self):
        # Tests creating a masked array from a list of masked arrays.
        x = array(np.arange(5), mask=[1, 0, 0, 0, 0])
        data = array((x, x[::-1]))
        assert_equal(data, [[0, 1, 2, 3, 4], [4, 3, 2, 1, 0]])
        assert_equal(data._mask, [[1, 0, 0, 0, 0], [0, 0, 0, 0, 1]])

        x.mask = nomask
        data = array((x, x[::-1]))
        assert_equal(data, [[0, 1, 2, 3, 4], [4, 3, 2, 1, 0]])
        assert_(data.mask is nomask)

    def test_creation_from_ndarray_with_padding(self):
        x = np.array([('A', 0)], dtype={'names':['f0','f1'],
                                        'formats':['S4','i8'],
                                        'offsets':[0,8]})
        array(x)  # used to fail due to 'V' padding field in x.dtype.descr

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

    def test_asarray_default_order(self):
        # See Issue #6646
        m = np.eye(3).T
        assert_(not m.flags.c_contiguous)

        new_m = asarray(m)
        assert_(new_m.flags.c_contiguous)

    def test_asarray_enforce_order(self):
        # See Issue #6646
        m = np.eye(3).T
        assert_(not m.flags.c_contiguous)

        new_m = asarray(m, order='C')
        assert_(new_m.flags.c_contiguous)

    def test_fix_invalid(self):
        # Checks fix_invalid.
        with np.errstate(invalid='ignore'):
            data = masked_array([np.nan, 0., 1.], mask=[0, 0, 1])
            data_fixed = fix_invalid(data)
            assert_equal(data_fixed._data, [data.fill_value, 0., 1.])
            assert_equal(data_fixed._mask, [1., 0., 1.])

    def test_maskedelement(self):
        # Test of masked element
        x = arange(6)
        x[1] = masked
        assert_(str(masked) == '--')
        assert_(x[1] is masked)
        assert_equal(filled(x[1], 0), 0)

    def test_set_element_as_object(self):
        # Tests setting elements with object
        a = empty(1, dtype=object)
        x = (1, 2, 3, 4, 5)
        a[0] = x
        assert_equal(a[0], x)
        assert_(a[0] is x)

        import datetime
        dt = datetime.datetime.now()
        a[0] = dt
        assert_(a[0] is dt)

    def test_indexing(self):
        # Tests conversions and indexing
        x1 = np.array([1, 2, 4, 3])
        x2 = array(x1, mask=[1, 0, 0, 0])
        x3 = array(x1, mask=[0, 1, 0, 1])
        x4 = array(x1)
        # test conversion to strings
        str(x2)  # raises?
        repr(x2)  # raises?
        assert_equal(np.sort(x1), sort(x2, endwith=False))
        # tests of indexing
        assert_(type(x2[1]) is type(x1[1]))
        assert_(x1[1] == x2[1])
        assert_(x2[0] is masked)
        assert_equal(x1[2], x2[2])
        assert_equal(x1[2:5], x2[2:5])
        assert_equal(x1[:], x2[:])
        assert_equal(x1[1:], x3[1:])
        x1[2] = 9
        x2[2] = 9
        assert_equal(x1, x2)
        x1[1:3] = 99
        x2[1:3] = 99
        assert_equal(x1, x2)
        x2[1] = masked
        assert_equal(x1, x2)
        x2[1:3] = masked
        assert_equal(x1, x2)
        x2[:] = x1
        x2[1] = masked
        assert_(allequal(getmask(x2), array([0, 1, 0, 0])))
        x3[:] = masked_array([1, 2, 3, 4], [0, 1, 1, 0])
        assert_(allequal(getmask(x3), array([0, 1, 1, 0])))
        x4[:] = masked_array([1, 2, 3, 4], [0, 1, 1, 0])
        assert_(allequal(getmask(x4), array([0, 1, 1, 0])))
        assert_(allequal(x4, array([1, 2, 3, 4])))
        x1 = np.arange(5) * 1.0
        x2 = masked_values(x1, 3.0)
        assert_equal(x1, x2)
        assert_(allequal(array([0, 0, 0, 1, 0], MaskType), x2.mask))
        assert_equal(3.0, x2.fill_value)
        x1 = array([1, 'hello', 2, 3], object)
        x2 = np.array([1, 'hello', 2, 3], object)
        s1 = x1[1]
        s2 = x2[1]
        assert_equal(type(s2), str)
        assert_equal(type(s1), str)
        assert_equal(s1, s2)
        assert_(x1[1:1].shape == (0,))

    @suppress_copy_mask_on_assignment
    def test_copy(self):
        # Tests of some subtle points of copying and sizing.