# -*- coding: utf-8 -*-
# *****************************************************************************
# Copyright (c) 2020, Intel Corporation All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
#     Redistributions of source code must retain the above copyright notice,
#     this list of conditions and the following disclaimer.
#
#     Redistributions in binary form must reproduce the above copyright notice,
#     this list of conditions and the following disclaimer in the documentation
#     and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
# *****************************************************************************

import numpy as np
import pandas as pd
import unittest
from itertools import (combinations_with_replacement, product, chain, )

import numba
from sdc.tests.indexes.index_datagens import (
    test_global_index_names,
    _generate_positional_range_params,
    _generate_positional_indexes_fixed,
    get_sample_index,
    )
from sdc.tests.test_base import TestCase
from sdc.extensions.indexes.positional_index_ext import init_positional_index
from sdc.datatypes.indexes import *


class TestPositionalIndex(TestCase):

    def test_positional_index_type_inferred(self):

        for params in _generate_positional_range_params():
            start, stop, step = params
            for name in test_global_index_names:
                index = pd.RangeIndex(start, stop, step, name=name)
                with self.subTest(index=index):
                    native_index_type = numba.typeof(index)
                    self.assertIsInstance(native_index_type, PositionalIndexType)

    def test_positional_index_create_and_box(self):
        @self.jit
        def sdc_func(stop, name):
            return init_positional_index(stop, name=name)

        for size, name in product([1, 5, 17], test_global_index_names):
            with self.subTest(size=size, name=name):
                result = sdc_func(size, name)
                expected_res = pd.RangeIndex(size, name=name)
                pd.testing.assert_index_equal(result, expected_res)

    def test_positional_index_unbox_and_box(self):
        def test_impl(index):
            return index
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            start, stop, step = params
            for name in test_global_index_names:
                index = pd.RangeIndex(start, stop, step, name=name)
                with self.subTest(index=index):
                    result = sdc_func(index)
                    result_ref = test_impl(index)
                    pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_create_param_name_literal_str(self):
        @self.jit
        def sdc_func(stop):
            return init_positional_index(stop, name='index')

        n = 11
        result = sdc_func(n)
        expected_res = pd.RangeIndex(n, name='index')
        pd.testing.assert_index_equal(result, expected_res)

    def test_positional_index_attribute_start(self):
        def test_impl(index):
            return index.start
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            with self.subTest(index=index):
                result = sdc_func(index)
                result_ref = test_impl(index)
                self.assertEqual(result, result_ref)

    def test_positional_index_attribute_stop(self):
        def test_impl(index):
            return index.stop
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            with self.subTest(index=index):
                result = sdc_func(index)
                result_ref = test_impl(index)
                self.assertEqual(result, result_ref)

    def test_positional_index_attribute_step(self):
        def test_impl(index):
            return index.step
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            with self.subTest(index=index):
                result = sdc_func(index)
                result_ref = test_impl(index)
                self.assertEqual(result, result_ref)

    def test_positional_index_attribute_dtype(self):
        def test_impl(index):
            return index.dtype
        sdc_func = self.jit(test_impl)

        index = pd.RangeIndex(11)
        result = sdc_func(index)
        result_ref = test_impl(index)
        self.assertEqual(result, result_ref)

    def test_positional_index_attribute_name(self):
        def test_impl(index):
            return index.name
        sdc_func = self.jit(test_impl)

        n = 11
        for name in test_global_index_names:
            with self.subTest(name=name):
                index = pd.RangeIndex(n, name=name)
                result = sdc_func(index)
                result_ref = test_impl(index)
                self.assertEqual(result, result_ref)

    def test_positional_index_len(self):
        def test_impl(index):
            return len(index)
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            with self.subTest(index=index):
                result = sdc_func(index)
                result_ref = test_impl(index)
                self.assertEqual(result, result_ref)

    def test_positional_index_attribute_values(self):
        def test_impl(index):
            return index.values
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            with self.subTest(index=index):
                result = sdc_func(index)
                result_ref = test_impl(index)
                np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_contains(self):
        def test_impl(index, value):
            return value in index
        sdc_func = self.jit(test_impl)

        index = pd.RangeIndex(11)
        values_to_test = [-5, 15, 1, 11, 5, 6]
        for value in values_to_test:
            with self.subTest(value=value):
                result = sdc_func(index, value)
                result_ref = test_impl(index, value)
                np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_copy(self):
        def test_impl(index, new_name):
            return index.copy(name=new_name)
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            start, stop, step = params
            for name, new_name in product(test_global_index_names, repeat=2):
                index = pd.RangeIndex(start, stop, step, name=name)
                with self.subTest(index=index, new_name=new_name):
                    result = sdc_func(index, new_name)
                    result_ref = test_impl(index, new_name)
                    pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_getitem_scalar(self):
        def test_impl(index, idx):
            return index[idx]
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            n = len(index)
            if not n:  # test only non-empty ranges
                continue
            values_to_test = [-n, n // 2, n - 1]
            for idx in values_to_test:
                with self.subTest(index=index, idx=idx):
                    result = sdc_func(index, idx)
                    result_ref = test_impl(index, idx)
                    self.assertEqual(result, result_ref)

    def test_positional_index_getitem_scalar_idx_bounds(self):
        def test_impl(index, idx):
            return index[idx]
        sdc_func = self.jit(test_impl)

        n = 11
        index = pd.RangeIndex(n, name='abc')
        values_to_test = [-(n + 1), n]
        for idx in values_to_test:
            with self.subTest(idx=idx):
                with self.assertRaises(Exception) as context:
                    test_impl(index, idx)
                pandas_exception = context.exception

                with self.assertRaises(type(pandas_exception)) as context:
                    sdc_func(index, idx)
                sdc_exception = context.exception
                self.assertIsInstance(sdc_exception, type(pandas_exception))
                self.assertIn("out of bounds", str(sdc_exception))

    def test_positional_index_getitem_slice(self):
        def test_impl(index, idx):
            return index[idx]
        sdc_func = self.jit(test_impl)

        index_len = 17
        slices_params = combinations_with_replacement(
            [None, 0, -1, index_len // 2, index_len, index_len - 3, index_len + 3, -(index_len + 3)],
            2,
        )

        index = pd.RangeIndex(0, index_len, 1, name='abc')
        for slice_start, slice_stop in slices_params:
            for slice_step in [1, -1, 2]:
                idx = slice(slice_start, slice_stop, slice_step)
                with self.subTest(index=index, idx=idx):
                    result = sdc_func(index, idx)
                    result_ref = test_impl(index, idx)
                    pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_iterator_1(self):
        def test_impl(index):
            res = []
            for i, label in enumerate(index):
                res.append((i, label))
            return res
        sdc_func = self.jit(test_impl)

        index = pd.RangeIndex(0, 21, 1)
        result = sdc_func(index)
        result_ref = test_impl(index)
        self.assertEqual(result, result_ref)

    def test_positional_index_iterator_2(self):
        def test_impl(index):
            res = []
            for label in index:
                if not label % 2:
                    res.append(label)
            return res
        sdc_func = self.jit(test_impl)

        index = pd.RangeIndex(0, 21, 1)
        result = sdc_func(index)
        result_ref = test_impl(index)
        self.assertEqual(result, result_ref)

    def test_positional_index_nparray(self):
        def test_impl(index):
            return np.array(index)
        sdc_func = self.jit(test_impl)

        n = 11
        index = get_sample_index(n, PositionalIndexType)
        result = sdc_func(index)
        result_ref = test_impl(index)
        np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_operator_eq_index_1(self):
        """ Verifies operator.eq implementation for pandas PositionalIndex in a case of equal range sizes """
        def test_impl(index1, index2):
            return index1 == index2
        sdc_func = self.jit(test_impl)

        n = 11
        for index1, index2 in product(_generate_positional_indexes_fixed(n), repeat=2):
            with self.subTest(index1=index1, index2=index2):
                result = np.asarray(sdc_func(index1, index2))   # FIXME_Numba#5157: remove np.asarray
                result_ref = test_impl(index1, index2)
                np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_operator_eq_index_2(self):
        """ Verifies operator.eq implementation for pandas PositionalIndex in a case of non equal range sizes """
        def test_impl(index1, index2):
            return index1 == index2
        sdc_func = self.jit(test_impl)

        index1 = pd.RangeIndex(11)
        index2 = pd.RangeIndex(22)
        with self.assertRaises(Exception) as context:
            test_impl(index1, index2)
        pandas_exception = context.exception

        with self.assertRaises(type(pandas_exception)) as context:
            sdc_func(index1, index2)
        sdc_exception = context.exception
        self.assertIn(str(sdc_exception), str(pandas_exception))

    def test_positional_index_operator_eq_scalar(self):
        """ Verifies operator.eq implementation for pandas PositionalIndex and a scalar value """
        def test_impl(A, B):
            return A == B
        sdc_func = self.jit(test_impl)

        n = 11
        A = pd.RangeIndex(n)
        scalars_to_test = [
            A.start,
            float(A.start),
            A.start + 1,
            (A.start + A.stop) / 2,
            A.stop,
        ]
        for B in scalars_to_test:
            for swap_operands in (False, True):
                if swap_operands:
                    A, B = B, A
                with self.subTest(left=A, right=B):
                    result = np.asarray(sdc_func(A, B))  # FIXME_Numba#5157: remove np.asarray
                    result_ref = test_impl(A, B)
                    np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_operator_eq_nparray(self):
        """ Verifies operator.eq implementation for pandas PositionalIndex and a numpy array """
        def test_impl(A, B):
            return A == B
        sdc_func = self.jit(test_impl)

        n = 11
        for A, B in product(
            _generate_positional_indexes_fixed(n),
            map(lambda x: np.array(x), _generate_positional_indexes_fixed(n))
        ):
            for swap_operands in (False, True):
                if swap_operands:
                    A, B = B, A
                with self.subTest(left=A, right=B):
                    result = np.asarray(sdc_func(A, B))  # FIXME_Numba#5157: remove np.asarray
                    result_ref = test_impl(A, B)
                    np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_operator_ne_index(self):
        """ Verifies operator.ne implementation for pandas PositionalIndex in a case of non equal range sizes """
        def test_impl(index1, index2):
            return index1 != index2
        sdc_func = self.jit(test_impl)

        n = 11
        for index1, index2 in product(_generate_positional_indexes_fixed(n), repeat=2):
            with self.subTest(index1=index1, index2=index2):
                result = np.asarray(sdc_func(index1, index2))   # FIXME_Numba#5157: remove np.asarray
                result_ref = test_impl(index1, index2)
                np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_operator_is_nounbox(self):
        def test_impl_1(*args):
            index1 = pd.RangeIndex(*args)
            index2 = index1
            return index1 is index2
        sdc_func_1 = self.jit(test_impl_1)

        def test_impl_2(*args):
            index1 = pd.RangeIndex(*args)
            index2 = pd.RangeIndex(*args)
            return index1 is index2
        sdc_func_2 = self.jit(test_impl_2)

        # positive testcase
        params = 1, 21, 3
        with self.subTest(subtest="same indexes"):
            result = sdc_func_1(*params)
            result_ref = test_impl_1(*params)
            self.assertEqual(result, result_ref)
            self.assertEqual(result, True)

        # negative testcase
        with self.subTest(subtest="not same indexes"):
            result = sdc_func_2(*params)
            result_ref = test_impl_2(*params)
            self.assertEqual(result, result_ref)
            self.assertEqual(result, False)

    def test_positional_index_getitem_by_mask(self):
        def test_impl(index, mask):
            return index[mask]
        sdc_func = self.jit(test_impl)

        n = 11
        np.random.seed(0)
        mask = np.random.choice([True, False], n)
        for index in _generate_positional_indexes_fixed(n):
            result = sdc_func(index, mask)
            result_ref = test_impl(index, mask)
            pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_getitem_by_array(self):
        def test_impl(index, idx):
            return index[idx]
        sdc_func = self.jit(test_impl)

        n, k = 11, 7
        np.random.seed(0)
        idx = np.random.choice(np.arange(n), k)
        for index in _generate_positional_indexes_fixed(n):
            result = sdc_func(index, idx)
            result_ref = test_impl(index, idx)
            pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_equals(self):
        def test_impl(index1, index2):
            return index1.equals(index2)
        sdc_func = self.jit(test_impl)

        n = 11
        self_indexes = list(chain(
            _generate_positional_indexes_fixed(n),
            _generate_positional_indexes_fixed(2 * n)
        ))

        all_positional_indexes = list(_generate_positional_indexes_fixed(n))
        other_indexes = chain(
            all_positional_indexes,
            map(lambda x: pd.Int64Index(x), all_positional_indexes),
        )

        for index1, index2 in product(self_indexes, other_indexes):
            with self.subTest(index1=index1, index2=index2):
                result = sdc_func(index1, index2)
                result_ref = test_impl(index1, index2)
                self.assertEqual(result, result_ref)

    def test_positional_index_ravel(self):
        def test_impl(index):
            return index.ravel()
        sdc_func = self.jit(test_impl)

        n = 11
        index = pd.RangeIndex(n)
        result = sdc_func(index)
        result_ref = test_impl(index)
        np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_reindex_equal_indexes(self):

        def test_func(index1, index2):
            return index1.reindex(index2)
        sdc_func = self.jit(test_func)

        n = 20
        np.random.seed(0)
        index1 = pd.RangeIndex(0, n, 1)
        index2 = index1.copy(deep=True)

        result = sdc_func(index1, index2)
        result_ref = test_func(index1, index2)
        pd.testing.assert_index_equal(result[0], result_ref[0])
        np.testing.assert_array_equal(result[1], result_ref[1])

    def test_positional_index_reindex(self):

        def test_impl(index1, index2):
            return index1.reindex(index2)
        sdc_func = self.jit(test_impl)

        n = 20
        np.random.seed(0)
        index1 = pd.RangeIndex(0, n, 1)
        reindex_by = [
            pd.RangeIndex(n + 2),
            pd.RangeIndex(0, n, 2),
            pd.Int64Index(np.random.choice(index1.values, n, replace=False)),
            pd.Int64Index(np.random.choice([0, 1, 11, 12, 100], n))
        ]

        for index2 in reindex_by:
            with self.subTest(index2=index2):
                result = sdc_func(index1, index2)
                result_ref = test_impl(index1, index2)
                pd.testing.assert_index_equal(result[0], result_ref[0])
                np.testing.assert_array_equal(result[1], result_ref[1])

    def test_positional_index_take(self):
        def test_impl(index, value):
            return index.take(value)
        sdc_func = self.jit(test_impl)

        n = 11
        np.random.seed(0)
        index_pos = np.arange(n)
        values_to_test = [
            np.random.choice(index_pos, 2*n),
            list(np.random.choice(index_pos, n, replace=False)),
            pd.RangeIndex(n // 2),
            pd.Int64Index(index_pos[n // 2:])
        ]
        for index, value in product(_generate_positional_indexes_fixed(n), values_to_test):
            with self.subTest(index=index, value=value):
                result = sdc_func(index, value)
                result_ref = test_impl(index, value)
                pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_append(self):
        def test_impl(index, other):
            return index.append(other)
        sdc_func = self.jit(test_impl)

        n = 11
        other_indexes = [
            get_sample_index(n, PositionalIndexType),
            get_sample_index(n, RangeIndexType),
            get_sample_index(n, Int64IndexType),
        ]
        for index, other in product(
                _generate_positional_indexes_fixed(n),
                other_indexes):
            with self.subTest(index=index, other=other):
                result = sdc_func(index, other)
                result_ref = test_impl(index, other)
                pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_join(self):
        def test_impl(index, other):
            return index.join(other, 'outer', return_indexers=True)
        sdc_func = self.jit(test_impl)

        n = 11
        other_indexes = [
            get_sample_index(2 * n, PositionalIndexType),
            get_sample_index(2 * n, RangeIndexType),
            get_sample_index(2 * n, Int64IndexType),
        ]
        for index, other in product(
                _generate_positional_indexes_fixed(n),
                other_indexes):
            with self.subTest(index=index, other=other):
                result = sdc_func(index, other)
                result_ref = test_impl(index, other)
                # check_names=False, since pandas behavior is not type-stable
                pd.testing.assert_index_equal(result[0], result_ref[0], check_names=False)
                np.testing.assert_array_equal(result[1], result_ref[1])
                np.testing.assert_array_equal(result[2], result_ref[2])


if __name__ == "__main__":
    unittest.main()

# -*- coding: utf-8 -*-
# *****************************************************************************
# Copyright (c) 2020, Intel Corporation All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
#     Redistributions of source code must retain the above copyright notice,
#     this list of conditions and the following disclaimer.
#
#     Redistributions in binary form must reproduce the above copyright notice,
#     this list of conditions and the following disclaimer in the documentation
#     and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
# *****************************************************************************

import numpy as np
import pandas as pd
import unittest
from itertools import (combinations_with_replacement, product, chain, )

import numba
from sdc.tests.indexes.index_datagens import (
    test_global_index_names,
    _generate_positional_range_params,
    _generate_positional_indexes_fixed,
    get_sample_index,
    )
from sdc.tests.test_base import TestCase
from sdc.extensions.indexes.positional_index_ext import init_positional_index
from sdc.datatypes.indexes import *


class TestPositionalIndex(TestCase):

    def test_positional_index_type_inferred(self):

        for params in _generate_positional_range_params():
            start, stop, step = params
            for name in test_global_index_names:
                index = pd.RangeIndex(start, stop, step, name=name)
                with self.subTest(index=index):
                    native_index_type = numba.typeof(index)
                    self.assertIsInstance(native_index_type, PositionalIndexType)

    def test_positional_index_create_and_box(self):
        @self.jit
        def sdc_func(stop, name):
            return init_positional_index(stop, name=name)

        for size, name in product([1, 5, 17], test_global_index_names):
            with self.subTest(size=size, name=name):
                result = sdc_func(size, name)
                expected_res = pd.RangeIndex(size, name=name)
                pd.testing.assert_index_equal(result, expected_res)

    def test_positional_index_unbox_and_box(self):
        def test_impl(index):
            return index
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            start, stop, step = params
            for name in test_global_index_names:
                index = pd.RangeIndex(start, stop, step, name=name)
                with self.subTest(index=index):
                    result = sdc_func(index)
                    result_ref = test_impl(index)
                    pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_create_param_name_literal_str(self):
        @self.jit
        def sdc_func(stop):
            return init_positional_index(stop, name='index')

        n = 11
        result = sdc_func(n)
        expected_res = pd.RangeIndex(n, name='index')
        pd.testing.assert_index_equal(result, expected_res)

    def test_positional_index_attribute_start(self):
        def test_impl(index):
            return index.start
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            with self.subTest(index=index):
                result = sdc_func(index)
                result_ref = test_impl(index)
                self.assertEqual(result, result_ref)

    def test_positional_index_attribute_stop(self):
        def test_impl(index):
            return index.stop
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            with self.subTest(index=index):
                result = sdc_func(index)
                result_ref = test_impl(index)
                self.assertEqual(result, result_ref)

    def test_positional_index_attribute_step(self):
        def test_impl(index):
            return index.step
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            with self.subTest(index=index):
                result = sdc_func(index)
                result_ref = test_impl(index)
                self.assertEqual(result, result_ref)

    def test_positional_index_attribute_dtype(self):
        def test_impl(index):
            return index.dtype
        sdc_func = self.jit(test_impl)

        index = pd.RangeIndex(11)
        result = sdc_func(index)
        result_ref = test_impl(index)
        self.assertEqual(result, result_ref)

    def test_positional_index_attribute_name(self):
        def test_impl(index):
            return index.name
        sdc_func = self.jit(test_impl)

        n = 11
        for name in test_global_index_names:
            with self.subTest(name=name):
                index = pd.RangeIndex(n, name=name)
                result = sdc_func(index)
                result_ref = test_impl(index)
                self.assertEqual(result, result_ref)

    def test_positional_index_len(self):
        def test_impl(index):
            return len(index)
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            with self.subTest(index=index):
                result = sdc_func(index)
                result_ref = test_impl(index)
                self.assertEqual(result, result_ref)

    def test_positional_index_attribute_values(self):
        def test_impl(index):
            return index.values
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            with self.subTest(index=index):
                result = sdc_func(index)
                result_ref = test_impl(index)
                np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_contains(self):
        def test_impl(index, value):
            return value in index
        sdc_func = self.jit(test_impl)

        index = pd.RangeIndex(11)
        values_to_test = [-5, 15, 1, 11, 5, 6]
        for value in values_to_test:
            with self.subTest(value=value):
                result = sdc_func(index, value)
                result_ref = test_impl(index, value)
                np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_copy(self):
        def test_impl(index, new_name):
            return index.copy(name=new_name)
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            start, stop, step = params
            for name, new_name in product(test_global_index_names, repeat=2):
                index = pd.RangeIndex(start, stop, step, name=name)
                with self.subTest(index=index, new_name=new_name):
                    result = sdc_func(index, new_name)
                    result_ref = test_impl(index, new_name)
                    pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_getitem_scalar(self):
        def test_impl(index, idx):
            return index[idx]
        sdc_func = self.jit(test_impl)

        for params in _generate_positional_range_params():
            index = pd.RangeIndex(*params)
            n = len(index)
            if not n:  # test only non-empty ranges
                continue
            values_to_test = [-n, n // 2, n - 1]
            for idx in values_to_test:
                with self.subTest(index=index, idx=idx):
                    result = sdc_func(index, idx)
                    result_ref = test_impl(index, idx)
                    self.assertEqual(result, result_ref)

    def test_positional_index_getitem_scalar_idx_bounds(self):
        def test_impl(index, idx):
            return index[idx]
        sdc_func = self.jit(test_impl)

        n = 11
        index = pd.RangeIndex(n, name='abc')
        values_to_test = [-(n + 1), n]
        for idx in values_to_test:
            with self.subTest(idx=idx):
                with self.assertRaises(Exception) as context:
                    test_impl(index, idx)
                pandas_exception = context.exception

                with self.assertRaises(type(pandas_exception)) as context:
                    sdc_func(index, idx)
                sdc_exception = context.exception
                self.assertIsInstance(sdc_exception, type(pandas_exception))
                self.assertIn("out of bounds", str(sdc_exception))

    def test_positional_index_getitem_slice(self):
        def test_impl(index, idx):
            return index[idx]
        sdc_func = self.jit(test_impl)

        index_len = 17
        slices_params = combinations_with_replacement(
            [None, 0, -1, index_len // 2, index_len, index_len - 3, index_len + 3, -(index_len + 3)],
            2,
        )

        index = pd.RangeIndex(0, index_len, 1, name='abc')
        for slice_start, slice_stop in slices_params:
            for slice_step in [1, -1, 2]:
                idx = slice(slice_start, slice_stop, slice_step)
                with self.subTest(index=index, idx=idx):
                    result = sdc_func(index, idx)
                    result_ref = test_impl(index, idx)
                    pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_iterator_1(self):
        def test_impl(index):
            res = []
            for i, label in enumerate(index):
                res.append((i, label))
            return res
        sdc_func = self.jit(test_impl)

        index = pd.RangeIndex(0, 21, 1)
        result = sdc_func(index)
        result_ref = test_impl(index)
        self.assertEqual(result, result_ref)

    def test_positional_index_iterator_2(self):
        def test_impl(index):
            res = []
            for label in index:
                if not label % 2:
                    res.append(label)
            return res
        sdc_func = self.jit(test_impl)

        index = pd.RangeIndex(0, 21, 1)
        result = sdc_func(index)
        result_ref = test_impl(index)
        self.assertEqual(result, result_ref)

    def test_positional_index_nparray(self):
        def test_impl(index):
            return np.array(index)
        sdc_func = self.jit(test_impl)

        n = 11
        index = get_sample_index(n, PositionalIndexType)
        result = sdc_func(index)
        result_ref = test_impl(index)
        np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_operator_eq_index_1(self):
        """ Verifies operator.eq implementation for pandas PositionalIndex in a case of equal range sizes """
        def test_impl(index1, index2):
            return index1 == index2
        sdc_func = self.jit(test_impl)

        n = 11
        for index1, index2 in product(_generate_positional_indexes_fixed(n), repeat=2):
            with self.subTest(index1=index1, index2=index2):
                result = np.asarray(sdc_func(index1, index2))   # FIXME_Numba#5157: remove np.asarray
                result_ref = test_impl(index1, index2)
                np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_operator_eq_index_2(self):
        """ Verifies operator.eq implementation for pandas PositionalIndex in a case of non equal range sizes """
        def test_impl(index1, index2):
            return index1 == index2
        sdc_func = self.jit(test_impl)

        index1 = pd.RangeIndex(11)
        index2 = pd.RangeIndex(22)
        with self.assertRaises(Exception) as context:
            test_impl(index1, index2)
        pandas_exception = context.exception

        with self.assertRaises(type(pandas_exception)) as context:
            sdc_func(index1, index2)
        sdc_exception = context.exception
        self.assertIn(str(sdc_exception), str(pandas_exception))

    def test_positional_index_operator_eq_scalar(self):
        """ Verifies operator.eq implementation for pandas PositionalIndex and a scalar value """
        def test_impl(A, B):
            return A == B
        sdc_func = self.jit(test_impl)

        n = 11
        A = pd.RangeIndex(n)
        scalars_to_test = [
            A.start,
            float(A.start),
            A.start + 1,
            (A.start + A.stop) / 2,
            A.stop,
        ]
        for B in scalars_to_test:
            for swap_operands in (False, True):
                if swap_operands:
                    A, B = B, A
                with self.subTest(left=A, right=B):
                    result = np.asarray(sdc_func(A, B))  # FIXME_Numba#5157: remove np.asarray
                    result_ref = test_impl(A, B)
                    np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_operator_eq_nparray(self):
        """ Verifies operator.eq implementation for pandas PositionalIndex and a numpy array """
        def test_impl(A, B):
            return A == B
        sdc_func = self.jit(test_impl)

        n = 11
        for A, B in product(
            _generate_positional_indexes_fixed(n),
            map(lambda x: np.array(x), _generate_positional_indexes_fixed(n))
        ):
            for swap_operands in (False, True):
                if swap_operands:
                    A, B = B, A
                with self.subTest(left=A, right=B):
                    result = np.asarray(sdc_func(A, B))  # FIXME_Numba#5157: remove np.asarray
                    result_ref = test_impl(A, B)
                    np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_operator_ne_index(self):
        """ Verifies operator.ne implementation for pandas PositionalIndex in a case of non equal range sizes """
        def test_impl(index1, index2):
            return index1 != index2
        sdc_func = self.jit(test_impl)

        n = 11
        for index1, index2 in product(_generate_positional_indexes_fixed(n), repeat=2):
            with self.subTest(index1=index1, index2=index2):
                result = np.asarray(sdc_func(index1, index2))   # FIXME_Numba#5157: remove np.asarray
                result_ref = test_impl(index1, index2)
                np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_operator_is_nounbox(self):
        def test_impl_1(*args):
            index1 = pd.RangeIndex(*args)
            index2 = index1
            return index1 is index2
        sdc_func_1 = self.jit(test_impl_1)

        def test_impl_2(*args):
            index1 = pd.RangeIndex(*args)
            index2 = pd.RangeIndex(*args)
            return index1 is index2
        sdc_func_2 = self.jit(test_impl_2)

        # positive testcase
        params = 1, 21, 3
        with self.subTest(subtest="same indexes"):
            result = sdc_func_1(*params)
            result_ref = test_impl_1(*params)
            self.assertEqual(result, result_ref)
            self.assertEqual(result, True)

        # negative testcase
        with self.subTest(subtest="not same indexes"):
            result = sdc_func_2(*params)
            result_ref = test_impl_2(*params)
            self.assertEqual(result, result_ref)
            self.assertEqual(result, False)

    def test_positional_index_getitem_by_mask(self):
        def test_impl(index, mask):
            return index[mask]
        sdc_func = self.jit(test_impl)

        n = 11
        np.random.seed(0)
        mask = np.random.choice([True, False], n)
        for index in _generate_positional_indexes_fixed(n):
            result = sdc_func(index, mask)
            result_ref = test_impl(index, mask)
            pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_getitem_by_array(self):
        def test_impl(index, idx):
            return index[idx]
        sdc_func = self.jit(test_impl)

        n, k = 11, 7
        np.random.seed(0)
        idx = np.random.choice(np.arange(n), k)
        for index in _generate_positional_indexes_fixed(n):
            result = sdc_func(index, idx)
            result_ref = test_impl(index, idx)
            pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_equals(self):
        def test_impl(index1, index2):
            return index1.equals(index2)
        sdc_func = self.jit(test_impl)

        n = 11
        self_indexes = list(chain(
            _generate_positional_indexes_fixed(n),
            _generate_positional_indexes_fixed(2 * n)
        ))

        all_positional_indexes = list(_generate_positional_indexes_fixed(n))
        other_indexes = chain(
            all_positional_indexes,
            map(lambda x: pd.Int64Index(x), all_positional_indexes),
        )

        for index1, index2 in product(self_indexes, other_indexes):
            with self.subTest(index1=index1, index2=index2):
                result = sdc_func(index1, index2)
                result_ref = test_impl(index1, index2)
                self.assertEqual(result, result_ref)

    def test_positional_index_ravel(self):
        def test_impl(index):
            return index.ravel()
        sdc_func = self.jit(test_impl)

        n = 11
        index = pd.RangeIndex(n)
        result = sdc_func(index)
        result_ref = test_impl(index)
        np.testing.assert_array_equal(result, result_ref)

    def test_positional_index_reindex_equal_indexes(self):

        def test_func(index1, index2):
            return index1.reindex(index2)
        sdc_func = self.jit(test_func)

        n = 20
        np.random.seed(0)
        index1 = pd.RangeIndex(0, n, 1)
        index2 = index1.copy(deep=True)

        result = sdc_func(index1, index2)
        result_ref = test_func(index1, index2)
        pd.testing.assert_index_equal(result[0], result_ref[0])
        np.testing.assert_array_equal(result[1], result_ref[1])

    def test_positional_index_reindex(self):

        def test_impl(index1, index2):
            return index1.reindex(index2)
        sdc_func = self.jit(test_impl)

        n = 20
        np.random.seed(0)
        index1 = pd.RangeIndex(0, n, 1)
        reindex_by = [
            pd.RangeIndex(n + 2),
            pd.RangeIndex(0, n, 2),
            pd.Int64Index(np.random.choice(index1.values, n, replace=False)),
            pd.Int64Index(np.random.choice([0, 1, 11, 12, 100], n))
        ]

        for index2 in reindex_by:
            with self.subTest(index2=index2):
                result = sdc_func(index1, index2)
                result_ref = test_impl(index1, index2)
                pd.testing.assert_index_equal(result[0], result_ref[0])
                np.testing.assert_array_equal(result[1], result_ref[1])

    def test_positional_index_take(self):
        def test_impl(index, value):
            return index.take(value)
        sdc_func = self.jit(test_impl)

        n = 11
        np.random.seed(0)
        index_pos = np.arange(n)
        values_to_test = [
            np.random.choice(index_pos, 2*n),
            list(np.random.choice(index_pos, n, replace=False)),
            pd.RangeIndex(n // 2),
            pd.Int64Index(index_pos[n // 2:])
        ]
        for index, value in product(_generate_positional_indexes_fixed(n), values_to_test):
            with self.subTest(index=index, value=value):
                result = sdc_func(index, value)
                result_ref = test_impl(index, value)
                pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_append(self):
        def test_impl(index, other):
            return index.append(other)
        sdc_func = self.jit(test_impl)

        n = 11
        other_indexes = [
            get_sample_index(n, PositionalIndexType),
            get_sample_index(n, RangeIndexType),
            get_sample_index(n, Int64IndexType),
        ]
        for index, other in product(
                _generate_positional_indexes_fixed(n),
                other_indexes):
            with self.subTest(index=index, other=other):
                result = sdc_func(index, other)
                result_ref = test_impl(index, other)
                pd.testing.assert_index_equal(result, result_ref)

    def test_positional_index_join(self):
        def test_impl(index, other):
            return index.join(other, 'outer', return_indexers=True)
        sdc_func = self.jit(test_impl)

        n = 11
        other_indexes = [
            get_sample_index(2 * n, PositionalIndexType),
            get_sample_index(2 * n, RangeIndexType),
            get_sample_index(2 * n, Int64IndexType),
        ]
        for index, other in product(
                _generate_positional_indexes_fixed(n),
                other_indexes):
            with self.subTest(index=index, other=other):
                result = sdc_func(index, other)
                result_ref = test_impl(index, other)
                # check_names=False, since pandas behavior is not type-stable
                pd.testing.assert_index_equal(result[0], result_ref[0], check_names=False)
                np.testing.assert_array_equal(result[1], result_ref[1])
                np.testing.assert_array_equal(result[2], result_ref[2])


if __name__ == "__main__":
    unittest.main()

# -*- coding: utf-8 -*- # ***************************************************************************** # Copyright (c) 2020, Intel Corporation All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # #     Redistributions of source code must retain the above copyright notice, #     this list of conditions and the following disclaimer. # #     Redistributions in binary form must reproduce the above copyright notice, #     this list of conditions and the following disclaimer in the documentation #     and/or other materials provided with the distribution. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, # THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR # PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR # CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, # EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, # PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; # OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, # WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR # OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, # EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # ***************************************************************************** # test only non-empty ranges Verifies operator.eq implementation for pandas PositionalIndex in a case of equal range sizes # FIXME_Numba#5157: remove np.asarray Verifies operator.eq implementation for pandas PositionalIndex in a case of non equal range sizes Verifies operator.eq implementation for pandas PositionalIndex and a scalar value # FIXME_Numba#5157: remove np.asarray Verifies operator.eq implementation for pandas PositionalIndex and a numpy array # FIXME_Numba#5157: remove np.asarray Verifies operator.ne implementation for pandas PositionalIndex in a case of non equal range sizes # FIXME_Numba#5157: remove np.asarray # positive testcase # negative testcase # check_names=False, since pandas behavior is not type-stable