from __future__ import division

from itertools import permutations

import numpy as np
import pytest

from pandas._libs.interval import IntervalTree

from pandas import compat
import pandas.util.testing as tm


def skipif_32bit(param):
    """
    Skip parameters in a parametrize on 32bit systems. Specifically used
    here to skip leaf_size parameters related to GH 23440.
    """
    marks = pytest.mark.skipif(compat.is_platform_32bit(),
                               reason='GH 23440: int type mismatch on 32bit')
    return pytest.param(param, marks=marks)


@pytest.fixture(
    scope='class', params=['int32', 'int64', 'float32', 'float64', 'uint64'])
def dtype(request):
    return request.param


@pytest.fixture(params=[skipif_32bit(1), skipif_32bit(2), 10])
def leaf_size(request):
    """
    Fixture to specify IntervalTree leaf_size parameter; to be used with the
    tree fixture.
    """
    return request.param


@pytest.fixture(params=[
    np.arange(5, dtype='int64'),
    np.arange(5, dtype='int32'),
    np.arange(5, dtype='uint64'),
    np.arange(5, dtype='float64'),
    np.arange(5, dtype='float32'),
    np.array([0, 1, 2, 3, 4, np.nan], dtype='float64'),
    np.array([0, 1, 2, 3, 4, np.nan], dtype='float32')])
def tree(request, leaf_size):
    left = request.param
    return IntervalTree(left, left + 2, leaf_size=leaf_size)


class TestIntervalTree(object):

    def test_get_loc(self, tree):
        result = tree.get_loc(1)
        expected = np.array([0], dtype='intp')
        tm.assert_numpy_array_equal(result, expected)

        result = np.sort(tree.get_loc(2))
        expected = np.array([0, 1], dtype='intp')
        tm.assert_numpy_array_equal(result, expected)

        with pytest.raises(KeyError):
            tree.get_loc(-1)

    def test_get_indexer(self, tree):
        result = tree.get_indexer(np.array([1.0, 5.5, 6.5]))
        expected = np.array([0, 4, -1], dtype='intp')
        tm.assert_numpy_array_equal(result, expected)

        with pytest.raises(KeyError):
            tree.get_indexer(np.array([3.0]))

    def test_get_indexer_non_unique(self, tree):
        indexer, missing = tree.get_indexer_non_unique(
            np.array([1.0, 2.0, 6.5]))

        result = indexer[:1]
        expected = np.array([0], dtype='intp')
        tm.assert_numpy_array_equal(result, expected)

        result = np.sort(indexer[1:3])
        expected = np.array([0, 1], dtype='intp')
        tm.assert_numpy_array_equal(result, expected)

        result = np.sort(indexer[3:])
        expected = np.array([-1], dtype='intp')
        tm.assert_numpy_array_equal(result, expected)

        result = missing
        expected = np.array([2], dtype='intp')
        tm.assert_numpy_array_equal(result, expected)

    def test_duplicates(self, dtype):
        left = np.array([0, 0, 0], dtype=dtype)
        tree = IntervalTree(left, left + 1)

        result = np.sort(tree.get_loc(0.5))
        expected = np.array([0, 1, 2], dtype='intp')
        tm.assert_numpy_array_equal(result, expected)

        with pytest.raises(KeyError):
            tree.get_indexer(np.array([0.5]))

        indexer, missing = tree.get_indexer_non_unique(np.array([0.5]))
        result = np.sort(indexer)
        expected = np.array([0, 1, 2], dtype='intp')
        tm.assert_numpy_array_equal(result, expected)

        result = missing
        expected = np.array([], dtype='intp')
        tm.assert_numpy_array_equal(result, expected)

    def test_get_loc_closed(self, closed):
        tree = IntervalTree([0], [1], closed=closed)
        for p, errors in [(0, tree.open_left),
                          (1, tree.open_right)]:
            if errors:
                with pytest.raises(KeyError):
                    tree.get_loc(p)
            else:
                result = tree.get_loc(p)
                expected = np.array([0], dtype='intp')
                tm.assert_numpy_array_equal(result, expected)

    @pytest.mark.parametrize('leaf_size', [
        skipif_32bit(1), skipif_32bit(10), skipif_32bit(100), 10000])
    def test_get_indexer_closed(self, closed, leaf_size):
        x = np.arange(1000, dtype='float64')
        found = x.astype('intp')
        not_found = (-1 * np.ones(1000)).astype('intp')

        tree = IntervalTree(x, x + 0.5, closed=closed, leaf_size=leaf_size)
        tm.assert_numpy_array_equal(found, tree.get_indexer(x + 0.25))

        expected = found if tree.closed_left else not_found
        tm.assert_numpy_array_equal(expected, tree.get_indexer(x + 0.0))

        expected = found if tree.closed_right else not_found
        tm.assert_numpy_array_equal(expected, tree.get_indexer(x + 0.5))

    @pytest.mark.parametrize('left, right, expected', [
        (np.array([0, 1, 4]), np.array([2, 3, 5]), True),
        (np.array([0, 1, 2]), np.array([5, 4, 3]), True),
        (np.array([0, 1, np.nan]), np.array([5, 4, np.nan]), True),
        (np.array([0, 2, 4]), np.array([1, 3, 5]), False),
        (np.array([0, 2, np.nan]), np.array([1, 3, np.nan]), False)])
    @pytest.mark.parametrize('order', map(list, permutations(range(3))))
    def test_is_overlapping(self, closed, order, left, right, expected):
        # GH 23309
        tree = IntervalTree(left[order], right[order], closed=closed)
        result = tree.is_overlapping
        assert result is expected

    @pytest.mark.parametrize('order', map(list, permutations(range(3))))
    def test_is_overlapping_endpoints(self, closed, order):
        """shared endpoints are marked as overlapping"""
        # GH 23309
        left, right = np.arange(3), np.arange(1, 4)
        tree = IntervalTree(left[order], right[order], closed=closed)
        result = tree.is_overlapping
        expected = closed is 'both'
        assert result is expected

    @pytest.mark.parametrize('left, right', [
        (np.array([], dtype='int64'), np.array([], dtype='int64')),
        (np.array([0], dtype='int64'), np.array([1], dtype='int64')),
        (np.array([np.nan]), np.array([np.nan])),
        (np.array([np.nan] * 3), np.array([np.nan] * 3))])
    def test_is_overlapping_trivial(self, closed, left, right):
        # GH 23309
        tree = IntervalTree(left, right, closed=closed)
        assert tree.is_overlapping is False

    @pytest.mark.skipif(compat.is_platform_32bit(), reason='GH 23440')
    def test_construction_overflow(self):
        # GH 25485
        left, right = np.arange(101), [np.iinfo(np.int64).max] * 101
        tree = IntervalTree(left, right)

        # pivot should be average of left/right medians
        result = tree.root.pivot
        expected = (50 + np.iinfo(np.int64).max) / 2
        assert result == expected