from functools import partial

import numpy as np
import pytest

from pandas.core.dtypes.common import is_categorical_dtype
from pandas.core.dtypes.dtypes import IntervalDtype

from pandas import (
    Categorical,
    CategoricalIndex,
    Float64Index,
    Index,
    Int64Index,
    Interval,
    IntervalIndex,
    date_range,
    notna,
    period_range,
    timedelta_range,
)
import pandas._testing as tm
from pandas.core.arrays import IntervalArray
import pandas.core.common as com


@pytest.fixture(params=[None, "foo"])
def name(request):
    return request.param


class Base:
    """
    Common tests for all variations of IntervalIndex construction. Input data
    to be supplied in breaks format, then converted by the subclass method
    get_kwargs_from_breaks to the expected format.
    """

    @pytest.mark.parametrize(
        "breaks",
        [
            [3, 14, 15, 92, 653],
            np.arange(10, dtype="int64"),
            Int64Index(range(-10, 11)),
            Float64Index(np.arange(20, 30, 0.5)),
            date_range("20180101", periods=10),
            date_range("20180101", periods=10, tz="US/Eastern"),
            timedelta_range("1 day", periods=10),
        ],
    )
    def test_constructor(self, constructor, breaks, closed, name):
        result_kwargs = self.get_kwargs_from_breaks(breaks, closed)
        result = constructor(closed=closed, name=name, **result_kwargs)

        assert result.closed == closed
        assert result.name == name
        assert result.dtype.subtype == getattr(breaks, "dtype", "int64")
        tm.assert_index_equal(result.left, Index(breaks[:-1]))
        tm.assert_index_equal(result.right, Index(breaks[1:]))

    @pytest.mark.parametrize(
        "breaks, subtype",
        [
            (Int64Index([0, 1, 2, 3, 4]), "float64"),
            (Int64Index([0, 1, 2, 3, 4]), "datetime64[ns]"),
            (Int64Index([0, 1, 2, 3, 4]), "timedelta64[ns]"),
            (Float64Index([0, 1, 2, 3, 4]), "int64"),
            (date_range("2017-01-01", periods=5), "int64"),
            (timedelta_range("1 day", periods=5), "int64"),
        ],
    )
    def test_constructor_dtype(self, constructor, breaks, subtype):
        # GH 19262: conversion via dtype parameter
        expected_kwargs = self.get_kwargs_from_breaks(breaks.astype(subtype))
        expected = constructor(**expected_kwargs)

        result_kwargs = self.get_kwargs_from_breaks(breaks)
        iv_dtype = IntervalDtype(subtype)
        for dtype in (iv_dtype, str(iv_dtype)):
            result = constructor(dtype=dtype, **result_kwargs)
            tm.assert_index_equal(result, expected)

    @pytest.mark.parametrize("breaks", [[np.nan] * 2, [np.nan] * 4, [np.nan] * 50])
    def test_constructor_nan(self, constructor, breaks, closed):
        # GH 18421
        result_kwargs = self.get_kwargs_from_breaks(breaks)
        result = constructor(closed=closed, **result_kwargs)

        expected_subtype = np.float64
        expected_values = np.array(breaks[:-1], dtype=object)

        assert result.closed == closed
        assert result.dtype.subtype == expected_subtype
        tm.assert_numpy_array_equal(result._ndarray_values, expected_values)

    @pytest.mark.parametrize(
        "breaks",
        [
            [],
            np.array([], dtype="int64"),
            np.array([], dtype="float64"),
            np.array([], dtype="datetime64[ns]"),
            np.array([], dtype="timedelta64[ns]"),
        ],
    )
    def test_constructor_empty(self, constructor, breaks, closed):
        # GH 18421
        result_kwargs = self.get_kwargs_from_breaks(breaks)
        result = constructor(closed=closed, **result_kwargs)

        expected_values = np.array([], dtype=object)
        expected_subtype = getattr(breaks, "dtype", np.int64)

        assert result.empty
        assert result.closed == closed
        assert result.dtype.subtype == expected_subtype
        tm.assert_numpy_array_equal(result._ndarray_values, expected_values)

    @pytest.mark.parametrize(
        "breaks",
        [
            tuple("0123456789"),
            list("abcdefghij"),
            np.array(list("abcdefghij"), dtype=object),
            np.array(list("abcdefghij"), dtype="<U1"),
        ],
    )
    def test_constructor_string(self, constructor, breaks):
        # GH 19016
        msg = (
            "category, object, and string subtypes are not supported "
            "for IntervalIndex"
        )
        with pytest.raises(TypeError, match=msg):
            constructor(**self.get_kwargs_from_breaks(breaks))

    @pytest.mark.parametrize("cat_constructor", [Categorical, CategoricalIndex])
    def test_constructor_categorical_valid(self, constructor, cat_constructor):
        # GH 21243/21253
        if isinstance(constructor, partial) and constructor.func is Index:
            # Index is defined to create CategoricalIndex from categorical data
            pytest.skip()

        breaks = np.arange(10, dtype="int64")
        expected = IntervalIndex.from_breaks(breaks)

        cat_breaks = cat_constructor(breaks)
        result_kwargs = self.get_kwargs_from_breaks(cat_breaks)
        result = constructor(**result_kwargs)
        tm.assert_index_equal(result, expected)

    def test_generic_errors(self, constructor):
        # filler input data to be used when supplying invalid kwargs
        filler = self.get_kwargs_from_breaks(range(10))

        # invalid closed
        msg = "invalid option for 'closed': invalid"
        with pytest.raises(ValueError, match=msg):
            constructor(closed="invalid", **filler)

        # unsupported dtype
        msg = "dtype must be an IntervalDtype, got int64"
        with pytest.raises(TypeError, match=msg):
            constructor(dtype="int64", **filler)

        # invalid dtype
        msg = "data type [\"']invalid[\"'] not understood"
        with pytest.raises(TypeError, match=msg):
            constructor(dtype="invalid", **filler)

        # no point in nesting periods in an IntervalIndex
        periods = period_range("2000-01-01", periods=10)
        periods_kwargs = self.get_kwargs_from_breaks(periods)
        msg = "Period dtypes are not supported, use a PeriodIndex instead"
        with pytest.raises(ValueError, match=msg):
            constructor(**periods_kwargs)

        # decreasing values
        decreasing_kwargs = self.get_kwargs_from_breaks(range(10, -1, -1))
        msg = "left side of interval must be <= right side"
        with pytest.raises(ValueError, match=msg):
            constructor(**decreasing_kwargs)


class TestFromArrays(Base):
    """Tests specific to IntervalIndex.from_arrays"""

    @pytest.fixture
    def constructor(self):
        return IntervalIndex.from_arrays

    def get_kwargs_from_breaks(self, breaks, closed="right"):
        """
        converts intervals in breaks format to a dictionary of kwargs to
        specific to the format expected by IntervalIndex.from_arrays
        """
        return {"left": breaks[:-1], "right": breaks[1:]}

    def test_constructor_errors(self):
        # GH 19016: categorical data
        data = Categorical(list("01234abcde"), ordered=True)
        msg = (
            "category, object, and string subtypes are not supported "
            "for IntervalIndex"
        )
        with pytest.raises(TypeError, match=msg):
            IntervalIndex.from_arrays(data[:-1], data[1:])

        # unequal length
        left = [0, 1, 2]
        right = [2, 3]
        msg = "left and right must have the same length"
        with pytest.raises(ValueError, match=msg):
            IntervalIndex.from_arrays(left, right)

    @pytest.mark.parametrize(
        "left_subtype, right_subtype", [(np.int64, np.float64), (np.float64, np.int64)]
    )
    def test_mixed_float_int(self, left_subtype, right_subtype):
        """mixed int/float left/right results in float for both sides"""
        left = np.arange(9, dtype=left_subtype)
        right = np.arange(1, 10, dtype=right_subtype)
        result = IntervalIndex.from_arrays(left, right)

        expected_left = Float64Index(left)
        expected_right = Float64Index(right)
        expected_subtype = np.float64

        tm.assert_index_equal(result.left, expected_left)
        tm.assert_index_equal(result.right, expected_right)
        assert result.dtype.subtype == expected_subtype


class TestFromBreaks(Base):
    """Tests specific to IntervalIndex.from_breaks"""

    @pytest.fixture
    def constructor(self):
        return IntervalIndex.from_breaks

    def get_kwargs_from_breaks(self, breaks, closed="right"):
        """
        converts intervals in breaks format to a dictionary of kwargs to
        specific to the format expected by IntervalIndex.from_breaks
        """
        return {"breaks": breaks}

    def test_constructor_errors(self):
        # GH 19016: categorical data
        data = Categorical(list("01234abcde"), ordered=True)
        msg = (
            "category, object, and string subtypes are not supported "
            "for IntervalIndex"
        )
        with pytest.raises(TypeError, match=msg):
            IntervalIndex.from_breaks(data)

    def test_length_one(self):
        """breaks of length one produce an empty IntervalIndex"""
        breaks = [0]
        result = IntervalIndex.from_breaks(breaks)
        expected = IntervalIndex.from_breaks([])
        tm.assert_index_equal(result, expected)


class TestFromTuples(Base):
    """Tests specific to IntervalIndex.from_tuples"""

    @pytest.fixture
    def constructor(self):
        return IntervalIndex.from_tuples

    def get_kwargs_from_breaks(self, breaks, closed="right"):
        """
        converts intervals in breaks format to a dictionary of kwargs to
        specific to the format expected by IntervalIndex.from_tuples
        """
        if len(breaks) == 0:
            return {"data": breaks}

        tuples = list(zip(breaks[:-1], breaks[1:]))
        if isinstance(breaks, (list, tuple)):
            return {"data": tuples}
        elif is_categorical_dtype(breaks):
            return {"data": breaks._constructor(tuples)}
        return {"data": com.asarray_tuplesafe(tuples)}

    def test_constructor_errors(self):
        # non-tuple
        tuples = [(0, 1), 2, (3, 4)]
        msg = "IntervalIndex.from_tuples received an invalid item, 2"
        with pytest.raises(TypeError, match=msg.format(t=tuples)):
            IntervalIndex.from_tuples(tuples)

        # too few/many items
        tuples = [(0, 1), (2,), (3, 4)]
        msg = "IntervalIndex.from_tuples requires tuples of length 2, got {t}"
        with pytest.raises(ValueError, match=msg.format(t=tuples)):
            IntervalIndex.from_tuples(tuples)

        tuples = [(0, 1), (2, 3, 4), (5, 6)]
        with pytest.raises(ValueError, match=msg.format(t=tuples)):
            IntervalIndex.from_tuples(tuples)

    def test_na_tuples(self):
        # tuple (NA, NA) evaluates the same as NA as an element
        na_tuple = [(0, 1), (np.nan, np.nan), (2, 3)]
        idx_na_tuple = IntervalIndex.from_tuples(na_tuple)
        idx_na_element = IntervalIndex.from_tuples([(0, 1), np.nan, (2, 3)])
        tm.assert_index_equal(idx_na_tuple, idx_na_element)


class TestClassConstructors(Base):
    """Tests specific to the IntervalIndex/Index constructors"""

    @pytest.fixture(
        params=[IntervalIndex, partial(Index, dtype="interval")],
        ids=["IntervalIndex", "Index"],
    )
    def constructor(self, request):
        return request.param

    def get_kwargs_from_breaks(self, breaks, closed="right"):
        """
        converts intervals in breaks format to a dictionary of kwargs to
        specific to the format expected by the IntervalIndex/Index constructors
        """
        if len(breaks) == 0:
            return {"data": breaks}

        ivs = [
            Interval(l, r, closed) if notna(l) else l
            for l, r in zip(breaks[:-1], breaks[1:])
        ]

        if isinstance(breaks, list):
            return {"data": ivs}
        elif is_categorical_dtype(breaks):
            return {"data": breaks._constructor(ivs)}
        return {"data": np.array(ivs, dtype=object)}

    def test_generic_errors(self, constructor):
        """
        override the base class implementation since errors are handled
        differently; checks unnecessary since caught at the Interval level
        """
        pass

    def test_constructor_string(self):
        # GH23013
        # When forming the interval from breaks,
        # the interval of strings is already forbidden.
        pass

    def test_constructor_errors(self, constructor):
        # mismatched closed within intervals with no constructor override
        ivs = [Interval(0, 1, closed="right"), Interval(2, 3, closed="left")]
        msg = "intervals must all be closed on the same side"
        with pytest.raises(ValueError, match=msg):
            constructor(ivs)

        # scalar
        msg = (
            r"IntervalIndex\(...\) must be called with a collection of "
            "some kind, 5 was passed"
        )
        with pytest.raises(TypeError, match=msg):
            constructor(5)

        # not an interval
        msg = "type <class 'numpy.int64'> with value 0 is not an interval"
        with pytest.raises(TypeError, match=msg):
            constructor([0, 1])

    @pytest.mark.parametrize(
        "data, closed",
        [
            ([], "both"),
            ([np.nan, np.nan], "neither"),
            (
                [Interval(0, 3, closed="neither"), Interval(2, 5, closed="neither")],
                "left",
            ),
            (
                [Interval(0, 3, closed="left"), Interval(2, 5, closed="right")],
                "neither",
            ),
            (IntervalIndex.from_breaks(range(5), closed="both"), "right"),
        ],
    )
    def test_override_inferred_closed(self, constructor, data, closed):
        # GH 19370
        if isinstance(data, IntervalIndex):
            tuples = data.to_tuples()
        else:
            tuples = [(iv.left, iv.right) if notna(iv) else iv for iv in data]
        expected = IntervalIndex.from_tuples(tuples, closed=closed)
        result = constructor(data, closed=closed)
        tm.assert_index_equal(result, expected)

    @pytest.mark.parametrize(
        "values_constructor", [list, np.array, IntervalIndex, IntervalArray]
    )
    def test_index_object_dtype(self, values_constructor):
        # Index(intervals, dtype=object) is an Index (not an IntervalIndex)
        intervals = [Interval(0, 1), Interval(1, 2), Interval(2, 3)]
        values = values_constructor(intervals)
        result = Index(values, dtype=object)

        assert type(result) is Index
        tm.assert_numpy_array_equal(result.values, np.array(values))

    def test_index_mixed_closed(self):
        # GH27172
        intervals = [
            Interval(0, 1, closed="left"),
            Interval(1, 2, closed="right"),
            Interval(2, 3, closed="neither"),
            Interval(3, 4, closed="both"),
        ]
        result = Index(intervals)
        expected = Index(intervals, dtype=object)
        tm.assert_index_equal(result, expected)