"""
Tests for DatetimeIndex methods behaving like their Timestamp counterparts
"""
from datetime import datetime

import numpy as np
import pytest

from pandas._libs.tslibs.np_datetime import OutOfBoundsDatetime

import pandas as pd
from pandas import DatetimeIndex, Timestamp, date_range
import pandas.util.testing as tm

from pandas.tseries.frequencies import to_offset


class TestDatetimeIndexOps:
    def test_dti_time(self):
        rng = date_range("1/1/2000", freq="12min", periods=10)
        result = pd.Index(rng).time
        expected = [t.time() for t in rng]
        assert (result == expected).all()

    def test_dti_date(self):
        rng = date_range("1/1/2000", freq="12H", periods=10)
        result = pd.Index(rng).date
        expected = [t.date() for t in rng]
        assert (result == expected).all()

    @pytest.mark.parametrize("data", [["1400-01-01"], [datetime(1400, 1, 1)]])
    def test_dti_date_out_of_range(self, data):
        # GH#1475
        msg = "Out of bounds nanosecond timestamp: 1400-01-01 00:00:00"
        with pytest.raises(OutOfBoundsDatetime, match=msg):
            DatetimeIndex(data)

    @pytest.mark.parametrize(
        "field",
        [
            "dayofweek",
            "dayofyear",
            "week",
            "weekofyear",
            "quarter",
            "days_in_month",
            "is_month_start",
            "is_month_end",
            "is_quarter_start",
            "is_quarter_end",
            "is_year_start",
            "is_year_end",
            "weekday_name",
        ],
    )
    def test_dti_timestamp_fields(self, field):
        # extra fields from DatetimeIndex like quarter and week
        idx = tm.makeDateIndex(100)
        expected = getattr(idx, field)[-1]
        if field == "weekday_name":
            with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
                result = getattr(Timestamp(idx[-1]), field)
        else:
            result = getattr(Timestamp(idx[-1]), field)
        assert result == expected

    def test_dti_timestamp_freq_fields(self):
        # extra fields from DatetimeIndex like quarter and week
        idx = tm.makeDateIndex(100)

        assert idx.freq == Timestamp(idx[-1], idx.freq).freq
        assert idx.freqstr == Timestamp(idx[-1], idx.freq).freqstr

    # ----------------------------------------------------------------
    # DatetimeIndex.round

    def test_round_daily(self):
        dti = date_range("20130101 09:10:11", periods=5)
        result = dti.round("D")
        expected = date_range("20130101", periods=5)
        tm.assert_index_equal(result, expected)

        dti = dti.tz_localize("UTC").tz_convert("US/Eastern")
        result = dti.round("D")
        expected = date_range("20130101", periods=5).tz_localize("US/Eastern")
        tm.assert_index_equal(result, expected)

        result = dti.round("s")
        tm.assert_index_equal(result, dti)

    @pytest.mark.parametrize(
        "freq, error_msg",
        [
            ("Y", "<YearEnd: month=12> is a non-fixed frequency"),
            ("M", "<MonthEnd> is a non-fixed frequency"),
            ("foobar", "Invalid frequency: foobar"),
        ],
    )
    def test_round_invalid(self, freq, error_msg):
        dti = date_range("20130101 09:10:11", periods=5)
        dti = dti.tz_localize("UTC").tz_convert("US/Eastern")
        with pytest.raises(ValueError, match=error_msg):
            dti.round(freq)

    def test_round(self, tz_naive_fixture):
        tz = tz_naive_fixture
        rng = date_range(start="2016-01-01", periods=5, freq="30Min", tz=tz)
        elt = rng[1]

        expected_rng = DatetimeIndex(
            [
                Timestamp("2016-01-01 00:00:00", tz=tz, freq="30T"),
                Timestamp("2016-01-01 00:00:00", tz=tz, freq="30T"),
                Timestamp("2016-01-01 01:00:00", tz=tz, freq="30T"),
                Timestamp("2016-01-01 02:00:00", tz=tz, freq="30T"),
                Timestamp("2016-01-01 02:00:00", tz=tz, freq="30T"),
            ]
        )
        expected_elt = expected_rng[1]

        tm.assert_index_equal(rng.round(freq="H"), expected_rng)
        assert elt.round(freq="H") == expected_elt

        msg = pd._libs.tslibs.frequencies.INVALID_FREQ_ERR_MSG
        with pytest.raises(ValueError, match=msg):
            rng.round(freq="foo")
        with pytest.raises(ValueError, match=msg):
            elt.round(freq="foo")

        msg = "<MonthEnd> is a non-fixed frequency"
        with pytest.raises(ValueError, match=msg):
            rng.round(freq="M")
        with pytest.raises(ValueError, match=msg):
            elt.round(freq="M")

        # GH#14440 & GH#15578
        index = DatetimeIndex(["2016-10-17 12:00:00.0015"], tz=tz)
        result = index.round("ms")
        expected = DatetimeIndex(["2016-10-17 12:00:00.002000"], tz=tz)
        tm.assert_index_equal(result, expected)

        for freq in ["us", "ns"]:
            tm.assert_index_equal(index, index.round(freq))

        index = DatetimeIndex(["2016-10-17 12:00:00.00149"], tz=tz)
        result = index.round("ms")
        expected = DatetimeIndex(["2016-10-17 12:00:00.001000"], tz=tz)
        tm.assert_index_equal(result, expected)

        index = DatetimeIndex(["2016-10-17 12:00:00.001501031"])
        result = index.round("10ns")
        expected = DatetimeIndex(["2016-10-17 12:00:00.001501030"])
        tm.assert_index_equal(result, expected)

        with tm.assert_produces_warning(False):
            ts = "2016-10-17 12:00:00.001501031"
            DatetimeIndex([ts]).round("1010ns")

    def test_no_rounding_occurs(self, tz_naive_fixture):
        # GH 21262
        tz = tz_naive_fixture
        rng = date_range(start="2016-01-01", periods=5, freq="2Min", tz=tz)

        expected_rng = DatetimeIndex(
            [
                Timestamp("2016-01-01 00:00:00", tz=tz, freq="2T"),
                Timestamp("2016-01-01 00:02:00", tz=tz, freq="2T"),
                Timestamp("2016-01-01 00:04:00", tz=tz, freq="2T"),
                Timestamp("2016-01-01 00:06:00", tz=tz, freq="2T"),
                Timestamp("2016-01-01 00:08:00", tz=tz, freq="2T"),
            ]
        )

        tm.assert_index_equal(rng.round(freq="2T"), expected_rng)

    @pytest.mark.parametrize(
        "test_input, rounder, freq, expected",
        [
            (["2117-01-01 00:00:45"], "floor", "15s", ["2117-01-01 00:00:45"]),
            (["2117-01-01 00:00:45"], "ceil", "15s", ["2117-01-01 00:00:45"]),
            (
                ["2117-01-01 00:00:45.000000012"],
                "floor",
                "10ns",
                ["2117-01-01 00:00:45.000000010"],
            ),
            (
                ["1823-01-01 00:00:01.000000012"],
                "ceil",
                "10ns",
                ["1823-01-01 00:00:01.000000020"],
            ),
            (["1823-01-01 00:00:01"], "floor", "1s", ["1823-01-01 00:00:01"]),
            (["1823-01-01 00:00:01"], "ceil", "1s", ["1823-01-01 00:00:01"]),
            (["2018-01-01 00:15:00"], "ceil", "15T", ["2018-01-01 00:15:00"]),
            (["2018-01-01 00:15:00"], "floor", "15T", ["2018-01-01 00:15:00"]),
            (["1823-01-01 03:00:00"], "ceil", "3H", ["1823-01-01 03:00:00"]),
            (["1823-01-01 03:00:00"], "floor", "3H", ["1823-01-01 03:00:00"]),
            (
                ("NaT", "1823-01-01 00:00:01"),
                "floor",
                "1s",
                ("NaT", "1823-01-01 00:00:01"),
            ),
            (
                ("NaT", "1823-01-01 00:00:01"),
                "ceil",
                "1s",
                ("NaT", "1823-01-01 00:00:01"),
            ),
        ],
    )
    def test_ceil_floor_edge(self, test_input, rounder, freq, expected):
        dt = DatetimeIndex(list(test_input))
        func = getattr(dt, rounder)
        result = func(freq)
        expected = DatetimeIndex(list(expected))
        assert expected.equals(result)

    @pytest.mark.parametrize(
        "start, index_freq, periods",
        [("2018-01-01", "12H", 25), ("2018-01-01 0:0:0.124999", "1ns", 1000)],
    )
    @pytest.mark.parametrize(
        "round_freq",
        [
            "2ns",
            "3ns",
            "4ns",
            "5ns",
            "6ns",
            "7ns",
            "250ns",
            "500ns",
            "750ns",
            "1us",
            "19us",
            "250us",
            "500us",
            "750us",
            "1s",
            "2s",
            "3s",
            "12H",
            "1D",
        ],
    )
    def test_round_int64(self, start, index_freq, periods, round_freq):
        dt = date_range(start=start, freq=index_freq, periods=periods)
        unit = to_offset(round_freq).nanos

        # test floor
        result = dt.floor(round_freq)
        diff = dt.asi8 - result.asi8
        mod = result.asi8 % unit
        assert (mod == 0).all(), "floor not a {} multiple".format(round_freq)
        assert (0 <= diff).all() and (diff < unit).all(), "floor error"

        # test ceil
        result = dt.ceil(round_freq)
        diff = result.asi8 - dt.asi8
        mod = result.asi8 % unit
        assert (mod == 0).all(), "ceil not a {} multiple".format(round_freq)
        assert (0 <= diff).all() and (diff < unit).all(), "ceil error"

        # test round
        result = dt.round(round_freq)
        diff = abs(result.asi8 - dt.asi8)
        mod = result.asi8 % unit
        assert (mod == 0).all(), "round not a {} multiple".format(round_freq)
        assert (diff <= unit // 2).all(), "round error"
        if unit % 2 == 0:
            assert (
                result.asi8[diff == unit // 2] % 2 == 0
            ).all(), "round half to even error"

    # ----------------------------------------------------------------
    # DatetimeIndex.normalize

    def test_normalize(self):
        rng = date_range("1/1/2000 9:30", periods=10, freq="D")

        result = rng.normalize()
        expected = date_range("1/1/2000", periods=10, freq="D")
        tm.assert_index_equal(result, expected)

        arr_ns = np.array([1380585623454345752, 1380585612343234312]).astype(
            "datetime64[ns]"
        )
        rng_ns = DatetimeIndex(arr_ns)
        rng_ns_normalized = rng_ns.normalize()

        arr_ns = np.array([1380585600000000000, 1380585600000000000]).astype(
            "datetime64[ns]"
        )
        expected = DatetimeIndex(arr_ns)
        tm.assert_index_equal(rng_ns_normalized, expected)

        assert result.is_normalized
        assert not rng.is_normalized

    def test_normalize_nat(self):
        dti = DatetimeIndex([pd.NaT, Timestamp("2018-01-01 01:00:00")])
        result = dti.normalize()
        expected = DatetimeIndex([pd.NaT, Timestamp("2018-01-01")])
        tm.assert_index_equal(result, expected)


class TestDateTimeIndexToJulianDate:
    def test_1700(self):
        dr = date_range(start=Timestamp("1710-10-01"), periods=5, freq="D")
        r1 = pd.Index([x.to_julian_date() for x in dr])
        r2 = dr.to_julian_date()
        assert isinstance(r2, pd.Float64Index)
        tm.assert_index_equal(r1, r2)

    def test_2000(self):
        dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="D")
        r1 = pd.Index([x.to_julian_date() for x in dr])
        r2 = dr.to_julian_date()
        assert isinstance(r2, pd.Float64Index)
        tm.assert_index_equal(r1, r2)

    def test_hour(self):
        dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="H")
        r1 = pd.Index([x.to_julian_date() for x in dr])
        r2 = dr.to_julian_date()
        assert isinstance(r2, pd.Float64Index)
        tm.assert_index_equal(r1, r2)

    def test_minute(self):
        dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="T")
        r1 = pd.Index([x.to_julian_date() for x in dr])
        r2 = dr.to_julian_date()
        assert isinstance(r2, pd.Float64Index)
        tm.assert_index_equal(r1, r2)

    def test_second(self):
        dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="S")
        r1 = pd.Index([x.to_julian_date() for x in dr])
        r2 = dr.to_julian_date()
        assert isinstance(r2, pd.Float64Index)
        tm.assert_index_equal(r1, r2)
