"""
Tests for scalar Timedelta arithmetic ops
"""
from datetime import datetime, timedelta
import operator

import numpy as np
import pytest

import pandas as pd
from pandas import NaT, Timedelta, Timestamp, _is_numpy_dev, offsets
import pandas._testing as tm
from pandas.core import ops


class TestTimedeltaAdditionSubtraction:
    """
    Tests for Timedelta methods:

        __add__, __radd__,
        __sub__, __rsub__
    """

    @pytest.mark.parametrize(
        "ten_seconds",
        [
            Timedelta(10, unit="s"),
            timedelta(seconds=10),
            np.timedelta64(10, "s"),
            np.timedelta64(10000000000, "ns"),
            offsets.Second(10),
        ],
    )
    def test_td_add_sub_ten_seconds(self, ten_seconds):
        # GH#6808
        base = Timestamp("20130101 09:01:12.123456")
        expected_add = Timestamp("20130101 09:01:22.123456")
        expected_sub = Timestamp("20130101 09:01:02.123456")

        result = base + ten_seconds
        assert result == expected_add

        result = base - ten_seconds
        assert result == expected_sub

    @pytest.mark.parametrize(
        "one_day_ten_secs",
        [
            Timedelta("1 day, 00:00:10"),
            Timedelta("1 days, 00:00:10"),
            timedelta(days=1, seconds=10),
            np.timedelta64(1, "D") + np.timedelta64(10, "s"),
            offsets.Day() + offsets.Second(10),
        ],
    )
    def test_td_add_sub_one_day_ten_seconds(self, one_day_ten_secs):
        # GH#6808
        base = Timestamp("20130102 09:01:12.123456")
        expected_add = Timestamp("20130103 09:01:22.123456")
        expected_sub = Timestamp("20130101 09:01:02.123456")

        result = base + one_day_ten_secs
        assert result == expected_add

        result = base - one_day_ten_secs
        assert result == expected_sub

    @pytest.mark.parametrize("op", [operator.add, ops.radd])
    def test_td_add_datetimelike_scalar(self, op):
        # GH#19738
        td = Timedelta(10, unit="d")

        result = op(td, datetime(2016, 1, 1))
        if op is operator.add:
            # datetime + Timedelta does _not_ call Timedelta.__radd__,
            # so we get a datetime back instead of a Timestamp
            assert isinstance(result, Timestamp)
        assert result == Timestamp(2016, 1, 11)

        result = op(td, Timestamp("2018-01-12 18:09"))
        assert isinstance(result, Timestamp)
        assert result == Timestamp("2018-01-22 18:09")

        result = op(td, np.datetime64("2018-01-12"))
        assert isinstance(result, Timestamp)
        assert result == Timestamp("2018-01-22")

        result = op(td, NaT)
        assert result is NaT

    @pytest.mark.parametrize("op", [operator.add, ops.radd])
    def test_td_add_td(self, op):
        td = Timedelta(10, unit="d")

        result = op(td, Timedelta(days=10))
        assert isinstance(result, Timedelta)
        assert result == Timedelta(days=20)

    @pytest.mark.parametrize("op", [operator.add, ops.radd])
    def test_td_add_pytimedelta(self, op):
        td = Timedelta(10, unit="d")
        result = op(td, timedelta(days=9))
        assert isinstance(result, Timedelta)
        assert result == Timedelta(days=19)

    @pytest.mark.parametrize("op", [operator.add, ops.radd])
    def test_td_add_timedelta64(self, op):
        td = Timedelta(10, unit="d")
        result = op(td, np.timedelta64(-4, "D"))
        assert isinstance(result, Timedelta)
        assert result == Timedelta(days=6)

    @pytest.mark.parametrize("op", [operator.add, ops.radd])
    def test_td_add_offset(self, op):
        td = Timedelta(10, unit="d")

        result = op(td, offsets.Hour(6))
        assert isinstance(result, Timedelta)
        assert result == Timedelta(days=10, hours=6)

    def test_td_sub_td(self):
        td = Timedelta(10, unit="d")
        expected = Timedelta(0, unit="ns")
        result = td - td
        assert isinstance(result, Timedelta)
        assert result == expected

    def test_td_sub_pytimedelta(self):
        td = Timedelta(10, unit="d")
        expected = Timedelta(0, unit="ns")

        result = td - td.to_pytimedelta()
        assert isinstance(result, Timedelta)
        assert result == expected

        result = td.to_pytimedelta() - td
        assert isinstance(result, Timedelta)
        assert result == expected

    def test_td_sub_timedelta64(self):
        td = Timedelta(10, unit="d")
        expected = Timedelta(0, unit="ns")

        result = td - td.to_timedelta64()
        assert isinstance(result, Timedelta)
        assert result == expected

        result = td.to_timedelta64() - td
        assert isinstance(result, Timedelta)
        assert result == expected

    def test_td_sub_nat(self):
        # In this context pd.NaT is treated as timedelta-like
        td = Timedelta(10, unit="d")
        result = td - NaT
        assert result is NaT

    def test_td_sub_td64_nat(self):
        td = Timedelta(10, unit="d")
        td_nat = np.timedelta64("NaT")

        result = td - td_nat
        assert result is NaT

        result = td_nat - td
        assert result is NaT

    def test_td_sub_offset(self):
        td = Timedelta(10, unit="d")
        result = td - offsets.Hour(1)
        assert isinstance(result, Timedelta)
        assert result == Timedelta(239, unit="h")

    def test_td_add_sub_numeric_raises(self):
        td = Timedelta(10, unit="d")
        for other in [2, 2.0, np.int64(2), np.float64(2)]:
            with pytest.raises(TypeError):
                td + other
            with pytest.raises(TypeError):
                other + td
            with pytest.raises(TypeError):
                td - other
            with pytest.raises(TypeError):
                other - td

    def test_td_rsub_nat(self):
        td = Timedelta(10, unit="d")
        result = NaT - td
        assert result is NaT

        result = np.datetime64("NaT") - td
        assert result is NaT

    def test_td_rsub_offset(self):
        result = offsets.Hour(1) - Timedelta(10, unit="d")
        assert isinstance(result, Timedelta)
        assert result == Timedelta(-239, unit="h")

    def test_td_sub_timedeltalike_object_dtype_array(self):
        # GH#21980
        arr = np.array([Timestamp("20130101 9:01"), Timestamp("20121230 9:02")])
        exp = np.array([Timestamp("20121231 9:01"), Timestamp("20121229 9:02")])
        res = arr - Timedelta("1D")
        tm.assert_numpy_array_equal(res, exp)

    def test_td_sub_mixed_most_timedeltalike_object_dtype_array(self):
        # GH#21980
        now = Timestamp.now()
        arr = np.array([now, Timedelta("1D"), np.timedelta64(2, "h")])
        exp = np.array(
            [
                now - Timedelta("1D"),
                Timedelta("0D"),
                np.timedelta64(2, "h") - Timedelta("1D"),
            ]
        )
        res = arr - Timedelta("1D")
        tm.assert_numpy_array_equal(res, exp)

    def test_td_rsub_mixed_most_timedeltalike_object_dtype_array(self):
        # GH#21980
        now = Timestamp.now()
        arr = np.array([now, Timedelta("1D"), np.timedelta64(2, "h")])
        with pytest.raises(TypeError):
            Timedelta("1D") - arr

    @pytest.mark.parametrize("op", [operator.add, ops.radd])
    def test_td_add_timedeltalike_object_dtype_array(self, op):
        # GH#21980
        arr = np.array([Timestamp("20130101 9:01"), Timestamp("20121230 9:02")])
        exp = np.array([Timestamp("20130102 9:01"), Timestamp("20121231 9:02")])
        res = op(arr, Timedelta("1D"))
        tm.assert_numpy_array_equal(res, exp)

    @pytest.mark.parametrize("op", [operator.add, ops.radd])
    def test_td_add_mixed_timedeltalike_object_dtype_array(self, op):
        # GH#21980
        now = Timestamp.now()
        arr = np.array([now, Timedelta("1D")])
        exp = np.array([now + Timedelta("1D"), Timedelta("2D")])
        res = op(arr, Timedelta("1D"))
        tm.assert_numpy_array_equal(res, exp)

    # TODO: moved from index tests following #24365, may need de-duplication
    def test_ops_ndarray(self):
        td = Timedelta("1 day")

        # timedelta, timedelta
        other = pd.to_timedelta(["1 day"]).values
        expected = pd.to_timedelta(["2 days"]).values
        tm.assert_numpy_array_equal(td + other, expected)
        tm.assert_numpy_array_equal(other + td, expected)
        msg = r"unsupported operand type\(s\) for \+: 'Timedelta' and 'int'"
        with pytest.raises(TypeError, match=msg):
            td + np.array([1])
        msg = r"unsupported operand type\(s\) for \+: 'numpy.ndarray' and 'Timedelta'"
        with pytest.raises(TypeError, match=msg):
            np.array([1]) + td

        expected = pd.to_timedelta(["0 days"]).values
        tm.assert_numpy_array_equal(td - other, expected)
        tm.assert_numpy_array_equal(-other + td, expected)
        msg = r"unsupported operand type\(s\) for -: 'Timedelta' and 'int'"
        with pytest.raises(TypeError, match=msg):
            td - np.array([1])
        msg = r"unsupported operand type\(s\) for -: 'numpy.ndarray' and 'Timedelta'"
        with pytest.raises(TypeError, match=msg):
            np.array([1]) - td

        expected = pd.to_timedelta(["2 days"]).values
        tm.assert_numpy_array_equal(td * np.array([2]), expected)
        tm.assert_numpy_array_equal(np.array([2]) * td, expected)
        msg = (
            "ufunc '?multiply'? cannot use operands with types"
            r" dtype\('<m8\[ns\]'\) and dtype\('<m8\[ns\]'\)"
        )
        with pytest.raises(TypeError, match=msg):
            td * other
        with pytest.raises(TypeError, match=msg):
            other * td

        tm.assert_numpy_array_equal(td / other, np.array([1], dtype=np.float64))
        tm.assert_numpy_array_equal(other / td, np.array([1], dtype=np.float64))

        # timedelta, datetime
        other = pd.to_datetime(["2000-01-01"]).values
        expected = pd.to_datetime(["2000-01-02"]).values
        tm.assert_numpy_array_equal(td + other, expected)
        tm.assert_numpy_array_equal(other + td, expected)

        expected = pd.to_datetime(["1999-12-31"]).values
        tm.assert_numpy_array_equal(-td + other, expected)
        tm.assert_numpy_array_equal(other - td, expected)


class TestTimedeltaMultiplicationDivision:
    """
    Tests for Timedelta methods:

        __mul__, __rmul__,
        __div__, __rdiv__,
        __truediv__, __rtruediv__,
        __floordiv__, __rfloordiv__,
        __mod__, __rmod__,
        __divmod__, __rdivmod__
    """

    # ---------------------------------------------------------------
    # Timedelta.__mul__, __rmul__

    @pytest.mark.parametrize(
        "td_nat", [NaT, np.timedelta64("NaT", "ns"), np.timedelta64("NaT")]
    )
    @pytest.mark.parametrize("op", [operator.mul, ops.rmul])
    def test_td_mul_nat(self, op, td_nat):
        # GH#19819
        td = Timedelta(10, unit="d")
        with pytest.raises(TypeError):
            op(td, td_nat)

    @pytest.mark.parametrize("nan", [np.nan, np.float64("NaN"), float("nan")])
    @pytest.mark.parametrize("op", [operator.mul, ops.rmul])
    def test_td_mul_nan(self, op, nan):
        # np.float64('NaN') has a 'dtype' attr, avoid treating as array
        td = Timedelta(10, unit="d")
        result = op(td, nan)
        assert result is NaT

    @pytest.mark.parametrize("op", [operator.mul, ops.rmul])
    def test_td_mul_scalar(self, op):
        # GH#19738
        td = Timedelta(minutes=3)

        result = op(td, 2)
        assert result == Timedelta(minutes=6)

        result = op(td, 1.5)
        assert result == Timedelta(minutes=4, seconds=30)

        assert op(td, np.nan) is NaT

        assert op(-1, td).value == -1 * td.value
        assert op(-1.0, td).value == -1.0 * td.value

        with pytest.raises(TypeError):
            # timedelta * datetime is gibberish
            op(td, Timestamp(2016, 1, 2))

        with pytest.raises(TypeError):
            # invalid multiply with another timedelta
            op(td, td)

    # ---------------------------------------------------------------
    # Timedelta.__div__, __truediv__

    def test_td_div_timedeltalike_scalar(self):
        # GH#19738
        td = Timedelta(10, unit="d")

        result = td / offsets.Hour(1)
        assert result == 240

        assert td / td == 1
        assert td / np.timedelta64(60, "h") == 4

        assert np.isnan(td / NaT)

    def test_td_div_numeric_scalar(self):
        # GH#19738
        td = Timedelta(10, unit="d")

        result = td / 2
        assert isinstance(result, Timedelta)
        assert result == Timedelta(days=5)

        result = td / 5.0
        assert isinstance(result, Timedelta)
        assert result == Timedelta(days=2)

    @pytest.mark.parametrize(
        "nan",
        [
            np.nan,
            pytest.param(
                np.float64("NaN"),
                marks=pytest.mark.xfail(
                    _is_numpy_dev,
                    reason="https://github.com/pandas-dev/pandas/issues/31992",
                    strict=False,
                ),
            ),
            float("nan"),
        ],
    )
    def test_td_div_nan(self, nan):
        # np.float64('NaN') has a 'dtype' attr, avoid treating as array
        td = Timedelta(10, unit="d")
        result = td / nan
        assert result is NaT

        result = td // nan
        assert result is NaT

    # ---------------------------------------------------------------
    # Timedelta.__rdiv__

    def test_td_rdiv_timedeltalike_scalar(self):
        # GH#19738
        td = Timedelta(10, unit="d")
        result = offsets.Hour(1) / td
        assert result == 1 / 240.0

        assert np.timedelta64(60, "h") / td == 0.25

    # ---------------------------------------------------------------
    # Timedelta.__floordiv__

    def test_td_floordiv_timedeltalike_scalar(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=4)
        scalar = Timedelta(hours=3, minutes=3)

        assert td // scalar == 1
        assert -td // scalar.to_pytimedelta() == -2
        assert (2 * td) // scalar.to_timedelta64() == 2

    def test_td_floordiv_null_scalar(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=4)

        assert td // np.nan is NaT
        assert np.isnan(td // NaT)
        assert np.isnan(td // np.timedelta64("NaT"))

    def test_td_floordiv_offsets(self):
        # GH#19738
        td = Timedelta(hours=3, minutes=4)
        assert td // offsets.Hour(1) == 3
        assert td // offsets.Minute(2) == 92

    def test_td_floordiv_invalid_scalar(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=4)

        with pytest.raises(TypeError):
            td // np.datetime64("2016-01-01", dtype="datetime64[us]")

    def test_td_floordiv_numeric_scalar(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=4)

        expected = Timedelta(hours=1, minutes=32)
        assert td // 2 == expected
        assert td // 2.0 == expected
        assert td // np.float64(2.0) == expected
        assert td // np.int32(2.0) == expected
        assert td // np.uint8(2.0) == expected

    def test_td_floordiv_timedeltalike_array(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=4)
        scalar = Timedelta(hours=3, minutes=3)

        # Array-like others
        assert td // np.array(scalar.to_timedelta64()) == 1

        res = (3 * td) // np.array([scalar.to_timedelta64()])
        expected = np.array([3], dtype=np.int64)
        tm.assert_numpy_array_equal(res, expected)

        res = (10 * td) // np.array([scalar.to_timedelta64(), np.timedelta64("NaT")])
        expected = np.array([10, np.nan])
        tm.assert_numpy_array_equal(res, expected)

    def test_td_floordiv_numeric_series(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=4)
        ser = pd.Series([1], dtype=np.int64)
        res = td // ser
        assert res.dtype.kind == "m"

    # ---------------------------------------------------------------
    # Timedelta.__rfloordiv__

    def test_td_rfloordiv_timedeltalike_scalar(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=3)
        scalar = Timedelta(hours=3, minutes=4)

        # scalar others
        # x // Timedelta is defined only for timedelta-like x. int-like,
        # float-like, and date-like, in particular, should all either
        # a) raise TypeError directly or
        # b) return NotImplemented, following which the reversed
        #    operation will raise TypeError.
        assert td.__rfloordiv__(scalar) == 1
        assert (-td).__rfloordiv__(scalar.to_pytimedelta()) == -2
        assert (2 * td).__rfloordiv__(scalar.to_timedelta64()) == 0

    def test_td_rfloordiv_null_scalar(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=3)

        assert np.isnan(td.__rfloordiv__(NaT))
        assert np.isnan(td.__rfloordiv__(np.timedelta64("NaT")))

    def test_td_rfloordiv_offsets(self):
        # GH#19738
        assert offsets.Hour(1) // Timedelta(minutes=25) == 2

    def test_td_rfloordiv_invalid_scalar(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=3)

        dt64 = np.datetime64("2016-01-01", "us")
        with pytest.raises(TypeError):
            td.__rfloordiv__(dt64)

    def test_td_rfloordiv_numeric_scalar(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=3)

        assert td.__rfloordiv__(np.nan) is NotImplemented
        assert td.__rfloordiv__(3.5) is NotImplemented
        assert td.__rfloordiv__(2) is NotImplemented

        with pytest.raises(TypeError):
            td.__rfloordiv__(np.float64(2.0))
        with pytest.raises(TypeError):
            td.__rfloordiv__(np.uint8(9))
        with pytest.raises(TypeError, match="Invalid dtype"):
            # deprecated GH#19761, enforced GH#29797
            td.__rfloordiv__(np.int32(2.0))

    def test_td_rfloordiv_timedeltalike_array(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=3)
        scalar = Timedelta(hours=3, minutes=4)

        # Array-like others
        assert td.__rfloordiv__(np.array(scalar.to_timedelta64())) == 1

        res = td.__rfloordiv__(np.array([(3 * scalar).to_timedelta64()]))
        expected = np.array([3], dtype=np.int64)
        tm.assert_numpy_array_equal(res, expected)

        arr = np.array([(10 * scalar).to_timedelta64(), np.timedelta64("NaT")])
        res = td.__rfloordiv__(arr)
        expected = np.array([10, np.nan])
        tm.assert_numpy_array_equal(res, expected)

    def test_td_rfloordiv_numeric_series(self):
        # GH#18846
        td = Timedelta(hours=3, minutes=3)
        ser = pd.Series([1], dtype=np.int64)
        res = td.__rfloordiv__(ser)
        assert res is NotImplemented

        with pytest.raises(TypeError, match="Invalid dtype"):
            # Deprecated GH#19761, enforced GH#29797
            # TODO: GH-19761. Change to TypeError.
            ser // td

    # ----------------------------------------------------------------
    # Timedelta.__mod__, __rmod__

    def test_mod_timedeltalike(self):
        # GH#19365
        td = Timedelta(hours=37)

        # Timedelta-like others
        result = td % Timedelta(hours=6)
        assert isinstance(result, Timedelta)
        assert result == Timedelta(hours=1)

        result = td % timedelta(minutes=60)
        assert isinstance(result, Timedelta)
        assert result == Timedelta(0)

        result = td % NaT
        assert result is NaT

    def test_mod_timedelta64_nat(self):
        # GH#19365
        td = Timedelta(hours=37)

        result = td % np.timedelta64("NaT", "ns")
        assert result is NaT

    def test_mod_timedelta64(self):
        # GH#19365
        td = Timedelta(hours=37)

        result = td % np.timedelta64(2, "h")
        assert isinstance(result, Timedelta)
        assert result == Timedelta(hours=1)

    def test_mod_offset(self):
        # GH#19365
        td = Timedelta(hours=37)

        result = td % offsets.Hour(5)
        assert isinstance(result, Timedelta)
        assert result == Timedelta(hours=2)

    def test_mod_numeric(self):
        # GH#19365
        td = Timedelta(hours=37)

        # Numeric Others
        result = td % 2
        assert isinstance(result, Timedelta)
        assert result == Timedelta(0)

        result = td % 1e12
        assert isinstance(result, Timedelta)
        assert result == Timedelta(minutes=3, seconds=20)

        result = td % int(1e12)
        assert isinstance(result, Timedelta)
        assert result == Timedelta(minutes=3, seconds=20)

    def test_mod_invalid(self):
        # GH#19365
        td = Timedelta(hours=37)

        with pytest.raises(TypeError):
            td % Timestamp("2018-01-22")

        with pytest.raises(TypeError):
            td % []

    def test_rmod_pytimedelta(self):
        # GH#19365
        td = Timedelta(minutes=3)

        result = timedelta(minutes=4) % td
        assert isinstance(result, Timedelta)
        assert result == Timedelta(minutes=1)

    def test_rmod_timedelta64(self):
        # GH#19365
        td = Timedelta(minutes=3)
        result = np.timedelta64(5, "m") % td
        assert isinstance(result, Timedelta)
        assert result == Timedelta(minutes=2)

    def test_rmod_invalid(self):
        # GH#19365
        td = Timedelta(minutes=3)

        with pytest.raises(TypeError):
            Timestamp("2018-01-22") % td

        with pytest.raises(TypeError):
            15 % td

        with pytest.raises(TypeError):
            16.0 % td

        with pytest.raises(TypeError):
            np.array([22, 24]) % td

    # ----------------------------------------------------------------
    # Timedelta.__divmod__, __rdivmod__

    def test_divmod_numeric(self):
        # GH#19365
        td = Timedelta(days=2, hours=6)

        result = divmod(td, 53 * 3600 * 1e9)
        assert result[0] == Timedelta(1, unit="ns")
        assert isinstance(result[1], Timedelta)
        assert result[1] == Timedelta(hours=1)

        assert result
        result = divmod(td, np.nan)
        assert result[0] is NaT
        assert result[1] is NaT

    def test_divmod(self):
        # GH#19365
        td = Timedelta(days=2, hours=6)

        result = divmod(td, timedelta(days=1))
        assert result[0] == 2
        assert isinstance(result[1], Timedelta)
        assert result[1] == Timedelta(hours=6)

        result = divmod(td, 54)
        assert result[0] == Timedelta(hours=1)
        assert isinstance(result[1], Timedelta)
        assert result[1] == Timedelta(0)

        result = divmod(td, NaT)
        assert np.isnan(result[0])
        assert result[1] is NaT

    def test_divmod_offset(self):
        # GH#19365
        td = Timedelta(days=2, hours=6)

        result = divmod(td, offsets.Hour(-4))
        assert result[0] == -14
        assert isinstance(result[1], Timedelta)
        assert result[1] == Timedelta(hours=-2)

    def test_divmod_invalid(self):
        # GH#19365
        td = Timedelta(days=2, hours=6)

        with pytest.raises(TypeError):
            divmod(td, Timestamp("2018-01-22"))

    def test_rdivmod_pytimedelta(self):
        # GH#19365
        result = divmod(timedelta(days=2, hours=6), Timedelta(days=1))
        assert result[0] == 2
        assert isinstance(result[1], Timedelta)
        assert result[1] == Timedelta(hours=6)

    def test_rdivmod_offset(self):
        result = divmod(offsets.Hour(54), Timedelta(hours=-4))
        assert result[0] == -14
        assert isinstance(result[1], Timedelta)
        assert result[1] == Timedelta(hours=-2)

    def test_rdivmod_invalid(self):
        # GH#19365
        td = Timedelta(minutes=3)

        with pytest.raises(TypeError):
            divmod(Timestamp("2018-01-22"), td)

        with pytest.raises(TypeError):
            divmod(15, td)

        with pytest.raises(TypeError):
            divmod(16.0, td)

        with pytest.raises(TypeError):
            divmod(np.array([22, 24]), td)

    # ----------------------------------------------------------------

    @pytest.mark.parametrize(
        "op", [operator.mul, ops.rmul, operator.truediv, ops.rdiv, ops.rsub]
    )
    @pytest.mark.parametrize(
        "arr",
        [
            np.array([Timestamp("20130101 9:01"), Timestamp("20121230 9:02")]),
            np.array([Timestamp.now(), Timedelta("1D")]),
        ],
    )
    def test_td_op_timedelta_timedeltalike_array(self, op, arr):
        with pytest.raises(TypeError):
            op(arr, Timedelta("1D"))
