import numpy as np
import pytest

from pandas import MultiIndex
import pandas._testing as tm


def test_numeric_compat(idx):
    with pytest.raises(TypeError, match="cannot perform __mul__"):
        idx * 1

    with pytest.raises(TypeError, match="cannot perform __rmul__"):
        1 * idx

    div_err = "cannot perform __truediv__"
    with pytest.raises(TypeError, match=div_err):
        idx / 1

    div_err = div_err.replace(" __", " __r")
    with pytest.raises(TypeError, match=div_err):
        1 / idx

    with pytest.raises(TypeError, match="cannot perform __floordiv__"):
        idx // 1

    with pytest.raises(TypeError, match="cannot perform __rfloordiv__"):
        1 // idx


@pytest.mark.parametrize("method", ["all", "any"])
def test_logical_compat(idx, method):
    msg = f"cannot perform {method}"

    with pytest.raises(TypeError, match=msg):
        getattr(idx, method)()


def test_boolean_context_compat(idx):

    msg = (
        "The truth value of a MultiIndex is ambiguous. "
        r"Use a.empty, a.bool\(\), a.item\(\), a.any\(\) or a.all\(\)."
    )
    with pytest.raises(ValueError, match=msg):
        bool(idx)


def test_boolean_context_compat2():

    # boolean context compat
    # GH7897
    i1 = MultiIndex.from_tuples([("A", 1), ("A", 2)])
    i2 = MultiIndex.from_tuples([("A", 1), ("A", 3)])
    common = i1.intersection(i2)

    msg = (
        r"The truth value of a MultiIndex is ambiguous\. "
        r"Use a\.empty, a\.bool\(\), a\.item\(\), a\.any\(\) or a\.all\(\)\."
    )
    with pytest.raises(ValueError, match=msg):
        bool(common)


def test_inplace_mutation_resets_values():
    levels = [["a", "b", "c"], [4]]
    levels2 = [[1, 2, 3], ["a"]]
    codes = [[0, 1, 0, 2, 2, 0], [0, 0, 0, 0, 0, 0]]

    mi1 = MultiIndex(levels=levels, codes=codes)
    mi2 = MultiIndex(levels=levels2, codes=codes)
    vals = mi1.values.copy()
    vals2 = mi2.values.copy()

    assert mi1._tuples is not None

    # Make sure level setting works
    new_vals = mi1.set_levels(levels2).values
    tm.assert_almost_equal(vals2, new_vals)

    # Non-inplace doesn't kill _tuples [implementation detail]
    tm.assert_almost_equal(mi1._tuples, vals)

    # ...and values is still same too
    tm.assert_almost_equal(mi1.values, vals)

    # Inplace should kill _tuples
    mi1.set_levels(levels2, inplace=True)
    tm.assert_almost_equal(mi1.values, vals2)

    # Make sure label setting works too
    codes2 = [[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0]]
    exp_values = np.empty((6,), dtype=object)
    exp_values[:] = [(1, "a")] * 6

    # Must be 1d array of tuples
    assert exp_values.shape == (6,)
    new_values = mi2.set_codes(codes2).values

    # Not inplace shouldn't change
    tm.assert_almost_equal(mi2._tuples, vals2)

    # Should have correct values
    tm.assert_almost_equal(exp_values, new_values)

    # ...and again setting inplace should kill _tuples, etc
    mi2.set_codes(codes2, inplace=True)
    tm.assert_almost_equal(mi2.values, new_values)


def test_ndarray_compat_properties(idx, compat_props):
    assert idx.T.equals(idx)
    assert idx.transpose().equals(idx)

    values = idx.values
    for prop in compat_props:
        assert getattr(idx, prop) == getattr(values, prop)

    # test for validity
    idx.nbytes
    idx.values.nbytes


def test_pickle_compat_construction():
    # this is testing for pickle compat
    # need an object to create with
    with pytest.raises(TypeError, match="Must pass both levels and codes"):
        MultiIndex()