import numpy as np
import pytest

import pandas as pd
from pandas import DataFrame, MultiIndex, date_range
import pandas._testing as tm


def test_tolist(idx):
    result = idx.tolist()
    exp = list(idx.values)
    assert result == exp


def test_to_numpy(idx):
    result = idx.to_numpy()
    exp = idx.values
    tm.assert_numpy_array_equal(result, exp)


def test_to_frame():
    tuples = [(1, "one"), (1, "two"), (2, "one"), (2, "two")]

    index = MultiIndex.from_tuples(tuples)
    result = index.to_frame(index=False)
    expected = DataFrame(tuples)
    tm.assert_frame_equal(result, expected)

    result = index.to_frame()
    expected.index = index
    tm.assert_frame_equal(result, expected)

    tuples = [(1, "one"), (1, "two"), (2, "one"), (2, "two")]
    index = MultiIndex.from_tuples(tuples, names=["first", "second"])
    result = index.to_frame(index=False)
    expected = DataFrame(tuples)
    expected.columns = ["first", "second"]
    tm.assert_frame_equal(result, expected)

    result = index.to_frame()
    expected.index = index
    tm.assert_frame_equal(result, expected)

    # See GH-22580
    index = MultiIndex.from_tuples(tuples)
    result = index.to_frame(index=False, name=["first", "second"])
    expected = DataFrame(tuples)
    expected.columns = ["first", "second"]
    tm.assert_frame_equal(result, expected)

    result = index.to_frame(name=["first", "second"])
    expected.index = index
    expected.columns = ["first", "second"]
    tm.assert_frame_equal(result, expected)

    msg = "'name' must be a list / sequence of column names."
    with pytest.raises(TypeError, match=msg):
        index.to_frame(name="first")

    msg = "'name' should have same length as number of levels on index."
    with pytest.raises(ValueError, match=msg):
        index.to_frame(name=["first"])

    # Tests for datetime index
    index = MultiIndex.from_product([range(5), pd.date_range("20130101", periods=3)])
    result = index.to_frame(index=False)
    expected = DataFrame(
        {
            0: np.repeat(np.arange(5, dtype="int64"), 3),
            1: np.tile(pd.date_range("20130101", periods=3), 5),
        }
    )
    tm.assert_frame_equal(result, expected)

    result = index.to_frame()
    expected.index = index
    tm.assert_frame_equal(result, expected)

    # See GH-22580
    result = index.to_frame(index=False, name=["first", "second"])
    expected = DataFrame(
        {
            "first": np.repeat(np.arange(5, dtype="int64"), 3),
            "second": np.tile(pd.date_range("20130101", periods=3), 5),
        }
    )
    tm.assert_frame_equal(result, expected)

    result = index.to_frame(name=["first", "second"])
    expected.index = index
    tm.assert_frame_equal(result, expected)


def test_to_frame_dtype_fidelity():
    # GH 22420
    mi = pd.MultiIndex.from_arrays(
        [
            pd.date_range("19910905", periods=6, tz="US/Eastern"),
            [1, 1, 1, 2, 2, 2],
            pd.Categorical(["a", "a", "b", "b", "c", "c"], ordered=True),
            ["x", "x", "y", "z", "x", "y"],
        ],
        names=["dates", "a", "b", "c"],
    )
    original_dtypes = {name: mi.levels[i].dtype for i, name in enumerate(mi.names)}

    expected_df = pd.DataFrame(
        {
            "dates": pd.date_range("19910905", periods=6, tz="US/Eastern"),
            "a": [1, 1, 1, 2, 2, 2],
            "b": pd.Categorical(["a", "a", "b", "b", "c", "c"], ordered=True),
            "c": ["x", "x", "y", "z", "x", "y"],
        }
    )
    df = mi.to_frame(index=False)
    df_dtypes = df.dtypes.to_dict()

    tm.assert_frame_equal(df, expected_df)
    assert original_dtypes == df_dtypes


def test_to_frame_resulting_column_order():
    # GH 22420
    expected = ["z", 0, "a"]
    mi = pd.MultiIndex.from_arrays(
        [["a", "b", "c"], ["x", "y", "z"], ["q", "w", "e"]], names=expected
    )
    result = mi.to_frame().columns.tolist()
    assert result == expected


def test_roundtrip_pickle_with_tz():
    return  # FIXME: this can't be right?

    # GH 8367
    # round-trip of timezone
    index = MultiIndex.from_product(
        [[1, 2], ["a", "b"], date_range("20130101", periods=3, tz="US/Eastern")],
        names=["one", "two", "three"],
    )
    unpickled = tm.round_trip_pickle(index)
    assert index.equal_levels(unpickled)


def test_pickle(indices):
    return  # FIXME: this can't be right?

    unpickled = tm.round_trip_pickle(indices)
    assert indices.equals(unpickled)
    original_name, indices.name = indices.name, "foo"
    unpickled = tm.round_trip_pickle(indices)
    assert indices.equals(unpickled)
    indices.name = original_name


def test_to_series(idx):
    # assert that we are creating a copy of the index

    s = idx.to_series()
    assert s.values is not idx.values
    assert s.index is not idx
    assert s.name == idx.name


def test_to_series_with_arguments(idx):
    # GH18699

    # index kwarg
    s = idx.to_series(index=idx)

    assert s.values is not idx.values
    assert s.index is idx
    assert s.name == idx.name

    # name kwarg
    idx = idx
    s = idx.to_series(name="__test")

    assert s.values is not idx.values
    assert s.index is not idx
    assert s.name != idx.name


def test_to_flat_index(idx):
    expected = pd.Index(
        (
            ("foo", "one"),
            ("foo", "two"),
            ("bar", "one"),
            ("baz", "two"),
            ("qux", "one"),
            ("qux", "two"),
        ),
        tupleize_cols=False,
    )
    result = idx.to_flat_index()
    tm.assert_index_equal(result, expected)
