# Licensed under a 3-clause BSD style license - see LICENSE.rst


import copy
import pickle
from io import StringIO

import numpy as np
import pytest

from astropy import coordinates, time
from astropy import units as u
from astropy.coordinates import EarthLocation, SkyCoord
from astropy.coordinates.tests.test_representation import representation_equal
from astropy.io.ascii.connect import _get_connectors_table
from astropy.table import (
    Column,
    NdarrayMixin,
    QTable,
    Table,
    hstack,
    join,
    serialize,
    table_helpers,
    vstack,
)
from astropy.table.column import BaseColumn
from astropy.table.serialize import represent_mixins_as_columns
from astropy.table.table_helpers import ArrayWrapper
from astropy.utils.data_info import ParentDtypeInfo
from astropy.utils.exceptions import AstropyUserWarning
from astropy.utils.metadata import MergeConflictWarning

from .conftest import MIXIN_COLS


def test_attributes(mixin_cols):
    """
    Required attributes for a column can be set.
    """
    m = mixin_cols["m"]
    m.info.name = "a"
    assert m.info.name == "a"

    m.info.description = "a"
    assert m.info.description == "a"

    # Cannot set unit for these classes
    if isinstance(
        m,
        (
            u.Quantity,
            coordinates.SkyCoord,
            time.Time,
            time.TimeDelta,
            coordinates.BaseRepresentationOrDifferential,
            coordinates.StokesCoord,
        ),
    ):
        with pytest.raises(AttributeError):
            m.info.unit = u.m
    else:
        m.info.unit = u.m
        assert m.info.unit is u.m

    m.info.format = "a"
    assert m.info.format == "a"

    m.info.meta = {"a": 1}
    assert m.info.meta == {"a": 1}

    with pytest.raises(AttributeError):
        m.info.bad_attr = 1

    with pytest.raises(AttributeError):
        m.info.bad_attr


def check_mixin_type(table, table_col, in_col):
    # We check for QuantityInfo rather than just isinstance(col, u.Quantity)
    # since we want to treat EarthLocation as a mixin, even though it is
    # a Quantity subclass.
    if (
        isinstance(in_col.info, u.QuantityInfo) and type(table) is not QTable
    ) or isinstance(in_col, Column):
        assert type(table_col) is table.ColumnClass
    else:
        assert type(table_col) is type(in_col)

    # Make sure in_col got copied and creating table did not touch it
    assert in_col.info.name is None


def test_make_table(table_types, mixin_cols):
    """
    Make a table with the columns in mixin_cols, which is an ordered dict of
    three cols: 'a' and 'b' are table_types.Column type, and 'm' is a mixin.
    """
    t = table_types.Table(mixin_cols)
    check_mixin_type(t, t["m"], mixin_cols["m"])

    cols = list(mixin_cols.values())
    t = table_types.Table(cols, names=("i", "a", "b", "m"))
    check_mixin_type(t, t["m"], mixin_cols["m"])

    t = table_types.Table(cols)
    check_mixin_type(t, t["col3"], mixin_cols["m"])


def test_io_ascii_write():
    """
    Test that table with mixin column can be written by io.ascii for
    every pure Python writer.  No validation of the output is done,
    this just confirms no exceptions.
    """
    t = QTable(MIXIN_COLS)
    for fmt in _get_connectors_table():
        if (
            fmt["Write"]
            and ".fast_" not in fmt["Format"]
            and fmt["Format"] != "ascii.tdat"
        ):
            out = StringIO()
            t.write(out, format=fmt["Format"])


def test_votable_quantity_write(tmp_path):
    """
    Test that table with Quantity mixin column can be round-tripped by
    io.votable.  Note that FITS and HDF5 mixin support are tested (much more
    thoroughly) in their respective subpackage tests
    (io/fits/tests/test_connect.py and io/misc/tests/test_hdf5.py).
    """
    t = QTable()
    t["a"] = u.Quantity([1, 2, 4], unit="nm")

    filename = tmp_path / "table-tmp"
    t.write(filename, format="votable", overwrite=True)
    qt = QTable.read(filename, format="votable")
    assert isinstance(qt["a"], u.Quantity)
    assert qt["a"].unit == "nm"


@pytest.mark.remote_data
@pytest.mark.parametrize("table_types", (Table, QTable))
def test_io_time_write_fits_standard(tmp_path, table_types):
    """
    Test that table with Time mixin columns can be written by io.fits.
    Validation of the output is done. Test that io.fits writes a table
    containing Time mixin columns that can be partially round-tripped
    (metadata scale, location).

    Note that we postpone checking the "local" scale, since that cannot
    be done with format 'cxcsec', as it requires an epoch.
    """
    t = table_types([[1, 2], ["string", "column"]])
    for scale in time.STANDARD_TIME_SCALES:
        t["a" + scale] = time.Time(
            [[1, 2], [3, 4]],
            format="cxcsec",
            scale=scale,
            location=EarthLocation(-2446354, 4237210, 4077985, unit="m"),
        )
        t["b" + scale] = time.Time(
            ["1999-01-01T00:00:00.123456789", "2010-01-01T00:00:00"], scale=scale
        )
    t["c"] = [3.0, 4.0]

    filename = tmp_path / "table-tmp"

    # Show that FITS format succeeds
    with pytest.warns(AstropyUserWarning) as record:
        t.write(filename, format="fits", overwrite=True)

    # The exact sequence probably
    # does not matter too much, so we'll just try to match the *set* of warnings
    warnings = {wm.message.args[0] for wm in record}

    expected = {
        (
            'Time Column "btai" has no specified location, '
            "but global Time Position is present, "
            "which will be the default for this column in FITS specification."
        ),
        (
            'Time Column "btdb" has no specified location, '
            "but global Time Position is present, "
            "which will be the default for this column in FITS specification."
        ),
        (
            'Time Column "btcg" has no specified location, '
            "but global Time Position is present, "
            "which will be the default for this column in FITS specification."
        ),
        (
            'Time Column "btt" has no specified location, '
            "but global Time Position is present, which will be the default "
            "for this column in FITS specification."
        ),
        (
            'Time Column "butc" has no specified location, '
            "but global Time Position is present, "
            "which will be the default for this column in FITS specification."
        ),
        (
            'Earth Location "TOPOCENTER" for Time Column "atdb"'
            ' is incompatible with scale "TDB".'
        ),
        (
            'Earth Location "TOPOCENTER" for Time Column "atcb"'
            ' is incompatible with scale "TCB".'
        ),
        (
            'Time Column "but1" has no specified location, '
            "but global Time Position is present, "
            "which will be the default for this column in FITS specification."
        ),
        (
            'Time Column "btcb" has no specified location, '
            "but global Time Position is present, "
            "which will be the default for this column in FITS specification."
        ),
    }
    assert warnings == expected, f"Got some unexpected warnings\n{warnings - expected}"
    with pytest.warns(
        AstropyUserWarning,
        match='Time column reference position "TRPOSn" is not specified',
    ):
        tm = table_types.read(filename, format="fits", astropy_native=True)

    for scale in time.STANDARD_TIME_SCALES:
        for ab in ("a", "b"):
            name = ab + scale

            # Assert that the time columns are read as Time
            assert isinstance(tm[name], time.Time)

            # Assert that the scales round-trip
            assert tm[name].scale == t[name].scale

            # Assert that the format is jd
            assert tm[name].format == "jd"

            # Assert that the location round-trips
            assert tm[name].location == t[name].location

            # Finally assert that the column data round-trips
            assert (tm[name] == t[name]).all()

    for name in ("col0", "col1", "c"):
        # Assert that the non-time columns are read as Column
        assert isinstance(tm[name], Column)

        # Assert that the non-time columns' data round-trips
        assert (tm[name] == t[name]).all()

    # Test for conversion of time data to its value, as defined by its format
    for scale in time.STANDARD_TIME_SCALES:
        for ab in ("a", "b"):
            name = ab + scale
            t[name].info.serialize_method["fits"] = "formatted_value"

    t.write(filename, format="fits", overwrite=True)
    tm = table_types.read(filename, format="fits")

    for scale in time.STANDARD_TIME_SCALES:
        for ab in ("a", "b"):
            name = ab + scale

            assert not isinstance(tm[name], time.Time)
            assert (tm[name] == t[name].value).all()


@pytest.mark.parametrize("table_types", (Table, QTable))
def test_io_time_write_fits_local(tmp_path, table_types):
    """
    Test that table with a Time mixin with scale local can also be written
    by io.fits. Like ``test_io_time_write_fits_standard`` above, but avoiding
    ``cxcsec`` format, which requires an epoch and thus cannot be used for a
    local time scale.
    """
    t = table_types([[1, 2], ["string", "column"]])
    t["a_local"] = time.Time(
        [[50001, 50002], [50003, 50004]],
        format="mjd",
        scale="local",
        location=EarthLocation(-2446354, 4237210, 4077985, unit="m"),
    )
    t["b_local"] = time.Time(
        ["1999-01-01T00:00:00.123456789", "2010-01-01T00:00:00"], scale="local"
    )
    t["c"] = [3.0, 4.0]

    filename = tmp_path / "table-tmp"

    # Show that FITS format succeeds

    with pytest.warns(
        AstropyUserWarning, match='Time Column "b_local" has no specified location'
    ):
        t.write(filename, format="fits", overwrite=True)

    with pytest.warns(
        AstropyUserWarning,
        match='Time column reference position "TRPOSn" is not specified.',
    ):
        tm = table_types.read(filename, format="fits", astropy_native=True)

    for ab in ("a", "b"):
        name = ab + "_local"

        # Assert that the time columns are read as Time
        assert isinstance(tm[name], time.Time)

        # Assert that the scales round-trip
        assert tm[name].scale == t[name].scale

        # Assert that the format is jd
        assert tm[name].format == "jd"

        # Assert that the location round-trips
        assert tm[name].location == t[name].location

        # Finally assert that the column data round-trips
        assert (tm[name] == t[name]).all()

    for name in ("col0", "col1", "c"):
        # Assert that the non-time columns are read as Column
        assert isinstance(tm[name], Column)

        # Assert that the non-time columns' data round-trips
        assert (tm[name] == t[name]).all()

    # Test for conversion of time data to its value, as defined by its format.
    for ab in ("a", "b"):
        name = ab + "_local"
        t[name].info.serialize_method["fits"] = "formatted_value"

    t.write(filename, format="fits", overwrite=True)
    tm = table_types.read(filename, format="fits")

    for ab in ("a", "b"):
        name = ab + "_local"

        assert not isinstance(tm[name], time.Time)
        assert (tm[name] == t[name].value).all()


def test_votable_mixin_write_fail(mixin_cols):
    """
    Test that table with mixin columns (excluding Quantity) cannot be written by
    io.votable.
    """
    t = QTable(mixin_cols)
    # Only do this test if there are unsupported column types (i.e. anything besides
    # BaseColumn and Quantity class instances).
    unsupported_cols = t.columns.not_isinstance((BaseColumn, u.Quantity))

    if not unsupported_cols:
        pytest.skip("no unsupported column types")

    out = StringIO()
    with pytest.raises(ValueError) as err:
        t.write(out, format="votable")
    assert "cannot write table with mixin column(s)" in str(err.value)


def test_join(table_types):
    """
    Join tables with mixin cols.  Use column "i" as proxy for what the
    result should be for each mixin.
    """
    t1 = table_types.Table()
    t1["a"] = table_types.Column(["a", "b", "b", "c"])
    t1["i"] = table_types.Column([0, 1, 2, 3])
    for name, col in MIXIN_COLS.items():
        t1[name] = col

    t2 = table_types.Table(t1)
    t2["a"] = ["b", "c", "a", "d"]

    for name in MIXIN_COLS:
        t1[name].info.description = name
        t2[name].info.description = name + "2"

    for join_type in ("inner", "left"):
        t12 = join(t1, t2, keys="a", join_type=join_type)
        idx1 = t12["i_1"]
        idx2 = t12["i_2"]
        for name, col in MIXIN_COLS.items():
            name1 = name + "_1"
            name2 = name + "_2"
            assert_table_name_col_equal(t12, name1, col[idx1])
            assert_table_name_col_equal(t12, name2, col[idx2])
            assert t12[name1].info.description == name
            assert t12[name2].info.description == name + "2"

    for join_type in ("outer", "right"):
        with pytest.raises(NotImplementedError) as exc:
            t12 = join(t1, t2, keys="a", join_type=join_type)
        assert "join requires masking column" in str(exc.value)

    with pytest.raises(TypeError) as exc:
        t12 = join(t1, t2, keys=["a", "skycoord"])
    assert "one or more key columns are not sortable" in str(exc.value)

    # Join does work for a mixin which is a subclass of np.ndarray
    with pytest.warns(
        MergeConflictWarning,
        match="In merged column 'quantity' the 'description' attribute does not match",
    ):
        t12 = join(t1, t2, keys=["quantity"])
    assert np.all(t12["a_1"] == t1["a"])


def test_hstack(table_types):
    """
    Hstack tables with mixin cols.  Use column "i" as proxy for what the
    result should be for each mixin.
    """
    t1 = table_types.Table()
    t1["i"] = table_types.Column([0, 1, 2, 3])
    for name, col in MIXIN_COLS.items():
        t1[name] = col
        t1[name].info.description = name
        t1[name].info.meta = {"a": 1}

    for join_type in ("inner", "outer"):
        for chop in (True, False):
            t2 = table_types.Table(t1)
            if chop:
                t2 = t2[:-1]
                if join_type == "outer":
                    with pytest.raises(NotImplementedError) as exc:
                        t12 = hstack([t1, t2], join_type=join_type)
                    assert "hstack requires masking column" in str(exc.value)
                    continue

            t12 = hstack([t1, t2], join_type=join_type)
            idx1 = t12["i_1"]
            idx2 = t12["i_2"]
            for name, col in MIXIN_COLS.items():
                name1 = name + "_1"
                name2 = name + "_2"
                assert_table_name_col_equal(t12, name1, col[idx1])
                assert_table_name_col_equal(t12, name2, col[idx2])
                for attr in ("description", "meta"):
                    assert getattr(t1[name].info, attr) == getattr(
                        t12[name1].info, attr
                    )
                    assert getattr(t2[name].info, attr) == getattr(
                        t12[name2].info, attr
                    )


def assert_table_name_col_equal(t, name, col):
    """
    Assert all(t[name] == col), with special handling for known mixin cols.
    """
    __tracebackhide__ = True
    if isinstance(col, coordinates.SkyCoord):
        assert np.all(t[name].ra == col.ra)
        assert np.all(t[name].dec == col.dec)
    elif isinstance(col, coordinates.BaseRepresentationOrDifferential):
        assert np.all(representation_equal(t[name], col))
    elif isinstance(col, u.Quantity):
        if type(t) is QTable:
            assert np.all(t[name] == col)
    elif isinstance(col, table_helpers.ArrayWrapper):
        assert np.all(t[name].data == col.data)
    else:
        assert np.all(t[name] == col)


def test_get_items(mixin_cols):
    """
    Test that slicing / indexing table gives right values and col attrs inherit
    """
    attrs = ("name", "unit", "dtype", "format", "description", "meta")
    m = mixin_cols["m"]
    m.info.name = "m"
    m.info.format = "{0}"
    m.info.description = "d"
    m.info.meta = {"a": 1}
    t = QTable([m])
    for item in ([1, 3], np.array([0, 2]), slice(1, 3)):
        t2 = t[item]
        m2 = m[item]
        assert_table_name_col_equal(t2, "m", m[item])
        for attr in attrs:
            assert getattr(t2["m"].info, attr) == getattr(m.info, attr)
            assert getattr(m2.info, attr) == getattr(m.info, attr)


def test_info_preserved_pickle_copy_init(mixin_cols):
    """
    Test copy, pickle, and init from class roundtrip preserve info.  This
    tests not only the mixin classes but a regular column as well.
    """

    def pickle_roundtrip(c):
        # protocol=5 matches the default for Python 3.14 and later
        # and is needed to preserve byteorder (available since Python 3.8)
        return pickle.loads(pickle.dumps(c, protocol=5))

    def init_from_class(c):
        return c.__class__(c)

    attrs = ("name", "unit", "dtype", "format", "description", "meta")
    for colname in ("i", "m"):
        m = mixin_cols[colname]
        m.info.name = colname
        m.info.format = "{0}"
        m.info.description = "d"
        m.info.meta = {"a": 1}
        for func in (copy.copy, copy.deepcopy, pickle_roundtrip, init_from_class):
            m2 = func(m)
            for attr in attrs:
                assert getattr(m2.info, attr) == getattr(m.info, attr)


def check_share_memory(col1, col2, copy):
    """Check whether data attributes in col1 and col2 share memory.

    If copy=True, this should not be the case for any, while
    if copy=False, all should share memory.
    """
    if isinstance(col1, SkyCoord):
        # For SkyCoord, .info does not access actual data by default,
        # but rather attributes like .ra, which are copies.
        map1 = col1.data.info._represent_as_dict()
        map2 = col2.data.info._represent_as_dict()
    else:
        map1 = col1.info._represent_as_dict()
        map2 = col2.info._represent_as_dict()

    # Check array attributes only (in principle, could iterate on, e.g.,
    # differentials in representations, but this is enough for table).
    shared = [
        np.may_share_memory(v1, v2)
        for (v1, v2) in zip(map1.values(), map2.values())
        if isinstance(v1, np.ndarray) and v1.shape
    ]
    if copy:
        assert not any(shared)
    else:
        assert all(shared)


@pytest.mark.parametrize("copy", [True, False])
def test_add_column(mixin_cols, copy):
    """
    Test that adding a column preserves values and attributes.
    For copy=True, the data should be independent;
    for copy=False, the data should be shared, but the instance independent.
    """
    attrs = ("name", "unit", "dtype", "format", "description", "meta")
    m = mixin_cols["m"]
    assert m.info.name is None

    # Make sure adding column in various ways doesn't touch info.
    t = QTable([m], names=["a"], copy=copy)
    assert m.info.name is None
    check_share_memory(m, t["a"], copy=copy)

    t["new"] = m
    assert m.info.name is None
    check_share_memory(m, t["new"], copy=True)

    m.info.name = "m"
    m.info.format = "{0}"
    m.info.description = "d"
    m.info.meta = {"a": 1}
    t = QTable([m], copy=copy)
    assert t.colnames == ["m"]
    check_share_memory(m, t["m"], copy=copy)

    t = QTable([m], names=["m1"], copy=copy)
    assert m.info.name == "m"
    assert t.colnames == ["m1"]
    check_share_memory(m, t["m1"], copy=copy)

    # Add columns m2, m3, m4 by two different methods and test expected equality
    t["m2"] = m
    check_share_memory(m, t["m2"], copy=True)
    m.info.name = "m3"
    t.add_columns([m], copy=copy)
    check_share_memory(m, t["m3"], copy=copy)
    for name in ("m2", "m3"):
        assert_table_name_col_equal(t, name, m)
        for attr in attrs:
            if attr != "name":
                assert getattr(t["m1"].info, attr) == getattr(t[name].info, attr)
    # Also check that one can set using a scalar.
    s = m[0]
    if type(s) is type(m) and "info" in s.__dict__:
        # We're not going to worry about testing classes for which scalars
        # are a different class than the real array, or where info is not copied.
        t["s"] = m[0]
        assert_table_name_col_equal(t, "s", m[0])
        check_share_memory(m, t["s"], copy=True)
        for attr in attrs:
            if attr != "name":
                assert getattr(t["m1"].info, attr) == getattr(t["s"].info, attr)

    # While we're add it, also check a length-1 table.
    t = QTable([m[1:2]], names=["m"], copy=copy)
    check_share_memory(m, t["m"], copy=copy)
    if type(s) is type(m) and "info" in s.__dict__:
        t["s"] = m[0]
        assert_table_name_col_equal(t, "s", m[0])
        for attr in attrs:
            if attr != "name":
                assert getattr(t["m1"].info, attr) == getattr(t["s"].info, attr)


def test_vstack():
    """
    Vstack tables with mixin cols.
    """
    t1 = QTable(MIXIN_COLS)
    t2 = QTable(MIXIN_COLS)
    with pytest.raises(NotImplementedError):
        vstack([t1, t2])


@pytest.mark.parametrize("empty_table", [False, True])
def test_insert_row(mixin_cols, empty_table):
    """
    Test inserting a row, which works for Column, Quantity, Time and SkyCoord.
    """
    t0 = QTable(mixin_cols)
    if empty_table:
        t = t0[:0].copy()
        insert_index = 0
        result_indices = [-1]
    else:
        t = t0.copy()
        insert_index = 1
        result_indices = [0, -1, 1, 2, 3]
    t["m"].info.description = "d"
    if isinstance(
        t["m"], (u.Quantity, Column, time.Time, time.TimeDelta, coordinates.SkyCoord)
    ):
        t.insert_row(insert_index, t0[-1])

        for name in t.colnames:
            assert np.all(t[name] == t0[name][result_indices])

        assert np.all(t == t0[result_indices])
        assert t["m"].info.description == "d"
    else:
        with pytest.raises(ValueError) as exc:
            t.insert_row(insert_index, t0[-1])
        assert "Unable to insert row" in str(exc.value)


def test_insert_row_bad_unit():
    """
    Insert a row into a QTable with the wrong unit
    """
    t = QTable([[1] * u.m])
    with pytest.raises(ValueError) as exc:
        t.insert_row(0, (2 * u.m / u.s,))
    assert "'m / s' (speed/velocity) and 'm' (length) are not convertible" in str(
        exc.value
    )


def test_convert_np_array(mixin_cols):
    """
    Test that converting to numpy array creates an object dtype and that
    each instance in the array has the expected type.
    """
    t = QTable(mixin_cols)
    ta = t.as_array()
    m = mixin_cols["m"]
    dtype_kind = m.dtype.kind if hasattr(m, "dtype") else "O"
    assert ta["m"].dtype.kind == dtype_kind


def test_assignment_and_copy():
    """
    Test that assignment of an int, slice, and fancy index works.
    Along the way test that copying table works.
    """
    for name in ("quantity", "arraywrap"):
        m = MIXIN_COLS[name]
        t0 = QTable([m], names=["m"])
        for i0, i1 in (
            (1, 2),
            (slice(0, 2), slice(1, 3)),
            (np.array([1, 2]), np.array([2, 3])),
        ):
            t = t0.copy()
            t["m"][i0] = m[i1]
            if name == "arraywrap":
                assert np.all(t["m"].data[i0] == m.data[i1])
                assert np.all(t0["m"].data[i0] == m.data[i0])
                assert np.all(t0["m"].data[i0] != t["m"].data[i0])
            else:
                assert np.all(t["m"][i0] == m[i1])
                assert np.all(t0["m"][i0] == m[i0])
                assert np.all(t0["m"][i0] != t["m"][i0])


def test_conversion_qtable_table():
    """
    Test that a table round trips from QTable => Table => QTable
    """
    qt = QTable(MIXIN_COLS)
    names = qt.colnames
    for name in names:
        qt[name].info.description = name

    t = Table(qt)
    for name in names:
        assert t[name].info.description == name
        if name == "quantity":
            assert np.all(t["quantity"] == qt["quantity"].value)
            assert np.all(t["quantity"].unit is qt["quantity"].unit)
            assert isinstance(t["quantity"], t.ColumnClass)
        else:
            assert_table_name_col_equal(t, name, qt[name])

    qt2 = QTable(qt)
    for name in names:
        assert qt2[name].info.description == name
        assert_table_name_col_equal(qt2, name, qt[name])


def test_setitem_as_column_name():
    """
    Test for mixin-related regression described in #3321.
    """
    t = Table()
    t["a"] = ["x", "y"]
    t["b"] = "b"  # Previously was failing with KeyError
    assert np.all(t["a"] == ["x", "y"])
    assert np.all(t["b"] == ["b", "b"])


def test_quantity_representation():
    """
    Test that table representation of quantities does not have unit
    """
    t = QTable([[1, 2] * u.m])
    assert t.pformat() == [
        "col0",
        " m  ",
        "----",
        " 1.0",
        " 2.0",
    ]


@pytest.mark.parametrize(
    "c, expected_pformat",
    [
        pytest.param(
            coordinates.CartesianRepresentation([0], [1], [0], unit=u.one),
            # With no unit we get "None" in the unit row
            [
                "      col0     ",
                "---------------",
                "(0.0, 1.0, 0.0)",
            ],
            id="cartesian_wo_unit",
        ),
        pytest.param(
            coordinates.CartesianRepresentation([0], [1], [0], unit="m"),
            [
                "      col0     ",
                "       m       ",
                "---------------",
                "(0.0, 1.0, 0.0)",
            ],
            id="cartesian_w_unit",
        ),
        pytest.param(
            coordinates.SphericalRepresentation([10] * u.deg, [20] * u.deg, [1] * u.pc),
            [
                "       col0      ",
                "   deg, deg, pc  ",
                "-----------------",
                "(10.0, 20.0, 1.0)",
            ],
            id="spherical",
        ),
        pytest.param(
            coordinates.UnitSphericalRepresentation([10] * u.deg, [20] * u.deg),
            [
                "    col0    ",
                "    deg     ",
                "------------",
                "(10.0, 20.0)",
            ],
            id="unitspherical",
        ),
        pytest.param(
            coordinates.SphericalCosLatDifferential(
                [10] * u.mas / u.yr, [2] * u.mas / u.yr, [10] * u.km / u.s
            ),
            [
                "           col0           ",
                "mas / yr, mas / yr, km / s",
                "--------------------------",
                "         (10.0, 2.0, 10.0)",
            ],
            id="sphericalcoslatdifferential",
        ),
    ],
)
def test_representation_representation(c, expected_pformat):
    """
    Test that Representations are represented correctly.
    """
    t = Table([c])
    assert t.pformat() == expected_pformat


def test_skycoord_representation():
    """
    Test that skycoord representation works, both in the way that the
    values are output and in changing the frame representation.
    """
    # With no unit we get "None" in the unit row
    c = coordinates.SkyCoord([0], [1], [0], representation_type="cartesian")
    t = Table([c])
    assert t.pformat() == [
        "     col0     ",
        "None,None,None",
        "--------------",
        "   0.0,1.0,0.0",
    ]

    # Test that info works with a dynamically changed representation
    c = coordinates.SkyCoord([0], [1], [0], unit="m", representation_type="cartesian")
    t = Table([c])
    assert t.pformat() == [
        "    col0   ",
        "   m,m,m   ",
        "-----------",
        "0.0,1.0,0.0",
    ]

    t["col0"].representation_type = "unitspherical"
    assert t.pformat() == [
        "  col0  ",
        "deg,deg ",
        "--------",
        "90.0,0.0",
    ]

    t["col0"].representation_type = "cylindrical"
    assert t.pformat() == [
        "    col0    ",
        "  m,deg,m   ",
        "------------",
        "1.0,90.0,0.0",
    ]


@pytest.mark.parametrize("as_ndarray_mixin", [True, False])
def test_ndarray_mixin(as_ndarray_mixin):
    """
    Test directly adding various forms of structured ndarray columns to a table.
    Adding as NdarrayMixin is expected to be somewhat unusual after #12644
    (which provides full support for structured array Column's). This test shows
    that the end behavior is the same in both cases.
    """
    a = np.array([(1, "a"), (2, "b"), (3, "c"), (4, "d")], dtype="<i4,|U1")
    b = np.array(
        [(10, "aa"), (20, "bb"), (30, "cc"), (40, "dd")],
        dtype=[("x", "i4"), ("y", "U2")],
    )
    c = np.rec.fromrecords(
        [(100.0, "raa"), (200.0, "rbb"), (300.0, "rcc"), (400.0, "rdd")],
        names=["rx", "ry"],
    )
    d = np.arange(8, dtype="i8").reshape(4, 2)

    if as_ndarray_mixin:
        a = a.view(NdarrayMixin)
        b = b.view(NdarrayMixin)
        c = c.view(NdarrayMixin)
        d = d.view(NdarrayMixin)
        class_exp = NdarrayMixin
    else:
        class_exp = Column

    # Add one during initialization and the next as a new column.
    t = Table([a], names=["a"])
    t["b"] = b
    t["c"] = c
    t["d"] = d

    assert isinstance(t["a"], class_exp)

    assert t["a"][1][1] == a[1][1]
    assert t["a"][2][0] == a[2][0]

    assert t[1]["a"][1] == a[1][1]
    assert t[2]["a"][0] == a[2][0]

    assert isinstance(t["b"], class_exp)

    assert t["b"][1]["x"] == b[1]["x"]
    assert t["b"][1]["y"] == b[1]["y"]

    assert t[1]["b"]["x"] == b[1]["x"]
    assert t[1]["b"]["y"] == b[1]["y"]

    assert isinstance(t["c"], class_exp)

    assert t["c"][1]["rx"] == c[1]["rx"]
    assert t["c"][1]["ry"] == c[1]["ry"]

    assert t[1]["c"]["rx"] == c[1]["rx"]
    assert t[1]["c"]["ry"] == c[1]["ry"]

    assert isinstance(t["d"], class_exp)

    assert t["d"][1][0] == d[1][0]
    assert t["d"][1][1] == d[1][1]

    assert t[1]["d"][0] == d[1][0]
    assert t[1]["d"][1] == d[1][1]

    assert t.pformat(show_dtype=True) == (
        [
            "  a [f0, f1]     b [x, y]      c [rx, ry]      d    ",
            "(int32, str1) (int32, str2) (float64, str3) int64[2]",
            "------------- ------------- --------------- --------",
            "     (1, 'a')    (10, 'aa')  (100.0, 'raa')   0 .. 1",
            "     (2, 'b')    (20, 'bb')  (200.0, 'rbb')   2 .. 3",
            "     (3, 'c')    (30, 'cc')  (300.0, 'rcc')   4 .. 5",
            "     (4, 'd')    (40, 'dd')  (400.0, 'rdd')   6 .. 7",
        ]
    )


def test_possible_string_format_functions():
    """
    The QuantityInfo info class for Quantity implements a
    possible_string_format_functions() method that overrides the
    standard pprint._possible_string_format_functions() function.
    Test this.
    """
    t = QTable([[1, 2] * u.m])
    t["col0"].info.format = "%.3f"
    assert t.pformat() == [
        " col0",
        "  m  ",
        "-----",
        "1.000",
        "2.000",
    ]

    t["col0"].info.format = "hi {:.3f}"
    assert t.pformat() == [
        "  col0  ",
        "   m    ",
        "--------",
        "hi 1.000",
        "hi 2.000",
    ]

    t["col0"].info.format = ".4f"
    assert t.pformat() == [
        " col0 ",
        "  m   ",
        "------",
        "1.0000",
        "2.0000",
    ]


def test_rename_mixin_columns(mixin_cols):
    """
    Rename a mixin column.
    """
    t = QTable(mixin_cols)
    tc = t.copy()
    t.rename_column("m", "mm")
    assert t.colnames == ["i", "a", "b", "mm"]
    if isinstance(t["mm"], table_helpers.ArrayWrapper):
        assert np.all(t["mm"].data == tc["m"].data)
    elif isinstance(t["mm"], coordinates.SkyCoord):
        assert np.all(t["mm"].ra == tc["m"].ra)
        assert np.all(t["mm"].dec == tc["m"].dec)
    elif isinstance(t["mm"], coordinates.BaseRepresentationOrDifferential):
        assert np.all(representation_equal(t["mm"], tc["m"]))
    else:
        assert np.all(t["mm"] == tc["m"])


def test_represent_mixins_as_columns_unit_fix():
    """
    If the unit is invalid for a column that gets serialized this would
    cause an exception.  Fixed in #7481.
    """
    t = Table({"a": [1, 2]}, masked=True)
    t["a"].unit = "not a valid unit"
    t["a"].mask[1] = True
    serialize.represent_mixins_as_columns(t)


def test_primary_data_column_gets_description():
    """
    If the mixin defines a primary data column, that should get the
    description, format, etc., so no __info__ should be needed.
    """
    t = QTable({"a": [1, 2] * u.m})
    t["a"].info.description = "parrot"
    t["a"].info.format = "7.2f"
    tser = serialize.represent_mixins_as_columns(t)
    assert "__info__" not in tser.meta["__serialized_columns__"]["a"]
    assert tser["a"].format == "7.2f"
    assert tser["a"].description == "parrot"


@pytest.mark.parametrize("copy", [True, False])
@pytest.mark.parametrize("table_cls", [Table, QTable])
def test_ensure_input_info_is_unchanged(table_cls, copy):
    """If a mixin input to a table has no info, it should stay that way.

    This since having 'info' slows down slicing, etc.
    See gh-11066.
    """
    q = [1, 2] * u.m
    assert "info" not in q.__dict__
    t = table_cls([q], names=["q"], copy=copy)
    assert "info" not in q.__dict__
    t = table_cls([q], copy=copy)
    assert "info" not in q.__dict__
    t = table_cls({"q": q}, copy=copy)
    assert "info" not in q.__dict__
    t["q2"] = q
    assert "info" not in q.__dict__
    sc = SkyCoord([1, 2], [2, 3], unit="deg")
    t["sc"] = sc
    assert "info" not in sc.__dict__


def test_bad_info_class():
    """Make a mixin column class that does not trigger the machinery to generate
    a pure column representation"""

    class MyArrayWrapper(ArrayWrapper):
        info = ParentDtypeInfo()

    t = Table()
    t["tm"] = MyArrayWrapper([0, 1, 2])
    out = StringIO()
    match = (
        r"failed to represent column 'tm' \(MyArrayWrapper\) as one or more Column"
        r" subclasses"
    )
    with pytest.raises(TypeError, match=match):
        represent_mixins_as_columns(t)
