projektAI/venv/Lib/site-packages/pandas/tests/indexes/interval/test_astype.py

import numpy as np
import pytest

from pandas.core.dtypes.dtypes import CategoricalDtype, IntervalDtype

from pandas import (
    CategoricalIndex,
    Index,
    IntervalIndex,
    NaT,
    Timedelta,
    Timestamp,
    interval_range,
)
import pandas._testing as tm


class AstypeTests:
    """Tests common to IntervalIndex with any subtype"""

    def test_astype_idempotent(self, index):
        result = index.astype("interval")
        tm.assert_index_equal(result, index)

        result = index.astype(index.dtype)
        tm.assert_index_equal(result, index)

    def test_astype_object(self, index):
        result = index.astype(object)
        expected = Index(index.values, dtype="object")
        tm.assert_index_equal(result, expected)
        assert not result.equals(index)

    def test_astype_category(self, index):
        result = index.astype("category")
        expected = CategoricalIndex(index.values)
        tm.assert_index_equal(result, expected)

        result = index.astype(CategoricalDtype())
        tm.assert_index_equal(result, expected)

        # non-default params
        categories = index.dropna().unique().values[:-1]
        dtype = CategoricalDtype(categories=categories, ordered=True)
        result = index.astype(dtype)
        expected = CategoricalIndex(index.values, categories=categories, ordered=True)
        tm.assert_index_equal(result, expected)

    @pytest.mark.parametrize(
        "dtype",
        [
            "int64",
            "uint64",
            "float64",
            "complex128",
            "period[M]",
            "timedelta64",
            "timedelta64[ns]",
            "datetime64",
            "datetime64[ns]",
            "datetime64[ns, US/Eastern]",
        ],
    )
    def test_astype_cannot_cast(self, index, dtype):
        msg = "Cannot cast IntervalIndex to dtype"
        with pytest.raises(TypeError, match=msg):
            index.astype(dtype)

    def test_astype_invalid_dtype(self, index):
        msg = "data type [\"']fake_dtype[\"'] not understood"
        with pytest.raises(TypeError, match=msg):
            index.astype("fake_dtype")


class TestIntSubtype(AstypeTests):
    """Tests specific to IntervalIndex with integer-like subtype"""

    indexes = [
        IntervalIndex.from_breaks(np.arange(-10, 11, dtype="int64")),
        IntervalIndex.from_breaks(np.arange(100, dtype="uint64"), closed="left"),
    ]

    @pytest.fixture(params=indexes)
    def index(self, request):
        return request.param

    @pytest.mark.parametrize(
        "subtype", ["float64", "datetime64[ns]", "timedelta64[ns]"]
    )
    def test_subtype_conversion(self, index, subtype):
        dtype = IntervalDtype(subtype)
        result = index.astype(dtype)
        expected = IntervalIndex.from_arrays(
            index.left.astype(subtype), index.right.astype(subtype), closed=index.closed
        )
        tm.assert_index_equal(result, expected)

    @pytest.mark.parametrize(
        "subtype_start, subtype_end", [("int64", "uint64"), ("uint64", "int64")]
    )
    def test_subtype_integer(self, subtype_start, subtype_end):
        index = IntervalIndex.from_breaks(np.arange(100, dtype=subtype_start))
        dtype = IntervalDtype(subtype_end)
        result = index.astype(dtype)
        expected = IntervalIndex.from_arrays(
            index.left.astype(subtype_end),
            index.right.astype(subtype_end),
            closed=index.closed,
        )
        tm.assert_index_equal(result, expected)

    @pytest.mark.xfail(reason="GH#15832")
    def test_subtype_integer_errors(self):
        # int64 -> uint64 fails with negative values
        index = interval_range(-10, 10)
        dtype = IntervalDtype("uint64")

        # Until we decide what the exception message _should_ be, we
        #  assert something that it should _not_ be.
        #  We should _not_ be getting a message suggesting that the -10
        #  has been wrapped around to a large-positive integer
        msg = "^(?!(left side of interval must be <= right side))"
        with pytest.raises(ValueError, match=msg):
            index.astype(dtype)


class TestFloatSubtype(AstypeTests):
    """Tests specific to IntervalIndex with float subtype"""

    indexes = [
        interval_range(-10.0, 10.0, closed="neither"),
        IntervalIndex.from_arrays(
            [-1.5, np.nan, 0.0, 0.0, 1.5], [-0.5, np.nan, 1.0, 1.0, 3.0], closed="both"
        ),
    ]

    @pytest.fixture(params=indexes)
    def index(self, request):
        return request.param

    @pytest.mark.parametrize("subtype", ["int64", "uint64"])
    def test_subtype_integer(self, subtype):
        index = interval_range(0.0, 10.0)
        dtype = IntervalDtype(subtype)
        result = index.astype(dtype)
        expected = IntervalIndex.from_arrays(
            index.left.astype(subtype), index.right.astype(subtype), closed=index.closed
        )
        tm.assert_index_equal(result, expected)

        # raises with NA
        msg = r"Cannot convert non-finite values \(NA or inf\) to integer"
        with pytest.raises(ValueError, match=msg):
            index.insert(0, np.nan).astype(dtype)

    @pytest.mark.xfail(reason="GH#15832")
    def test_subtype_integer_errors(self):
        # float64 -> uint64 fails with negative values
        index = interval_range(-10.0, 10.0)
        dtype = IntervalDtype("uint64")
        with pytest.raises(ValueError):
            index.astype(dtype)

        # float64 -> integer-like fails with non-integer valued floats
        index = interval_range(0.0, 10.0, freq=0.25)
        dtype = IntervalDtype("int64")
        with pytest.raises(ValueError):
            index.astype(dtype)

        dtype = IntervalDtype("uint64")
        with pytest.raises(ValueError):
            index.astype(dtype)

    @pytest.mark.parametrize("subtype", ["datetime64[ns]", "timedelta64[ns]"])
    def test_subtype_datetimelike(self, index, subtype):
        dtype = IntervalDtype(subtype)
        msg = "Cannot convert .* to .*; subtypes are incompatible"
        with pytest.raises(TypeError, match=msg):
            index.astype(dtype)


class TestDatetimelikeSubtype(AstypeTests):
    """Tests specific to IntervalIndex with datetime-like subtype"""

    indexes = [
        interval_range(Timestamp("2018-01-01"), periods=10, closed="neither"),
        interval_range(Timestamp("2018-01-01"), periods=10).insert(2, NaT),
        interval_range(Timestamp("2018-01-01", tz="US/Eastern"), periods=10),
        interval_range(Timedelta("0 days"), periods=10, closed="both"),
        interval_range(Timedelta("0 days"), periods=10).insert(2, NaT),
    ]

    @pytest.fixture(params=indexes)
    def index(self, request):
        return request.param

    @pytest.mark.parametrize("subtype", ["int64", "uint64"])
    def test_subtype_integer(self, index, subtype):
        dtype = IntervalDtype(subtype)
        result = index.astype(dtype)
        expected = IntervalIndex.from_arrays(
            index.left.astype(subtype), index.right.astype(subtype), closed=index.closed
        )
        tm.assert_index_equal(result, expected)

    def test_subtype_float(self, index):
        dtype = IntervalDtype("float64")
        msg = "Cannot convert .* to .*; subtypes are incompatible"
        with pytest.raises(TypeError, match=msg):
            index.astype(dtype)

    def test_subtype_datetimelike(self):
        # datetime -> timedelta raises
        dtype = IntervalDtype("timedelta64[ns]")
        msg = "Cannot convert .* to .*; subtypes are incompatible"

        index = interval_range(Timestamp("2018-01-01"), periods=10)
        with pytest.raises(TypeError, match=msg):
            index.astype(dtype)

        index = interval_range(Timestamp("2018-01-01", tz="CET"), periods=10)
        with pytest.raises(TypeError, match=msg):
            index.astype(dtype)

        # timedelta -> datetime raises
        dtype = IntervalDtype("datetime64[ns]")
        index = interval_range(Timedelta("0 days"), periods=10)
        with pytest.raises(TypeError, match=msg):
            index.astype(dtype)