from __future__ import annotations

from typing import Any

import pytest

from PIL import Image

from .helper import hopper

numpy = pytest.importorskip("numpy", reason="NumPy not installed")

im = hopper().resize((128, 100))

TYPE_CHECKING = False
if TYPE_CHECKING:
    import numpy.typing as npt


def test_toarray() -> None:
    def test(mode: str) -> tuple[tuple[int, ...], str, int]:
        ai = numpy.array(im.convert(mode))
        return ai.shape, ai.dtype.str, ai.nbytes

    def test_with_dtype(dtype: npt.DTypeLike) -> None:
        ai = numpy.array(im, dtype=dtype)
        assert ai.dtype.type is dtype

    # assert test("1") == ((100, 128), '|b1', 1600))
    assert test("L") == ((100, 128), "|u1", 12800)

    # FIXME: wrong?
    assert test("I") == ((100, 128), Image._ENDIAN + "i4", 51200)
    # FIXME: wrong?
    assert test("F") == ((100, 128), Image._ENDIAN + "f4", 51200)

    assert test("LA") == ((100, 128, 2), "|u1", 25600)
    assert test("RGB") == ((100, 128, 3), "|u1", 38400)
    assert test("RGBA") == ((100, 128, 4), "|u1", 51200)
    assert test("RGBX") == ((100, 128, 4), "|u1", 51200)

    test_with_dtype(numpy.float64)
    test_with_dtype(numpy.uint8)

    with Image.open("Tests/images/truncated_jpeg.jpg") as im_truncated:
        with pytest.raises(OSError):
            numpy.array(im_truncated)


def test_fromarray() -> None:
    class Wrapper:
        """Class with API matching Image.fromarray"""

        def __init__(self, img: Image.Image, arr_params: dict[str, Any]) -> None:
            self.img = img
            self.__array_interface__ = arr_params

        def __len__(self) -> int:
            return len(self.img.tobytes())

        def tobytes(self) -> bytes:
            return self.img.tobytes()

    def test(mode: str) -> tuple[str, tuple[int, int], bool]:
        i = im.convert(mode)
        a = numpy.array(i)
        # Make wrapper instance for image, new array interface
        wrapped = Wrapper(
            i,
            {
                "shape": a.shape,
                "typestr": a.dtype.str,
                "version": 3,
                "data": a.data,
                "strides": 1,  # pretend it's non-contiguous
            },
        )
        out = Image.fromarray(wrapped)
        return out.mode, out.size, i.get_flattened_data() == out.get_flattened_data()

    # assert test("1") == ("1", (128, 100), True)
    assert test("L") == ("L", (128, 100), True)
    assert test("I") == ("I", (128, 100), True)
    assert test("F") == ("F", (128, 100), True)
    assert test("LA") == ("LA", (128, 100), True)
    assert test("RGB") == ("RGB", (128, 100), True)
    assert test("RGBA") == ("RGBA", (128, 100), True)
    assert test("RGBX") == ("RGBA", (128, 100), True)

    # Test mode is None with no "typestr" in the array interface
    wrapped = Wrapper(hopper("L"), {"shape": (100, 128)})
    with pytest.raises(TypeError):
        Image.fromarray(wrapped)


def test_fromarray_strides_without_tobytes() -> None:
    class Wrapper:
        def __init__(self, arr_params: dict[str, Any]) -> None:
            self.__array_interface__ = arr_params

        def __len__(self) -> int:
            return 1

    with pytest.raises(ValueError):
        wrapped = Wrapper({"shape": (1, 1), "strides": (1, 1), "typestr": "|u1"})
        Image.fromarray(wrapped, "L")


def test_fromarray_palette() -> None:
    # Arrange
    i = im.convert("L")
    a = numpy.array(i)

    # Act
    out = Image.fromarray(a, "P")

    # Assert that the Python and C palettes match
    assert out.palette is not None
    assert len(out.palette.colors) == len(out.im.getpalette()) / 3
