import numpy as np
import pytest
from numpy.testing import assert_array_equal, assert_allclose

from skimage._shared.utils import _supported_float_type
from skimage.segmentation import find_boundaries, mark_boundaries


white = (1, 1, 1)


def test_find_boundaries():
    image = np.zeros((10, 10), dtype=np.uint8)
    image[2:7, 2:7] = 1

    ref = np.array(
        [
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
            [0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
            [0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
            [0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
            [0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
            [0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
            [0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        ]
    )

    result = find_boundaries(image)
    assert_array_equal(result, ref)


def test_find_boundaries_bool():
    image = np.zeros((5, 5), dtype=bool)
    image[2:5, 2:5] = True

    ref = np.array(
        [
            [False, False, False, False, False],
            [False, False, True, True, True],
            [False, True, True, True, True],
            [False, True, True, False, False],
            [False, True, True, False, False],
        ],
        dtype=bool,
    )
    result = find_boundaries(image)
    assert_array_equal(result, ref)


@pytest.mark.parametrize('dtype', [np.uint8, np.float16, np.float32, np.float64])
def test_mark_boundaries(dtype):
    image = np.zeros((10, 10), dtype=dtype)
    label_image = np.zeros((10, 10), dtype=np.uint8)
    label_image[2:7, 2:7] = 1

    ref = np.array(
        [
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
            [0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
            [0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
            [0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
            [0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
            [0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
            [0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        ]
    )

    marked = mark_boundaries(image, label_image, color=white, mode='thick')
    assert marked.dtype == _supported_float_type(dtype)
    result = np.mean(marked, axis=-1)
    assert_array_equal(result, ref)

    ref = np.array(
        [
            [0, 2, 2, 2, 2, 2, 2, 2, 0, 0],
            [2, 2, 1, 1, 1, 1, 1, 2, 2, 0],
            [2, 1, 1, 1, 1, 1, 1, 1, 2, 0],
            [2, 1, 1, 2, 2, 2, 1, 1, 2, 0],
            [2, 1, 1, 2, 0, 2, 1, 1, 2, 0],
            [2, 1, 1, 2, 2, 2, 1, 1, 2, 0],
            [2, 1, 1, 1, 1, 1, 1, 1, 2, 0],
            [2, 2, 1, 1, 1, 1, 1, 2, 2, 0],
            [0, 2, 2, 2, 2, 2, 2, 2, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        ]
    )
    marked = mark_boundaries(
        image, label_image, color=white, outline_color=(2, 2, 2), mode='thick'
    )
    result = np.mean(marked, axis=-1)
    assert_array_equal(result, ref)


def test_mark_boundaries_bool():
    image = np.zeros((10, 10), dtype=bool)
    label_image = np.zeros((10, 10), dtype=np.uint8)
    label_image[2:7, 2:7] = 1

    ref = np.array(
        [
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
            [0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
            [0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
            [0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
            [0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
            [0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
            [0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        ]
    )

    marked = mark_boundaries(image, label_image, color=white, mode='thick')
    result = np.mean(marked, axis=-1)
    assert_array_equal(result, ref)


@pytest.mark.parametrize('dtype', [np.float16, np.float32, np.float64])
def test_mark_boundaries_subpixel(dtype):
    labels = np.array(
        [[0, 0, 0, 0], [0, 0, 5, 0], [0, 1, 5, 0], [0, 0, 5, 0], [0, 0, 0, 0]],
        dtype=np.uint8,
    )
    np.random.seed(0)
    image = np.round(np.random.rand(*labels.shape), 2)
    image = image.astype(dtype, copy=False)
    marked = mark_boundaries(image, labels, color=white, mode='subpixel')
    assert marked.dtype == _supported_float_type(dtype)
    marked_proj = np.round(np.mean(marked, axis=-1), 2)

    ref_result = np.array(
        [
            [0.55, 0.63, 0.72, 0.69, 0.6, 0.55, 0.54],
            [0.45, 0.58, 0.72, 1.0, 1.0, 1.0, 0.69],
            [0.42, 0.54, 0.65, 1.0, 0.44, 1.0, 0.89],
            [0.69, 1.0, 1.0, 1.0, 0.69, 1.0, 0.83],
            [0.96, 1.0, 0.38, 1.0, 0.79, 1.0, 0.53],
            [0.89, 1.0, 1.0, 1.0, 0.38, 1.0, 0.16],
            [0.57, 0.78, 0.93, 1.0, 0.07, 1.0, 0.09],
            [0.2, 0.52, 0.92, 1.0, 1.0, 1.0, 0.54],
            [0.02, 0.35, 0.83, 0.9, 0.78, 0.81, 0.87],
        ]
    )
    assert_allclose(marked_proj, ref_result, atol=0.01)


@pytest.mark.parametrize('mode', ['thick', 'inner', 'outer', 'subpixel'])
def test_boundaries_constant_image(mode):
    """A constant-valued image has not boundaries."""
    ones = np.ones((8, 8), dtype=int)
    b = find_boundaries(ones, mode=mode)
    assert np.all(b == 0)