import numpy as np
import pytest
import scipy.ndimage as ndi

from skimage import io, draw
from skimage.data import binary_blobs
from skimage.morphology import skeletonize, skeletonize_3d

from skimage._shared import testing
from skimage._shared.testing import assert_equal, assert_, parametrize, fetch

# basic behavior tests (mostly copied over from 2D skeletonize)


def test_skeletonize_wrong_dim():
    im = np.zeros(5, dtype=bool)
    with testing.raises(ValueError):
        skeletonize(im, method='lee')

    im = np.zeros((5, 5, 5, 5), dtype=bool)
    with testing.raises(ValueError):
        skeletonize(im, method='lee')


def test_skeletonize_1D_old_api():
    # a corner case of an image of a shape(1, N)
    im = np.ones((5, 1), dtype=bool)
    res = skeletonize(im)
    assert_equal(res, im)


def test_skeletonize_1D():
    # a corner case of an image of a shape(1, N)
    im = np.ones((5, 1), dtype=bool)
    res = skeletonize(im, method='lee')
    assert_equal(res, im)


def test_skeletonize_no_foreground():
    im = np.zeros((5, 5), dtype=bool)
    result = skeletonize(im, method='lee')
    assert_equal(result, im)


def test_skeletonize_all_foreground():
    im = np.ones((3, 4), dtype=bool)
    assert_equal(
        skeletonize(im, method='lee'),
        np.array([[0, 0, 0, 0], [1, 1, 1, 1], [0, 0, 0, 0]], dtype=bool),
    )


def test_skeletonize_single_point():
    im = np.zeros((5, 5), dtype=bool)
    im[3, 3] = 1
    result = skeletonize(im, method='lee')
    assert_equal(result, im)


def test_skeletonize_already_thinned():
    im = np.zeros((5, 5), dtype=bool)
    im[3, 1:-1] = 1
    im[2, -1] = 1
    im[4, 0] = 1
    result = skeletonize(im, method='lee')
    assert_equal(result, im)


def test_dtype_conv():
    # check that the operation does the right thing with floats etc
    # also check non-contiguous input
    img = np.random.random((16, 16))[::2, ::2]
    img[img < 0.5] = 0

    orig = img.copy()
    res = skeletonize(img, method='lee')

    assert res.dtype == bool
    assert_equal(img, orig)  # operation does not clobber the original


@parametrize("img", [np.ones((8, 8), dtype=bool), np.ones((4, 8, 8), dtype=bool)])
def test_input_with_warning(img):
    # check that the input is not clobbered
    # for 2D and 3D images of varying dtypes
    check_input(img)


@parametrize("img", [np.ones((8, 8), dtype=bool), np.ones((4, 8, 8), dtype=bool)])
def test_input_without_warning(img):
    # check that the input is not clobbered
    # for 2D and 3D images of varying dtypes
    check_input(img)


def check_input(img):
    orig = img.copy()
    skeletonize(img, method='lee')
    assert_equal(img, orig)


@pytest.mark.parametrize("dtype", [bool, float, int])
def test_skeletonize_num_neighbors(dtype):
    # an empty image
    image = np.zeros((300, 300), dtype=dtype)

    # foreground object 1
    image[10:-10, 10:100] = 1
    image[-100:-10, 10:-10] = 2
    image[10:-10, -100:-10] = 3

    # foreground object 2
    rs, cs = draw.line(250, 150, 10, 280)
    for i in range(10):
        image[rs + i, cs] = 4
    rs, cs = draw.line(10, 150, 250, 280)
    for i in range(20):
        image[rs + i, cs] = 5

    # foreground object 3
    ir, ic = np.indices(image.shape)
    circle1 = (ic - 135) ** 2 + (ir - 150) ** 2 < 30**2
    circle2 = (ic - 135) ** 2 + (ir - 150) ** 2 < 20**2
    image[circle1] = 1
    image[circle2] = 0
    result = skeletonize(image, method='lee').astype(np.uint8)

    # there should never be a 2x2 block of foreground pixels in a skeleton
    mask = np.array([[1, 1], [1, 1]], np.uint8)
    blocks = ndi.correlate(result, mask, mode='constant')
    assert_(not np.any(blocks == 4))


def test_two_hole_image():
    # test a simple 2D image against FIJI
    img_o = np.array(
        [
            [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0],
            [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
            [0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0],
            [0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0],
            [0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0],
            [0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0],
            [0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0],
            [0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
            [0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
            [0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
            [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        ],
        dtype=bool,
    )
    img_f = np.array(
        [
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0],
            [0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0],
            [0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0],
            [0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0],
            [0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0],
            [0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0],
            [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0],
            [0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 1, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        ],
        dtype=bool,
    )
    res = skeletonize(img_o, method='lee')
    assert_equal(res, img_f)


def test_3d_vs_fiji():
    # generate an image with blobs and compate its skeleton to
    # the skeleton generated by FIJI (Plugins>Skeleton->Skeletonize)
    img = binary_blobs(32, 0.05, n_dim=3, rng=1234)
    img = img[:-2, ...]

    img_s = skeletonize(img)
    img_f = io.imread(fetch("data/_blobs_3d_fiji_skeleton.tif")).astype(bool)
    assert_equal(img_s, img_f)


def test_deprecated_skeletonize_3d():
    image = np.ones((10, 10), dtype=bool)
    regex = "Use `skimage\\.morphology\\.skeletonize"
    with pytest.warns(FutureWarning, match=regex) as record:
        skeletonize_3d(image)
    assert len(record) == 1
    assert record[0].filename == __file__, "warning points at wrong file"