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

from skimage.draw import ellipsoid, ellipsoid_stats
from skimage.measure import marching_cubes, mesh_surface_area


def test_marching_cubes_isotropic():
    ellipsoid_isotropic = ellipsoid(6, 10, 16, levelset=True)
    _, surf = ellipsoid_stats(6, 10, 16)

    # Classic
    verts, faces = marching_cubes(ellipsoid_isotropic, 0.0, method='lorensen')[:2]
    surf_calc = mesh_surface_area(verts, faces)
    # Test within 1% tolerance for isotropic. Will always underestimate.
    assert surf > surf_calc and surf_calc > surf * 0.99

    # Lewiner
    verts, faces = marching_cubes(ellipsoid_isotropic, 0.0)[:2]
    surf_calc = mesh_surface_area(verts, faces)
    # Test within 1% tolerance for isotropic. Will always underestimate.
    assert surf > surf_calc and surf_calc > surf * 0.99


def test_marching_cubes_anisotropic():
    # test spacing as numpy array (and not just tuple)
    spacing = np.array([1.0, 10 / 6.0, 16 / 6.0])
    ellipsoid_anisotropic = ellipsoid(6, 10, 16, spacing=spacing, levelset=True)
    _, surf = ellipsoid_stats(6, 10, 16)

    # Classic
    verts, faces = marching_cubes(
        ellipsoid_anisotropic, 0.0, spacing=spacing, method='lorensen'
    )[:2]
    surf_calc = mesh_surface_area(verts, faces)
    # Test within 1.5% tolerance for anisotropic. Will always underestimate.
    assert surf > surf_calc and surf_calc > surf * 0.985

    # Lewiner
    verts, faces = marching_cubes(ellipsoid_anisotropic, 0.0, spacing=spacing)[:2]
    surf_calc = mesh_surface_area(verts, faces)
    # Test within 1.5% tolerance for anisotropic. Will always underestimate.
    assert surf > surf_calc and surf_calc > surf * 0.985

    # Test marching cube with mask
    with pytest.raises(ValueError):
        verts, faces = marching_cubes(
            ellipsoid_anisotropic, 0.0, spacing=spacing, mask=np.array([])
        )[:2]

    # Test spacing together with allow_degenerate=False
    marching_cubes(ellipsoid_anisotropic, 0, spacing=spacing, allow_degenerate=False)


def test_invalid_input():
    # Classic
    with pytest.raises(ValueError):
        marching_cubes(np.zeros((2, 2, 1)), 0, method='lorensen')
    with pytest.raises(ValueError):
        marching_cubes(np.zeros((2, 2, 1)), 1, method='lorensen')
    with pytest.raises(ValueError):
        marching_cubes(np.ones((3, 3, 3)), 1, spacing=(1, 2), method='lorensen')
    with pytest.raises(ValueError):
        marching_cubes(np.zeros((20, 20)), 0, method='lorensen')

    # Lewiner
    with pytest.raises(ValueError):
        marching_cubes(np.zeros((2, 2, 1)), 0)
    with pytest.raises(ValueError):
        marching_cubes(np.zeros((2, 2, 1)), 1)
    with pytest.raises(ValueError):
        marching_cubes(np.ones((3, 3, 3)), 1, spacing=(1, 2))
    with pytest.raises(ValueError):
        marching_cubes(np.zeros((20, 20)), 0)

    # invalid method name
    ellipsoid_isotropic = ellipsoid(6, 10, 16, levelset=True)
    with pytest.raises(ValueError):
        marching_cubes(ellipsoid_isotropic, 0.0, method='abcd')


def test_both_algs_same_result_ellipse():
    # Performing this test on data that does not have ambiguities

    sphere_small = ellipsoid(1, 1, 1, levelset=True)

    vertices1, faces1 = marching_cubes(sphere_small, 0, allow_degenerate=False)[:2]
    vertices2, faces2 = marching_cubes(
        sphere_small, 0, allow_degenerate=False, method='lorensen'
    )[:2]

    # Order is different, best we can do is test equal shape and same
    # vertices present
    assert _same_mesh(vertices1, faces1, vertices2, faces2)


def _same_mesh(vertices1, faces1, vertices2, faces2, tol=1e-10):
    """Compare two meshes, using a certain tolerance and invariant to
    the order of the faces.
    """
    # Unwind vertices
    triangles1 = vertices1[np.array(faces1)]
    triangles2 = vertices2[np.array(faces2)]
    # Sort vertices within each triangle
    triang1 = [np.concatenate(sorted(t, key=lambda x: tuple(x))) for t in triangles1]
    triang2 = [np.concatenate(sorted(t, key=lambda x: tuple(x))) for t in triangles2]
    # Sort the resulting 9-element "tuples"
    triang1 = np.array(sorted([tuple(x) for x in triang1]))
    triang2 = np.array(sorted([tuple(x) for x in triang2]))
    return triang1.shape == triang2.shape and np.allclose(triang1, triang2, 0, tol)


def test_both_algs_same_result_donut():
    # Performing this test on data that does not have ambiguities
    n = 48
    a, b = 2.5 / n, -1.25

    vol = np.empty((n, n, n), 'float32')
    for iz in range(vol.shape[0]):
        for iy in range(vol.shape[1]):
            for ix in range(vol.shape[2]):
                # Double-torii formula by Thomas Lewiner
                z, y, x = float(iz) * a + b, float(iy) * a + b, float(ix) * a + b
                vol[iz, iy, ix] = (
                    ((8 * x) ** 2 + (8 * y - 2) ** 2 + (8 * z) ** 2 + 16 - 1.85 * 1.85)
                    * (
                        (8 * x) ** 2
                        + (8 * y - 2) ** 2
                        + (8 * z) ** 2
                        + 16
                        - 1.85 * 1.85
                    )
                    - 64 * ((8 * x) ** 2 + (8 * y - 2) ** 2)
                ) * (
                    (
                        (8 * x) ** 2
                        + ((8 * y - 2) + 4) * ((8 * y - 2) + 4)
                        + (8 * z) ** 2
                        + 16
                        - 1.85 * 1.85
                    )
                    * (
                        (8 * x) ** 2
                        + ((8 * y - 2) + 4) * ((8 * y - 2) + 4)
                        + (8 * z) ** 2
                        + 16
                        - 1.85 * 1.85
                    )
                    - 64 * (((8 * y - 2) + 4) * ((8 * y - 2) + 4) + (8 * z) ** 2)
                ) + 1025

    vertices1, faces1 = marching_cubes(vol, 0, method='lorensen')[:2]
    vertices2, faces2 = marching_cubes(vol, 0)[:2]

    # Old and new alg are different
    assert not _same_mesh(vertices1, faces1, vertices2, faces2)


def test_masked_marching_cubes():
    ellipsoid_scalar = ellipsoid(6, 10, 16, levelset=True)
    mask = np.ones_like(ellipsoid_scalar, dtype=bool)
    mask[:10, :, :] = False
    mask[:, :, 20:] = False
    ver, faces, _, _ = marching_cubes(ellipsoid_scalar, 0, mask=mask)
    area = mesh_surface_area(ver, faces)

    assert_allclose(area, 299.56878662109375, rtol=0.01)


def test_masked_marching_cubes_empty():
    ellipsoid_scalar = ellipsoid(6, 10, 16, levelset=True)
    mask = np.array([])
    with pytest.raises(ValueError):
        _ = marching_cubes(ellipsoid_scalar, 0, mask=mask)


def test_masked_marching_cubes_all_true():
    ellipsoid_scalar = ellipsoid(6, 10, 16, levelset=True)
    mask = np.ones_like(ellipsoid_scalar, dtype=bool)
    ver_m, faces_m, _, _ = marching_cubes(ellipsoid_scalar, 0, mask=mask)
    ver, faces, _, _ = marching_cubes(ellipsoid_scalar, 0, mask=mask)
    assert_allclose(ver_m, ver, rtol=0.00001)
    assert_allclose(faces_m, faces, rtol=0.00001)
