Vehicle-Anti-Theft-Face-Recognition-System/venv/Lib/site-packages/skimage/morphology/tests/test_util.py

"""Tests for `_util`."""


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

from skimage.morphology import _util


@pytest.mark.parametrize("image_shape", [
    (111,), (33, 44), (22, 55, 11), (6, 5, 4, 3)
])
@pytest.mark.parametrize("order", ["C", "F"])
def test_offsets_to_raveled_neighbors_highest_connectivity(image_shape, order):
    """
    Check scenarios where selem is always of the highest connectivity
    and all dimensions are > 2.
    """
    selem = np.ones((3,) * len(image_shape), dtype=bool)
    center = (1,) * len(image_shape)
    offsets = _util._offsets_to_raveled_neighbors(
        image_shape, selem, center, order
    )

    # Assert only neighbors are present, center was removed
    assert len(offsets) == selem.sum() - 1
    assert 0 not in offsets
    # Assert uniqueness
    assert len(set(offsets)) == offsets.size
    # offsets form pairs of with same value but different signs
    # if selem is symmetric around center
    assert all(-x in offsets for x in offsets)

    # Construct image whose values are the Manhattan distance to its center
    image_center = tuple(s // 2 for s in image_shape)
    coords = [
        np.abs(np.arange(s, dtype=np.intp) - c)
        for s, c in zip(image_shape, image_center)
    ]
    grid = np.meshgrid(*coords, indexing="ij")
    image = np.sum(grid, axis=0)

    image_raveled = image.ravel(order)
    image_center_raveled = np.ravel_multi_index(
        image_center, image_shape, order=order
    )

    # Sample raveled image around its center
    samples = []
    for offset in offsets:
        index = image_center_raveled + offset
        samples.append(image_raveled[index])

    # Assert that center with value 0 wasn't selected
    assert np.min(samples) == 1
    # Assert that only neighbors where selected
    # (highest value == connectivity)
    assert np.max(samples) == len(image_shape)
    # Assert that nearest neighbors are selected first
    assert list(sorted(samples)) == samples


@pytest.mark.parametrize("image_shape", [
    (2,), (2, 2), (2, 1, 2), (2, 2, 1, 2), (0, 2, 1, 2)
])
@pytest.mark.parametrize("order", ["C", "F"])
def test_offsets_to_raveled_neighbors_selem_smaller_image(image_shape, order):
    """
    Test if a dimension indicated by `image_shape` is smaller than in
    `selem`.
    """
    selem = np.ones((3,) * len(image_shape), dtype=bool)
    center = (1,) * len(image_shape)
    offsets = _util._offsets_to_raveled_neighbors(
        image_shape, selem, center, order
    )

    # Assert only neighbors are present, center and duplicates (possible
    # for this scenario) where removed
    assert len(offsets) <= selem.sum() - 1
    assert 0 not in offsets
    # Assert uniqueness
    assert len(set(offsets)) == offsets.size
    # offsets form pairs of with same value but different signs
    # if selem is symmetric around center
    assert all(-x in offsets for x in offsets)


def test_offsets_to_raveled_neighbors_explicit_0():
    """Check reviewed example."""
    image_shape = (100, 200, 3)
    selem = np.ones((3, 3, 3), dtype=bool)
    center = (1, 1, 1)
    offsets = _util._offsets_to_raveled_neighbors(
        image_shape, selem, center
    )

    desired = np.array([
          3, -600,    1,   -1,  600,   -3,    4,    2,  603,   -2,   -4,
        -597,  601, -599, -601, -603,  599,  597,  602, -604,  596, -596,
        -598, -602,  598,  604
    ])
    assert_array_equal(offsets, desired)


def test_offsets_to_raveled_neighbors_explicit_1():
    """Check reviewed example where selem is larger in last dimension."""
    image_shape = (10, 9, 8, 3)
    selem = np.ones((3, 3, 3, 4), dtype=bool)
    center = (1, 1, 1, 1)
    offsets = _util._offsets_to_raveled_neighbors(
        image_shape, selem, center
    )

    desired = np.array([
          24,    3,    1,   -1,   -3,  -24, -216,  216, -192,  215,   -2,
         -21,  -23,    2,  -25,  -27,    4,  217,   21,  219,   -4,   23,
          25, -240,  240,  192,   27, -213, -219,  213, -215, -217, -243,
         191, -241,  195,  189,  212,   26,    5,   20,   28,   22,  214,
         243, -237,  -22,  241, -214, -212,  237, -218, -195,  -20,  220,
        -193, -191,  218, -189,  -28,  -26,  193, -239, -220,  239,  196,
         221,  242,  236,  238,  194, -244, -188, -238, -211, -196, -194,
        -190, -236,  -19,  244,   29,  188, -242,  190, -187,  197, -235,
         245
    ])
    assert_array_equal(offsets, desired)