import matplotlib.pyplot as plt
import numpy as np
from scipy.spatial import ConvexHull

from concave_hull import (  # noqa: F401
    concave_hull,
    concave_hull_indexes,
    convex_hull_indexes,
)

points = []
c = np.array([250, 250])
for x in np.arange(100, 400, 5 * np.pi):
    for y in np.arange(100, 400, 5 * np.pi):
        if x > c[0] and y > c[1]:
            continue
        r = np.linalg.norm(c - [x, y])
        if r > 150:
            continue
        points.append([x, y])
points = np.array(points)
convex_hull = ConvexHull(points[:, :2])  # it's already N-by-2, I'm just emphasizing

# https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.ConvexHull.html

plt.plot(points[:, 0], points[:, 1], "o")
for simplex in convex_hull.simplices:
    continue
    plt.plot(points[simplex, 0], points[simplex, 1], "g-", alpha=0.5)

hull = convex_hull_indexes(points[:, :2])
for i, j in zip(hull[:-1], hull[1:]):  # noqa: B905
    plt.plot(
        [points[i, 0], points[j, 0]], [points[i, 1], points[j, 1]], "g-", alpha=0.5
    )

idxes = concave_hull_indexes(
    points[:, :2],
    length_threshold=50,
    # convex_hull_indexes=convex_hull.vertices.astype(np.int32),
)
# you can get coordinates by `points[idxes]`
# assert np.all(points[idxes] == concave_hull(points, length_threshold=50))

for f, t in zip(idxes[:-1], idxes[1:]):  # noqa
    seg = points[[f, t]]
    plt.plot(seg[:, 0], seg[:, 1], "r-", alpha=0.5)

plt.gca().set_aspect("equal")
# plt.savefig("docs/hull.png")
plt.show()
