# -*- coding: utf-8 -*-
import heapq
import sys

import numpy as np
import pylab as PL
from scipy.spatial.ckdtree import cKDTree

exit()


def vec(a, b):
    return b - a


def bfs(points):
    return


def in_ellipse(p, f1, f2, r, offset=0):
    df = ((f1 - f2) ** 2).sum(0) ** 0.5
    d_f1 = ((p - f1) ** 2).sum(1) ** 0.5
    d_f2 = ((p - f2) ** 2).sum(1) ** 0.5
    return (d_f1 + d_f2) < (df * (1 + r))


num_points = 100000

p_orig = np.random.normal(0, 10, size=(num_points, 2))
tree = cKDTree(p_orig)
f1 = np.array([0, -30])
f2 = -f1  # np.random.normal(0, 20, (3,))
# r = 2 ** ((n / cnt) - cnt)

mask = in_ellipse(p_orig, f1, f2, 0.1)

p = p_orig[mask]
p_orig = p_orig[~mask]

colors = np.random.random(p.shape[0])
fig = PL.gcf()
PL.scatter(
    p_orig[:, 0],
    p_orig[:, 1],
    marker=".",
    s=0.2,
    edgecolor="None",
    c=[(0.0, 0.0, 0.0)],
    alpha=0.75,
    rasterized=True,
)
PL.scatter(
    p[:, 0], p[:, 1], marker="s", s=0.2, edgecolor="None", c=colors, rasterized=True
)
PL.plot(f1[0], f1[1], "r.", label="Source")
PL.plot(f2[0], f2[1], "g.", label="Destination")

max_v = max(p_orig[:, 0].max(), p_orig[:, 1].max(), f1[0], f1[1], f2[0], f2[1]) + 2
min_v = min(p_orig[:, 0].min(), p_orig[:, 1].min(), f1[0], f1[1], f2[0], f2[1]) - 2


PL.xlim(min_v, max_v)
PL.ylim(min_v, max_v)

PL.legend()
PL.savefig(sys.argv[1], dpi=1200)