2018-10-11 13:54:52 +00:00
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import random
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2018-09-24 13:27:08 +00:00
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import statistics
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2018-10-08 16:31:00 +00:00
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from math import inf
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from typing import Set, List, Tuple
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2018-10-08 13:17:02 +00:00
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2018-10-11 13:54:52 +00:00
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from scipy.optimize import linprog
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import util
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2018-10-09 17:26:55 +00:00
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from util import Side, Point, gen_point, display
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2018-09-24 13:27:08 +00:00
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2018-10-11 13:54:52 +00:00
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def sidedness(slope: float, intersection: float, p3: Point, flipper: callable, eps=0.0000001) -> Side:
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2018-10-09 17:26:55 +00:00
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# finds where a point is in regards to a line
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2018-10-11 13:54:52 +00:00
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if flipper(p3.y) - eps <= flipper(slope * p3.x + intersection) <= flipper(p3.y) + eps:
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2018-10-08 13:17:02 +00:00
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return Side.ON
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elif p3.y > slope * p3.x + intersection:
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return Side.ABOVE
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return Side.BELOW
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2018-10-08 16:31:00 +00:00
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def solve_1dlp(c: float, constraints: List[Tuple[float, float]]):
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"""
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:param c: c1
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:param constraints: [(ai, bi), ...]
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:return: x1
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"""
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2018-10-09 17:26:55 +00:00
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try:
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if c > 0:
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return max(b/a for a, b in constraints if a < 0)
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return min(b/a for a, b in constraints if a > 0)
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except ValueError: # unbounded
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return -inf if c > 0 else inf
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2018-10-09 15:52:53 +00:00
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2018-10-09 17:26:55 +00:00
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assert solve_1dlp(1, [(-1, -2)]) == 2
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assert solve_1dlp(1, [(-1, -2), (-1, -3)]) == 3
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assert solve_1dlp(1, [(-1, -3), (-1, -2)]) == 3
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assert solve_1dlp(-1, [(1, 3), (1, 2)]) == 2
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assert solve_1dlp(1, [(-1, 3), (-1, 2)]) == -2
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2018-10-08 16:31:00 +00:00
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def solve_2dlp(c: Tuple[float, float], constraints: List[Tuple[Tuple[float, float], float]]):
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"""
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:param c: (c1, c2)
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:param constraints: [(ai1, ai2, bi), ...]
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:return: x1, x2
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"""
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2018-10-09 17:26:55 +00:00
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c1, c2 = c
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x1, x2 = (-inf, -inf) if c1 > 0 else (inf, inf)
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#random.shuffle(constraints)
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2018-10-09 15:52:53 +00:00
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2018-10-11 13:54:52 +00:00
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for i, ((a1, a2), b) in enumerate(constraints[1:], start=0):
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if not a1*x1 + a2*x2 <= b:
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x1 = solve_1dlp(c1 - c2*a1/a2,
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[(ai1 - ai2*a1 / a2, bi - ai2*b / a2) for (ai1, ai2), bi in constraints[:i]])
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x2 = (b - a1*x1) / a2
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2018-10-08 18:02:33 +00:00
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2018-10-08 16:31:00 +00:00
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return x1, x2
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2018-10-11 13:54:52 +00:00
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def mbc_ch(points: Set[Point], flipper: callable) -> Set[Point]:
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2018-10-08 13:17:02 +00:00
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if len(points) <= 2:
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return points
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# Find the point with median x-coordinate, and partition the points on this point
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med_x = statistics.median(p.x for p in points)
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# Find left and right points in regards to median
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pl = {p for p in points if p.x < med_x}
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pr = {p for p in points if p.x >= med_x}
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2018-09-24 13:27:08 +00:00
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# Find the bridge over the vertical line in pm
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2018-10-11 13:54:52 +00:00
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slope, intercept = solve_2dlp((flipper(med_x), flipper(1)),
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[((flipper(-p.x), flipper(-1)), flipper(-p.y)) for p in points])
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2018-10-08 13:17:02 +00:00
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# Find the two points which are on the line, should work
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2018-10-11 13:54:52 +00:00
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on = {p for p in points if sidedness(slope, intercept, p, flipper) == Side.ON}
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left_point = min(on)
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right_point = max(on)
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2018-10-08 13:17:02 +00:00
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# Prune the points between the two line points
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2018-10-11 13:54:52 +00:00
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pl = {p for p in points if p.x <= left_point.x}
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pr = {p for p in points if p.x >= right_point.x}
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2018-10-08 13:17:02 +00:00
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2018-10-11 13:54:52 +00:00
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return set.union(mbc_ch(pl, flipper), {left_point, right_point}, mbc_ch(pr, flipper))
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2018-10-08 13:17:02 +00:00
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2018-10-11 12:38:59 +00:00
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def mbc(points: Set[Point]) -> Set[Point]:
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return set.union(mbc_ch(points, lambda x: x), mbc_ch(points, lambda x: -x))
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2018-10-08 13:17:02 +00:00
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2018-10-11 12:38:59 +00:00
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if __name__ == '__main__':
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points = {gen_point(1, 10) for _ in range(20)}
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upper_hull_points = mbc_ch(points, lambda x: x)
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lower_hull_points = mbc_ch(points, lambda x: -x)
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display(points, upper_hull_points.union(lower_hull_points))
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