Profiling.
This commit is contained in:
parent
54c97fc832
commit
776412995c
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@ -1,9 +1,11 @@
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# Use atan2 instead of acos to calc angle; atan2(x,y) of the point we potentially want to add
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from math import acos, sqrt
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from profile import Profiler
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from util import Vector, Point, gen_point
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@Profiler("calculating angle")
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def calc_angle(v1: Vector, v2: Vector) -> float:
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dot = (v1.x * v2.x) + (v1.y * v2.y)
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len_1 = sqrt(v1.x**2 + v1.y**2)
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@ -13,18 +15,21 @@ def calc_angle(v1: Vector, v2: Vector) -> float:
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return acos(max(min(tmp, 1), -1)) # acos is only defined in [-1,1]
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@Profiler("calculating vector")
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def calc_vector(p1: Point, p2: Point) -> Vector:
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return Vector((p2.x - p1.x), (p2.y - p1.y))
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return Vector((p2.x - p1.x), (p2. y - p1.y))
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@Profiler("gift_wrapper")
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def rapper(points: set):
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min_pt = min(points)
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hull = [min_pt]
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comp_vec = Vector(0, 1)
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with Profiler("iterating points", excluded=("calculating angle", "calculating vector")):
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while True:
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hull.append(min(points - {hull[-1]},
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key=lambda p: calc_angle(comp_vec,
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calc_vector(hull[-1], p))))
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key=lambda p: calc_angle(comp_vec, calc_vector(hull[-1], p))))
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comp_vec = calc_vector(hull[-2], hull[-1])
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if hull[-1] == min_pt:
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23
h2/graham.py
23
h2/graham.py
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@ -1,8 +1,10 @@
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from util import gen_point, Side, Point, display
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from profile import Profiler
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from util import gen_point, Side, display
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@Profiler("calculating sidedness")
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def sidedness(p1, p2, p3, eps=0.0000001):
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# Find line from p1 to p2, ask where p3 is in relation to this
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y = p3.y * (p2.x - p1.x)
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@ -18,33 +20,26 @@ def sidedness(p1, p2, p3, eps=0.0000001):
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return Side.BELOW
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# test
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p1 = Point(4, 4)
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p2 = Point(0, 0)
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p3 = Point(5, 2)
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# print(sidedness(p1, p2, p3))
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@Profiler("graham_scan")
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def graham_scan(points):
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# A funky issue where both a and b become negative in the sidedness test causes us to have to use
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# Side.ABOVE for both tests, regardless of UH or LH.
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with Profiler("sorting points"):
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sorted_points = sorted(points)
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UH = sorted_points[:2]
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with Profiler("iterating upper hull", excluded=("calculating sidedness",)):
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for s in sorted_points[2:]:
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while len(UH) > 1 and (sidedness(UH[-2], UH[-1], s) != Side.ABOVE):
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del UH[-1]
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UH.append(s)
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with Profiler("reversing list"):
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reversed_list = list(reversed(sorted_points))
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reversed_list.append(UH[0])
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LH = reversed_list[:2]
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with Profiler("iterating lower hull", excluded=("calculating sidedness",)):
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for s in reversed_list[2:]:
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while len(LH) > 1 and (sidedness(LH[-2], LH[-1], s) != Side.ABOVE):
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del LH[-1]
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69
h2/mbc.py
69
h2/mbc.py
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@ -1,8 +1,8 @@
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import random
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from math import sqrt
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from typing import Set
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from util import Side, Point, gen_point, display, gen_circular_point, gen_triangular_point
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from profile import Profiler
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from util import Side, Point, gen_point, display, gen_circular_point
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def sidedness(slope: float, intersection: float, p3: Point, flipper: callable, eps=0.0000001) -> Side:
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@ -14,6 +14,7 @@ def sidedness(slope: float, intersection: float, p3: Point, flipper: callable, e
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return Side.BELOW
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@Profiler("solving 1D LP")
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def solve_1dlp(c, constraints):
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c1, c2 = c
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((a1, a2), b) = constraints[-1]
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@ -22,7 +23,6 @@ def solve_1dlp(c, constraints):
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interval = [-10_000, 10_000]
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for (lel_a1, lel_a2), lel_b in constraints:
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bj, aj = (lel_b - lel_a2 * q), (lel_a1 - lel_a2 * p)
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if aj < 0 and bj / aj > interval[0]:
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interval[0] = bj / aj
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@ -36,6 +36,7 @@ def solve_1dlp(c, constraints):
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return interval[1], q - (p * interval[1])
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@Profiler("solving 2D LP")
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def solve_2dlp(c, constraints):
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c1, c2 = c
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x1 = -10_000 if c1 > 0 else 10_000
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@ -47,6 +48,7 @@ def solve_2dlp(c, constraints):
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return x1, x2
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@Profiler("finding median")
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def find_median(points):
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num_candidates = min(5, len(points))
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candidates = random.sample(points, num_candidates)
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@ -59,40 +61,77 @@ def find_median(points):
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return median[0]
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def mbc_ch(points: Set[Point], flipper: callable) -> Set[Point]:
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def is_left(a: Point, b: Point, c: Point):
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return ((b.x - a.x) * (c.y - a.y) - (b.y - a.y) * (c.x - a.x)) > 0
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def mbc_ch(points: Set[Point], flipper: callable, extra_prune=False, shuffle=True) -> Set[Point]:
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if len(points) < 2:
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return points
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# Extra pruning step
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if extra_prune:
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with Profiler("extra pruning step"):
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left_point = min(points, key=lambda p: (p.x, -p.y))
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right_point = max(points, key=lambda p: (p.x, -p.y))
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if flipper(1) == 1:
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points = {p for p in points if is_left(left_point, right_point, p)}.union({left_point, right_point})
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else:
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points = {p for p in points if not is_left(left_point, right_point, p)}.union({left_point, right_point})
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# Find the point with median x-coordinate, and partition the points on this point
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med_x = find_median(points)
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# Find left and right points in regards to median
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with Profiler("partitioning set"):
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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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# Shuffle
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constraints = [((flipper(-p.x), flipper(-1)), flipper(-p.y)) for p in points]
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if shuffle:
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with Profiler("shuffling constraints"):
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random.shuffle(constraints)
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# Find the bridge over the vertical line in pm
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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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slope, intercept = solve_2dlp((flipper(med_x), flipper(1)), constraints)
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with Profiler("finding bridge points"):
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left_point = next(p for p in pl if sidedness(slope, intercept, p, flipper) == Side.ON)
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right_point = next(p for p in pr if sidedness(slope, intercept, p, flipper) == Side.ON)
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# Find the two points which are on the line
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#dist_to_line = lambda p: abs(intercept + slope * p.x - p.y)/sqrt(1 + slope**2)
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#left_point = min(pl, key=dist_to_line)
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#right_point = min(pr, key=dist_to_line)
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# Prune the points between the two line points
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with Profiler("pruning between line points"):
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pl = {p for p in pl if p.x <= left_point.x}
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pr = {p for p in pr if p.x >= right_point.x}
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return set.union(mbc_ch(pl, flipper), {left_point, right_point}, mbc_ch(pr, flipper))
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return set.union(mbc_ch(pl, flipper, extra_prune=extra_prune, shuffle=shuffle),
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{left_point, right_point},
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mbc_ch(pr, flipper, extra_prune=extra_prune, shuffle=shuffle))
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@Profiler("mbc")
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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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return set.union(mbc_ch(points, lambda x: x, extra_prune=False, shuffle=True),
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mbc_ch(points, lambda x: -x, extra_prune=False, shuffle=True))
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@Profiler("mbc2")
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def mbc2(points: Set[Point]) -> Set[Point]:
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return set.union(mbc_ch(points, lambda x: x, extra_prune=True, shuffle=True),
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mbc_ch(points, lambda x: -x, extra_prune=True, shuffle=True))
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@Profiler("mbc_no_shuffle")
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def mbc_no_shuffle(points: Set[Point]) -> Set[Point]:
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return set.union(mbc_ch(points, lambda x: x, extra_prune=False, shuffle=False),
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mbc_ch(points, lambda x: -x, extra_prune=False, shuffle=False))
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@Profiler("mbc2_no_shuffle")
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def mbc2_no_shuffle(points: Set[Point]) -> Set[Point]:
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return set.union(mbc_ch(points, lambda x: x, extra_prune=True, shuffle=False),
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mbc_ch(points, lambda x: -x, extra_prune=True, shuffle=False))
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if __name__ == '__main__':
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26
h2/profile.py
Normal file
26
h2/profile.py
Normal file
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@ -0,0 +1,26 @@
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import time
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from collections import defaultdict
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from contextlib import ContextDecorator
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from typing import Tuple
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class Profiler(ContextDecorator):
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results = defaultdict(float)
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def __init__(self, name: str, excluded: Tuple = None) -> None:
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self.name = name
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self.excluded = excluded or ()
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def __enter__(self):
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self.start = time.time()
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return self
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def __exit__(self, *exc):
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stop = time.time()
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excluded = sum(self.results[e] for e in self.excluded)
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self.results[self.name] += stop - self.start - excluded
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return False
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@classmethod
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def reset(cls):
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cls.results.clear()
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from math import sqrt
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from typing import Set
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from profile import Profiler
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from util import Point, gen_point, display
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@ -14,6 +15,7 @@ def is_left(a: Point, b: Point, c: Point):
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return ((b.x - a.x) * (c.y - a.y) - (b.y - a.y) * (c.x - a.x)) > 0
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@Profiler("quick_hull")
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def quick_hull(points: Set[Point]):
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left = min(points)
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right = max(points)
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@ -21,12 +23,16 @@ def quick_hull(points: Set[Point]):
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hull = {left, right}
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points = points - hull
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find_hull({p for p in points if not is_left(left, right, p)},
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with Profiler("partitioning set"):
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partition = {p for p in points if not is_left(left, right, p)}
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find_hull(partition,
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left,
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right,
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hull)
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find_hull({p for p in points if not is_left(right, left, p)},
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with Profiler("partitioning set"):
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partition = {p for p in points if not is_left(right, left, p)}
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find_hull(partition,
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right,
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left,
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hull)
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@ -38,16 +44,21 @@ def find_hull(points: Set[Point], p: Point, q: Point, hull: Set[Point]):
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if not points:
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return
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with Profiler("finding farthest point from line"):
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farthest = max(points, key=lambda point: abs(distance(p, q, point)))
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hull.add(farthest)
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points.remove(farthest)
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find_hull({po for po in points if not is_left(p, farthest, po)},
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with Profiler("partitioning set"):
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partition = {po for po in points if not is_left(p, farthest, po)}
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find_hull(partition,
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p,
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farthest,
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hull)
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find_hull({po for po in points if not is_left(farthest, q, po)},
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with Profiler("partitioning set"):
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partition = {po for po in points if not is_left(farthest, q, po)}
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find_hull(partition,
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farthest,
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q,
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hull)
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@ -4,7 +4,8 @@ from collections import namedtuple
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import util
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from gift_wrapper import rapper
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from graham import graham_scan
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from mbc import mbc
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from mbc import mbc, mbc_no_shuffle, mbc2_no_shuffle, mbc2
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from profile import Profiler
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from quick_hull import quick_hull
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import os.path
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TimedResult = namedtuple("TimedResult", "algorithm points running_time")
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def time_it(f: callable, args: tuple = (), iterations=1):
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def time_it(f: callable, args: tuple = ()):
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start = time()
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for i in range(iterations):
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f(*args)
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return str(time() - start)
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@ -26,7 +26,6 @@ def initiate_file(file):
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def write_to_log(file, data):
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if not os.path.isfile(file):
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initiate_file(file)
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open_file.write(write_string)
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def do_square_tests(amount_of_points):
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points_square = {util.gen_point(0, 100) for _ in range(amount_of_points)}
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amount_of_points = str(amount_of_points)
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def calculate_hulls(number_of_points, points):
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return [TimedResult("graham", number_of_points, time_it(graham_scan, args=(points,))),
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TimedResult("gift", number_of_points, time_it(rapper, args=(points,))),
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TimedResult("quick", number_of_points, time_it(quick_hull, args=(points,))),
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TimedResult("mbch", number_of_points, time_it(mbc, args=(points,))),
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TimedResult("mbch2", number_of_points, time_it(mbc2, args=(points,)))]
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results = [TimedResult("graham", amount_of_points, time_it(graham_scan, args=(points_square,))),
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TimedResult("gift", amount_of_points, time_it(rapper, args=(points_square,))),
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TimedResult("quick", amount_of_points, time_it(quick_hull, args=(points_square,))),
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TimedResult("mbch", amount_of_points, time_it(mbc, args=(points_square,)))]
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def do_square_tests(number_of_points):
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points_square = {util.gen_point(0, 100) for _ in range(number_of_points)}
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number_of_points = str(number_of_points)
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results = calculate_hulls(number_of_points, points_square)
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write_to_log("square_tests.log", results)
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def do_circular_tests(amount_of_points):
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points_circular = {util.gen_point(0, 100) for _ in range(amount_of_points)}
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results = [TimedResult("graham", amount_of_points, time_it(graham_scan, args=(points_circular,))),
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TimedResult("gift", amount_of_points, time_it(rapper, args=(points_circular,))),
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TimedResult("quick", amount_of_points, time_it(quick_hull, args=(points_circular,))),
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TimedResult("mbc", amount_of_points, time_it(mbc, args=(points_circular,)))]
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def do_circular_tests(number_of_points):
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points_circular = {util.gen_point(0, 100) for _ in range(number_of_points)}
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results = calculate_hulls(number_of_points, points_circular)
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write_to_log("circular_tests.log", results)
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def do_triangular_tests(amount_of_points):
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def do_triangular_tests(number_of_points):
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left, right, top = util.Point(1,1), util.Point(51,1), util.Point(26,40)
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points = {util.gen_triangular_point(left, right, top) for _ in range(amount_of_points)}
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results = [TimedResult("graham", amount_of_points, time_it(graham_scan, args=(points,))),
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TimedResult("gift", amount_of_points, time_it(rapper, args=(points,))),
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TimedResult("quick", amount_of_points, time_it(quick_hull, args=(points,))),
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TimedResult("mbc", amount_of_points, time_it(mbc, args=(points,)))]
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points = {util.gen_triangular_point(left, right, top) for _ in range(number_of_points)}
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results = calculate_hulls(number_of_points, points)
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write_to_log("triangular_tests.log", results)
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def do_quadratic_tests(amount_of_points):
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points = {util.gen_weird_point(-10, 10) for _ in range(amount_of_points)}
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results = [TimedResult("graham", amount_of_points, time_it(graham_scan, args=(points,))),
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TimedResult("gift", amount_of_points, time_it(rapper, args=(points,))),
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TimedResult("quick", amount_of_points, time_it(quick_hull, args=(points,))),
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TimedResult("mbc", amount_of_points, time_it(mbc, args=(points,)))]
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def do_quadratic_tests(number_of_points):
|
||||
points = {util.gen_weird_point(-10, 10) for _ in range(number_of_points)}
|
||||
|
||||
results = calculate_hulls(number_of_points, points)
|
||||
write_to_log("quadratic_tests.log", results)
|
||||
|
||||
|
||||
|
|
@ -94,10 +85,46 @@ def sanity_check():
|
|||
gift = set(rapper(points))
|
||||
quick = quick_hull(points)
|
||||
mbch = set.union(mbc(points))
|
||||
assert gift == graham == quick == mbch
|
||||
mbch2 = set.union(mbc2(points))
|
||||
assert gift == graham == quick == mbch == mbch2
|
||||
|
||||
|
||||
def do_profile():
|
||||
print("==================================== PROFILE RESULTS ====================================")
|
||||
random.seed(6)
|
||||
points = {util.gen_point(0, 100) for _ in range(60_000)}
|
||||
|
||||
tests = [
|
||||
("graham_scan", graham_scan),
|
||||
("gift_wrapper", rapper),
|
||||
("quick_hull", quick_hull),
|
||||
("mbc", mbc),
|
||||
("mbc2", mbc2),
|
||||
("mbc_no_shuffle", mbc_no_shuffle),
|
||||
("mbc2_no_shuffle", mbc2_no_shuffle),
|
||||
]
|
||||
|
||||
for algorithm, func in tests:
|
||||
Profiler.reset()
|
||||
func(points)
|
||||
|
||||
times = Profiler.results
|
||||
|
||||
print(f"-------------- {algorithm} --------------")
|
||||
print("Times:", times)
|
||||
|
||||
total = times[algorithm]
|
||||
print("Total:", total)
|
||||
|
||||
sum_profiled = sum(times.values()) - total
|
||||
print("Total Profiled:", sum_profiled)
|
||||
|
||||
print("Unaccounted:", total - sum_profiled)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
sanity_check()
|
||||
do_profile()
|
||||
exit()
|
||||
for i in range(50, 1000, 50):
|
||||
do_square_tests(i)
|
||||
|
|
|
|||
|
|
@ -72,6 +72,7 @@ def gen_graph(data):
|
|||
graham = data['graham']
|
||||
quick = data['quick']
|
||||
mbch = data['mbch']
|
||||
mbch2 = data['mbch2']
|
||||
gift = data['gift']
|
||||
|
||||
graham_x = [p[0] for p in graham]
|
||||
|
|
@ -83,15 +84,19 @@ def gen_graph(data):
|
|||
mbch_x = [p[0] for p in mbch]
|
||||
mbch_y = [p[1] for p in mbch]
|
||||
|
||||
mbch2_x = [p[0] for p in mbch2]
|
||||
mbch2_y = [p[1] for p in mbch2]
|
||||
|
||||
gift_x = [p[0] for p in gift]
|
||||
gift_y = [p[1] for p in gift]
|
||||
|
||||
plt.plot(graham_x, graham_y)
|
||||
plt.plot(quick_x, quick_y)
|
||||
plt.plot(mbch_x, mbch_y)
|
||||
plt.plot(mbch2_x, mbch2_y)
|
||||
plt.plot(gift_x, gift_y)
|
||||
|
||||
plt.legend(['graham', 'quick', 'mbch', 'gift'], loc='upper left')
|
||||
plt.legend(['graham', 'quick', 'mbch', 'mbch2', 'gift'], loc='upper left')
|
||||
|
||||
plt.show()
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user