import json import random from time import time from collections import namedtuple import util from gift_wrapper import rapper from graham import graham_scan from mbc import mbc, mbc_no_shuffle, mbc2_no_shuffle, mbc2 from profile import Profiler from quick_hull import quick_hull import os.path import matplotlib.pyplot as plt #random.seed(1337_420) TimedResult = namedtuple("TimedResult", "algorithm points running_time") def time_it(f: callable, args: tuple = ()): start = time() f(*args) return str(time() - start) def initiate_file(file): with open(file, "w+") as tmp: tmp.write("algorithm\t\tpoints\t\ttime") def write_to_log(file, data): if not os.path.isfile(file): initiate_file(file) tmp = [] for res in data: line = str.join("\t\t", res) print(line) tmp.append(line) write_string = "\n" + str.join("\n", tmp) with open(file, "a+") as open_file: open_file.write(write_string) def calculate_hulls(number_of_points, points): return [TimedResult("graham", number_of_points, time_it(graham_scan, args=(points,))), TimedResult("gift", number_of_points, time_it(rapper, args=(points,))), TimedResult("quick", number_of_points, time_it(quick_hull, args=(points,))), TimedResult("mbch", number_of_points, time_it(mbc, args=(points,))), TimedResult("mbch2", number_of_points, time_it(mbc2, args=(points,)))] def do_square_tests(number_of_points): points_square = {util.gen_point(0, 100) for _ in range(number_of_points)} number_of_points = str(number_of_points) results = calculate_hulls(number_of_points, points_square) write_to_log("square_tests.log", results) def do_circular_tests(number_of_points): points_circular = {util.gen_point(0, 100) for _ in range(number_of_points)} results = calculate_hulls(number_of_points, points_circular) write_to_log("circular_tests.log", results) def do_triangular_tests(number_of_points): left, right, top = util.Point(1,1), util.Point(51,1), util.Point(26,40) points = {util.gen_triangular_point(left, right, top) for _ in range(number_of_points)} results = calculate_hulls(number_of_points, points) write_to_log("triangular_tests.log", results) 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) def sanity_check(): points = {util.gen_point(1, 50) for i in range(100)} graham = set(graham_scan(points)) gift = set(rapper(points)) quick = quick_hull(points) mbch = set.union(mbc(points)) mbch2 = set.union(mbc2(points)) assert gift == graham == quick == mbch == mbch2 def do_one_profile(num_points): print(f"==================================== PROFILE ({num_points}) ====================================") random.seed(6) points = {util.gen_point(0, 100) for _ in range(num_points)} tests = [ ("graham_scan", graham_scan), #("gift_wrapper", rapper), ("quick_hull", quick_hull), ("mbc", mbc), ("mbc_no_shuffle", mbc_no_shuffle), ("mbc2", mbc2), ("mbc2_no_shuffle", mbc2_no_shuffle), ] results = {} for algorithm, func in tests: Profiler.reset() func(points) times = dict(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) unaccounted = total - sum_profiled print("Unaccounted:", unaccounted) times["other"] = unaccounted results[algorithm] = { "times": times, "total": total, "total_profiled": sum_profiled, "unaccounted": unaccounted, } return results def plot_mbc(results, ax): algorithms = list(results.keys()) steps = ( "other", "finding median", "partitioning set", "building constraints", "solving LP", "finding bridge points", "pruning between line points", "shuffling constraints", "extra pruning step", ) util.stacked_bar(ax=ax, data=[[result["times"].get(step, 0) * 1000 for result in results.values()] for step in steps], series_labels=steps, category_labels=algorithms, value_format="{:.1f}") def plot_graham(result, ax): steps = ( "other", "sorting points", "iterating points", "calculating sidedness", ) util.stacked_bar(ax=ax, data=[[result["times"][step] * 1000] for step in steps], series_labels=steps, category_labels=["graham scan"], value_format="{:.1f}") def plot_gift(result, ax): steps = ( "other", "calculating angle", "calculating vector", ) util.stacked_bar(ax=ax, data=[[result["times"][step] * 1000] for step in steps], series_labels=steps, category_labels=["gift wrapper"], value_format="{:.1f}") def plot_quick(result, ax): steps = ( "other", "partitioning set", "finding farthest point from line", ) util.stacked_bar(ax=ax, data=[[result["times"][step] * 1000] for step in steps], series_labels=steps, category_labels=["quickhull"], value_format="{:.1f}") def do_profile(): num_points = 60_000 results = do_one_profile(num_points) print("================== RESULTS ==================") print(json.dumps(results)) fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, sharex=False, sharey=True, gridspec_kw={"width_ratios": (1, 1, 4)}) fig.add_subplot(111, frameon=False) plt.tick_params(labelcolor='none', top='off', bottom='off', left='off', right='off') plt.ylabel("time (ms)") plt.subplots_adjust(wspace=0) plot_graham(results["graham_scan"], ax1) #plot_gift(results["gift_wrapper"], ax2) plot_quick(results["quick_hull"], ax2) plot_mbc({alg: data for alg, data in results.items() if alg.startswith("mbc")}, ax3) plt.show() if __name__ == '__main__': sanity_check() do_profile() exit() for i in range(50, 1000, 50): do_square_tests(i)