how to use visualize_runtimes

import threading<br /> import multiprocessing<br /> import math<br /> import numpy as np<br /> import time<br /> import matplotlib.pyplot as plt<br /> import glob<br /> from PIL import Image<br /> import random<br /> from random import sample<br /> import string<br /> from concurrent.futures import ThreadPoolExecutor</p> <p>cpu_workers = 3<br /> nSim = 12</p> <p>def generate_bar_colors(cpu_workers):<br /> colors = [‘red’, ‘gold’, ‘royalblue’]<br /> return colors</p> <p>def visualize_runtimes(results, title):<br /> colors = generate_bar_colors(cpu_workers)<br /> plt.rcParams[“font.family”] = “Times New Roman”<br /> plt.rcParams[‘axes.axisbelow’] = True<br /> start,stop = np.array(results).T<br /> plt.barh(range(len(start)),stop-start,left=start, color=colors)<br /> plt.grid(axis=”x”, color=”lightgrey”)<br /> plt.title(“Tasks”, rotation=’horizontal’, fontsize=12, horizontalalignment=”left”, x=0)<br /> plt.xlabel(“Seconds”, fontsize=12, horizontalalignment=”right”, x=1.0)</p> <p>def multithreading(func, args, workers):<br /> begin_time=time.time()<br /> with ThreadPoolExecutor(max_workers = workers) as executor:<br /> res = executor.map(func, args, [begin_time for i in range (len(args))])<br /> return list(res)</p> <p>def simulation(i, base):<br /> start = time.time() – base<br /> print(str(threading.current_thread().getName()) + ‘: ‘+ str(i))<br /> time.sleep(math.cos(i)+i*0.1+1)<br /> stop = time.time() – base<br /> return start, stop</p> <p>if __name__ == ‘__main__’:<br /> visualize_runtimes(multithreading(simulation, i, cpu_workers), “Multi-threading”)<br /> plt.savefig(‘foo.png’, bbox_inches=”tight”)</p> <p>plt.show()