【问题标题】:How to visualize threads in a multi-threading task/time graph?如何在多线程任务/时间图中可视化线程?
【发布时间】:2019-10-14 01:52:30
【问题描述】:

我正在尝试使用 matplotlib 以一种有意义的方式绘制我的多线程代码的线程。 我希望每个线程都用一种颜色可视化。通过这种方式,绘图将清楚地显示哪些任务由哪个线程执行等。 所以要明确一点,我想说(下图)黄色条是线程1执行的进程,红色条是线程2执行的进程,蓝色条是线程3执行的进程。

这似乎很难,我能想到的最好的方法是在下面(见图和代码)。 在示例中,我们有 3 个线程和 12 个任务(每个任务的持续时间在某个点上都是可变的)。线程 1 以黄色开始,线程 2 以红色开始,线程 3 以蓝色开始。我希望在整个图表中保持它们的颜色编码。然而,我们看到的是线程 1 执行任务 0、7 和 10,但它会将颜色从黄色变为红色再变为红色。线程 2 也是如此:它执行任务 2、5、8 和 11,但将颜色从红色切换到蓝色,再从蓝色切换到蓝色。线程 3 相同。 所以颜色实际上在这里以 3 为周期出现,并且与线程无关。正如我之前所说,我想让它们依赖于线程号,以使多线程图更有意义(因为目前还没有)。

有人知道怎么做吗?

import threading
import multiprocessing
import math
import numpy as np
import time
import matplotlib.pyplot as plt
import glob
from PIL import Image
import random
from random import sample
import string
from concurrent.futures import ThreadPoolExecutor


cpu_workers = 3
nSim = 12

def generate_bar_colors(cpu_workers):
    colors = ['red', 'gold', 'royalblue']
    return colors

def visualize_runtimes(results, title):
    colors = generate_bar_colors(cpu_workers)
    plt.rcParams["font.family"] = "Times New Roman"
    plt.rcParams['axes.axisbelow'] = True
    start,stop = np.array(results).T
    plt.barh(range(len(start)),stop-start,left=start, color=colors)
    plt.grid(axis='x', color= 'lightgrey')
    plt.title("Tasks", rotation='horizontal', fontsize=12, horizontalalignment="left", x=0)
    plt.xlabel("Seconds", fontsize=12, horizontalalignment='right', x=1.0)

def multithreading(func, args, workers):
    begin_time=time.time()
    with ThreadPoolExecutor(max_workers = workers) as executor:
        res = executor.map(func, args, [begin_time for i in range (len(args))])
    return list(res)

def simulation(i, base):
    start = time.time() - base
    print(str(threading.current_thread().getName()) + ': '+ str(i))
    time.sleep(math.cos(i)+i*0.1+1)
    stop = time.time() - base
    return start, stop


if __name__ == '__main__':
    visualize_runtimes(multithreading(simulation, i, cpu_workers), "Multi-threading")
    plt.savefig('foo.png', bbox_inches='tight')

plt.show()

【问题讨论】:

  • 您的示例代码不完整,Unknown: 'i'。您如何将 taks 映射到颜色,因为您的 simulation 仅返回 return start, stop

标签: python multithreading matplotlib plot data-visualization


【解决方案1】:

实现此目的的一种方法(参见下面的代码)。现在每个线程都分配了颜色,很明显计算是多线程的(在这种情况下,3 个线程正在执行 12 个任务)。

import threading

import math

from matplotlib.lines import Line2D


from concurrent.futures import ThreadPoolExecutor

from concurrent.futures import ProcessPoolExecutor

import matplotlib.pyplot as plt

from matplotlib.ticker import AutoMinorLocator, MultipleLocator, FuncFormatter
import time

import numpy as np




cpu_workers = 3

nSim = 12

i = range(nSim)



#Multi-threading function ----------------------------------------------------------------------------------------------

def multithreading(func, args, workers):

    with ThreadPoolExecutor(max_workers = workers) as executor:
        
        responses = executor.map(func, args)

    return list(responses)



#List of unique arguments in preserved order as in my_list -------------------------------------------------------------

def pres_uniq_list(my_list): #returns a unique list in preserved order

    seen = set()

    result = []

    for e in my_list:

        if e not in seen:

            result.append(e)

            seen.add(e)

    return result



#Get netto simulation start- and end-times as well as duration ---------------------------------------------------------

def sep_list_elements(list_of_lists, proc_start_t):

    start_values = [inner_list[0] for inner_list in list_of_lists]

    start_values = np.array(start_values) - proc_start_t


    end_values = [inner_list[1] for inner_list in list_of_lists]

    end_values = np.array(end_values) - proc_start_t

    return start_values, end_values



#Match colors with threads (one color per thread) ----------------------------------------------------------------------

def thread_colors(list_of_lists):

    thread_ids = [inner_list[2] for inner_list in list_of_lists]

    color_guide = ['red', 'royalblue', 'gold', 'darkgray', 'forestgreen', 'orangered', 'lightpink', 'teal']


    lookup = dict(zip(pres_uniq_list(thread_ids), color_guide))

    colors = [lookup[number] for number in thread_ids]

    return colors



#Graph legend to match with bars ---------------------------------------------------------------------------------------

def thread_legend(list_of_lists):

    thread_list = [inner_list[3] for inner_list in list_of_lists]

    color_guide = ['red', 'royalblue', 'gold', 'darkgray', 'forestgreen', 'orangered', 'lightpink', 'teal']


    lookup = dict(zip(pres_uniq_list(thread_list), color_guide))

    colors = [lookup[number] for number in thread_list]

    thread_legend = ([Line2D([0], [0], color=c, alpha=0.4, lw=4) for c in pres_uniq_list(colors)])

    names = [str('Thread-')+str(i) for i in range(cpu_workers)]

    return thread_legend, names



#Graph definition using MatPlotLib -------------------------------------------------------------------------------------

def graph_settings(start_t, end_t, title, colors, legend):


    plt.rcParams["font.family"] = "Times New Roman"

    plt.rcParams["font.size"] = 10

    plt.rcParams['axes.axisbelow'] = True

    plt.rcParams['axes.edgecolor'] = 'black'

    plt.rcParams['axes.linewidth'] = 0.8

    plt.rcParams['xtick.color'] = 'black'

    plt.rcParams['ytick.color'] = 'black'

    #plt.rcParams['font.weight']= 'heavy'



    fig = plt.figure(figsize=((12.0/2.54), (7.42/2.54)), facecolor='w', edgecolor='black')  #set (12,7.42) gulden snede but figsize is in inches

    fig, ax = plt.subplots()


    #ax.xaxis.set_major_locator(MultipleLocator(1.000))

    #ax.xaxis.set_minor_locator(AutoMinorLocator(4))

    #ax.yaxis.set_major_locator(MultipleLocator(1.000))

    #ax.yaxis.set_minor_locator(AutoMinorLocator(4))


    ax.set_xlim(-0.2, end_t[nSim-1])

    ax.set_ylim(-1, nSim)

    ax.spines['top'].set_visible(False) #to set color: ax.spines['top'].set_color('green')

    ax.spines['right'].set_visible(False)

    ax.spines['left'].set_smart_bounds(True)

    ax.spines['bottom'].set_smart_bounds(True)


    #ax.tick_params(which='major')

    #ax.tick_params(which='major', length=5)

    #ax.tick_params(which='minor', labelsize=10)

    #ax.tick_params(which='minor', length=2.5, labelsize=10, labelcolor='0.25')

    ax.margins(0.02) #margins in %, default is 5%

    ax.barh(range(len(start_t)), end_t-start_t, left=start_t, color=colors, alpha=0.4, edgecolor="none") #alpha adds vagueness to the bars

    ax.barh(range(len(start_t)), end_t-end_t+0.00001, left=end_t, color=colors, alpha=1, edgecolor="none") #alpha adds vagueness to the bars


    #w = pres_uniq_list(p.get_height() for p in ax.patches)
    #w_fl = float(i) for i in w]

    #ax.plot(end_t, range(nSim), linewidth=0, marker="o", markersize=w[0], color="grey")

    #print(end_t)

    #plt.grid(axis='x', color= 'lightgrey')

    #plt.ylabel("Tasks", fontsize=12, horizontalalignment='left', y=1.02, rotation='horizontal')

    ax.set_title(title, fontsize=14, fontweight="bold", horizontalalignment='center', y=1.04) #set title instead of y-label, bold does not work

    ax.annotate("Tasks", fontsize=12, xy=(0, 1), xytext=(0, 10), xycoords="axes fraction", textcoords="offset points", ha="right", ) #set ha="left" to have it above the axis

    ax.annotate(("Tasks: " + str(nSim) + " - Threads: " + str(cpu_workers)), fontsize=10, fontstyle='italic', xy=(0.5, 1), xytext=(0, 4), xycoords="axes fraction", textcoords="offset points", ha="center", color='gray' ) #set ha="left" to have it above the axis


    ax.set_xlabel("Time [s]", fontsize=12, horizontalalignment='right', x=1.0)
    #ax.set_suptitle(title, fontsize=16, fontweight='bold', y=1.005)

    thread_legend = reversed(legend[0])

    names = reversed(legend[1])



    leg = ax.legend(thread_legend, names, fancybox=True, loc='lower right', fontsize=10, edgecolor=None)

    #plt.legend(frameon=False)

    leg.get_frame().set_facecolor('none')

    leg.get_frame().set_edgecolor('none')


    plt.savefig('P1_5test.pdf', bbox_inches='tight')  #dpi=300 when png , bbox_inches='tight'

    plt.show()

    #plt.figure(figsize=(12, 10))

    #plt.savefig('foo1.pdf', , dpi = 300)

    return None



#Run code for if __name__ == '__main__' that links all functions -------------------------------------------------------

def plot_runtimes(workers, func, args, title):

    proc_start_t = time.time() # we track time from here

    runtimes = multithreading(func, args, workers) #collect task runtimes from function

    #net_runtimes = net_start_t(proc_start_t, runtimes) #extract net_runtimes from runtimes

    start_t, end_t = sep_list_elements(runtimes, proc_start_t) #seperate start_t and end_t

    colors = thread_colors(runtimes) #select thread colors

    legend = thread_legend(runtimes) #define thread legend

    graph_settings(start_t, end_t, title, colors, legend) #settings for the horizontal bar charts



#Tasks to perform ------------------------------------------------------------------------------------------------------

def simulation(i):

    #i = range(nSim)

    start_t = time.time()

    #print(str(i) + ': start')

    a = str(threading.current_thread().ident)

    b = str(threading.current_thread().getName())

    print(str(threading.current_thread().getName()) + ': '+ str(i))

    #print(str(i) + ': finish')

    time.sleep(math.cos(i)+i*0.1+1)

    end_t = time.time()

    return [start_t, end_t, a, b]

    #return a



#Definition ------------------------------------------------------------------------------------------------------------

if __name__ == '__main__':


    plot_runtimes(workers = cpu_workers,

                  func = simulation,

                  args = i,

                  title = "Multi-threading")

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