5

我想通过多处理模块为许多图形加速 matplotlib.savefig()，并尝试对并行和序列之间的性能进行基准测试。

以下是代码：

# -*- coding: utf-8 -*-
"""
Compare the time of matplotlib savefig() in parallel and sequence
"""

import numpy as np
import matplotlib.pyplot as plt
import multiprocessing
import time


def gen_fig_list(n):
    ''' generate a list to contain n demo scatter figure object '''
    plt.ioff()
    fig_list = []
    for i in range(n):
        plt.figure();
        dt = np.random.randn(5, 4);
        fig = plt.scatter(dt[:,0], dt[:,1], s=abs(dt[:,2]*1000), c=abs(dt[:,3]*100)).get_figure()
        fig.FM_figname = "img"+str(i)
        fig_list.append(fig)
    plt.ion()
    return fig_list


def savefig_worker(fig, img_type, folder):
    file_name = folder+"\\"+fig.FM_figname+"."+img_type
    fig.savefig(file_name, format=img_type, dpi=fig.dpi)
    return file_name


def parallel_savefig(fig_list, folder):
    proclist = []
    for fig in fig_list:
        print fig.FM_figname,
        p = multiprocessing.Process(target=savefig_worker, args=(fig, 'png', folder)) # cause error
        proclist.append(p)
        p.start()

    for i in proclist:
        i.join()



if __name__ == '__main__':
    folder_1, folder_2 = 'Z:\\A1', 'Z:\\A2'
    fig_list = gen_fig_list(10)

    t1 = time.time()
    parallel_savefig(fig_list,folder_1)
    t2 = time.time()
    print '\nMulprocessing time    : %0.3f'%((t2-t1))

    t3 = time.time()
    for fig in fig_list:
        savefig_worker(fig, 'png', folder_2)
    t4 = time.time()
    print 'Non_Mulprocessing time: %0.3f'%((t4-t3))

我遇到"This application has requested the Runtime to terminate it in an unusual way. Please contact the application's support team for more information."了由p = multiprocessing.Process(target=savefig_worker, args=(fig, 'png', folder)).

为什么 ？以及如何解决？

（Windows XP + Python：2.6.1 + Numpy：1.6.2 + Matplotlib：1.2.0）

编辑：（在 python 2.7.3 上添加错误消息）

在 python 2.7.3 的 IDLE 上运行时，它会给出以下错误消息：

>>> 
img0

Traceback (most recent call last):
  File "C:\Documents and Settings\Administrator\desktop\mulsavefig_pilot.py", line 61, in <module>
    proc.start()
  File "d:\Python27\lib\multiprocessing\process.py", line 130, in start

  File "d:\Python27\lib\pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "d:\Python27\lib\pickle.py", line 748, in save_global
    (obj, module, name))
PicklingError: Can't pickle <function notify_axes_change at 0x029F5030>: it's not found as matplotlib.backends.backend_qt4.notify_axes_change

编辑：（我的解决方案演示）

受Matplotlib 启发：在多个线程中同时绘图

# -*- coding: utf-8 -*-
"""
Compare the time of matplotlib savefig() in parallel and sequence
"""

import numpy as np
import matplotlib.pyplot as plt
import multiprocessing
import time


def gen_data(fig_qty, bubble_qty):
    ''' generate data for fig drawing '''
    dt = np.random.randn(fig_qty, bubble_qty, 4)
    return dt


def parallel_savefig(draw_data, folder):
    ''' prepare data and pass to worker '''

    pool = multiprocessing.Pool()

    fig_qty = len(draw_data)
    fig_para = zip(range(fig_qty), draw_data, [folder]*fig_qty)

    pool.map(fig_draw_save_worker, fig_para)
    return None


def fig_draw_save_worker(args):
    seq, dt, folder = args
    plt.figure()
    fig = plt.scatter(dt[:,0], dt[:,1], s=abs(dt[:,2]*1000), c=abs(dt[:,3]*100), alpha=0.7).get_figure()
    plt.title('Plot of a scatter of %i' % seq)
    fig.savefig(folder+"\\"+'fig_%02i.png' % seq)
    plt.close()
    return None


if __name__ == '__main__':
    folder_1, folder_2 = 'A1', 'A2'
    fig_qty, bubble_qty =  500, 100
    draw_data = gen_data(fig_qty, bubble_qty)

    print 'Mulprocessing  ...   ',
    t1 = time.time()
    parallel_savefig(draw_data, folder_1)
    t2 = time.time()
    print 'Time : %0.3f'%((t2-t1))

    print 'Non_Mulprocessing .. ', 
    t3 = time.time()
    for para in zip(range(fig_qty), draw_data, [folder_2]*fig_qty):
        fig_draw_save_worker(para)
    t4 = time.time()
    print 'Time : %0.3f'%((t4-t3))

    print 'Speed Up: %0.1fx'%(((t4-t3)/(t2-t1)))
4

2 回答 2

9

您可以尝试将所有 matplotlib 代码（包括导入）移动到一个函数中。

  1. 确保您的代码顶部没有 import matplotlib 或 import matplotlib.pyplot as plt。

  2. 创建一个执行所有 matplotlib 的函数，包括导入。

例子：

import numpy as np
from multiprocessing import pool

def graphing_function(graph_data):
    import matplotlib.pyplot as plt
    plt.figure()
    plt.hist(graph_data.data)
    plt.savefig(graph_data.filename)
    plt.close()
    return

pool = Pool(4)
pool.map(graphing_function, data_list)
于 2016-10-13T22:34:19.983 回答
3

这并不是一个真正的错误，而是更多的限制。

解释在错误消息的最后一行：

PicklingError: Can't pickle <function notify_axes_change at 0x029F5030>: it's not found as matplotlib.backends.backend_qt4.notify_axes_change

它告诉您图形对象的元素不能被腌制，这就是MultiProcess在进程之间传递数据的方式。对象在主要过程中被腌制，作为腌制运输，然后在另一侧重新构建。即使您解决了这个确切的问题（可能通过使用不同的后端，或剥离有问题的功能（这可能会以其他方式破坏事情））我很确定 , 或对象的核心部分Figure不能Axes被Canvas腌制。

正如@bigbug 所指出的，如何解决这个限制的一个例子，Matplotlib: 同时在多个线程中绘图。基本思想是将整个绘图例程推送到子流程，因此您只推送numpy数组和可能跨流程边界的一些配置信息。

于 2013-03-22T19:28:54.323 回答