matplotlib绘图速度很慢

时间:2016-09-07 13:36:39

标签: python matplotlib plot figure figures

我有多个函数,我输入一个数组或dict以及一个路径作为参数,该函数将一个数字保存到特定路径的路径。

尽量保持示例尽可能小,但这里有两个函数:

dict = {"a": {"Germany": 20006.0, "United Kingdom": 20016.571428571428}, "b": {"Chad": 13000.0, "South Africa": 3000000.0},"c":{"Chad": 200061.0, "South Africa": 3000000.0}
    }

一个非常小的示例dict是,但实际的dict包含56000个值:

if __name__ == "__main__":

    plt.close('all')

    print "Starting pattern charting...\n"

    countryChartPatterns(dict,'newPatternCountries.png'))

    valueChartPatterns(dict,'newPatternValues.png'))

在我的剧本中,我打电话给:

import matplotlib.pyplot as plt

注意,我加载了Starting pattern charting...

在PyCharm中运行此脚本时,我在我的控制台中获得了joe = fulfill.receipt joe.response_status = "Accepted" joe.response_comment = "Your order was received by Yo Mama" joe.save ,但这些函数需要超长时间来绘制。

我做错了什么?我应该使用直方图而不是条形图,因为这应该达到给出国家/值出现次数的相同目的吗?我可以以某种方式更改我的GUI后端吗?欢迎任何建议。

1 个答案:

答案 0 :(得分:1)

这是我在上面的评论中提到的测试,结果是:

Elapsed pre-processing = 13.79 s
Elapsed plotting = 0.17 s
Pre-processing / plotting = 83.3654562565

测试脚本:

import matplotlib.pylab as plt
from collections import Counter
from operator import itemgetter
import time

def countryChartPatterns(dict,path):
    # pre-processing -------------------
    t0 = time.time()

    seen_countries = Counter()

    for data in dict.itervalues():
        seen_countries += Counter(data.keys())

    seen_countries = seen_countries.most_common()

    yvals = map(itemgetter(1), seen_countries)
    xvals = map(itemgetter(0), seen_countries)

    dt1 = time.time() - t0
    print("Elapsed pre-processing = {0:.2f} s".format(dt1))

    t0 = time.time()

    # plotting -------------------
    plt.figure()

    countrychart = plt.bar(range(len(seen_countries)), yvals, width=0.9,align='center')
    plt.xticks(range(len(seen_countries)), xvals)

    plt.title('Countries in Pattern Dataset')
    plt.xlabel('Countries in Data')
    plt.ylabel('Occurrences')

    plt.tick_params(axis='both', which='major', labelsize=6)
    plt.tick_params(axis='both', which='minor', labelsize=6)
    plt.tight_layout()

    plt.savefig(path)
    plt.clf()

    dt2 = time.time() - t0 
    print("Elapsed plotting = {0:.2f} s".format(dt2))
    print("Pre-processing / plotting = {}".format(dt1/dt2))

if __name__ == "__main__":
    import random as rd
    import numpy as np

    countries = ["United States of America", "Afghanistan", "Albania", "Algeria", "Andorra", "Angola", "Antigua & Deps", "Argentina", "Armenia", "Australia", "Austria", "Azerbaijan"]

    def item():
        return {rd.choice(countries): np.random.randint(1e3), rd.choice(countries): np.random.randint(1e3)}
    dict = {}
    for i in range(1000000):
        dict[i] = item()

    print("Starting pattern charting...")

    countryChartPatterns(dict,'newPatternCountries.png')