我创建了Django视图“graph”，目的是显示从matplotlib.pyplot模块。我编写了我的函数plot\u bubbles（返回amatplotlib.figure.figure对象）在脚本数据中_分析.py导入到视图.py脚本。在

Tkinter只能在主线程上运行，我的网页在我第一次请求时按预期工作，但在刷新或再次请求时它不显示图像。我的理解是，当视图再次被请求时，Django在一个新线程上操作代码。在from django.http import HttpResponse

from . import data_analysis

import Queue

import threading

q = Queue.Queue()

def graph(request):

parties = ["Conservative Party", "Labour Party", "Green Party", "UKIP"]

def from_other_thread(graph_function):

q.put(graph_function)

def main_thread_execute():

callback = q.get()

fig = callback

return fig

def grapher(arguments, area_variable):

data_analysis.plt.close('all')

from_other_thread(data_analysis.plot_bubbles(arguments, area_variable))

t = threading.Thread(target = grapher, args=(parties, data_analysis.all_data['2015 Pay']))

t.start()

t.join()

fig = main_thread_execute()

response = HttpResponse(content_type='image/png')

fig.savefig(response, format='png')

return response

其目的是在主线程中运行函数，以便Tkinter可以实际工作并创建图像我希望每次请求url时都创建图像，因为我将允许用户通过表单选择他想要可视化的变量，并将它们作为plot_bubbles函数的参数传递。在

我是django的初学者，从未在代码中使用过多线程，感谢您阅读本文。如有任何关于您的解决方案的解释，我们将不胜感激。在

编辑

不一定需要穿线。问题源于我的数据分析脚本生成绘图的方式。尤其是方法调用的代码matplotlib.pyplot.subplothttp://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.subplots生成一个带有4个轴对象的图形

^{pr2}$

这似乎导致Tkinter无法在主循环上运行，我还没有完全理解原因。这就是代码现在的样子#!/usr/bin/python

# -*- coding: utf-8 -*-

import pandas as pd

import numpy as np

from pandas import Series, DataFrame

from pylab import figure, axes, plot, title, subplots

import statsmodels.api as sm

from sqlalchemy import create_engine

from matplotlib.backends.backend_agg import FigureCanvasAgg

import matplotlib

# Load data from database into dataframe

engine = create_engine("postgresql://user_name:password@localhost:5432/brexit")

all_data = pd.read_sql('''SELECT * FROM records;''', engine, index_col='Borough')

# Bubble Plot function creation

colors = np.random.rand(len(all_data.index))

area = []

def plot_bubbles(arguments, area_variable, space=0):

ah = iter(arguments)

eh = iter(arguments)

ih = iter(arguments)

kh = iter(arguments)

th = iter(arguments)

zh = iter(arguments)

mh = iter(arguments)

fig = figure(figsize=(30, 25))

ax1 = fig.add_subplot(2,2,1)

ax2 = fig.add_subplot(2,2,2)

ax3 = fig.add_subplot(2,2,3)

ax4 = fig.add_subplot(2,2,4)

collection = [ax1, ax2, ax3, ax4]

for x in area_variable:

#want the bubbles to have an average area of 40, add a factor to increase the variability in size

factor = ((x-area_variable.mean())**2/400)

area.append(factor*x*(40/area_variable.mean()))

for ax in collection:

orient = all_data[ah.next()]

ax.set_ylabel('Leave %')

ax.set_xlim([max(0, all_data[zh.next()].min()-all_data[mh.next()].min()/3),

all_data[ih.next()].max()+all_data[th.next()].max()/7])

results = sm.OLS(all_data['Leave votes'], sm.add_constant(orient)).fit()

X_plot = np.linspace(orient.min()-0.05, orient.max(), 100)

ax.plot(X_plot, X_plot*results.params[1] + results.params[0], )

for label, ori, leave in zip(all_data.index, orient, all_data['Leave votes']):

ax.annotate(label, xy=(ori, leave), xytext=(ori, leave+0.05),

arrowprops={'facecolor':'black', 'connectionstyle':'arc3,rad=0.3', 'arrowstyle':'simple'})

ax.scatter(orient, all_data['Leave votes'], s=area, c=colors, alpha=0.6)

ax.set_title(kh.next())

fig.subplots_adjust(hspace=space, wspace=space)

return fig

随着图形和轴创建方式的改变，问题得到了解决。如果有人能解释一下为什么会这样，那就很有趣了。在