Python 从matplotlib继承

我想创建自己的plotting类，如下所示，但在使用

plt

模块时，我找不到从

Figure

继承的方法（见下文）。它要么继承自

图

，要么更改

勾选参数

Figure

是一个类，因此我可以继承，但是

plt

不是一个模块？我只是一个初学者试图找到我的方式通过

有人能告诉我它是怎么工作的吗

import matplotlib.pyplot as plt
from matplotlib.figure import Figure

class custom_plot(Figure):
    def __init__(self, *args, **kwargs):
        #fn = os.path.join(os.path.dirname(__file__), 'custom_plot.mplstyle')
        self.fig = plt

    self.fig.tick_params(
        axis='x',  # changes apply to the x-axis
        which='both',  # both major and minor ticks are affected
        bottom='off',  # ticks along the bottom edge are off
        top='off',  # ticks along the top edge are off
        labelbottom='off')  # labels along the bottom edge are off

    # here id like to use a custom style sheet:
    # self.fig.style.use([fn])

    figtitle = kwargs.pop('figtitle', 'no title')
    Figure.__init__(self, *args, **kwargs)
    self.text(0.5, 0.95, figtitle, ha='center')

# Inherits but ignores the tick_params
# fig2 = plt.figure(FigureClass=custom_plot, figtitle='my title')
# ax = fig2.add_subplot(111)
# ax.plot([1, 2, 3],'b')

# No inheritance and no plotting
fig1 = custom_plot()
fig1.fig.plot([1,2,3],'w')

plt.show()

---

好的，同时我自己也找到了一个解决办法。首先，我从

Figure

创建了一个继承的类

custom\u plot

，它与

plt.Figure（FigureClass=custom\u plot，figtitle='my title'）

一起使用。我使用

cplot

收集与

plt

相关的修改，并获得可接受的结果，如下所示：

import os
import matplotlib.pyplot as plt
from matplotlib.figure import Figure

class custom_plot(Figure):
    def __init__(self, *args, **kwargs):

        figtitle = kwargs.pop('figtitle', 'no title')
        super(custom_plot,self).__init__(*args, **kwargs)
        #Figure.__init__(self, *args, **kwargs)
        self.text(0.5, 0.95, figtitle, ha='center')

    def cplot(self,data):

        self.fig = plt
        fn = os.path.join(os.path.dirname(__file__), 'custom_plot.mplstyle')
        self.fig.style.use([fn])
        self.fig.tick_params(
            axis='x',  # changes apply to the x-axis
            which='both',  # both major and minor ticks are affected
            bottom='off',  # ticks along the bottom edge are off
            top='off',  # ticks along the top edge are off
            labelbottom='off')  # labels along the bottom edge are off
        self.fig.plot(data)

fig1 = plt.figure(FigureClass=custom_plot, figtitle='my title')
fig1.cplot([1,2,3])
plt.show()