matplotlib:在函数中绘制图，然后将每个图添加到单个子图中 [英] matplotlib: make plots in functions and then add each to a single subplot figure

问题描述

我一直无法找到解决方案..假设我定义了一些绘图函数，这样我就不必每次制作类似的绘图时都复制粘贴大量代码......

I haven't been able to find a solution to this.. Say I define some plotting function so that I don't have to copy-paste tons of code every time I make similar plots...

我想要做的是使用此功能分别创建几个不同的图，然后将它们作为子图组合成一个图.这有可能吗?我尝试了以下操作，但它只返回空白:

What I'd like to do is use this function to create a few different plots individually and then put them together as subplots into one figure. Is this even possible? I've tried the following but it just returns blanks:

import numpy as np
import matplotlib.pyplot as plt

# function to make boxplots
def make_boxplots(box_data):

    fig, ax = plt.subplots()

    box = ax.boxplot(box_data)

    #plt.show()

    return ax

# make some data:
data_1 = np.random.normal(0,1,500)
data_2 = np.random.normal(0,1.1,500)

# plot it
box1 = make_boxplots(box_data=data_1)
box2 = make_boxplots(box_data=data_2)

plt.close('all')

fig, ax = plt.subplots(2)

ax[0] = box1
ax[1] = box2

plt.show()

推荐答案

我倾向于使用以下模板

def plot_something(data, ax=None, **kwargs):
    ax = ax or plt.gca()
    # Do some cool data transformations...
    return ax.boxplot(data, **kwargs)

然后您可以通过简单地调用 plot_something(my_data) 来试验您的绘图功能，并且您可以像这样指定要使用的轴.

Then you can experiment with your plotting function by simply calling plot_something(my_data) and you can specify which axes to use like so.

fig, (ax1, ax2) = plt.subplots(2)
plot_something(data1, ax1, color='blue')
plot_something(data2, ax2, color='red')

添加 kwargs 允许您将任意参数传递给绘图功能，例如标签，线条样式或颜色.

Adding the kwargs allows you to pass in arbitrary parameters to the plotting function such as labels, line styles, or colours.

ax = ax或plt.gca()行使用您指定的轴或从matplotlib获取当前轴(如果尚未创建，则可能是新轴).

The line ax = ax or plt.gca() uses the axes you have specified or gets the current axes from matplotlib (which may be new axes if you haven't created any yet).

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