matplotlib Axes.plot()与pyplot.plot() [英] matplotlib Axes.plot() vs pyplot.plot()

问题描述

Axes.plot()和pyplot.plot()方法之间有什么区别?一个人是否将另一个人用作子例程?

What is the difference between the Axes.plot() and pyplot.plot() methods? Does one use another as a subroutine?

看来我的绘图选项是

line = plt.plot(data)

或

ax = plt.axes()
line = ax.plot(data)

甚至

fig = plt.figure()
ax = fig.add_axes([0,0,1,1])
line = ax.plot(data)

在某些情况下，最好使用一种方法而不是另一种方法吗?

Are there situations where it is preferable to use one over the other?

推荐答案

对于绘制单个图，最佳实践可能是

For drawing a single plot, the best practice is probably

fig = plt.figure()
plt.plot(data)
fig.show()

现在，让我们看一下问题中的3个示例，并说明它们的作用.

Now, lets take a look in to 3 examples from the queston and explain what they do.

1. 获取当前图形和轴(如果不存在，将创建一个新的图形和轴)并绘制到其中.

1. Takes the current figure and axes (if none exists it will create a new one) and plot into them.

line = plt.plot(data)

在您的情况下，行为与之前相同，但明确说明了 绘图轴.

In your case, the behavior is same as before with explicitly stating the axes for plot.

ax = plt.axes()
line = ax.plot(data)

如果要绘制到多个轴(可能在一个图中)，则必须使用这种使用ax.plot(...)的方法.例如，当使用子图.

This approach of using ax.plot(...) is a must, if you want to plot into multiple axes (possibly in one figure). For example when using a subplots.

显式创建新图形-您不会在前一个图形上添加任何内容. 明确创建具有给定矩形形状的新轴，其余的是 与2相同.

Explicitly creates new figure - you will not add anything to previous one. Explicitly creates a new axes with given rectangle shape and the rest is the same as with 2.

fig = plt.figure()
ax = fig.add_axes([0,0,1,1])
line = ax.plot(data)

使用figure.add_axes的可能问题是它可能会添加新的轴对象 到该图，它将覆盖第一个(或其他).如果发生这种情况 请求的大小与现有大小不匹配.

possible problem using figure.add_axes is that it may add a new axes object to the figure, which will overlay the first one (or others). This happens if the requested size does not match the existing ones.

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