将Matplotlib数据单位转换为归一化单位 [英] Convert matplotlib data units to normalized units

问题描述

有人知道如何将matplotlib数据单位转换为标准化单位吗?

Does anyone know how to convert matplotlib data units into normalized units?

我需要它的原因是我需要在另一个图的顶部创建一个子图. 以及默认语法:

The reason that I need it is that I need to create a subplot on top of another plot. And the default syntax:

plt.axes([0.1,0.1,0.3,0.3])

需要归一化的坐标，但是我想使用数据坐标:

requires normalized coordinates, but I want to use the data coordinates:

例如此代码:

  plt.plot([0,2],[2,4]);
  plt.axes([0.3,.3,0.4,.4])

产生此:

但我希望能够使用子图的数据坐标来定义子图的位置 ，例如[0.7,2.5,1.7,3.5].我试图摆弄axes.transData，axes.get_transform()之类的东西，但是没有成功找到合适的函数来完成工作

But I'd like to be able to define the location of the subplot using the data coordinates of it , something like [0.7,2.5,1.7,3.5]. I've tried to fiddle with axes.transData, axes.get_transform() and the like but didn't succeed to find the right function to do the job

推荐答案

这里是一种方法:

内部axes打印在0.5, 2.5, 1.0, 0.3上(在外部axes坐标中)

inner axes printed at 0.5, 2.5, 1.0, 0.3 (in outer axes coords)

您基本上需要进行两种转换-一种从src-coords到display，另一种从display到dest-coord.从文档看来，似乎没有直接的方法:
http://matplotlib.org/users/transforms_tutorial.html

You basically need two transformations -- one from src-coords to display, and one from display to dest-coord. From the docs there seems to be no direct way:
http://matplotlib.org/users/transforms_tutorial.html

bb_data = Bbox.from_bounds(0.5, 2.5, 1.0, 0.3)
disp_coords = ax.transData.transform(bb_data)
fig_coords = fig.transFigure.inverted().transform(disp_coords)

ax和fig都带有变压器-显示坐标！
如果对它们调用inverted，则会得到一个反方向的变压器.

ax and fig both carry transformer with them -- to display-coords!
If you call inverted on them, you get an transformer for the inverse direction.

这是上面示例的完整代码:

Here's the full code for the above example:

import matplotlib.pyplot as plt
from matplotlib.transforms import Bbox

plt.plot([0,2], [2,4])
fig = plt.gcf()
ax = plt.gca()

bb_data = Bbox.from_bounds(0.5, 2.5, 1.0, 0.3)
disp_coords = ax.transData.transform(bb_data)
fig_coords = fig.transFigure.inverted().transform(disp_coords)

fig.add_axes(Bbox(fig_coords))

plt.show()

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