如何将旋转的子图叠加到另一个子图上？

Question

我想发布如图所示的绘图配置：

接下来的参数必须是可变的：

1. 子图原点位置
2. 子图旋转角度
3. 子图大小

我尝试使用 mpl_toolkits.axes_grid1.inset_locator.inset_axes 找到解决方案（见下文），但我无法更改上面列表中参数 1,2 的值。请帮我找到解决方案。

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.axes_grid1.inset_locator import inset_axes

x = np.linspace(0,100,100)
y = np.linspace(0,100,100)

fig, ax = plt.subplots(1, 1, figsize=[8, 8])
axins = inset_axes(ax, width='40%', height='40%', loc='center')
axins.set_xlim(0,80)
axins.set_ylim(0,80)
axins.plot(x,y)

plt.show()

Answer 1

基于使用浮动轴（如这个答案）和示例这里，我有以下解决方案：

import numpy as np

import matplotlib.pyplot as plt
from matplotlib.transforms import Affine2D
import mpl_toolkits.axisartist.floating_axes as floating_axes
from mpl_toolkits.axisartist.grid_finder import MaxNLocator

# create a figure and original axis
fig, ax_orig = plt.subplots(figsize=(7, 7))

# data for plotting in subplot
subplot_xdata = np.linspace(0, 80, 100)
subplot_ydata = np.linspace(0, 80, 100)

# extents of the subplot (based on data)
plot_extents = (
    subplot_xdata[0],
    subplot_xdata[-1],
    subplot_ydata[0],
    subplot_ydata[-1],
)

# create the floating subplot
rotation = 145  # rotation of subplot (degrees)
transform = Affine2D().rotate_deg(rotation)  # transform with rotation applied

# set the subplot grid to allow ticks at multiples of 5 or 10
grid_locator = MaxNLocator(steps=[5, 10])

helper = floating_axes.GridHelperCurveLinear(
    transform,
    plot_extents,
    grid_locator1=grid_locator,
    grid_locator2=grid_locator,
)
ax = floating_axes.FloatingSubplot(fig, 111, grid_helper=helper)

# position and scale the subplot (play about with these)
width = 0.35  # width relative to original axis
height = 0.35  # height relative to original axis
xloc = 0.4  # x-location (in axis coordinates between 0-1) of bottom left corner of (unrotated) subplot
yloc = 0.5  # y-location of bottom left corner of (unrotated) subplot
ax.set_position((xloc, yloc, width, height))

# get auxilary axis to for actually plotting the subplot data
aux_ax = ax.get_aux_axes(transform)
aux_ax.plot(subplot_xdata, subplot_ydata)

# add subplot to the figure
fig.add_subplot(ax)

# plot something on the original axes
ax_orig.plot(np.linspace(0, 2, 100), np.linspace(0, 2, 100))

请注意，此解决方案要求您指定子图的 x-y 范围。