Python 如何在matplotlib中使用注释环绕曲线？

我有一个python代码，它可以生成下面的图。如图所示，我想用椭圆对曲线进行注释

注意：该图是使用MATLAB生成的，我无法在python matplotlib中完成。

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谢谢。

您可以尝试以下方法来定位椭圆：选择一个x坐标，并计算椭圆的高度，以将提供的函数列表包含在该坐标处

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Ellipse

x = np.linspace(1,10,1000)

flogs = [lambda x, a=a: np.log(a * x) for a in range(1,4)]
fexps = [lambda x, a=a: np.exp(a * x) for a in [0.18,0.2]]
funcs = flogs + fexps

fig = plt.figure()
ax = fig.add_subplot(111)

for func in funcs:
    ax.plot(x,func(x))


def add_ellipse(funcs, x):
    # the y-coordinate of the center of our ellipse:
    y = np.mean([funcs[i](x) for i in range(len(funcs))])
    # fix the width of the ellipse to this value:
    w = 0.4
    # find the height of the ellipse needed, and pad a bit:
    h = np.ptp([funcs[i](x) for i in range(len(funcs))]) * 1.5
    e = Ellipse(xy=(x,y), width=w, height=h, angle=0)
    e.set_facecolor('none')
    ax.add_artist(e)

add_ellipse(fexps, 8.5)
add_ellipse(flogs, 8)

plt.show()

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您可以尝试以下方法来定位椭圆：选择一个x坐标并计算椭圆的高度，该高度是在该坐标处封闭提供的函数列表所必需的

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Ellipse

x = np.linspace(1,10,1000)

flogs = [lambda x, a=a: np.log(a * x) for a in range(1,4)]
fexps = [lambda x, a=a: np.exp(a * x) for a in [0.18,0.2]]
funcs = flogs + fexps

fig = plt.figure()
ax = fig.add_subplot(111)

for func in funcs:
    ax.plot(x,func(x))


def add_ellipse(funcs, x):
    # the y-coordinate of the center of our ellipse:
    y = np.mean([funcs[i](x) for i in range(len(funcs))])
    # fix the width of the ellipse to this value:
    w = 0.4
    # find the height of the ellipse needed, and pad a bit:
    h = np.ptp([funcs[i](x) for i in range(len(funcs))]) * 1.5
    e = Ellipse(xy=(x,y), width=w, height=h, angle=0)
    e.set_facecolor('none')
    ax.add_artist(e)

add_ellipse(fexps, 8.5)
add_ellipse(flogs, 8)

plt.show()

这是您的解决方案：这是您的解决方案：