如何使用Matplotlib处理渐近线/不连续性 [英] how to handle an asymptote/discontinuity with Matplotlib

问题描述

在绘制具有不连续点/渐近线/奇异点/任何东西的图形时，是否有任何自动方法来防止Matplotlib跨越断裂"而连接点"? (请参见下面的代码/图像).
我读到Sage的[detect_poles]工具看起来不错，但我真的希望它可以与Matplotlib一起使用.

When plotting a graph with a discontinuity/asymptote/singularity/whatever, is there any automatic way to prevent Matplotlib from 'joining the dots' across the 'break'? (please see code/image below).
I read that Sage has a [detect_poles] facility that looked good, but I really want it to work with Matplotlib.

import matplotlib.pyplot as plt 
import numpy as np
from sympy import sympify, lambdify
from sympy.abc import x

fig = plt.figure(1) 
ax = fig.add_subplot(111) 

# set up axis 
ax.spines['left'].set_position('zero') 
ax.spines['right'].set_color('none') 
ax.spines['bottom'].set_position('zero') 
ax.spines['top'].set_color('none') 
ax.xaxis.set_ticks_position('bottom') 
ax.yaxis.set_ticks_position('left') 

# setup x and y ranges and precision
xx = np.arange(-0.5,5.5,0.01) 

# draw my curve 
myfunction=sympify(1/(x-2))
mylambdifiedfunction=lambdify(x,myfunction,'numpy')
ax.plot(xx, mylambdifiedfunction(xx),zorder=100,linewidth=3,color='red') 

#set bounds 
ax.set_xbound(-1,6)
ax.set_ybound(-4,4) 

plt.show()

推荐答案

这可能不是您想要的优雅解决方案，但是如果只想在大多数情况下获得结果，则可以剪切"绘图的大大小小的值数据分别发送到+∞和-∞. Matplotlib不会绘制这些.当然，您必须注意不要使分辨率太低或削波阈值太高.

This may not be the elegant solution you are looking for, but if just want results for most cases, you can "clip" large and small values of your plotted data to +∞ and -∞ respectively. Matplotlib does not plot these. Of course you have to be careful not to make your resolution too low or your clipping threshold too high.

utol = 100.
ltol = -100.
yy = 1/(xx-2)
yy[yy>utol] = np.inf
yy[yy<ltol] = -np.inf

ax.plot(xx, yy, zorder=100, linewidth=3, color='red') 

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