how to handle an asymptote/discontinuity
equation, matplotlib, numpy, python, sympy
Solution
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')
Problem
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() ```