当绘制具有不连续性/渐近线/奇异性/任何东西的图形时，是否有任何自动方法可以防止 Matplotlib 在“断点”上“连接点”？ （请参阅下面的代码/图像）。
我读到 Sage 有一个看起来不错的 [detect_poles] 工具，但我真的希望它能够与 Matplotlib 一起使用。
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()
通过使用屏蔽数组您可以避免绘制曲线的选定区域。
要消除 x=2 处的奇点：
import matplotlib.numerix.ma as M # for older versions, prior to .98
#import numpy.ma as M # for newer versions of matplotlib
from pylab import *
figure()
xx = np.arange(-0.5,5.5,0.01)
vals = 1/(xx-2)
vals = M.array(vals)
mvals = M.masked_where(xx==2, vals)
subplot(121)
plot(xx, mvals, linewidth=3, color='red')
xlim(-1,6)
ylim(-5,5)
这条简单的曲线可能更清楚地说明了哪些点被排除在外：
xx = np.arange(0,6,.2)
vals = M.array(xx)
mvals = M.masked_where(vals%2==0, vals)
subplot(122)
plot(xx, mvals, color='b', linewidth=3)
plot(xx, vals, 'rx')
show()
