Adding extra contour lines using matplotlib 2D contour plotting

Question

I am creating a two-dimensional contour plot with matplotlib. Using the documentation provided http://matplotlib.org/examples/pylab_examples/contour_demo.html, such a contou

Answer 1

To draw isolines at specified level values, set the levels parameter:

levels = np.arange(-1.0,1.5,0.25)
CS = plt.contour(X, Y, Z, levels=levels)

---

import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt

delta = 0.025
x = np.arange(-3.0, 3.0, delta)
y = np.arange(-2.0, 2.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
# difference of Gaussians
Z = 10.0 * (Z2 - Z1)

plt.figure()
levels = np.arange(-1.0,1.5,0.25)
CS = plt.contour(X, Y, Z, levels=levels)
plt.clabel(CS, inline=1, fontsize=10)
plt.title('levels = {}'.format(levels.tolist()))
plt.show()

The sixth figure here uses this method to draw isolines at levels = np.arange(-1.2, 1.6, 0.2).

---

To zoom in, set the x limits and y limits of the desired region:

plt.xlim(0, 3)
plt.ylim(0, 2)

and to draw, say, 24 automatically-chosen levels, use

CS = plt.contour(X, Y, Z, 24)

---

For example,

import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt

delta = 0.025
x = np.arange(-3.0, 3.0, delta)
y = np.arange(-2.0, 2.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
# difference of Gaussians
Z = 10.0 * (Z2 - Z1)

plt.figure()
N = 24
CS = plt.contour(X, Y, Z, N)
plt.clabel(CS, inline=1, fontsize=10)
plt.title('{} levels'.format(N))
plt.xlim(0, 3)
plt.ylim(0, 2)
plt.show()

The third figure here uses this method to draw 6 isolines.