import matplotlib
import numpy as np
import matplotlib.cm as cm
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
matplotlib.rcParams['xtick.direction'] = 'out'
matplotlib.rcParams['ytick.direction'] = 'out'
%matplotlib inline
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)
# Create a simple contour plot with labels using default colors. The
# inline argument to clabel will control whether the labels are draw
# over the line segments of the contour, removing the lines beneath
# the label
plt.figure()
CS = plt.contour(x, y, Z)
plt.clabel(CS, inline=1, fontsize=10)
plt.title('Simplest default with labels')
<matplotlib.text.Text at 0x7fcfeedc1310>
Z.shape, x.shape, y.shape
((160, 240), (240,), (160,))
Z
array([[-0.0023928 , -0.00257835, -0.00277656, ..., -0.00298812, -0.00277655, -0.00257834], [-0.00251469, -0.0027097 , -0.00291801, ..., -0.00314034, -0.00291799, -0.00270968], [-0.00264115, -0.00284596, -0.00306474, ..., -0.00329825, -0.00306472, -0.00284594], ..., [ 0.00817778, 0.00845885, 0.00874442, ..., 0.16478335, 0.16144524, 0.15812319], [ 0.00732895, 0.00757579, 0.00782611, ..., 0.14989083, 0.14686179, 0.14384672], [ 0.00654051, 0.00675572, 0.00697347, ..., 0.13599164, 0.1332508 , 0.13052201]])