Surface Plot of Test Function
Finally, we may want to create a three-dimensional plot of the objective function to get a fuller idea of the curvature of the function.
This can be achieved using the plot_surface() Matplotlib function, that, like the contour plot, takes the mesh grid and function evaluation directly.
create a surface plot with the jet color scheme
figure = pyplot.figure()
axis = figure.gca(projection=‘3d’)
axis.plot_surface(x, y, results, cmap=‘jet’)
The complete example of creating a surface plot is listed below.
surface plot for 2d objective function
from numpy import arange
from numpy import meshgrid
from matplotlib import pyplot
from mpl_toolkits.mplot3d import Axes3D
objective function
def objective(x, y):
return x2.0 + y2.0
define range for input
r_min, r_max = -5.0, 5.0
sample input range uniformly at 0.1 increments
xaxis = arange(r_min, r_max, 0.1)
yaxis = arange(r_min, r_max, 0.1)
create a mesh from the axis
x, y = meshgrid(xaxis, yaxis)
compute targets
results = objective(x, y)
create a surface plot with the jet color scheme
figure = pyplot.figure()
axis = figure.gca(projection=‘3d’)
axis.plot_surface(x, y, results, cmap=‘jet’)
show the plot
pyplot.show()
Running the example creates a three-dimensional surface plot of the objective function.