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This example generates a multivariate polynomial using the MPoly class. The polynomial is shown in a 3-D surface plot. plot.
MPoly
# This import registers the 3D projection, but is otherwise unused. from mpl_toolkits.mplot3d import Axes3D # noqa: F401 unused import import lmlib as lm import matplotlib.pyplot as plt import numpy as np # creating a multivariate polynomial with two variables of order 2 mpoly = lm.MPoly(coefs=([0.1, -0.3, -0.1, 0.1],), expos=([0, 2], [0, 2])) # defining the variables for evaluation x = np.arange(-3, 3, 0.1) y = np.arange(-3, 3, 0.1) X, Y = np.meshgrid(x, y) z = mpoly.eval((X, Y)) # create figure and an axes for a 3d plot fig = plt.figure() ax = fig.add_subplot(projection='3d') # surface plot of the multivariate polynomial ax.plot_surface(X, Y, z, cmap="twilight") plt.show()
Total running time of the script: ( 0 minutes 0.471 seconds)
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