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Tri-Surface Plot in Python using Matplotlib
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Matplotlib was introduced keeping in mind, only two-dimensional plotting. But at the time when the release of 1.0 occurred, the 3d utilities were developed upon the 2d and thus, we have 3d implementation of data available today! The 3d plots are enabled by importing themplot3d toolkit. Let's look at a 3d contour diagram of a 3d cosine function. The code is attached for reference.
Function ArgumentsDescription
meshgridFunction of numpy used to create a rectangular grid out of two given one-dimensional arrays representing the Cartesian indexing or Matrix indexing
plt.axes()To create object of the axis
ax.contour3DTo form the contour
ax.set_xlabelTo label the X-axis
ax.set_titleTo give a title to the plot
Example 1:Python3
frommpl_toolkitsimportmplot3dimportnumpyasnpimportmatplotlib.pyplotaspltfrommatplotlibimportcmimportmathx=[iforiinrange(0,200,100)]y=[iforiinrange(0,200,100)]X,Y=np.meshgrid(x,y)Z=[]foriinx:t=[]forjiny:t.append(math.cos(math.sqrt(i*2+j*2)))Z.append(t)fig=plt.figure()ax=plt.axes(projection='3d')ax.contour3D(X,Y,Z,50,cmap=cm.cool)ax.set_xlabel('a')ax.set_ylabel('b')ax.set_zlabel('c')ax.set_title('3D contour for cosine')plt.show()
Output:3D Contour Plotting Example 2: Let's look at another 3d diagram for better understanding of the concept. This time, of a 3d tan function.Python3
frommpl_toolkitsimportmplot3dimportnumpyasnpimportmatplotlib.pyplotaspltfrommatplotlibimportcmimportmathx=[iforiinrange(0,200,100)]y=[iforiinrange(0,200,100)]X,Y=np.meshgrid(x,y)Z=[]foriinx:t=[]forjiny:t.append(math.tan(math.sqrt(i*2+j*2)))Z.append(t)fig=plt.figure()ax=plt.axes(projection='3d')ax.contour3D(X,Y,Z,50,cmap=cm.cool)ax.set_xlabel('a')ax.set_ylabel('b')ax.set_zlabel('c')ax.set_title('3D contour for tan')plt.show()
Output:3D Contour Plotting

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