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- # View more python tutorials on my Youtube and Youku channel!!!
- # Youtube video tutorial: https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg
- # Youku video tutorial: http://i.youku.com/pythontutorial
- # 14 - 3d
- """
- Please note, this script is for python3+.
- If you are using python2+, please modify it accordingly.
- Tutorial reference:
- http://www.python-course.eu/matplotlib_multiple_figures.php
- """
- import numpy as np
- import matplotlib.pyplot as plt
- from mpl_toolkits.mplot3d import Axes3D
- fig = plt.figure()
- ax = Axes3D(fig)
- # X, Y value
- X = np.arange(-4, 4, 0.25)
- Y = np.arange(-4, 4, 0.25)
- X, Y = np.meshgrid(X, Y)
- R = np.sqrt(X ** 2 + Y ** 2)
- # height value
- Z = np.sin(R)
- ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=plt.get_cmap('rainbow'))
- """
- ============= ================================================
- Argument Description
- ============= ================================================
- *X*, *Y*, *Z* Data values as 2D arrays
- *rstride* Array row stride (step size), defaults to 10
- *cstride* Array column stride (step size), defaults to 10
- *color* Color of the surface patches
- *cmap* A colormap for the surface patches.
- *facecolors* Face colors for the individual patches
- *norm* An instance of Normalize to map values to colors
- *vmin* Minimum value to map
- *vmax* Maximum value to map
- *shade* Whether to shade the facecolors
- ============= ================================================
- """
- # I think this is different from plt12_contours
- ax.contourf(X, Y, Z, zdir='z', offset=-2, cmap=plt.get_cmap('rainbow'))
- """
- ========== ================================================
- Argument Description
- ========== ================================================
- *X*, *Y*, Data values as numpy.arrays
- *Z*
- *zdir* The direction to use: x, y or z (default)
- *offset* If specified plot a projection of the filled contour
- on this position in plane normal to zdir
- ========== ================================================
- """
- ax.set_zlim(-2, 2)
- plt.show()
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