The code example below provides a way to scale each axis relative to the others. However, to do so you need to modify the Axes3D.get_proj function. Below is an example based on the example provided by matplot lib: http://matplotlib.org/1.4.0/mpl_toolkits/mplot3d/tutorial.html#line-plots (There is a shorter version at the end of this answer) from mpl_toolkits.mplot3d.axes3d import Axes3D from … Read more
I think you’ve almost got it. Is this what you want? from mpl_toolkits.mplot3d import Axes3D from mpl_toolkits.mplot3d.art3d import Poly3DCollection import matplotlib.pyplot as plt fig = plt.figure() ax = Axes3D(fig, auto_add_to_figure=False) fig.add_axes(ax) x = [0,1,1,0] y = [0,0,1,1] z = [0,1,0,1] verts = [list(zip(x,y,z))] ax.add_collection3d(Poly3DCollection(verts)) plt.show() You might also be interested in art3d.pathpatch_2d_to_3d.
Maybe easier via ax.text(…): from matplotlib import pyplot from mpl_toolkits.mplot3d import Axes3D from numpy.random import rand from pylab import figure m=rand(3,3) # m is an array of (x,y,z) coordinate triplets fig = figure() ax = fig.add_subplot(projection=’3d’) for i in range(len(m)): #plot each point + it’s index as text above ax.scatter(m[i,0],m[i,1],m[i,2],color=”b”) ax.text(m[i,0],m[i,1],m[i,2], ‘%s’ % (str(i)), size=20, … Read more
I like some of the previously posted solutions, but they do have the drawback that you need to keep track of the ranges and means over all your data. This could be cumbersome if you have multiple data sets that will be plotted together. To fix this, I made use of the ax.get_[xyz]lim3d() methods and … Read more
Change to: ax.plot_wireframe(T, z, abs(U), cstride=1000) and call: drawPropagation(1.0, 1.0, numpy.linspace(-2, 2, 10)) will create the following graph: If you need the curve been filled with white color: import numpy from mpl_toolkits.mplot3d import Axes3D from matplotlib import pyplot from matplotlib.collections import PolyCollection def drawPropagation(beta2, C, z): “”” beta2 in ps / km C is chirp … Read more
Abritrary points can be supplied as 1D arrays to matplotlib.Axes3D.plot_trisurf. It doesn’t matter whether they follow a specific structure. Other methods which would depend on the structure of the data would be Interpolate the points on a regular rectangular grid. This can be accomplished using scipy.interpolate.griddata. See example here Reshape the input arrays such that … Read more
The matplotlib.offsetbox does not work in 3D. As a workaround one may use a 2D axes overlaying the 3D plot and place the image annotation to that 2D axes at the position which corresponds to the position in the 3D axes. To calculate the coordinates of those positions, one may refer to How to transform … Read more
There seems to be no obvious way to do this at the moment. Setting the spines when the axis projection is 3D is not implemented. However, there is a small hack here. The ax.spines setting is for 2D rendering. When you set projection=3d in the initialization of the figure, certain 2D properties (like ax.spines, etc.) … Read more
I share your frustration. I worked on it for a good half hour and got nowhere. The docs say set_xlabel takes an arg labelpad but I get an error (AttributeError: Unknown property labelpad)! Setting it after the fact doesn’t do anything, on xaxis or w_xaxis. Here’s a crude workaround: import matplotlib matplotlib.use(“TKAGG”) import matplotlib.pyplot as … Read more
First off, I think mplot3D worked a bit differently in matplotlib version 0.99 than it does in the current version of matplotlib. Which version are you using? (Try running: python -c ‘import matplotlib; print matplotlib.”__version__”) I’m guessing you’re running version 0.99, in which case you’ll need to either use a slightly different syntax or update … Read more