Heh, thanks :) It's free interpretation made from quick idea then immediately shared. Original logo can be made exact I guess with interlaced planes and shallower bars or similar... On Tue, Jun 26, 2012 at 8:19 AM, Anthony Scopatz wrote:

This is awesome!

I'll try, thanks ^_^ As I said I'm learning mayavi, and wasn't expecting that drawing trivial objects like planes would be trouble. It seems it is, and the way to do this would be using triangular_mesh function. So I looked elsewhere, i.e. matplotlib and abused bars: ======================================== from numpy import arange, ones import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D fig = plt.figure() ax = fig.add_subplot(111, projection='3d') o = ones(4) r = arange(4) # planes: for z in arange(3)+1: ax.bar(r, o*4, zs=z, zdir='x', alpha=.05, width=1) ax.bar(r, o*4, zs=z, zdir='y', alpha=.05, width=1) ax.bar(r, o*4, zs=z, zdir='z', alpha=.05, width=1) # N for i in [1, 2]: ax.bar3d([i], [0], [i], [.9], [.1], [.9], color='y', linewidth=.1) ax.bar3d(o+(i*(-1)**i), o-1, r, o-.1, o-.9, o-.1, color='y', linewidth=.1) # cage ax.bar3d([0], [0], [0], [4], [4], [4], alpha=.05, color='w', linewidth=0) plt.show() # plt.savefig('numpy.png') ======================================== Results in attachment. Annotation stuff can be turned off in above case like this: ======================================== ax.grid(False) for a in (ax.w_xaxis, ax.w_yaxis, ax.w_zaxis): for t in a.get_ticklines()+a.get_ticklabels(): t.set_visible(False) a.line.set_visible(False) a.pane.set_visible(False) ======================================== I'll try later with mayavi again, simply because it can export to 3D format suitable for further enhancing and rendering, if needed. Default lights in matplotlib 3D scene seem too low and colors are pale compared to mayavi, and I'm not sure if there is way to tweak it. Hope to see other competitors with different approach ;) Cheers

I continued in this mpl trip, with small animation sequence: ======================================== # animation ax.view_init(90,-90) plt.ion() plt.draw() plt.show() for l in arange(25): ax.set_xlim3d(1.5-.1*l,2.5+.1*l) ax.set_ylim3d(1.5-.1*l,2.5+.1*l) ax.view_init(90-3*l, -90+l) plt.draw() plt.title("NumPy") plt.ioff() plt.show() ======================================== Try it or check it out on YouTube: www.youtube.com/watch?v=mpYPS_zXAFw Whole script in attachment

Yeah, camera is in cliche, I know :D Something more original can be done, perhaps some idea of transforming grid in 2D (in Z plane) for opening sequence and then emerging latices in some analogy with numpy arrays, finishing with complete figure, but I guess not in matplotlib ;)

This is cool. It would be nice to put these things somewhere where they could be available for reference. -Travis On Jun 27, 2012, at 10:20 AM, Virgil Stokes wrote:

On 27-Jun-2012 11:40, klo uo wrote:

...

I continued in this mpl trip, with small animation sequence:

======================================== # animation ax.view_init(90,-90) plt.ion() plt.draw() plt.show()

for l in arange(25): ax.set_xlim3d(1.5-.1*l,2.5+.1*l) ax.set_ylim3d(1.5-.1*l,2.5+.1*l) ax.view_init(90-3*l, -90+l) plt.draw()

plt.title("NumPy") plt.ioff() plt.show() ========================================

Try it or check it out on YouTube: www.youtube.com/watch?v=mpYPS_zXAFw

Whole script in attachment

_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion +1 --- looks good. --V

---

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In the first version this line: ax.bar3d([i], [0], [i], [.9], [.1], [.9], color='y', linewidth=.1) is responsible for diagonal in N, and it is inverted. In the second version you quoted this is corrected with: ax.bar3d([3-i], [0], [i], [.9], [.1], [.9], color='y', linewidth=.1) Also snippet for clearing axis decorations, (grid, ticks, lines...) is posted separately besides first version. Anyhow attached python script in later mail (with youtube link) has all this together plus anim sequence On Wed, Jun 27, 2012 at 6:34 PM, Virgil Stokes <vs@it.uu.se> wrote:

...

from numpy import arange, ones import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure() ax = fig.add_subplot(111, projection='3d')

o = ones(4) r = arange(4)

# planes: for z in arange(3)+1:     ax.bar(r, o*4, zs=z, zdir='x', alpha=.05, width=1)     ax.bar(r, o*4, zs=z, zdir='y', alpha=.05, width=1)     ax.bar(r, o*4, zs=z, zdir='z', alpha=.05, width=1)

# N for i in [1, 2]:      ax.bar3d([3-i], [0], [i], [.9], [.1], [.9], color='y', linewidth=.1)      ax.bar3d(o+(i*(-1)**i), o-1, r, o-.1, o-.9, o-.1, color='y', linewidth=.1)

# cage ax.bar3d([0], [0], [0], [4], [4], [4], alpha=.05, color='w', linewidth=0)

plt.show() # plt.savefig('numpy.png') Umh... The first version that you posted looks ok on my screen (N is not inverted). And

On 27-Jun-2012 08:04, klo uo wrote: this version shows no difference in the "N"; but, it does show tick marks labeled with numerical values.

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