Thread: [Matplotlib-users] 3D histogram

Hi,
I would like to generate (or simulate) 3D histogram... How I can do this with matplotlib/pylab (if I can) ?
I tried different ways :
 - 2D histogram in 3D but the result is not usable for me (because I have lot of small bars)
 - generation of bars with, for each bar, 5 Polygons but I didn't success (I don't hunderstand the main principle of the 3D module) and it seems to be slow (I must draw approximatively 300 bars)
 - simulation of bars with large lines (like in Gnuplot, see below) but, again, I don't hunderstand the main principle of the 3D module and I don't know how I can plot set of lines in a 3D environment...
Today, I do this with Gnuplot :
>>> splot "hist3D.dat" with boxes linewidth 10
hist.dat :
0 0 3
0 1 2
0 2 5
1 0 1
1 1 4
1 2 1
2 0 5
2 1 2
2 2 3
Does someone have an idea ?
Thanks

Hi,
this is my best result... figure is acceptable when I use a lot of points...
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import matplotlib
import matplotlib.art3d
import matplotlib.axes3d
import pylab
if __name__ == "__main__":
 data_filename = ...
 # We load data
 # 
 # x1 y1 v1
 # x2 y2 v2
 # x3 y3 v3
 # ...
 #
 data_file = pylab.load(data_filename)
 # We get x coordinate
 lstX = data_file[:, 0]
 # We get y coordinate
 lstY = data_file[:, 1]
 # We get data values
 lstV = data_file[:, 2]
 # We create list of lines from (x, y, 0) to (x, y, value)
 lstLines = [[(x, y, 0), (x, y, v)] for (x, y, v) in zip(lstX, lstY,
lstV)]
 # We create the figure
 fig = pylab.figure(1)
 # We get the axe reference
 ax = matplotlib.axes3d.Axes3D(fig)
 # We create a matplotlib line collection
 lines = matplotlib.art3d.Line3DCollection(lstLines, linewidths=5)
 # We add the collection to the axes
 ax.add_3DCollection(lines)
 # Auto scale
 ax.auto_scale_xyz(lstX, lstY, lstV, ax.has_data())
 # Draw
 pylab.show()
 # Bye
 exit(0)
Example of data file :
0 0 -4.49132
0 1 0.676531
0 2 -1.60375
0 3 -0.184649
0 4 0.958887
0 5 -0.165971
1 0 -0.0216472
1 1 0.157346
1 2 -0.372853
1 3 0.2576
1 4 0.654506
2 0 0.139453
2 1 -0.204437
2 2 0.151606
2 3 0.271027
3 0 0.222327
3 1 0.921501
3 2 0.500956
4 0 0.104108
4 1 0.415777
5 0 0.244248
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