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
--
View this message in context:
http://www.nabble.com/3D-histogram-tp16986530p20268667.html
Sent from the matplotlib - users mailing list archive at Nabble.com.
-------------------------------------------------------------------------
This SF.Net email is sponsored by the Moblin Your Move Developer's challenge
Build the coolest Linux based applications with Moblin SDK & win great prizes
Grand prize is a trip for two to an Open Source event anywhere in the world
http://moblin-contest.org/redirect.php?banner_id=100&url=/
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
