Matplotlib - Wrong normals on 3D bars plot

Question

PROBLEM

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When using matplotlib and plotting 3d bars on a chart I got wrong normals values on some bar faces.

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EXAMPLE

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When I plot a high density bins graph, with 240 bars, I get this result:

See that some faces of some bars are wrong? The bars Z order gets wrong too.

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ABOUT

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I'm using the latest stable version of Matplotlib and Numpy. My Python version is 2.7.3

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LOGS

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This is the only warning the I get from console:

RuntimeWarning: invalid value encountered in divide for n in normals])

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Any help is much appreciated.

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EDIT

With @Saullo Castro answer, this is the new graph produced:

Or, using the sample presented in the answer (see the region marked with red dots):

The only problem left is the bar face on the top, but is already pretty good. If anyone has any comments on this, feel free to help me.

Answer 1

Using the parameter zsort='max' when you call ax.bar3d()solves your problem (see here):

ax.bar3d(xpos,ypos,zpos, dx, dy, dz,  color='b', alpha=1., zsort='max')

I used a modified version of the code from this other question to play with your problem:

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np

data = np.array([[0,1,0,2,0],
                 [0,3,0,2,0],
                 [6,1,1,7,0],
                 [0,5,0,2,9],
                 [0,1,0,4,0],
                 [9,1,3,4,2],
                 [0,0,2,1,3], ])

column_names = ['a','b','c','d','e']
row_names = ['Mon','Tue','Wed','Thu','Fri','Sat','Sun']

fig = plt.figure()
ax = Axes3D(fig)

lx= len(data[0])            # Work out matrix dimensions
ly= len(data[:,0])
xpos = np.arange(0,lx,1)    # Set up a mesh of positions
ypos = np.arange(0,ly,1)
xpos, ypos = np.meshgrid(xpos+0.5, ypos+0.5)

xpos = xpos.flatten()   # Convert positions to 1D array
ypos = ypos.flatten()
zpos = np.ones(lx*ly)*1e-10

dx = 1. * np.ones_like(zpos)
dy = dx.copy()
dz = data.flatten()

ax.bar3d(xpos,ypos,zpos, dx, dy, dz,  color='b', alpha=1., zsort='max')
plt.ion()
plt.show()