Matplotlib - Wrong normals on 3D bars plot

PROBLEM

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

EXAMPLE

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.

ABOUT

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

LOGS

This is the only warning the I get from console:

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

Any help is much appreciated.

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.

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()