Thanks,
This almost does what I want. The labels are now changed to log notation,
but the tick locations have remained the same. I want the spacing between
each logarithmic decade to be equal. I just did an svn up and rebuild so I
am working with bleeding edge matplotlib. Do I need to manually set the
locations of the ticks? I'll play around a bit more with w_yaxis, I wasn't
aware of this.
Danke vel,
Trevor
2009/12/13 Reinier Heeres <rein...@heeres.eu>
> Hi,
>
> You'll have to use ax.w_yaxis.set_yscale('log'), which should work fine.
>
> Hope this helps,
> Reinier
>
> On Tue, Dec 8, 2009 at 5:11 PM, Trevor Irons <trevorir...@gmail.com>
> wrote:
> > Hi:
> >
> > I'm trying to get a semilog 3D plot. I want to plot several 2D time
> series
> > lines, with the third axis being on a log scale. I am trying to set an
> axis
> > to log using ax.set_yscale('log'), but am getting errors. Is this
> possible?
> >
> > I keep getting numpy errors when I try:
> > raise MaskError, 'Cannot convert masked element to a Python int.'
> > numpy.ma.core.MaskError: Cannot convert masked element to a Python int.
> >
> > My attempt:
> >
> > from mpl_toolkits.mplot3d import Axes3D
> > import matplotlib.pyplot as plt
> > import numpy as np
> >
> > fig = plt.figure()
> > #ax = fig.gca()
> > ax = Axes3D(fig)
> >
> > colors = ('r', 'g', 'b', 'k')
> > zd = (0., 1., 2., 3.)
> > T2 = (0.9, .8, .7, .6)
> > ic = 1
> >
> > for ic in xrange(len(colors)):
> > x = np.arange(0.05,1,.005)
> > z = np.exp(-x/T2[ic]) + np.random.normal(0, .05, len(x))
> > y = np.exp(zd[ic])*np.ones(len(x))
> > ax.plot(x,y,z)
> >
> > # Error if uncommented
> > #ax.set_yscale('log')
> > plt.show()
> >
> > Thanks for any insight.
>
> --
> Reinier Heeres
> Tel: +31 6 10852639
>
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