matplotlib-users Mailing List for matplotlib

I don't think there is a direct support for this in mpl and I guess
only way is to adjust the parameters of each ticks.
def set_ticks_both(axis):
 ticks = list( axis.majorTicks ) # a copy
 ticks.extend( axis.minorTicks )
 for t in ticks:
 t.tick1On = True # tick marker on left (or bottom)
 t.tick2On = True # tick marker on right (or top)
 t.label1On = True # tick label marker on left (or bottom)
 t.label2On = True # tick label on right (or top)
set_ticks_both(ax.yaxis)
-JJ
On Thu, Aug 27, 2009 at 7:22 AM, Peter Saffrey<pz...@dc...> wrote:
> Some of my plots are very wide. I'd like Y axis labels on both sides so
> that it's clearer to read the bars towards the right hand side.
>
> I can change the ticks with yaxis.set_ticks_position("both") but there
> doesn't seem to be a similar call for labels. Any ideas?
>
> Thanks,
>
> Peter
>
> ------------------------------------------------------------------------------
> Let Crystal Reports handle the reporting - Free Crystal Reports 2008 30-Day
> trial. Simplify your report design, integration and deployment - and focus on
> what you do best, core application coding. Discover what's new with
> Crystal Reports now. http://p.sf.net/sfu/bobj-july
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Christian Meesters wrote:
>> Christian: That should work, if you created the masked array 
>> correctly. Why are you creating the mask with data=='NA'? I suspect 
>> that this always evaluates to False, so you don't get a mask. You 
>> probably want to check for a numeric value, not a string. For example:
>> 
> Thanks a lot, Jeff!
>
> Yes, the non-numerical comparison was indeed causing problems - although
> I don't understand why.
>
> However, I can easily inject numerical non-sense values into the array.
> As to the 'NA': The data are an R output file. As I don't like R too
> much, I'm falling back to Python.
>
> Christian
>
> 
Christian: What type of array is that (data.dtype)? I don't see how a 
numpy array can have values equal to 'NA', unless it is an array of 
strings. In that case, it would not be plottable anyway. 
-Jeff

> Christian: That should work, if you created the masked array 
> correctly. Why are you creating the mask with data=='NA'? I suspect 
> that this always evaluates to False, so you don't get a mask. You 
> probably want to check for a numeric value, not a string. For example:
Thanks a lot, Jeff!
Yes, the non-numerical comparison was indeed causing problems - although
I don't understand why.
However, I can easily inject numerical non-sense values into the array.
As to the 'NA': The data are an R output file. As I don't like R too
much, I'm falling back to Python.
Christian

Christian Meesters wrote:
> Hi,
>
> I have a 2D masked array, created like:
>
> import numpy as np
> data = np.ma.array(data, mask=[data == 'NA'])
>
> which I would like to plot as a heatmap.
>
> import pylab
>
> pylab.pcolor(data)
> or
> pylab.pcolormesh(data)
>
> Well, it works with any array, but not if masked values are in there.
> Can somebody supply me with a snippet, as I apparently don't get the
> relevant piece in the docs (or did not find it ;-) ).
>
> TIA
> Christian
>
> 
Christian: That should work, if you created the masked array 
correctly. Why are you creating the mask with data=='NA'? I suspect 
that this always evaluates to False, so you don't get a mask. You 
probably want to check for a numeric value, not a string. For example:
import matplotlib.pyplot as plt
import numpy as np
def func3(x,y):
 return (1- x/2 + x**5 + y**3)*np.exp(-x**2-y**2)
dx, dy = 0.05, 0.05
x = np.arange(-3.0, 3.0001, dx)
y = np.arange(-3.0, 3.0001, dy)
X,Y = np.meshgrid(x, y)
Z = func3(X, Y)
Z = np.ma.array(Z, mask=Z>0.5)
plt.pcolor(Z)
plt.show()
-Jeff 

Some of my plots are very wide. I'd like Y axis labels on both sides so 
that it's clearer to read the bars towards the right hand side.
I can change the ticks with yaxis.set_ticks_position("both") but there 
doesn't seem to be a similar call for labels. Any ideas?
Thanks,
Peter

Hi,
I have a 2D masked array, created like:
import numpy as np
data = np.ma.array(data, mask=[data == 'NA'])
which I would like to plot as a heatmap.
import pylab
pylab.pcolor(data)
or
pylab.pcolormesh(data)
Well, it works with any array, but not if masked values are in there.
Can somebody supply me with a snippet, as I apparently don't get the
relevant piece in the docs (or did not find it ;-) ).
TIA
Christian