matplotlib-users Mailing List for matplotlib

Thank you for the 'fix'. Both the demo and my old matplotlib based scripts work again.
Richard
On Friday 28 July 2006 17:19, Richard Ruth wrote:
> I upgraded to matplotlib-0.87.4 Now I receive an error like the following
> every time I try to use matplotlib.dates. The following error messages
> were generated when I tried to run matplotlib-0.87.4/examples/date_demo1.py
>
> Any Idea on how I can get dates working again?
> (I am running the 2.6.17.6 kernel on a 64-bit linux system)
Richard,
in matplotlib/dates.py, change line 155 from
remainder = x - ix
to
remainder = float(x) - ix
The problem is that matplotlib uses numpy arrays for the xaxis. As you have a 
64b system, the arrays are in float64scalars, that divmod doesn't know how to 
process (unless you have a very recent of numpy). The trick above forces a 
downcasting of float64scalar to float32scalar, divmod can now work.

I am doing a buch of plots and I would like to set the dash on/off
list globally (to [2,4]) rather than everytime I run pylab.plot(). Is
there any such thing?
Thanks!

Hi,
this is a question I have posted earlier, but unfortunately I didn't get
any answer.
if anybody has any hint on how to do this, I would be most graceful!!
Thanks in advance!
I would like to visualize an image after a rotation:
==> this means to view each squared pixels as "rotated" (seen as an
rotated square). I have in fact several images which I need to plot on
the same figure (with subplot), each of these having different "rotation
angles".
The rough solution would be to rotate the data itself (x and y) and use
imshow after some rebinning on a squared grid. But this would not be
showing the original data, which is what I wish to do.
Is it possible to do this in mpl?
thanks!
Eric

Stefan van der Walt wrote:
> On Thu, Jul 27, 2006 at 08:57:47PM -0400, PGM wrote:
> 
>>>Is this normal? If so, how do I get around the problem? I also
>>>noticed that, even without extents, the image gets scaled after
>>>plotting.
>>
>>Try to set the "_autoscale" parameter of your current 'axes' to False. That 
>>way, you should avoid any inopportune rescaling. For the image, try to use 
>>aspect='auto'.
>>
>>For example,
>>
>>P.imshow(x,extent=(0,x.shape[1],x.shape[0],0))
>>P.gca().set_autoscale_on(False)
> 
> 
> Thanks, P., that did the trick! It looks like the right way to fix
> the scaling of the axes extents, but I am still not sure whether the
> axis flipping behaviour I described earlier is correct.
I changed it in svn 2636; now Axes.autoscale_view() preserves axis 
direction. I think this will be generally useful and will cause less 
user surprise than the previous behavior.
Eric