matplotlib-devel Mailing List for matplotlib

On 2012年5月26日 at 03:30PM -1000, Eric Firing wrote:
> It is easy enough to remove the immediate roadblock in scale_range,
> but that just opens up a can of floating point worms. The axis spines
> start getting misplaced, for example, as the range being plotted gets
> too small relative to the offset. Straightening all this out, or even
> substantially improving it, is potentially tricky. To the extent that
> it can be done, it will have to be in master, which already includes
> one cleanup of a floating point kluge.
> 
> Note that part of the problem here is that in your example we are
> running out of precision. The best way to handle it is to subtract an
> offset first, and just plot the deviation from that offset. I think
> this is best done at the application level. We can probably make
> mpl's handling of the problem degrade more gracefully, however, than
> it does at present.
Thanks for your help. I'll look at your links and see what we can do.
Dan
--
--- Dan Drake
----- http://mathsci.kaist.ac.kr/~drake
-------

On 05/25/2012 12:46 PM, Dan Drake wrote:
> Hello matplotlib developers,
>
> In Sage, we've run into a problem with plotting a sequence whose
> y-values change by very small amounts. Here's an example that doesn't
> use anything from Sage:
>
> import pylab
> pylab.plot([0, 1], [0, 1e-14])
> pylab.savefig("works.png")
> pylab.close()
> pylab.plot([0, 1], [1, 1+1e-14])
> pylab.savefig("fails.png")
> pylab.close()
>
> We're using matplotlib 1.1. Here's a trac ticket where we are working on
> this: http://trac.sagemath.org/sage_trac/ticket/11973. One of our
> developers suspects matplotlib.ticker.MaxNLocator.bin_boundaries but we
> don't really know.
See https://github.com/matplotlib/matplotlib/pull/904
Eric
>
> Thanks for any help or comments!
>
> Dan
>
> --
> --- Dan Drake
> ----- http://mathsci.kaist.ac.kr/~drake
> -------

On 05/25/2012 12:46 PM, Dan Drake wrote:
> Hello matplotlib developers,
>
> In Sage, we've run into a problem with plotting a sequence whose
> y-values change by very small amounts. Here's an example that doesn't
> use anything from Sage:
>
> import pylab
> pylab.plot([0, 1], [0, 1e-14])
> pylab.savefig("works.png")
> pylab.close()
> pylab.plot([0, 1], [1, 1+1e-14])
> pylab.savefig("fails.png")
> pylab.close()
>
> We're using matplotlib 1.1. Here's a trac ticket where we are working on
> this: http://trac.sagemath.org/sage_trac/ticket/11973. One of our
> developers suspects matplotlib.ticker.MaxNLocator.bin_boundaries but we
> don't really know.
Dan,
It is easy enough to remove the immediate roadblock in scale_range, but 
that just opens up a can of floating point worms. The axis spines start 
getting misplaced, for example, as the range being plotted gets too 
small relative to the offset. Straightening all this out, or even 
substantially improving it, is potentially tricky. To the extent that 
it can be done, it will have to be in master, which already includes one 
cleanup of a floating point kluge.
Note that part of the problem here is that in your example we are 
running out of precision. The best way to handle it is to subtract an 
offset first, and just plot the deviation from that offset. I think 
this is best done at the application level. We can probably make mpl's 
handling of the problem degrade more gracefully, however, than it does 
at present.
Eric
>
> Thanks for any help or comments!
>
> Dan
>
> --
> --- Dan Drake
> ----- http://mathsci.kaist.ac.kr/~drakes
> -------