[yt-users] Clumps, contours, n_contours

[David Collins]

Hi, Matt-

That's a good idea.  I tried
np.unique(buff)
and it fixed the problem.  Should I make a PR with this change?

d.


On Tue, May 21, 2013 at 7:16 AM, Matthew Turk <matthewturk at gmail.com> wrote:

> Hi Dave,
>
> I think the way contours works is that it sets N contours.  What might
> work better, since we're contouring images, would be to explicitly
> specify the contours.  Can you test if something like range(N+1) works
> better, rather than len(contours)?
>
> -Matt
>
> On Mon, May 20, 2013 at 7:04 PM, David Collins <dcollins4096 at gmail.com>
> wrote:
> > Hi, Nathan--
> >
> > I thought about the colorbar thing, so I made the image grayscale and it
> > still doesnt' show up.  I also set the zlim so that the data was either
> all
> > white or black, and it shows up in neither.
> >
> > I've attached two representative images.  By construction all of these
> > contours are disjoint.  The missing clump is pretty obvious, as it takes
> up
> > most of the image where it exists.
> >
> > The two attached plots are two tweaks to
> > plot_modifications.py/ClumpContourCallback, at line ~700
> > the "plus_3" plot uses
> > self.rv = plot._axes.contour(buff,  len(self.clumps)+3,
> >                                      extent=extent,**self.plot_args)
> > the "plus_5" plot uses
> >
> > self.rv = plot._axes.contour(buff,  len(self.clumps)+5,
> >                                      extent=extent,**self.plot_args)
> >
> > The code to reproduce the plot is pretty benign, and is below for
> > generality.  the list clumps_to_use comes from a set of pickled clumps
> for
> > this dataset.  I'll see if I can reproduce it with something more
> > universally accessible.  I'm quite sure that it doesn't have anything to
> do
> > with the clump itself, as I've seen this behavior with other calls to
> > 'contour'.  I'm working on a simpler thing that demonstrates this-- I've
> > seen it with code that uses no piece of yt, so I'm 97.2% sure that it's
> > contour and not yt.  (Might be something else dumb I'm doing, that's
> pretty
> > common, but I haven't been able to sort out what it is.)
> >
> > <code>
> >     field='Density'
> >     center = [0.5]*3
> >     proj = pf.h.proj(ax,field,center=center)
> >     plot = proj.to_pw(origin='domain')
> >     plot.set_cmap('Density','gray')
> >     subset = 'black_map_fixed'
> >     plot.set_zlim('Density',1e6,1e7)
> >     if clumps_to_use is not None:
> >         plot.annotate_clumps(clumps_to_use)
> >     print plot.save('%s_n%04d_%s'%(name,frame,subset))
> > </code>
> >
> >
> >
> >
> > On Mon, May 20, 2013 at 4:21 PM, Nathan Goldbaum <nathan12343 at gmail.com>
> > wrote:
> >>
> >> Hi Dave,
> >>
> >> I haven't seen this.  Could this be due to the colorbar?  I believe it
> >> picks the contour colors based on a colorbar.  If the colors it picks
> are
> >> invisible on your plot, you won't see the contours.
> >>
> >> It would help to figure out what's going on if you could come up with a
> >> sample script that illustrates the issue.  Bonus points if you use one
> of
> >> the datasets on yt-project.org/data.
> >>
> >> -Nathan
> >>
> >>
> >> On Mon, May 20, 2013 at 3:17 PM, david collins <dcollins4096 at gmail.com>
> >> wrote:
> >>>
> >>> Hi, all--
> >>>
> >>> I'm seeing a glitch in the matplotlib countor function, as employed by
> >>> annotate_clumps.  As is, I'm seeing some clumps that are not plotted
> by the
> >>> countour plotter unless I bump the number of contours-- I get all the
> plots
> >>> if I change the contour line to:
> >>>
> >>> self.rv = plot._axes.contour(buff, len(self.clumps)+5,
> >>>                                      extent=extent,**self.plot_args)
> >>>
> >>> instead of
> >>>
> >>> self.rv = plot._axes.contour(buff, len(self.clumps)+1,
> >>>                                      extent=extent,**self.plot_args)
> >>>
> >>>
> >>> Is this a glitch that anyone is aware of?  Is there a more general fix?
> >>> The clump contour is not the only time I've run into this glitch. It
> seems
> >>> to happen on large contours, for what that's worth.
> >>>
> >>> Thanks!
> >>> d.
> >>>
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> >>>
> >>
> >>
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