Hi Sean, thanks for the response. This is pretty much what I figured :p
I'll just stick with the 'fixed precision like hack' and use that as a
workaround. It's not the end of the world (get it?)... I guess I could
store a mapping of the floating point to the rounded values (not ideal) if
I really needed to get them back...
Cheers,
Carson
On Tue, Nov 3, 2015 at 9:30 AM Sean Gillies <sean.gill...@gmail.com> wrote:
> Hi Carson,
>
> I've scoped out the work of adding fixed precision geometry models to
> Shapely but haven't begun. It's a pretty big lift and I've got too
> much other stuff on my plate right now. For now, Shapely has only a
> floating point precision model. This causes many problems with Natural
> Earth: that dataset is full of features that are invalid under the
> floating point model (due to microscopic self-intersections &c) but
> that would be perfectly valid with a fixed precision model.
>
> For merging anti-meridian crossers: once you've shifted geometry parts
> from one side by 360 degrees, you should be able to use
> shapely.ops.unary_union.
>
> On Thu, Oct 22, 2015 at 1:13 PM, Carson Farmer <carson.far...@gmail.com>
> wrote:
> > Hi all, I’m wondering if someone can provide some guidance on a ‘problem’
> > I’m working on. In the following example, I’m trying to ‘stitch’ together
> > geometries which cross the anti-meridian. Here I’m working with a (subset
> > of) the Russian geometries that comes from the Natural Earth 110m Admin
> > Shapefile (I’ve just included the WKT to make things more reproducible).
> See
> > this Gist for the full example. The question is: “is it possible to use
> > ‘fuzzy’ tolerances in any of the Shapely/GEOS geometry functions (or
> > linemerge in particular )?” or “is it possible to work around the fact
> that
> > I can’t use fuzzy tolerances?”. I don’t mind making copies of things or
> > passing things around to get this to work… I’d just like to avoid having
> to
> > decrease the output precision of my merged geometries if possible…
> > Alternatively, is there a better way to stitch geometries which cross the
> > anti-meridian using shapely? The TopoJSON commadline utility does it,
> but I
> > want to stay in Python land...
> >
> > from shapely import wit
> > from shapely import ops
> > import matplotlib.pyplot as plt
> > %matplotlib inline
> >
> > # These are provided in full in the Gist
> > a = wkt.loads("LINESTRING (-180 68.96363636363637…
> > b = wkt.loads("LINESTRING (180 64.974329999999999…
> >
> > def plot_line(ob, ax, **kwargs):
> > x, y = ob.xy
> > ax.plot(x, y, linewidth=1, zorder=1, **kwargs)
> >
> > def simplify(x, y, tol=8):
> > return round(x, tol), round(y, too)
> >
> > def shift(x, y):
> > """Sometimes x is a tuple, sometimes a float?!"""
> > try:
> > x = [i + 360 if i < 0 else i for i in x]
> > except:
> > x = x + 360 if x < 0 else x
> > return x, y
> >
> > fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(10, 4))
> >
> > # This obviously isn't going to work…
> > l = ops.linemerge([a, b])
> > for i in l:
> > plot_line(i, ax1)
> >
> > # This should work, but the points aren't exactly coincident
> > l = ops.linemerge([ops.transform(shift, a), b])
> > for i in l:
> > plot_line(i, ax2)
> >
> > # This does work, but the process is ‘destructive'
> > # (i.e., we lose precision)
> > # You can check this by looking at l.coords
> > l = ops.linemerge([ops.transform(simplify, ops.transform(shift, i)) for
> i in
> > [a, b]])
> > plot_line(l, ax3)
> >
> > plt.show()
> >
> > _______________________________________________
> > Community mailing list
> > Community@lists.gispython.org
> > http://lists.gispython.org/mailman/listinfo/community
> >
>
>
>
> --
> Sean Gillies
> _______________________________________________
> Community mailing list
> Community@lists.gispython.org
> http://lists.gispython.org/mailman/listinfo/community
>
--
Dr. Carson Farmer (mobile edition)
Assistant Professor
Department of Geography
University of Colorado at Boulder
303.492.3252
@carsonfarmer
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