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From: Luke <hazelnusse@gm...>  20110428 07:51:55

I have a set of unstructured (x,y) points which I would like to compute a boundary polygon for. I don't want the convex hull. I was able to use matplotlib.tri to get a Delaunay triangulation for my points by following the examples online, but I'm having trouble masking everything but the triangles with a boundary edge. Additionally, once I get this, I'm not clear on how to plot just the boundary. Here is what it seems like the mask should be, assume triang comes from matplotlib.tri.Triangulation(). mask = np.where(np.where(triang.neighbors < 0, 0, 1).all(axis=1), 1, 0) triang.set_mask(mask) but, when I plot triang using plot.triplot(), or plt.plot() to plot the edges, I am getting a bunch of extra stuff that isn't just the boundary triangles/edges. Anybody have example code for properly masking and plotting only the boundary edges? ~Luke  "Those who would give up essential liberty to purchase a little temporary safety deserve neither liberty nor safety."  Benjamin Franklin, Historical Review of Pennsylvania, 1759 
From: Ian Thomas <ianthomas23@gm...>  20110428 21:14:46
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tri_boundaries.py

From: Luke <hazelnusse@gm...>  20110428 21:56:30

Ian, Thanks for the response and the example code. I guess what I'm trying to do might be well defined. Here is a plot that should illustrate the data I'm working with: http://biosport.ucdavis.edu/blog/copy_of_steady_benchmark_tau.png The green and red regions are being displayed by plotting each and every point in my data set that is stable. So the set of points I was describing in my original message looks like these green and red regions. What I would like is just the boundary of the stable region, which maybe isn't a very well defined statement. The convex hull of these points would enclose a part of the xy plane that isn't stable, so I don't want to include it in my plot. I am thinking that perhaps the approach I should be taking should involve contouring the real part of the eigenvalues which determine the stability, and then plot the zerolevel curve. I'll have to think about that some more. Is it clear what I am trying to do? If so, do you think the Delaunay triangulation is the right way to go? ~Luke On Thu, Apr 28, 2011 at 2:14 PM, Ian Thomas <ianthomas23@...> wrote: > On 28 April 2011 08:51, Luke <hazelnusse@...> wrote: >> >> I have a set of unstructured (x,y) points which I would like to >> compute a boundary polygon for. I don't want the convex hull. >> >> I was able to use matplotlib.tri to get a Delaunay triangulation for >> my points by following the examples online, but I'm having trouble >> masking everything but the triangles with a boundary edge. >> Additionally, once I get this, I'm not clear on how to plot just the >> boundary. >> >> Here is what it seems like the mask should be, assume triang comes >> from matplotlib.tri.Triangulation(). >> >> mask = np.where(np.where(triang.neighbors < 0, 0, 1).all(axis=1), 1, 0) >> triang.set_mask(mask) >> >> but, when I plot triang using plot.triplot(), or plt.plot() to plot >> the edges, I am getting a bunch of extra stuff that isn't just the >> boundary triangles/edges. >> >> Anybody have example code for properly masking and plotting only the >> boundary edges? >> >> ~Luke > > Luke, > > I am not entirely clear exactly what you want to do, but I'll try to help. > > Your masking of the triangulation masks the triangles not the edges, and so > your triplot call displays those triangles that include a boundary edge but > also the other edges of those triangles. As you say, this isn't what you > want. > > I've attached an example script that follows on from your idea of testing > triang.neighbors to determine the boundary edges, and displays just those > edges. However, this is the convex hull as, by definition, the boundary of > an unconstrained Delaunay triangulation is the convex hull. As you don't > want the convex hull, I am not clear what you want instead. > > If I have misunderstood your requirements and/or you have further questions, > please post your example code as it is much easier for others on the mailing > list to correct existing code than come up with their own freestanding > example. > > I hope some of this helps! > Ian Thomas >  "Those who would give up essential liberty to purchase a little temporary safety deserve neither liberty nor safety."  Benjamin Franklin, Historical Review of Pennsylvania, 1759 
From: gary ruben <gruben@bi...>  20110429 02:03:31

If you generate a big list of all the edges from the triangle data, you should get repeat entries only for all the internal edges. You could then find all the duplicates using this recipe http://stackoverflow.com/questions/1920145/howtofindduplicateelementsinarrayusingforloopinpythonlikecc i.e. dups = [x for x in list_a if list_a.count(x) > 1] After removing all of these, you should be left with just the boundary edges. Gary R. On Fri, Apr 29, 2011 at 7:56 AM, Luke <hazelnusse@...> wrote: > Ian, > Thanks for the response and the example code. I guess what I'm > trying to do might be well defined. Here is a plot that should > illustrate the data I'm working with: > > http://biosport.ucdavis.edu/blog/copy_of_steady_benchmark_tau.png > > The green and red regions are being displayed by plotting each and > every point in my data set that is stable. So the set of points I was > describing in my original message looks like these green and red > regions. > > What I would like is just the boundary of the stable region, which > maybe isn't a very well defined statement. The convex hull of these > points would enclose a part of the xy plane that isn't stable, so I > don't want to include it in my plot. > > I am thinking that perhaps the approach I should be taking should > involve contouring the real part of the eigenvalues which determine > the stability, and then plot the zerolevel curve. I'll have to think > about that some more. > > Is it clear what I am trying to do? If so, do you think the Delaunay > triangulation is the right way to go? > > ~Luke > > On Thu, Apr 28, 2011 at 2:14 PM, Ian Thomas <ianthomas23@...> wrote: >> On 28 April 2011 08:51, Luke <hazelnusse@...> wrote: >>> >>> I have a set of unstructured (x,y) points which I would like to >>> compute a boundary polygon for. I don't want the convex hull. >>> >>> I was able to use matplotlib.tri to get a Delaunay triangulation for >>> my points by following the examples online, but I'm having trouble >>> masking everything but the triangles with a boundary edge. >>> Additionally, once I get this, I'm not clear on how to plot just the >>> boundary. >>> >>> Here is what it seems like the mask should be, assume triang comes >>> from matplotlib.tri.Triangulation(). >>> >>> mask = np.where(np.where(triang.neighbors < 0, 0, 1).all(axis=1), 1, 0) >>> triang.set_mask(mask) >>> >>> but, when I plot triang using plot.triplot(), or plt.plot() to plot >>> the edges, I am getting a bunch of extra stuff that isn't just the >>> boundary triangles/edges. >>> >>> Anybody have example code for properly masking and plotting only the >>> boundary edges? >>> >>> ~Luke >> >> Luke, >> >> I am not entirely clear exactly what you want to do, but I'll try to help. >> >> Your masking of the triangulation masks the triangles not the edges, and so >> your triplot call displays those triangles that include a boundary edge but >> also the other edges of those triangles. As you say, this isn't what you >> want. >> >> I've attached an example script that follows on from your idea of testing >> triang.neighbors to determine the boundary edges, and displays just those >> edges. However, this is the convex hull as, by definition, the boundary of >> an unconstrained Delaunay triangulation is the convex hull. As you don't >> want the convex hull, I am not clear what you want instead. >> >> If I have misunderstood your requirements and/or you have further questions, >> please post your example code as it is much easier for others on the mailing >> list to correct existing code than come up with their own freestanding >> example. >> >> I hope some of this helps! >> Ian Thomas >> > > > >  > "Those who would give up essential liberty to purchase a little > temporary safety deserve neither liberty nor safety." > >  Benjamin Franklin, Historical Review of Pennsylvania, 1759 > >  > WhatsUp Gold  Download Free Network Management Software > The most intuitive, comprehensive, and costeffective network > management toolset available today. Delivers lowest initial > acquisition cost and overall TCO of any competing solution. > http://p.sf.net/sfu/whatsupgoldsd > _______________________________________________ > Matplotlibusers mailing list > Matplotlibusers@... > https://lists.sourceforge.net/lists/listinfo/matplotlibusers > 
From: Jason Grout <jasonsage@cr...>  20110429 03:08:51

On 4/28/11 9:03 PM, gary ruben wrote: > http://stackoverflow.com/questions/1920145/howtofindduplicateelementsinarrayusingforloopinpythonlikecc > i.e. > dups = [x for x in list_a if list_a.count(x)> 1] That involves iterating through your list_a a number of times to look for elements. It probably would be much faster to use something like the Counter class to just get the items that occur once or more than once: http://docs.python.org/library/collections.html#counterobjects Thanks, Jason 
From: Ian Thomas <ianthomas23@gm...>  20110429 08:50:58
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On 28 April 2011 22:56, Luke <hazelnusse@...> wrote: > I am thinking that perhaps the approach I should be taking should > involve contouring the real part of the eigenvalues which determine > the stability, and then plot the zerolevel curve. I'll have to think > about that some more. > This sounds like a very sensible approach and is quick and easy to try out using tricontour/tricontourf. You may have to use a very small positive value for the contour level rather then zero to get what you want. > Is it clear what I am trying to do? If so, do you think the Delaunay > triangulation is the right way to go? > Yes, it is clear what you are trying to do. I think that you shouldn't be concerned with the triangulation, Delaunay or not, as this is at too low a level for what you are attempting. Stick to the highlevel data analysis and presentation functions like tricontour and ignore details of the underlying triangulation. If you are having to manipulate a triangulation then you are becoming a computational geometrist  it is a completely valid and interesting thing to do but is probably taking your attention away from your real work. Ian 