[Matplotlib-users] exporting tricontour function results

Ian Thomas ianthomas23 at gmail.com
Wed Dec 2 15:00:00 EST 2015


Your question about interior and exterior polygons is already answered in
the thread you keep referring to.  I'll repeat it here.  tricontouf does
not return any information about which interior polygons are located inside
which exterior polygons.  All you get is a collection of polygons, composed
of one or more exteriors and zero or more interiors, and they can be in any
order.  The backends take these arbitrary collections of exterior and
interior polygons and render them correctly.  As all of the backends are
capable of calculating the exterior/interior containment themselves, there
is no need for tricontourf to do it as well.

contourf produces different output, grouping each exterior polygon with its
contained interior polygons.  This is because it dates from before all the
backends were capable of calculating polygon containment, so contourf had
to do it.  The recent rewrite of the contourf C++ code still does this so
that it produces output consistent with the legacy code.

If you want take the output of tricontourf and calculate the
exterior/interior containment, you'll either have to find some other
library to do it, or write the code yourself.  I have not looked into
libraries that do this as I do not need this functionality.  Writing the
code to do it yourself is pretty easy, but making it robust and efficient
is much harder.


I think you have misunderstood my comments from last year.  When I was
talking about what I consider private, I was referring to the segs and
kinds that are passed from C++ to python to make up the various Path
objects.  I didn't refer to the function to_polygons() being private, in
fact I didn't refer to it at all.


On 1 December 2015 at 21:57, Francis Chabouis <fchabouis at gmail.com> wrote:

> Ben,
> 1. Exporting data like this was never an intended use => I understand your
> point. In fact if calling the underlying C++ code for tricontour had been
> easy I would happily have skipped the call to MPL. All I'm interested in is
> the polygons coordinates really.
> 2. good news :)
> 3. please find the script attached.
> thanks
> Francis
> 2015-12-01 22:33 GMT+01:00 Benjamin Root <ben.v.root at gmail.com>:
>> Francis,
>> 1. Keep in mind, matplotlib is a plotting library first. Path
>> simplification takes into account the resolution of the output device when
>> used for drawing and essentially simplifies out any unresolvable features,
>> which greatly reduces drawing time for complex plots. Exporting data like
>> this was never an intended use.
>> 2. I will have to respectfully disagree with Ian on this point.
>> to_polygons() is not a private method and it is perfectly reasonable to
>> expect it to be used by people outside the matplotlib codebase. As a
>> developer, I would reject any patches that changes the output semantics of
>> to_polygons() without going through a lengthy deprecation cycle. Plus, the
>> primary use of this method is for easy input to Polygon artist objects,
>> which has a constructor that isn't going to change, so why should
>> to_polygons() change?
>> 3. Without the source example data, I am at a bit of a loss for what is
>> happening here. I could come up with all sorts of guesses, but I can't tell
>> you for sure without having something I can run myself.
>> Cheers!
>> Ben Root
>> On Tue, Dec 1, 2015 at 4:18 PM, Francis Chabouis <fchabouis at gmail.com>
>> wrote:
>>> Thanks Ben for your answer.
>>> I didn't know about that should_simplify attribute. It was effectively
>>> the reason for the disappearing points. Thanks a lot.
>>> I still have a few questions if you don't mind :
>>> 1. [low importance] Isn't it weird to have this attribute set to True by
>>> default ? I would find it  more natural if simplification had to be
>>> explicitly requested.
>>> 2. You say "The first element of that list is the external vertexes, and
>>> the rest of the elements are all vertex lists of the internal holes." I
>>> like this a lot, but are you sure it is true ? As it comes in contradiction
>>> with Ian Thomas explanation :
>>> "The returned geometries are purposefully not documented.  They are an
>>> 'implementation detail' and not considered part of the public interface.
>>> and as such they could change at any time and hence should not be relied
>>> upon.  Of course you can choose to access them if you wish, as I do myself
>>> sometimes, but we make no promises about what the order of the polygons is,
>>> or that it won't change tomorrow."
>>> http://matplotlib.1069221.n5.nabble.com/Structure-of-contour-object-returned-from-tricontourf-td44203.html
>>> 3. I have done a simple test and the output looks like this (2 rings):
>>> [image: Images intégrées 1]
>>> So I'm a bit confused as :
>>> cs = plt.tricontourf(t, v, levels)
>>> #cs.collections has 1 element (ok as there is only one level)
>>> for i,collection in enumerate(cs.collections):
>>>     for path in collection.get_paths():
>>>     #collection.get_paths() has only 1 element, I would eventually have
>>> expected 2 (1 for each ring)
>>>     polygons = path.to_polygons()
>>>     # polygons has 4 elements : the 4 rings are stored at the same place
>>>     # how can I recognise the exteriors from the interiors ?
>>> Thanks for your help,
>>> Francis
>>> 2015-11-30 19:37 GMT+01:00 Benjamin Root <ben.v.root at gmail.com>:
>>>> Francis,
>>>> I bet you that the inconsistency in the number of vertexes is due to
>>>> path simplification. The list of Path objects you get when you call
>>>> get_paths() on the collection object each have an attribute
>>>> "should_simplify" and that defaults to True. Set it to False, and you will
>>>> have all of the vertexes. Also, what you want to call is to_polygons() on
>>>> the Path object after setting "should_simplify" to False. That will return
>>>> a list of lists. The first element of that list is the external vertexes,
>>>> and the rest of the elements are all vertex lists of the internal holes.
>>>> I hope this description helps. I can't really give you more detailed
>>>> description due to the fact that I have developed software that does this
>>>> very thing for my employer, but what you want is certainly possible.
>>>> Also, as for whether or not we would want a geojson export function
>>>> available for matplotlib, it isn't really correct to have it in matplotlib
>>>> because we are a graphing library. However, it would make sense to make the
>>>> process of extracting the polygon information a bit easier, which would
>>>> make it easier for another package to be made that would export that
>>>> information into various data formats, not just geojson.
>>>> Cheers!
>>>> Ben Root
>>>> On Mon, Nov 30, 2015 at 12:46 PM, Francis Chabouis <fchabouis at gmail.com
>>>> > wrote:
>>>>> Hello,
>>>>> I'm having some difficulties with the results of the tricontour
>>>>> function. What I'm trying to achieve is fairly simple : I'd like to export
>>>>> the results of the tricontour function as a geoJson. (I think a function
>>>>> doing exactly this job would be nice to have in the library).
>>>>> I wrote this :
>>>>> cs = plt.tricontourf(t, v, levels)
>>>>> for i,collection in enumerate(cs.collections):
>>>>>     for path in collection.get_paths():
>>>>> Now I have this path object.
>>>>> My first problem : when I check the number of vertices (via
>>>>> len(path.vertices)) I get 732 vertices.
>>>>> If I try to access those vertices with iter_segments as recommended in
>>>>> the doc, I get only 125 vertices.
>>>>> seg = path.iter_segments()
>>>>> print len(list(seg))
>>>>> ==> 125
>>>>> Am I doing something wrong, or is it possibly a bug ?
>>>>> My second problem : geoJson works with interior and exterior rings. To
>>>>> describe a polygon with a hole in it, we first declare a closed line (that
>>>>> will be the exterior) and all the subsequent lines will be the "holes"
>>>>> (interiors). It seems that what I get from iter_segments and to_polygons is
>>>>> a bunch of lines, but there is no way to know which is an interior, which
>>>>> is an exterior. But I guess this must be stored somewhere as MPL is able to
>>>>> draw a graph from this information !
>>>>> Any hints on how I should proceed ?
>>>>> Let me know if you need additional information.
>>>>> Thanks
>>>>> ps : I got some of my infos from this thread :
>>>>> http://matplotlib.1069221.n5.nabble.com/Structure-of-contour-object-returned-from-tricontourf-td44203.html
>>>>> ps2 : If I can write this function I would be happy to integrate it in
>>>>> the lib if you're interested.
>>>>> _______________________________________________
>>>>> Matplotlib-users mailing list
>>>>> Matplotlib-users at python.org
>>>>> https://mail.python.org/mailman/listinfo/matplotlib-users
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