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On Tue, Jan 7, 2014 at 2:29 PM, Adam Hughes <hug...@gm...> wrote:

> Sorry, quick followup.  I did find the gallery example to plot multiple
> patches together:
>
> http://matplotlib.org/examples/api/patch_collection.html
>
> That's excellent.  Now I guess my question is how best to generalize the
> process of turning my objects into patches.  I think I will just try to
> keep the geometry (ie line --> mpatch.Line) unless anyone has any better
> suggestions.
>

As you've already found out, it sounds like you want a PatchCollection.

There is one catch, though.  Your lines/curves will need to be converted to
PathPatches (which is trivial), which can then have a facecolor.  Because
all items in a collection will have the same facecolor by default, this
means that your lines will become "filled" polygons, unless you specify
otherwise.

Therefore, you'll need to do something like this:

import matplotlib.pyplot as plt
from matplotlib.path import Path
import matplotlib.patches as mpatches
from matplotlib.collections import PatchCollection

# Just a simple line, but it could be a bezier curve, etc.
line = Path([(-20, -20), (-10, 10), (20, 20)])

# We'll need to convert the line to a PathPatch, and we'll throw in a
circle, too
line = mpatches.PathPatch(line)
circle = mpatches.Circle([0, 0])

# If we don't specify facecolor='none' for the line, it will be filled!
col = PatchCollection([line, circle], facecolors=['none', 'red'])

fig, ax = plt.subplots()
ax.add_collection(col)
ax.autoscale()
plt.show()

Alternatively, you can just put the lines/curves in a PathCollection and
the patches/polygons/etc in a PatchCollection.

Hope that helps!
-Joe


>
> Thanks!
>
>
> On Tue, Jan 7, 2014 at 3:08 PM, Adam Hughes <hug...@gm...>wrote:
>
>> Hi,
>>
>> I am working on a library for image analysis which stores particles as
>> indexed numpy arrays and provides functionality for managing the particles
>> beyond merely image masking or altering the arrays directly.  I've already
>> designed classes for many common shapes including Lines/Curves,
>> Circles/Ellipses, Polygons, Multi-shapes (eg 4 circles with variable
>> overlap).
>>
>> What I'd really LOVE to do would be able to generate a
>> matplotlib.Collection instance from these objects as generally as possible.
>>  Then, I'd be able to show data as a masked image, but also get a really
>> nice looking plot from the objects in their Collection representation.
>>
>> So my question really is in the implementation.  First, is there a
>> general collection object that could work with ANY shape, or am I better
>> off matching my shape to that collection?  For example:
>>
>>     line --> LineCollection       *vs.*    line --> GeneralCollection
>>     circle --> CircleCollection           circle ---> GeneralCollection
>>
>> And then, is the Collections plotting API flexible enough to mix all of
>> these types together?  Or would I have to settle for only being able to
>> plot a collection of any 1 shape type at at time?
>>
>> I will delve into the API further, but ascertaining this information
>> would really help me get started.
>>
>> Thanks
>>
>
>
>
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Adam,

Not sure if this is the try you're trying to bark up, but I've used a total
hack to do what I think you're describing:
 1) store lists of coordinate pairs in a pandas DataFrame
 2) use df.apply() to turn each list of coords in to a patch and add to an
axes object

I'm sure you know this, but for posterity's sake, I'll mention that you
*really* should only store primitives in pandas DataFrames. For that reason
alone, I would describe the method above as the death-throes of a failing
project trying to meet deadlines.

Perhaps a more robust way would be to store the coordinates in a "long"
format, i.e.,

shapeid, vertexid, x, y
1,1,0,0
1,2,1,1
1,3,2,2
2,1,10,10
2,2,11,11
3,3,12,12
...

And the group that DataFrame by `shapeid` and use `apply` on the pandas
GroupBy object to construct a patch and add it to an axes object.

Just a thought.


On Tue, Jan 7, 2014 at 12:29 PM, Adam Hughes <hug...@gm...> wrote:

> Sorry, quick followup.  I did find the gallery example to plot multiple
> patches together:
>
> http://matplotlib.org/examples/api/patch_collection.html
>
> That's excellent.  Now I guess my question is how best to generalize the
> process of turning my objects into patches.  I think I will just try to
> keep the geometry (ie line --> mpatch.Line) unless anyone has any better
> suggestions.
>
> Thanks!
>
>
> On Tue, Jan 7, 2014 at 3:08 PM, Adam Hughes <hug...@gm...>wrote:
>
>> Hi,
>>
>> I am working on a library for image analysis which stores particles as
>> indexed numpy arrays and provides functionality for managing the particles
>> beyond merely image masking or altering the arrays directly.  I've already
>> designed classes for many common shapes including Lines/Curves,
>> Circles/Ellipses, Polygons, Multi-shapes (eg 4 circles with variable
>> overlap).
>>
>> What I'd really LOVE to do would be able to generate a
>> matplotlib.Collection instance from these objects as generally as possible.
>>  Then, I'd be able to show data as a masked image, but also get a really
>> nice looking plot from the objects in their Collection representation.
>>
>> So my question really is in the implementation.  First, is there a
>> general collection object that could work with ANY shape, or am I better
>> off matching my shape to that collection?  For example:
>>
>>     line --> LineCollection       *vs.*    line --> GeneralCollection
>>     circle --> CircleCollection           circle ---> GeneralCollection
>>
>> And then, is the Collections plotting API flexible enough to mix all of
>> these types together?  Or would I have to settle for only being able to
>> plot a collection of any 1 shape type at at time?
>>
>> I will delve into the API further, but ascertaining this information
>> would really help me get started.
>>
>> Thanks
>>
>
>
>
> ------------------------------------------------------------------------------
> Rapidly troubleshoot problems before they affect your business. Most IT
> organizations don't have a clear picture of how application performance
> affects their revenue. With AppDynamics, you get 100% visibility into your
> Java,.NET, & PHP application. Start your 15-day FREE TRIAL of AppDynamics
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> _______________________________________________
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> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Sorry, quick followup.  I did find the gallery example to plot multiple
patches together:

http://matplotlib.org/examples/api/patch_collection.html

That's excellent.  Now I guess my question is how best to generalize the
process of turning my objects into patches.  I think I will just try to
keep the geometry (ie line --> mpatch.Line) unless anyone has any better
suggestions.

Thanks!


On Tue, Jan 7, 2014 at 3:08 PM, Adam Hughes <hug...@gm...> wrote:

> Hi,
>
> I am working on a library for image analysis which stores particles as
> indexed numpy arrays and provides functionality for managing the particles
> beyond merely image masking or altering the arrays directly.  I've already
> designed classes for many common shapes including Lines/Curves,
> Circles/Ellipses, Polygons, Multi-shapes (eg 4 circles with variable
> overlap).
>
> What I'd really LOVE to do would be able to generate a
> matplotlib.Collection instance from these objects as generally as possible.
>  Then, I'd be able to show data as a masked image, but also get a really
> nice looking plot from the objects in their Collection representation.
>
> So my question really is in the implementation.  First, is there a general
> collection object that could work with ANY shape, or am I better off
> matching my shape to that collection?  For example:
>
>     line --> LineCollection       *vs.*    line --> GeneralCollection
>     circle --> CircleCollection           circle ---> GeneralCollection
>
> And then, is the Collections plotting API flexible enough to mix all of
> these types together?  Or would I have to settle for only being able to
> plot a collection of any 1 shape type at at time?
>
> I will delve into the API further, but ascertaining this information would
> really help me get started.
>
> Thanks
>

Hi,

I am working on a library for image analysis which stores particles as
indexed numpy arrays and provides functionality for managing the particles
beyond merely image masking or altering the arrays directly.  I've already
designed classes for many common shapes including Lines/Curves,
Circles/Ellipses, Polygons, Multi-shapes (eg 4 circles with variable
overlap).

What I'd really LOVE to do would be able to generate a
matplotlib.Collection instance from these objects as generally as possible.
 Then, I'd be able to show data as a masked image, but also get a really
nice looking plot from the objects in their Collection representation.

So my question really is in the implementation.  First, is there a general
collection object that could work with ANY shape, or am I better off
matching my shape to that collection?  For example:

    line --> LineCollection       *vs.*    line --> GeneralCollection
    circle --> CircleCollection           circle ---> GeneralCollection

And then, is the Collections plotting API flexible enough to mix all of
these types together?  Or would I have to settle for only being able to
plot a collection of any 1 shape type at at time?

I will delve into the API further, but ascertaining this information would
really help me get started.

Thanks

On 07.01.2014 18:18, Fabrice Silva wrote:
> Le mardi 07 janvier 2014 à 17:57 +0100, V. Armando Sole a écrit :
>> > What about using axvline with the picker argument?
>> > see http://matplotlib.org/users/event_handling.html
>> >
>>
>> I think axvline is part of the pyplot interface that I am not using.
>>
>> However your link is going to help me a lot. I thought picking was
>> restricted to patches, and I had missed Line2D is an Artist too with 
>> the
>> same capabilities.
>
> axvline is a pyplot function, but it is also a method of the Axes 
> class.
> So if you have an Axes in your Figure, everything is ok
> http://matplotlib.org/api/axes_api.html#matplotlib.axes.Axes.axvline
>

Even better :-)

Thanks a lot,

Armando

Le mardi 07 janvier 2014 à 17:57 +0100, V. Armando Sole a écrit :
> > What about using axvline with the picker argument?
> > see http://matplotlib.org/users/event_handling.html
> >
> 
> I think axvline is part of the pyplot interface that I am not using.
> 
> However your link is going to help me a lot. I thought picking was 
> restricted to patches, and I had missed Line2D is an Artist too with the 
> same capabilities.

axvline is a pyplot function, but it is also a method of the Axes class.
So if you have an Axes in your Figure, everything is ok
http://matplotlib.org/api/axes_api.html#matplotlib.axes.Axes.axvline

regards

> I believe (as of v1.3.1) that after you create the legend you call
> leg.draggable(True)
> http://matplotlib.org/api/legend_api.html#matplotlib.legend.Legend.draggable

Outstanding! (Google was not my friend here. I wasn't searching for
"draggable.")

Skip

On 07.01.2014 16:27, Fabrice Silva wrote:
> Le mardi 07 janvier 2014 à 15:19 +0100, "V. Armando Solé" a écrit :
>> Hello,
>>
>> I am trying to add some vertical lines into a matplotlib figure 
>> axes.
>>
>> The idea is to detect when the mouse passes over those lines in 
>> order to
>> displace them following the mouse if the left button is pressed.
>>
>> I need some help to know the simplest way to proceed. Currently I am
>> looking into matplotlib.patches and considering to use a Polygon or 
>> a
>> Rectangle but perhaps that solution is overkill for a simple line. 
>> Is
>> there any example about how to do it? I am not using the pyplot
>> interface but instantiating myself the Figure,  the FigureCanvas and
>> adding the axes to the figure.
>
> What about using axvline with the picker argument?
> see http://matplotlib.org/users/event_handling.html
>

I think axvline is part of the pyplot interface that I am not using.

However your link is going to help me a lot. I thought picking was 
restricted to patches, and I had missed Line2D is an Artist too with the 
same capabilities.

Armando

I believe (as of v1.3.1) that after you create the legend you call
leg.draggable(True)
http://matplotlib.org/api/legend_api.html#matplotlib.legend.Legend.draggable



On Tue, Jan 7, 2014 at 6:37 AM, Skip Montanaro <sk...@po...> wrote:

> Sometimes the legend simply gets in the way. You can't always guess
> the correct placement (think generic tool which processes lots of
> different input data sets), or zooming/panning makes it obscure a
> chunk of the plot you want to look at. Is it possible to move it
> interactively? I'm using mpl 1.3.1.
>
> Thx,
>
> Skip
>
>
> ------------------------------------------------------------------------------
> Rapidly troubleshoot problems before they affect your business. Most IT
> organizations don't have a clear picture of how application performance
> affects their revenue. With AppDynamics, you get 100% visibility into your
> Java,.NET, & PHP application. Start your 15-day FREE TRIAL of AppDynamics
> Pro!
> http://pubads.g.doubleclick.net/gampad/clk?id=84349831&iu=/4140/ostg.clktrk
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>

Le mardi 07 janvier 2014 à 15:19 +0100, "V. Armando Solé" a écrit :
> Hello,
> 
> I am trying to add some vertical lines into a matplotlib figure axes.
> 
> The idea is to detect when the mouse passes over those lines in order to 
> displace them following the mouse if the left button is pressed.
> 
> I need some help to know the simplest way to proceed. Currently I am 
> looking into matplotlib.patches and considering to use a Polygon or a 
> Rectangle but perhaps that solution is overkill for a simple line. Is 
> there any example about how to do it? I am not using the pyplot 
> interface but instantiating myself the Figure,  the FigureCanvas and 
> adding the axes to the figure.

What about using axvline with the picker argument?
see http://matplotlib.org/users/event_handling.html

Sometimes the legend simply gets in the way. You can't always guess
the correct placement (think generic tool which processes lots of
different input data sets), or zooming/panning makes it obscure a
chunk of the plot you want to look at. Is it possible to move it
interactively? I'm using mpl 1.3.1.

Thx,

Skip

Hello,

I am trying to add some vertical lines into a matplotlib figure axes.

The idea is to detect when the mouse passes over those lines in order to 
displace them following the mouse if the left button is pressed.

I need some help to know the simplest way to proceed. Currently I am 
looking into matplotlib.patches and considering to use a Polygon or a 
Rectangle but perhaps that solution is overkill for a simple line. Is 
there any example about how to do it? I am not using the pyplot 
interface but instantiating myself the Figure,  the FigureCanvas and 
adding the axes to the figure.

Thanks for your time,

Armando