Hi,
I tried ds9 and It looks like this is what I would like to do (though I
couldn't try funtools, but what you describe is good). DO you think it is
possible to make something like this with matplotlib?
Thanks a lot for your help,
Chiara
> Date: Wed, 12 Mar 2008 02:55:55 -0400
> From: [EMAIL PROTECTED]
> To: [EMAIL PROTECTED]
> Subject: Re: [Matplotlib-users] Polygon masking possible?
> CC: matplotlib-users@lists.sourceforge.net
>
> Hi,
>
> I often do this with ds9 and funtools.
> ds9 is an astronomy-oriented image viewer (http://hea-www.harvard.edu/RD/ds9/)
> but you can also use it with numpy array.
> Within ds9, you can define regions (ellipse, polynomial, etc) easily
> with a mouse.
> After you define a region (and save it as a file), you can convert it
> to a mask image
> with funtools (funtools is a name of an astronomy-oriented image
> utility pacakge).
> funtools only support fits file (image format in astronomy) so this
> can be a bit tricky, but if you're
> interested i'll send my python wrapper code for it.
>
> So, take a look at ds9 and see it fits your need.
> To view numpy array in ds9,
> *. From python, save the array as a file (tofile method, better use
> "arr" as an extension)
> * in ds9, file-> open others -> open array. You need to select
> array dimension, type and endianness of the array.
>
> Regards,
>
> -JJ
>
>
>
>
>
> On Sat, Mar 8, 2008 at 11:17 AM, Chiara Caronna
> <[EMAIL PROTECTED]> wrote:
> >
> > Hello,
> > I am also interested in masking polygons and defining the polygon by
> > 'clicking' on the image... but I do not know anything about GUI.... does
> > anyone can help? Is there already something implemented?
> > Thanks!
> > Chiara
> >
> > > Date: Wed, 23 Jan 2008 13:50:15 +1300
> > > From: [EMAIL PROTECTED]
> > > To: matplotlib-users@lists.sourceforge.net
> > > Subject: Re: [Matplotlib-users] Polygon masking possible?
> >
> >
> > >
> > > Hi Søren,
> > >
> > > I've put this back on the list in case it's useful to anyone else, or
> > > if there are better suggestions or improvements around. Hope you don't
> > > mind.
> > >
> > > On 22/01/2008, Søren Nielsen <[EMAIL PROTECTED]> wrote:
> > > > Yeah i'd like to see your code if I can..
> > >
> > > import numpy as n
> > >
> > > def get_poly_pts(x, y, shape):
> > > """Creates convex polygon mask from list of corners.
> > >
> > > Parameters
> > > ----------
> > > x : array_like
> > > x co-ordinates of corners
> > > y : array_like
> > > y co-ordinates of corners, in order corresponding to x
> > > shape : array_like
> > > dimension sizes of result
> > >
> > > Returns
> > > -------
> > > build : ndarray
> > > 2-D array of shape shape with values True inside polygon
> > >
> > > Notes
> > > -----
> > > Code is constrained to convex polygons by "inside"
> > > assessment criterion.
> > >
> > > """
> > > x = n.asarray(x)
> > > y = n.asarray(y)
> > > shape = n.asarray(shape)
> > > npts = x.size # should probably assert x.size == y.size
> > > inds = n.indices( shape )
> > > xs = inds[0]
> > > ys = inds[1]
> > > xav = n.round(x.mean()).astype(int)
> > > yav = n.round(y.mean()).astype(int)
> > > for i in xrange(npts): # iterate over pairs of co-ordinates
> > > j = (i + 1) % npts
> > > m = (y[j] - y[i])/(x[j] - x[i])
> > > c = (x[j] * y[i] - x[i] * y[j])/(x[j] - x[i])
> > > thisone = ( ys > m * xs + c )
> > > if thisone[xav, yav] == False:
> > > thisone = ~thisone
> > > if i == 0:
> > > build = thisone
> > > else:
> > > build &= thisone
> > > return build
> > >
> > > (released under BSD licence)
> > >
> > > > I just needed the push over the edge to know how to draw on the canvas,
> > > > mapping clicks etc. since i'm still fairly new to matplotlib, so I think
> > > > your code will be helpfull.
> > >
> > > I hope so. As you can see this code doesn't do any of the drawing or
> > > click collecting, but the cookbook page should be able to guide you
> > > there. Ask again on the list if you have any further questions and
> > > we'll see if we can help.
> > >
> > > Also, the code assumes that the average co-ordinate is inside the
> > > shape - that's true for convex polygons, but not necessarily for
> > > arbitrary ones. I use if after taking a convex hull of a greater list
> > > of points (using the delaunay module in scipy (now in scikits, I
> > > hear)), which ensures convexity. You just need to be aware of that
> > > limitation.
> > >
> > > Cheers,
> > >
> > > A.
> > > --
> > > AJC McMorland, PhD candidate
> > > Physiology, University of Auckland
> > >
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