Thread: [Matplotlib-users] Analog of processing map() or protovis scale?

Hi all,

Does there already exist some python implementation (in MPL or other) of an
easy-to-use 1D scale transformation?  This is something analogous to
processing's map function or protovis's scale functionality.  It would work
something like:

s = linear().domain(5,100).range(13000,15000)

or

s = root(p=5).domain(0.1,0.6).range(0,1)

There could be multiple versions, including linear, log, symlog, root
(power), discrete, etc.

Thanks!
Uri

...................................................................................
Uri Laserson
Graduate Student, Biomedical Engineering
Harvard-MIT Division of Health Sciences and Technology
M +1 917 742 8019
las...@mi...

Uri Laserson, on 2011-01-16 17:41,  wrote:
> Hi all,
> 
> Does there already exist some python implementation (in MPL or other) of an
> easy-to-use 1D scale transformation?  This is something analogous to
> processing's map function or protovis's scale functionality.  It would work
> something like:
> 
> s = linear().domain(5,100).range(13000,15000)
> 
> or
> 
> s = root(p=5).domain(0.1,0.6).range(0,1)
> 
> There could be multiple versions, including linear, log, symlog, root
> (power), discrete, etc.

Hi Uri,

I think that the closest we have matplotlib is
matplotlib.colors.Normalize[1] and matplotlib.colors.LogNorm[2], but
both of these have a fixed range of the 0-1 (which is the reason
they are in colors). Both of these do end up with an inverse
method that you could leverage to get an arbitrary range, though.

1. http://matplotlib.sourceforge.net/api/colors_api.html#matplotlib.colors.Normalize
2. http://matplotlib.sourceforge.net/api/colors_api.html#matplotlib.colors.LogNorm

-- 
Paul Ivanov
314 address only used for lists,  off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7 

For convenience of use, I implemented three simple scales.  I have not yet
tested it rigorously, but the usage is similar to protovis scales.

https://github.com/laserson/pytools/blob/master/scale.py

Uri

...................................................................................
Uri Laserson
Graduate Student, Biomedical Engineering
Harvard-MIT Division of Health Sciences and Technology
M +1 917 742 8019
las...@mi...


On Sun, Jan 16, 2011 at 21:23, Paul Ivanov <piv...@gm...> wrote:

> Uri Laserson, on 2011-01-16 17:41,  wrote:
> > Hi all,
> >
> > Does there already exist some python implementation (in MPL or other) of
> an
> > easy-to-use 1D scale transformation?  This is something analogous to
> > processing's map function or protovis's scale functionality.  It would
> work
> > something like:
> >
> > s = linear().domain(5,100).range(13000,15000)
> >
> > or
> >
> > s = root(p=5).domain(0.1,0.6).range(0,1)
> >
> > There could be multiple versions, including linear, log, symlog, root
> > (power), discrete, etc.
>
> Hi Uri,
>
> I think that the closest we have matplotlib is
> matplotlib.colors.Normalize[1] and matplotlib.colors.LogNorm[2], but
> both of these have a fixed range of the 0-1 (which is the reason
> they are in colors). Both of these do end up with an inverse
> method that you could leverage to get an arbitrary range, though.
>
> 1.
> http://matplotlib.sourceforge.net/api/colors_api.html#matplotlib.colors.Normalize
> 2.
> http://matplotlib.sourceforge.net/api/colors_api.html#matplotlib.colors.LogNorm
>
> --
> Paul Ivanov
> 314 address only used for lists,  off-list direct email at:
> http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7
>
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> =x2vj
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