Analog of processing map() or protovis scale?

Community matplotlib-users
1

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
laserson@…2705…66…

2

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

3

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
laserson@…1166…

···

On Sun, Jan 16, 2011 at 21:23, Paul Ivanov <pivanov314@…287…> 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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