matplotlib-users

 [Matplotlib-users] Analog of processing map() or protovis scale? From: Uri Laserson - 2011-01-16 22:41:31 Attachments: Message as HTML ```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@... ```
 Re: [Matplotlib-users] Analog of processing map() or protovis scale? From: Paul Ivanov - 2011-01-17 02:23:56 Attachments: application/pgp-signature ```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 ```
 Re: [Matplotlib-users] Analog of processing map() or protovis scale? From: Uri Laserson - 2011-01-17 08:39:13 Attachments: Message as HTML ```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@... On Sun, Jan 16, 2011 at 21:23, Paul Ivanov 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 > > -----BEGIN PGP SIGNATURE----- > Version: GnuPG v1.4.10 (GNU/Linux) > > iEYEARECAAYFAk0zqBAACgkQe+cmRQ8+KPcfSwCdGJp3J4uENsx11VMKAJdxkLEG > SEMAn1qqBYY8G6M1bcsfl7+7yc3doKiw > =x2vj > -----END PGP SIGNATURE----- > > > ------------------------------------------------------------------------------ > Protect Your Site and Customers from Malware Attacks > Learn about various malware tactics and how to avoid them. Understand > malware threats, the impact they can have on your business, and how you > can protect your company and customers by using code signing. > http://p.sf.net/sfu/oracle-sfdevnl > _______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > ```