[SciPy-user] mapminmax function?

[Scott MacDonald]

Oops, I guess that information would have been helpful.  The description:

%   MAPMINMAX processes matrices by normalizing the minimum and maximum
values
%   of each row to [YMIN, YMAX].

%   MAPMINMAX(X,YMIN,YMAX) takes X and optional parameters,
%     X - NxQ matrix or a 1xTS row cell array of NxQ matrices.
%     YMIN - Minimum value for each row of Y. (Default is -1)
%     YMAX - Maximum value for each row of Y. (Default is +1)
%   and returns,
%     Y - Each MxQ matrix (where M == N) (optional).
%     PS - Process settings, to allow consistent processing of values.

%    Examples
%
%   Here is how to format a matrix so that the minimum and maximum
%   values of each row are mapped to default interval [-1,+1].
%
%     x1 = [1 2 4; 1 1 1; 3 2 2; 0 0 0]
%     [y1,ps] = mapminmax(x1)
%
%   Next, we apply the same processing settings to new values.
%
%     x2 = [5 2 3; 1 1 1; 6 7 3; 0 0 0]
%     y2 = mapminmax('apply',x2,ps)
%
%   Here we reverse the processing of y1 to get x1 again.
%
%     x1_again = mapminmax('reverse',y1,ps)
%
%  Algorithm
%
%     It is assumed that X has only finite real values, and that
%     the elements of each row are not all equal.
%
%     y = (ymax-ymin)*(x-xmin)/(xmax-xmin) + ymin;

On Sun, Jan 4, 2009 at 2:12 PM, Robert Kern <robert.kern at gmail.com> wrote:

> On Sun, Jan 4, 2009 at 13:53, Scott MacDonald
> <scott.p.macdonald at gmail.com> wrote:
> > I was wondering if there is a function analogous to Matlab's mapminmax
> (in
> > the neural network toolbox)?
>
> What does it do?
>
> --
> Robert Kern
>
> "I have come to believe that the whole world is an enigma, a harmless
> enigma that is made terrible by our own mad attempt to interpret it as
> though it had an underlying truth."
>  -- Umberto Eco
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.scipy.org/pipermail/scipy-user/attachments/20090104/da28a7e0/attachment.html>