[Scilab-users] circshift() : Scilab Enhancement Proposal

[Rafael Guerra]

Hi Samuel,

The functionality is very nice but the syntax proposed is maybe a bit complicated?
It would be easier to combine ‘newSizes’ with a new ‘shift’ argument (but with no wrapping as proposed in circshift).
For example:

 m  =
   2.   5.   9.   3.
   2.   4.   5.   5.
   4.   1.   8.   5.

resize_matrix(m, newSizes=[5 7], shift=[1 2])
 ans  =
   0.   0.   0.   0.   0.   0.   0.
   0.   0.   2.   5.   9.   3.   0.
   0.   0.   2.   4.   5.   5.   0.
   0.   0.   4.   1.   8.   5.   0.
   0.   0.   0.   0.   0.   0.   0.

resize_matrix(m, newSizes=[-1 -1], shift=[-1 -2])
 ans  =
   5.   5.   0.   0.
   8.   5.   0.   0.
   0.   0.   0.   0.


Regarding extending circshift() to non-integers I had in mind n-dimensional matrices and the discrete Fourier transform.
These matrices could represent regularly sampled 1D time signals, or 2D/3D spatial functions, etc.
In this context the shift theorem gives a specific meaning to the circular shifts of the input signals (corresponding to linear phase shifts in their spectrum).

Regards,
Rafael

From: users [mailto:users-bounces at lists.scilab.org] On Behalf Of Samuel Gougeon
Sent: Tuesday, January 09, 2018 8:26 PM
To: Users mailing list for Scilab <users at lists.scilab.org>
Subject: Re: [Scilab-users] circshift() : Scilab Enhancement Proposal

Hello Rafael,

To go on about resize_matrix() , padding, and shifting without wrapping:
Specifying a (N>1 x 2) matrix of positive (pad) or negative (trim) margins resizing
would be simple.
Padding with other default elements for non-numerical arrays, or with a chosen
value, is already enabled.
Possible new syntaxes and examples of usages:



resMat = resize_matrix(mat, frameWidth)

resMat = resize_matrix(mat, frameWidth, ..)



m = [

  6 -7 -1 -2

 -6  0 -2 -5

 -5  4 -1  8

  ];



// shift without extension nor wrapping:

resize_matrix(m, [0 0 ; -1 1])

ans =

  -7 -1 -2  0

   0 -2 -5  0

   4 -1  8  0



// Another case without extensions nor wrapping:

resize_matrix(m, [1 -1 ; 2 -2])

ans =

0  0  0  0

0  0  6 -7

0  0 -6  0



// More general

resize_matrix(m, [2 1 ; 1 -1])

ans =

0  0  0  0

0  0  0  0

0  6 -7 -1

0 -6  0 -2

0 -5  4 -1

0  0  0  0




Is it the kind of features you were thinking about?

IMO, there is no need to implement this in another specific function, because these features are just particular cases or resizing, with a simple syntax allowing to crop borders as well.

Best regards
Samuel
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