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https://issues.apache.org/jira/browse/MATH-1267?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14737533#comment-14737533
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Gilles commented on MATH-1267:
------------------------------

{quote}
The design idea that I'm advocating comes from MVC theory, hence the references 
to things you can do. I think it's nice that you can do these things and that 
the design easily supports it, even though the classes are purely used for 
computation ATM.
{quote}

What are the things that the design does not support?

{quote}
Even though there may not be a Neuron at every point in a square mesh / 
coordinate system, we can still think of a Neuron as belonging to a row, column 
coordinate, right?
{quote}

It depends.
If the network is static and has uniform density, yes.  If not, no.
Even in the former case, in an hexagonal layout, the (row, column) concept is 
not that useful I think (because the network is not the grid anymore).

Then when the network is adaptive:
Before:
{noformat}
       *-----*-----X
       |     |     |
       *-----*-----*
{noformat}
Neuron "X" is at (0, 2).
After adding a neuron:
{noformat}
       *-----*--*--X
       |     |     |
       *-----*-----*
{noformat}
Neuron "X" is at (0, 3).

Hence the "Neuron2D" coordinates of "X" have become wrong.

> Grid coordinate of "Neuron" that belongs to a "NeuronSquareMesh2D"
> ------------------------------------------------------------------
>
>                 Key: MATH-1267
>                 URL: https://issues.apache.org/jira/browse/MATH-1267
>             Project: Commons Math
>          Issue Type: Wish
>            Reporter: Gilles
>            Assignee: Gilles
>            Priority: Minor
>             Fix For: 4.0, 3.6
>
>         Attachments: LocationFinder.java
>
>
> When the network layout is a 2D grid, it useful to be able to retrieve the 
> grid coordinate (row, column) of a a neuron.
> I propose to define a new class "LocationFinder" (in package 
> "o.a.c.m.ml.neuralnet.twod.util") that will provide the functionality through 
> a "getLocation(Neuron n)" method.



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