Hello Mickael

Michael Bedward a écrit :
> Then there is another project where I am working on simulations of
> animal populations where the summed value of habitat resources
> available to an animal is constrained by the presence of other animal
> territories.

This is a nice example, but I wonder: using a mask in this case means applying
the contraints in a "all or nothing" fashion. This is quite convenient for
exploratory work. But as the model become more elaborate, I would intuitively (I
may be totally wrong - I work more with oceans than habitats) expect the "all or
nothing" behavior to be replaced by some sigmoid function like the one used in
artificial neural network (http://en.wikipedia.org/wiki/Sigmoid_function). So if
R is the habitat resources, T the other animal territories and S some sigmoid
function, I would be tempted to compute the convolution (without mask) of:

  R * S(T)

Using a mask could be seen as a special case of the above formula where S is a
function going from 0 to 1 at a threshold value, without intermediate values.
The advantage of the above formula instead than a mask is to allow modelizer to
experiment different S functions having intermediate values, which is probably
closer to the real world.


> One can also imagine making the operator (or probably a second
> operator) use a set of rules prescribing how to respond to source
> image values directly rather than using separate controlling images.
> I imagine this would result in slow processing - but it would avoid
> the need to construct ROIs or similar so might be preferable in some
> cases such as your example of differently valued NaNs in a source
> image.

I don't have a clear opinion on this topic since I believe that it depends on
the experience gained with pratical work, and this experience is likely to vary
in different applications. The rules approach is nice if the rules can be simple
and "universal" enough, otherwise controlling images are preferable. But my
notion of "universal" is biased toward what I have seen in oceanography
(continuous functions are more frequent than discontinuities, hence my
preference for a sigmoid function in my previous paragraph), and my position
sometime change with time... So I can not really emmit a reliable advice here.

        Regards,

                Martin

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