With food, however it come.
The B cells are the adaptive encoder, we already know the relative concentrations, there are four of them. Realattive to them, you already know the number of macrophages showing up. And loose food.
You are looking for the paths between some mix of food and the group of B cells mostly likely o consume just that mix. You are trying to color a literal surface, an internal surface of tissue. What you need are all the paths from the proper eaters to the proper food. One complete sequence, on area or density of tissue that contains all the components to bring the balance is what you need, and from that count make your color operator. It will have some complex selection paths from one set of corrections to another, and you may have many of too few degrees of motion in your restrictions.. Order the possible outcome by deviations in count, how shots of action is needed to fill the void.
Computer programs can search your conditions off line and merge paths systematically to re run the model. This is not your basically modeling in economics, these numbers the docs have on tissue and propagation steps are pretty hard numbers. There charts of protein derivations steps almost fit right into this kind of discrete step model.
When you add the conditonals and coefficients on each pass then you are effecting the system via N density. The largest concentration of B cell will over count a bit, and that provides the kinetic energy. This is sniff and reject.
Why not make a fake operators, give it 15 items of four colors. Order he count for each of your four colors, let the computer draw colored dots and give us a show. You know your deviation counts, just maximize separation between your lowest counter, all you need is counts per set.
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