Re: Function definitions - with clarification

[montgrimpulo <aghte@hotlinemail.com>]

I've tried to figure out how my problem could be programmed
using generic functions and access types. Any comments ?

package paradigm is
   type Individual;
   type Rvp is array (Positive range <>) of Long_Float;
   type Ivq is array (Positive range <>) of Long_Integer;
   type Bvr is array (Positive range <>) of Natural range 0 .. 1;
   type Lux is array (Positive range <>, Positive range <>) of Long_Float;
   type Luy is array (Positive range <>, Positive range <>) of Long_Integer;
   type Individual (P,Q,R : Natural) is record
      X : Rvp (1..P);
      Y : Ivq (1..Q);
      Z : Bvr (1..R);
   end record;

   generic
      with function F (V : Individual) return Long_Float;
      with function G (V : Individual; M : Natural) return Long_Float;
   procedure EA (P1, Q1, R1, Popsize : Natural);

end paradigm;

package body paradigm is

   procedure EA (P1,Q1,R1,Popsize : Natural) is

      type vi is access Individual;
      V : vi := new Individual (P=>P1,Q=>Q1,R=>R1);
      type population is array (1 .. Popsize) of vi; 
   begin
      V.Y(1) := 1;
   end EA;

end paradigm;


On Sunday, June 22, 2014 1:34:09 PM UTC+2, montgrimpulo wrote:
> Here is another try to describe my problem. 
> 
> 
> 
> I want to conduct a genetic search-program. There is a function F (the objective function), 
> 
> and a function G (the constraint function) which I want to define only at runtime. The search-program handles individuals within a population. The size of an individual as well as the size of the population is dynamic and is known at runtime. 
> 
> 
> 
> There is a proposed solution to define (in search.ads)
> 
> 
> 
> ...
> 
> generic 
> 
> with function F (V : Individual) return Float; 
> 
> with function G (V : Individual; M : Positive) return Float; 
> 
> procedure Search (V : Individual); 
> 
> 
> 
> which seems to be an appropriate solution for that part. 
> 
> 
> 
> The search program handles individuals from a population. 
> 
> 
> 
> type x_array is array (positive range <>) of Float; 
> 
> type y_array is array (positive range <>) of Integer; 
> 
> type z_array is array (positive range <>) of Boolean; 
> 
> 
> 
> type Individual (P, Q, R) is record 
> 
> X : x_array (0..P); 
> 
> Y : y_array (0..Q); 
> 
> Z : z_array (0..R); 
> 
> end record; 
> 
> 
> 
> P,Q and R are only known at runtime. 
> 
> 
> 
> A population has a number (Popsize) of individuals (definition see above), which is also only known at runtime. 
> 
> 
> 
> Due to some reading, I learned that dynamic arrays in Ada 
> 
> 
> 
> - can be declared in blocks, meaning no inheritance 
> 
> - by limits passed as parameters in subprograms 
> 
> - by use of linked lists 
> 
> - by use of containers ? 
> 
> - by use of discriminated records ? 
> 
> 
> 
> Using  the proposed record type from above, 
> 
> my search-program may look like: (in search.adb)
> 
> 
> 
> procedure Search (V : Individual) is 
> 
> 
> 
> P : Natural := V.P; 
> 
> Q : Natural := V.Q; 
> 
> R : Natural := V.R; 
> 
> Vi : Individual := V; 
> 
> 
> 
> 
> 
> -- type population is array (1 .. Popsize) of Individual; 
> 
> -- gives: unconstrained element in array declaration 
> 
> 
> 
> ... 
> 
> begin 
> 
> -- fill Vi with distinct values and put it into an (array?, container ?, List ?, whatever) 
> 
> -- to get a population with size Popsize
> 
> -- work on all individuals within that population 
> 
> ... 
> 
> end Search; 
> 
> 
> 
> What I still need is a definition for the population (a collection of Individuals) of size Popsize, which is only defined at runtime.
> 
> 
> 
> I want to use my search program for a specific objective- and for a specific constraint-function with a certain size for an individual and a certain size of population. If I do not find a solution then I want to change some elements, eg. size of the population, size of an individual, or to try modified objective- or constraint-functions. 
> 
> 
> 
> After I have found a solution or not, I want to use the same search program with a new and different objective- and a new and different constraint function with a different size of an individual and  different population size.