Procedures

Dynamical adjustment of mutation rate:

breeds two parent chromosomes into two offspring chromosomes. breeding occurs through crossover. If the crossover probability test yields true (crossover taking place), either one-point or two-point crossover is used, with equal probabilities.

decode genotype into phenotype parameters ph(k) are x,y coordinates [ 0 < x,y < 1 ]

Encode phenotype parameters into integer genotype ph(k) are x,y coordinates [ 0 < x,y < 1 ]

Wrapper for the user's function that is used by the main pikaia routine The x input to this function comes from pikaia, and will be between [0,1].

Full generational replacement: accumulate offspring into new population array

Introduces random mutation in a genotype. Mutations occur at rate pmut at all gene loci.

Replaces old population by new; recomputes fitnesses & ranks

Optimization (maximization) of user-supplied "fitness" function over n-dimensional parameter space x using a basic genetic algorithm method.

Write generation report to standard output

Initialize the random number generator with the input seed value.

Ranks initial population. Calls external sort routine to produce key index and rank order of input array arrin (which is not altered).

Return integer array p which indexes array a in increasing order. Array a is not disturbed. The Quicksort algorithm is used.

Selects two parents from the population, using roulette wheel algorithm with the relative fitnesses of the phenotypes as the "hit" probabilities.

Constructor for the pikaia_class. The routine must be called before the solve routine can be used.

Main pikaia wrapper used by the class.

Steady-state reproduction: insert offspring pair into population only if they are fit enough (replace-random if irep=2 or replace-worst if irep=3).

Return the next pseudo-random deviate from a sequence which is uniformly distributed in the interval [0,1]