The GP and the GA can be run via the find_prime_polynomial()-function in Callables.py. The function has the following parameters: Constructor :param constructor: list of Fitness enums :param fitness_functions: Selectively choose between 3 functions (MSE has hard-coded labels, do not use for prime GP) int :param num_populations: Number of populations float :param merge_point: percentage for population size to shrink for population merges int :param population_size: number of trees/functions/polynomials in a population (int, int) :param test_interval: interval to test fitness on float :param birth_rate: replenishing rate float :param mutation: mutation rate (int, int) :param coeffs_bound: terminal/coefficient bounds int :param constraint: order/depth limit list of functions :param operator_functions: list of functions the GP can use to build trees Tree_Population :return: Object that contains fitness history and final polynomial/function/tree

The final tree can be accessed via population.polynomials[0]. It can be evaluated with its function called eval_polynomial(x), where x can be a vector or scalar. It is best to look at the examples in the jupyter notebook provided.