"""

Build a PDF report for a small multi-objective GA run.

Requires the optional ``report`` extra: pip install pygad[report].

The output file ``pygad_report.pdf`` is written next to this script.

"""

import numpy

import pygad

def fitness_func(ga_instance, solution, solution_idx):

return [float(numpy.sum(solution)),

-float(numpy.sum(numpy.asarray(solution) ** 2))]

ga_instance = pygad.GA(num_generations=30,

num_parents_mating=8,

fitness_func=fitness_func,

sol_per_pop=20,

num_genes=4,

parent_selection_type="nsga2",

save_solutions=True,

random_seed=42,

suppress_warnings=True,)

ga_instance.run()

output_path = ga_instance.generate_report(filename="pygad_report",

title="PyGAD multi-objective demo",

notes="A short two-objective example with 30 generations.",)

print(f"Report written to: {output_path}")