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Update all numpy.max to numpy.nanmax in pygad.py #87

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Update all numpy.max to numpy.nanmax in pygad.py #87

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6 changes: 3 additions & 3 deletions pygad.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1312,7 +1312,7 @@ def run(self):
_, best_solution_fitness, _ = self.best_solution(pop_fitness=self.last_generation_fitness)
self.best_solutions_fitness.append(best_solution_fitness)

self.best_solution_generation = numpy.where(numpy.array(self.best_solutions_fitness) == numpy.max(numpy.array(self.best_solutions_fitness)))[0][0]
self.best_solution_generation = numpy.where(numpy.array(self.best_solutions_fitness) == numpy.nanmax(numpy.array(self.best_solutions_fitness)))[0][0]
# After the run() method completes, the run_completed flag is changed from False to True.
self.run_completed = True # Set to True only after the run() method completes gracefully.

Expand Down Expand Up @@ -1411,7 +1411,7 @@ def tournament_selection(self, fitness, num_parents):
for parent_num in range(num_parents):
rand_indices = numpy.random.randint(low=0.0, high=len(fitness), size=self.K_tournament)
K_fitnesses = fitness[rand_indices]
selected_parent_idx = numpy.where(K_fitnesses == numpy.max(K_fitnesses))[0][0]
selected_parent_idx = numpy.where(K_fitnesses == numpy.nanmax(K_fitnesses))[0][0]
parents_indices.append(selected_parent_idx)
parents[parent_num, :] = self.population[rand_indices[selected_parent_idx], :].copy()

Expand Down Expand Up @@ -3121,7 +3121,7 @@ def best_solution(self, pop_fitness=None):
if pop_fitness is None:
pop_fitness = self.cal_pop_fitness()
# Then return the index of that solution corresponding to the best fitness.
best_match_idx = numpy.where(pop_fitness == numpy.max(pop_fitness))[0][0]
best_match_idx = numpy.where(pop_fitness == numpy.nanmax(pop_fitness))[0][0]

best_solution = self.population[best_match_idx, :].copy()
best_solution_fitness = pop_fitness[best_match_idx]
Expand Down