def train(self):
        self.totalepochs += 1

        if self.totalepochs - self._max_fitness_epoch >= self.nBurstMutationEpochs:
            if self.verbosity: print("RUNNING BURST MUTATION")
            self.burstMutate()
            self._max_fitness_epoch = self.totalepochs


        for filter in self._filters:
            filter.apply(self._population)

        if self._max_fitness < self.evaluation.max_fitness:
            if self.verbosity: print(("GAINED FITNESS: ", self._max_fitness, " -->" , self.evaluation.max_fitness, "\n"))
            self._max_fitness = self.evaluation.max_fitness
            self._max_fitness_epoch = self.totalepochs
        else:
            if self.verbosity: print(("DIDN'T GAIN FITNESS:", "best =", self._max_fitness, "    current-best = ", self.evaluation.max_fitness, "\n"))
Evolve for one epoch.
dataset/ETHPy150Open pybrain/pybrain/pybrain/supervised/trainers/evolino.py/EvolinoTrainer.train