Beispiel #1
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    def get_generation(self, generation):
        result = self.store.get_genomes(self.name, generation)

        if result:
            self.searched_generation = []

            for i in result:
                g = song(i[1], i[2], i[3], i[4], i[5], i[6], i[7], i[8])
                self.searched_generation.append(g)
Beispiel #2
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    def get_generation(self, generation):
        result = self.store.get_genomes(self.name, generation)

        if result:
            self.searched_generation = []
            
            for i in result:
                g = song(i[1], i[2], i[3], i[4], i[5], i[6], i[7], i[8])
                self.searched_generation.append(g)
Beispiel #3
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    def get_current_generation(self):
        result = self.store.get_genomes(self.name, self.generation_count)

        if result:
            self.current_generation = []

            for i in result:
                g = song(i[1], i[2], i[3], i[4], i[5], i[6], i[7], i[8])
                self.current_generation.append(g)

        return
Beispiel #4
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    def get_current_generation(self):
        result = self.store.get_genomes(self.name, self.generation_count)

        if result:
            self.current_generation = []

            for i in result:
                g = song(i[1], i[2], i[3], i[4], i[5], i[6], i[7], i[8])
                self.current_generation.append(g)

        return
Beispiel #5
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    def initialize(self, console=None):
        self.current_generation = []

        for i in xrange(self.population_size):
            g = song(operators.random_genome(), self.name, 0, i)
            self.current_generation.append(g)

        self.state = 'evaluate'
        self.save_genomes()
        self.save()

        if console:
            console('%s is initialized' % self.name)
        return
Beispiel #6
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    def initialize(self, console = None):
        self.current_generation = []

        for i in xrange(self.population_size):
            g = song(operators.random_genome(), self.name, 0, i)
            self.current_generation.append(g)

        self.state = 'evaluate'
        self.save_genomes()
        self.save()

        if console:
            console('%s is initialized'%self.name)
        return
Beispiel #7
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    def reproduce(self, console=None):
        self.generation_count += 1

        console('%s : reproducing of generation %d started' %
                (self.name, self.generation_count))

        pool = []

        index = 0
        while self.current_generation:
            l = len(self.current_generation) - 1

            if not l:
                break

            a = operators.r(l)

            parent_1 = self.current_generation[a]
            del self.current_generation[a]

            a = operators.r(l - 1)
            parent_2 = self.current_generation[a]

            del self.current_generation[a]

            child_1_g, child_2_g = operators.random_crossover(
                parent_1.note_list, parent_2.note_list)
            operators.random_mutator(child_1_g)
            operators.random_mutator(child_2_g)

            parent_1.individual_id = index
            parent_1.status = 'created'
            parent_1.generation = self.generation_count
            parent_1.grade = 0.0
            index += 1

            parent_2.individual_id = index
            parent_2.status = 'created'
            parent_2.generation = self.generation_count
            parent_2.grade = 0.0
            index += 1

            child_1 = song(child_1_g, self.name, self.generation_count, index,
                           parent_1.name, parent_2.name)
            index += 1

            child_2 = song(child_2_g, self.name, self.generation_count, index,
                           parent_1.name, parent_2.name)
            index += 1

            t = parent_1.note_list
            operators.random_mutator(t)
            parent_1.set_genome(t)

            t = parent_2.note_list
            operators.random_mutator(t)
            parent_2.set_genome(t)

            pool += [parent_1, parent_2, child_1, child_2]

            console('created %s and %s from %s and %s' %
                    (child_1.name, child_2.name, parent_1.name, parent_2.name))

        self.current_generation = pool

        self.save()
        self.save_genomes()
        self.state = 'evaluate'
        console('%s : created generation %d' %
                (self.name, self.generation_count))
Beispiel #8
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    def reproduce(self, console = None):
        self.generation_count += 1

        console('%s : reproducing of generation %d started'%(self.name, self.generation_count))

        pool = []
        
        index = 0
        while self.current_generation:
            l = len(self.current_generation) - 1

            if not l:
                break

            a = operators.r(l)

            parent_1 = self.current_generation[a]
            del self.current_generation[a]

            a = operators.r(l - 1)
            parent_2 = self.current_generation[a]

            del self.current_generation[a]

            child_1_g, child_2_g = operators.random_crossover(parent_1.note_list,
                                                              parent_2.note_list)
            operators.random_mutator(child_1_g)
            operators.random_mutator(child_2_g)

            parent_1.individual_id = index
            parent_1.status = 'created'
            parent_1.generation = self.generation_count
            parent_1.grade = 0.0
            index += 1

            parent_2.individual_id = index
            parent_2.status = 'created'
            parent_2.generation = self.generation_count
            parent_2.grade = 0.0
            index += 1

            child_1 = song(child_1_g,
                           self.name,
                           self.generation_count,
                           index,
                           parent_1.name,
                           parent_2.name)
            index += 1

            child_2 = song(child_2_g,
                           self.name,
                           self.generation_count,
                           index,
                           parent_1.name,
                           parent_2.name)
            index += 1

            t = parent_1.note_list
            operators.random_mutator(t)
            parent_1.set_genome(t)

            t = parent_2.note_list
            operators.random_mutator(t)
            parent_2.set_genome(t)

            pool += [parent_1, parent_2, child_1, child_2]

            console('created %s and %s from %s and %s'%(child_1.name, child_2.name, parent_1.name, parent_2.name))

        self.current_generation = pool

        self.save()
        self.save_genomes()
        self.state = 'evaluate'
        console('%s : created generation %d'%(self.name, self.generation_count))