Esempio n. 1
0
    def testNsgaii(self):
        pop = [ChromosomeTestImplementation() for i in range(10)]
        self.assertEqual(3, len(pop[0].genes))
        pop = NSGAII.nsgaii(pop, 100)
        
        expected = [5.198961969831384, 0.08305567759063237, 5.9249528286171405, -2.292726823088209, 5.9249528286171405, 2.8836408759525156, -2.292726823088209, 5.9249528286171405, 5.198961969831384, 13.01326687754792]
        actual = [p.x() for p in pop]
        self.assertEqual(expected, actual)

        expected = [-14.893629327366531, -14.893629327366531, -4.073355846562075, -14.893629327366531, -10.698973150220933, -14.893629327366531, -14.893629327366531, -4.073355846562075, -14.893629327366531, 1.956945448043296]
        actual = [p.y() for p in pop]
        self.assertEqual(expected, actual)
Esempio n. 2
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def demonstrate(seed = 42):
    random.seed(seed)
    logger = NSGAII.log_file('demonsga.log')
    pop = [ChromosomeTestImplementation() for i in range(10)]
    return NSGAII.nsgaii(pop, 100, logger.log)
Esempio n. 3
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def evolveMnist(seed = 42):
    logger = NSGAII.log_file('mnistgenerations.log')
    pop = chromosome.initialMnistPopulation(40)
    sys.stdout.flush()
    result = NSGAII.nsgaii(pop, 100, logger.log)
    print result