def test_optimizer_1dim_brent_0(self):
fct = self._init_polynom()
opt = Optimizer1Dim(minimize_algorithm=brent)
result = []
result.append(opt.optimize(fct, Constraint(0.0, 2.0), 1.0))
result.append(opt.optimize(fct, Constraint(0.0, 2.7), 1.0))
result.append(opt.optimize(fct, Constraint(0.0, 4.2), 1.0))
benchmark = []
benchmark.append(OptimizerResult.create_succesful(1.07728364364, -6.07916570029, 32))
benchmark.append(OptimizerResult.create_succesful(1.07728363789, -6.07916570029, 40))
benchmark.append(OptimizerResult.create_succesful(1.07728363067, -6.07916570029, 50))
for i in xrange(3):
self._assert_optimizer_results(benchmark[i], result[i], 7)
def test_optimizer_1dim_golden_0(self):
fct = self._init_polynom()
opt = Optimizer1Dim(minimize_algorithm=golden)
result = []
result.append(opt.optimize(fct, Constraint(0.0, 2.0), 1.0))
result.append(opt.optimize(fct, Constraint(0.0, 2.7), 1.0))
result.append(opt.optimize(fct, Constraint(0.0, 4.2), 1.0))
benchmark = []
benchmark.append(OptimizerResult.create_succesful(1.0, -6.0, 6))
benchmark.append(OptimizerResult.create_succesful(1.0, -6.0, 80))
benchmark.append(OptimizerResult.create_succesful(1.0, -6.0, 80))
for i in xrange(3):
self._assert_optimizer_results(benchmark[i], result[i])
def test_optimizer_1dim_brent_2(self):
fct = lambda x: x * (x - PI) * (x - PI)
constraint = Constraint(0.0, 5.0)
opt = Optimizer1Dim(minimize_algorithm=brent)
result = opt.optimize(fct, constraint, 1.0)
benchmark = OptimizerResult.create_succesful(3.14159265057, 2.87208663251e-17, 43)
self._assert_optimizer_results(benchmark, result)
def test_minimum_bracketing_scaled(self):
constraint = Constraint(0.0, 5.0)
t = TangentsTransformation(constraint)
p = self._init_polynom()
fct = CompositionFct(p, t)
result = mn_brak(0.1, 1.0, fct)
benchmark = (0.1, 1.0, 1.556230591, 46343.60499652936, -8.949238582537712, 1.3006670200315953)
self._assertEqual(benchmark, result, 7)
def test_tangents_tangents_invers_transformation(self):
constraint = Constraint(-30.0, 1002.0)
t = TangentsTransformation(constraint)
tinv = TangentsInverseTransformation(constraint)
values = [-4.2, -2.03, -1.0, 0.0, 1.0, 2.3, 4.5, 1001.01]
for x in values:
z = tinv(t(x))
self.assertAlmostEqual(x, z, 8)
def test_minimize_algorithm_1dim_brent_scaled(self):
constraint = Constraint(0.0, 4.0)
t = TangentsTransformation(constraint)
tinv = TangentsInverseTransformation(constraint)
p = self._init_polynom()
fct = CompositionFct(p, tinv)
result_scaled = brent(fct, t(0.1), t(1.0), t(3.9))
benchmark_rescaled = (-0.8854173749579757, -6.079165700291461)
result = (tinv(result_scaled[0]), result_scaled[1])
benchmark = (1.0772836393669956, -6.079165700291461)
self._assertEqual(benchmark_rescaled, result_scaled)
self._assertEqual(benchmark, result)
def test_optimizer_1dim_brent_1(self):
fct = self._init_polynom()
opt = Optimizer1Dim(minimize_algorithm=brent)
result = opt.optimize(fct, Constraint(-10.0, -2.0), 1.0)
benchmark = OptimizerResult.create_succesful(-3.70107061641, -74.1359364077, 40)
self._assert_optimizer_results(benchmark, result)