def runTest(self):
n, m = 2, 2
npt = n + 1
x0 = np.array([-1.2, 1.0])
xl = -1e20 * np.ones((n,))
xu = 1e20 * np.ones((n,))
model = Model(npt, x0, rosenbrock(x0), xl, xu, 1)
self.assertEqual(model.npt(), 1, 'Wrong npt after initialisation')
self.assertTrue(array_compare(model.xopt(abs_coordinates=True), x0), 'Wrong xopt after initialisation')
self.assertTrue(array_compare(model.ropt(), rosenbrock(x0)), 'Wrong ropt after initialisation')
self.assertAlmostEqual(model.fopt(), sumsq(rosenbrock(x0)), 'Wrong fopt after initialisation')
# Now add better point
x1 = np.array([1.0, 0.9])
rvec = rosenbrock(x1)
model.change_point(1, x1 - model.xbase, rvec, allow_kopt_update=True)
self.assertEqual(model.npt(), 2, 'Wrong npt after x1')
self.assertTrue(array_compare(model.xopt(abs_coordinates=True), x1), 'Wrong xopt after x1')
self.assertTrue(array_compare(model.ropt(), rosenbrock(x1)), 'Wrong ropt after x1')
self.assertAlmostEqual(model.fopt(), sumsq(rosenbrock(x1)), 'Wrong fopt after x1')
# Now add worse point
x2 = np.array([2.0, 0.9])
rvec = rosenbrock(x2)
model.change_point(2, x2 - model.xbase, rvec, allow_kopt_update=True)
self.assertEqual(model.npt(), 3, 'Wrong npt after x2')
self.assertTrue(array_compare(model.xpt(0, abs_coordinates=True), x0), 'Wrong xpt(0) after x2')
self.assertTrue(array_compare(model.xpt(1, abs_coordinates=True), x1), 'Wrong xpt(1) after x2')
self.assertTrue(array_compare(model.xpt(2, abs_coordinates=True), x2), 'Wrong xpt(2) after x2')
self.assertTrue(array_compare(model.xopt(abs_coordinates=True), x1), 'Wrong xopt after x2')
self.assertTrue(array_compare(model.ropt(), rosenbrock(x1)), 'Wrong ropt after x2')
self.assertAlmostEqual(model.fopt(), sumsq(rosenbrock(x1)), 'Wrong fopt after x2')
# Now add best point (but don't update kopt)
x3 = np.array([1.0, 1.0])
rvec = rosenbrock(x3)
model.change_point(0, x3 - model.xbase, rvec, allow_kopt_update=False) # full: overwrite x0
self.assertEqual(model.npt(), 3, 'Wrong npt after x3')
self.assertTrue(array_compare(model.xopt(abs_coordinates=True), x1), 'Wrong xopt after x3')
self.assertTrue(array_compare(model.ropt(), rosenbrock(x1)), 'Wrong ropt after x3')
self.assertAlmostEqual(model.fopt(), sumsq(rosenbrock(x1)), 'Wrong fopt after x3')
self.assertTrue(array_compare(model.xopt(abs_coordinates=True), model.as_absolute_coordinates(model.xopt())),
'Comparison wrong after x3')
dirns = model.xpt_directions(include_kopt=True)
self.assertTrue(array_compare(x3 - x1, dirns[0, :]), 'Wrong dirn 0')
self.assertTrue(array_compare(x1 - x1, dirns[1, :]), 'Wrong dirn 1')
self.assertTrue(array_compare(x2 - x1, dirns[2, :]), 'Wrong dirn 2')
dirns = model.xpt_directions(include_kopt=False)
self.assertTrue(array_compare(x3 - x1, dirns[0, :]), 'Wrong dirn 0 (no kopt)')
# self.assertTrue(array_compare(x1 - x1, dirns[1, :]), 'Wrong dirn 1')
self.assertTrue(array_compare(x2 - x1, dirns[1, :]), 'Wrong dirn 1 (no kopt)')
def runTest(self):
n, m = 2, 2
npt = n + 1
x0 = np.array([-1.2, 1.0])
xl = -1e2 * np.ones((n, ))
xu = 1e2 * np.ones((n, ))
model = Model(npt, x0, rosenbrock(x0), xl, xu, [], 1)
x1 = np.array([1.0, 0.9])
model.change_point(1, x1 - model.xbase, rosenbrock(x1))
x2 = np.array([2.0, 0.9])
model.change_point(2, x2 - model.xbase, rosenbrock(x2))
self.assertAlmostEqual(model.min_objective_value(), 1e-12,
'Wrong min obj value')
model = Model(npt, x0, rosenbrock(x0), xl, xu, [], 1, rel_tol=1e-2)
self.assertAlmostEqual(model.min_objective_value(),
1e-2 * sumsq(rosenbrock(x0)),
'Wrong min obj value 2')
model = Model(npt, x0, rosenbrock(x0), xl, xu, [], 1, abs_tol=1.0)
self.assertAlmostEqual(model.min_objective_value(), 1.0,
'Wrong min obj value 3')
model = Model(npt,
x0,
rosenbrock(x0),
xl,
xu, [],
1,
abs_tol=1.0,
rel_tol=1e-2)
self.assertAlmostEqual(model.min_objective_value(), 1.0,
'Wrong min obj value 4')
def runTest(self):
n, m = 2, 2
npt = n + 1
x0 = np.array([-1.2, 1.0])
xl = -1e2 * np.ones((n,))
xu = 1e2 * np.ones((n,))
model = Model(npt, x0, rosenbrock(x0), xl, xu, 1)
self.assertTrue(array_compare(model.sl, xl - x0), 'Wrong sl after initialisation')
self.assertTrue(array_compare(model.su, xu - x0), 'Wrong su after initialisation')
x1 = np.array([1.0, 0.9])
model.change_point(1, x1 - model.xbase, rosenbrock(x1))
self.assertTrue(array_compare(model.as_absolute_coordinates(x1 - x0), x1), 'Wrong abs coords')
self.assertTrue(array_compare(model.as_absolute_coordinates(np.array([-1e3, 1e3])-x0), np.array([-1e2, 1e2])),
'Bad abs coords with bounds')
x2 = np.array([2.0, 0.9])
model.change_point(2, x2 - model.xbase, rosenbrock(x2))
sqdists = model.distances_to_xopt()
self.assertAlmostEqual(sqdists[0], sumsq(x0 - x1), 'Wrong distance 0')
self.assertAlmostEqual(sqdists[1], sumsq(x1 - x1), 'Wrong distance 1')
self.assertAlmostEqual(sqdists[2], sumsq(x2 - x1), 'Wrong distance 2')
model.add_new_sample(0, rosenbrock(x0))
self.assertEqual(model.nsamples[0], 2, 'Wrong number of samples 0')
self.assertEqual(model.nsamples[1], 1, 'Wrong number of samples 1')
self.assertEqual(model.nsamples[2], 1, 'Wrong number of samples 2')
for i in range(50):
model.add_new_sample(0, np.array([0.0, 0.0]))
self.assertEqual(model.kopt, 0, 'Wrong kopt after bad resampling')
self.assertTrue(array_compare(model.ropt(), 2*rosenbrock(x0)/52), 'Wrong ropt after bad resampling')
self.assertAlmostEqual(model.fopt(), sumsq(2 * rosenbrock(x0) / 52), 'Wrong fopt after bad resampling')
d = np.array([10.0, 10.0])
dirns_old = model.xpt_directions(include_kopt=True)
model.shift_base(d)
dirns_new = model.xpt_directions(include_kopt=True)
self.assertTrue(array_compare(model.xbase, x0 + d), 'Wrong new base')
self.assertEqual(model.kopt, 0, 'Wrong kopt after shift base')
for i in range(3):
self.assertTrue(array_compare(dirns_old[i, :], dirns_new[i, :]), 'Wrong dirn %i after shift base' % i)
self.assertTrue(array_compare(model.sl, xl - x0 - d), 'Wrong sl after shift base')
self.assertTrue(array_compare(model.su, xu - x0 - d), 'Wrong su after shift base')
# save_point and get_final_results
model.change_point(0, x0 - model.xbase, rosenbrock(x0)) # revert after resampling
model.change_point(1, x1 - model.xbase, rosenbrock(x1)) # revert after resampling
x, rvec, f, jacmin, nsamples = model.get_final_results()
self.assertTrue(array_compare(x, x1), 'Wrong final x')
self.assertTrue(array_compare(rvec, rosenbrock(x1)), 'Wrong final rvec')
self.assertAlmostEqual(sumsq(rosenbrock(x1)), f, 'Wrong final f')
self.assertTrue(array_compare(np.zeros((2,2)), jacmin), 'Wrong final jacmin')
self.assertEqual(1, nsamples, 'Wrong final nsamples')
self.assertIsNone(model.xsave, 'xsave not none after initialisation')
self.assertIsNone(model.rsave, 'rsave not none after initialisation')
self.assertIsNone(model.fsave, 'fsave not none after initialisation')
self.assertIsNone(model.nsamples_save, 'nsamples_save not none after initialisation')
model.save_point(x0, rosenbrock(x0), 1, x_in_abs_coords=True)
self.assertTrue(array_compare(model.xsave, x0), 'Wrong xsave after saving')
self.assertTrue(array_compare(model.rsave, rosenbrock(x0)), 'Wrong rsave after saving')
self.assertAlmostEqual(model.fsave, sumsq(rosenbrock(x0)), 'Wrong fsave after saving')
self.assertEqual(model.nsamples_save, 1, 'Wrong nsamples_save after saving')
x, rvec, f, jacmin, nsamples = model.get_final_results()
self.assertTrue(array_compare(x, x1), 'Wrong final x after saving')
self.assertTrue(array_compare(rvec, rosenbrock(x1)), 'Wrong final rvec after saving')
self.assertAlmostEqual(sumsq(rosenbrock(x1)), f, 'Wrong final f after saving')
self.assertEqual(1, nsamples, 'Wrong final nsamples after saving')
model.save_point(x2 - model.xbase, np.array([0.0, 0.0]), 2, x_in_abs_coords=False)
self.assertTrue(array_compare(model.xsave, x2), 'Wrong xsave after saving 2')
self.assertTrue(array_compare(model.rsave, np.array([0.0, 0.0])), 'Wrong rsave after saving 2')
self.assertAlmostEqual(model.fsave, 0.0, 'Wrong fsave after saving 2')
self.assertEqual(model.nsamples_save, 2, 'Wrong nsamples_save after saving 2')
x, rvec, f, jacmin, nsamples = model.get_final_results()
self.assertTrue(array_compare(x, x2), 'Wrong final x after saving 2')
self.assertTrue(array_compare(rvec, np.array([0.0, 0.0])), 'Wrong final rvec after saving 2')
self.assertAlmostEqual(f, 0.0, 'Wrong final f after saving 2')
self.assertEqual(2, nsamples, 'Wrong final nsamples after saving 2')
model.save_point(x0, rosenbrock(x0), 3, x_in_abs_coords=True) # try to re-save a worse value
self.assertTrue(array_compare(model.xsave, x2), 'Wrong xsave after saving 3')
self.assertTrue(array_compare(model.rsave, np.array([0.0, 0.0])), 'Wrong rsave after saving 3')
self.assertAlmostEqual(model.fsave, 0.0, 'Wrong fsave after saving 3')
self.assertEqual(model.nsamples_save, 2, 'Wrong nsamples_save after saving 3')
