def test_merge(self): isa1 = ISA(5, ssize=2) isa2 = ISA(5) isa1.initialize() isa1.orthogonalize() isa2.initialize() isa2.A = isa1.A params = isa2.default_parameters() params['train_basis'] = False params['merge_subspaces'] = True params['merge']['verbosity'] = 0 isa2.train(isa1.sample(10000), params) ssizes1 = [gsm.dim for gsm in isa1.subspaces()] ssizes2 = [gsm.dim for gsm in isa2.subspaces()] # algorithm should be able to recover subspace sizes self.assertTrue(all(sort(ssizes1) == sort(ssizes2)))
def test_merge(self):
isa1 = ISA(5, ssize=2)
isa2 = ISA(5)
isa1.initialize()
isa1.orthogonalize()
isa2.initialize()
isa2.A = isa1.A
params = isa2.default_parameters()
params['train_basis'] = False
params['merge_subspaces'] = True
params['merge']['verbosity'] = 0
isa2.train(isa1.sample(10000), params)
ssizes1 = [gsm.dim for gsm in isa1.subspaces()]
ssizes2 = [gsm.dim for gsm in isa2.subspaces()]
# algorithm should be able to recover subspace sizes
self.assertTrue(all(sort(ssizes1) == sort(ssizes2)))
def test_orthogonalize(self): isa = ISA(4, 8) isa.orthogonalize() self.assertLess(sum(square(dot(isa.A, isa.A.T) - eye(4)).flatten()), 1e-3)
def test_orthogonalize(self):
isa = ISA(4, 8)
isa.orthogonalize()
self.assertLess(sum(square(dot(isa.A, isa.A.T) - eye(4)).flatten()),
1e-3)