def test_reduce_B(self):
"""Given modes, test reduced B matrix"""
B_returned = self.LTI_proj.reduce_B(self.B_on_standard_basis_array)
np.testing.assert_allclose(B_returned, self.B_true)
LTI_proj = LGP.LTIGalerkinProjectionMatrices(self.basis_vecs,
self.adjoint_basis_vecs, is_basis_orthonormal=False)
B_returned = LTI_proj.reduce_B(self.B_on_standard_basis_array)
np.testing.assert_allclose(B_returned, self.B_true_nonorth)
def setUp(self):
self.num_basis_vecs = 10
self.num_adjoint_basis_vecs = 10
self.num_states = 11
self.num_inputs = 3
self.num_outputs = 2
self.generate_data_set(self.num_basis_vecs, self.num_adjoint_basis_vecs,
self.num_states, self.num_inputs, self.num_outputs)
self.LTI_proj = LGP.LTIGalerkinProjectionMatrices(self.basis_vecs,
self.adjoint_basis_vecs, is_basis_orthonormal=True)
def test_reduce_A(self):
"""Reduction of A matrix for Matrix, LookUp operators and in_memory."""
A_returned = self.LTI_proj.reduce_A(self.A_on_basis_vecs)
np.testing.assert_allclose(A_returned, self.A_true)
# Precomputed operations A object with vec handles, non-orthonormal
# modes
LTI_proj = LGP.LTIGalerkinProjectionMatrices(self.basis_vecs,
self.adjoint_basis_vecs, is_basis_orthonormal=False)
A_returned = LTI_proj.reduce_A(self.A_on_basis_vecs)
np.testing.assert_allclose(LTI_proj._proj_mat, self.proj_mat)
np.testing.assert_allclose(A_returned, self.A_true_nonorth)
def test_adjoint_basis_vec_optional(self):
"""Test that adjoint modes default to direct modes"""
no_adjoints_LTI_proj = LGP.LTIGalerkinProjectionMatrices(
self.basis_vecs, is_basis_orthonormal=True)
np.testing.assert_equal(no_adjoints_LTI_proj.adjoint_basis_vecs,
self.basis_vecs)
