def test_ALPHA_from_matrices(param, expected):
'''
Function to test instantiating Alpha class from matrices
param, expected : from config.yaml file
'''
for key, value in param[0].items():
globals()[key] = value
my_ALPHA = hs.Alpha()
my_A = hs.convert_matrix_to_cart(A)
my_B = hs.convert_matrix_to_cart(B)
my_U = hs.convert_matrix_to_cart(U)
print(A, B, U, keep_trial)
my_ALPHA.add(A=my_A, B=my_B, U=my_U, keep_trial=keep_trial)
expected = hs.convert_matrix_to_cart(expected)
np.testing.assert_allclose(my_ALPHA.value, expected,
rtol=0.05) # allowance 5% error
def test_Min_max(param, expected):
'''
Testing instantiate Min_Max model and test it against test cases
'''
my_ALPHA = hs.Alpha()
A = hs.convert_matrix_to_cart(param[0]['A'])
weight_const = param[0]['weight_const']
A0 = [0]
# It is acceptable to enter either direct_matrix or A,B,U matrices
try:
direct_matrix = hs.convert_matrix_to_cart(param[0]['ALPHA'])
my_ALPHA.add(direct_matrix=direct_matrix)
except KeyError:
B = hs.convert_matrix_to_cart(param[0]['B'])
U = hs.convert_matrix_to_cart(param[0]['U'])
my_ALPHA.add(A=A, B=B, U=U)
try:
A0 = hs.convert_matrix_to_cart(param[0]['A0'])
except KeyError:
pass
expected_W = hs.convert_matrix_to_cart(expected)
my_model = hs.Min_max(A, my_ALPHA,
weight_const=weight_const,name='Min_max') # Setting the model almost with no constraints
W = my_model.solve()
print((expected))
print('Residual Vibration rmse calculated = ', my_model.rmse())
print('Residual Vibration rmse from test_case = ',
hs.rmse(hs.residual_vibration(my_ALPHA.value, expected_W, A)))
print('expected_residual_vibration',
hs.convert_matrix_to_math(my_model.expected_residual_vibration()))
print('Correction weights', hs.convert_cart_math(W))
# Constraint Minmax algorithm was slightly inefficient in CVXPY
# The rmse was marginally more than the author solution
np.testing.assert_allclose(W, expected_W, rtol=0.09) # allowance 9% error
def test_WLS(param, expected):
'''
Testing instantiate LMI model and test it against test cases
'''
my_ALPHA = hs.Alpha()
A = hs.convert_matrix_to_cart(param[0]['A'])
A0 = [0]
# It is acceptable to enter either direct_matrix or A,B,U matrices
try:
direct_matrix = hs.convert_matrix_to_cart(param[0]['ALPHA'])
my_ALPHA.add(direct_matrix=direct_matrix)
except KeyError:
B = hs.convert_matrix_to_cart(param[0]['B'])
U = hs.convert_matrix_to_cart(param[0]['U'])
my_ALPHA.add(A=A, B=B, U=U)
try:
A0 = hs.convert_matrix_to_cart(param[0]['A0'])
except KeyError:
pass
expected_W = hs.convert_matrix_to_cart(expected)
my_model = hs.LeastSquares(A - A0, my_ALPHA, name='simple_least_square')
W = my_model.solve(solver='WLS')
print('Residual Vibration rmse calculated = ', my_model.rmse())
print('Residual Vibration rmse from test_case = ',
hs.rmse(hs.residual_vibration(my_ALPHA.value, expected_W, A)))
print('expected_residual_vibration',
hs.convert_matrix_to_math(my_model.expected_residual_vibration()))
np.testing.assert_allclose(W, expected_W, rtol=0.05) # allowance 5% error
def test_ALPHA_direct(param, expected):
'''
Pytest function to test instantiate Alpha from direct_matrix
Inputs:
param, expected : from config.yaml file
'''
# Instantiate Alpha class
my_ALPHA = hs.Alpha()
# Add direct matrix to the instance
my_ALPHA.add(direct_matrix=hs.convert_matrix_to_cart(param))
expected = list(list(complex(x) for x in item) for item in expected)
np.testing.assert_allclose(my_ALPHA.value, expected,
rtol=0.05) # allowance 5% error
def test_LMI(param, expected):
'''
Testing insantiate Least square model and test it against test cases
'''
my_ALPHA = hs.Alpha()
A = hs.convert_matrix_to_cart(param[0]['A'])
weight_const = param[0]['weight_const']
A0 = [0]
# It is acceptable to enter either direct_matrix or A,B,U matrices
try:
direct_matrix = hs.convert_matrix_to_cart(param[0]['ALPHA'])
my_ALPHA.add(direct_matrix=direct_matrix)
except KeyError:
B = hs.convert_matrix_to_cart(param[0]['B'])
U = hs.convert_matrix_to_cart(param[0]['U'])
my_ALPHA.add(A=A, B=B, U=U)
try:
A0 = hs.convert_matrix_to_cart(param[0]['A0'])
except KeyError:
pass
expected_W = hs.convert_matrix_to_cart(expected)
my_model = hs.LMI(A,
my_ALPHA,
weight_const=weight_const,
V_max=76,
critical_planes={1, 9},
name='LMI')
W = my_model.solve()
print('Residual Vibration rmse calculated = ', my_model.rmse())
print('Residual Vibration rmse from test_case = ',
hs.rmse(hs.residual_vibration(my_ALPHA.value, expected_W, A)))
print('expected_residual_vibration',
hs.convert_matrix_to_math(my_model.expected_residual_vibration()))
print('Correction weights', hs.convert_cart_math(W))
np.testing.assert_allclose(W, expected_W, rtol=0.05) # allowance 5% error