def test_model_with_no_argument():
with pytest.raises(TypeError) as e_info:
model = hs.LeastSquares()
assert 'Either (A and Alpha) or `conditions` should be assigned.' in str(
e_info)
A = np.random.rand(2, 1)
condition = hs.Conditions()
model = hs.LeastSquares(A=A, conditions=[condition])
assert 'Either (A and Alpha) or `conditions` should be assigned.' in str(
e_info)
def test_A_dim():
'''
Test the dimension of A to be 2x1
'''
real = np.random.uniform(0, 10, [1, 2])
imag = np.random.uniform(0, 10, [1, 2])
A = real + imag * 1j
with pytest.raises(hs.CustomError) as e_info:
hs.LeastSquares(test_A_dim, test_alpha)
real = np.random.uniform(0, 10, [2, 2])
imag = np.random.uniform(0, 10, [2, 2])
A = real + imag * 1j
with pytest.raises(hs.CustomError) as e_info:
hs.LeastSquares(test_A_dim, test_alpha)
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_performance(n):
alpha = hs.Alpha()
real = np.random.uniform(0, 10, [n, n])
imag = np.random.uniform(0, 10, [n, n])
alpha.add(real + imag * 1j)
real = np.random.uniform(0, 10, [n, 1])
imag = np.random.uniform(0, 10, [n, 1])
A = real + imag * 1j
start = time.time()
w = hs.LeastSquares(A, alpha).solve()
error = hs.residual_vibration(alpha.value, w, A)
t = time.time() - start
return round(t, 2)
def test_model_conditions():
test_alpha_1 = hs.Alpha()
test_alpha_1.add(np.ones((2, 2)))
test_alpha_2 = hs.Alpha()
test_alpha_2.add(np.ones((2, 2)) * 2)
test_A_1 = np.ones((2, 1))
test_A_2 = np.ones((2, 1)) * 2
condition_1 = hs.Condition()
condition_1.add(test_alpha_1, test_A_1)
condition_2 = hs.Condition()
condition_2.add(test_alpha_2, test_A_2)
model = hs.LeastSquares(conditions=[condition_1, condition_2])
np.testing.assert_allclose(model.ALPHA,
np.array([[1, 1], [1, 1], [2, 2], [2, 2]]))
np.testing.assert_allclose(model.A, np.array([[1], [1], [2], [2]]))
def test_info_model():
# Set random data
np.random.seed(42)
m = 3
n = 3
real = np.random.rand(m, n)
imag = np.random.rand(m, n)
comp = real + imag * 1j
alpha1 = hs.Alpha()
alpha1.add(comp)
real = np.random.rand(m, n)
imag = np.random.rand(m, n)
comp = real + imag * 1j
alpha2 = hs.Alpha()
alpha2.add(comp)
# Condition logging and printing
condition1 = hs.Condition(name='Speed 1300')
condition1.add(alpha2, A=np.random.rand(m, 1))
condition2 = hs.Condition(name='Speed 2500')
condition2.add(alpha2, A=np.random.rand(m, 1))
model = hs.LeastSquares(conditions=[condition1, condition2])
model.solve()
angles = np.arange(100, 300, 10) # angles
split1 = model.create_split()
split1.split_setup(0,
max_number_weights_per_hole=1,
holes_available=[angles],
weights_available=[0.1])
split2 = model.create_split()
split2.split_setup(1,
max_number_weights_per_hole=1,
holes_available=[angles],
weights_available=[0.2])
split1.split_solve()
split2.split_solve()
split1.update(confirm=True)
split2.update(confirm=True)
print(model.info())
def test_model_LSQ(test_big_A, test_big_alpha):
'''
Creating a test model
'''
w = hs.LeastSquares(test_big_A, test_big_alpha).solve()
return w
def test_faults():
with pytest.raises(hs.CustomError) as error:
hs.LeastSquares([1, 2], [1, 2])
import hsbalance as hs
A = [['170@112'],
['53@78']] # --> Initial vibration conditions First Row in Table above.
B = [
[
'235@94', '185@115'
], # --> Vibration at sensor 1 when trial masses were added at plane 1&2 (First column for both trial runs)
['58@68', '77@104']
] # Vibration at sensor 2 when trial masses were added at plane 1&2 (Second column for both trial runs)
U = ['1.15@0', '1.15@0'] # Trial masses 2.5 g at plane 1 and 2 consequently
A = hs.convert_math_cart(A)
B = hs.convert_math_cart(B)
U = hs.convert_math_cart(U)
alpha = hs.Alpha() # Instantiate Alpha class
alpha.add(A=A, B=B, U=U)
model_LeastSquares = hs.LeastSquares(A=A, alpha=alpha)
w = model_LeastSquares.solve(
) # Solve the model and get the correction weights vector
# Calculate Residual vibration vector
residual_vibration = hs.residual_vibration(alpha.value, w, A)
# Caculate Root mean square error for model
RMSE = hs.rmse(residual_vibration)
# Convert w back into mathmatical expression
w = hs.convert_cart_math(w)
# print results
print(model_LeastSquares.info())