def test_basic_input1():
EEG = np.array([[1,2],[3,4]])
expected_A = np.array([[1.00000014,1.47051825],[1.47569674,2.17003868]])
expected_E = np.array([[0.,0.52948166],[1.52430317,1.82996138]])
A,E = performRPCA.performRPCA(EEG);
assert(np.allclose(A,expected_A))
assert(np.allclose(E,expected_E))
print('test_basic_input1 Pass')
def test_basic_input3():
EEG = np.array([[1,2,3,4,5,6,7],[10,2,-30,6,15,39,92]])
expected_A = np.array([[0.99999674,2.00000276,0.34522968,4.00000449,5.00000174,5.9999975,6.99999895],\
[10.00000152,1.99999938,-29.50244429,5.99999916,15.00000048,35.50896724,36.46037802]])
expected_E = np.array([[0,0,2.65476565,0,0,0,0],\
[0,0,-0.49755573,0,0,3.49103264,55.5396215]])
A,E = performRPCA.performRPCA(EEG);
assert(np.allclose(A,expected_A))
assert(np.allclose(E,expected_E))
print('test_basic_input3 Pass')
def test_params2():
EEG = np.array([[1,2,3],[4,5,6],[7,8,9]])
lam = .2
tol = 1e-3
maxIter = 100
expected_A = np.array([[0,0,0],[0,0,0],[0,0,0]])
expected_E = np.array([[1,2,3],[4,5,6],[7,8,9]])
A,E = performRPCA.performRPCA(EEG,lam,tol,maxIter)
assert(np.allclose(A,expected_A))
assert(np.allclose(E,expected_E))
print('test_params2 Pass')
def test_basic_input2():
EEG = np.array([[1,2,3],[4,5,6],[7,8,9]])
expected_A = np.array([[1.5999989,1.99999912,2.3999982],\
[3.99999961,5.00000076,5.99999904],\
[5.13368148,6.41710344,7.70052173]])
expected_E = np.array([[-5.99998725e-01,4.82951146e-07,6.00002018e-01],\
[0.00000000e+00,-0.00000000e+00,5.78509154e-07],\
[1.86631877e+00,1.58289609e+00,1.29947849e+00]])
A,E = performRPCA.performRPCA(EEG);
assert(np.allclose(A,expected_A))
assert(np.allclose(E,expected_E))
print('test_basic_input2 Pass')
def test_params3():
EEG = np.array([[1,2,3],[4,5,6],[7,8,9]])
lam = .5
tol = 1e-10
maxIter = 1000
expected_A = np.array([[1.45445617,2,2.14299791],\
[3.30885118,4.54994966,4.8752663],\
[3.31508751,4.55852514,4.88445492]])
expected_E = np.array([[-0.45445617,0,0.85700209],\
[0.69114882,0.45005034,1.1247337],\
[3.68491249,3.44147486,4.11554508]])
A,E = performRPCA.performRPCA(EEG,lam,tol,maxIter)
assert(np.allclose(A,expected_A))
assert(np.allclose(E,expected_E))
print('test_params3 Pass')
def test_params1():
EEG = np.array([[1,2,3],[4,5,6],[7,8,9]])
lam = .7
tol = 1e-8
maxIter = 20
expected_A = np.array([[1.21416342,1.99964425,2.79453087],\
[3.99964063,5.00068211,5.94182001],\
[6.75789278,7.94410702,9.00016552]])
expected_E = np.array([[-0.21397595,0.,0.20564244],\
[0.,0.,0.05784774],\
[ 0.24228631,0.05555309,0.]])
A,E = performRPCA.performRPCA(EEG,lam,tol,maxIter)
assert(np.allclose(A,expected_A))
assert(np.allclose(E,expected_E))
print('test_params1 Pass')
def test_incorrect_input():
with pytest.raises(AttributeError):
A,E = performRPCA.performRPCA("Wrong input Type")
assert(True)
print('test_incorrect_input Pass')
def test_no_input():
with pytest.raises(TypeError):
A,E = performRPCA.performRPCA()
assert(True)
print('test_no_input Pass')