@@ -43,13 +43,13 @@ def testMarkovSignature(self):
43
43
44
44
# Basic usage
45
45
m = 3
46
- H = markov (Y , U , m , transpose = False )
47
46
Htrue = np .array ([1. , 0. , 0. ])
47
+
48
+ H = markov (Y , U , m , transpose = False )
48
49
np .testing .assert_array_almost_equal (H , Htrue )
49
50
50
51
response .transpose = False
51
52
H = markov (response , m )
52
- Htrue = np .array ([1. , 0. , 0. ])
53
53
np .testing .assert_array_almost_equal (H , Htrue )
54
54
55
55
# Make sure that transposed data also works
@@ -69,15 +69,19 @@ def testMarkovSignature(self):
69
69
np .testing .assert_array_almost_equal (H , Htrue )
70
70
71
71
# Test example from docstring
72
+ # TODO: There is a problem here
73
+ # Htrue = np.array([1., 0.5, 0.])
72
74
T = np .linspace (0 , 10 , 100 )
73
75
U = np .ones ((1 , 100 ))
74
- _ , Y = forced_response (tf ([1 ], [1 , 0.5 ], True ), T , U )
75
- H = markov (Y , U , 3 )
76
+ T , Y = forced_response (tf ([1 ], [1 , 0.5 ], True ), T , U )
77
+ H = markov (Y , U , 3 , transpose = False )
78
+ #np.testing.assert_array_almost_equal(H, Htrue)
76
79
77
80
T = np .linspace (0 , 10 , 100 )
78
81
U = np .ones ((1 , 100 ))
79
82
response = forced_response (tf ([1 ], [1 , 0.5 ], True ), T , U )
80
83
H = markov (response , 3 )
84
+ #np.testing.assert_array_almost_equal(H, Htrue)
81
85
82
86
# Test example from issue #395
83
87
inp = np .array ([1 , 2 ])
0 commit comments