Source Code for Module test_suite.unit_tests._specific_fns.test_n_state_model

 1  ############################################################################### 
 2  #                                                                             # 
 3  # Copyright (C) 2008 Edward d'Auvergne                                        # 
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 5  # This file is part of the program relax.                                     # 
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19  # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA   # 
20  #                                                                             # 
21  ############################################################################### 
22   
23  # Python module imports. 
24  from math import pi 
25  from unittest import TestCase 
26   
27  # relax module imports. 
28  from specific_fns import n_state_model 
29  from test_suite.unit_tests.n_state_model_testing_base import N_state_model_base_class 
30   
31   
32 -class Test_n_state_model(N_state_model_base_class, TestCase): 
33      """Unit tests for the functions of the 'specific_fns.n_state_model' module.""" 
34   
35      # Place the specific_fns.n_state_model module into the class namespace. 
36      n_state_model_fns = n_state_model.N_state_model() 
37   
38   
39 -    def test__assemble_param_vector(self): 
40          """Test the operation of the specific_fns.n_state_model._assemble_param_vector() method.""" 
41   
42          # Set up the N, probabilities and Euler angles. 
43          cdp.N = 3 
44          cdp.probs = [0.1, 0.3, 0.6] 
45          cdp.alpha = [0.0, pi/2, pi] 
46          cdp.beta = [pi/2, pi, 3*pi/2] 
47          cdp.gamma = [1.0, 3*pi/2, 2*pi] 
48          cdp.model = '2-domain' 
49   
50          # Set up a dummy alignment tensor variable to allow the test to pass. 
51          cdp.align_tensors = None 
52   
53          # Get the parameter vector. 
54          param_vector = self.n_state_model_fns._assemble_param_vector() 
55   
56          # The correct result. 
57          vector_true = [0.1, 0.3, 0.0, pi/2, 1.0, pi/2, pi, 3*pi/2, pi, 3*pi/2, 2*pi] 
58   
59          # Check the vector. 
60          self.assertEqual(len(param_vector), len(vector_true)) 
61          for i in xrange(len(param_vector)): 
62              self.assertEqual(param_vector[i], vector_true[i]) 
63   
64   
65 -    def test__disassemble_param_vector(self): 
66          """Test the operation of the specific_fns.n_state_model._disassemble_param_vector() method.""" 
67   
68          # Set up the initial N, probabilities and Euler angles. 
69          cdp.N = 3 
70          cdp.probs = [None]*3 
71          cdp.alpha = [None]*3 
72          cdp.beta = [None]*3 
73          cdp.gamma = [None]*3 
74          cdp.model = '2-domain' 
75   
76          # The parameter vector. 
77          param_vector = [0.1, 0.3, 0.0, pi/2, 1.0, pi/2, pi, 3*pi/2, pi, 3*pi/2, 2*pi] 
78   
79          # Disassemble the parameter vector. 
80          self.n_state_model_fns._disassemble_param_vector(param_vector, data_types=['tensor']) 
81   
82          # Check the probabilities. 
83          self.assertEqual(cdp.probs, [0.1, 0.3, 0.6]) 
84          self.assertEqual(cdp.alpha, [0.0, pi/2, pi]) 
85          self.assertEqual(cdp.beta, [pi/2, pi, 3*pi/2]) 
86          self.assertEqual(cdp.gamma, [1.0, 3*pi/2, 2*pi]) 
87