Source Code for Module test_suite.unit_tests._prompt.test_diffusion_tensor

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  3  # Copyright (C) 2007-2008, 2010 Edward d'Auvergne                             # 
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 21  ############################################################################### 
 22   
 23  # Python module imports. 
 24  from unittest import TestCase 
 25   
 26  # relax module imports. 
 27  from prompt.diffusion_tensor import Diffusion_tensor 
 28  from relax_errors import RelaxError, RelaxBoolError, RelaxIntError, RelaxNoneStrError, RelaxNumError, RelaxNumTupleNumError, RelaxStrError 
 29  from test_suite.unit_tests.diffusion_tensor_testing_base import Diffusion_tensor_base_class 
 30   
 31  # Unit test imports. 
 32  from data_types import DATA_TYPES 
 33   
 34   
 35 -class Test_diffusion_tensor(Diffusion_tensor_base_class, TestCase): 
 36      """Unit tests for the functions of the 'prompt.diffusion_tensor' module.""" 
 37   
 38      # Instantiate the user function class. 
 39      diffusion_tensor_fns = Diffusion_tensor() 
 40   
 41   
 42 -    def test_copy_argfail_pipe_from(self): 
 43          """The pipe_from arg test of the diffusion_tensor.copy() user function.""" 
 44   
 45          # Loop over the data types. 
 46          for data in DATA_TYPES: 
 47              # Catch the None and str arguments, and skip them. 
 48              if data[0] == 'None' or data[0] == 'str': 
 49                  continue 
 50   
 51              # The argument test. 
 52              self.assertRaises(RelaxNoneStrError, self.diffusion_tensor_fns.copy, pipe_from=data[1]) 
 53   
 54   
 55 -    def test_copy_argfail_pipe_to(self): 
 56          """The pipe_to arg test of the diffusion_tensor.copy() user function.""" 
 57   
 58          # Loop over the data types. 
 59          for data in DATA_TYPES: 
 60              # Catch the None and str arguments, and skip them. 
 61              if data[0] == 'None' or data[0] == 'str': 
 62                  continue 
 63   
 64              # The argument test. 
 65              self.assertRaises(RelaxNoneStrError, self.diffusion_tensor_fns.copy, pipe_to=data[1]) 
 66   
 67   
 68 -    def test_copy_argfail_both_pipes(self): 
 69          """The pipe_from and pipe_to arg test of the diffusion_tensor.copy() user function.""" 
 70   
 71          # Test that both cannot be None (the default)! 
 72          self.assertRaises(RelaxError, self.diffusion_tensor_fns.copy) 
 73   
 74   
 75 -    def test_init_argfail_params(self): 
 76          """The params arg test of diffusion_tensor.init() user function.""" 
 77   
 78          # Loop over the data types. 
 79          for data in DATA_TYPES: 
 80              # Catch a single float, int, or bin, and skip them. 
 81              if data[0] == 'int' or data[0] == 'bin' or data[0] == 'float': 
 82                  continue 
 83   
 84              # Catch the tuple arguments. 
 85              if data[0] == 'tuple' or data[0] == 'float tuple' or data[0] == 'str tuple': 
 86                  # Correct tuple length. 
 87                  if len(data[1]) == 4 or len(data[1]) == 6: 
 88                      continue 
 89   
 90              # The argument test. 
 91              self.assertRaises(RelaxNumTupleNumError, self.diffusion_tensor_fns.init, params=data[1]) 
 92   
 93   
 94 -    def test_init_argfail_time_scale(self): 
 95          """The time_scale arg test of the diffusion_tensor.init() user function.""" 
 96   
 97          # Loop over the data types. 
 98          for data in DATA_TYPES: 
 99              # Catch the number arguments, and skip them. 
100              if data[0] == 'bin' or data[0] == 'int' or data[0] == 'float': 
101                  continue 
102   
103              # The argument test. 
104              self.assertRaises(RelaxNumError, self.diffusion_tensor_fns.init, params=1e-9, time_scale=data[1]) 
105   
106   
107 -    def test_init_argfail_d_scale(self): 
108          """The d_scale arg test of the diffusion_tensor.init() user function.""" 
109   
110          # Loop over the data types. 
111          for data in DATA_TYPES: 
112              # Catch the number arguments, and skip them. 
113              if data[0] == 'bin' or data[0] == 'int' or data[0] == 'float': 
114                  continue 
115   
116              # The argument test. 
117              self.assertRaises(RelaxNumError, self.diffusion_tensor_fns.init, params=1e-9, d_scale=data[1]) 
118   
119   
120 -    def test_init_argfail_angle_units(self): 
121          """The angle_units arg test of the diffusion_tensor.init() user function.""" 
122   
123          # Loop over the data types. 
124          for data in DATA_TYPES: 
125              # Catch the str argument, and skip it. 
126              if data[0] == 'str': 
127                  continue 
128   
129              # The argument test. 
130              self.assertRaises(RelaxStrError, self.diffusion_tensor_fns.init, params=1e-9, angle_units=data[1]) 
131   
132   
133 -    def test_init_argfail_param_types(self): 
134          """The param_types arg test of the diffusion_tensor.init() user function.""" 
135   
136          # Loop over the data types. 
137          for data in DATA_TYPES: 
138              # Catch the int and bin arguments, and skip them. 
139              if data[0] == 'int' or data[0] == 'bin': 
140                  continue 
141   
142              # The argument test. 
143              self.assertRaises(RelaxIntError, self.diffusion_tensor_fns.init, params=1e-9, param_types=data[1]) 
144   
145   
146 -    def test_init_argfail_spheroid_type(self): 
147          """The spheroid_type arg test of the diffusion_tensor.init() user function.""" 
148   
149          # Loop over the data types. 
150          for data in DATA_TYPES: 
151              # Catch the None and str arguments, and skip them. 
152              if data[0] == 'None' or data[0] == 'str': 
153                  continue 
154   
155              # The argument test. 
156              self.assertRaises(RelaxNoneStrError, self.diffusion_tensor_fns.init, params=1e-9, spheroid_type=data[1]) 
157   
158   
159 -    def test_init_argfail_fixed(self): 
160          """The fixed arg test of the diffusion_tensor.init() user function.""" 
161   
162          # Loop over the data types. 
163          for data in DATA_TYPES: 
164              # Catch the bool arguments, and skip them. 
165              if data[0] == 'bool': 
166                  continue 
167   
168              # The argument test. 
169              self.assertRaises(RelaxBoolError, self.diffusion_tensor_fns.init, params=1e-9, fixed=data[1]) 
170