Source Code for Module test_suite.system_tests.align_tensor

  1  ############################################################################### 
  2  #                                                                             # 
  3  # Copyright (C) 2006-2013 Edward d'Auvergne                                   # 
  4  #                                                                             # 
  5  # This file is part of the program relax (http://www.nmr-relax.com).          # 
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 20  ############################################################################### 
 21   
 22  # Python module imports. 
 23  from tempfile import mktemp 
 24   
 25  # relax module imports. 
 26  from data import Relax_data_store; ds = Relax_data_store() 
 27  from test_suite.system_tests.base_classes import SystemTestCase 
 28   
 29   
 30 -class Align_tensor(SystemTestCase): 
 31      """Class for testing various aspects specific to the alignment tensors.""" 
 32   
 33 -    def setUp(self): 
 34          """Function for initialising a few alignment tensors.""" 
 35   
 36          # Create a data pipe. 
 37          self.interpreter.pipe.create('test', 'N-state') 
 38   
 39          # Temp file name. 
 40          ds.tmpfile = mktemp() 
 41   
 42          # Tensor name lists. 
 43          self.full_list = ['0 full', '1 full', '2 full', '3 full', '4 full'] 
 44          self.red_list = ['0 red', '1 red', '2 red', '3 red', '4 red'] 
 45   
 46          # Error. 
 47          error = 1.47411211147e-05 
 48   
 49          # Tensor lists. 
 50          self.tensors_full = [ 
 51                  (0.00014221982216882766, -0.00014454300156652134, -0.00070779621164871397, -0.00060161949408277324, 0.00020200800707295083), 
 52                  (-0.00014307694949297205, -0.00039671919293883539, -0.00024724524395487659, 0.00031948292975139144, 0.00018868359624777637), 
 53                  (-0.00022967898444150887, -0.00027171643813494106, -0.00021961563147411279, 0.00010337393266477703, 0.00029030226175831515), 
 54                  (0.00043690692358615301, -0.00034379559287467062, -0.00019359695171683388, 0.00030194133983804048, -6.314162250164486e-05), 
 55                  (-0.00026249527958822807, 0.00073561736796410628, 6.3975419225898133e-05, 6.2788017118057252e-05, 0.00020119758245770023) 
 56          ] 
 57          self.tensors_red = [ 
 58                  (-0.0004037026160192775, 0.00023172423501111316, -0.00020915186581478394, -0.00028817367472760139, -8.7172337025481604e-05), 
 59                  (0.0003767999506688964, -0.00021492227011444111, 0.00019620694392616774, 0.00027163215478635274, 8.147201253457049e-05), 
 60                  (0.00025970120925482461, -0.00014782823602910519, 0.00013565269563569894, 0.00018741173517420359, 5.6252903270026344e-05), 
 61                  (0.00014574884684542708, -8.3162940224598374e-05, 7.4927100277784987e-05, 0.00010508245294401461, 3.1156238348722986e-05), 
 62                  (-0.00011267453337899962, 6.412308037476237e-05, -5.7897942333203444e-05, -8.1865863377039068e-05, -2.5273427585025123e-05) 
 63          ] 
 64   
 65          # Set up the tensors. 
 66          for i in range(5): 
 67              # Load the tensor. 
 68              self.interpreter.align_tensor.init(tensor=self.full_list[i], params=self.tensors_full[i], param_types=0) 
 69              self.interpreter.align_tensor.init(tensor=self.red_list[i], params=self.tensors_red[i], param_types=0) 
 70   
 71              # Errors. 
 72              self.interpreter.align_tensor.init(tensor=self.full_list[i], params=(error, error, error, error, error), param_types=0, errors=True) 
 73              self.interpreter.align_tensor.init(tensor=self.red_list[i], params=(error, error, error, error, error), param_types=0, errors=True) 
 74   
 75              # Domain. 
 76              self.interpreter.align_tensor.set_domain(tensor=self.full_list[i], domain='full') 
 77              self.interpreter.align_tensor.set_domain(tensor=self.red_list[i], domain='red') 
 78   
 79              # Tensor reductions. 
 80              self.interpreter.align_tensor.reduction(full_tensor=self.full_list[i], red_tensor=self.red_list[i]) 
 81   
 82          # Reset some values. 
 83          cdp.align_tensors[2].set(param='Axx', value=1) 
 84   
 85   
 86 -    def test_copy(self): 
 87          """Test the copying of alignment tensors (to catch U{bug #20338<https://web.archive.org/web/https://gna.org/bugs/?20338>}.""" 
 88   
 89          # First reset. 
 90          self.interpreter.reset() 
 91   
 92          # Create a data pipe. 
 93          self.interpreter.pipe.create('copy test', 'N-state') 
 94   
 95          # Initialise one tensor. 
 96          self.interpreter.align_tensor.init(tensor='orig', params=self.tensors_full[0], param_types=0) 
 97   
 98          # Copy the tensor. 
 99          self.interpreter.align_tensor.copy(tensor_from='orig', tensor_to='new') 
100   
101          # Checks. 
102          self.assertEqual(len(cdp.align_tensors), 2) 
103          self.assertEqual(cdp.align_tensors[0].name, 'orig') 
104          self.assertEqual(cdp.align_tensors[1].name, 'new') 
105   
106   
107 -    def test_fix(self): 
108          """Test the align_tensor.fix user function.""" 
109   
110          # Fix all tensors. 
111          self.interpreter.align_tensor.fix() 
112   
113          # Unfix one tensor. 
114          self.interpreter.align_tensor.fix('2 full', fixed=False) 
115   
116          # Check the fixed flags. 
117          flags = [True]*10 
118          flags[4] = False 
119          for i in range(10): 
120              print("Checking the tensor %s: '%s'." % (i, cdp.align_tensors[i].name)) 
121              self.assertEqual(cdp.align_tensors[i].fixed, flags[i]) 
122   
123   
124 -    def test_to_and_from_xml(self): 
125          """Test the conversion to and from XML.""" 
126   
127          # Save the data pipe. 
128          self.interpreter.results.write(ds.tmpfile, dir=None, compress_type=0) 
129   
130          # Create a new data pipe. 
131          self.interpreter.pipe.create('new', 'N-state') 
132   
133          # Load the data. 
134          self.interpreter.results.read(ds.tmpfile, dir=None) 
135   
136          # Checks. 
137          self.assertEqual(len(cdp.align_tensors), 10) 
138          self.assert_(hasattr(cdp.align_tensors, 'reduction')) 
139          for i in range(5): 
140              # Full tensors. 
141              if i == 1: 
142                  self.assertAlmostEqual(cdp.align_tensors[i*2].Axx, 1.0) 
143              else: 
144                  self.assertAlmostEqual(cdp.align_tensors[i*2].Sxx, self.tensors_full[i][0]) 
145              self.assertAlmostEqual(cdp.align_tensors[i*2].Syy, self.tensors_full[i][1]) 
146              self.assertAlmostEqual(cdp.align_tensors[i*2].Sxy, self.tensors_full[i][2]) 
147              self.assertAlmostEqual(cdp.align_tensors[i*2].Sxz, self.tensors_full[i][3]) 
148              self.assertAlmostEqual(cdp.align_tensors[i*2].Syz, self.tensors_full[i][4]) 
149              self.assertEqual(cdp.align_tensors[i*2].name, self.full_list[i]) 
150   
151              # Reduced tensors. 
152              self.assertAlmostEqual(cdp.align_tensors[i*2+1].Sxx, self.tensors_red[i][0]) 
153              self.assertAlmostEqual(cdp.align_tensors[i*2+1].Syy, self.tensors_red[i][1]) 
154              self.assertAlmostEqual(cdp.align_tensors[i*2+1].Sxy, self.tensors_red[i][2]) 
155              self.assertAlmostEqual(cdp.align_tensors[i*2+1].Sxz, self.tensors_red[i][3]) 
156              self.assertAlmostEqual(cdp.align_tensors[i*2+1].Syz, self.tensors_red[i][4]) 
157              self.assertEqual(cdp.align_tensors[i*2+1].name, self.red_list[i]) 
158   
159              # Reduction. 
160              self.assertEqual(cdp.align_tensors.reduction[i], [i*2, i*2+1]) 
161