Source Code for Module test_suite.system_tests.align_tensor

  1  ############################################################################### 
  2  #                                                                             # 
  3  # Copyright (C) 2006-2011 Edward d'Auvergne                                   # 
  4  #                                                                             # 
  5  # This file is part of the program relax.                                     # 
  6  #                                                                             # 
  7  # relax is free software; you can redistribute it and/or modify               # 
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 10  # (at your option) any later version.                                         # 
 11  #                                                                             # 
 12  # relax is distributed in the hope that it will be useful,                    # 
 13  # but WITHOUT ANY WARRANTY; without even the implied warranty of              # 
 14  # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the               # 
 15  # GNU General Public License for more details.                                # 
 16  #                                                                             # 
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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 tempfile import mktemp 
 25   
 26  # relax module imports. 
 27  from base_classes import SystemTestCase 
 28  from data import Relax_data_store; ds = Relax_data_store() 
 29   
 30   
 31 -class Align_tensor(SystemTestCase): 
 32      """Class for testing various aspects specific to the alignment tensors.""" 
 33   
 34 -    def setUp(self): 
 35          """Function for initialising a few alignment tensors.""" 
 36   
 37          # Create a data pipe. 
 38          self.interpreter.pipe.create('test', 'N-state') 
 39   
 40          # Temp file name. 
 41          ds.tmpfile = mktemp() 
 42   
 43          # Tensor name lists. 
 44          self.full_list = ['0 full', '1 full', '2 full', '3 full', '4 full'] 
 45          self.red_list = ['0 red', '1 red', '2 red', '3 red', '4 red'] 
 46   
 47          # Error. 
 48          error = 1.47411211147e-05 
 49   
 50          # Tensor lists. 
 51          self.tensors_full = [ 
 52                  (0.00014221982216882766, -0.00014454300156652134, -0.00070779621164871397, -0.00060161949408277324, 0.00020200800707295083), 
 53                  (-0.00014307694949297205, -0.00039671919293883539, -0.00024724524395487659, 0.00031948292975139144, 0.00018868359624777637), 
 54                  (-0.00022967898444150887, -0.00027171643813494106, -0.00021961563147411279, 0.00010337393266477703, 0.00029030226175831515), 
 55                  (0.00043690692358615301, -0.00034379559287467062, -0.00019359695171683388, 0.00030194133983804048, -6.314162250164486e-05), 
 56                  (-0.00026249527958822807, 0.00073561736796410628, 6.3975419225898133e-05, 6.2788017118057252e-05, 0.00020119758245770023) 
 57          ] 
 58          self.tensors_red = [ 
 59                  (-0.0004037026160192775, 0.00023172423501111316, -0.00020915186581478394, -0.00028817367472760139, -8.7172337025481604e-05), 
 60                  (0.0003767999506688964, -0.00021492227011444111, 0.00019620694392616774, 0.00027163215478635274, 8.147201253457049e-05), 
 61                  (0.00025970120925482461, -0.00014782823602910519, 0.00013565269563569894, 0.00018741173517420359, 5.6252903270026344e-05), 
 62                  (0.00014574884684542708, -8.3162940224598374e-05, 7.4927100277784987e-05, 0.00010508245294401461, 3.1156238348722986e-05), 
 63                  (-0.00011267453337899962, 6.412308037476237e-05, -5.7897942333203444e-05, -8.1865863377039068e-05, -2.5273427585025123e-05) 
 64          ] 
 65   
 66          # Set up the tensors. 
 67          for i in range(5): 
 68              # Load the tensor. 
 69              self.interpreter.align_tensor.init(tensor=self.full_list[i], params=self.tensors_full[i], param_types=0) 
 70              self.interpreter.align_tensor.init(tensor=self.red_list[i], params=self.tensors_red[i], param_types=0) 
 71   
 72              # Errors. 
 73              self.interpreter.align_tensor.init(tensor=self.full_list[i], params=(error, error, error, error, error), param_types=0, errors=True) 
 74              self.interpreter.align_tensor.init(tensor=self.red_list[i], params=(error, error, error, error, error), param_types=0, errors=True) 
 75   
 76              # Domain. 
 77              self.interpreter.align_tensor.set_domain(tensor=self.full_list[i], domain='full') 
 78              self.interpreter.align_tensor.set_domain(tensor=self.red_list[i], domain='red') 
 79   
 80              # Tensor reductions. 
 81              self.interpreter.align_tensor.reduction(full_tensor=self.full_list[i], red_tensor=self.red_list[i]) 
 82   
 83          # Reset some values. 
 84          cdp.align_tensors[2].Axx = 1 
 85   
 86   
 87 -    def test_to_and_from_xml(self): 
 88          """Test the conversion to and from XML.""" 
 89   
 90          # Save the data pipe. 
 91          self.interpreter.results.write(ds.tmpfile, dir=None, compress_type=0) 
 92   
 93          # Create a new data pipe. 
 94          self.interpreter.pipe.create('new', 'N-state') 
 95   
 96          # Load the data. 
 97          self.interpreter.results.read(ds.tmpfile, dir=None) 
 98   
 99          # Checks. 
100          self.assertEqual(len(cdp.align_tensors), 10) 
101          self.assert_(hasattr(cdp.align_tensors, 'reduction')) 
102          for i in range(5): 
103              # Full tensors. 
104              if i == 1: 
105                  self.assertAlmostEqual(cdp.align_tensors[i*2].Axx, 1.0) 
106              else: 
107                  self.assertAlmostEqual(cdp.align_tensors[i*2].Sxx, self.tensors_full[i][0]) 
108              self.assertAlmostEqual(cdp.align_tensors[i*2].Syy, self.tensors_full[i][1]) 
109              self.assertAlmostEqual(cdp.align_tensors[i*2].Sxy, self.tensors_full[i][2]) 
110              self.assertAlmostEqual(cdp.align_tensors[i*2].Sxz, self.tensors_full[i][3]) 
111              self.assertAlmostEqual(cdp.align_tensors[i*2].Syz, self.tensors_full[i][4]) 
112              self.assertEqual(cdp.align_tensors[i*2].name, self.full_list[i]) 
113   
114              # Reduced tensors. 
115              self.assertAlmostEqual(cdp.align_tensors[i*2+1].Sxx, self.tensors_red[i][0]) 
116              self.assertAlmostEqual(cdp.align_tensors[i*2+1].Syy, self.tensors_red[i][1]) 
117              self.assertAlmostEqual(cdp.align_tensors[i*2+1].Sxy, self.tensors_red[i][2]) 
118              self.assertAlmostEqual(cdp.align_tensors[i*2+1].Sxz, self.tensors_red[i][3]) 
119              self.assertAlmostEqual(cdp.align_tensors[i*2+1].Syz, self.tensors_red[i][4]) 
120              self.assertEqual(cdp.align_tensors[i*2+1].name, self.red_list[i]) 
121   
122              # Reduction. 
123              self.assertEqual(cdp.align_tensors.reduction[i], [i*2, i*2+1]) 
124