Author: bugman Date: Fri Sep 26 18:51:31 2008 New Revision: 7366 URL: http://svn.gna.org/viewcvs/relax?rev=7366&view=rev Log: Significantly expanded the test_load_results() system test. All atomic data is now tested. Modified: 1.3/test_suite/system_tests/structure.py Modified: 1.3/test_suite/system_tests/structure.py URL: http://svn.gna.org/viewcvs/relax/1.3/test_suite/system_tests/structure.py?rev=7366&r1=7365&r2=7366&view=diff ============================================================================== --- 1.3/test_suite/system_tests/structure.py (original) +++ 1.3/test_suite/system_tests/structure.py Fri Sep 26 18:51:31 2008 @@ -53,10 +53,38 @@ # Read the results file. self.relax.interpreter._Results.read(file='str', dir=path) - # Aliases. + # Alias the current data pipe. cdp = ds[ds.current_pipe] - # Test the structure. + # Test the structure metadata. self.assert_(hasattr(cdp, 'structure')) self.assertEqual(cdp.structure.file, ['Ap4Aase_res1-12.pdb']) self.assertEqual(cdp.structure.path, ['../structures']) + + # The real atomic data. + atom_name = ['N', 'CA', '1HA', '2HA', 'C', 'O', '1HT', '2HT', '3HT', 'N', 'CD', 'CA', 'HA', 'CB', '1HB', '2HB', 'CG', '1HG', '2HG', '1HD', '2HD', 'C', 'O', 'N', 'H', 'CA', 'HA', 'CB', '1HB', '2HB', 'CG', 'HG', 'CD1', '1HD1', '2HD1', '3HD1', 'CD2', '1HD2', '2HD2', '3HD2', 'C', 'O', 'N', 'H', 'CA', '1HA', '2HA', 'C', 'O', 'N', 'H', 'CA', 'HA', 'CB', '1HB', '2HB', 'OG', 'HG', 'C', 'O', 'N', 'H', 'CA', 'HA', 'CB', '1HB', '2HB', 'CG', '1HG', '2HG', 'SD', 'CE', '1HE', '2HE', '3HE', 'C', 'O', 'N', 'H', 'CA', 'HA', 'CB', '1HB', '2HB', 'CG', 'OD1', 'OD2', 'C', 'O', 'N', 'H', 'CA', 'HA', 'CB', '1HB', '2HB', 'OG', 'HG', 'C', 'O', 'N', 'CD', 'CA', 'HA', 'CB', '1HB', '2HB', 'CG', '1HG', '2HG', '1HD', '2HD', 'C', 'O', 'N', 'CD', 'CA', 'HA', 'CB', '1HB', '2HB', 'CG', '1HG', '2HG', '1HD', '2HD', 'C', 'O', 'N', 'H', 'CA', 'HA', 'CB', '1HB', '2HB', 'CG', '1HG', '2HG', 'CD', 'OE1', 'OE2', 'C', 'O', 'N', 'H', 'CA', '1HA', '2HA', 'C', 'O'] + bonded = [[]]*174 + chain_id = [None]*174 + element = ['N', 'C', 'H', 'H', 'C', 'O', 'H', 'H', 'H', 'N', 'C', 'C', 'H', 'C', 'H', 'H', 'C', 'H', 'H', 'H', 'H', 'C', 'O', 'N', 'H', 'C', 'H', 'C', 'H', 'H', 'C', 'H', 'C', 'H', 'H', 'H', 'C', 'H', 'H', 'H', 'C', 'O', 'N', 'H', 'C', 'H', 'H', 'C', 'O', 'N', 'H', 'C', 'H', 'C', 'H', 'H', 'O', 'H', 'C', 'O', 'N', 'H', 'C', 'H', 'C', 'H', 'H', 'C', 'H', 'H', 'S', 'C', 'H', 'H', 'H', 'C', 'O', 'N', 'H', 'C', 'H', 'C', 'H', 'H', 'C', 'O', 'O', 'C', 'O', 'N', 'H', 'C', 'H', 'C', 'H', 'H', 'O', 'H', 'C', 'O', 'N', 'C', 'C', 'H', 'C', 'H', 'H', 'C', 'H', 'H', 'H', 'H', 'C', 'O', 'N', 'C', 'C', 'H', 'C', 'H', 'H', 'C', 'H', 'H', 'H', 'H', 'C', 'O', 'N', 'H', 'C', 'H', 'C', 'H', 'H', 'C', 'H', 'H', 'C', 'O', 'O', 'C', 'O', 'N', 'H', 'C', 'H', 'H', 'C', 'O'] + pdb_record = ['ATOM']*174 + res_name = ['GLY', 'GLY', 'GLY', 'GLY', 'GLY', 'GLY', 'GLY', 'GLY', 'GLY', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'LEU', 'GLY', 'GLY', 'GLY', 'GLY', 'GLY', 'GLY', 'GLY', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'MET', 'ASP', 'ASP', 'ASP', 'ASP', 'ASP', 'ASP', 'ASP', 'ASP', 'ASP', 'ASP', 'ASP', 'ASP', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'SER', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'PRO', 'GLU', 'GLU', 'GLU', 'GLU', 'GLU', 'GLU', 'GLU', 'GLU', 'GLU', 'GLU', 'GLU', 'GLU', 'GLU', 'GLU', 'GLU', 'GLY', 'GLY', 'GLY', 'GLY', 'GLY', 'GLY', 'GLY'] + res_num = [1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12] + seg_id = [None]*174 + x = [8.442, 7.469, 8.013, 6.825, 6.610, 6.827, 9.398, 8.180, 8.448, 5.613, 5.281, 4.714, 5.222, 3.646, 3.332, 2.800, 4.319, 4.853, 3.587, 6.162, 4.805, 4.075, 3.593, 4.074, 4.475, 3.498, 3.572, 2.025, 1.965, 1.609, 1.176, 1.823, 0.176, 0.096, 0.509, -0.789, 0.474, 0.809, -0.595, 0.707, 4.264, 4.364, 4.809, 4.697, 5.561, 6.220, 6.156, 4.659, 4.746, 3.786, 3.770, 2.851, 2.368, 1.785, 1.177, 1.165, 2.360, 1.690, 3.546, 3.804, 3.814, 3.563, 4.442, 4.984, 5.411, 6.192, 4.872, 6.068, 6.868, 5.332, 6.747, 6.155, 5.409, 6.977, 5.721, 3.369, 2.255, 3.703, 4.604, 2.753, 1.851, 3.329, 4.182, 3.644, 2.319, 1.992, 1.854, 2.419, 1.251, 3.451, 4.359, 3.267, 2.246, 4.223, 4.054, 4.040, 5.573, 6.142, 3.488, 4.276, 2.795, 1.828, 2.929, 2.810, 1.772, 0.912, 2.067, 1.505, 0.464, 2.138, 0.938, 2.273, 4.268, 4.585, 5.076, 4.776, 6.392, 6.925, 7.120, 7.968, 7.464, 6.130, 6.384, 6.135, 4.210, 4.246, 6.325, 5.263, 7.477, 8.281, 7.587, 7.039, 9.047, 9.133, 9.654, 9.590, 10.670, 9.215, 9.190, 10.055, 8.012, 7.007, 7.361, 6.144, 5.925, 5.555, 6.329, 4.814, 4.894, 4.761] + y = [10.188, 9.889, 9.712, 10.745, 8.674, 7.991, 10.291, 11.073, 9.416, 8.385, 9.152, 7.243, 6.302, 7.443, 6.483, 7.963, 8.253, 7.605, 8.842, 9.327, 10.088, 7.251, 8.285, 6.099, 5.309, 5.986, 4.953, 6.396, 7.471, 6.106, 5.775, 5.225, 4.796, 4.954, 3.787, 4.949, 6.853, 7.828, 6.775, 6.720, 6.853, 8.068, 6.222, 5.251, 6.956, 6.273, 7.706, 7.634, 8.841, 6.847, 5.889, 7.360, 6.511, 8.230, 7.620, 8.669, 9.269, 9.652, 8.174, 9.362, 7.546, 6.604, 8.253, 9.095, 7.354, 7.976, 6.886, 6.258, 5.824, 5.499, 6.846, 5.570, 5.985, 5.190, 4.766, 8.771, 8.245, 9.789, 10.161, 10.351, 10.605, 11.610, 11.341, 12.287, 12.322, 11.787, 13.410, 9.322, 9.015, 8.776, 9.052, 7.758, 7.826, 7.990, 8.977, 7.248, 7.894, 8.285, 6.370, 6.214, 5.342, 5.431, 3.973, 3.943, 3.230, 3.234, 2.212, 3.991, 3.892, 3.624, 5.960, 5.908, 3.339, 3.179, 2.980, 3.150, 2.375, 2.876, 2.616, 3.262, 1.675, 3.264, 4.305, 2.758, 4.055, 2.299, 0.876, 0.258, 0.312, 0.871, -1.106, -1.253, -1.489, -2.564, -1.049, -1.041, -1.011, -0.052, -1.970, -2.740, -1.931, -2.037, -1.962, -2.949, -2.983, -3.917, -4.588, -4.488, -3.289, -3.932] + z = [6.302, 7.391, 8.306, 7.526, 7.089, 6.087, 6.697, 5.822, 5.604, 7.943, 9.155, 7.752, 7.908, 8.829, 9.212, 8.407, 9.880, 10.560, 10.415, 9.754, 8.900, 6.374, 5.909, 5.719, 6.139, 4.391, 4.081, 4.415, 4.326, 5.367, 3.307, 2.640, 3.889, 4.956, 3.700, 3.430, 2.493, 2.814, 2.633, 1.449, 3.403, 3.572, 2.369, 2.281, 1.371, 0.855, 1.868, 0.359, 0.149, -0.269, -0.055, -1.268, -1.726, -0.608, 0.037, -1.377, 0.162, 0.731, -2.354, -2.175, -3.496, -3.603, -4.606, -4.199, -5.387, -5.803, -6.196, -4.563, -5.146, -4.350, -3.001, -1.895, -1.241, -1.307, -2.472, -5.551, -5.582, -6.328, -6.269, -7.274, -6.735, -7.913, -8.518, -7.133, -8.791, -9.871, -8.395, -8.346, -8.584, -8.977, -8.732, -10.002, -10.355, -11.174, -11.584, -11.936, -10.759, -11.425, -9.403, -8.469, -9.921, -11.030, -9.410, -8.336, -10.080, -9.428, -10.291, -11.333, -11.606, -12.128, -10.723, -11.893, -9.781, -10.959, -8.768, -7.344, -8.971, -9.765, -7.642, -7.816, -7.251, -6.715, -6.584, -5.765, -7.175, -6.955, -9.288, -9.222, -9.654, -9.696, -10.009, -10.928, -10.249, -10.194, -9.475, -11.596, -11.540, -11.813, -12.724, -13.193, -13.137, -8.947, -7.774, -9.383, -10.338, -8.477, -8.138, -9.017, -7.265, -6.226] + + # Test the atomic data. + str = cdp.structure.structural_data[0] + for i in xrange(len(str.atom_name)): + self.assertEqual(str.atom_name[i], atom_name[i]) + self.assertEqual(str.bonded[i], bonded[i]) + self.assertEqual(str.chain_id[i], chain_id[i]) + self.assertEqual(str.element[i], element[i]) + self.assertEqual(str.pdb_record[i], pdb_record[i]) + self.assertEqual(str.res_name[i], res_name[i]) + self.assertEqual(str.res_num[i], res_num[i]) + self.assertEqual(str.seg_id[i], seg_id[i]) + self.assertEqual(str.x[i], x[i]) + self.assertEqual(str.y[i], y[i]) + self.assertEqual(str.z[i], z[i])