Author: bugman Date: Sun Jun 22 02:32:53 2008 New Revision: 6368 URL: http://svn.gna.org/viewcvs/relax?rev=6368&view=rev Log: Updated the model-free 1.2 results file reading system test. The values are now hard coded into the test, rather than relying on a saved state file. Modified: 1.3/test_suite/system_tests/model_free.py Modified: 1.3/test_suite/system_tests/model_free.py URL: http://svn.gna.org/viewcvs/relax/1.3/test_suite/system_tests/model_free.py?rev=6368&r1=6367&r2=6368&view=diff ============================================================================== --- 1.3/test_suite/system_tests/model_free.py (original) +++ 1.3/test_suite/system_tests/model_free.py Sun Jun 22 02:32:53 2008 @@ -633,59 +633,79 @@ # Alias the current data pipe. cdp = ds[ds.current_pipe] + # The spin specific data. + num = [3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 27, 28, 29, 30, 31, 33, 34, 35] + select = [False, False, False, False, False, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, False, False, False] + model = ['m6', 'm8', 'm6', 'm6', 'm5', 'm5', 'm6', 'm5', 'm5', 'm5', 'm5', 'm5', 'm5', 'm5', 'm5', 'm5', 'm5', 'm5', 'm5', 'm5', 'm5', 'm8'] + params = [['S2f', 'tf', 'S2', 'ts'], ['S2f', 'tf', 'S2', 'ts', 'Rex'], ['S2f', 'tf', 'S2', 'ts'], ['S2f', 'tf', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'tf', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'S2', 'ts'], ['S2f', 'tf', 'S2', 'ts', 'Rex']] + s2 = [0.36670427146403667, 0.29007016882193892, 0.32969827132809559, 0.32795333510352148, 0.48713005133752196, 0.40269538236298569, 0.40700811448591556, 0.4283551026406261, 0.51176783207279875, 0.40593664887508263, 0.39437732735324443, 0.51457448574034614, 0.3946900969237977, 0.44740698217286901, 0.48527716982891644, 0.40845486062540021, 0.45839900995265137, 0.52650140958170921, 0.4293599736020427, 0.4057313062564018, 0.49877862202992485, 0.2592017578673716] + s2f = [0.74487419686217116, 0.75358958979175727, 0.77751085082436211, 0.79095600331751026, 0.81059857999556584, 0.83190224667917501, 0.80119109731193627, 0.83083248649122576, 0.86030420847112021, 0.84853537580616367, 0.82378413185968968, 0.82419108009774422, 0.85121172821954216, 0.8736616181472916, 0.84117641395909415, 0.82881488883235521, 0.82697284935760407, 0.85172375147802715, 0.81366357660551614, 0.80525752789388483, 0.87016608774434312, 0.72732036363757913] + s2s = [0.49230363061145249, 0.38491796164819009, 0.4240433056059994, 0.41462904855388333, 0.60095102971952741, 0.48406574687168274, 0.50800379067049317, 0.51557336720143987, 0.59486845122178478, 0.47839684761453399, 0.47873867934666214, 0.62433881919629686, 0.46368028522041266, 0.51210557140148982, 0.57690296800513374, 0.49281795745831319, 0.55430962492751434, 0.61815983018913379, 0.5276873464009153, 0.50385285725620466, 0.57319933407525203, 0.35637907423767778] + tf = [51.972302580836775, 40.664901270582988, 28.130299965023671, 33.804249387275249, None, None, 39.01236115991609, None, None, None, None, None, None, None, None, None, None, None, None, None, None, 44.039078787981225] + ts = [4485.91415175767, 4102.7781982031429, 3569.2837792404325, 6879.5308400989479, 3372.9879908647699, 4029.0617588044606, 4335.5290462417324, 4609.1336532777468, 2628.5638771308277, 3618.1332115807745, 6208.3028336637644, 3763.0843884066526, 3847.9994107906346, 2215.2061317769703, 2936.1282626562524, 3647.0715185456729, 3803.6990762708042, 2277.5259401416288, 3448.4496004396187, 3884.6917561878495, 1959.3267951363712, 4100.8496898773756] + rex = [None, 4102.7781982031429, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, 4100.8496898773756] + r1_500 = [2.2480000000000002, 2.2679999999999998, 2.2309999999999999, 2.383, 2.1960000000000002, 2.3570000000000002, 2.3340000000000001, 2.3999999999999999, 2.2839999999999998, 2.3889999999999998, 2.375, 2.274, 2.407, 2.3220000000000001, 2.2130000000000001, 2.351, 2.3260000000000001, 2.2949999999999999, 2.2829999999999999, 2.302, 2.2719999999999998, 2.2280000000000002] + r2_500 = [5.3419999999999996, 5.3730000000000002, 5.1280000000000001, 5.6749999999999998, 5.9669999999999996, 5.8410000000000002, 5.774, 6.0419999999999998, 6.3129999999999997, 5.9210000000000003, 6.1269999999999998, 6.1120000000000001, 6.0570000000000004, 5.6399999999999997, 6.2809999999999997, 5.8890000000000002, 5.875, 6.1429999999999998, 5.7370000000000001, 5.5490000000000004, 5.7110000000000003, 5.4020000000000001] + noe_500 = [0.4617, 0.46560000000000001, 0.61670000000000003, 0.60860000000000003, 0.68869999999999998, 0.6663, 0.58620000000000005, 0.64939999999999998, 0.61070000000000002, 0.61180000000000001, 0.73129999999999995, 0.69650000000000001, 0.65139999999999998, 0.4929, 0.65920000000000001, 0.63029999999999997, 0.64380000000000004, 0.53500000000000003, 0.63839999999999997, 0.65000000000000002, 0.49909999999999999, 0.45979999999999999] + r1_600 = [1.8879999999999999, 1.992, 2.0270000000000001, 1.9790000000000001, 1.9399999999999999, 2.0550000000000002, 2.0030000000000001, 2.0139999999999998, 1.982, 2.1000000000000001, 2.008, 1.927, 2.1019999999999999, 2.0830000000000002, 1.9910000000000001, 2.036, 1.9990000000000001, 1.9490000000000001, 1.976, 1.9870000000000001, 2.0, 1.9379999999999999] + r2_600 = [5.6100000000000003, 5.7869999999999999, 5.4029999999999996, 6.1849999999999996, 6.3150000000000004, 5.9809999999999999, 6.1600000000000001, 6.2460000000000004, 6.4340000000000002, 6.0069999999999997, 6.399, 6.6799999999999997, 6.1369999999999996, 5.952, 6.3239999999999998, 5.9699999999999998, 6.3979999999999997, 6.4379999999999997, 6.1139999999999999, 6.0960000000000001, 6.3250000000000002, 6.1050000000000004] + noe_600 = [0.62929999999999997, 0.64429999999999998, 0.5393, 0.71509999999999996, 0.73870000000000002, 0.75580000000000003, 0.64239999999999997, 0.74429999999999996, 0.69440000000000002, 0.73140000000000005, 0.7681, 0.73399999999999999, 0.75680000000000003, 0.62470000000000003, 0.73529999999999995, 0.73740000000000006, 0.73080000000000001, 0.6603, 0.70899999999999996, 0.69040000000000001, 0.59199999999999997, 0.56830000000000003] + r1_750 = [1.6220000000000001, 1.706, 1.73, 1.665, 1.627, 1.768, 1.706, 1.7030000000000001, 1.7649999999999999, 1.8129999999999999, 1.675, 1.6339999999999999, 1.845, 1.7829999999999999, 1.764, 1.7470000000000001, 1.681, 1.647, 1.6850000000000001, 1.667, 1.7010000000000001, 1.6850000000000001] + r2_750 = [6.2619999999999996, 6.5359999999999996, 5.8959999999999999, 6.6840000000000002, 6.8819999999999997, 6.7569999999999997, 6.5620000000000003, 7.0030000000000001, 6.9740000000000002, 6.649, 6.9829999999999997, 7.2309999999999999, 6.4429999999999996, 6.6840000000000002, 6.8070000000000004, 6.4850000000000003, 6.9400000000000004, 6.944, 6.4640000000000004, 6.4889999999999999, 6.9009999999999998, 6.9539999999999997] + noe_750 = [0.61909999999999998, 0.65890000000000004, 0.72009999999999996, 0.71009999999999995, 0.75219999999999998, 0.80420000000000003, 0.70020000000000004, 0.81999999999999995, 0.81040000000000001, 0.83409999999999995, 0.81299999999999994, 0.81910000000000005, 0.7782, 0.74760000000000004, 0.8115, 0.7379, 0.81100000000000005, 0.78249999999999997, 0.75729999999999997, 0.78259999999999996, 0.75139999999999996, 0.65210000000000001] + # Diffusion tensor type. - self.assertEqual(ds['orig'].diff.type, cdp.diff.type) + self.assertEqual(cdp.diff.type, 'sphere') # tm. - self.assertEqual(ds['orig'].diff.tm, cdp.diff.tm) + self.assertEqual(cdp.diff.tm, 6.2029050826362826e-09) # Loop over the residues of the original data. for i in xrange(len(cdp.mol[0].res)): # Aliases - orig_data_res = ds['orig'].mol[0].res[i] - new_data_res = cdp.mol[0].res[i] - orig_data = ds['orig'].mol[0].res[i].spin[0] - new_data = cdp.mol[0].res[i].spin[0] + res = cdp.mol[0].res[i] + spin = cdp.mol[0].res[i].spin[0] # Spin info tests. - self.assertEqual(orig_data_res.num, new_data_res.num) - self.assertEqual(orig_data_res.name, new_data_res.name) - self.assertEqual(orig_data.num, new_data.num) - self.assertEqual(orig_data.name, new_data.name) - self.assertEqual(orig_data.select, new_data.select) - - # Skip deselected residues. - if not orig_data.select: + self.assertEqual(num[i], res.num) + self.assertEqual('XXX', res.name) + self.assertEqual(None, spin.num) + self.assertEqual(None, spin.name) + self.assertEqual(select[i], spin.select) + + # Skip deselected spins. + if not select[i]: continue # Model-free tests. - self.assertEqual(orig_data.model, new_data.model) - self.assertEqual(orig_data.params, new_data.params) - self.assertEqual(orig_data.s2, new_data.s2) - self.assertEqual(orig_data.s2f, new_data.s2f) - self.assertEqual(orig_data.s2s, new_data.s2s) - self.assertEqual(orig_data.local_tm, new_data.local_tm) - self.assertEqual(orig_data.te, new_data.te) - self.assertEqual(orig_data.tf, new_data.tf) - self.assertEqual(orig_data.ts, new_data.ts) - self.assertEqual(orig_data.rex, new_data.rex) - self.assertEqual(orig_data.r, new_data.r) - self.assertEqual(orig_data.csa, new_data.csa) + self.assertEqual(model[i], spin.model) + self.assertEqual(params[i], spin.params) + self.assertEqual(s2[i], spin.s2) + self.assertEqual(s2f[i], spin.s2f) + self.assertEqual(s2s[i], spin.s2s) + self.assertEqual(None, spin.local_tm) + self.assertEqual(None, spin.te) + self.assertEqual(tf[i], spin.tf) + self.assertEqual(ts[i], spin.ts) + self.assertEqual(rex[i], spin.rex) + self.assertEqual(1.02, spin.r) + self.assertEqual(-170.0, spin.csa) # Minimisation statistic tests. - self.assertEqual(orig_data.chi2, new_data.chi2) - self.assertEqual(orig_data.iter, new_data.iter) - self.assertEqual(orig_data.f_count, new_data.f_count) - self.assertEqual(orig_data.g_count, new_data.g_count) - self.assertEqual(orig_data.h_count, new_data.h_count) - self.assertEqual(orig_data.warning, new_data.warning) + self.assertEqual(88.0888600975, spin.chi2) + self.assertEqual(1, spin.iter) + self.assertEqual(20, spin.f_count) + self.assertEqual(2, spin.g_count) + self.assertEqual(1, spin.h_count) + self.assertEqual(None, spin.warning) # Relaxation data tests. - self.assertEqual(orig_data.ri_labels, new_data.ri_labels) - self.assertEqual(orig_data.remap_table, new_data.remap_table) - self.assertEqual(orig_data.frq_labels, new_data.frq_labels) - self.assertEqual(orig_data.relax_data, new_data.relax_data) - self.assertEqual(orig_data.relax_error, new_data.relax_error) + self.assertEqual(['R1','R2','NOE','R1','R2','NOE','R1','R2','NOE'], spin.ri_labels) + self.assertEqual([0,0,0,1,1,1,2,2,2], spin.remap_table) + self.assertEqual(['500','600','750'], spin.frq_labels) + self.assertEqual([500000000.0,600000000.0,750000000.0], spin.frq) + self.assertEqual(relax_data[i], spin.relax_data) + self.assertEqual(relax_error[i], spin.relax_error) def test_select_m4(self):