Author: bugman
Date: Mon Dec 20 14:05:59 2010
New Revision: 11904
URL: http://svn.gna.org/viewcvs/relax?rev=11904&view=rev
Log:
Added a system test for reading relax 1.2.x version results files.
This is from Sebastian Morin's PSE-4 data, truncated, and is to catch the bug
of not being able to
handle simulations.
Added:
1.3/test_suite/shared_data/results_files/pse_trunc.bz2 (with props)
Modified:
1.3/test_suite/system_tests/model_free.py
Added: 1.3/test_suite/shared_data/results_files/pse_trunc.bz2
URL:
http://svn.gna.org/viewcvs/relax/1.3/test_suite/shared_data/results_files/pse_trunc.bz2?rev=11904&view=auto
==============================================================================
Binary file - no diff available.
Propchange: 1.3/test_suite/shared_data/results_files/pse_trunc.bz2
------------------------------------------------------------------------------
svn:mime-type = application/octet-stream
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=11904&r1=11903&r2=11904&view=diff
==============================================================================
--- 1.3/test_suite/system_tests/model_free.py (original)
+++ 1.3/test_suite/system_tests/model_free.py Mon Dec 20 14:05:59 2010
@@ -1466,6 +1466,141 @@
j = j + 1
+ def test_read_results_1_2_pse(self):
+ """Read the truncated relax 1.2 model-free results file for PSE-4."""
+
+ # Read the results.
+ self.interpreter.results.read(file='pse_trunc',
dir=__main__.install_path +
sep+'test_suite'+sep+'shared_data'+sep+'results_files')
+
+ # Debugging print out.
+ print(cdp)
+
+ # 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, 0.37670424516405815, None, None, None, None, None,
None, None, None, None, None, None, None, None, None, None, None, None, None,
None, 0.71472288436387088]
+ 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]
+ r1_500_err = [0.044999999999999998, 0.044999999999999998,
0.044499999999999998, 0.048000000000000001, 0.043999999999999997, 0.047,
0.0465, 0.048000000000000001, 0.045499999999999999, 0.048000000000000001,
0.047500000000000001, 0.045499999999999999, 0.048000000000000001, 0.0465,
0.044499999999999998, 0.047, 0.0465, 0.045499999999999999,
0.045499999999999999, 0.045999999999999999, 0.045499999999999999,
0.044499999999999998]
+ r2_500_err = [0.107, 0.1075, 0.10249999999999999, 0.1135,
0.11899999999999999, 0.11650000000000001, 0.11600000000000001, 0.121, 0.1265,
0.11799999999999999, 0.123, 0.122, 0.1215, 0.1125, 0.17599999999999999,
0.11749999999999999, 0.11749999999999999, 0.123, 0.1145, 0.111, 0.1145, 0.108]
+ noe_500_err = [0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003]
+ r1_600_err = [0.037999999999999999, 0.040000000000000001,
0.040500000000000001, 0.0395, 0.0385, 0.041000000000000002,
0.040000000000000001, 0.040500000000000001, 0.040000000000000001,
0.042000000000000003, 0.041500000000000002, 0.039, 0.042000000000000003,
0.042000000000000003, 0.0395, 0.040500000000000001, 0.040000000000000001,
0.039, 0.0395, 0.040000000000000001, 0.040500000000000001, 0.039]
+ r2_600_err = [0.1125, 0.11550000000000001, 0.108, 0.1235, 0.1265,
0.1275, 0.123, 0.125, 0.1285, 0.12, 0.128, 0.13350000000000001, 0.1225,
0.11899999999999999, 0.1265, 0.1195, 0.128, 0.129, 0.1225, 0.122, 0.1265,
0.1225]
+ noe_600_err = [0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003]
+ r1_750_err = [0.032500000000000001, 0.034000000000000002,
0.035000000000000003, 0.033500000000000002, 0.032500000000000001,
0.035499999999999997, 0.034000000000000002, 0.034000000000000002,
0.035499999999999997, 0.036499999999999998, 0.033500000000000002,
0.032500000000000001, 0.036999999999999998, 0.035499999999999997,
0.035499999999999997, 0.035000000000000003, 0.033500000000000002,
0.033000000000000002, 0.034000000000000002, 0.033000000000000002,
0.034000000000000002, 0.033500000000000002]
+ r2_750_err = [0.1255, 0.1305, 0.11799999999999999,
0.13400000000000001, 0.13800000000000001, 0.13550000000000001,
0.13150000000000001, 0.14050000000000001, 0.13950000000000001,
0.13300000000000001, 0.14000000000000001, 0.14449999999999999, 0.129,
0.13400000000000001, 0.13600000000000001, 0.1295, 0.13850000000000001,
0.13900000000000001, 0.1295, 0.13, 0.13800000000000001, 0.13900000000000001]
+ noe_750_err = [0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003, 0.050000000000000003,
0.050000000000000003, 0.050000000000000003]
+
+ # Misc tests.
+ self.assertEqual(cdp.pipe_type, 'mf')
+ self.assertEqual(cdp.hybrid_pipes, [])
+
+ # Diffusion tensor tests.
+ self.assertEqual(cdp.diff_tensor.type, 'sphere')
+ self.assertEqual(cdp.diff_tensor.tm, 6.2029050826362826e-09)
+
+ # Global minimisation statistic tests.
+ self.assertEqual(cdp.chi2, 88.0888600975)
+ self.assertEqual(cdp.iter, 1)
+ self.assertEqual(cdp.f_count, 20)
+ self.assertEqual(cdp.g_count, 2)
+ self.assertEqual(cdp.h_count, 1)
+ self.assertEqual(cdp.warning, None)
+
+ # Global relaxation data tests.
+ self.assertEqual(cdp.ri_labels, ['R1', 'R2', 'NOE', 'R1', 'R2',
'NOE', 'R1', 'R2', 'NOE'])
+ self.assertEqual(cdp.remap_table, [0, 0, 0, 1, 1, 1, 2, 2, 2])
+ self.assertEqual(cdp.frq_labels, ['500', '600', '750'])
+ self.assertEqual(cdp.frq, [500000000.0, 600000000.0, 750000000.0])
+ self.assertEqual(cdp.noe_r1_table, [None, None, 0, None, None, 3,
None, None, 6])
+ self.assertEqual(cdp.num_frq, 3)
+ self.assertEqual(cdp.num_ri, 9)
+
+ # Loop over the residues of the original data.
+ j = 0
+ for i in xrange(len(cdp.mol[0].res)):
+ # Aliases
+ res = cdp.mol[0].res[i]
+ spin = cdp.mol[0].res[i].spin[0]
+
+ # Debugging print out.
+ print(res)
+ print(spin)
+
+ # Spin info tests.
+ self.assertEqual(res.num, num[i])
+ self.assertEqual(res.name, 'XXX')
+ self.assertEqual(spin.num, None)
+ self.assertEqual(spin.name, None)
+ self.assertEqual(spin.select, select[i])
+ self.assertEqual(spin.fixed, False)
+
+ # Skip deselected spins.
+ if not select[i]:
+ continue
+
+ # Structural info.
+ self.assertEqual(spin.heteronuc_type, '15N')
+ self.assertEqual(spin.proton_type, '1H')
+ self.assertEqual(spin.attached_proton, None)
+ self.assertEqual(spin.nucleus, None)
+
+ # Model-free tests.
+ self.assertEqual(spin.model, model[j])
+ self.assertEqual(spin.equation, 'mf_ext')
+ self.assertEqual(spin.params, params[j])
+ self.assertEqual(spin.s2, s2[j])
+ self.assertEqual(spin.s2f, s2f[j])
+ self.assertEqual(spin.s2s, s2s[j])
+ self.assertEqual(spin.local_tm, None)
+ self.assertEqual(spin.te, None)
+ if tf[j] != None:
+ tf[j] = tf[j]*1e-12
+ self.assertEqual(spin.tf, tf[j])
+ self.assertEqual(spin.ts, ts[j]*1e-12)
+ if rex[j] != None:
+ rex[j] = rex[j]/(2.0*pi*500000000.0)**2
+ self.assertEqual(spin.rex, rex[j])
+ self.assertEqual(spin.r, 1.0200000000000001e-10)
+ self.assertEqual(spin.csa, -0.00016999999999999999)
+
+ # Minimisation statistic tests.
+ self.assertEqual(spin.chi2, None)
+ self.assertEqual(spin.iter, None)
+ self.assertEqual(spin.f_count, None)
+ self.assertEqual(spin.g_count, None)
+ self.assertEqual(spin.h_count, None)
+ self.assertEqual(spin.warning, None)
+
+ # Relaxation data tests.
+ self.assertEqual(spin.ri_labels, ['R1', 'R2', 'NOE', 'R1', 'R2',
'NOE', 'R1', 'R2', 'NOE'])
+ self.assertEqual(spin.remap_table, [0, 0, 0, 1, 1, 1, 2, 2, 2])
+ self.assertEqual(spin.frq_labels, ['500', '600', '750'])
+ self.assertEqual(spin.frq, [500000000.0, 600000000.0,
750000000.0])
+ self.assertEqual(spin.noe_r1_table, [None, None, 0, None, None,
3, None, None, 6])
+ self.assertEqual(spin.num_frq, 3)
+ self.assertEqual(spin.num_ri, 9)
+ self.assertEqual(spin.relax_data, [r1_500[j], r2_500[j],
noe_500[j], r1_600[j], r2_600[j], noe_600[j], r1_750[j], r2_750[j],
noe_750[j]])
+ self.assertEqual(spin.relax_error, [r1_500_err[j],
r2_500_err[j], noe_500_err[j], r1_600_err[j], r2_600_err[j], noe_600_err[j],
r1_750_err[j], r2_750_err[j], noe_750_err[j]])
+
+ # Secondary index.
+ j = j + 1
+
+
def test_read_results_1_3(self):
"""Read a relax 1.3 model-free results file using the user function
results.read()."""
r11904 - in /1.3/test_suite: shared_data/results_files/pse_trunc.bz2 system_tests/model_free.py