test_suite.system_tests.relax

42 """Class for testing various aspects specific to relaxation dispersion curve-fitting.""" 43

44 - def __init__(self, methodName='runTest'):

45 """Skip certain tests if the C modules are non-functional. 46 47 @keyword methodName: The name of the test. 48 @type methodName: str 49 """ 50 51 # Execute the base class method. 52 super(Relax_disp, self).__init__(methodName) 53 54 # Missing module. 55 if not dep_check.C_module_exp_fn: 56 # The list of tests to skip. 57 to_skip = [ 58 "test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp", 59 "test_exp_fit", 60 "test_m61_exp_data_to_m61", 61 "test_r1rho_kjaergaard", 62 "test_value_write_calc_rotating_frame_params_auto_analysis" 63 ] 64 65 # Store in the status object. 66 if methodName in to_skip: 67 status.skipped_tests.append([methodName, 'Relax curve-fitting C module', self._skip_type])

68 69

70 - def setUp(self):

71 """Set up for all the functional tests.""" 72 73 # Create the data pipe. 74 self.interpreter.pipe.create('relax_disp', 'relax_disp') 75 76 # Create a temporary directory for dumping files. 77 ds.tmpdir = mkdtemp() 78 self.tmpdir = ds.tmpdir

79 80

81 - def setup_bug_22146_unpacking_r2a_r2b_cluster(self, folder=None, model_analyse=None, places = 7):

82 """Setup data for the catch of U{bug #22146<https://web.archive.org/web/https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered full dispersion models. 83 84 @keyword folder: The name of the folder for the test data. 85 @type folder: str 86 @keyword model_analyse: The name of the model which will be tested. 87 @type model_analyse: str 88 """ 89 90 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 91 92 # Data. 93 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22146_unpacking_r2a_r2b_cluster'+sep+folder 94 95 ## Experiments 96 # Exp 1 97 sfrq_1 = 500.0*1E6 98 r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 99 time_T2_1 = 0.05 100 ncycs_1 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 50] 101 # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 102 #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 103 r2eff_errs_1 = [0.0] * len(ncycs_1) 104 exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 105 106 sfrq_2 = 600.0*1E6 107 r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 108 time_T2_2 = 0.06 109 ncycs_2 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 60] 110 # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 111 #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 112 r2eff_errs_2 = [0.0] * len(ncycs_2) 113 exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 114 115 sfrq_3 = 700.0*1E6 116 r20_key_3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_3) 117 time_T2_3 = 0.07 118 ncycs_3 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 50, 70] 119 # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 120 #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 121 r2eff_errs_3 = [0.0] * len(ncycs_3) 122 exp_3 = [sfrq_3, time_T2_3, ncycs_3, r2eff_errs_3] 123 124 # Collect all exps 125 exps = [exp_1, exp_2, exp_3] 126 127 R20 = [5.1, 5.2, 5.3, 10.1, 10.2, 10.3, 6.1, 6.2, 6.3, 11.1, 11.2, 11.3, 7.1, 7.2, 7.3, 12.1, 12.2, 12.3, 8.1, 8.2, 8.3, 13.1, 13.2, 13.3] 128 dw_arr = [1.0, 2.0, 3.0, 4.0] 129 pA_arr = [0.9] 130 kex_arr = [1000.] 131 132 spins = [ 133 ['Ala', 1, 'N', {'r2a': {r20_key_1: R20[0], r20_key_2: R20[1], r20_key_3: R20[2]}, 'r2b': {r20_key_1: R20[3], r20_key_2: R20[4], r20_key_3: R20[5]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[0]}], 134 ['Ala', 2, 'N', {'r2a': {r20_key_1: R20[6], r20_key_2: R20[7], r20_key_3: R20[8]}, 'r2b': {r20_key_1: R20[9], r20_key_2: R20[10], r20_key_3: R20[11]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[1]}], 135 ['Ala', 3, 'N', {'r2a': {r20_key_1: R20[12], r20_key_2: R20[13], r20_key_3: R20[14]}, 'r2b': {r20_key_1: R20[15], r20_key_2: R20[16], r20_key_3: R20[17]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[2]}], 136 ['Ala', 4, 'N', {'r2a': {r20_key_1: R20[18], r20_key_2: R20[19], r20_key_3: R20[20]}, 'r2b': {r20_key_1: R20[21], r20_key_2: R20[22], r20_key_3: R20[23]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[3]}], 137 ] 138 139 # Create the data pipe. 140 pipe_name = 'base pipe' 141 pipe_type = 'relax_disp' 142 pipe_bundle = 'relax_disp' 143 self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type, bundle = pipe_bundle) 144 145 # Generate the sequence. 146 for res_name, res_num, spin_name, params in spins: 147 self.interpreter.spin.create(res_name=res_name, res_num=res_num, spin_name=spin_name) 148 149 # Set isotope 150 self.interpreter.spin.isotope('15N', spin_id='@N') 151 152 # Now loop over the experiments, to set the variables in relax. 153 exp_ids = [] 154 for exp in exps: 155 sfrq, time_T2, ncycs, r2eff_errs = exp 156 exp_id = 'CPMG_%3.1f' % (sfrq/1E6) 157 exp_ids.append(exp_id) 158 159 ids = [] 160 for ncyc in ncycs: 161 nu_cpmg = ncyc / time_T2 162 cur_id = '%s_%.1f' % (exp_id, nu_cpmg) 163 ids.append(cur_id) 164 165 # Set the spectrometer frequency. 166 self.interpreter.spectrometer.frequency(id=cur_id, frq=sfrq) 167 168 # Set the experiment type. 169 self.interpreter.relax_disp.exp_type(spectrum_id=cur_id, exp_type=EXP_TYPE_CPMG_SQ) 170 171 # Set the relaxation dispersion CPMG constant time delay T (in s). 172 self.interpreter.relax_disp.relax_time(spectrum_id=cur_id, time=time_T2) 173 174 # Set the relaxation dispersion CPMG frequencies. 175 self.interpreter.relax_disp.cpmg_setup(spectrum_id=cur_id, cpmg_frq=nu_cpmg) 176 177 print("\n\nThe experiment IDs are %s." % cdp.spectrum_ids) 178 179 ### Now do fitting. 180 # Change pipe. 181 182 pipe_name_MODEL = "%s_%s"%(pipe_name, model_analyse) 183 self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_MODEL, bundle_to = pipe_bundle) 184 self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 185 186 # Now read data in. 187 for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 188 exp_id = exp_ids[mi] 189 exp = exps[mi] 190 sfrq, time_T2, ncycs, r2eff_errs = exp 191 192 # Then loop over the spins. 193 for res_name, res_num, spin_name, params in spins: 194 cur_spin_id = ":%i@%s"%(res_num, spin_name) 195 196 # Define file name 197 file_name = "%s%s.txt" % (exp_id, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 198 199 # Read in the R2eff file to put into spin structure. 200 self.interpreter.relax_disp.r2eff_read_spin(id=exp_id, spin_id=cur_spin_id, file=file_name, dir=data_path, disp_point_col=1, data_col=2, error_col=3) 201 202 # Then select model. 203 self.interpreter.relax_disp.select_model(model=model_analyse) 204 205 # Then cluster 206 self.interpreter.relax_disp.cluster('model_cluster', ":1-100") 207 208 # Grid search 209 low_arr = R20 + dw_arr + pA_arr + kex_arr 210 self.interpreter.grid_search(lower=low_arr, upper=low_arr, inc=1, constraints=True, verbosity=1) 211 212 # Then loop over the defined spins and read the parameters. 213 for i in range(len(spins)): 214 res_name, res_num, spin_name, params = spins[i] 215 cur_spin_id = ":%i@%s"%(res_num, spin_name) 216 cur_spin = return_spin(cur_spin_id) 217 218 for mo_param in cur_spin.params: 219 print(mo_param) 220 # The R2 is a dictionary, depending on spectrometer frequency. 221 if isinstance(getattr(cur_spin, mo_param), dict): 222 for key, val in getattr(cur_spin, mo_param).items(): 223 should_be = params[mo_param][key] 224 print(cur_spin.model, res_name, cur_spin_id, mo_param, key, float(val), should_be) 225 self.assertAlmostEqual(val, should_be) 226 else: 227 should_be = float(params[mo_param]) 228 val = getattr(cur_spin, mo_param) 229 print(cur_spin.model, res_name, cur_spin_id, mo_param, val, should_be) 230 self.assertAlmostEqual(val, should_be) 231 232 # Test chi2. 233 # At this point the chi-squared value at the solution should be zero, as the relaxation data was created with the same parameter values. 234 self.assertAlmostEqual(cur_spin.chi2, 0.0, places = places)

235 236

237 - def setup_hansen_cpmg_data(self, model=None):

238 """Set up the data for the test_hansen_cpmg_data_*() system tests. 239 240 @keyword model: The name of the model which will be tested. 241 @type model: str 242 """ 243 244 # Create the data pipe and load the base data. 245 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 246 self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 247 self.interpreter.results.read(data_path+sep+'base_pipe') 248 self.interpreter.deselect.spin(':4') 249 250 # Set the nuclear isotope data. 251 self.interpreter.spin.isotope('15N') 252 253 # Create the R2eff data pipe and load the results. 254 self.interpreter.pipe.create(pipe_name='R2eff - relax_disp', pipe_type='relax_disp') 255 self.interpreter.pipe.switch(pipe_name='R2eff - relax_disp') 256 self.interpreter.results.read(data_path+sep+'r2eff_pipe') 257 self.interpreter.deselect.spin(':4') 258 259 # The model data pipe. 260 pipe_name = "%s - relax_disp" % model 261 self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 262 self.interpreter.pipe.switch(pipe_name=pipe_name) 263 264 # Set the model. 265 self.interpreter.relax_disp.select_model(model=model) 266 267 # Copy the data. 268 self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to=pipe_name, param='r2eff')

269 270

271 - def setup_kteilum_fmpoulsen_makke_cpmg_data(self, model=None, expfolder=None):

272 """Set up the data for the test_kteilum_fmpoulsen_makke_cpmg_data_*() system tests. 273 274 @keyword model: The name of the model which will be tested. 275 @type model: str 276 """ 277 278 # Create the data pipe and load the base data. 279 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder 280 self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 281 self.interpreter.results.read(data_path+sep+'ini_setup_trunc') 282 283 # Create the R2eff data pipe and load the results. 284 self.interpreter.pipe.create(pipe_name='R2eff', pipe_type='relax_disp') 285 self.interpreter.pipe.switch(pipe_name='R2eff') 286 self.interpreter.results.read(data_path+sep+'r2eff_pipe_trunc') 287 288 # The model data pipe. 289 pipe_name = "%s - relax_disp" % model 290 self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 291 self.interpreter.pipe.switch(pipe_name=pipe_name) 292 293 # Set the model. 294 self.interpreter.relax_disp.select_model(model=model) 295 296 # Copy the data. 297 self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff')

298 299

300 - def setup_korzhnev_2005_data(self, data_list=[]):

301 """Set up the data for the test_korzhnev_2005_data_*() system tests using the 'NS MMQ 2-site' model. 302 303 This loads the proton-heteronuclear SQ, ZQ, DQ, and MQ (MMQ) data from: 304 305 - Dmitry M. Korzhnev, Philipp Neudecker, Anthony Mittermaier, Vladislav Yu. Orekhov, and Lewis E. Kay (2005) Multiple-site exchange in proteins studied with a suite of six NMR relaxation dispersion experiments: An application to the folding of a Fyn SH3 domain mutant. 127, 15602-15611 (U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}). 306 307 It consists of the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 308 309 310 @keyword data_list: The list of data to load. It can contain 'SQ', '1H SQ', 'ZQ', 'DQ', 'MQ', and '1H MQ'. 311 @type data_list: list of str 312 """ 313 314 # Create the data pipe and load the base data. 315 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 316 self.interpreter.pipe.create(pipe_name='Korzhnev et al., 2005', pipe_type='relax_disp') 317 318 # Create the spin system. 319 self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 320 self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 321 self.interpreter.spin.element('H', spin_id='@H') 322 self.interpreter.spin.element('N', spin_id='@N') 323 self.interpreter.spin.isotope('1H', spin_id='@H') 324 self.interpreter.spin.isotope('15N', spin_id='@N') 325 326 # Define the magnetic dipole-dipole relaxation interaction. 327 self.interpreter.interatom.define(spin_id1=':9@N', spin_id2=':9@H', direct_bond=True) 328 329 # The spectral data - experiment ID, R2eff file name, experiment type, spin ID string, spectrometer frequency in Hertz, relaxation time. 330 data = [ 331 ['1H SQ', '1H_SQ_CPMG_500_MHz', 'hs_500.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 500e6, 0.03], 332 ['1H SQ', '1H_SQ_CPMG_600_MHz', 'hs_600.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 600e6, 0.03], 333 ['1H SQ', '1H_SQ_CPMG_800_MHz', 'hs_800.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 800e6, 0.03], 334 ['SQ', '15N_SQ_CPMG_500_MHz', 'ns_500.res', EXP_TYPE_CPMG_SQ, ':9@N', 500e6, 0.04], 335 ['SQ', '15N_SQ_CPMG_600_MHz', 'ns_600.res', EXP_TYPE_CPMG_SQ, ':9@N', 600e6, 0.04], 336 ['SQ', '15N_SQ_CPMG_800_MHz', 'ns_800.res', EXP_TYPE_CPMG_SQ, ':9@N', 800e6, 0.04], 337 ['DQ', '15N_DQ_CPMG_500_MHz', 'dq_500.res', EXP_TYPE_CPMG_DQ, ':9@N', 500e6, 0.03], 338 ['DQ', '15N_DQ_CPMG_600_MHz', 'dq_600.res', EXP_TYPE_CPMG_DQ, ':9@N', 600e6, 0.03], 339 ['DQ', '15N_DQ_CPMG_800_MHz', 'dq_800.res', EXP_TYPE_CPMG_DQ, ':9@N', 800e6, 0.03], 340 ['ZQ', '15N_ZQ_CPMG_500_MHz', 'zq_500.res', EXP_TYPE_CPMG_ZQ, ':9@N', 500e6, 0.03], 341 ['ZQ', '15N_ZQ_CPMG_600_MHz', 'zq_600.res', EXP_TYPE_CPMG_ZQ, ':9@N', 600e6, 0.03], 342 ['ZQ', '15N_ZQ_CPMG_800_MHz', 'zq_800.res', EXP_TYPE_CPMG_ZQ, ':9@N', 800e6, 0.03], 343 ['1H MQ', '1H_MQ_CPMG_500_MHz', 'hm_500.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 500e6, 0.02], 344 ['1H MQ', '1H_MQ_CPMG_600_MHz', 'hm_600.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 600e6, 0.02], 345 ['1H MQ', '1H_MQ_CPMG_800_MHz', 'hm_800.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 800e6, 0.02], 346 ['MQ', '15N_MQ_CPMG_500_MHz', 'nm_500.res', EXP_TYPE_CPMG_MQ, ':9@N', 500e6, 0.02], 347 ['MQ', '15N_MQ_CPMG_600_MHz', 'nm_600.res', EXP_TYPE_CPMG_MQ, ':9@N', 600e6, 0.02], 348 ['MQ', '15N_MQ_CPMG_800_MHz', 'nm_800.res', EXP_TYPE_CPMG_MQ, ':9@N', 800e6, 0.02] 349 ] 350 cpmg_frqs_1h_sq = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 351 cpmg_frqs_sq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 352 cpmg_frqs_dq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 353 cpmg_frqs_zq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 354 cpmg_frqs_1h_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 1000.0, 1500.0, 2000.0, 2500.0] 355 cpmg_frqs_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 356 357 # Loop over the files, reading in the data. 358 for data_type, id, file, exp_type, spin_id, H_frq, relax_time in data: 359 # Skip undesired data. 360 if data_type not in data_list: 361 continue 362 363 # Alias the CPMG frequencies. 364 if data_type == 'SQ': 365 cpmg_frqs = cpmg_frqs_sq 366 elif data_type == '1H SQ': 367 cpmg_frqs = cpmg_frqs_1h_sq 368 elif data_type == 'DQ': 369 cpmg_frqs = cpmg_frqs_dq 370 elif data_type == 'ZQ': 371 cpmg_frqs = cpmg_frqs_zq 372 elif data_type == '1H MQ': 373 cpmg_frqs = cpmg_frqs_1h_mq 374 elif data_type == 'MQ': 375 cpmg_frqs = cpmg_frqs_mq 376 377 # Loop over each CPMG frequency. 378 for cpmg_frq in cpmg_frqs: 379 # The id. 380 new_id = "%s_%s" % (id, cpmg_frq) 381 382 # Set the NMR field strength. 383 self.interpreter.spectrometer.frequency(id=new_id, frq=H_frq) 384 385 # Set the relaxation dispersion experiment type. 386 self.interpreter.relax_disp.exp_type(spectrum_id=new_id, exp_type=exp_type) 387 388 # Relaxation dispersion CPMG constant time delay T (in s). 389 self.interpreter.relax_disp.relax_time(spectrum_id=new_id, time=relax_time) 390 391 # Set the CPMG frequency. 392 self.interpreter.relax_disp.cpmg_setup(spectrum_id=new_id, cpmg_frq=cpmg_frq) 393 394 # Read the R2eff data. 395 self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 396 397 # Change the model. 398 self.interpreter.relax_disp.select_model('NS MMQ 2-site')

399 400

401 - def setup_sod1wt_t25(self, pipe_name, pipe_type, pipe_name_r2eff, select_spin_index):

402 """Setup of data SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 403 404 Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 405 'SOD1-WT' CPMG data to the CR72 dispersion model. 406 407 This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 408 Data is for experiment at 25 degree Celcius. 409 """ 410 411 # Create the data pipe and load the base data. 412 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'sod1wt_t25' 413 414 # Set experiment settings. sfrq, time_T2, ncyc 415 Exps = [ 416 ["600MHz", "Z_A", 599.8908617*1E6, 0.06, [28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 50, 18, 40, 6, 12, 0, 24], ["Z_A1", "Z_A15"] ], 417 ["500MHz", "Z_B", 499.862139*1E6, 0.04, [20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0], ["Z_B1", "Z_B18"] ] ] 418 419 # Create base pipe 420 self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 421 422 # Loop throug experiments 423 id_lists = [] 424 for folder, key, sfrq, time_T2, ncycs, rep_ncyss in Exps: 425 # Read spins 426 self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 427 self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 428 429 # Make spectrum id list 430 id_list = list(key+str(i) for i in range(len(ncycs))) 431 id_lists.append(id_list) 432 433 # Read intensities 434 self.interpreter.spectrum.read_intensities(file="128_FT.ser", dir=data_path+sep+folder, int_method='height', spectrum_id=id_list, int_col=list(range(len(id_list))) ) 435 436 # Loop over experiments 437 for i in range(len(ncycs)): 438 ncyc = ncycs[i] 439 vcpmg = ncyc/time_T2 440 441 # Test if spectrum is a reference 442 if float(vcpmg) == 0.0: 443 vcpmg = None 444 else: 445 vcpmg = round(float(vcpmg), 3) 446 447 # Set current id 448 current_id = id_list[i] 449 450 # Set the current experiment type. 451 self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 452 453 # Set the NMR field strength of the spectrum. 454 self.interpreter.spectrometer.frequency(id=current_id, frq=sfrq, units='Hz') 455 456 # Relaxation dispersion CPMG constant time delay T (in s). 457 self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 458 459 # Set the relaxation dispersion CPMG frequencies. 460 self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 461 462 # Define replicated 463 self.interpreter.spectrum.replicated(spectrum_ids=Exps[0][5]) 464 self.interpreter.spectrum.replicated(spectrum_ids=Exps[1][5]) 465 466 # Perform error analysis 467 self.interpreter.spectrum.error_analysis(subset=id_lists[0]) 468 self.interpreter.spectrum.error_analysis(subset=id_lists[1]) 469 470 # Define isotope 471 self.interpreter.spin.isotope(isotope='15N') 472 473 ############# 474 475 # Define the 64 residues which was used for Global fitting 476 glob_assn = ["G10N-H", "D11N-H", "Q15N-H", "G16N-H", "G37N-H", "G41N-H", "L42N-H", "H43N-H", "H46N-H", "V47N-H", "E49N-H", 477 "E50N-H", "E51N-H", "N53N-H", "T54N-H", "G56N-H", "C57N-H", "T58N-H", "G61N-H", "H63aN-H", "F64aN-H", "N65aN-H", 478 "L67N-H", "S68N-H", "K70N-H", "G72N-H", "G73N-H", "K75N-H", "E78N-H", "R79N-H", "H80N-H", "V81N-H", "G82N-H", 479 "G85N-H", "N86N-H", "V87N-H", "S102N-H", "V103N-H", "I104N-H", "S105N-H", "A111N-H", "I112N-H", "R115N-H", 480 "V118N-H", "E121N-H", "A123N-H", "L126N-H", "G127N-H", "K128N-H", "G129N-H", "G130N-H", "N131N-H", "E133N-H", 481 "S134N-H", "T135N-H", "T137N-H", "G138N-H", "N139N-H", "A140N-H", "G141N-H", "S142N-H", "R143N-H", "C146N-H", "G147N-H"] 482 483 # Test number of global 484 self.assertEqual(64, len(glob_assn )) 485 486 ## Turn assignments into relax spin ids. 487 # Define regular expression search 488 r = re.compile("([a-zA-Z]+)([0-9]+)([a-zA-Z]+)") 489 490 # Create list to hold regular expression search 491 relax_glob_ids = [] 492 493 # Loop over assignments 494 for assn in glob_assn: 495 # Make match for the regular search 496 m = r.match(assn) 497 # Convert to relax spin string 498 relax_string = ":%s@%s"%(m.group(2), m.group(3)) 499 500 # Save the relax spin string and the regular search 501 relax_glob_ids.append([m.group(0), m.group(1), m.group(2), m.group(3), relax_string]) 502 503 ############# Deselect all spins, and select few spins 504 505 ## Deselect all spins, and select a few for analysis 506 self.interpreter.deselect.all() 507 508 # Select few spins 509 for i in select_spin_index: 510 self.interpreter.select.spin(spin_id=relax_glob_ids[i][4], change_all=False) 511 512 ############## 513 514 # Prepare for R2eff calculation 515 self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 516 self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 517 518 # Select model for points calculation 519 MODEL = "R2eff" 520 self.interpreter.relax_disp.select_model(model=MODEL) 521 # Calculate R2eff values 522 self.interpreter.calc(verbosity=1)

523 524

525 - def test_baldwin_synthetic(self):

526 """Test synthetic data of Andrew J. Baldwin B14 model whereby the simplification R20A = R20B is assumed. 527 528 Support requst sr #3154 U{https://web.archive.org/web/https://gna.org/support/index.php?3154}. 529 530 This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>} with R20A, R20B = 2. rad/s. 531 """ 532 533 # The path to the data files. 534 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 535 536 # Create pipe 537 pipe_name = 'base pipe' 538 pipe_type = 'relax_disp' 539 pipe_name_r2eff = "%s_R2eff"%(pipe_name) 540 541 # Create base pipe 542 self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 543 544 # Generate the sequence. 545 self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 546 547 # Define the isotope. 548 self.interpreter.spin.isotope('1H', spin_id='@H') 549 550 # Build the experiment IDs. 551 # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 552 ncycs = [2, 4, 8, 10, 20, 40, 500] 553 ids = [] 554 for ncyc in ncycs: 555 ids.append('CPMG_%s' % ncyc) 556 557 print("\n\nThe experiment IDs are %s." % ids) 558 559 # Set up the metadata for the experiments. 560 # This value is used in Baldwin.py. It is the 1H Larmor frequency. 561 sfrq= 200. * 1E6 562 563 # Total time of CPMG block. 564 Trelax=0.04 565 566 # First set the 567 for i in range(len(ids)): 568 id = ids[i] 569 # Set the spectrometer frequency. 570 self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 571 572 # Set the experiment type. 573 self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 574 575 # Set the relaxation dispersion CPMG constant time delay T (in s). 576 self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 577 578 # Set the relaxation dispersion CPMG frequencies. 579 ncyc = ncycs[i] 580 nu_cpmg = ncyc / Trelax 581 self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 582 583 # Prepare for R2eff reading. 584 self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 585 self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 586 587 # Try reading the R2eff file. 588 self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_r2a_eq_r2b_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 589 590 # Check the global data. 591 data = [ 592 ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 593 ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 594 ['dispersion_points', len(ncycs)], 595 ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 596 ['exp_type_list', ['SQ CPMG']], 597 ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 598 ['spectrometer_frq_count', 1], 599 ['spectrometer_frq_list', [sfrq]], 600 ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 601 ] 602 for name, value in data: 603 # Does it exist? 604 self.assert_(hasattr(cdp, name)) 605 606 # Check the object. 607 obj = getattr(cdp, name) 608 if not isinstance(data, dict): 609 self.assertEqual(obj, value) 610 611 # Check the global dictionary data. 612 else: 613 for id in ids: 614 self.assertEqual(obj[id], value[id]) 615 616 # Check the spin data. 617 n_data = [ 618 [ 50.000000, 10.367900, 0.1], 619 [ 100.000000, 10.146849, 0.1], 620 [ 200.000000, 9.765987, 0.1], 621 [ 250.000000, 9.409789, 0.1], 622 [ 500.000000, 5.829819, 0.1], 623 [ 1000.000000, 3.191928, 0.1], 624 [ 12500.000000, 2.008231, 0.1] 625 ] 626 for disp_point, value, error in n_data: 627 id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 628 self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 629 self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 630 631 # Generate r20 key. 632 r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 633 634 ## Now prepare for MODEL calculation. 635 MODEL = "B14" 636 637 # Change pipe. 638 pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 639 self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 640 self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 641 642 # Then select model. 643 self.interpreter.relax_disp.select_model(model=MODEL) 644 645 # Store grid and minimisations results. 646 grid_results = [] 647 mini_results = [] 648 649 # The grid search size (the number of increments per dimension). 650 # If None, use the default values. 651 #GRID = None 652 GRID = 13 653 # Perform Grid Search. 654 if GRID: 655 # Set the R20 parameters in the default grid search using the minimum R2eff value. 656 # This speeds it up considerably. 657 self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 658 659 # Then do grid search. 660 self.interpreter.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 661 662 # If no Grid search, set the default values. 663 else: 664 for param in MODEL_PARAMS[MODEL]: 665 self.interpreter.value.set(param=param, index=None) 666 # Do a grid search, which will store the chi2 value. 667 self.interpreter.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 668 669 # Store result. 670 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 671 grid_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 672 673 ## Now do minimisation. 674 # Standard parameters are: func_tol=1e-25, grad_tol=None, max_iter=10000000, 675 set_func_tol = 1e-10 676 set_max_iter = 1000 677 self.interpreter.minimise(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 678 679 # Store result. 680 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 681 mini_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 682 683 # Print results. 684 for i in range(len(grid_results)): 685 g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 686 m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 687 print("GRID %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 688 print("MIN %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 689 690 # Reference values from Baldwin.py. 691 # Exchange rate = k+ + k- (s-1) 692 kex=1000. 693 # Fractional population of excited state k+/kex 694 pb=0.01 695 # deltaOmega in ppm 696 dw_ppm=2. 697 #relaxation rate of ground (s-1) 698 R2g=2. 699 #relaxation rate of excited (s-1) 700 R2e=2. 701 702 # Test the parameters which created the data. 703 # This is for the 1H spin. 704 self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2[r20_key], R2g, 6) 705 706 self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 707 self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 8) 708 self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 3)

709 710

711 - def test_baldwin_synthetic_full(self):

712 """Test synthetic data of Andrew J. Baldwin B14 model. Support requst sr #3154 U{https://web.archive.org/web/https://gna.org/support/index.php?3154}. 713 714 This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>}.""" 715 716 # The path to the data files. 717 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 718 719 # Create pipe 720 pipe_name = 'base pipe' 721 pipe_type = 'relax_disp' 722 pipe_name_r2eff = "%s_R2eff"%(pipe_name) 723 724 # Create base pipe 725 self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 726 727 # Generate the sequence. 728 # Generate both a 1H spin, and 15N spin. 729 self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 730 731 # Define the isotope. 732 self.interpreter.spin.isotope('1H', spin_id='@H') 733 734 # Build the experiment IDs. 735 # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 736 ncycs = [2, 4, 8, 10, 20, 40, 500] 737 ids = [] 738 for ncyc in ncycs: 739 ids.append('CPMG_%s' % ncyc) 740 741 print("\n\nThe experiment IDs are %s." % ids) 742 743 # Set up the metadata for the experiments. 744 # This value is used in Baldwin.py. It is the 1H Larmor frequency. 745 sfrq= 200. * 1E6 746 747 # Total time of CPMG block. 748 Trelax=0.04 749 750 # First set the 751 for i in range(len(ids)): 752 id = ids[i] 753 # Set the spectrometer frequency. 754 self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 755 756 # Set the experiment type. 757 self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 758 759 # Set the relaxation dispersion CPMG constant time delay T (in s). 760 self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 761 762 # Set the relaxation dispersion CPMG frequencies. 763 ncyc = ncycs[i] 764 nu_cpmg = ncyc / Trelax 765 self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 766 767 # Prepare for R2eff reading. 768 self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 769 self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 770 771 # Try reading the R2eff file. 772 self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 773 774 # Check the global data. 775 data = [ 776 ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 777 ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 778 ['dispersion_points', len(ncycs)], 779 ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 780 ['exp_type_list', ['SQ CPMG']], 781 ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 782 ['spectrometer_frq_count', 1], 783 ['spectrometer_frq_list', [sfrq]], 784 ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 785 ] 786 for name, value in data: 787 # Does it exist? 788 self.assert_(hasattr(cdp, name)) 789 790 # Check the object. 791 obj = getattr(cdp, name) 792 if not isinstance(data, dict): 793 self.assertEqual(obj, value) 794 795 # Check the global dictionary data. 796 else: 797 for id in ids: 798 self.assertEqual(obj[id], value[id]) 799 800 # Check the spin data. 801 n_data = [ 802 [ 50.000000, 10.286255, 0.1], 803 [ 100.000000, 10.073083, 0.1], 804 [ 200.000000, 9.692746, 0.1], 805 [ 250.000000, 9.382441, 0.1], 806 [ 500.000000, 6.312396, 0.1], 807 [ 1000.000000, 3.957029, 0.1], 808 [ 12500.000000, 2.880420, 0.1] 809 ] 810 for disp_point, value, error in n_data: 811 id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 812 self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 813 self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 814 815 # Generate r20 key. 816 r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 817 818 ## Now prepare for MODEL calculation. 819 MODEL = "B14 full" 820 821 # Change pipe. 822 pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 823 self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 824 self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 825 826 # Then select model. 827 self.interpreter.relax_disp.select_model(model=MODEL) 828 829 # Store grid and minimisations results. 830 grid_results = [] 831 mini_results = [] 832 clust_results = [] 833 834 # The grid search size (the number of increments per dimension). 835 # If None, use the default values. 836 #GRID = None 837 GRID = 13 838 # Perform Grid Search. 839 if GRID: 840 # Set the R20 parameters in the default grid search using the minimum R2eff value. 841 # This speeds it up considerably. 842 self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 843 844 # Then do grid search. 845 self.interpreter.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 846 847 # If no Grid search, set the default values. 848 else: 849 for param in MODEL_PARAMS[MODEL]: 850 self.interpreter.value.set(param=param, index=None) 851 # Do a grid search, which will store the chi2 value. 852 self.interpreter.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 853 854 # Store result. 855 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 856 grid_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 857 858 ## Now do minimisation. 859 # Standard parameters are: func_tol=1e-25, grad_tol=None, max_iter=10000000, 860 set_func_tol = 1e-11 861 set_max_iter = 10000 862 self.interpreter.minimise(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 863 864 # Store result. 865 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 866 mini_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 867 868 print("\n# Now print before and after minimisation-\n") 869 870 # Print results. 871 for i in range(len(grid_results)): 872 g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 873 m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 874 print("GRID %s r2a=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 875 print("MIN %s r2b=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 876 877 # Reference values from Baldwin.py. 878 # Exchange rate = k+ + k- (s-1) 879 kex=1000. 880 # Fractional population of excited state k+/kex 881 pb=0.01 882 # deltaOmega in ppm 883 dw_ppm=2. 884 #relaxation rate of ground (s-1) 885 R2g=2. 886 #relaxation rate of excited (s-1) 887 R2e=100. 888 889 # Test the parameters which created the data. 890 # This is for the 1H spin. 891 self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2a[r20_key], R2g, 4) 892 self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2b[r20_key], R2e, 2) 893 894 self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 895 self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 6) 896 self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 2)

897 898

899 - def test_bug_21081_disp_cluster_fail(self):

900 """U{Bug #21081<https://web.archive.org/web/https://gna.org/bugs/?21081>} catch, the failure of a cluster analysis when spins are deselected.""" 901 902 # Clear the data store. 903 self.interpreter.reset() 904 905 # Load the state. 906 state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21081_disp_cluster_fail.bz2' 907 self.interpreter.state.load(state, force=True) 908 909 # Model selection - to catch the failure. 910 self.interpreter.model_selection(method='AIC', modsel_pipe='final', bundle='relax_disp', pipes=['No Rex', 'CR72'])

911 912

913 - def test_bug_21460_disp_cluster_fail(self):

914 """U{Bug #21460<https://web.archive.org/web/https://gna.org/bugs/?21460>} catch, the failure due to a spectrometer frequency having no relaxation data.""" 915 916 # Clear the data store. 917 self.interpreter.reset() 918 919 # Load the state. 920 state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21460_bad_fields.bz2' 921 self.interpreter.state.load(state, force=True) 922 923 # Execute the auto-analysis (fast). 924 relax_disp.Relax_disp.opt_func_tol = 1e-5 925 relax_disp.Relax_disp.opt_max_iterations = 1000 926 relax_disp.Relax_disp(pipe_name="origin - relax_disp (Thu Jan 2 13:46:44 2014)", pipe_bundle="relax_disp (Thu Jan 2 13:46:44 2014)", results_dir=self.tmpdir, models=['R2eff', 'No Rex', 'CR72', 'NS CPMG 2-site expanded'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True)

927 928

929 - def test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp(self):

930 """U{Bug #21665<https://web.archive.org/web/https://gna.org/bugs/?21344>} catch, the failure of an analysis of a sparse acquired R1rho dataset with missing combinations of time and spin-lock field strengths using auto_analysis.""" 931 932 # Clear the data store. 933 self.interpreter.reset() 934 935 # Load the state. 936 state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 937 self.interpreter.state.load(state, force=True) 938 939 # Execute the auto-analysis (fast). 940 relax_disp.Relax_disp.opt_func_tol = 1e-5 941 relax_disp.Relax_disp.opt_max_iterations = 1000 942 relax_disp.Relax_disp(pipe_name='base pipe', pipe_bundle='relax_disp', results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True)

943 944

945 - def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_calc(self):

946 """U{Bug #21665<https://web.archive.org/web/https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times, using calc().""" 947 948 # Clear the data store. 949 self.interpreter.reset() 950 951 # Load the state. 952 state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 953 self.interpreter.state.load(state, force=True) 954 955 # Run the calculation. 956 self.interpreter.calc(verbosity=1)

957 958

959 - def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_relax_disp(self):

960 """U{Bug #21665<https://web.archive.org/web/https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times using auto_analysis.""" 961 962 # Clear the data store. 963 self.interpreter.reset() 964 965 # Load the state. 966 state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 967 self.interpreter.state.load(state, force=True) 968 969 # Execute the auto-analysis (fast). 970 relax_disp.Relax_disp.opt_func_tol = 1e-5 971 relax_disp.Relax_disp.opt_max_iterations = 1000 972 relax_disp.Relax_disp(pipe_name="compare_128_FT_R2eff", pipe_bundle="cpmg_disp_sod1d90a", results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True)

973 974

975 - def test_bug_21715_clustered_indexerror(self):

976 """Catch U{bug #21715<https://web.archive.org/web/https://gna.org/bugs/?21715>}, the failure of a clustered auto-analysis due to an IndexError.""" 977 978 # Clear the data store. 979 self.interpreter.reset() 980 981 # Load the state. 982 state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'state.bz2' 983 self.interpreter.state.load(state, force=True) 984 985 # Execute the auto-analysis (fast). 986 pre_run_dir = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'non_clustered' 987 relax_disp.Relax_disp.opt_func_tol = 1e-5 988 relax_disp.Relax_disp.opt_max_iterations = 1000 989 relax_disp.Relax_disp(pipe_name='origin - relax_disp (Sun Feb 23 19:36:51 2014)', pipe_bundle='relax_disp (Sun Feb 23 19:36:51 2014)', results_dir=self.tmpdir, models=['R2eff', 'No Rex'], grid_inc=11, mc_sim_num=2, modsel='AIC', pre_run_dir=pre_run_dir, insignificance=1.0, numeric_only=True, mc_sim_all_models=False, eliminate=True)

990 991

992 - def test_bug_22146_unpacking_r2a_r2b_cluster_B14(self):

993 """Catch U{bug #22146<https://web.archive.org/web/https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered B14 full analysis.""" 994 995 # Base data setup. 996 self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='B14_full', model_analyse = MODEL_B14_FULL)

997 998

999 - def test_bug_22146_unpacking_r2a_r2b_cluster_CR72(self):

1000 """Catch U{bug #22146<https://web.archive.org/web/https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered CR72 full analysis.""" 1001 1002 # Base data setup. 1003 self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='CR72_full', model_analyse = MODEL_CR72_FULL)

1004 1005

1006 - def test_bug_22146_unpacking_r2a_r2b_cluster_NS_3D(self):

1007 """Catch U{bug #22146<https://web.archive.org/web/https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE 3D full analysis.""" 1008 1009 # Base data setup. 1010 self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_3d_full', model_analyse = MODEL_NS_CPMG_2SITE_3D_FULL)

1011 1012

1013 - def test_bug_22146_unpacking_r2a_r2b_cluster_NS_STAR(self):

1014 """Catch U{bug #22146<https://web.archive.org/web/https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE STAR full analysis.""" 1015 1016 # Base data setup. 1017 self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_star_full', model_analyse = MODEL_NS_CPMG_2SITE_STAR_FULL, places = 4)

1018 1019

1020 - def test_cpmg_synthetic_ns3d_to_cr72(self):

1021 """Test synthetic cpmg data. 1022 1023 This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with CR72. 1024 """ 1025 1026 # Reset. 1027 #self.interpreter.reset() 1028 1029 ## Set Experiments. 1030 model_create = 'NS CPMG 2-site 3D' 1031 #model_create = 'NS CPMG 2-site expanded' 1032 model_analyse = 'CR72' 1033 # Exp 1 1034 sfrq_1 = 599.8908617*1E6 1035 r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 1036 time_T2_1 = 0.06 1037 ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 1038 r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 1039 exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 1040 1041 sfrq_2 = 499.8908617*1E6 1042 r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 1043 time_T2_2 = 0.05 1044 ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 1045 r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 1046 exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 1047 1048 # Collect all exps 1049 exps = [exp_1, exp_2] 1050 1051 spins = [ 1052 ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 1053 ] 1054 1055 # Collect the data to be used. 1056 ds.data = [model_create, model_analyse, spins, exps] 1057 1058 # The tmp directory. None is the local directory. 1059 ds.tmpdir = ds.tmpdir 1060 1061 # The results directory. None is the local directory. 1062 #ds.resdir = None 1063 ds.resdir = ds.tmpdir 1064 1065 # Do r20_from_min_r2eff ?. 1066 ds.r20_from_min_r2eff = True 1067 1068 # Remove insignificant level. 1069 ds.insignificance = 0.0 1070 1071 # The grid search size (the number of increments per dimension). 1072 ds.GRID_INC = 8 1073 1074 # The do clustering. 1075 ds.do_cluster = False 1076 1077 # The function tolerance. This is used to terminate minimisation once the function value between iterations is less than the tolerance. 1078 # The default value is 1e-25. 1079 ds.set_func_tol = 1e-9 1080 1081 # The maximum number of iterations. 1082 # The default value is 1e7. 1083 ds.set_max_iter = 1000 1084 1085 # The verbosity level. 1086 ds.verbosity = 1 1087 1088 # The rel_change WARNING level. 1089 ds.rel_change = 0.05 1090 1091 # The plot_curves. 1092 ds.plot_curves = False 1093 1094 # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 1095 ds.sherekhan_input = False 1096 1097 # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 1098 ds.opendx = False 1099 1100 # The set r2eff err. 1101 ds.r2eff_err = 0.1 1102 1103 # The print result info. 1104 ds.print_res = False 1105 1106 # Execute the script. 1107 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 1108 1109 cur_spins = ds.data[2] 1110 # Compare results. 1111 for i in range(len(cur_spins)): 1112 res_name, res_num, spin_name, params = cur_spins[i] 1113 cur_spin_id = ":%i@%s"%(res_num, spin_name) 1114 cur_spin = return_spin(cur_spin_id) 1115 1116 grid_params = ds.grid_results[i][3] 1117 min_params = ds.min_results[i][3] 1118 # Now read the parameters. 1119 print("For spin: '%s'"%cur_spin_id) 1120 for mo_param in cur_spin.params: 1121 # The R2 is a dictionary, depending on spectrometer frequency. 1122 if isinstance(getattr(cur_spin, mo_param), dict): 1123 grid_r2 = grid_params[mo_param] 1124 min_r2 = min_params[mo_param] 1125 set_r2 = params[mo_param] 1126 for key, val in set_r2.items(): 1127 grid_r2_frq = grid_r2[key] 1128 min_r2_frq = min_r2[key] 1129 set_r2_frq = set_r2[key] 1130 frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 1131 rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 1132 print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 1133 if rel_change > ds.rel_change: 1134 print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 1135 print("###################################") 1136 1137 ## Make test on R2. 1138 self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 1139 else: 1140 grid_val = grid_params[mo_param] 1141 min_val = min_params[mo_param] 1142 set_val = params[mo_param] 1143 rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 1144 print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 1145 if rel_change > ds.rel_change: 1146 print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 1147 print("###################################") 1148 1149 ## Make test on parameters. 1150 if mo_param == 'dw': 1151 self.assertAlmostEqual(set_val/10, min_val/10, 1) 1152 elif mo_param == 'kex': 1153 self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 1154 elif mo_param == 'pA': 1155 self.assertAlmostEqual(set_val, min_val, 3)

1156 1157

1158 - def test_cpmg_synthetic_ns3d_to_b14(self):

1159 """Test synthetic cpmg data. 1160 1161 This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with B14. 1162 Try to catch bug #22021 U{https://web.archive.org/web/https://gna.org/bugs/index.php?22021}: Model B14 shows bad fitting to data. 1163 """ 1164 1165 # Reset. 1166 #self.interpreter.reset() 1167 1168 ## Set Experiments. 1169 model_create = 'NS CPMG 2-site 3D' 1170 #model_create = 'NS CPMG 2-site expanded' 1171 model_analyse = 'B14' 1172 # Exp 1 1173 sfrq_1 = 599.8908617*1E6 1174 r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 1175 time_T2_1 = 0.06 1176 ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 1177 r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 1178 exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 1179 1180 sfrq_2 = 499.8908617*1E6 1181 r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 1182 time_T2_2 = 0.05 1183 ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 1184 r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 1185 exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 1186 1187 # Collect all exps 1188 exps = [exp_1, exp_2] 1189 1190 spins = [ 1191 ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 1192 ] 1193 1194 # Collect the data to be used. 1195 ds.data = [model_create, model_analyse, spins, exps] 1196 1197 # The tmp directory. None is the local directory. 1198 ds.tmpdir = ds.tmpdir 1199 1200 # The results directory. None is the local directory. 1201 #ds.resdir = None 1202 ds.resdir = ds.tmpdir 1203 1204 # Do r20_from_min_r2eff ?. 1205 ds.r20_from_min_r2eff = True 1206 1207 # Remove insignificant level. 1208 ds.insignificance = 0.0 1209 1210 # The grid search size (the number of increments per dimension). 1211 ds.GRID_INC = 8 1212 1213 # The do clustering. 1214 ds.do_cluster = False 1215 1216 # The function tolerance. This is used to terminate minimisation once the function value between iterations is less than the tolerance. 1217 # The default value is 1e-25. 1218 ds.set_func_tol = 1e-9 1219 1220 # The maximum number of iterations. 1221 # The default value is 1e7. 1222 ds.set_max_iter = 1000 1223 1224 # The verbosity level. 1225 ds.verbosity = 1 1226 1227 # The rel_change WARNING level. 1228 ds.rel_change = 0.05 1229 1230 # The plot_curves. 1231 ds.plot_curves = False 1232 1233 # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 1234 ds.sherekhan_input = False 1235 1236 # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 1237 ds.opendx = False 1238 1239 # The set r2eff err. 1240 ds.r2eff_err = 0.1 1241 1242 # The print result info. 1243 ds.print_res = False 1244 1245 # Execute the script. 1246 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 1247 1248 cur_spins = ds.data[2] 1249 # Compare results. 1250 for i in range(len(cur_spins)): 1251 res_name, res_num, spin_name, params = cur_spins[i] 1252 cur_spin_id = ":%i@%s"%(res_num, spin_name) 1253 cur_spin = return_spin(cur_spin_id) 1254 1255 grid_params = ds.grid_results[i][3] 1256 min_params = ds.min_results[i][3] 1257 # Now read the parameters. 1258 print("For spin: '%s'"%cur_spin_id) 1259 for mo_param in cur_spin.params: 1260 # The R2 is a dictionary, depending on spectrometer frequency. 1261 if isinstance(getattr(cur_spin, mo_param), dict): 1262 grid_r2 = grid_params[mo_param] 1263 min_r2 = min_params[mo_param] 1264 set_r2 = params[mo_param] 1265 for key, val in set_r2.items(): 1266 grid_r2_frq = grid_r2[key] 1267 min_r2_frq = min_r2[key] 1268 set_r2_frq = set_r2[key] 1269 frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 1270 rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 1271 print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 1272 if rel_change > ds.rel_change: 1273 print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 1274 print("###################################") 1275 1276 ## Make test on R2. 1277 self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 1278 else: 1279 grid_val = grid_params[mo_param] 1280 min_val = min_params[mo_param] 1281 set_val = params[mo_param] 1282 rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 1283 print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 1284 if rel_change > ds.rel_change: 1285 print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 1286 print("###################################") 1287 1288 ## Make test on parameters. 1289 if mo_param == 'dw': 1290 self.assertAlmostEqual(set_val/10, min_val/10, 5) 1291 elif mo_param == 'kex': 1292 self.assertAlmostEqual(set_val/1000, min_val/1000, 5) 1293 elif mo_param == 'pA': 1294 self.assertAlmostEqual(set_val, min_val, 6)

1295 1296

1297 - def test_cpmg_synthetic_ns3d_to_cr72_noise_cluster(self):

1298 """Test synthetic cpmg data. For CR72 with small noise and cluster. 1299 1300 This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 1301 """ 1302 1303 # Reset. 1304 #self.interpreter.reset() 1305 1306 ## Set Experiments. 1307 model_create = 'NS CPMG 2-site 3D' 1308 #model_create = 'NS CPMG 2-site expanded' 1309 model_analyse = 'CR72' 1310 1311 # Exp 1 1312 sfrq_1 = 599.8908617*1E6 1313 r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 1314 time_T2_1 = 0.06 1315 ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 1316 r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 1317 #r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 1318 exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 1319 1320 sfrq_2 = 499.8908617*1E6 1321 r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 1322 time_T2_2 = 0.05 1323 ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 1324 r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 1325 #r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 1326 exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 1327 1328 # Collect all exps 1329 exps = [exp_1, exp_2] 1330 1331 spins = [ 1332 ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ], 1333 ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.99, 'dw': 1.} ] 1334 ] 1335 1336 # Collect the data to be used. 1337 ds.data = [model_create, model_analyse, spins, exps] 1338 1339 # The tmp directory. None is the local directory. 1340 ds.tmpdir = ds.tmpdir 1341 1342 # The results directory. None is the local directory. 1343 #ds.resdir = None 1344 ds.resdir = ds.tmpdir 1345 1346 # Do r20_from_min_r2eff ?. 1347 ds.r20_from_min_r2eff = True 1348 1349 # Remove insignificant level. 1350 ds.insignificance = 0.0 1351 1352 # The grid search size (the number of increments per dimension). 1353 ds.GRID_INC = 13 1354 1355 # The do clustering. 1356 ds.do_cluster = True 1357 1358 # The function tolerance. This is used to terminate minimisation once the function value between iterations is less than the tolerance. 1359 # The default value is 1e-25. 1360 ds.set_func_tol = 1e-8 1361 1362 # The maximum number of iterations. 1363 # The default value is 1e7. 1364 ds.set_max_iter = 10000 1365 1366 # The verbosity level. 1367 ds.verbosity = 1 1368 1369 # The rel_change WARNING level. 1370 ds.rel_change = 0.05 1371 1372 # The plot_curves. 1373 ds.plot_curves = False 1374 1375 # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 1376 ds.sherekhan_input = False 1377 1378 # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 1379 ds.opendx = False 1380 1381 # The set r2eff err. 1382 ds.r2eff_err = 0.1 1383 1384 # The print result info. 1385 ds.print_res = False 1386 1387 # Execute the script. 1388 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 1389 1390 cur_spins = ds.data[2] 1391 # Compare results. 1392 for i in range(len(cur_spins)): 1393 res_name, res_num, spin_name, params = cur_spins[i] 1394 cur_spin_id = ":%i@%s"%(res_num, spin_name) 1395 cur_spin = return_spin(cur_spin_id) 1396 1397 grid_params = ds.grid_results[i][3] 1398 1399 # Extract the clust results. 1400 min_params = ds.clust_results[i][3] 1401 # Now read the parameters. 1402 print("For spin: '%s'"%cur_spin_id) 1403 for mo_param in cur_spin.params: 1404 # The R2 is a dictionary, depending on spectrometer frequency. 1405 if isinstance(getattr(cur_spin, mo_param), dict): 1406 grid_r2 = grid_params[mo_param] 1407 min_r2 = min_params[mo_param] 1408 set_r2 = params[mo_param] 1409 for key, val in set_r2.items(): 1410 grid_r2_frq = grid_r2[key] 1411 min_r2_frq = min_r2[key] 1412 set_r2_frq = set_r2[key] 1413 frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 1414 rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 1415 print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 1416 if rel_change > ds.rel_change: 1417 print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 1418 print("###################################") 1419 1420 ## Make test on R2. 1421 self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 1422 else: 1423 grid_val = grid_params[mo_param] 1424 min_val = min_params[mo_param] 1425 set_val = params[mo_param] 1426 rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 1427 print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 1428 if rel_change > ds.rel_change: 1429 print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 1430 print("###################################") 1431 1432 ## Make test on parameters. 1433 if mo_param == 'dw': 1434 self.assertAlmostEqual(set_val/10, min_val/10, 1) 1435 elif mo_param == 'kex': 1436 self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 1437 elif mo_param == 'pA': 1438 self.assertAlmostEqual(set_val, min_val, 2)

1439 1440

1441 - def test_cpmg_synthetic_dx_map_points(self):

1442 """Test synthetic cpmg data, calling the dx.map function with one or two points. 1443 1444 This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 1445 """ 1446 1447 # Reset. 1448 #self.interpreter.reset() 1449 1450 ## Set Experiments. 1451 model_create = MODEL_NS_CPMG_2SITE_EXPANDED 1452 model_analyse = 'CR72' 1453 # Exp 1 1454 sfrq_1 = 599.8908617*1E6 1455 r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 1456 time_T2_1 = 0.06 1457 ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 1458 r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 1459 exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 1460 1461 sfrq_2 = 499.8908617*1E6 1462 r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 1463 time_T2_2 = 0.05 1464 ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 1465 r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 1466 exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 1467 1468 # Collect all exps 1469 exps = [exp_1, exp_2] 1470 1471 spins = [ 1472 ['Ala', 1, 'N', {'r2': {r20_key_1:2, r20_key_2:2}, 'r2a': {r20_key_1:2, r20_key_2:2}, 'r2b': {r20_key_1:2, r20_key_2:2}, 'kex': 1000, 'pA': 0.99, 'dw': 2} ] 1473 ] 1474 1475 # Collect the data to be used. 1476 ds.data = [model_create, model_analyse, spins, exps] 1477 1478 # The tmp directory. None is the local directory. 1479 ds.tmpdir = ds.tmpdir 1480 1481 # The results directory. None is the local directory. 1482 #ds.resdir = None 1483 ds.resdir = ds.tmpdir 1484 1485 # Do r20_from_min_r2eff ?. 1486 ds.r20_from_min_r2eff = True 1487 1488 # Remove insignificant level. 1489 ds.insignificance = 0.0 1490 1491 # The grid search size (the number of increments per dimension). 1492 ds.GRID_INC = None 1493 1494 # The do clustering. 1495 ds.do_cluster = False 1496 1497 # The function tolerance. This is used to terminate minimisation once the function value between iterations is less than the tolerance. 1498 # The default value is 1e-25. 1499 ds.set_func_tol = 1e-9 1500 1501 # The maximum number of iterations. 1502 # The default value is 1e7. 1503 ds.set_max_iter = 1000 1504 1505 # The verbosity level. 1506 ds.verbosity = 1 1507 1508 # The rel_change WARNING level. 1509 ds.rel_change = 0.05 1510 1511 # The plot_curves. 1512 ds.plot_curves = False 1513 1514 # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 1515 ds.sherekhan_input = False 1516 1517 # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 1518 ds.opendx = False 1519 1520 # The set r2eff err. 1521 ds.r2eff_err = 0.1 1522 1523 # The print result info. 1524 ds.print_res = False 1525 1526 # Execute the script. 1527 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 1528 1529 # Get the spins. 1530 cur_spins = ds.data[2] 1531 1532 # First switch pipe, since dx.map will go through parameters and end up a "bad" place. :-) 1533 ds.pipe_name_MODEL_MAP = "%s_%s_map"%(ds.pipe_name, model_analyse) 1534 self.interpreter.pipe.copy(pipe_from=ds.pipe_name, pipe_to=ds.pipe_name_MODEL_MAP, bundle_to = ds.pipe_bundle) 1535 self.interpreter.pipe.switch(pipe_name=ds.pipe_name_MODEL_MAP) 1536 1537 # Copy R2eff, but not the original parameters 1538 self.interpreter.value.copy(pipe_from=ds.pipe_name_r2eff, pipe_to=ds.pipe_name_MODEL_MAP, param='r2eff') 1539 1540 # Then select model. 1541 self.interpreter.relax_disp.select_model(model=model_analyse) 1542 1543 # Define dx.map settings. 1544 ds.dx_inc = 4 1545 ds.dx_params = ['dw', 'pA', 'kex'] 1546 1547 res_name, res_num, spin_name, params = cur_spins[0] 1548 cur_spin_id = ":%i@%s"%(res_num, spin_name) 1549 cur_spin = return_spin(cur_spin_id) 1550 1551 print("Params for dx map is") 1552 print(ds.dx_params) 1553 print("Point param for dx map is") 1554 print(ds.dx_set_val) 1555 cur_model = model_analyse.replace(' ', '_') 1556 file_name_map = "%s_map%s" % (cur_model, cur_spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 1557 file_name_point = "%s_point%s" % (cur_model, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 1558 self.interpreter.dx.map(params=ds.dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=ds.dx_inc, lower=None, upper=None, axis_incs=10, file_prefix=file_name_map, dir=ds.resdir, point=[ds.dx_set_val, ds.dx_clust_val], point_file=file_name_point) 1559 1560 ## Check for file creation 1561 # Set filepaths. 1562 map_cfg = ds.tmpdir+sep+file_name_map+".cfg" 1563 map_net = ds.tmpdir+sep+file_name_map+".net" 1564 map_general = ds.tmpdir+sep+file_name_map+".general" 1565 1566 point_general = ds.tmpdir+sep+file_name_point+".general" 1567 point_point = ds.tmpdir+sep+file_name_point 1568 1569 # Test the files exists. 1570 self.assert_(access(map_cfg, F_OK)) 1571 self.assert_(access(map_net, F_OK)) 1572 self.assert_(access(map_general, F_OK)) 1573 self.assert_(access(point_general, F_OK)) 1574 self.assert_(access(point_point, F_OK)) 1575 1576 # Open the files for testing. 1577 # Check the cfg file. 1578 print("\nChecking the dx map .cfg file.") 1579 res_file = [ 1580 '//'+"\n", 1581 '//'+"\n", 1582 '// time: Thu May 8 18:55:31 2014'+"\n", 1583 '//'+"\n", 1584 '// version: 3.2.0 (format), 4.3.2 (DX)'+"\n", 1585 '//'+"\n", 1586 '//'+"\n", 1587 '// panel[0]: position = (0.0164,0.0000), size = 0.2521x0.1933, startup = 1, devstyle = 1'+"\n", 1588 '// title: value = Control Panel'+"\n", 1589 '//'+"\n", 1590 '// workspace: width = 251, height = 142'+"\n", 1591 '// layout: snap = 0, width = 50, height = 50, align = NN'+"\n", 1592 '//'+"\n", 1593 '// interactor Selector[1]: num_components = 1, value = 1 '+"\n", 1594 '// selections: maximum = 2, current = 0 '+"\n", 1595 '// option[0]: name = "Colour", value = 1'+"\n", 1596 '// option[1]: name = "Grey", value = 2'+"\n", 1597 '// instance: panel = 0, x = 81, y = 6, style = Scrolled List, vertical = 1, size = 170x136'+"\n", 1598 '// label: value = Colour Selector'+"\n", 1599 '//'+"\n", 1600 '// node Image[3]:'+"\n", 1601 '// title: value = Surface'+"\n", 1602 '// depth: value = 24'+"\n", 1603 '// window: position = (0.0000,0.0400), size = 0.9929x0.9276'+"\n", 1604 ] 1605 file = open(map_cfg, 'r') 1606 lines = file.readlines() 1607 file.close() 1608 for i in range(len(res_file)): 1609 # Skip time point 1610 if i == 2: 1611 continue 1612 self.assertEqual(res_file[i], lines[i]) 1613 1614 print("\nChecking the dx map .general file.") 1615 res_file = [ 1616 'file = CR72_map_1_N'+"\n", 1617 'grid = 5 x 5 x 5'+"\n", 1618 'format = ascii'+"\n", 1619 'interleaving = field'+"\n", 1620 'majority = row'+"\n", 1621 'field = data'+"\n", 1622 'structure = scalar'+"\n", 1623 'type = float'+"\n", 1624 'dependency = positions'+"\n", 1625 'positions = regular, regular, regular, 0, 1, 0, 1, 0, 1'+"\n", 1626 ''+"\n", 1627 'end'+"\n", 1628 ] 1629 file = open(map_general, 'r') 1630 lines = file.readlines() 1631 file.close() 1632 for i in range(len(res_file)): 1633 # Skip time point 1634 #if i == 2: 1635 # continue 1636 self.assertEqual(res_file[i], lines[i]) 1637 1638 print("\nChecking the dx point .general file.") 1639 res_file = [ 1640 'file = CR72_point_1_N'+"\n", 1641 'points = 2'+"\n", 1642 'format = ascii'+"\n", 1643 'interleaving = field'+"\n", 1644 'field = locations, field0'+"\n", 1645 'structure = 3-vector, scalar'+"\n", 1646 'type = float, float'+"\n", 1647 ''+"\n", 1648 'end'+"\n", 1649 ] 1650 file = open(point_general, 'r') 1651 lines = file.readlines() 1652 file.close() 1653 for i in range(len(res_file)): 1654 # Skip time point 1655 #if i == 2: 1656 # continue 1657 self.assertEqual(res_file[i], lines[i]) 1658 1659 print("\nChecking the dx point point file.") 1660 res_file = [ 1661 '0.8 3.92 0.39964 1'+"\n", 1662 '0.76981 3.9169 0.41353 1'+"\n", 1663 ] 1664 file = open(point_point, 'r') 1665 lines = file.readlines() 1666 file.close() 1667 for i in range(len(res_file)): 1668 # Skip time point 1669 #if i == 2: 1670 # continue 1671 self.assertEqual(res_file[i], lines[i])

1672 1673

1674 - def test_curve_type_cpmg_fixed_time(self):

1675 """Test the curve type detection using the Dr. Flemming Hansen's CPMG fixed time test data.""" 1676 1677 # Reset. 1678 self.interpreter.reset() 1679 1680 # Load the base data. 1681 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 1682 self.interpreter.state.load(data_path+sep+'r2eff_values') 1683 1684 # The type. 1685 curve_type = get_curve_type(id='500_133.33.in') 1686 self.assertEqual(curve_type, 'fixed time')

1687 1688

1689 - def test_curve_type_r1rho_exponential(self, model=None):

1690 """Test the curve type detection using the 'M61' exponential test data.""" 1691 1692 # Reset. 1693 self.interpreter.reset() 1694 1695 # Load the base data. 1696 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_on_res_m61' 1697 self.interpreter.state.load(data_path+sep+'r2eff_values') 1698 1699 # The type. 1700 curve_type = get_curve_type(id='nu_2000_ncyc9') 1701 self.assertEqual(curve_type, 'exponential')

1702 1703

1704 - def test_curve_type_r1rho_fixed_time(self, model=None):

1705 """Test the curve type detection using the 'TP02' fixed time test data.""" 1706 1707 # Reset. 1708 self.interpreter.reset() 1709 1710 # Load the base data. 1711 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 1712 self.interpreter.state.load(data_path+sep+'r2eff_values') 1713 1714 # The type. 1715 curve_type = get_curve_type(id='nu_1000.0_500MHz') 1716 self.assertEqual(curve_type, 'fixed time')

1717 1718

1719 - def test_dpl94_data_to_dpl94(self):

1720 """Test the relaxation dispersion 'DPL94' model curve fitting to fixed time synthetic data.""" 1721 1722 # Fixed time variable. 1723 ds.fixed = True 1724 1725 # Execute the script. 1726 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_dpl94.py') 1727 1728 # The original parameters. 1729 i0 = [100000.0, 20000.0] 1730 r1rho_prime = [2.25, 24.0] 1731 pA = 0.7 1732 kex = 1000.0 1733 delta_omega = [1.0, 2.0] 1734 phi_ex = [] 1735 for i in range(2): 1736 phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 1737 1738 # Switch to the 'DPL94' model data pipe, then check for each spin. 1739 self.interpreter.pipe.switch('DPL94 - relax_disp') 1740 spin_index = 0 1741 for spin, spin_id in spin_loop(return_id=True): 1742 # Printout. 1743 print("\nSpin %s." % spin_id) 1744 1745 # Check the fitted parameters. 1746 self.assertAlmostEqual(spin.r2['R1rho - 800.00000000 MHz']/10, r1rho_prime[spin_index]/10, 2) 1747 self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 1748 self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 1749 1750 # Increment the spin index. 1751 spin_index += 1

1752 1753

1754 - def test_exp_fit(self):

1755 """Test the relaxation dispersion 'exp_fit' model curve fitting.""" 1756 1757 # Execute the script. 1758 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'exp_fit.py') 1759 1760 # The original exponential curve parameters. 1761 res_data = [ 1762 [15., 10., 20000., 25000.], 1763 [12., 11., 50000., 51000.], 1764 [17., 9., 100000., 96000.] 1765 ] 1766 1767 # List of parameters which do not belong to the model. 1768 blacklist = ['cpmg_frqs', 'r2', 'rex', 'kex', 'r2a', 'k_AB', 'dw'] 1769 1770 # Checks for each residue. 1771 for i in range(len(res_data)): 1772 # Printout. 1773 print("\nResidue number %s." % (i+1)) 1774 1775 # Check the fitted parameters. 1776 self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_1000.000'], res_data[i][0], places=2) 1777 self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_2000.000'], res_data[i][1], places=2) 1778 self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_1000.000']/10000, res_data[i][2]/10000, places=3) 1779 self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_2000.000']/10000, res_data[i][3]/10000, places=3) 1780 1781 # Check the simulation errors. 1782 self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_1000.000'] < 5.0) 1783 self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_2000.000'] < 5.0) 1784 self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_1000.000']/10000 < 5.0) 1785 self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_2000.000']/10000 < 5.0) 1786 1787 # Check that certain parameters are not present. 1788 for param in blacklist: 1789 print("\tChecking for the absence of the '%s' parameter." % param) 1790 self.assert_(not hasattr(cdp.mol[0].res[i].spin[0], param)) 1791 1792 # Check the clustering information. 1793 self.assert_(hasattr(cdp, 'clustering')) 1794 keys = ['free spins', 'cluster'] 1795 for key in keys: 1796 self.assert_(key in cdp.clustering) 1797 self.assert_('test' not in cdp.clustering) 1798 self.assertEqual(cdp.clustering['free spins'], [':2@N']) 1799 self.assertEqual(cdp.clustering['cluster'], [':1@N', ':3@N'])

1800 1801

1802 - def test_hansen_catia_input(self):

1803 """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CATIA. 1804 1805 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 1806 """ 1807 1808 # Load the R2eff results file. 1809 file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 1810 self.interpreter.results.read(file_name) 1811 self.interpreter.deselect.spin(':4') 1812 1813 # The spin isotopes. 1814 self.interpreter.spin.isotope("15N") 1815 1816 # Generate the input files. 1817 self.interpreter.relax_disp.catia_input(dir=ds.tmpdir, force=True) 1818 1819 # Check the r2eff set files. 1820 print("\nChecking the R2eff input set files.") 1821 files = ['data_set_500.inp', 'data_set_500.inp'] 1822 for file in files: 1823 self.assert_(access(ds.tmpdir+sep+file, F_OK)) 1824 data_set_500 = [ 1825 "ID=500\n", 1826 "Sfrq = 500\n", 1827 "Temperature = 0.0\n", 1828 "Nucleus = N15\n", 1829 "Couplednucleus = H1\n", 1830 "Time_equil = 0.0\n", 1831 "Pwx_cp = 0.0\n", 1832 "Taub = 0.0\n", 1833 "Time_T2 = 0.03\n", 1834 "Xcar = 0.0\n", 1835 "Seqfil = CW_CPMG\n", 1836 "Minerror = (2.%;0.5/s)\n", 1837 "Basis = (Iph_7)\n", 1838 "Format = (0;1;2)\n", 1839 "DataDirectory = /tmp/tmpNjOGNG/input_r2eff\n", 1840 "Data = (\n", 1841 " [70N;spin_70_N_500.cpmg];\n", 1842 " [71N;spin_71_N_500.cpmg];\n", 1843 ")\n", 1844 ] 1845 file = open(ds.tmpdir+sep+files[0]) 1846 lines = file.readlines() 1847 file.close() 1848 for i in range(len(data_set_500)): 1849 # Skip the data directory, as this is a random file name. 1850 if i == 14: 1851 continue 1852 1853 self.assertEqual(data_set_500[i], lines[i]) 1854 1855 # Check the r2eff files. 1856 print("\nChecking the R2eff input files.") 1857 files = ['spin_70_N_500.cpmg', 'spin_70_N_800.cpmg', 'spin_71_N_500.cpmg', 'spin_71_N_800.cpmg'] 1858 for file in files: 1859 self.assert_(access(ds.tmpdir+sep+'input_r2eff'+sep+file, F_OK)) 1860 spin_70_N_500 = [ 1861 "# nu_cpmg(Hz) R2(1/s) Esd(R2)\n", 1862 " 66.666600000000003 16.045540885533605 0.310924686180635\n", 1863 " 133.333300000000008 14.877924861181727 0.303217270671013\n", 1864 " 200.000000000000000 14.357820247260586 0.299894424543361\n", 1865 " 266.666600000000017 12.664494620416516 0.289532060485796\n", 1866 " 333.333300000000008 12.363204802467891 0.287759631749322\n", 1867 " 400.000000000000000 11.092532381134513 0.280514035409862\n", 1868 " 466.666600000000017 10.566090057649893 0.277618625949722\n", 1869 " 533.333300000000008 9.805806894657803 0.273544382200754\n", 1870 " 600.000000000000000 9.564300692201730 0.272276309984954\n", 1871 " 666.666600000000017 9.015633750407980 0.269441511838159\n", 1872 " 733.333300000000008 8.607764958055581 0.267375134391053\n", 1873 " 800.000000000000000 8.279997179221338 0.265739551961997\n", 1874 " 866.666600000000017 8.474535940963516 0.266707642726566\n", 1875 " 933.333300000000008 8.158972897365194 0.265141210539941\n", 1876 "1000.000000000000000 7.988630509501972 0.264304105548559\n", 1877 ] 1878 file = open(ds.tmpdir+sep+'input_r2eff'+sep+files[0]) 1879 lines = file.readlines() 1880 file.close() 1881 for i in range(len(lines)): 1882 print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 1883 for i in range(len(spin_70_N_500)): 1884 self.assertEqual(spin_70_N_500[i], lines[i]) 1885 1886 # Check the main file. 1887 print("\nChecking the main CATIA execution file.") 1888 main_file = [ 1889 "ReadDataset(data_set_500.inp)\n", 1890 "ReadDataset(data_set_800.inp)\n", 1891 "ReadParam_Global(ParamGlobal.inp)\n", 1892 "ReadParam_Local(ParamSet1.inp)\n", 1893 "\n", 1894 "FreeLocalParam(all;Omega;false)\n", 1895 "FreeLocalParam(all;R1iph_500;false)\n", 1896 "FreeLocalParam(all;R1iph_800;false)\n", 1897 "\n", 1898 "Minimize(print=y;tol=1e-25;maxiter=10000000)\n", 1899 "\n", 1900 "PrintParam(output/GlobalParam.fit;global)\n", 1901 "PrintParam(output/DeltaOmega.fit;DeltaO)\n", 1902 "PrintData(output/)\n", 1903 "\n", 1904 "ChiSq(all;all)\n", 1905 "exit(0)\n" 1906 ] 1907 file = open("%s%sFit.catia" % (ds.tmpdir, sep)) 1908 lines = file.readlines() 1909 file.close() 1910 for i in range(len(main_file)): 1911 self.assertEqual(main_file[i], lines[i])

1912 1913

1914 - def test_hansen_cpmg_data_auto_analysis(self):

1915 """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 1916 1917 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 1918 """ 1919 1920 # Set the model. 1921 ds.models = [ 1922 MODEL_NOREX, 1923 MODEL_LM63, 1924 MODEL_CR72, 1925 MODEL_IT99 1926 ] 1927 1928 # Execute the script. 1929 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 1930 self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 1931 1932 # The R20 keys. 1933 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 1934 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 1935 1936 # The 'No Rex' model checks. 1937 self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 1938 spin70 = return_spin(":70") 1939 spin71 = return_spin(":71") 1940 print("\n\nOptimised parameters:\n") 1941 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 1942 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 1943 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 1944 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 1945 self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 1946 self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 1947 self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 1948 self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 1949 self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 1950 self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 1951 1952 # The 'LM63' model checks. 1953 self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 1954 spin70 = return_spin(":70") 1955 spin71 = return_spin(":71") 1956 print("\n\nOptimised parameters:\n") 1957 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 1958 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 1959 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 1960 print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 1961 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 1962 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 1963 self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 1964 self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 1965 self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 1966 self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 1967 self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 1968 self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 1969 self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 1970 self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 1971 self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 1972 self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 1973 1974 # The 'CR72' model checks. 1975 self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 1976 spin70 = return_spin(":70") 1977 spin71 = return_spin(":71") 1978 print("\n\nOptimised parameters:\n") 1979 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 1980 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 1981 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 1982 print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 1983 print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 1984 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 1985 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 1986 self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 1987 self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 1988 self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 1989 self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 1990 self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 1991 self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 1992 self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 1993 self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 1994 self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 1995 self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 1996 self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 1997 self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3)

1998 1999

2000 - def test_hansen_cpmg_data_auto_analysis_numeric(self):

2001 """Test of the numeric model only dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 2002 2003 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2004 """ 2005 2006 # Set the model and numeric flag. 2007 ds.models = [ 2008 MODEL_NOREX, 2009 MODEL_CR72, 2010 MODEL_NS_CPMG_2SITE_EXPANDED 2011 ] 2012 ds.numeric_only = True 2013 2014 # Execute the script. 2015 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 2016 2017 # The R20 keys. 2018 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2019 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2020 2021 # The 'No Rex' model checks. 2022 self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 2023 spin70 = return_spin(":70") 2024 spin71 = return_spin(":71") 2025 print("\n\nOptimised parameters:\n") 2026 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2027 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2028 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2029 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2030 self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 2031 self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 2032 self.assertAlmostEqual(spin70.chi2/10000, 8973.84810025761/10000, 3) 2033 self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 2034 self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 2035 self.assertAlmostEqual(spin71.chi2/10000, 3908.00127830003/10000, 3) 2036 2037 # The 'CR72' model checks. 2038 self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 2039 spin70 = return_spin(":70") 2040 spin71 = return_spin(":71") 2041 print("\n\nOptimised parameters:\n") 2042 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2043 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2044 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2045 print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 2046 print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 2047 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 2048 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2049 self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 2050 self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 2051 self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 2052 self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 2053 self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 2054 self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 2055 self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 2056 self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 2057 self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 2058 self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 2059 self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 2060 self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 2061 2062 # The 'NS CPMG 2-site expanded' model checks. 2063 self.interpreter.pipe.switch(pipe_name='NS CPMG 2-site expanded - relax_disp') 2064 spin70 = return_spin(":70") 2065 spin71 = return_spin(":71") 2066 print("\n\nOptimised parameters:\n") 2067 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2068 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2069 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2070 print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 2071 print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 2072 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 2073 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2074 self.assertAlmostEqual(spin70.r2[r20_key1], 6.95815351460902, 3) 2075 self.assertAlmostEqual(spin70.r2[r20_key2], 9.39649535771294, 3) 2076 self.assertAlmostEqual(spin70.pA, 0.989701014493195, 3) 2077 self.assertAlmostEqual(spin70.dw, 5.67314464776128, 3) 2078 self.assertAlmostEqual(spin70.kex/10000, 1713.65380495429/10000, 3) 2079 self.assertAlmostEqual(spin70.chi2, 52.5106880917473, 3) 2080 self.assertAlmostEqual(spin71.r2[r20_key1], 4.99889337382435, 3) 2081 self.assertAlmostEqual(spin71.r2[r20_key2], 6.89822887466673, 3) 2082 self.assertAlmostEqual(spin71.pA, 0.986709050819695, 3) 2083 self.assertAlmostEqual(spin71.dw, 2.09238266766502, 3) 2084 self.assertAlmostEqual(spin71.kex/10000, 2438.27019901422/10000, 3) 2085 self.assertAlmostEqual(spin71.chi2, 15.1644906963987, 3) 2086 2087 # The final data pipe checks. 2088 self.interpreter.pipe.switch(pipe_name='final - relax_disp') 2089 spin70 = return_spin(":70") 2090 spin71 = return_spin(":71") 2091 self.assertEqual(spin70.model, 'NS CPMG 2-site expanded') 2092 self.assertEqual(spin71.model, 'NS CPMG 2-site expanded')

2093 2094

2095 - def test_hansen_cpmg_data_auto_analysis_r2eff(self):

2096 """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data (using the R2eff data directly instead of peak intensities). 2097 2098 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2099 """ 2100 2101 # Set the model. 2102 ds.models = [ 2103 MODEL_NOREX, 2104 MODEL_LM63, 2105 MODEL_CR72, 2106 MODEL_IT99 2107 ] 2108 2109 # Execute the script. 2110 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_r2eff_data.py') 2111 self.interpreter.state.save('analysis_r2eff', dir=ds.tmpdir, force=True) 2112 2113 # The R20 keys. 2114 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2115 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2116 2117 # The 'No Rex' model checks. 2118 self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 2119 spin70 = return_spin(":70") 2120 spin71 = return_spin(":71") 2121 print("\n\nOptimised parameters:\n") 2122 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2123 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2124 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2125 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2126 self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 2127 self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 2128 self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 2129 self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 2130 self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 2131 self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 2132 2133 # The 'LM63' model checks. 2134 self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 2135 spin70 = return_spin(":70") 2136 spin71 = return_spin(":71") 2137 print("\n\nOptimised parameters:\n") 2138 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2139 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2140 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2141 print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 2142 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 2143 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2144 self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 2145 self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 2146 self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 2147 self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 2148 self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 2149 self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 2150 self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 2151 self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 2152 self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 2153 self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 2154 2155 # The 'CR72' model checks. 2156 self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 2157 spin70 = return_spin(":70") 2158 spin71 = return_spin(":71") 2159 print("\n\nOptimised parameters:\n") 2160 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2161 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2162 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2163 print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 2164 print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 2165 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 2166 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2167 self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 2168 self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 2169 self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 2170 self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 2171 self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 2172 self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 2173 self.assertAlmostEqual(spin71.r2[r20_key1], 5.00317154730225, 3) 2174 self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797713541, 3) 2175 self.assertAlmostEqual(spin71.pA, 0.985922406429147, 3) 2176 self.assertAlmostEqual(spin71.dw, 2.00500965887772, 2) 2177 self.assertAlmostEqual(spin71.kex/10000, 2481.10839579804/10000, 3) 2178 self.assertAlmostEqual(spin71.chi2, 15.6595374288635, 3)

2179 2180

2181 - def test_hansen_cpmg_data_missing_auto_analysis(self):

2182 """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data with parts missing. 2183 2184 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2185 """ 2186 2187 # Set the model. 2188 ds.models = [ 2189 MODEL_R2EFF, 2190 MODEL_NOREX, 2191 MODEL_CR72, 2192 MODEL_NS_CPMG_2SITE_EXPANDED 2193 ] 2194 2195 # Execute the script. 2196 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data_missing.py') 2197 self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 2198 2199 # The R20 keys. 2200 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2201 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2202 2203 # The 'No Rex' model checks. 2204 self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 2205 spin4 = return_spin(":4") 2206 spin70 = return_spin(":70") 2207 spin71 = return_spin(":71") 2208 print("\n\nOptimised parameters:\n") 2209 print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 2210 print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 2211 print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 2212 print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 2213 self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463084515171, 3) 2214 self.assertAlmostEqual(spin4.r2[r20_key2], 1.63220784651911, 3) 2215 self.assertAlmostEqual(spin4.chi2, 26.7356700694891, 3) 2216 self.assertAlmostEqual(spin70.r2[r20_key1], 10.534285641325, 3) 2217 self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112794857068, 3) 2218 self.assertAlmostEqual(spin70.chi2, 8973.84809774722, 3) 2219 self.assertAlmostEqual(spin71.r2[r20_key1], 5.83136858890037, 3) 2220 self.assertAlmostEqual(spin71.chi2, 182.60081909193, 3) 2221 2222 # The 'CR72' model checks. 2223 self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 2224 spin4 = return_spin(":4") 2225 spin70 = return_spin(":70") 2226 spin71 = return_spin(":71") 2227 print("\n\nOptimised parameters:\n") 2228 print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 2229 print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 2230 print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 2231 print("%-20s %20.15g %20.15g %20.15g" % ("pA", spin4.pA, spin70.pA, spin71.pA)) 2232 print("%-20s %20.15g %20.15g %20.15g" % ("dw", spin4.dw, spin70.dw, spin71.dw)) 2233 print("%-20s %20.15g %20.15g %20.15g" % ("kex", spin4.kex, spin70.kex, spin71.kex)) 2234 print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 2235 self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463650370664, 2) 2236 self.assertAlmostEqual(spin4.r2[r20_key2], 1.63221675941434, 3) 2237 #self.assertAlmostEqual(spin4.pA, 0.818979078699935, 3) # As dw (and kex) is zero, this parameter is not stable. 2238 self.assertAlmostEqual(spin4.dw, 0.0, 6) 2239 self.assertAlmostEqual(spin4.kex/10000, 0.0, 3) 2240 self.assertAlmostEqual(spin4.chi2, 26.7356711142038, 3) 2241 self.assertAlmostEqual(spin70.r2[r20_key1], 6.97268077496405, 3) 2242 self.assertAlmostEqual(spin70.r2[r20_key2], 9.41028133407727, 3) 2243 self.assertAlmostEqual(spin70.pA, 0.989856641885939, 3) 2244 self.assertAlmostEqual(spin70.dw, 5.60889911049405, 3) 2245 self.assertAlmostEqual(spin70.kex/10000, 1752.62025618632/10000, 3) 2246 self.assertAlmostEqual(spin70.chi2, 53.8382196964083, 3) 2247 self.assertAlmostEqual(spin71.r2[r20_key1], 4.98123328466942, 3) 2248 self.assertAlmostEqual(spin71.pA, 0.996607425484157, 3) 2249 self.assertAlmostEqual(spin71.dw, 4.34346257383825, 3) 2250 self.assertAlmostEqual(spin71.kex/10000, 1936.73197158804/10000, 3) 2251 self.assertAlmostEqual(spin71.chi2, 5.51703791653689, 3)

2252 2253

2254 - def test_hansen_cpmg_data_to_cr72(self):

2255 """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 dispersion model. 2256 2257 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2258 """ 2259 2260 # Base data setup. 2261 self.setup_hansen_cpmg_data(model='CR72') 2262 2263 # Alias the spins. 2264 spin70 = return_spin(":70") 2265 spin71 = return_spin(":71") 2266 2267 # The R20 keys. 2268 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2269 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2270 2271 # Set the initial parameter values. 2272 spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 2273 spin70.pA = 0.9 2274 spin70.dw = 6.0 2275 spin70.kex = 1500.0 2276 spin71.r2 = {r20_key1: 5, r20_key2: 9.0} 2277 spin71.pA = 0.9 2278 spin71.dw = 4.0 2279 spin71.kex = 1900.0 2280 2281 # Low precision optimisation. 2282 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 2283 2284 # Printout. 2285 print("\n\nOptimised parameters:\n") 2286 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2287 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2288 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2289 print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 2290 print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 2291 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 2292 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2293 2294 # Checks for residue :70. 2295 self.assertAlmostEqual(spin70.r2[r20_key1], 6.9724581325007, 4) 2296 self.assertAlmostEqual(spin70.r2[r20_key2], 9.40968331038162, 2) 2297 self.assertAlmostEqual(spin70.pA, 0.989856656702431, 4) 2298 self.assertAlmostEqual(spin70.dw, 5.60885879594746, 3) 2299 self.assertAlmostEqual(spin70.kex/1000, 1752.91052702273/1000, 3) 2300 self.assertAlmostEqual(spin70.chi2, 53.8382133597495, 4) 2301 2302 # Checks for residue :71. 2303 self.assertAlmostEqual(spin71.r2[r20_key1], 5.0030740940524, 4) 2304 self.assertAlmostEqual(spin71.pA, 0.985941082507823, 4) 2305 self.assertAlmostEqual(spin71.dw, 2.00640384113696, 4) 2306 self.assertAlmostEqual(spin71.kex/1000, 2480.79614442041/1000, 4) 2307 self.assertAlmostEqual(spin71.chi2, 15.6595388312451, 4) 2308 2309 # Test the conversion to k_AB from kex and pA. 2310 self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 2311 self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 2312 2313 # Test the conversion to k_BA from kex and pA. 2314 self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 2315 self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA)

2316 2317

2318 - def test_hansen_cpmg_data_to_cr72_full(self):

2319 """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 full dispersion model. 2320 2321 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2322 """ 2323 2324 # Base data setup. 2325 self.setup_hansen_cpmg_data(model='CR72 full') 2326 2327 # Alias the spins. 2328 spin70 = return_spin(":70") 2329 spin71 = return_spin(":71") 2330 2331 # The R20 keys. 2332 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2333 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2334 2335 # Set the initial parameter values. 2336 spin70.r2a = {r20_key1: 7.0, r20_key2: 9.0} 2337 spin70.r2b = {r20_key1: 7.0, r20_key2: 9.0} 2338 spin70.pA = 0.9 2339 spin70.dw = 6.0 2340 spin70.kex = 1500.0 2341 spin71.r2a = {r20_key1: 5.0, r20_key2: 9.0} 2342 spin71.r2b = {r20_key1: 5.0, r20_key2: 9.0} 2343 spin71.pA = 0.9 2344 spin71.dw = 4.0 2345 spin71.kex = 1900.0 2346 2347 # Low precision optimisation. 2348 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 2349 2350 # Printout. 2351 print("\n\nOptimised parameters:\n") 2352 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2353 print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 2354 print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 2355 print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 2356 print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 2357 print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 2358 print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 2359 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 2360 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2361 2362 # Checks for residue :70. 2363 self.assertAlmostEqual(spin70.r2a[r20_key1], 6.87485258365614, 4) 2364 self.assertAlmostEqual(spin70.r2b[r20_key1], 1.26075839074614, 4) 2365 self.assertAlmostEqual(spin70.r2a[r20_key2], 8.79580446260797, 4) 2366 self.assertAlmostEqual(spin70.r2b[r20_key2], 51.188411562843, 4) 2367 self.assertAlmostEqual(spin70.pA, 0.989384178573802, 4) 2368 self.assertAlmostEqual(spin70.dw, 5.54738203723682, 4) 2369 self.assertAlmostEqual(spin70.kex/1000, 1831.4566463179/1000, 4) 2370 self.assertAlmostEqual(spin70.chi2, 50.450410782403, 4) 2371 2372 # Checks for residue :71. 2373 self.assertAlmostEqual(spin71.r2a[r20_key1], 5.04185695754972, 4) 2374 self.assertAlmostEqual(spin71.r2b[r20_key1], 1.62857899941921, 4) 2375 self.assertAlmostEqual(spin71.pA, 0.988832866751676, 4) 2376 self.assertAlmostEqual(spin71.dw, 2.24905251856265, 4) 2377 self.assertAlmostEqual(spin71.kex/1000, 2397.64122642946/1000, 4) 2378 self.assertAlmostEqual(spin71.chi2, 15.8586492923672, 4) 2379 2380 # Test the conversion to k_AB from kex and pA. 2381 self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 2382 self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 2383 2384 # Test the conversion to k_BA from kex and pA. 2385 self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 2386 self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA)

2387 2388

2389 - def test_hansen_cpmg_data_to_it99(self):

2390 """Optimisation of Dr. Flemming Hansen's CPMG data to the IT99 dispersion model. 2391 2392 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2393 """ 2394 2395 # Base data setup. 2396 self.setup_hansen_cpmg_data(model='IT99') 2397 2398 # Alias the spins. 2399 spin70 = return_spin(":70") 2400 spin71 = return_spin(":71") 2401 2402 # The R20 keys. 2403 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2404 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2405 2406 # Set the initial parameter values. 2407 spin70.r2 = {r20_key1: 8.8, r20_key2: 16.6} 2408 spin70.dw = 10.0 2409 spin70.pA = 0.5 2410 spin70.tex = 1000.09 2411 spin71.r2 = {r20_key1: 1.0, r20_key2: 1.0} 2412 spin71.dw = 10.0 2413 spin71.pA = 0.95 2414 spin71.tex = 0.1 2415 2416 # Low precision optimisation. 2417 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-10, grad_tol=None, max_iter=10000, constraints=True, scaling=True, verbosity=1) 2418 2419 # Printout. 2420 print("\n\nOptimised parameters:\n") 2421 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2422 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2423 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2424 print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 2425 print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 2426 print("%-20s %20.15g %20.15g" % ("tex", spin70.tex, spin71.tex)) 2427 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2428 2429 # Checks for residue :70. 2430 self.assertAlmostEqual(spin70.r2[r20_key1], 7.24471197811838, 4) 2431 self.assertAlmostEqual(spin70.r2[r20_key2], 10.0571040704729, 4) 2432 self.assertAlmostEqual(spin70.dw, 5.2116923222744, 4) 2433 self.assertAlmostEqual(spin70.pA, 0.990253627907212, 4) 2434 self.assertAlmostEqual(spin70.tex*1000, 0.000638394793480444*1000, 4) 2435 self.assertAlmostEqual(spin70.chi2, 93.5135798618747, 4) 2436 2437 # Checks for residue :71. 2438 self.assertAlmostEqual(spin71.r2[r20_key1], 5.05971235970214, 4) 2439 self.assertAlmostEqual(spin71.r2[r20_key2], 6.96641194493447, 4) 2440 self.assertAlmostEqual(spin71.dw, 0.435389946897141, 4) 2441 self.assertAlmostEqual(spin71.pA, 0.500000000213519, 3) 2442 self.assertAlmostEqual(spin71.tex*1000, 0.000372436400585538*1000, 4) 2443 self.assertAlmostEqual(spin71.chi2, 23.7895798801404, 4)

2444 2445

2446 - def test_hansen_cpmg_data_to_lm63(self):

2447 """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 2448 2449 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2450 """ 2451 2452 # Base data setup. 2453 self.setup_hansen_cpmg_data(model='LM63') 2454 2455 # Alias the spins. 2456 spin70 = return_spin(":70") 2457 spin71 = return_spin(":71") 2458 2459 # The R20 keys. 2460 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2461 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2462 2463 # Set the initial parameter values. 2464 spin70.r2 = {r20_key1: 7.0, r20_key2: 7.0} 2465 spin70.phi_ex = 0.3 2466 spin70.kex = 5000.0 2467 spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 2468 spin71.phi_ex = 0.1 2469 spin71.kex = 2500.0 2470 2471 # Low precision optimisation. 2472 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 2473 2474 # Printout. 2475 print("\n\nOptimised parameters:\n") 2476 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2477 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2478 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2479 print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 2480 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 2481 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2482 2483 # Checks for residue :70. 2484 self.assertAlmostEqual(spin70.r2[r20_key1], 6.7436229263957, 5) 2485 self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406788826655, 5) 2486 self.assertAlmostEqual(spin70.phi_ex, 0.31273301746411, 5) 2487 self.assertAlmostEqual(spin70.kex/1000, 4723.09901154387/1000, 5) 2488 self.assertAlmostEqual(spin70.chi2, 363.534044873483, 5) 2489 2490 # Checks for residue :71. 2491 self.assertAlmostEqual(spin71.r2[r20_key1], 5.00776657729728, 5) 2492 self.assertAlmostEqual(spin71.phi_ex, 0.0553787825650613, 5) 2493 self.assertAlmostEqual(spin71.kex/1000, 2781.72292994154/1000, 5) 2494 self.assertAlmostEqual(spin71.chi2, 17.0776399916287, 5)

2495 2496

2497 - def test_hansen_cpmg_data_to_ns_cpmg_2site_3D(self):

2498 """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D' dispersion model. 2499 2500 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2501 """ 2502 2503 # Base data setup. 2504 self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D') 2505 2506 # Alias the spins. 2507 spin70 = return_spin(":70") 2508 spin71 = return_spin(":71") 2509 2510 # The R20 keys. 2511 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2512 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2513 2514 # Set the initial parameter values. 2515 spin70.r2 = {r20_key1: 6.994165925, r20_key2: 9.428129427} 2516 spin70.pA = 0.9897754407 2517 spin70.dw = 5.642418428 2518 spin70.kex = 1743.666375 2519 spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 2520 spin71.pA = 0.9968032899 2521 spin71.dw = 4.577891393 2522 spin71.kex = 1830.044597 2523 2524 # Low precision optimisation. 2525 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 2526 2527 # Printout. 2528 print("\n\nOptimised parameters:\n") 2529 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2530 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2531 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2532 print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 2533 print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 2534 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 2535 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2536 2537 # Checks for residue :70. 2538 self.assertAlmostEqual(spin70.r2[r20_key1], 6.95797760459016, 4) 2539 self.assertAlmostEqual(spin70.r2[r20_key2], 9.39628959312699, 4) 2540 self.assertAlmostEqual(spin70.pA, 0.989700985380975, 4) 2541 self.assertAlmostEqual(spin70.dw, 5.6733714171086, 4) 2542 self.assertAlmostEqual(spin70.kex/1000, 1713.63101361545/1000, 4) 2543 self.assertAlmostEqual(spin70.chi2, 52.5106928523775, 4) 2544 2545 # Checks for residue :71. 2546 self.assertAlmostEqual(spin71.r2[r20_key1], 4.99893565849977, 4) 2547 self.assertAlmostEqual(spin71.r2[r20_key2], 6.89825625944034, 4) 2548 self.assertAlmostEqual(spin71.pA, 0.986716058519642, 4) 2549 self.assertAlmostEqual(spin71.dw, 2.09292495350993, 4) 2550 self.assertAlmostEqual(spin71.kex/1000, 2438.04423541463/1000, 4) 2551 self.assertAlmostEqual(spin71.chi2, 15.164490242352, 4) 2552 2553 # Test the conversion to k_AB from kex and pA. 2554 self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 2555 self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 2556 2557 # Test the conversion to k_BA from kex and pA. 2558 self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 2559 self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA)

2560 2561

2562 - def test_hansen_cpmg_data_to_ns_cpmg_2site_3D_full(self):

2563 """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D full' dispersion model. 2564 2565 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2566 """ 2567 2568 # Base data setup. 2569 self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D full') 2570 2571 # Alias the spins. 2572 spin70 = return_spin(":70") 2573 spin71 = return_spin(":71") 2574 2575 # The R20 keys. 2576 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2577 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2578 2579 # Set the initial parameter values. 2580 spin70.r2a = {r20_key1: 6.644753428, r20_key2: 7.891776687} 2581 spin70.r2b = {r20_key1: 7.163478485, r20_key2: 138.5170395} 2582 spin70.pA = 0.9884781357 2583 spin70.dw = 5.456507396 2584 spin70.kex = 1906.521189 2585 spin71.r2a = {r20_key1: 4.99893524108981, r20_key2: 100.0} 2586 spin71.r2b = {r20_key1: 8.27456243639973, r20_key2: 100.0} 2587 spin71.pA = 0.986709616684097 2588 spin71.dw = 2.09245158280905 2589 spin71.kex = 2438.2766211401 2590 2591 # Low precision optimisation. 2592 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 2593 2594 # Printout. 2595 print("\n\nOptimised parameters:\n") 2596 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2597 print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 2598 print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 2599 print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 2600 print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 2601 print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 2602 print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 2603 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 2604 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2605 2606 # Checks for residue :70. 2607 self.assertAlmostEqual(spin70.r2a[r20_key1], 6.61176004043484, 4) 2608 self.assertAlmostEqual(spin70.r2b[r20_key1], 7.4869316381241, 4) 2609 self.assertAlmostEqual(spin70.r2a[r20_key2], 7.78200386067591, 4) 2610 self.assertAlmostEqual(spin70.r2b[r20_key2], 141.703593742468, 4) 2611 self.assertAlmostEqual(spin70.pA, 0.988404987055969, 4) 2612 self.assertAlmostEqual(spin70.dw, 5.4497360203213, 4) 2613 self.assertAlmostEqual(spin70.kex/1000, 1934.09304607082/1000, 4) 2614 self.assertAlmostEqual(spin70.chi2, 44.6793752187925, 4) 2615 2616 # Checks for residue :71. 2617 self.assertAlmostEqual(spin71.r2a[r20_key1], 4.6013095731966, 4) 2618 self.assertAlmostEqual(spin71.r2b[r20_key1], 13.3245678276332, 4) 2619 self.assertAlmostEqual(spin71.r2a[r20_key2], 2.08243621257779, 4) 2620 self.assertAlmostEqual(spin71.r2b[r20_key2], 153.355765094575, 4) 2621 self.assertAlmostEqual(spin71.pA, 0.9665748685124, 4) 2622 self.assertAlmostEqual(spin71.dw, 1.41898001408953, 4) 2623 self.assertAlmostEqual(spin71.kex/1000, 2580.65795560688/1000, 4) 2624 self.assertAlmostEqual(spin71.chi2, 13.4937006732165, 4) 2625 2626 # Test the conversion to k_AB from kex and pA. 2627 self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 2628 self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 2629 2630 # Test the conversion to k_BA from kex and pA. 2631 self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 2632 self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA)

2633 2634

2635 - def test_hansen_cpmg_data_to_ns_cpmg_2site_expanded(self):

2636 """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site expanded' dispersion model. 2637 2638 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2639 """ 2640 2641 # Base data setup. 2642 self.setup_hansen_cpmg_data(model='NS CPMG 2-site expanded') 2643 2644 # Alias the spins. 2645 spin70 = return_spin(":70") 2646 spin71 = return_spin(":71") 2647 2648 # The R20 keys. 2649 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2650 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2651 2652 # Set the initial parameter values. 2653 spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 2654 spin70.pA = 0.9 2655 spin70.dw = 6.0 2656 spin70.kex = 1500.0 2657 spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 2658 spin71.pA = 0.9 2659 spin71.dw = 4.0 2660 spin71.kex = 1900.0 2661 2662 # Low precision optimisation. 2663 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 2664 2665 # Printout. 2666 print("\n\nOptimised parameters:\n") 2667 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2668 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2669 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2670 print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 2671 print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 2672 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 2673 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2674 2675 # Checks for residue :70. 2676 self.assertAlmostEqual(spin70.r2[r20_key1], 6.95813330991529, 4) 2677 self.assertAlmostEqual(spin70.r2[r20_key2], 9.39663480561524, 4) 2678 self.assertAlmostEqual(spin70.pA, 0.989700843879574, 4) 2679 self.assertAlmostEqual(spin70.dw, 5.67315878825691, 4) 2680 self.assertAlmostEqual(spin70.kex/1000, 1713.56110716632/1000, 4) 2681 self.assertAlmostEqual(spin70.chi2, 52.5106879242812, 4) 2682 2683 # Checks for residue :71. 2684 self.assertAlmostEqual(spin71.r2[r20_key1], 4.99881666793312, 4) 2685 self.assertAlmostEqual(spin71.r2[r20_key2], 6.89817482453042, 4) 2686 self.assertAlmostEqual(spin71.pA, 0.986712911453639, 4) 2687 self.assertAlmostEqual(spin71.dw, 2.09273069372236, 4) 2688 self.assertAlmostEqual(spin71.kex/1000, 2438.20525930405/1000, 4) 2689 self.assertAlmostEqual(spin71.chi2, 15.1644913030633, 4) 2690 2691 # Test the conversion to k_AB from kex and pA. 2692 self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 2693 self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 2694 2695 # Test the conversion to k_BA from kex and pA. 2696 self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 2697 self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA)

2698 2699

2700 - def test_hansen_cpmg_data_to_ns_cpmg_2site_star(self):

2701 """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star' dispersion model. 2702 2703 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2704 """ 2705 2706 # Base data setup. 2707 self.setup_hansen_cpmg_data(model='NS CPMG 2-site star') 2708 2709 # Alias the spins. 2710 spin70 = return_spin(":70") 2711 spin71 = return_spin(":71") 2712 2713 # The R20 keys. 2714 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2715 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2716 2717 # Set the initial parameter values. 2718 spin70.r2 = {r20_key1: 6.996327746, r20_key2: 9.452051268} 2719 spin70.pA = 0.9897519798 2720 spin70.dw = 5.644862195 2721 spin70.kex = 1723.820567 2722 spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 2723 spin71.pA = 0.9968032899 2724 spin71.dw = 4.577891393 2725 spin71.kex = 1830.044597 2726 2727 # Low precision optimisation. 2728 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 2729 2730 # Printout. 2731 print("\n\nOptimised parameters:\n") 2732 print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 2733 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 2734 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 2735 print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 2736 print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 2737 print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 2738 print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 2739 2740 # Checks for residue :70. 2741 self.assertAlmostEqual(spin70.r2[r20_key1], 6.95543947938561, 1) 2742 self.assertAlmostEqual(spin70.r2[r20_key2], 9.38991914134929, 1) 2743 self.assertAlmostEqual(spin70.pA, 0.989702750971153, 3) 2744 self.assertAlmostEqual(spin70.dw, 5.67527122494516, 1) 2745 self.assertAlmostEqual(spin70.kex/1000, 1715.72032391817/1000, 1) 2746 self.assertAlmostEqual(spin70.chi2, 52.5011991483842, 1) 2747 2748 # Checks for residue :71. 2749 self.assertAlmostEqual(spin71.r2[r20_key1], 4.992594256544, 1) 2750 self.assertAlmostEqual(spin71.pA, 0.992258541625787, 2) 2751 self.assertAlmostEqual(spin71.dw/100, 2.75140650899058/100, 2) 2752 self.assertAlmostEqual(spin71.kex/100000, 2106.60885247431/100000, 2) 2753 self.assertAlmostEqual(spin71.chi2/100, 17.3293856656588/100, 1) 2754 2755 # Test the conversion to k_AB from kex and pA. 2756 self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 2757 self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 2758 2759 # Test the conversion to k_BA from kex and pA. 2760 self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 2761 self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA)

2762 2763

2764 - def test_hansen_cpmg_data_to_ns_cpmg_2site_star_full(self):

2765 """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star full' dispersion model. 2766 2767 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2768 """ 2769 2770 # Base data setup. 2771 self.setup_hansen_cpmg_data(model='NS CPMG 2-site star full') 2772 2773 # Alias the spins. 2774 spin70 = return_spin(":70") 2775 spin71 = return_spin(":71") 2776 2777 # The R20 keys. 2778 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 2779 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 2780 2781 # Set the initial parameter values. 2782 spin70.r2a = {r20_key1: 6.44836878645126, r20_key2: 7.00382877393494} 2783 spin70.r2b = {r20_key1: 12.2083127421994, r20_key2: 199.862962628402} 2784 spin70.pA = 0.987648082613451 2785 spin70.dw = 5.30679853807572 2786 spin70.kex = 2033.25380420666 2787 spin71.r2a = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 2788 spin71.r2b = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 2789 spin71.pA = 0.992258541625787 2790 spin71.dw = 2.75140650899058 2791 spin71.kex = 2106.60885247431 2792 2793 # Low precision optimisation. 2794 self.interpreter.calc() 2795 2796 # Checks for residue :70. 2797 self.assertAlmostEqual(spin70.chi2/10, 45.773987568491123/10, 2) 2798 self.assertAlmostEqual(spin71.chi2/10, 17.329385665659192/10, 2)

2799 2800

2801 - def test_hansen_cpmgfit_input(self):

2802 """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CPMGFit. 2803 2804 This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o. This is CPMG data with a fixed relaxation time period. 2805 """ 2806 2807 # Load the R2eff results file. 2808 file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 2809 self.interpreter.results.read(file_name) 2810 self.interpreter.deselect.spin(':4') 2811 2812 # Set up the model. 2813 self.interpreter.relax_disp.select_model('LM63') 2814 2815 # Generate the input files. 2816 self.interpreter.relax_disp.cpmgfit_input(force=True, dir=ds.tmpdir) 2817 2818 # What the files should contain. 2819 batch_file = ['#! /bin/sh\n', '\n', 'cpmgfit -grid -xmgr -f spin_70_N.in | tee spin_70_N.out\n', 'cpmgfit -grid -xmgr -f spin_71_N.in | tee spin_71_N.out\n'] 2820 spin1 = [ 2821 "title :70@N\n", 2822 "fields 2 11.7432964915 18.7892743865\n", 2823 "function CPMG\n", 2824 "R2 1 10 20\n", 2825 "Rex 0 100.0 100\n", 2826 "Tau 0 10.0 100\n", 2827 "xmgr\n", 2828 "@ xaxis label \"1/tcp (1/ms)\"\n", 2829 "@ yaxis label \"R2(tcp) (rad/s)\"\n", 2830 "@ xaxis ticklabel format decimal\n", 2831 "@ yaxis ticklabel format decimal\n", 2832 "@ xaxis ticklabel char size 0.8\n", 2833 "@ yaxis ticklabel char size 0.8\n", 2834 "@ world xmin 0.0\n", 2835 "data\n", 2836 "0.133333 16.045541 0.310925 11.743296 \n", 2837 "0.266667 14.877925 0.303217 11.743296 \n", 2838 "0.400000 14.357820 0.299894 11.743296 \n", 2839 "0.533333 12.664495 0.289532 11.743296 \n", 2840 "0.666667 12.363205 0.287760 11.743296 \n", 2841 "0.800000 11.092532 0.280514 11.743296 \n", 2842 "0.933333 10.566090 0.277619 11.743296 \n", 2843 "1.066667 9.805807 0.273544 11.743296 \n", 2844 "1.200000 9.564301 0.272276 11.743296 \n", 2845 "1.333333 9.015634 0.269442 11.743296 \n", 2846 "1.466667 8.607765 0.267375 11.743296 \n", 2847 "1.600000 8.279997 0.265740 11.743296 \n", 2848 "1.733333 8.474536 0.266708 11.743296 \n", 2849 "1.866667 8.158973 0.265141 11.743296 \n", 2850 "2.000000 7.988631 0.264304 11.743296 \n", 2851 "0.133333 22.224914 0.166231 18.789274 \n", 2852 "0.266667 21.230874 0.162377 18.789274 \n", 2853 "0.400000 20.603704 0.160017 18.789274 \n", 2854 "0.533333 20.327797 0.158996 18.789274 \n", 2855 "0.666667 18.855377 0.153719 18.789274 \n", 2856 "0.800000 18.537531 0.152617 18.789274 \n", 2857 "0.933333 17.508069 0.149138 18.789274 \n", 2858 "1.066667 16.035604 0.144391 18.789274 \n", 2859 "1.200000 15.168192 0.141717 18.789274 \n", 2860 "1.333333 14.431802 0.139516 18.789274 \n", 2861 "1.466667 14.034137 0.138354 18.789274 \n", 2862 "1.600000 12.920148 0.135192 18.789274 \n", 2863 "1.733333 12.653673 0.134456 18.789274 \n", 2864 "1.866667 12.610864 0.134338 18.789274 \n", 2865 "2.000000 11.969303 0.132601 18.789274 \n" 2866 ] 2867 spin2 = [ 2868 "title :71@N\n", 2869 "fields 2 11.7432964915 18.7892743865\n", 2870 "function CPMG\n", 2871 "R2 1 10 20\n", 2872 "Rex 0 100.0 100\n", 2873 "Tau 0 10.0 100\n", 2874 "xmgr\n", 2875 "@ xaxis label \"1/tcp (1/ms)\"\n", 2876 "@ yaxis label \"R2(tcp) (rad/s)\"\n", 2877 "@ xaxis ticklabel format decimal\n", 2878 "@ yaxis ticklabel format decimal\n", 2879 "@ xaxis ticklabel char size 0.8\n", 2880 "@ yaxis ticklabel char size 0.8\n", 2881 "@ world xmin 0.0\n", 2882 "data\n", 2883 "0.133333 7.044342 0.170035 11.743296 \n", 2884 "0.266667 6.781033 0.169228 11.743296 \n", 2885 "0.400000 6.467623 0.168279 11.743296 \n", 2886 "0.533333 6.333340 0.167876 11.743296 \n", 2887 "0.666667 6.323238 0.167846 11.743296 \n", 2888 "0.800000 6.005245 0.166902 11.743296 \n", 2889 "0.933333 5.767052 0.166203 11.743296 \n", 2890 "1.066667 5.476968 0.165361 11.743296 \n", 2891 "1.200000 5.469949 0.165341 11.743296 \n", 2892 "1.333333 5.295113 0.164838 11.743296 \n", 2893 "1.466667 5.435648 0.165242 11.743296 \n", 2894 "1.600000 5.410400 0.165169 11.743296 \n", 2895 "1.733333 5.437554 0.165247 11.743296 \n", 2896 "1.866667 5.176844 0.164501 11.743296 \n", 2897 "2.000000 5.227232 0.164644 11.743296 \n", 2898 "0.133333 11.530903 0.081928 18.789274 \n", 2899 "0.266667 10.983094 0.081041 18.789274 \n", 2900 "0.400000 10.512403 0.080294 18.789274 \n", 2901 "0.533333 9.984805 0.079473 18.789274 \n", 2902 "0.666667 9.573163 0.078845 18.789274 \n", 2903 "0.800000 9.178810 0.078253 18.789274 \n", 2904 "0.933333 8.935719 0.077893 18.789274 \n", 2905 "1.066667 8.610147 0.077416 18.789274 \n", 2906 "1.200000 8.353778 0.077045 18.789274 \n", 2907 "1.333333 8.173729 0.076787 18.789274 \n", 2908 "1.466667 8.091607 0.076670 18.789274 \n", 2909 "1.600000 7.706420 0.076126 18.789274 \n", 2910 "1.733333 7.709125 0.076129 18.789274 \n", 2911 "1.866667 7.610856 0.075992 18.789274 \n", 2912 "2.000000 7.552584 0.075911 18.789274 \n", 2913 ] 2914 2915 # Check the batch file. 2916 print("\nChecking the batch file.") 2917 file = open("%s%sbatch_run.sh" % (ds.tmpdir, sep)) 2918 lines = file.readlines() 2919 file.close() 2920 for i in range(len(lines)): 2921 self.assertEqual(batch_file[i], lines[i]) 2922 2923 # Check spin :70@N. 2924 print("\nChecking the spin :70@N input file.") 2925 file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_70_N')) 2926 lines = file.readlines() 2927 file.close() 2928 for i in range(len(spin1)): 2929 print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 2930 for i in range(len(lines)): 2931 self.assertEqual(spin1[i], lines[i]) 2932 2933 # Check spin :71@N. 2934 print("\nChecking the spin :71@N input file.") 2935 file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_71_N')) 2936 lines = file.readlines() 2937 file.close() 2938 for i in range(len(lines)): 2939 print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 2940 for i in range(len(spin2)): 2941 self.assertEqual(spin2[i], lines[i])

2942 2943

2944 - def test_korzhnev_2005_15n_dq_data(self):

2945 """Optimisation of the Korzhnev et al., 2005 15N DQ CPMG data using the 'NS MMQ 2-site' model. 2946 2947 This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}. This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 2948 2949 Here only the 15N DQ data will be optimised. The values found by cpmg_fit using just this data are: 2950 2951 - r2 = {'500': 9.487269007171426, '600': 11.718267257562591, '800': 13.624551743116887}, 2952 - pA = 0.965402506690231, 2953 - dw = 0.805197170133360, 2954 - dwH = -0.595536627771890, 2955 - kex = 569.003663067619868, 2956 - chi2 = 9.297671357952812. 2957 """ 2958 2959 # Base data setup. 2960 self.setup_korzhnev_2005_data(data_list=['DQ']) 2961 2962 # Alias the spin. 2963 spin = return_spin(":9@N") 2964 2965 # The R20 keys. 2966 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 2967 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 2968 r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 2969 2970 # Set the initial parameter values. 2971 spin.r2 = {r20_key1: 9.48527908326952, r20_key2: 11.7135951595536, r20_key3: 13.6153887849344} 2972 spin.pA = 0.965638501551899 2973 spin.dw = 2.8537583461577 2974 spin.dwH = -0.387633062766635 2975 spin.kex = 573.704033851592 2976 2977 # Low precision optimisation. 2978 self.interpreter.minimise(min_algor='simplex', func_tol=1e-05, max_iter=1000) 2979 2980 # Monte Carlo simulations. 2981 self.interpreter.monte_carlo.setup(number=2) 2982 self.interpreter.monte_carlo.create_data(method='back_calc') 2983 self.interpreter.monte_carlo.initial_values() 2984 self.interpreter.minimise(min_algor='simplex', max_iter=10) 2985 self.interpreter.monte_carlo.error_analysis() 2986 2987 # Plot the dispersion curves. 2988 self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 2989 2990 # Save the results. 2991 self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 2992 2993 # Printout. 2994 print("\n\nOptimised parameters:\n") 2995 print("%-20s %-20s" % ("Parameter", "Value (:9)")) 2996 print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 2997 print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 2998 print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 2999 print("%-20s %20.15g" % ("pA", spin.pA)) 3000 print("%-20s %20.15g" % ("dw", spin.dw)) 3001 print("%-20s %20.15g" % ("dwH", spin.dwH)) 3002 print("%-20s %20.15g" % ("kex", spin.kex)) 3003 print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 3004 3005 # Checks for residue :9. 3006 self.assertAlmostEqual(spin.r2[r20_key1], 9.48527908326952, 2) 3007 self.assertAlmostEqual(spin.r2[r20_key2], 11.7135951595536, 2) 3008 self.assertAlmostEqual(spin.r2[r20_key3], 13.6153887849344, 2) 3009 self.assertAlmostEqual(spin.pA, 0.965638501551899, 4) 3010 self.assertAlmostEqual(spin.dw, 2.8537583461577, 1) 3011 self.assertAlmostEqual(spin.dwH, -0.387633062766635, 2) 3012 self.assertAlmostEqual(spin.kex/1000, 573.704033851592/1000, 3) 3013 self.assertAlmostEqual(spin.chi2, 9.29563496654824, 2)

3014 3015

3016 - def test_korzhnev_2005_15n_mq_data(self):

3017 """Optimisation of the Korzhnev et al., 2005 15N MQ CPMG data using the 'NS MMQ 2-site' model. 3018 3019 This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}. This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 3020 3021 Here only the 15N MQ data will be optimised. The values found by cpmg_fit using just this data are: 3022 3023 - r2 = {'500': 5.993083514798655, '600': 6.622184438384841, '800': 8.640765919352019}, 3024 - pA = 0.930027999814003, 3025 - dw = 4.338620619954370, 3026 - dwH = -0.274250775560818, 3027 - kex = 344.613362916544475, 3028 - chi2 = 10.367733168217050. 3029 """ 3030 3031 # Base data setup. 3032 self.setup_korzhnev_2005_data(data_list=['MQ']) 3033 3034 # Alias the spin. 3035 spin = return_spin(":9@N") 3036 3037 # The R20 keys. 3038 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 3039 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 3040 r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 3041 3042 # Set the initial parameter values. 3043 spin.r2 = {r20_key1: 6.02016436619016, r20_key2: 6.65421500772308, r20_key3: 8.6729591487622} 3044 spin.pA = 0.930083249288083 3045 spin.dw = 4.33890689462363 3046 spin.dwH = -0.274316585638047 3047 spin.kex = 344.329651956132 3048 3049 # Low precision optimisation. 3050 self.interpreter.minimise(min_algor='simplex', func_tol=1e-05, max_iter=1000) 3051 3052 # Monte Carlo simulations. 3053 self.interpreter.monte_carlo.setup(number=2) 3054 self.interpreter.monte_carlo.create_data(method='back_calc') 3055 self.interpreter.monte_carlo.initial_values() 3056 self.interpreter.minimise(min_algor='simplex', max_iter=10) 3057 self.interpreter.monte_carlo.error_analysis() 3058 3059 # Plot the dispersion curves. 3060 self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 3061 3062 # Save the results. 3063 self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 3064 3065 # Printout. 3066 print("\n\nOptimised parameters:\n") 3067 print("%-20s %-20s" % ("Parameter", "Value (:9)")) 3068 print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 3069 print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 3070 print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 3071 print("%-20s %20.15g" % ("pA", spin.pA)) 3072 print("%-20s %20.15g" % ("dw", spin.dw)) 3073 print("%-20s %20.15g" % ("dwH", spin.dwH)) 3074 print("%-20s %20.15g" % ("kex", spin.kex)) 3075 print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 3076 3077 # Checks for residue :9. 3078 self.assertAlmostEqual(spin.r2[r20_key1], 6.02016436619016, 1) 3079 self.assertAlmostEqual(spin.r2[r20_key2], 6.65421500772308, 1) 3080 self.assertAlmostEqual(spin.r2[r20_key3], 8.6729591487622, 1) 3081 self.assertAlmostEqual(spin.pA, 0.930083249288083, 3) 3082 self.assertAlmostEqual(spin.dw, 4.33890689462363, 2) 3083 self.assertAlmostEqual(spin.dwH, -0.274316585638047, 3) 3084 self.assertAlmostEqual(spin.kex/1000, 344.329651956132/1000, 3) 3085 self.assertAlmostEqual(spin.chi2, 10.3654315659173, 2)

3086 3087

3088 - def test_korzhnev_2005_15n_sq_data(self):

3089 """Optimisation of the Korzhnev et al., 2005 15N SQ CPMG data using the 'NS MMQ 2-site' model. 3090 3091 This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}. This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 3092 3093 Here only the 15N SQ data will be optimised. The values found by cpmg_fit using just this data are: 3094 3095 - r2 = {'500': 8.335037972570017, '600': 8.761366016417508, '800': 10.225001019091822}, 3096 - pA = 0.950003458294991, 3097 - dw = 4.358402855315123, 3098 - kex = 429.906473361926999, 3099 - chi2 = 17.393331915567252. 3100 """ 3101 3102 # Base data setup. 3103 self.setup_korzhnev_2005_data(data_list=['SQ']) 3104 3105 # Alias the spin. 3106 spin = return_spin(":9@N") 3107 3108 # The R20 keys. 3109 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 3110 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 3111 r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 3112 3113 # Set the initial parameter values. 3114 spin.r2 = {r20_key1: 8.334232330326190, r20_key2: 8.756773997879968, r20_key3: 10.219320492033058} 3115 spin.pA = 0.950310172115387 3116 spin.dw = 4.356737157889636 3117 spin.kex = 433.176323890829849 3118 3119 # Low precision optimisation. 3120 self.interpreter.minimise(min_algor='simplex', func_tol=1e-05, max_iter=1000) 3121 3122 # Monte Carlo simulations. 3123 self.interpreter.monte_carlo.setup(number=2) 3124 self.interpreter.monte_carlo.create_data(method='back_calc') 3125 self.interpreter.monte_carlo.initial_values() 3126 self.interpreter.minimise(min_algor='simplex', max_iter=10) 3127 self.interpreter.monte_carlo.error_analysis() 3128 3129 # Plot the dispersion curves. 3130 self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 3131 3132 # Save the results. 3133 self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 3134 3135 # Printout. 3136 print("\n\nOptimised parameters:\n") 3137 print("%-20s %-20s" % ("Parameter", "Value (:9)")) 3138 print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 3139 print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 3140 print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 3141 print("%-20s %20.15g" % ("pA", spin.pA)) 3142 print("%-20s %20.15g" % ("dw", spin.dw)) 3143 print("%-20s %20.15g" % ("kex", spin.kex)) 3144 print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 3145 3146 # Checks for residue :9. 3147 self.assertAlmostEqual(spin.r2[r20_key1], 8.334232330326190, 2) 3148 self.assertAlmostEqual(spin.r2[r20_key2], 8.756773997879968, 2) 3149 self.assertAlmostEqual(spin.r2[r20_key3], 10.219320492033058, 1) 3150 self.assertAlmostEqual(spin.pA, 0.950310172115387, 3) 3151 self.assertAlmostEqual(spin.dw, 4.356737157889636, 2) 3152 self.assertAlmostEqual(spin.kex/1000, 433.176323890829849/1000, 3) 3153 self.assertAlmostEqual(spin.chi2, 17.37460582872912, 1)

3154 3155

3156 - def test_korzhnev_2005_15n_zq_data(self):

3157 """Optimisation of the Korzhnev et al., 2005 15N ZQ CPMG data using the 'NS MMQ 2-site' model. 3158 3159 This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}. This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 3160 3161 Here only the 15N ZQ data will be optimised. The values found by cpmg_fit using just this data are: 3162 3163 - r2 = {'500': 5.909812628572937, '600': 6.663690132557320, '800': 6.787171647689906}, 3164 - pA = 0.942452612380140, 3165 - dw = 0.858972784230892, 3166 - dwH = 0.087155962730608, 3167 - kex = 373.219151384798920, 3168 - chi2 = 23.863208106025152. 3169 """ 3170 3171 # Base data setup. 3172 self.setup_korzhnev_2005_data(data_list=['ZQ']) 3173 3174 # Alias the spin. 3175 spin = return_spin(":9@N") 3176 3177 # The R20 keys. 3178 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 3179 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 3180 r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 3181 3182 # Set the initial parameter values. 3183 spin.r2 = {r20_key1: 5.91033272691614, r20_key2: 6.66368695342258, r20_key3: 6.78922219135537} 3184 spin.pA = 0.942457332074014 3185 spin.dw = 0.850592422908884 3186 spin.dwH = 0.0881272284455416 3187 spin.kex = 372.745483351305 3188 3189 # Low precision optimisation. 3190 self.interpreter.minimise(min_algor='simplex', func_tol=1e-05, max_iter=1000) 3191 3192 # Monte Carlo simulations. 3193 self.interpreter.monte_carlo.setup(number=2) 3194 self.interpreter.monte_carlo.create_data(method='back_calc') 3195 self.interpreter.monte_carlo.initial_values() 3196 self.interpreter.minimise(min_algor='simplex', max_iter=10) 3197 self.interpreter.monte_carlo.error_analysis() 3198 3199 # Plot the dispersion curves. 3200 self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 3201 3202 # Save the results. 3203 self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 3204 3205 # Printout. 3206 print("\n\nOptimised parameters:\n") 3207 print("%-20s %-20s" % ("Parameter", "Value (:9)")) 3208 print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 3209 print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 3210 print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 3211 print("%-20s %20.15g" % ("pA", spin.pA)) 3212 print("%-20s %20.15g" % ("dw", spin.dw)) 3213 print("%-20s %20.15g" % ("dwH", spin.dwH)) 3214 print("%-20s %20.15g" % ("kex", spin.kex)) 3215 print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 3216 3217 # Checks for residue :9. 3218 self.assertAlmostEqual(spin.r2[r20_key1], 5.91033272691614, 2) 3219 self.assertAlmostEqual(spin.r2[r20_key2], 6.66368695342258, 2) 3220 self.assertAlmostEqual(spin.r2[r20_key3], 6.78922219135537, 2) 3221 self.assertAlmostEqual(spin.pA, 0.942457332074014, 4) 3222 self.assertAlmostEqual(spin.dw, 0.850592422908884, 1) 3223 self.assertAlmostEqual(spin.dwH, 0.0881272284455416, 2) 3224 self.assertAlmostEqual(spin.kex/1000, 372.745483351305/1000, 3) 3225 self.assertAlmostEqual(spin.chi2, 23.8464637019392, 1)

3226 3227

3228 - def test_korzhnev_2005_1h_mq_data(self):

3229 """Optimisation of the Korzhnev et al., 2005 1H MQ CPMG data using the 'NS MMQ 2-site' model. 3230 3231 This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}. This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 3232 3233 Here only the 1H MQ data will be optimised. The values found by cpmg_fit using just this data are: 3234 3235 - r2 = {'500': -0.000016676911302, '600': 0.036594127620440, '800': 2.131014839635728}, 3236 - pA = 0.936911090448340, 3237 - dw = 4.325314846914845, 3238 - dwH = -0.213870168665628, 3239 - kex = 487.361914835074117, 3240 - chi2 = 14.870371897291138. 3241 """ 3242 3243 # Base data setup. 3244 self.setup_korzhnev_2005_data(data_list=['1H MQ']) 3245 3246 # Alias the spin. 3247 spin = return_spin(":9@N") 3248 3249 # The R20 keys. 3250 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 3251 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 3252 r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 3253 3254 # Set the initial parameter values. 3255 spin.r2 = {r20_key1: 0.000022585022901, r20_key2: 0.039223196112941, r20_key3: 2.136576686700357} 3256 spin.pA = 0.936884348941701 3257 spin.dw = 4.326454531583964 3258 spin.dwH = -0.214026093221782 3259 spin.kex = 487.043592705469223 3260 3261 # Low precision optimisation. 3262 self.interpreter.minimise(min_algor='simplex', func_tol=1e-05, max_iter=100) 3263 3264 # Monte Carlo simulations. 3265 self.interpreter.monte_carlo.setup(number=2) 3266 self.interpreter.monte_carlo.create_data(method='back_calc') 3267 self.interpreter.monte_carlo.initial_values() 3268 self.interpreter.minimise(min_algor='simplex', max_iter=10) 3269 self.interpreter.monte_carlo.error_analysis() 3270 3271 # Plot the dispersion curves. 3272 self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 3273 3274 # Save the results. 3275 self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 3276 3277 # Printout. 3278 print("\n\nOptimised parameters:\n") 3279 print("%-20s %-20s" % ("Parameter", "Value (:9)")) 3280 print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 3281 print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 3282 print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 3283 print("%-20s %20.15g" % ("pA", spin.pA)) 3284 print("%-20s %20.15g" % ("dw", spin.dw)) 3285 print("%-20s %20.15g" % ("dwH", spin.dwH)) 3286 print("%-20s %20.15g" % ("kex", spin.kex)) 3287 print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 3288 3289 # Checks for residue :9. 3290 self.assertAlmostEqual(spin.r2[r20_key1], 0.000023714274046, 4) 3291 self.assertAlmostEqual(spin.r2[r20_key2], 0.039223196112941, 2) 3292 self.assertAlmostEqual(spin.r2[r20_key3], 2.13657668670036, 2) 3293 self.assertAlmostEqual(spin.pA, 0.936884348941701, 4) 3294 self.assertAlmostEqual(spin.dw, 4.32645453158396, 2) 3295 self.assertAlmostEqual(spin.dwH, -0.214026093221782, 2) 3296 self.assertAlmostEqual(spin.kex/1000, 487.043592705469/1000, 4) 3297 self.assertAlmostEqual(spin.chi2, 14.8642315375301, 2)

3298 3299

3300 - def test_korzhnev_2005_1h_sq_data(self):

3301 """Optimisation of the Korzhnev et al., 2005 1H SQ CPMG data using the 'NS MMQ 2-site' model. 3302 3303 This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}. This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 3304 3305 Here only the 1H SQ data will be optimised. The values found by cpmg_fit using just this data are: 3306 3307 - r2 = {'500': 6.691697587650816, '600': 6.998915158708793, '800': 5.519267837559072}, 3308 - pA = 0.946949480545876, 3309 - dwH = -0.265279672133308, 3310 - kex = 406.548178869750700, 3311 - chi2 = 50.400680290545026. 3312 """ 3313 3314 # Base data setup. 3315 self.setup_korzhnev_2005_data(data_list=['1H SQ']) 3316 3317 # Alias the spin. 3318 spin = return_spin(":9@N") 3319 3320 # The R20 keys. 3321 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 3322 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 3323 r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 3324 3325 # Set the initial parameter values. 3326 spin.r2 = {r20_key1: 6.69107911078939, r20_key2: 6.99888898689085, r20_key3: 5.52012880268077} 3327 spin.pA = 0.946990967372467 3328 spin.dwH = -0.265308128403529 3329 spin.kex = 406.843250675648 3330 3331 # Low precision optimisation. 3332 self.interpreter.minimise(min_algor='simplex', func_tol=1e-05, max_iter=1000) 3333 3334 # Monte Carlo simulations. 3335 self.interpreter.monte_carlo.setup(number=2) 3336 self.interpreter.monte_carlo.create_data(method='back_calc') 3337 self.interpreter.monte_carlo.initial_values() 3338 self.interpreter.minimise(min_algor='simplex', max_iter=10) 3339 self.interpreter.monte_carlo.error_analysis() 3340 3341 # Plot the dispersion curves. 3342 self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 3343 3344 # Save the results. 3345 self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 3346 3347 # Printout. 3348 print("\n\nOptimised parameters:\n") 3349 print("%-20s %-20s" % ("Parameter", "Value (:9)")) 3350 print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 3351 print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 3352 print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 3353 print("%-20s %20.15g" % ("pA", spin.pA)) 3354 print("%-20s %20.15g" % ("dwH", spin.dwH)) 3355 print("%-20s %20.15g" % ("kex", spin.kex)) 3356 print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 3357 3358 # Checks for residue :9. 3359 self.assertAlmostEqual(spin.r2[r20_key1], 6.69107911078939, 2) 3360 self.assertAlmostEqual(spin.r2[r20_key2], 6.99888898689085, 2) 3361 self.assertAlmostEqual(spin.r2[r20_key3], 5.52012880268077, 2) 3362 self.assertAlmostEqual(spin.pA, 0.946990967372467, 4) 3363 self.assertAlmostEqual(spin.dwH, -0.265308128403529, 4) 3364 self.assertAlmostEqual(spin.kex/1000, 406.843250675648/1000, 2) 3365 self.assertAlmostEqual(spin.chi2, 50.3431330819767, 1)

3366 3367

3368 - def test_korzhnev_2005_all_data(self):

3369 """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 3370 3371 This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}. This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 3372 3373 Here all data will be optimised. The values found by cpmg_fit using just this data are: 3374 3375 - r2 = {'H-S 500': 6.671649051677150, 'H-S 600': 6.988634195648529, 'H-S 800': 5.527971316790596, 3376 'N-S 500': 8.394988400015988, 'N-S 600': 8.891359568401835, 'N-S 800': 10.405356669006709, 3377 'NHZ 500': 5.936446687394352, 'NHZ 600': 6.717058062814535, 'NHZ 800': 6.838733853403030, 3378 'NHD 500': 8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 3379 'HNM 500': 7.851325614877817, 'HNM 600': 8.408803624020202, 'HNM 800': 11.227489645758979, 3380 'NHM 500': 9.189159145380575, 'NHM 600': 9.856814478405868, 'NHM 800': 11.967910041807118}, 3381 - pA = 0.943125351763911, 3382 - dw = 4.421827493809807, 3383 - dwH = -0.272637034755752, 3384 - kex = 360.609744568697238, 3385 - chi2 = 162.589570340050813. 3386 """ 3387 3388 # Base data setup. 3389 self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 3390 3391 # Alias the spin. 3392 spin = return_spin(":9@N") 3393 3394 # The R20 keys. 3395 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 3396 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 3397 r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 3398 r20_key4 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 3399 r20_key5 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 3400 r20_key6 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 3401 r20_key7 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 3402 r20_key8 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 3403 r20_key9 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 3404 r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 3405 r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 3406 r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 3407 r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 3408 r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 3409 r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 3410 r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 3411 r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 3412 r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 3413 3414 # Set the initial parameter values. 3415 spin.r2 = { 3416 r20_key1: 6.67288025927458, r20_key2: 6.98951408255098, r20_key3: 5.52959273852704, 3417 r20_key4: 8.39471048876782, r20_key5: 8.89290699178799, r20_key6: 10.40770687236930, 3418 r20_key7: 5.93611174376373, r20_key8: 6.71735669582514, r20_key9: 6.83835225518265, 3419 r20_key10: 8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 3420 r20_key13: 7.85956711501608, r20_key14: 8.41891642907918, r20_key15: 11.23620892230380, 3421 r20_key16: 9.19654863789350, r20_key17: 9.86031627358462, r20_key18: 11.97523755925750 3422 } 3423 spin.pA = 0.943129019477673 3424 spin.dw = 4.42209952545181 3425 spin.dwH = -0.27258970590969 3426 spin.kex = 360.516132791038 3427 3428 # Low precision optimisation. 3429 self.interpreter.minimise(min_algor='simplex', func_tol=1e-05, max_iter=10) 3430 3431 # Monte Carlo simulations. 3432 self.interpreter.monte_carlo.setup(number=2) 3433 self.interpreter.monte_carlo.create_data(method='back_calc') 3434 self.interpreter.monte_carlo.initial_values() 3435 self.interpreter.minimise(min_algor='simplex', max_iter=10) 3436 self.interpreter.monte_carlo.error_analysis() 3437 3438 # Plot the dispersion curves. 3439 self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 3440 3441 # Save the results. 3442 self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 3443 3444 # Printout. 3445 print("\n\nOptimised parameters:\n") 3446 print("%-20s %-20s" % ("Parameter", "Value (:9)")) 3447 print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 3448 print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 3449 print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 3450 print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 3451 print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 3452 print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 3453 print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 3454 print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 3455 print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 3456 print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 3457 print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 3458 print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 3459 print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 3460 print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 3461 print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 3462 print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 3463 print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 3464 print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 3465 print("%-20s %20.15g" % ("pA", spin.pA)) 3466 print("%-20s %20.15g" % ("dw", spin.dw)) 3467 print("%-20s %20.15g" % ("dwH", spin.dwH)) 3468 print("%-20s %20.15g" % ("kex", spin.kex)) 3469 print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 3470 3471 # Checks for residue :9. 3472 self.assertAlmostEqual(spin.r2[r20_key1], 6.67288025927458, 4) 3473 self.assertAlmostEqual(spin.r2[r20_key2], 6.98951408255098, 4) 3474 self.assertAlmostEqual(spin.r2[r20_key3], 5.52959273852704, 4) 3475 self.assertAlmostEqual(spin.r2[r20_key4], 8.39471048876782, 4) 3476 self.assertAlmostEqual(spin.r2[r20_key5], 8.89290699178799, 4) 3477 self.assertAlmostEqual(spin.r2[r20_key6], 10.4077068723693, 4) 3478 self.assertAlmostEqual(spin.r2[r20_key7], 5.93611174376373, 4) 3479 self.assertAlmostEqual(spin.r2[r20_key8], 6.71735669582514, 4) 3480 self.assertAlmostEqual(spin.r2[r20_key9], 6.83835225518265, 4) 3481 self.assertAlmostEqual(spin.r2[r20_key10], 8.59615074668922, 4) 3482 self.assertAlmostEqual(spin.r2[r20_key11], 10.6512137889291, 4) 3483 self.assertAlmostEqual(spin.r2[r20_key12], 12.5710822919109, 4) 3484 self.assertAlmostEqual(spin.r2[r20_key13], 7.85956711501608, 4) 3485 self.assertAlmostEqual(spin.r2[r20_key14], 8.41891642907918, 4) 3486 self.assertAlmostEqual(spin.r2[r20_key15], 11.2362089223038, 4) 3487 self.assertAlmostEqual(spin.r2[r20_key16], 9.1965486378935, 4) 3488 self.assertAlmostEqual(spin.r2[r20_key17], 9.86031627358462, 4) 3489 self.assertAlmostEqual(spin.r2[r20_key18], 11.9752375592575, 4) 3490 self.assertAlmostEqual(spin.pA, 0.943129019477673, 4) 3491 self.assertAlmostEqual(spin.dw, 4.42209952545181, 4) 3492 self.assertAlmostEqual(spin.dwH, -0.27258970590969, 4) 3493 self.assertAlmostEqual(spin.kex/1000, 360.516132791038/1000, 4) 3494 self.assertAlmostEqual(spin.chi2/1000, 162.511988511609/1000, 3)

3495 3496

3497 - def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72(self):

3498 """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 3499 3500 This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}. This is CPMG data with a fixed relaxation time period. Experiment in 0.48 M GuHCl (guanidine hydrochloride). 3501 """ 3502 3503 # Base data setup. 3504 self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 3505 3506 # Alias the spins. 3507 res61L = cdp.mol[0].res[0].spin[0] 3508 3509 # The R20 keys. 3510 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 3511 3512 # Set the initial parameter values. 3513 res61L.r2 = {r20_key1: 8.0} 3514 res61L.pA = 0.9 3515 res61L.dw = 6.0 3516 res61L.kex = 600.0 3517 3518 # Low precision optimisation. 3519 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 3520 3521 # Printout. 3522 print("\n\nOptimised parameters:\n") 3523 print("%-20s %-20s" % ("Parameter", "Value (:61)")) 3524 print("%-20s %20.15g" % ("R2 (600 MHz)", res61L.r2[r20_key1])) 3525 print("%-20s %20.15g" % ("pA", res61L.pA)) 3526 print("%-20s %20.15g" % ("dw", res61L.dw)) 3527 print("%-20s %20.15g" % ("kex", res61L.kex)) 3528 print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 3529 3530 # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 3531 self.assertAlmostEqual(res61L.r2[r20_key1], 8.69277980194016, 4) 3532 self.assertAlmostEqual(res61L.pA, 0.9943781590842946, 5) 3533 self.assertAlmostEqual(res61L.dw, 6.389453131263374, 3) 3534 self.assertAlmostEqual(res61L.kex, 609.262167216419, 0) 3535 self.assertAlmostEqual(res61L.chi2, 65.99987828889657, 5) 3536 3537 # Test the conversion to k_AB from kex and pA. 3538 self.assertEqual(res61L.k_AB, res61L.kex * (1.0 - res61L.pA)) 3539 3540 # Test the conversion to k_BA from kex and pA. 3541 self.assertEqual(res61L.k_BA, res61L.kex * res61L.pA)

3542 3543

3544 - def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72_full(self):

3545 """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 3546 3547 This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}. This is CPMG data with a fixed relaxation time period. Experiment in 0.48 M GuHCl (guanidine hydrochloride). 3548 """ 3549 3550 # Base data setup. 3551 self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72 full', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 3552 3553 # Alias the spins. 3554 res61L = cdp.mol[0].res[0].spin[0] 3555 3556 # The R20 keys. 3557 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 3558 3559 # Set the initial parameter values. 3560 res61L.r2a = {r20_key1: 8.0} 3561 res61L.r2b = {r20_key1: 105.0} 3562 res61L.pA = 0.9 3563 res61L.dw = 6.0 3564 res61L.kex = 500.0 3565 3566 # Low precision optimisation. 3567 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 3568 3569 # Printout. 3570 print("\n\nOptimised parameters:\n") 3571 print("%-20s %-20s" % ("Parameter", "Value (:61)")) 3572 print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 3573 print("%-20s %20.15g" % ("R2B (600 MHz)", res61L.r2b[r20_key1])) 3574 print("%-20s %20.15g" % ("pA", res61L.pA)) 3575 print("%-20s %20.15g" % ("dw", res61L.dw)) 3576 print("%-20s %20.15g" % ("kex", res61L.kex)) 3577 print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 3578 3579 # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 3580 self.assertAlmostEqual(res61L.r2a[r20_key1], 8.044428899438309, 0) 3581 self.assertAlmostEqual(res61L.r2b[r20_key1], 105.11894506392449, -2) 3582 self.assertAlmostEqual(res61L.pA, 0.992066883657578, 2) 3583 self.assertAlmostEqual(res61L.dw, 6.389453586338883, 3) 3584 self.assertAlmostEqual(res61L.kex, 513.483608742063, -2) 3585 self.assertAlmostEqual(res61L.chi2, 65.99987828890289, 5)

3586 3587

3588 - def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_tsmfk01(self):

3589 """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 3590 3591 This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}. This is CPMG data with a fixed relaxation time period. Experiment in 0.48 M GuHCl (guanidine hydrochloride). 3592 3593 Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 3594 3595 - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 3596 - 0.483 0.89623903 2.4503699912708878 3597 - 0.545 1.1694838 3598 - 0.545 1.1761503 3599 - 0.622 1.294 3600 - 0.669 1.5176493 3601 - 0.722 1.6238791 3602 - 0.813 1.9395758 3603 - 1.011 2.3558415 10.547000429321157 3604 """ 3605 3606 # Base data setup. 3607 self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 3608 3609 # Alias the spins. 3610 res61L = cdp.mol[0].res[0].spin[0] 3611 3612 # The R20 keys. 3613 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 3614 3615 # Set the initial parameter values. 3616 res61L.r2a = {r20_key1: 8.0} 3617 res61L.dw = 6.5 3618 res61L.k_AB = 2.5 3619 3620 # Low precision optimisation. 3621 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 3622 3623 # Printout. 3624 print("\n\nOptimised parameters:\n") 3625 print("%-20s %-20s" % ("Parameter", "Value (:61)")) 3626 print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 3627 print("%-20s %20.15g" % ("dw", res61L.dw)) 3628 print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 3629 print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 3630 3631 # Checks for residue :61. Reference values from paper 3632 3633 self.assertAlmostEqual(res61L.k_AB, 2.45, 1)

3634 3635

3636 - def test_kteilum_fmpoulsen_makke_cpmg_data_101m_guhcl_to_tsmfk01(self):

3637 """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 3638 3639 This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}. This is CPMG data with a fixed relaxation time period. Experiment in 1.01 M GuHCl (guanidine hydrochloride). 3640 3641 The comparison is to Figure 2, which is for dataset with 1 M GuHCl. The reported results are expected to be in rad.s^-1. Conversion into relax stored values is preferably. 3642 3643 Representative 15N CPMG relaxation dispersion curve measured on the cross peaks from residue L61 in folded ACBP at pH 5.3, 1 M GuHCl, and 40C: 3644 3645 1. The dotted line represents a residue-specific fit of all parameters in Eq. 1: 3646 - k_AB = 11.3 +/- 0.7 s^-1, 3647 - dw = (2.45 +/- 0.09) * 10^3 s^-1, 3648 - R2 = 8.0 +/- 0.5 s^-1. 3649 3650 2. The solid line represents a global fit of k_AB to all protein residues and a residue-specific fit of dw and R2.: 3651 - k_AB = 10.55 +/- 0.08 s^-1, 3652 - dw = (2.44 +/- 0.08) * 10^3 s^-1, 3653 - R2 = 8.4 +/- 0.3 s^-1. 3654 3655 Conversion of paper results to relax results is performed by: 3656 3657 - dw(ppm) = dw(rad.s^-1) * 10^6 * 1/(2*pi) * (gyro1H/(gyro15N*spectrometer_freq)) = 2.45E3 * 1E6 / (2 * math.pi) * (26.7522212E7/(-2.7126E7 * 599.8908622E6)) = -6.41 ppm. 3658 3659 Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 3660 3661 - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 3662 - 0.483 0.89623903 2.4503699912708878 3663 - 0.545 1.1694838 3664 - 0.545 1.1761503 3665 - 0.622 1.294 3666 - 0.669 1.5176493 3667 - 0.722 1.6238791 3668 - 0.813 1.9395758 3669 - 1.011 2.3558415 10.547000429321157 3670 """ 3671 3672 # Base data setup. 3673 self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_101MGuHCl_40C_041223") 3674 3675 # Alias the spins. 3676 res61L = cdp.mol[0].res[0].spin[0] 3677 3678 # The R20 keys. 3679 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086270e6) 3680 3681 # Set the initial parameter values. 3682 res61L.r2a = {r20_key1: 8.0} 3683 res61L.dw = 6.5 3684 res61L.k_AB = 11.0 3685 3686 # Low precision optimisation. 3687 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 3688 3689 # Printout. 3690 print("\n\nOptimised parameters:\n") 3691 print("%-20s %-20s" % ("Parameter", "Value (:61)")) 3692 print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 3693 print("%-20s %20.15g" % ("dw", res61L.dw)) 3694 print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 3695 print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 3696 3697 # Checks for residue :61. Reference values from paper 3698 3699 self.assertAlmostEqual(res61L.r2a[r20_key1], 8.4, 0) 3700 self.assertAlmostEqual(res61L.dw, 6.41, 0) 3701 self.assertAlmostEqual(res61L.k_AB, 10.55, 0)

3702 3703

3704 - def test_lm63_3site_synthetic(self):

3705 """Test the 'LM63 3-site' dispersion model using the pure noise-free synthetic data.""" 3706 3707 # The path to the data files. 3708 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'lm63_3site' 3709 3710 # Load the state file. 3711 self.interpreter.reset() 3712 self.interpreter.state.load(data_path+sep+'r2eff_values') 3713 3714 # A new data pipe. 3715 self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to='LM63 3-site', bundle_to='relax_disp') 3716 self.interpreter.pipe.switch(pipe_name='LM63 3-site') 3717 3718 # Set up the model data. 3719 self.interpreter.relax_disp.select_model(model='LM63 3-site') 3720 self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to='LM63 3-site', param='r2eff') 3721 self.interpreter.spin.isotope('15N') 3722 3723 # Alias the spins. 3724 spin1 = return_spin(":1") 3725 spin2 = return_spin(":2") 3726 3727 # The R20 keys. 3728 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 3729 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 3730 3731 # Manually set the parameter values. 3732 spin1.r2 = {r20_key1: 12.0, r20_key2: 12.0} 3733 spin1.phi_ex_B = 0.1 3734 spin1.phi_ex_C = 0.5 3735 spin1.kB = 1500.0 3736 spin1.kC = 2500.0 3737 spin2.r2 = {r20_key1: 15.0, r20_key2: 15.0} 3738 spin2.phi_ex_B = 0.1 3739 spin2.phi_ex_C = 0.5 3740 spin2.kB = 1500.0 3741 spin2.kC = 2500.0 3742 3743 # Low precision optimisation. 3744 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 3745 3746 # Monte Carlo simulations. 3747 self.interpreter.monte_carlo.setup(number=3) 3748 self.interpreter.monte_carlo.create_data(method='back_calc') 3749 self.interpreter.monte_carlo.initial_values() 3750 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-2, grad_tol=None, max_iter=10, constraints=True, scaling=True, verbosity=1) 3751 self.interpreter.monte_carlo.error_analysis() 3752 3753 # Save the results. 3754 self.interpreter.results.write(file='devnull', compress_type=1, force=True) 3755 3756 # The model checks. 3757 print("\n\nOptimised parameters:\n") 3758 print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 3759 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 3760 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 3761 print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin1.phi_ex_B, spin2.phi_ex_B)) 3762 print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin1.phi_ex_C, spin2.phi_ex_C)) 3763 print("%-20s %20.15g %20.15g" % ("kB", spin1.kB, spin2.kB)) 3764 print("%-20s %20.15g %20.15g" % ("kC", spin1.kC, spin2.kC)) 3765 print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 3766 self.assertAlmostEqual(spin1.r2[r20_key1], 12.0, 2) 3767 self.assertAlmostEqual(spin1.r2[r20_key2], 12.0, 2) 3768 self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 3769 self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 3770 self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 3771 self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 3772 self.assertAlmostEqual(spin1.chi2, 0.0, 3) 3773 self.assertAlmostEqual(spin2.r2[r20_key1], 15.0, 3) 3774 self.assertAlmostEqual(spin2.r2[r20_key2], 15.0, 3) 3775 self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 3776 self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 3777 self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 3778 self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 3779 self.assertAlmostEqual(spin2.chi2, 0.0, 3)

3780 3781

3782 - def test_m61_data_to_m61(self):

3783 """Test the relaxation dispersion 'M61' model curve fitting to fixed time synthetic data.""" 3784 3785 # Fixed time variable. 3786 ds.fixed = True 3787 3788 # Execute the script. 3789 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 3790 3791 # The original parameters. 3792 i0 = [100000.0, 20000.0] 3793 r1rho_prime = [2.25, 24.0] 3794 pA = 0.7 3795 kex = 1000.0 3796 delta_omega = [1.0, 2.0] 3797 keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 3798 phi_ex = [] 3799 for i in range(2): 3800 phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 3801 rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 3802 3803 # Switch to the 'R2eff' model data pipe, then check for each spin. 3804 self.interpreter.pipe.switch('R2eff - relax_disp') 3805 spin_index = 0 3806 for spin, spin_id in spin_loop(return_id=True): 3807 # Printout. 3808 print("\nSpin %s." % spin_id) 3809 3810 # Check the fitted parameters. 3811 for i in range(len(keys)): 3812 self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 3813 3814 # Increment the spin index. 3815 spin_index += 1 3816 3817 # The R20 keys. 3818 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 3819 3820 # Switch to the 'M61' model data pipe, then check for each spin. 3821 self.interpreter.pipe.switch('M61 - relax_disp') 3822 spin_index = 0 3823 for spin, spin_id in spin_loop(return_id=True): 3824 # Printout. 3825 print("\nSpin %s." % spin_id) 3826 3827 # Check the fitted parameters. 3828 self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 3829 self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 3830 self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 3831 3832 # Increment the spin index. 3833 spin_index += 1

3834 3835

3836 - def test_m61_exp_data_to_m61(self):

3837 """Test the relaxation dispersion 'M61' model curve fitting to the full exponential synthetic data.""" 3838 3839 # Fixed time variable. 3840 ds.fixed = False 3841 3842 # Single spin optimisation. 3843 ds.single = True 3844 3845 # Execute the script. 3846 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 3847 3848 # The original parameters. 3849 i0 = [100000.0, 20000.0] 3850 r1rho_prime = [2.25, 24.0] 3851 pA = 0.7 3852 kex = 1000.0 3853 delta_omega = [1.0, 2.0] 3854 keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 3855 phi_ex = [] 3856 for i in range(2): 3857 phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 3858 rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 3859 3860 # Switch to the 'R2eff' model data pipe, then check for each spin. 3861 self.interpreter.pipe.switch('R2eff - relax_disp') 3862 spin_index = 0 3863 for spin, spin_id in spin_loop(return_id=True): 3864 # Printout. 3865 print("\nSpin %s." % spin_id) 3866 3867 # Check the fitted parameters. 3868 for i in range(len(keys)): 3869 self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 3870 3871 # Increment the spin index. 3872 spin_index += 1 3873 3874 # The R20 keys. 3875 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 3876 3877 # Switch to the 'M61' model data pipe, then check for each spin. 3878 self.interpreter.pipe.switch('M61 - relax_disp') 3879 spin_index = 0 3880 for spin, spin_id in spin_loop(return_id=True): 3881 # Printout. 3882 print("\nSpin %s." % spin_id) 3883 3884 # Check the fitted parameters. 3885 self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 3886 self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 3887 self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 3888 3889 # Increment the spin index. 3890 spin_index += 1

3891 3892

3893 - def xxx_test_m61b_data_to_m61b(self):

3894 """Test the relaxation dispersion 'M61 skew' model curve fitting to fixed time synthetic data.""" 3895 3896 # Execute the script. 3897 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61b.py') 3898 3899 # The original parameters. 3900 i0 = [100000.0, 20000.0] 3901 r1rho_prime = [10.0, 24.0] 3902 pA = 0.95 3903 kex = 2000.0 3904 delta_omega = [1.0, 2.0] 3905 3906 # The R20 keys. 3907 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 3908 3909 # Switch to the 'M61 skew' model data pipe, then check for each spin. 3910 self.interpreter.pipe.switch("%s - relax_disp" % MODEL_M61B) 3911 spin_index = 0 3912 for spin, spin_id in spin_loop(return_id=True): 3913 # Printout. 3914 print("\nSpin %s." % spin_id) 3915 3916 # Check the fitted parameters. 3917 self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 3918 self.assertAlmostEqual(spin.pA, pA, 2) 3919 self.assertAlmostEqual(spin.dw, dw[spin_index], 2) 3920 self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 3921 3922 # Increment the spin index. 3923 spin_index += 1

3924 3925

3926 - def test_ns_mmq_3site(self):

3927 """Compare the 'NS MMQ 3-site' dispersion model to synthetic data from cpmg_fit.""" 3928 3929 # Execute the script. 3930 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site.py') 3931 3932 # Check the chi-squared value. 3933 self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3)

3934 3935

3936 - def test_ns_mmq_3site_linear(self):

3937 """Compare the 'NS MMQ 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 3938 3939 # Execute the script. 3940 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site_linear.py') 3941 3942 # Check the chi-squared value. 3943 self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3)

3944 3945

3946 - def test_ns_r1rho_3site(self):

3947 """Compare the 'NS R1rho 3-site' dispersion model to synthetic data from cpmg_fit.""" 3948 3949 # Execute the script. 3950 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site.py') 3951 3952 # Check the chi-squared value. 3953 self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 136.13141468674999, 3)

3954 3955

3956 - def test_ns_r1rho_3site_linear(self):

3957 """Compare the 'NS R1rho 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 3958 3959 # Execute the script. 3960 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site_linear.py') 3961 3962 # Check the chi-squared value. 3963 self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 0.030959849811015544, 3)

3964 3965

3966 - def test_r1rho_kjaergaard(self):

3967 """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 3968 3969 This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 3970 3971 """ 3972 3973 # The path to the data files. 3974 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 3975 3976 # Set pipe name, bundle and type. 3977 pipe_name = 'base pipe' 3978 pipe_bundle = 'relax_disp' 3979 pipe_type= 'relax_disp' 3980 3981 # Create the data pipe. 3982 self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 3983 3984 # Read the spins. 3985 self.interpreter.spectrum.read_spins(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 3986 3987 # Test some of the sequence. 3988 self.assertEqual(len(cdp.mol), 1) 3989 self.assertEqual(cdp.mol[0].name, None) 3990 self.assertEqual(len(cdp.mol[0].res), 48) 3991 3992 # Name the isotope for field strength scaling. 3993 self.interpreter.spin.isotope(isotope='15N') 3994 3995 # Set number of experiments to be used. 3996 NR_exp = 70 3997 3998 # Load the experiments settings file. 3999 expfile = open(data_path+sep+'exp_parameters_sort.txt', 'r') 4000 expfileslines = expfile.readlines()[:NR_exp] 4001 expfile.close() 4002 4003 # In MHz 4004 yOBS = 81.050 4005 # In ppm 4006 yCAR = 118.078 4007 centerPPM_N15 = yCAR 4008 4009 ## Read the chemical shift data. 4010 self.interpreter.chemical_shift.read(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 4011 4012 # Test the chemical shift data. 4013 cs = [122.223, 122.162, 114.250, 125.852, 118.626, 117.449, 119.999, 122.610, 118.602, 118.291, 115.393, 4014 121.288, 117.448, 116.378, 116.316, 117.263, 122.211, 118.748, 118.103, 119.421, 119.317, 119.386, 117.279, 4015 122.103, 120.038, 116.698, 111.811, 118.639, 118.285, 121.318, 117.770, 119.948, 119.759, 118.314, 118.160, 4016 121.442, 118.714, 113.080, 125.706, 119.183, 120.966, 122.361, 126.675, 117.069, 120.875, 109.372, 119.811, 126.048] 4017 4018 i = 0 4019 for spin, spin_id in spin_loop(return_id=True): 4020 # Check the chemical shift. 4021 self.assertEqual(spin.chemical_shift, cs[i]) 4022 4023 # Increment the index. 4024 i += 1 4025 4026 # The lock power to field, has been found in an calibration experiment. 4027 spin_lock_field_strengths_Hz = {'35': 431.0, '39': 651.2, '41': 800.5, '43': 984.0, '46': 1341.11, '48': 1648.5} 4028 4029 # Apply spectra settings. 4030 # Count settings 4031 j = 0 4032 for i in range(len(expfileslines)): 4033 line=expfileslines[i] 4034 if line[0] == "#": 4035 continue 4036 else: 4037 # DIRN I deltadof2 dpwr2slock ncyc trim ss sfrq 4038 DIRN = line.split()[0] 4039 I = int(line.split()[1]) 4040 deltadof2 = line.split()[2] 4041 dpwr2slock = line.split()[3] 4042 ncyc = int(line.split()[4]) 4043 trim = float(line.split()[5]) 4044 ss = int(line.split()[6]) 4045 set_sfrq = float(line.split()[7]) 4046 apod_rmsd = float(line.split()[8]) 4047 spin_lock_field_strength = spin_lock_field_strengths_Hz[dpwr2slock] 4048 4049 # Calculate spin_lock time 4050 time_sl = 2*ncyc*trim 4051 4052 # Define file name for peak list. 4053 FNAME = "%s_%s_%s_%s_max_standard.ser"%(I, deltadof2, dpwr2slock, ncyc) 4054 sp_id = "%s_%s_%s_%s"%(I, deltadof2, dpwr2slock, ncyc) 4055 4056 # Load the peak intensities. 4057 self.interpreter.spectrum.read_intensities(file=FNAME, dir=data_path+sep+'peak_lists', spectrum_id=sp_id, int_method='height') 4058 4059 # Set the peak intensity errors, as defined as the baseplane RMSD. 4060 self.interpreter.spectrum.baseplane_rmsd(error=apod_rmsd, spectrum_id=sp_id) 4061 4062 # Set the relaxation dispersion experiment type. 4063 self.interpreter.relax_disp.exp_type(spectrum_id=sp_id, exp_type='R1rho') 4064 4065 # Set The spin-lock field strength, nu1, in Hz 4066 self.interpreter.relax_disp.spin_lock_field(spectrum_id=sp_id, field=spin_lock_field_strength) 4067 4068 # Calculating the spin-lock offset in ppm, from offsets values provided in Hz. 4069 frq_N15_Hz = yOBS * 1E6 4070 offset_ppm_N15 = float(deltadof2) / frq_N15_Hz * 1E6 4071 omega_rf_ppm = centerPPM_N15 + offset_ppm_N15 4072 4073 # Set The spin-lock offset, omega_rf, in ppm. 4074 self.interpreter.relax_disp.spin_lock_offset(spectrum_id=sp_id, offset=omega_rf_ppm) 4075 4076 # Set the relaxation times (in s). 4077 self.interpreter.relax_disp.relax_time(spectrum_id=sp_id, time=time_sl) 4078 4079 # Set the spectrometer frequency. 4080 self.interpreter.spectrometer.frequency(id=sp_id, frq=set_sfrq, units='MHz') 4081 4082 # Add to counter 4083 j += 1 4084 4085 # Read the R1 data 4086 self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 4087 4088 print("Testing the number of settings") 4089 print("Number of settings iterations is: %s. Number of cdp.exp_type.keys() is: %s"%(i, len(cdp.exp_type.keys() ) ) ) 4090 self.assertEqual(70, len(expfileslines)) 4091 self.assertEqual(69, j) 4092 self.assertEqual(69, len(cdp.exp_type.keys()) ) 4093 4094 # Cluster residues 4095 cluster_ids = [ 4096 ":13@N", 4097 ":15@N", 4098 ":16@N", 4099 ":25@N", 4100 ":26@N", 4101 ":28@N", 4102 ":39@N", 4103 ":40@N", 4104 ":41@N", 4105 ":43@N", 4106 ":44@N", 4107 ":45@N", 4108 ":49@N", 4109 ":52@N", 4110 ":53@N"] 4111 4112 # Cluster spins 4113 for curspin in cluster_ids: 4114 print("Adding spin %s to cluster"%curspin) 4115 self.interpreter.relax_disp.cluster('model_cluster', curspin) 4116 4117 # De-select for analysis those spins who have not been clustered 4118 for free_spin in cdp.clustering['free spins']: 4119 print("Deselecting free spin %s"%free_spin) 4120 self.interpreter.deselect.spin(spin_id=free_spin, change_all=False) 4121 4122 # Initialize counter 4123 i = 0 4124 j = 0 4125 # Count instances of select/deselect 4126 for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 4127 if curspin.select == True: 4128 i += 1 4129 if curspin.select == False: 4130 j += 1 4131 4132 # Test number of selected/deselected spins. 4133 self.assertEqual(i, len(cluster_ids)) 4134 self.assertEqual(j, 48-len(cluster_ids)) 4135 4136 #Paper reference values 4137 # Resi Resn R1_rad_s R1err_rad_s R2_rad_s R2err_rad_s kEX_rad_s kEXerr_rad_s phi_rad2_s2 phierr_rad2_s2 phi_ppm2 phierr_ppm2 4138 # Scaling rad2_s2 to ppm2: scaling_rad2_s2 = frequency_to_ppm(frq=1/(2*pi), B0=cdp.spectrometer_frq_list[0], isotope='15N')**2 = 3.85167990165e-06 4139 ref = dict() 4140 ref[':13@N'] = [13, 'L13N-HN', 1.32394, 0.14687, 8.16007, 1.01237, 13193.82986, 2307.09152, 58703.06446, 22413.09854, 0.2261054135, 0.0863280812] 4141 ref[':15@N'] = [15, 'R15N-HN', 1.34428, 0.14056, 7.83256, 0.67559, 13193.82986, 2307.09152, 28688.33492, 13480.72253, 0.110498283, 0.051923428] 4142 ref[':16@N'] = [16, 'T16N-HN', 1.71514, 0.13651, 17.44216, 0.98583, 13193.82986, 2307.09152, 57356.77617, 21892.44205, 0.220919942, 0.084322679] 4143 ref[':25@N'] = [25, 'Q25N-HN', 1.82412, 0.15809, 9.09447, 2.09215, 13193.82986, 2307.09152, 143111.13431, 49535.80302, 0.5512182797, 0.1907960569] 4144 ref[':26@N'] = [26, 'Q26N-HN', 1.45746, 0.14127, 10.22801, 0.67116, 13193.82986, 2307.09152, 28187.06876, 13359.01615, 0.1085675662, 0.051454654] 4145 ref[':28@N'] = [28, 'Q28N-HN', 1.48095, 0.14231, 10.33552, 0.691, 13193.82986, 2307.09152, 30088.0686, 13920.25654, 0.1158896091, 0.0536163723] 4146 ref[':39@N'] = [39, 'L39N-HN', 1.46094, 0.14514, 8.02194, 0.84649, 13193.82986, 2307.09152, 44130.18538, 18104.55064, 0.1699753481, 0.0697329338] 4147 ref[':40@N'] = [40, 'M40N-HN', 1.21381, 0.14035, 12.19112, 0.81418, 13193.82986, 2307.09152, 41834.90493, 17319.92156, 0.1611346625, 0.0667107938] 4148 ref[':41@N'] = [41, 'A41N-HN', 1.29296, 0.14286, 9.29941, 0.66246, 13193.82986, 2307.09152, 26694.8921, 13080.66782, 0.1028201794, 0.0503825453] 4149 ref[':43@N'] = [43, 'F43N-HN', 1.33626, 0.14352, 12.73816, 1.17386, 13193.82986, 2307.09152, 70347.63797, 26648.30524, 0.2709565833, 0.1026407417] 4150 ref[':44@N'] = [44, 'I44N-HN', 1.28487, 0.1462, 12.70158, 1.52079, 13193.82986, 2307.09152, 95616.20461, 35307.79817, 0.3682830136, 0.1359943366] 4151 ref[':45@N'] = [45, 'K45N-HN', 1.59227, 0.14591, 9.54457, 0.95596, 13193.82986, 2307.09152, 53849.7826, 21009.89973, 0.2074121253, 0.0809234085] 4152 ref[':49@N'] = [49, 'A49N-HN', 1.38521, 0.14148, 4.44842, 0.88647, 13193.82986, 2307.09152, 40686.65286, 18501.20774, 0.1567119631, 0.07126073] 4153 ref[':52@N'] = [52, 'V52N-HN', 1.57531, 0.15042, 6.51945, 1.43418, 13193.82986, 2307.09152, 93499.92172, 33233.23039, 0.3601317693, 0.1280037656] 4154 ref[':53@N'] = [53, 'A53N-HN', 1.27214, 0.13823, 4.0705, 0.85485, 13193.82986, 2307.09152, 34856.18636, 17505.02393, 0.1342548725, 0.0674237488] 4155 4156 guess = dict() 4157 guess[':13@N'] = [13, 'L13N-HN', 1.32394, 0.14687, 8.16007, 1.01237, 13193.82986, 2307.09152, 58703.06446, 22413.09854, 0.2261054135, 0.0863280812] 4158 guess[':15@N'] = [15, 'R15N-HN', 1.34428, 0.14056, 7.83256, 0.67559, 13193.82986, 2307.09152, 28688.33492, 13480.72253, 0.110498283, 0.051923428] 4159 guess[':16@N'] = [16, 'T16N-HN', 1.71514, 0.13651, 17.44216, 0.98583, 13193.82986, 2307.09152, 57356.77617, 21892.44205, 0.220919942, 0.084322679] 4160 guess[':25@N'] = [25, 'Q25N-HN', 1.82412, 0.15809, 9.09447, 2.09215, 13193.82986, 2307.09152, 143111.13431, 49535.80302, 0.5512182797, 0.1907960569] 4161 guess[':26@N'] = [26, 'Q26N-HN', 1.45746, 0.14127, 10.22801, 0.67116, 13193.82986, 2307.09152, 28187.06876, 13359.01615, 0.1085675662, 0.051454654] 4162 guess[':28@N'] = [28, 'Q28N-HN', 1.48095, 0.14231, 10.33552, 0.691, 13193.82986, 2307.09152, 30088.0686, 13920.25654, 0.1158896091, 0.0536163723] 4163 guess[':39@N'] = [39, 'L39N-HN', 1.46094, 0.14514, 8.02194, 0.84649, 13193.82986, 2307.09152, 44130.18538, 18104.55064, 0.1699753481, 0.0697329338] 4164 guess[':40@N'] = [40, 'M40N-HN', 1.21381, 0.14035, 12.19112, 0.81418, 13193.82986, 2307.09152, 41834.90493, 17319.92156, 0.1611346625, 0.0667107938] 4165 guess[':41@N'] = [41, 'A41N-HN', 1.29296, 0.14286, 9.29941, 0.66246, 13193.82986, 2307.09152, 26694.8921, 13080.66782, 0.1028201794, 0.0503825453] 4166 guess[':43@N'] = [43, 'F43N-HN', 1.33626, 0.14352, 12.73816, 1.17386, 13193.82986, 2307.09152, 70347.63797, 26648.30524, 0.2709565833, 0.1026407417] 4167 guess[':44@N'] = [44, 'I44N-HN', 1.28487, 0.1462, 12.70158, 1.52079, 13193.82986, 2307.09152, 95616.20461, 35307.79817, 0.3682830136, 0.1359943366] 4168 guess[':45@N'] = [45, 'K45N-HN', 1.59227, 0.14591, 9.54457, 0.95596, 13193.82986, 2307.09152, 53849.7826, 21009.89973, 0.2074121253, 0.0809234085] 4169 guess[':49@N'] = [49, 'A49N-HN', 1.38521, 0.14148, 4.44842, 0.88647, 13193.82986, 2307.09152, 40686.65286, 18501.20774, 0.1567119631, 0.07126073] 4170 guess[':52@N'] = [52, 'V52N-HN', 1.57531, 0.15042, 6.51945, 1.43418, 13193.82986, 2307.09152, 93499.92172, 33233.23039, 0.3601317693, 0.1280037656] 4171 guess[':53@N'] = [53, 'A53N-HN', 1.27214, 0.13823, 4.0705, 0.85485, 13193.82986, 2307.09152, 34856.18636, 17505.02393, 0.1342548725, 0.0674237488] 4172 4173 # Assign guess values. 4174 for spin, spin_id in spin_loop(return_id=True): 4175 if spin_id in cluster_ids: 4176 print("spin_id %s in cluster ids"%(spin_id)) 4177 spin.kex = guess[spin_id][6] 4178 spin.phi_ex = guess[spin_id][10] 4179 else: 4180 print("spin_id %s NOT in cluster ids"%(spin_id)) 4181 4182 # Check the initial setup. 4183 self.assertEqual(cdp.mol[0].res[7].num, 13) 4184 self.assertEqual(cdp.mol[0].res[7].spin[0].kex, guess[':13@N'][6]) 4185 self.assertEqual(cdp.mol[0].res[7].spin[0].ri_data['R1'], ref[':13@N'][2]) 4186 4187 self.assertEqual(cdp.mol[0].res[9].num, 15) 4188 self.assertEqual(cdp.mol[0].res[9].spin[0].kex, guess[':15@N'][6]) 4189 self.assertEqual(cdp.mol[0].res[9].spin[0].ri_data['R1'], ref[':15@N'][2]) 4190 4191 self.assertEqual(cdp.mol[0].res[10].num, 16) 4192 self.assertEqual(cdp.mol[0].res[10].spin[0].kex, guess[':16@N'][6]) 4193 self.assert_(hasattr(cdp.mol[0].res[10].spin[0], 'ri_data')) 4194 4195 self.assertEqual(cdp.mol[0].res[16].num, 25) 4196 self.assertEqual(cdp.mol[0].res[16].spin[0].kex, guess[':25@N'][6]) 4197 self.assert_(hasattr(cdp.mol[0].res[16].spin[0], 'ri_data')) 4198 4199 self.assertEqual(cdp.mol[0].res[17].num, 26) 4200 self.assertEqual(cdp.mol[0].res[17].spin[0].kex, guess[':26@N'][6]) 4201 self.assert_(hasattr(cdp.mol[0].res[17].spin[0], 'ri_data')) 4202 4203 self.assertEqual(cdp.mol[0].res[19].num, 28) 4204 self.assertEqual(cdp.mol[0].res[19].spin[0].kex, guess[':28@N'][6]) 4205 self.assert_(hasattr(cdp.mol[0].res[19].spin[0], 'ri_data')) 4206 4207 self.assertEqual(cdp.mol[0].res[29].num, 39) 4208 self.assertEqual(cdp.mol[0].res[29].spin[0].kex, guess[':39@N'][6]) 4209 self.assert_(hasattr(cdp.mol[0].res[29].spin[0], 'ri_data')) 4210 4211 self.assertEqual(cdp.mol[0].res[30].num, 40) 4212 self.assertEqual(cdp.mol[0].res[30].spin[0].kex, guess[':40@N'][6]) 4213 self.assert_(hasattr(cdp.mol[0].res[30].spin[0], 'ri_data')) 4214 4215 self.assertEqual(cdp.mol[0].res[31].num, 41) 4216 self.assertEqual(cdp.mol[0].res[31].spin[0].kex, guess[':41@N'][6]) 4217 self.assert_(hasattr(cdp.mol[0].res[31].spin[0], 'ri_data')) 4218 4219 self.assertEqual(cdp.mol[0].res[33].num, 43) 4220 self.assertEqual(cdp.mol[0].res[33].spin[0].kex, guess[':43@N'][6]) 4221 self.assert_(hasattr(cdp.mol[0].res[33].spin[0], 'ri_data')) 4222 4223 self.assertEqual(cdp.mol[0].res[34].num, 44) 4224 self.assertEqual(cdp.mol[0].res[34].spin[0].kex, guess[':44@N'][6]) 4225 self.assert_(hasattr(cdp.mol[0].res[34].spin[0], 'ri_data')) 4226 4227 self.assertEqual(cdp.mol[0].res[35].num, 45) 4228 self.assertEqual(cdp.mol[0].res[35].spin[0].kex, guess[':45@N'][6]) 4229 self.assert_(hasattr(cdp.mol[0].res[35].spin[0], 'ri_data')) 4230 4231 self.assertEqual(cdp.mol[0].res[38].num, 49) 4232 self.assertEqual(cdp.mol[0].res[38].spin[0].kex, guess[':49@N'][6]) 4233 self.assert_(hasattr(cdp.mol[0].res[38].spin[0], 'ri_data')) 4234 4235 self.assertEqual(cdp.mol[0].res[41].num, 52) 4236 self.assertEqual(cdp.mol[0].res[41].spin[0].kex, guess[':52@N'][6]) 4237 self.assert_(hasattr(cdp.mol[0].res[41].spin[0], 'ri_data')) 4238 4239 self.assertEqual(cdp.mol[0].res[42].num, 53) 4240 self.assertEqual(cdp.mol[0].res[42].spin[0].kex, guess[':53@N'][6]) 4241 self.assert_(hasattr(cdp.mol[0].res[42].spin[0], 'ri_data')) 4242 4243 # The dispersion models. 4244 MODELS = ['R2eff', 'DPL94'] 4245 4246 # The grid search size (the number of increments per dimension). 4247 GRID_INC = 4 4248 4249 # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 4250 MC_NUM = 3 4251 4252 # Model selection technique. 4253 MODSEL = 'AIC' 4254 4255 # Execute the auto-analysis (fast). 4256 # Standard parameters are: func_tol=1e-25, grad_tol=None, max_iter=10000000, 4257 OPT_FUNC_TOL = 1e-1 4258 relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 4259 OPT_MAX_ITERATIONS = 1000 4260 relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 4261 4262 analysis_mode = "auto" 4263 4264 if analysis_mode == "auto": 4265 # Make all spins free 4266 for curspin in cluster_ids: 4267 self.interpreter.relax_disp.cluster('free spins', curspin) 4268 # Shut them down 4269 self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 4270 4271 # Select only a subset of spins for global fitting 4272 #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 4273 #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 4274 4275 #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 4276 #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 4277 4278 self.interpreter.select.spin(spin_id=':52@N', change_all=False) 4279 #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 4280 4281 # Run the analysis. 4282 relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=ds.tmpdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 4283 4284 # Check the kex value of residue 52 4285 #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ref[':52@N'][6]) 4286 4287 ########### 4288 elif analysis_mode == "man": 4289 for curspin in cluster_ids: 4290 self.interpreter.relax_disp.cluster('free spins', curspin) 4291 4292 # Do the analysis manual 4293 self.interpreter.spectrum.error_analysis(subset=['46_0_35_0', '48_0_35_4', '47_0_35_10', '49_0_35_20', '36_0_39_0', '39_0_39_4', '37_0_39_10', '40_0_39_20', '38_0_39_40', '41_0_41_0', '44_0_41_4', '42_0_41_10', '45_0_41_20', '43_0_41_40', '31_0_43_0', '34_0_43_4', '32_0_43_10', '35_0_43_20', '33_0_43_40', '1_0_46_0', '4_0_46_4', '2_0_46_10', '5_0_46_20', '3_0_46_40', '60_0_48_0', '63_0_48_4', '61_0_48_10', '62_0_48_14', '64_0_48_20', '11_500_46_0', '14_500_46_4', '12_500_46_10', '15_500_46_20', '13_500_46_40', '50_1000_41_0', '53_1000_41_4', '51_1000_41_10', '54_1000_41_20', '52_1000_41_40', '21_1000_46_0', '24_1000_46_4', '22_1000_46_10', '25_1000_46_20', '23_1000_46_40', '65_1000_48_0', '68_1000_48_4', '66_1000_48_10', '67_1000_48_14', '69_1000_48_20', '55_2000_41_0', '58_2000_41_4', '56_2000_41_10', '59_2000_41_20', '57_2000_41_40', '6_2000_46_0', '9_2000_46_4', '7_2000_46_10', '10_2000_46_20', '8_2000_46_40', '16_5000_46_0', '19_5000_46_4', '17_5000_46_10', '20_5000_46_20', '18_5000_46_40', '26_10000_46_0', '29_10000_46_4', '27_10000_46_10', '30_10000_46_20', '28_10000_46_40']) 4294 4295 ##- The 'R2eff' model - 4296 self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to='R2eff - relax_disp', bundle_to='relax_disp') 4297 self.interpreter.pipe.switch(pipe_name='R2eff - relax_disp') 4298 self.interpreter.relax_disp.select_model(model='R2eff') 4299 self.interpreter.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 4300 4301 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=OPT_FUNC_TOL, grad_tol=None, max_iter=OPT_MAX_ITERATIONS, constraints=True, scaling=True, verbosity=1) 4302 self.interpreter.eliminate(function=None, args=None) 4303 self.interpreter.monte_carlo.setup(number=MC_NUM) 4304 self.interpreter.monte_carlo.create_data(method='back_calc') 4305 self.interpreter.monte_carlo.initial_values() 4306 4307 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=OPT_FUNC_TOL, grad_tol=None, max_iter=OPT_MAX_ITERATIONS, constraints=True, scaling=True, verbosity=1) 4308 self.interpreter.eliminate(function=None, args=None) 4309 self.interpreter.monte_carlo.error_analysis() 4310 4311 # Write results 4312 #self.interpreter.relax_disp.plot_exp_curves(file='intensities.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'R2eff', force=True, norm=False) 4313 #self.interpreter.relax_disp.plot_exp_curves(file='intensities_norm.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'R2eff', force=True, norm=True) 4314 #self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir+sep+'resultsR1'+sep+'R2eff', num_points=1000, extend=500.0, force=True) 4315 #self.interpreter.relax_disp.write_disp_curves(dir=ds.tmpdir+sep+'resultsR1'+sep+'R2eff', force=True) 4316 #self.interpreter.value.write(param='r2eff', file='r2eff.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'R2eff', scaling=1.0, comment=None, bc=False, force=True) 4317 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='r2eff', spin_id=None, plot_data='value', file='r2eff.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'R2eff', force=True, norm=False) 4318 #self.interpreter.value.write(param='i0', file='i0.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'R2eff', scaling=1.0, comment=None, bc=False, force=True) 4319 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='i0', spin_id=None, plot_data='value', file='i0.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'R2eff', force=True, norm=False) 4320 #self.interpreter.value.write(param='chi2', file='chi2.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'R2eff', scaling=1.0, comment=None, bc=False, force=True) 4321 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='chi2', spin_id=None, plot_data='value', file='chi2.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'R2eff', force=True, norm=False) 4322 4323 ## Save results as state 4324 #self.interpreter.results.write(file='results', dir=ds.tmpdir+sep+'resultsR1'+sep+'R2eff', compress_type=1, force=True) 4325 4326 ##- The 'No Rex' model - 4327 self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to='No Rex - relax_disp', bundle_to='relax_disp') 4328 self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 4329 self.interpreter.relax_disp.select_model(model='No Rex') 4330 self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to='No Rex - relax_disp', param='r2eff') 4331 self.interpreter.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 4332 4333 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=OPT_FUNC_TOL, grad_tol=None, max_iter=OPT_MAX_ITERATIONS, constraints=True, scaling=True, verbosity=1) 4334 self.interpreter.eliminate(function=None, args=None) 4335 4336 ## Write results 4337 #self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir+sep+'resultsR1'+sep+'No Rex', num_points=1000, extend=500.0, force=True) 4338 #self.interpreter.relax_disp.write_disp_curves(dir=ds.tmpdir+sep+'resultsR1'+sep+'No Rex', force=True) 4339 #self.interpreter.value.write(param='chi2', file='chi2.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'No Rex', scaling=1.0, comment=None, bc=False, force=True) 4340 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='chi2', spin_id=None, plot_data='value', file='chi2.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'No Rex', force=True, norm=False) 4341 4342 ## Save results as state 4343 self.interpreter.results.write(file='results', dir=ds.tmpdir+sep+'resultsR1'+sep+'No Rex', compress_type=1, force=True) 4344 4345 ##- The 'DPL94' model - 4346 self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to='DPL94 - relax_disp', bundle_to='relax_disp') 4347 self.interpreter.pipe.switch(pipe_name='DPL94 - relax_disp') 4348 self.interpreter.relax_disp.select_model(model='DPL94') 4349 self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to='DPL94 - relax_disp', param='r2eff') 4350 self.interpreter.relax_disp.insignificance(level=1.0) 4351 self.interpreter.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 4352 4353 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=OPT_FUNC_TOL, grad_tol=None, max_iter=OPT_MAX_ITERATIONS, constraints=True, scaling=True, verbosity=1) 4354 self.interpreter.eliminate(function=None, args=None) 4355 4356 ## Write results 4357 #self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', num_points=1000, extend=500.0, force=True) 4358 #self.interpreter.relax_disp.write_disp_curves(dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', force=True) 4359 #self.interpreter.value.write(param='phi_ex', file='phi_ex.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', scaling=1.0, comment=None, bc=False, force=True) 4360 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='phi_ex', spin_id=None, plot_data='value', file='phi_ex.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', force=True, norm=False) 4361 #self.interpreter.value.write(param='k_AB', file='k_AB.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', scaling=1.0, comment=None, bc=False, force=True) 4362 #self.interpreter.value.write(param='kex', file='kex.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', scaling=1.0, comment=None, bc=False, force=True) 4363 #self.interpreter.value.write(param='tex', file='tex.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', scaling=1.0, comment=None, bc=False, force=True) 4364 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='k_AB', spin_id=None, plot_data='value', file='k_AB.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', force=True, norm=False) 4365 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='kex', spin_id=None, plot_data='value', file='kex.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', force=True, norm=False) 4366 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='tex', spin_id=None, plot_data='value', file='tex.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', force=True, norm=False) 4367 #self.interpreter.value.write(param='chi2', file='chi2.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', scaling=1.0, comment=None, bc=False, force=True) 4368 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='chi2', spin_id=None, plot_data='value', file='chi2.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', force=True, norm=False) 4369 4370 ## Save results as state 4371 #self.interpreter.results.write(file='results', dir=ds.tmpdir+sep+'resultsR1'+sep+'DPL94', compress_type=1, force=True) 4372 4373 ##- The 'final' model - 4374 self.interpreter.model_selection(method='AIC', modsel_pipe='final - relax_disp', bundle='relax_disp', pipes=['No Rex - relax_disp', 'DPL94 - relax_disp']) 4375 self.interpreter.monte_carlo.setup(number=MC_NUM) 4376 self.interpreter.monte_carlo.create_data(method='back_calc') 4377 self.interpreter.monte_carlo.initial_values() 4378 4379 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=OPT_FUNC_TOL, grad_tol=None, max_iter=OPT_MAX_ITERATIONS, constraints=True, scaling=True, verbosity=1) 4380 self.interpreter.eliminate(function=None, args=None) 4381 self.interpreter.monte_carlo.error_analysis() 4382 4383 ## Write results 4384 #self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir+sep+'resultsR1'+sep+'final', num_points=1000, extend=500.0, force=True) 4385 #self.interpreter.relax_disp.write_disp_curves(dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True) 4386 #self.interpreter.value.write(param='model', file='model.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4387 #self.interpreter.value.write(param='pA', file='pA.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4388 #self.interpreter.value.write(param='pB', file='pB.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4389 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='pA', spin_id=None, plot_data='value', file='pA.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4390 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='pB', spin_id=None, plot_data='value', file='pB.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4391 self.interpreter.value.write(param='phi_ex', file='phi_ex.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4392 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='phi_ex', spin_id=None, plot_data='value', file='phi_ex.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4393 #self.interpreter.value.write(param='phi_ex_B', file='phi_ex_B.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4394 #self.interpreter.value.write(param='phi_ex_C', file='phi_ex_C.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4395 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='phi_ex_B', spin_id=None, plot_data='value', file='phi_ex_B.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4396 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='phi_ex_C', spin_id=None, plot_data='value', file='phi_ex_C.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4397 #self.interpreter.value.write(param='dw', file='dw.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4398 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='dw', spin_id=None, plot_data='value', file='dw.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4399 #self.interpreter.value.write(param='dwH', file='dwH.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4400 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='dwH', spin_id=None, plot_data='value', file='dwH.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4401 #self.interpreter.value.write(param='k_AB', file='k_AB.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4402 self.interpreter.value.write(param='kex', file='kex.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4403 #self.interpreter.value.write(param='tex', file='tex.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4404 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='k_AB', spin_id=None, plot_data='value', file='k_AB.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4405 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='kex', spin_id=None, plot_data='value', file='kex.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4406 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='tex', spin_id=None, plot_data='value', file='tex.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4407 #self.interpreter.value.write(param='k_AB', file='k_AB.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4408 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='k_AB', spin_id=None, plot_data='value', file='k_AB.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4409 #self.interpreter.value.write(param='kB', file='kB.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4410 #self.interpreter.value.write(param='kC', file='kC.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4411 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='kB', spin_id=None, plot_data='value', file='kB.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4412 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='kC', spin_id=None, plot_data='value', file='kC.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4413 #self.interpreter.value.write(param='chi2', file='chi2.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4414 #self.interpreter.grace.write(x_data_type='res_num', y_data_type='chi2', spin_id=None, plot_data='value', file='chi2.agr', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', force=True, norm=False) 4415 4416 # Test of new parameters to write out. 4417 self.interpreter.value.write(param='theta', file='theta.out', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', scaling=1.0, comment=None, bc=False, force=True) 4418 #self.interpreter.value.write(param='theta', file='theta.out', dir='~', scaling=1.0, comment=None, bc=False, force=True) 4419 #self.assert_(hasattr(cdp.mol[0].res[7].spin[0], 'theta')) 4420 4421 ## Save results as state 4422 #self.interpreter.results.write(file='results', dir=ds.tmpdir+sep+'resultsR1'+sep+'final', compress_type=1, force=True) 4423 ## Save all results in all pipes in state 4424 #self.interpreter.state.save(state='final_state', dir=ds.tmpdir+sep+'resultsR1', compress_type=1, force=True) 4425 4426 # Assert the file existence of the written value files 4427 self.assert_(access(ds.tmpdir+sep+'resultsR1'+sep+'final'+sep+'phi_ex.out', F_OK)) 4428 self.assert_(access(ds.tmpdir+sep+'resultsR1'+sep+'final'+sep+'kex.out', F_OK))

4429 4430

4431 - def test_r2eff_read(self):

4432 """Test the operation of the relax_disp.r2eff_read user function.""" 4433 4434 # The path to the data files. 4435 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'800_MHz' 4436 4437 # Read the sequence data. 4438 self.interpreter.sequence.read(file='66.667.in', dir=data_path, res_num_col=1) 4439 4440 # The ID. 4441 id = 'test' 4442 4443 # Set up the metadata. 4444 self.interpreter.spectrometer.frequency(id=id, frq=800e6) 4445 self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 4446 4447 # Try reading the file. 4448 self.interpreter.relax_disp.r2eff_read(id=id, file='66.667.in', dir=data_path, disp_frq=66.667, res_num_col=1, data_col=2, error_col=3) 4449 4450 # Check the global data. 4451 data = [ 4452 ['cpmg_frqs', {'test': 66.667}], 4453 ['cpmg_frqs_list', [66.667]], 4454 ['dispersion_points', 1], 4455 ['exp_type', {'test': 'SQ CPMG'}], 4456 ['exp_type_list', ['SQ CPMG']], 4457 ['spectrometer_frq', {'test': 800000000.0}], 4458 ['spectrometer_frq_count', 1], 4459 ['spectrometer_frq_list', [800000000.0]], 4460 ['spectrum_ids', ['test']] 4461 ] 4462 for name, value in data: 4463 # Does it exist? 4464 self.assert_(hasattr(cdp, name)) 4465 4466 # Check the object. 4467 obj = getattr(cdp, name) 4468 self.assertEqual(obj, value) 4469 4470 # Check the spin data. 4471 data = [ 4472 [1, 2.3035747e+04, 8.5467725e+01], 4473 [2, 9.9629762e+04, 2.8322033e+02], 4474 [3, 9.5663137e+04, 2.8632929e+02], 4475 [4, 1.7089893e+05, 3.1089428e+02], 4476 [5, 4.7323876e+04, 1.0084269e+02], 4477 [6, 2.0199122e+04, 1.0135220e+02], 4478 [7, 1.6655488e+05, 3.1609061e+02], 4479 [8, 9.0061074e+04, 1.9176585e+02], 4480 [10, 8.4726204e+04, 2.8898155e+02], 4481 [11, 1.5050233e+05, 4.3138029e+02], 4482 [12, 9.2998531e+04, 3.0440191e+02], 4483 [13, 1.6343507e+05, 3.3144097e+02], 4484 [14, 1.0137301e+05, 3.7314642e+02], 4485 [15, 8.3407837e+04, 1.6546473e+02], 4486 [16, 1.3819126e+05, 3.3388517e+02], 4487 [17, 1.1010490e+05, 3.5639222e+02], 4488 [18, 9.4324035e+04, 3.2343585e+02], 4489 [19, 1.1135179e+05, 3.0706671e+02], 4490 [20, 7.6339410e+04, 1.7377460e+02], 4491 [21, 6.2008453e+04, 1.7327150e+02], 4492 [22, 1.0590404e+05, 2.4814635e+02], 4493 [23, 1.0630198e+05, 2.3601100e+02], 4494 [24, 7.2996320e+04, 1.4952465e+02], 4495 [25, 9.5486742e+04, 2.7080766e+02], 4496 [26, 5.8067989e+04, 1.6820462e+02], 4497 [27, -1.7168510e+04, 2.2519560e+02], 4498 [28, 1.6891473e+05, 2.3497525e+02], 4499 [29, 9.4038555e+04, 2.0357593e+02], 4500 [30, 2.1386951e+04, 2.2153532e+02], 4501 [31, 9.3982899e+04, 2.0937056e+02], 4502 [32, 8.6097484e+04, 2.3868467e+02], 4503 [33, 1.0194337e+05, 2.7370704e+02], 4504 [34, 8.5683111e+04, 2.0838076e+02], 4505 [35, 8.6985768e+04, 2.0889310e+02], 4506 [36, 8.6011237e+04, 1.7498390e+02], 4507 [37, 1.0984097e+05, 2.7622998e+02], 4508 [38, 8.7017879e+04, 2.6547994e+02], 4509 [39, 9.1682649e+04, 5.2777676e+02], 4510 [40, 7.6370440e+04, 1.9873214e+02], 4511 [41, 9.1393531e+04, 2.4483824e+02], 4512 [42, 1.1017111e+05, 2.8020699e+02], 4513 [43, 9.4552366e+04, 3.4394150e+02], 4514 [44, 1.2858281e+05, 6.8449252e+02], 4515 [45, 7.4583525e+04, 1.9544210e+02], 4516 [46, 9.2087490e+04, 2.0491066e+02], 4517 [47, 9.7507255e+04, 2.5162839e+02], 4518 [48, 1.0033842e+05, 2.7566430e+02], 4519 [49, 1.3048305e+05, 2.6797466e+02], 4520 [50, 1.0546796e+05, 1.9304384e+02], 4521 [51, 9.3099697e+04, 2.0773311e+02], 4522 [52, 4.6863758e+04, 1.3169068e+02], 4523 [53, 6.1055806e+04, 1.5448477e+02], 4524 [55, 6.8629994e+04, 1.6868673e+02], 4525 [56, 1.1005552e+05, 2.1940465e+02], 4526 [57, 1.0572760e+05, 1.9768486e+02], 4527 [58, 1.1176950e+05, 3.0009610e+02], 4528 [59, 9.8758603e+04, 3.3803895e+02], 4529 [60, 9.9517201e+04, 3.5137994e+02], 4530 [61, 5.4357946e+04, 2.5896579e+02], 4531 [62, 1.0899978e+05, 2.8720371e+02], 4532 [63, 8.4549759e+04, 4.1401837e+02], 4533 [64, 5.5014550e+04, 2.1135781e+02], 4534 [65, 8.0569666e+04, 2.3249709e+02], 4535 [66, 1.2936610e+05, 3.5218725e+02], 4536 [67, 3.6438010e+04, 8.7924003e+01], 4537 [70, 3.8763157e+04, 1.3325040e+02], 4538 [71, 8.5711411e+04, 2.9316183e+02], 4539 [72, 3.3211541e+04, 1.2182123e+02], 4540 [73, 3.2070576e+04, 1.2305430e+02] 4541 ] 4542 for res_num, value, error in data: 4543 # Get the spin. 4544 spin = return_spin(spin_id=":%s"%res_num) 4545 4546 # Check the values. 4547 self.assertEqual(spin.r2eff['sq_cpmg_800.00000000_0.000_66.667'], value) 4548 self.assertEqual(spin.r2eff_err['sq_cpmg_800.00000000_0.000_66.667'], error)

4549 4550

4551 - def test_r2eff_read_spin(self):

4552 """Test the operation of the relax_disp.r2eff_read_spin user function.""" 4553 4554 # The path to the data files. 4555 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 4556 4557 # Generate the sequence. 4558 self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 4559 self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 4560 self.interpreter.spin.isotope('1H', spin_id='@H') 4561 self.interpreter.spin.isotope('15N', spin_id='@N') 4562 4563 # Build the experiment IDs. 4564 H_disp_points = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 4565 N_disp_points = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 4566 ids = [] 4567 for value in H_disp_points: 4568 ids.append('1H_CPMG_%s' % value) 4569 for value in N_disp_points: 4570 ids.append('15N_CPMG_%s' % value) 4571 print("\n\nThe experiment IDs are %s." % ids) 4572 4573 # Set up the metadata for the experiments. 4574 for id in ids: 4575 self.interpreter.spectrometer.frequency(id=id, frq=500e6) 4576 self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 4577 for value in H_disp_points: 4578 self.interpreter.relax_disp.cpmg_setup(spectrum_id='1H_CPMG_%s' % value, cpmg_frq=value) 4579 for value in N_disp_points: 4580 self.interpreter.relax_disp.cpmg_setup(spectrum_id='15N_CPMG_%s' % value, cpmg_frq=value) 4581 4582 # Loop over the experiments. 4583 for id, file, spin_id in [['1H_CPMG', 'hs_500.res', ':9@H'], ['15N_CPMG', 'ns_500.res', ':9@N']]: 4584 # Try reading the file. 4585 self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 4586 4587 # Check the global data. 4588 data = [ 4589 ['cpmg_frqs', {'1H_CPMG_667.0': 667.0, '1H_CPMG_1067.0': 1067.0, '15N_CPMG_350.0': 350.0, '1H_CPMG_933.0': 933.0, '15N_CPMG_50.0': 50.0, '15N_CPMG_100.0': 100.0, '1H_CPMG_400.0': 400.0, '1H_CPMG_533.0': 533.0, '1H_CPMG_800.0': 800.0, '15N_CPMG_900.0': 900.0, '15N_CPMG_150.0': 150.0, '15N_CPMG_800.0': 800.0, '1H_CPMG_267.0': 267.0, '1H_CPMG_2667.0': 2667.0, '15N_CPMG_300.0': 300.0, '1H_CPMG_133.0': 133.0, '15N_CPMG_700.0': 700.0, '1H_CPMG_67.0': 67.0, '15N_CPMG_400.0': 400.0, '15N_CPMG_250.0': 250.0, '1H_CPMG_2133.0': 2133.0, '1H_CPMG_1600.0': 1600.0, '15N_CPMG_200.0': 200.0, '15N_CPMG_1000.0': 1000.0, '15N_CPMG_500.0': 500.0, '15N_CPMG_600.0': 600.0}], 4590 ['cpmg_frqs_list', [50.0, 67.0, 100.0, 133.0, 150.0, 200.0, 250.0, 267.0, 300.0, 350.0, 400.0, 500.0, 533.0, 600.0, 667.0, 700.0, 800.0, 900.0, 933.0, 1000.0, 1067.0, 1600.0, 2133.0, 2667.0]], 4591 ['dispersion_points', 24], 4592 ['exp_type', {'1H_CPMG_667.0': 'SQ CPMG', '1H_CPMG_1067.0': 'SQ CPMG', '15N_CPMG_350.0': 'SQ CPMG', '1H_CPMG_933.0': 'SQ CPMG', '15N_CPMG_50.0': 'SQ CPMG', '15N_CPMG_100.0': 'SQ CPMG', '1H_CPMG_400.0': 'SQ CPMG', '1H_CPMG_533.0': 'SQ CPMG', '1H_CPMG_800.0': 'SQ CPMG', '15N_CPMG_900.0': 'SQ CPMG', '15N_CPMG_150.0': 'SQ CPMG', '15N_CPMG_800.0': 'SQ CPMG', '1H_CPMG_267.0': 'SQ CPMG', '1H_CPMG_2667.0': 'SQ CPMG', '15N_CPMG_300.0': 'SQ CPMG', '1H_CPMG_133.0': 'SQ CPMG', '15N_CPMG_700.0': 'SQ CPMG', '1H_CPMG_67.0': 'SQ CPMG', '15N_CPMG_400.0': 'SQ CPMG', '15N_CPMG_250.0': 'SQ CPMG', '1H_CPMG_2133.0': 'SQ CPMG', '1H_CPMG_1600.0': 'SQ CPMG', '15N_CPMG_200.0': 'SQ CPMG', '15N_CPMG_1000.0': 'SQ CPMG', '15N_CPMG_500.0': 'SQ CPMG', '15N_CPMG_600.0': 'SQ CPMG'}], 4593 ['exp_type_list', ['SQ CPMG']], 4594 ['spectrometer_frq', {'1H_CPMG_667.0': 500000000.0, '1H_CPMG_1067.0': 500000000.0, '15N_CPMG_350.0': 500000000.0, '1H_CPMG_933.0': 500000000.0, '15N_CPMG_50.0': 500000000.0, '15N_CPMG_100.0': 500000000.0, '1H_CPMG_400.0': 500000000.0, '1H_CPMG_533.0': 500000000.0, '1H_CPMG_800.0': 500000000.0, '15N_CPMG_900.0': 500000000.0, '15N_CPMG_150.0': 500000000.0, '15N_CPMG_800.0': 500000000.0, '1H_CPMG_267.0': 500000000.0, '1H_CPMG_2667.0': 500000000.0, '15N_CPMG_300.0': 500000000.0, '1H_CPMG_133.0': 500000000.0, '15N_CPMG_700.0': 500000000.0, '1H_CPMG_67.0': 500000000.0, '15N_CPMG_400.0': 500000000.0, '15N_CPMG_250.0': 500000000.0, '1H_CPMG_2133.0': 500000000.0, '1H_CPMG_1600.0': 500000000.0, '15N_CPMG_200.0': 500000000.0, '15N_CPMG_1000.0': 500000000.0, '15N_CPMG_500.0': 500000000.0, '15N_CPMG_600.0': 500000000.0}], 4595 ['spectrometer_frq_count', 1], 4596 ['spectrometer_frq_list', [500000000.0]], 4597 ['spectrum_ids', ['1H_CPMG_67.0', '1H_CPMG_133.0', '1H_CPMG_267.0', '1H_CPMG_400.0', '1H_CPMG_533.0', '1H_CPMG_667.0', '1H_CPMG_800.0', '1H_CPMG_933.0', '1H_CPMG_1067.0', '1H_CPMG_1600.0', '1H_CPMG_2133.0', '1H_CPMG_2667.0', '15N_CPMG_50.0', '15N_CPMG_100.0', '15N_CPMG_150.0', '15N_CPMG_200.0', '15N_CPMG_250.0', '15N_CPMG_300.0', '15N_CPMG_350.0', '15N_CPMG_400.0', '15N_CPMG_500.0', '15N_CPMG_600.0', '15N_CPMG_700.0', '15N_CPMG_800.0', '15N_CPMG_900.0', '15N_CPMG_1000.0']] 4598 ] 4599 for name, value in data: 4600 # Does it exist? 4601 self.assert_(hasattr(cdp, name)) 4602 4603 # Check the object. 4604 obj = getattr(cdp, name) 4605 if not isinstance(data, dict): 4606 self.assertEqual(obj, value) 4607 4608 # Check the global dictionary data. 4609 else: 4610 for id in ids: 4611 self.assertEqual(obj[id], value[id]) 4612 4613 # Check the spin data. 4614 h_data = [ 4615 [ 67.0, 21.47924, 0.42958], 4616 [ 133.0, 16.73898, 0.33478], 4617 [ 267.0, 9.97357, 0.19947], 4618 [ 400.0, 8.23877, 0.24737], 4619 [ 533.0, 7.59290, 0.24263], 4620 [ 667.0, 7.45843, 0.24165], 4621 [ 800.0, 7.11222, 0.23915], 4622 [ 933.0, 7.40880, 0.24129], 4623 [1067.0, 6.55191, 0.16629], 4624 [1600.0, 6.72177, 0.23637], 4625 [2133.0, 7.09629, 0.23904], 4626 [2667.0, 7.14675, 0.23940] 4627 ] 4628 for disp_point, value, error in h_data: 4629 id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 4630 self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 4631 self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 4632 n_data = [ 4633 [ 50.0, 27.15767, 0.54315], 4634 [ 100.0, 26.55781, 0.53116], 4635 [ 150.0, 24.73462, 0.49469], 4636 [ 200.0, 20.98617, 0.41972], 4637 [ 250.0, 17.82442, 0.35649], 4638 [ 300.0, 15.55352, 0.31107], 4639 [ 350.0, 13.78958, 0.27579], 4640 [ 400.0, 12.48334, 0.24967], 4641 [ 500.0, 11.55724, 0.23114], 4642 [ 600.0, 10.53874, 0.21077], 4643 [ 700.0, 10.07395, 0.20148], 4644 [ 800.0, 9.62952, 0.19259], 4645 [ 900.0, 9.49994, 0.19000], 4646 [1000.0, 8.71350, 0.17427] 4647 ] 4648 for disp_point, value, error in n_data: 4649 id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 4650 self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff[id], value) 4651 self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff_err[id], error)

4652 4653

4654 - def test_r2eff_fit_fixed_time(self):

4655 """Test the relaxation dispersion 'R2eff' model for fixed time data in the auto-analysis.""" 4656 4657 # Execute the script. 4658 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r2eff_calc.py')

4659 4660

4661 - def test_read_r2eff(self):

4662 """Test the reading of a file containing r2eff values.""" 4663 4664 # Create the sequence data, and name the spins. 4665 self.interpreter.residue.create(1, 'Gly') 4666 self.interpreter.residue.create(2, 'Gly') 4667 self.interpreter.residue.create(3, 'Gly') 4668 4669 # Read the file. 4670 self.interpreter.relax_data.read(ri_id='R2eff.600', ri_type='R2eff', frq=600*1e6, file='r2eff.out', dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r2eff', res_num_col=1, res_name_col=2, data_col=3, error_col=4) 4671 4672 # Test the data. 4673 self.assertEqual(cdp.mol[0].res[0].spin[0].ri_data['R2eff.600'], 15.000) 4674 self.assertEqual(cdp.mol[0].res[1].spin[0].ri_data['R2eff.600'], 4.2003) 4675 self.assertEqual(cdp.mol[0].res[2].spin[0].ri_data['R2eff.600'], 7.2385)

4676 4677

4678 - def test_r20_from_min_r2eff_cpmg(self):

4679 """Test speeding up grid search. Support requst sr #3151 U{https://web.archive.org/web/https://gna.org/support/index.php?3151}. 4680 4681 User function to set the R20 parameters in the default grid search using the minimum R2eff value. 4682 4683 Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 4684 'SOD1-WT' CPMG data to the CR72 dispersion model. 4685 4686 This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 4687 Data is for experiment at 25 degree Celcius. 4688 """ 4689 4690 # Base data setup. 4691 pipe_name = 'base pipe' 4692 pipe_type = 'relax_disp' 4693 pipe_name_r2eff = "%s_R2eff"%(pipe_name) 4694 select_spin_index = list(range(0, 1)) 4695 self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 4696 4697 # Generate r20 key. 4698 r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 4699 r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 4700 4701 ## Now prepare for MODEL calculation. 4702 MODEL = "CR72" 4703 4704 # Change pipe. 4705 pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 4706 self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 4707 self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 4708 4709 # Then select model. 4710 self.interpreter.relax_disp.select_model(model=MODEL) 4711 4712 # Set the R20 parameters in the default grid search using the minimum R2eff value. 4713 self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 4714 4715 # Test result, for normal run. 4716 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 4717 # Get the spin_params. 4718 spin_params = spin.params 4719 4720 # Defined fixed values for testing. 4721 if spin_id == ":10@N": 4722 self.assertEqual(spin.r2[r20_key_600], 20.282732526087106) 4723 self.assertEqual(spin.r2[r20_key_500], 18.475299724356649) 4724 4725 # Print out. 4726 print("r2_600=%2.2f r2_500=%2.2f spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin_id, resi, resn)) 4727 4728 # Testing the r2 values for the different fields are not the same. 4729 self.assert_(spin.r2[r20_key_600] != spin.r2[r20_key_500]) 4730 4731 # Test values are larger than 0. 4732 self.assert_(spin.r2[r20_key_600] > 0.0) 4733 self.assert_(spin.r2[r20_key_500] > 0.0) 4734 4735 # Loop over the experiment settings. 4736 r2eff_600 = [] 4737 r2eff_500 = [] 4738 for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 4739 # Create the data key. 4740 data_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 4741 4742 # Extract the r2 eff data. 4743 r2eff = spin.r2eff[data_key] 4744 if frq == 599.8908617*1E6: 4745 r2eff_600.append(r2eff) 4746 elif frq == 499.862139*1E6: 4747 r2eff_500.append(r2eff) 4748 4749 # Sort values. 4750 r2eff_600.sort() 4751 r2eff_500.sort() 4752 4753 # Test values again. 4754 print("For r20 600MHz min r2eff=%3.3f."%(min(r2eff_600))) 4755 print(r2eff_600) 4756 self.assertEqual(spin.r2[r20_key_600], min(r2eff_600)) 4757 print("") 4758 4759 print("For r20 500MHz min r2eff=%3.3f."%(min(r2eff_500))) 4760 print(r2eff_500) 4761 self.assertEqual(spin.r2[r20_key_500], min(r2eff_500)) 4762 print("") 4763 4764 print("###########################################") 4765 print("Trying GRID SEARCH for minimum R2eff values") 4766 4767 ### Test just the Grid search. 4768 GRID_INC = 5 4769 4770 self.interpreter.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 4771 4772 ### Then test the value.set function. 4773 # Change pipe. 4774 pipe_name_MODEL = "%s_%s_2"%(pipe_name, MODEL) 4775 self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 4776 self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 4777 4778 # Then select model. 4779 self.interpreter.relax_disp.select_model(model=MODEL) 4780 4781 # Then set the standard parameter values. 4782 for param in spin_params: 4783 print("Setting standard parameter for param: %s"%param) 4784 self.interpreter.value.set(param=param, index=None) 4785 4786 # Test result, for normal run. 4787 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 4788 # Print out. 4789 print("r2_600=%2.2f r2_500=%2.2f pA=%2.2f, dw=%2.2f, kex=%2.2f, spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin.pA, spin.dw, spin.kex, spin_id, resi, resn)) 4790 4791 # Testing the r2 values. 4792 self.assertEqual(spin.r2[r20_key_600], 10.00) 4793 self.assertEqual(spin.r2[r20_key_500], 10.00) 4794 self.assertEqual(spin.pA, 0.9) 4795 self.assertEqual(spin.dw, 1.0) 4796 self.assertEqual(spin.kex, 1000.0) 4797 4798 print("###########################################") 4799 print("Trying GRID SEARCH for standard R2eff values") 4800 4801 ### Test just the Grid search. 4802 GRID_INC = 5 4803 4804 self.interpreter.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 4805 4806 ### Run auto_analysis. 4807 # The grid search size (the number of increments per dimension). 4808 GRID_INC = 5 4809 4810 # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 4811 MC_NUM = 3 4812 4813 # Model selection technique. 4814 MODSEL = 'AIC' 4815 4816 # Execute the auto-analysis (fast). 4817 # Standard parameters are: func_tol=1e-25, grad_tol=None, max_iter=10000000. 4818 OPT_FUNC_TOL = 1e-1 4819 relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 4820 OPT_MAX_ITERATIONS = 1000 4821 relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 4822 4823 # Run the analysis. 4824 relax_disp.Relax_disp(pipe_name=pipe_name_r2eff, results_dir=ds.tmpdir, models=[MODEL], grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, set_grid_r20=True)

4825 4826

4827 - def test_sod1wt_t25_bug_21954_order_error_analysis(self):

4828 """Error analysis of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 4829 4830 Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 4831 'SOD1-WT' CPMG data to the CR72 dispersion model. 4832 4833 This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 4834 Data is for experiment at 25 degree Celcius. 4835 4836 bug #21954 U{https://web.archive.org/web/https://gna.org/bugs/index.php?21954}: Order of spectrum.error_analysis is important. 4837 """ 4838 4839 # Base data setup. 4840 pipe_name = 'base pipe' 4841 pipe_type = 'relax_disp' 4842 pipe_name_r2eff = "%s_R2eff"%(pipe_name) 4843 select_spin_index = list(range(0, 1)) 4844 self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 4845 4846 # Define replicated 4847 repl_A = ['Z_A1', 'Z_A15'] 4848 repl_B = ['Z_B1', 'Z_B18'] 4849 4850 # Loop over spectrum ID, and sort them 4851 spectrum_ids_A = [] 4852 spectrum_ids_B = [] 4853 for spectrum_id in cdp.spectrum_ids: 4854 if "A" in spectrum_id: 4855 spectrum_ids_A.append(spectrum_id) 4856 elif "B" in spectrum_id: 4857 spectrum_ids_B.append(spectrum_id) 4858 4859 # To clean up old error analysis, delete attributes 4860 delattr(cdp, "var_I") 4861 delattr(cdp, "sigma_I") 4862 4863 # Perform error analysis 4864 self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 4865 self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 4866 4867 # Loop over spins, save errors to list 4868 Errors_A_B = [] 4869 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 4870 A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 4871 B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 4872 Errors_A_B.append([A_err, B_err]) 4873 4874 # To clean up old error analysis, delete attributes 4875 delattr(cdp, "var_I") 4876 delattr(cdp, "sigma_I") 4877 4878 # Perform error analysis. Order is important 4879 self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 4880 self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 4881 4882 # Loop over spins, save errors to list 4883 Errors_B_A = [] 4884 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 4885 A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 4886 B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 4887 Errors_B_A.append([A_err, B_err]) 4888 4889 # Make test for order of error 4890 for i in range(len(Errors_A_B)): 4891 Error_A_B = Errors_A_B[i] 4892 Error_B_A = Errors_B_A[i] 4893 self.assertAlmostEqual(Error_A_B[0], Error_B_A[0], 4) 4894 self.assertAlmostEqual(Error_A_B[1], Error_B_A[1], 4) 4895 4896 # Make further tests for fixed values 4897 std_A = math.sqrt((cdp.var_I[repl_A[0]] + cdp.var_I[repl_A[1]])/2) 4898 std_A_fix = 2785.7263335738567 4899 4900 for id_A in spectrum_ids_A: 4901 self.assertEqual(cdp.sigma_I[id_A], std_A) 4902 self.assertAlmostEqual(cdp.sigma_I[id_A], std_A_fix, 7) 4903 4904 std_B = math.sqrt((cdp.var_I[repl_B[0]] + cdp.var_I[repl_B[1]])/2) 4905 std_B_fix = 4967.3772030667988 4906 4907 for id_B in spectrum_ids_B: 4908 self.assertEqual(cdp.sigma_I[id_B], std_B) 4909 self.assertAlmostEqual(cdp.sigma_I[id_B], std_B_fix, 7)

4910 4911

4912 - def test_sod1wt_t25_to_cr72(self):

4913 """Optimisation of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 4914 4915 Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 4916 'SOD1-WT' CPMG data to the CR72 dispersion model. 4917 4918 This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 4919 Data is for experiment at 25 degree Celcius. 4920 """ 4921 4922 # Base data setup. 4923 pipe_name = 'base pipe' 4924 pipe_type = 'relax_disp' 4925 pipe_name_r2eff = "%s_R2eff"%(pipe_name) 4926 select_spin_index = list(range(0, 2)) 4927 self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 4928 4929 # Generate r20 key. 4930 r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 4931 r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 4932 4933 ## Now prepare for MODEL calculation. 4934 MODEL = "CR72" 4935 4936 # Change pipe. 4937 pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 4938 self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 4939 self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 4940 4941 # Then select model. 4942 self.interpreter.relax_disp.select_model(model=MODEL) 4943 4944 # GRID inc of 7 was found to be appropriate not to find pA=0.5. 4945 GRID_INC = 7 4946 4947 # Store grid and minimisations results. 4948 grid_results = [] 4949 mini_results = [] 4950 clust_results = [] 4951 4952 # Set the R20 parameters in the default grid search using the minimum R2eff value. 4953 self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 4954 4955 # Deselect insignificant spins. 4956 self.interpreter.relax_disp.insignificance(level=1.0) 4957 4958 # Perform Grid Search. 4959 self.interpreter.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 4960 4961 # Store result. 4962 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 4963 # Store grid results. 4964 grid_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 4965 4966 ## Now do minimisation. 4967 # Standard parameters are: func_tol=1e-25, grad_tol=None, max_iter=10000000, 4968 set_func_tol = 1e-9 4969 set_max_iter = 100000 4970 self.interpreter.minimise(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 4971 4972 # Store result. 4973 pA_values = [] 4974 kex_values = [] 4975 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 4976 # Store minimisation results. 4977 mini_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 4978 4979 # Store pA values. 4980 pA_values.append(spin.pA) 4981 4982 # Store kex values. 4983 kex_values.append(spin.kex) 4984 4985 print("\n# Now print before and after minimisation.\n") 4986 4987 # Print results. 4988 for i in range(len(grid_results)): 4989 # Get values. 4990 g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 4991 m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 4992 4993 print("GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 4994 print("MIN r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 4995 4996 ## Prepare for clustering 4997 # Change pipe. 4998 pipe_name_MODEL_CLUSTER = "%s_%s_Cluster"%(pipe_name, MODEL) 4999 self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL_CLUSTER) 5000 self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL_CLUSTER) 5001 5002 # Then select model. 5003 self.interpreter.relax_disp.select_model(model=MODEL) 5004 5005 # Define cluster id. 5006 cluster_id = 'clust' 5007 5008 # Loop over spins to cluster them. 5009 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 5010 self.interpreter.relax_disp.cluster(cluster_id, spin_id) 5011 5012 # Copy over values. 5013 self.interpreter.relax_disp.parameter_copy(pipe_from=pipe_name_MODEL, pipe_to=pipe_name_MODEL_CLUSTER) 5014 5015 # Test the median values is correct 5016 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 5017 print(pA_values) 5018 # The the median pA value returned. 5019 self.assertEqual(median(pA_values), spin.pA) 5020 5021 # The the median kex value returned. 5022 self.assertEqual(median(kex_values), spin.kex) 5023 5024 ## Now do minimisation. 5025 self.interpreter.minimise(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 5026 5027 # Store result. 5028 for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 5029 # Store clust results. 5030 clust_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 5031 5032 # Store the outcome of the clustering minimisation. 5033 clust_pA = spin.pA 5034 clust_kex = spin.kex 5035 5036 print("\n# Now testing.\n") 5037 5038 # Define results 5039 test_res = {} 5040 test_res[':10@N'] = {} 5041 test_res[':10@N']['r2600'] = 18.429755324773360 5042 test_res[':10@N']['r2500'] = 16.981349161968630 5043 test_res[':10@N']['dw'] = 2.700755859433969 5044 test_res[':10@N']['pA'] = 0.971531659288657 5045 test_res[':10@N']['kex'] = 3831.766337047963134 5046 test_res[':11@N'] = {} 5047 test_res[':11@N']['r2600'] = 18.193409421115213 5048 test_res[':11@N']['r2500'] = 17.308838135567765 5049 test_res[':11@N']['dw'] = 2.706650302761793 5050 test_res[':11@N']['pA'] = 0.971531659288657 5051 test_res[':11@N']['kex'] = 3831.766337047963134 5052 5053 # Then make tests. 5054 for i in range(len(grid_results)): 5055 # Get values. 5056 g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 5057 m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 5058 c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn = clust_results[i] 5059 5060 print("%s GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 5061 print("%s MIN r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 5062 print("%s Clust r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn)) 5063 5064 # Make tests. 5065 self.assertEqual(clust_pA, c_pA) 5066 self.assertEqual(clust_kex, c_kex) 5067 5068 # Test values. 5069 if c_spin_id in test_res: 5070 self.assertAlmostEqual(c_r2_600, test_res[c_spin_id]['r2600'], 4) 5071 self.assertAlmostEqual(c_r2_500, test_res[c_spin_id]['r2500'], 4) 5072 self.assertAlmostEqual(c_dw, test_res[c_spin_id]['dw'], 3) 5073 self.assertAlmostEqual(c_pA, test_res[c_spin_id]['pA'], 5) 5074 self.assertAlmostEqual(c_kex, test_res[c_spin_id]['kex'], 1)

5075 5076 # Save disp graph to temp. 5077 #self.interpreter.relax_disp.plot_disp_curves(dir="~"+sep+"test", num_points=1000, extend=500.0, force=True). 5078 5079

5080 - def test_sod1wt_t25_to_sherekhan_input(self):

5081 """Conversion of SOD1-WT CPMG R2eff values into input files for sherekhan. 5082 5083 Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 5084 'SOD1-WT' CPMG data to the CR72 dispersion model. 5085 5086 This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 5087 Data is for experiment at 25 degree Celcius. 5088 """ 5089 5090 # Base data setup. 5091 pipe_name = 'base pipe' 5092 pipe_type = 'relax_disp' 5093 pipe_name_r2eff = "%s_R2eff"%(pipe_name) 5094 select_spin_index = list(range(0, 2)) 5095 self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 5096 5097 # Generate r20 key. 5098 r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 5099 r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 5100 5101 # Cluster everything, to analyse together. 5102 self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-1000") 5103 5104 # Write input 5105 self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=ds.tmpdir) 5106 5107 # Check the r2eff set files. 5108 print("\nChecking the R2eff input set files.") 5109 files = [[ds.tmpdir + sep + 'cluster1', 'sherekhan_frq1.in'], [ ds.tmpdir + sep + 'cluster1', 'sherekhan_frq2.in']] 5110 5111 # First check file exists 5112 for dir, file in files: 5113 print(dir+sep+file) 5114 self.assert_(access(dir+sep+file, F_OK)) 5115 5116 # Define how files should look like 5117 data_set_600 = [ 5118 "60.8272464287\n", 5119 "0.06\n", 5120 "# nu_cpmg (Hz) R2eff (rad/s) Error \n", 5121 "# G10\n", 5122 " 33.333 26.53556078711 0.5236104771163\n", 5123 " 66.667 25.29735243318 0.48766574122\n", 5124 " 100 25.09470361403 0.4820438864671\n", 5125 " 133.333 25.15603274331 0.4837377286085\n", 5126 " 166.667 24.27213341753 0.4599457904395\n", 5127 " 200 24.00364120328 0.4529773198905\n", 5128 " 266.667 24.03511395168 0.4537880662536\n", 5129 " 300 23.04761040024 0.4291039120557\n", 5130 " 333.333 22.95530300787 0.4268745963972\n", 5131 " 400 23.06158810662 0.4294426293624\n", 5132 " 466.667 22.26799054092 0.4106809618644\n", 5133 " 533.333 21.99851418823 0.4045232104735\n", 5134 " 666.667 21.19651570955 0.3868136173831\n", 5135 " 833.333 20.30938498379 0.3682604887899\n", 5136 " 1000 20.28273252609 0.367719392568\n", 5137 "# D11\n", 5138 " 33.333 24.76520269878 0.5026475808706\n", 5139 " 66.667 24.8773107448 0.5058752916906\n", 5140 " 100 24.90357815239 0.5066348551479\n", 5141 " 133.333 23.7782506151 0.4751950583865\n", 5142 " 166.667 23.68548762076 0.4727017128631\n", 5143 " 200 23.58629651618 0.4700517377679\n", 5144 " 266.667 23.47734671187 0.4671601744044\n", 5145 " 300 24.08647493772 0.4835855560598\n", 5146 " 333.333 22.98314371029 0.4542918950801\n", 5147 " 400 22.80339361568 0.4497107885587\n", 5148 " 466.667 22.91634335366 0.4525833037874\n", 5149 " 533.333 22.59774140046 0.4445334311324\n", 5150 " 666.667 20.9177750759 0.4046955726046\n", 5151 " 833.333 20.71792550566 0.4002363835007\n", 5152 " 1000 19.54080006349 0.3751112751853\n", 5153 ] 5154 5155 # Check data_set_600 5156 file = open(files[0][0]+sep+files[0][1]) 5157 lines = file.readlines() 5158 file.close() 5159 self.assertEqual(len(data_set_600), len(lines)) 5160 for i in range(len(data_set_600)): 5161 # Make the string test 5162 self.assertEqual(data_set_600[i], lines[i]) 5163 5164 # Define how files should look like 5165 data_set_500 = [ 5166 "50.6846152368\n", 5167 "0.04\n", 5168 "# nu_cpmg (Hz) R2eff (rad/s) Error \n", 5169 "# G10\n", 5170 " 50 22.28084307393 0.2944966344183\n", 5171 " 100 21.93494977761 0.2910362768307\n", 5172 " 150 21.09850032232 0.282892238351\n", 5173 " 200 20.86493960397 0.2806737853646\n", 5174 " 250 20.75287269752 0.2796178205016\n", 5175 " 300 20.25597152406 0.2750013546989\n", 5176 " 350 19.92172163467 0.2719555756504\n", 5177 " 400 19.97712052922 0.272457105051\n", 5178 " 450 19.46807010415 0.2678972122793\n", 5179 " 500 19.76875460947 0.2705774849203\n", 5180 " 550 19.39161367402 0.2672216964327\n", 5181 " 600 19.03949517697 0.2641417899694\n", 5182 " 650 19.12218812132 0.2648605059901\n", 5183 " 700 19.01037461457 0.2638893584683\n", 5184 " 800 18.83395162904 0.2623674321143\n", 5185 " 900 18.47529972436 0.2593123604687\n", 5186 " 1000 18.5252023121 0.2597343394038\n", 5187 "# D11\n", 5188 " 50 22.15403890237 0.3285588379827\n", 5189 " 100 21.80946781746 0.3247185598713\n", 5190 " 150 21.77715415505 0.324361526682\n", 5191 " 200 21.41647464235 0.3204122024881\n", 5192 " 250 21.17099940822 0.3177616325958\n", 5193 " 300 21.03740030577 0.3163316496664\n", 5194 " 350 20.95393648281 0.3154427665172\n", 5195 " 400 20.93311399332 0.315221543436\n", 5196 " 450 20.18219905222 0.3073848655291\n", 5197 " 500 19.93599065085 0.3048744697057\n", 5198 " 550 19.68475725452 0.3023424499113\n", 5199 " 600 19.33575433934 0.2988741928798\n", 5200 " 650 19.53915692194 0.3008886196853\n", 5201 " 700 19.2018754351 0.2975587767134\n", 5202 " 800 18.82360965368 0.2938866923878\n", 5203 " 900 18.71861761238 0.2928790380131\n", 5204 " 1000 17.95878049287 0.2857341721151\n", 5205 ] 5206 5207 # Check data_set_500 5208 file = open(files[1][0]+sep+files[1][1]) 5209 lines = file.readlines() 5210 file.close() 5211 self.assertEqual(len(data_set_500), len(lines)) 5212 for i in range(len(data_set_500)): 5213 # Make the string test 5214 self.assertEqual(data_set_500[i], lines[i]) 5215 5216 # Test local dir tests. This will be turned off in system test. 5217 turn_on_local_dir_test = False 5218 5219 if turn_on_local_dir_test: 5220 ## Now check to local folder with None argument. 5221 # Write input 5222 self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None) 5223 5224 # Check the r2eff set files. 5225 print("\nChecking the R2eff input set files.") 5226 files = [[path.join(getcwd(), 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), 'cluster1'), 'sherekhan_frq2.in']] 5227 5228 # First check file exists 5229 for dir, file in files: 5230 print(dir+sep+file) 5231 self.assert_(access(dir+sep+file, F_OK)) 5232 5233 ## Now check to local folder with dir argument. 5234 # Write input 5235 set_dir = "Test_ShereKhan" 5236 self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=set_dir) 5237 5238 # Check the r2eff set files. 5239 print("\nChecking the R2eff input set files.") 5240 files = [[path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq2.in']] 5241 5242 # First check file exists 5243 for dir, file in files: 5244 print(dir+sep+file) 5245 self.assert_(access(dir+sep+file, F_OK))

5246 5247

5248 - def test_sprangers_data_to_mmq_cr72(self, model=None):

5249 """Test the 'MMQ CR72' model fitting against Remco Sprangers' ClpP data. 5250 5251 This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102. This is MMQ CPMG data with a fixed relaxation time period. 5252 """ 5253 5254 # Reset. 5255 self.interpreter.reset() 5256 5257 # Create the data pipe and load the base data. 5258 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 5259 self.interpreter.state.load(data_path+sep+'r2eff_values') 5260 5261 # The model data pipe. 5262 model = 'MMQ CR72' 5263 pipe_name = "%s - relax_disp" % model 5264 self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 5265 self.interpreter.pipe.switch(pipe_name=pipe_name) 5266 5267 # Set the model. 5268 self.interpreter.relax_disp.select_model(model=model) 5269 5270 # Cluster everything. 5271 self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 5272 5273 # Copy the data. 5274 self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 5275 5276 # Alias the spins. 5277 spin135S = cdp.mol[0].res[0].spin[0] 5278 spin135F = cdp.mol[0].res[0].spin[1] 5279 spin137S = cdp.mol[0].res[1].spin[0] 5280 spin137F = cdp.mol[0].res[1].spin[1] 5281 5282 # The R20 keys. 5283 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 5284 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 5285 5286 # Set the cluster specific parameters (only for the first spin). 5287 spin135S.pA = 0.836591763632 5288 spin135S.kex = 241.806525261 5289 5290 # Set the initial parameter values. 5291 spin135S.r2 = {r20_key1: 28.2493431552, r20_key2: 31.7517334715} 5292 spin135S.dw = 0.583003118785 5293 spin135S.dwH = 0.0361441944301 5294 5295 spin135F.r2 = {r20_key1: 42.7201839991, r20_key2: 57.3178617389} 5296 spin135F.dw = 0.805849745104 5297 spin135F.dwH = 0.0215791945715 5298 5299 spin137S.r2 = {r20_key1: 26.0134115256, r20_key2: 30.575806934} 5300 spin137S.dw = 0.688107568372 5301 spin137S.dwH = 0.0344463604043 5302 5303 spin137F.r2 = {r20_key1: 46.6969397337, r20_key2: 58.602384101} 5304 spin137F.dw = 0.94978299907 5305 spin137F.dwH = 1.4818877939e-07 5306 5307 # Low precision optimisation. 5308 self.interpreter.minimise(min_algor='simplex', func_tol=1e-10, max_iter=1000) 5309 5310 # Printout. 5311 print("\n\nOptimised parameters:\n") 5312 print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 5313 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 5314 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 5315 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 5316 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 5317 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 5318 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 5319 print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 5320 print("\n # Set the cluster specific parameters (only for the first spin).") 5321 print(" spin135S.pA = %s" % spin135S.pA) 5322 print(" spin135S.kex = %s" % spin135S.kex) 5323 print("\n # Set the initial parameter values.") 5324 print(" spin135S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135S.r2[r20_key1], spin135S.r2[r20_key2])) 5325 print(" spin135S.dw = %s" % spin135S.dw) 5326 print(" spin135S.dwH = %s" % spin135S.dwH) 5327 print("\n spin135F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135F.r2[r20_key1], spin135F.r2[r20_key2])) 5328 print(" spin135F.dw = %s" % spin135F.dw) 5329 print(" spin135F.dwH = %s" % spin135F.dwH) 5330 print("\n spin137S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137S.r2[r20_key1], spin137S.r2[r20_key2])) 5331 print(" spin137S.dw = %s" % spin137S.dw) 5332 print(" spin137S.dwH = %s" % spin137S.dwH) 5333 print("\n spin137F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137F.r2[r20_key1], spin137F.r2[r20_key2])) 5334 print(" spin137F.dw = %s" % spin137F.dw) 5335 print(" spin137F.dwH = %s" % spin137F.dwH) 5336 5337 # Checks for residue :135S. 5338 self.assertAlmostEqual(spin135S.r2[r20_key1], 28.2493445347425, 4) 5339 self.assertAlmostEqual(spin135S.r2[r20_key2], 31.7517352342937, 4) 5340 self.assertAlmostEqual(spin135S.pA, 0.836591714049569, 4) 5341 self.assertAlmostEqual(spin135S.dw, 0.583003004605869, 4) 5342 self.assertAlmostEqual(spin135S.dwH, 0.0361441894065963, 4) 5343 self.assertAlmostEqual(spin135S.kex/100, 241.806464344233/100, 4) 5344 self.assertAlmostEqual(spin135S.chi2, 12.4224060116473, 4) 5345 5346 # Checks for residue :135F. 5347 self.assertAlmostEqual(spin135F.r2[r20_key1], 42.7201844426839, 4) 5348 self.assertAlmostEqual(spin135F.r2[r20_key2], 57.3178718548898, 4) 5349 self.assertAlmostEqual(spin135F.pA, 0.836591714049569, 4) 5350 self.assertAlmostEqual(spin135F.dw, 0.805849748711916, 4) 5351 self.assertAlmostEqual(spin135F.dwH, 0.0215791669142752, 4) 5352 self.assertAlmostEqual(spin135F.kex/100, 241.806464344233/100, 4) 5353 self.assertAlmostEqual(spin135F.chi2, 12.4224060116473, 4) 5354 5355 # Checks for residue :137S. 5356 self.assertAlmostEqual(spin137S.r2[r20_key1], 26.013412509919, 4) 5357 self.assertAlmostEqual(spin137S.r2[r20_key2], 30.5758092335097, 4) 5358 self.assertAlmostEqual(spin137S.pA, 0.836591714049569, 4) 5359 self.assertAlmostEqual(spin137S.dw, 0.688107406812537, 4) 5360 self.assertAlmostEqual(spin137S.dwH, 0.034446357344577, 4) 5361 self.assertAlmostEqual(spin137S.kex/100, 241.806464344233/100, 4) 5362 self.assertAlmostEqual(spin137S.chi2, 12.4224060116473, 4) 5363 5364 # Checks for residue :137F. 5365 self.assertAlmostEqual(spin137F.r2[r20_key1], 46.696935090697, 4) 5366 self.assertAlmostEqual(spin137F.r2[r20_key2], 58.6023842513446, 4) 5367 self.assertAlmostEqual(spin137F.pA, 0.836591714049569, 4) 5368 self.assertAlmostEqual(spin137F.dw, 0.94978325541294, 4) 5369 self.assertAlmostEqual(spin137F.dwH, 1.5189362257653e-07, 4) 5370 self.assertAlmostEqual(spin137F.kex/100, 241.806464344233/100, 4) 5371 self.assertAlmostEqual(spin137F.chi2, 12.4224060116473, 4)

5372 5373

5374 - def test_sprangers_data_to_ns_mmq_2site(self, model=None):

5375 """Test the 'NS MMQ 2-site' model fitting against Remco Sprangers' ClpP data. 5376 5377 This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102. This is MQ CPMG data with a fixed relaxation time period. 5378 """ 5379 5380 # Reset. 5381 self.interpreter.reset() 5382 5383 # Create the data pipe and load the base data. 5384 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 5385 self.interpreter.state.load(data_path+sep+'r2eff_values') 5386 5387 # The model data pipe. 5388 model = 'NS MMQ 2-site' 5389 pipe_name = "%s - relax_disp" % model 5390 self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 5391 self.interpreter.pipe.switch(pipe_name=pipe_name) 5392 5393 # Set the model. 5394 self.interpreter.relax_disp.select_model(model=model) 5395 5396 # Cluster everything. 5397 self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 5398 5399 # Copy the data. 5400 self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 5401 5402 # Alias the spins. 5403 spin135S = cdp.mol[0].res[0].spin[0] 5404 spin135F = cdp.mol[0].res[0].spin[1] 5405 spin137S = cdp.mol[0].res[1].spin[0] 5406 spin137F = cdp.mol[0].res[1].spin[1] 5407 5408 # The R20 keys. 5409 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 5410 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 5411 5412 # Set the cluster specific parameters (only for the first spin). 5413 spin135S.pA = 0.847378444499757 5414 spin135S.kex = 264.055604934724329 5415 5416 # Set the initial parameter values. 5417 spin135S.r2 = {r20_key1: 30.315119723745390, r20_key2: 37.411874745645299} 5418 spin135S.dw = 0.585574008745351 5419 spin135S.dwH = 0.000000000000002 5420 5421 spin135F.r2 = {r20_key1: 41.440843383778287, r20_key2: 56.989726795397893} 5422 spin135F.dw = 0.856699277665748 5423 spin135F.dwH = 0.000000000582587 5424 5425 spin137S.r2 = {r20_key1: 23.051695938570266, r20_key2: 28.352806483953824} 5426 spin137S.dw = 0.772904450844973 5427 spin137S.dwH = 0.183351478512970 5428 5429 spin137F.r2 = {r20_key1: 44.702032074210429, r20_key2: 56.453146052685319} 5430 spin137F.dw = 0.984568590342831 5431 spin137F.dwH = 0.000000001993458 5432 5433 # Low precision optimisation. 5434 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-5, grad_tol=None, max_iter=100, constraints=True, scaling=True, verbosity=1) 5435 5436 # Printout. 5437 print("\n\nOptimised parameters:\n") 5438 print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 5439 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 5440 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 5441 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 5442 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 5443 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 5444 print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 5445 print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 5446 5447 # FIXME: Remove this temporary return and properly check the results. 5448 return 5449 5450 # Checks for residue :135S. 5451 self.assertAlmostEqual(spin135S.r2[r20_key1], 30.3151197237454, 4) 5452 self.assertAlmostEqual(spin135S.r2[r20_key2], 37.4118747456453, 4) 5453 self.assertAlmostEqual(spin135S.pA, 0.847378444499757, 4) 5454 self.assertAlmostEqual(spin135S.dw, 0.585574008745351, 4) 5455 self.assertAlmostEqual(spin135S.dwH, 2e-15, 4) 5456 self.assertAlmostEqual(spin135S.kex, 264.055604934724, 4) 5457 self.assertAlmostEqual(spin135S.chi2, 13.859423588071, 1) 5458 5459 # Checks for residue :135F. 5460 self.assertAlmostEqual(spin135F.r2[r20_key1], 41.4408433837783, 4) 5461 self.assertAlmostEqual(spin135F.r2[r20_key2], 56.9897267953979, 4) 5462 self.assertAlmostEqual(spin135F.pA, 0.847378444499757, 4) 5463 self.assertAlmostEqual(spin135F.dw, 0.856699277665748, 4) 5464 self.assertAlmostEqual(spin135F.dwH, 5.82587e-10, 4) 5465 self.assertAlmostEqual(spin135F.kex, 264.055604934724, 4) 5466 self.assertAlmostEqual(spin135F.chi2, 13.859423588071, 1) 5467 5468 # Checks for residue :137S. 5469 self.assertAlmostEqual(spin137S.r2[r20_key1], 23.0516959385703, 4) 5470 self.assertAlmostEqual(spin137S.r2[r20_key2], 28.3528064839538, 4) 5471 self.assertAlmostEqual(spin137S.pA, 0.847378444499757, 4) 5472 self.assertAlmostEqual(spin137S.dw, 0.772904450844973, 4) 5473 self.assertAlmostEqual(spin137S.dwH, 0.18335147851297, 4) 5474 self.assertAlmostEqual(spin137S.kex, 264.055604934724, 4) 5475 self.assertAlmostEqual(spin137S.chi2, 13.859423588071, 1) 5476 5477 # Checks for residue :137F. 5478 self.assertAlmostEqual(spin137F.r2[r20_key1], 44.7020320742104, 4) 5479 self.assertAlmostEqual(spin137F.r2[r20_key2], 56.4531460526853, 4) 5480 self.assertAlmostEqual(spin137F.pA, 0.847378444499757, 4) 5481 self.assertAlmostEqual(spin137F.dw, 0.984568590342831, 4) 5482 self.assertAlmostEqual(spin137F.dwH, 2.0931309e-09, 4) 5483 self.assertAlmostEqual(spin137F.kex, 264.055604934724, 4) 5484 self.assertAlmostEqual(spin137F.chi2, 13.859423588071, 1)

5485 5486

5487 - def test_tp02_data_to_ns_r1rho_2site(self, model=None):

5488 """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 5489 5490 # Reset. 5491 self.interpreter.reset() 5492 5493 # Create the data pipe and load the base data. 5494 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 5495 self.interpreter.state.load(data_path+sep+'r2eff_values') 5496 5497 # The model data pipe. 5498 model = 'NS R1rho 2-site' 5499 pipe_name = "%s - relax_disp" % model 5500 self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 5501 self.interpreter.pipe.switch(pipe_name=pipe_name) 5502 5503 # Set the model. 5504 self.interpreter.relax_disp.select_model(model=model) 5505 5506 # Copy the data. 5507 self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 5508 5509 # Alias the spins. 5510 spin1 = cdp.mol[0].res[0].spin[0] 5511 spin2 = cdp.mol[0].res[1].spin[0] 5512 5513 # The R20 keys. 5514 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 5515 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 5516 5517 # Set the initial parameter values. 5518 spin1.r2 = {r20_key1: 9.9963793866185, r20_key2: 15.0056724422684} 5519 spin1.pA = 0.779782428085762 5520 spin1.dw = 7.57855284496424 5521 spin1.kex = 1116.7911285203 5522 spin2.r2 = {r20_key1: 11.9983346935434, r20_key2: 18.0076097513337} 5523 spin2.pA = 0.826666229688602 5524 spin2.dw = 9.5732624231366 5525 spin2.kex = 1380.46162655657 5526 5527 # Low precision optimisation. 5528 self.interpreter.minimise(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 5529 5530 # Printout. 5531 print("\n\nOptimised parameters:\n") 5532 print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 5533 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 5534 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 5535 print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 5536 print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 5537 print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 5538 print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 5539 5540 # Checks for residue :1. 5541 self.assertAlmostEqual(spin1.r2[r20_key1], 8.50207717367548, 4) 5542 self.assertAlmostEqual(spin1.r2[r20_key2], 13.4680429589972, 4) 5543 self.assertAlmostEqual(spin1.pA, 0.864523128842393, 4) 5544 self.assertAlmostEqual(spin1.dw, 8.85204828994151, 4) 5545 self.assertAlmostEqual(spin1.kex/1000, 1199.56359549637/1000, 4) 5546 self.assertAlmostEqual(spin1.chi2, 2.99182130153514, 4) 5547 5548 # Checks for residue :2. 5549 self.assertAlmostEqual(spin2.r2[r20_key1], 10.2099357790203, 4) 5550 self.assertAlmostEqual(spin2.r2[r20_key2], 16.2137648697873, 4) 5551 self.assertAlmostEqual(spin2.pA, 0.836488681031685, 4) 5552 self.assertAlmostEqual(spin2.dw, 9.5505714779503, 4) 5553 self.assertAlmostEqual(spin2.kex/1000, 1454.45726998929/1000, 4) 5554 self.assertAlmostEqual(spin2.chi2, 0.000402231563481261, 4)

5555 5556

5557 - def test_tp02_data_to_mp05(self):

5558 """Test the dispersion 'MP05' model fitting against the 'TP02' test data.""" 5559 5560 # Fixed time variable and the models. 5561 ds.fixed = True 5562 ds.models = ['R2eff', 'MP05'] 5563 5564 # Execute the script. 5565 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 5566 5567 # Switch back to the data pipe for the optimisation. 5568 self.interpreter.pipe.switch('MP05 - relax_disp') 5569 5570 # The equivalent MP05 parameters. 5571 r1rho_prime = [[10.0058086343329, 15.005806870124], [12.0766320470785, 18.0767503536277]] 5572 pA = [0.775055484521586, 0.500000000036595] 5573 kex = [1235.20361276079, 2378.31403454691] 5574 delta_omega = [7.08194146569694, 5.4083562844306] 5575 chi2 = [0.0370400968727768, 0.182141732163934] 5576 5577 # Alias the spins. 5578 spin1 = cdp.mol[0].res[0].spin[0] 5579 spin2 = cdp.mol[0].res[1].spin[0] 5580 5581 # The R20 keys. 5582 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 5583 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 5584 5585 # Printout. 5586 print("\n\nOptimised parameters:\n") 5587 print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 5588 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 5589 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 5590 print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 5591 print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 5592 print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 5593 print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 5594 5595 # Check each spin. 5596 spin_index = 0 5597 for spin, spin_id in spin_loop(return_id=True): 5598 # Printout. 5599 print("\nSpin %s." % spin_id) 5600 5601 # Check the fitted parameters. 5602 self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 5603 self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 5604 self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 5605 self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 5606 self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 5607 self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 5608 5609 # Increment the spin index. 5610 spin_index += 1

5611 5612

5613 - def test_tp02_data_to_tap03(self):

5614 """Test the dispersion 'TAP03' model fitting against the 'TP02' test data.""" 5615 5616 # Fixed time variable and the models. 5617 ds.fixed = True 5618 ds.models = ['R2eff', 'TAP03'] 5619 5620 # Execute the script. 5621 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 5622 5623 # Switch back to the data pipe for the optimisation. 5624 self.interpreter.pipe.switch('TAP03 - relax_disp') 5625 5626 # The equivalent TAP03 parameters. 5627 r1rho_prime = [[10.0058156589442, 15.005818505006], [12.0766046472748, 18.076648462452]] 5628 pA = [0.775042569092891, 0.500000000229685] 5629 kex = [1235.20852748765, 2379.47085580169] 5630 delta_omega = [7.08176806468445, 5.40708372863538] 5631 chi2 = [0.0371366837083293, 0.182212857256044] 5632 5633 # Alias the spins. 5634 spin1 = cdp.mol[0].res[0].spin[0] 5635 spin2 = cdp.mol[0].res[1].spin[0] 5636 5637 # The R20 keys. 5638 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 5639 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 5640 5641 # Printout. 5642 print("\n\nOptimised parameters:\n") 5643 print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 5644 print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 5645 print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 5646 print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 5647 print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 5648 print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 5649 print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 5650 5651 # Switch to the 'MP05' model data pipe, then check for each spin. 5652 self.interpreter.pipe.switch('TAP03 - relax_disp') 5653 spin_index = 0 5654 for spin, spin_id in spin_loop(return_id=True): 5655 # Printout. 5656 print("\nSpin %s." % spin_id) 5657 5658 # Check the fitted parameters. 5659 self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 5660 self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 5661 self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 5662 self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 5663 self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 5664 self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 5665 5666 # Increment the spin index. 5667 spin_index += 1

5668 5669

5670 - def test_tp02_data_to_tp02(self):

5671 """Test the relaxation dispersion 'TP02' model curve fitting to fixed time synthetic data.""" 5672 5673 # Fixed time variable. 5674 ds.fixed = True 5675 5676 # Execute the script. 5677 self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 5678 5679 # The original parameters. 5680 r1rho_prime = [[10.0, 15.0], [12.0, 18.0]] 5681 pA = 0.7654321 5682 kex = 1234.56789 5683 delta_omega = [7.0, 9.0] 5684 5685 # The R20 keys. 5686 r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 5687 r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 5688 5689 # Switch to the 'TP02' model data pipe, then check for each spin. 5690 self.interpreter.pipe.switch('TP02 - relax_disp') 5691 spin_index = 0 5692 for spin, spin_id in spin_loop(return_id=True): 5693 # Printout. 5694 print("\nSpin %s." % spin_id) 5695 5696 # Check the fitted parameters. 5697 self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 5698 self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 5699 self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 5700 self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 3) 5701 5702 # Increment the spin index. 5703 spin_index += 1

5704 5705

5706 - def test_value_write_calc_rotating_frame_params_int(self):

5707 """System test of the value.write function to write intensities for an R1rho setup. 5708 This system test is to make sure, that modifying the API for special parameters theta and w_eff does not alter the functionality value.write. 5709 5710 This uses the data of the saved state attached to U{bug #21344<https://web.archive.org/web/https://gna.org/bugs/?21344>}. 5711 """ 5712 5713 # Load the state. 5714 statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 5715 self.interpreter.state.load(statefile, force=True) 5716 5717 # Set filepaths. 5718 int_filepath = ds.tmpdir+sep+'int.out' 5719 5720 # Write out the intensity parameter file. 5721 # The writing out of intensity file is to make sure the API function retains its function after modification for special parameters. 5722 self.interpreter.value.write(param='peak_intensity', file='int.out', dir=ds.tmpdir, scaling=1.0, force=True) 5723 5724 # Test the file exists. 5725 self.assert_(access(int_filepath, F_OK)) 5726 5727 # Open the files for testing. 5728 int_file = open(int_filepath, 'r') 5729 5730 # Loop over the intensity file to test values. 5731 for line in int_file: 5732 # Skip lines starting with #. 5733 if line[0] == "#": 5734 continue 5735 5736 # Split the line 5737 linesplit = line.split() 5738 5739 # Assume values 5740 if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 5741 self.assertEqual(linesplit[5], "115571.4") 5742 elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 5743 self.assertEqual(linesplit[5], "68377.52") 5744 elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 5745 self.assertEqual(linesplit[5], "9141.689") 5746 elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 5747 self.assertEqual(linesplit[5], "29123.77") 5748 elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 5749 self.assertEqual(linesplit[5], "58914.94") 5750 5751 # Close files 5752 int_file.close()

5753 5754

5755 - def test_value_write_calc_rotating_frame_params_theta(self):

5756 """System test of the value.write function to write return values of theta from calc_rotating_frame_params() function for an R1rho setup. 5757 5758 This uses the data of the saved state attached to U{bug #21344<https://web.archive.org/web/https://gna.org/bugs/?21344>}. 5759 """ 5760 5761 # Load the state. 5762 statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 5763 self.interpreter.state.load(statefile, force=True) 5764 5765 # Set filepaths. 5766 theta_filepath = ds.tmpdir+sep+'theta.out' 5767 5768 # Write out the theta parameter file. 5769 self.interpreter.value.write(param='theta', file='theta.out', dir=ds.tmpdir, scaling=1.0, force=True) 5770 5771 # Test the file exists. 5772 self.assert_(access(theta_filepath, F_OK)) 5773 5774 # Open the files for testing. 5775 theta_file = open(theta_filepath, 'r') 5776 5777 # Loop over the theta file to test values. 5778 for line in theta_file: 5779 # Skip lines starting with #. 5780 if line[0] == "#": 5781 continue 5782 # Print lines, not including newline character. 5783 print(line[:-1]) 5784 5785 # Split the line 5786 linesplit = line.split() 5787 5788 # Assume values 5789 if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 5790 self.assertNotEqual(linesplit[5], "None") 5791 elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 5792 self.assertNotEqual(linesplit[5], "None") 5793 elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 5794 self.assertNotEqual(linesplit[5], "None") 5795 elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 5796 self.assertNotEqual(linesplit[5], "None") 5797 elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 5798 self.assertNotEqual(linesplit[5], "None") 5799 5800 # Close files 5801 theta_file.close()

5802 5803

5804 - def test_value_write_calc_rotating_frame_params_w_eff(self):

5805 """System test of the value.write function to write return values of w_eff from calc_rotating_frame_params() function for an R1rho setup. 5806 5807 This uses the data of the saved state attached to U{bug #21344<https://web.archive.org/web/https://gna.org/bugs/?21344>}. 5808 """ 5809 5810 # Load the state. 5811 statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 5812 self.interpreter.state.load(statefile, force=True) 5813 5814 # Set filepaths. 5815 w_eff_filepath = ds.tmpdir+sep+'w_eff.out' 5816 5817 # Write out the w_eff parameter file. 5818 self.interpreter.value.write(param='w_eff', file='w_eff.out', dir=ds.tmpdir, scaling=1.0, force=True) 5819 5820 # Test the file exists. 5821 self.assert_(access(w_eff_filepath, F_OK)) 5822 5823 # Open the files for testing. 5824 w_eff_file = open(w_eff_filepath, 'r') 5825 5826 # Loop over the w_eff file to test values. 5827 for line in w_eff_file: 5828 # Skip lines starting with #. 5829 if line[0] == "#": 5830 continue 5831 # Print lines, not including newline character. 5832 print(line[:-1]) 5833 5834 # Split the line 5835 linesplit = line.split() 5836 5837 # Assume values 5838 if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 5839 self.assertNotEqual(linesplit[5], "None") 5840 elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 5841 self.assertNotEqual(linesplit[5], "None") 5842 elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 5843 self.assertNotEqual(linesplit[5], "None") 5844 elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 5845 self.assertNotEqual(linesplit[5], "None") 5846 elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 5847 self.assertNotEqual(linesplit[5], "None") 5848 5849 # Close files 5850 w_eff_file.close()

5851 5852

5853 - def test_value_write_calc_rotating_frame_params_auto_analysis(self):

5854 """System test of the auto_analysis value.write function to write theta and w_eff values for an R1rho setup. 5855 5856 This uses the data of the saved state attached to U{bug #21344<https://web.archive.org/web/https://gna.org/bugs/?21344>}. 5857 """ 5858 5859 # Load the state. 5860 statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344.bz2' 5861 self.interpreter.state.load(statefile, force=True) 5862 5863 # Set pipe name, bundle and type. 5864 pipe_name = 'base pipe' 5865 pipe_bundle = 'relax_disp' 5866 pipe_type= 'relax_disp' 5867 5868 # The path to the data files. 5869 data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 5870 5871 # Deselect all spins 5872 self.interpreter.deselect.all() 5873 5874 # Specify spins to be selected. 5875 select_spin_ids = [ 5876 ":13@N", 5877 ":15@N", 5878 ":16@N", 5879 ":25@N", 5880 ":26@N", 5881 ":28@N", 5882 ":39@N", 5883 ":40@N", 5884 ":41@N", 5885 ":43@N", 5886 ":44@N", 5887 ":45@N", 5888 ":49@N", 5889 ":52@N", 5890 ":53@N"] 5891 5892 # Reverse the selection for the spins. 5893 for curspin in select_spin_ids: 5894 print("Selecting spin %s"%curspin) 5895 self.interpreter.deselect.reverse(spin_id=curspin) 5896 5897 # Read the R1 data 5898 self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 5899 5900 # The dispersion models. 5901 MODELS = ['R2eff'] 5902 5903 # The grid search size (the number of increments per dimension). 5904 GRID_INC = 4 5905 5906 # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 5907 MC_NUM = 3 5908 5909 # Model selection technique. 5910 MODSEL = 'AIC' 5911 5912 # Execute the auto-analysis (fast). 5913 # Standard parameters are: func_tol=1e-25, grad_tol=None, max_iter=10000000, 5914 OPT_FUNC_TOL = 1e-1 5915 relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 5916 OPT_MAX_ITERATIONS = 1000 5917 relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 5918 5919 # Run the analysis. 5920 relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=ds.tmpdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 5921 5922 ## Check for file creation 5923 # Set filepaths. 5924 theta_filepath = ds.tmpdir+sep+MODELS[0]+sep+'theta.out' 5925 w_eff_filepath = ds.tmpdir+sep+MODELS[0]+sep+'w_eff.out' 5926 5927 # Test the files exists. 5928 self.assert_(access(theta_filepath, F_OK)) 5929 self.assert_(access(w_eff_filepath, F_OK)) 5930 5931 # Open the files for testing. 5932 theta_file = open(theta_filepath, 'r') 5933 theta_result = [ 5934 "# Parameter description: Rotating frame tilt angle : ( theta = arctan(w_1 / Omega) ) (rad).\n", 5935 "#\n", 5936 "# mol_name res_num res_name spin_num spin_name r1rho_799.77739910_118.078_1341.110 sd(r1rho_799.77739910_118.078_1341.110) r1rho_799.77739910_118.078_1648.500 sd(r1rho_799.77739910_118.078_1648.500) r1rho_799.77739910_118.078_431.000 sd(r1rho_799.77739910_118.078_431.000) r1rho_799.77739910_118.078_651.200 sd(r1rho_799.77739910_118.078_651.200) r1rho_799.77739910_118.078_800.500 sd(r1rho_799.77739910_118.078_800.500) r1rho_799.77739910_118.078_984.000 sd(r1rho_799.77739910_118.078_984.000) r1rho_799.77739910_124.247_1341.110 sd(r1rho_799.77739910_124.247_1341.110) r1rho_799.77739910_130.416_1341.110 sd(r1rho_799.77739910_130.416_1341.110) r1rho_799.77739910_130.416_1648.500 sd(r1rho_799.77739910_130.416_1648.500) r1rho_799.77739910_130.416_800.500 sd(r1rho_799.77739910_130.416_800.500) r1rho_799.77739910_142.754_1341.110 sd(r1rho_799.77739910_142.754_1341.110) r1rho_799.77739910_142.754_800.500 sd(r1rho_799.77739910_142.754_800.500) r1rho_799.77739910_179.768_1341.110 sd(r1rho_799.77739910_179.768_1341.110) r1rho_799.77739910_241.459_1341.110 sd(r1rho_799.77739910_241.459_1341.110) \n", 5937 "None 5 I None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5938 "None 6 S None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5939 "None 8 S None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5940 "None 9 A None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5941 "None 10 L None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5942 "None 11 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5943 "None 12 D None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5944 "None 13 L None N 1.83827367612531 None 1.79015307643158 None 2.2768687598681 None 2.08461171779445 None 2.00120623474388 None 1.92825070277699 None 1.47212860033516 None 1.12978017906854 None 1.20415336139956 None 0.901691390796334 None 0.687390207543568 None 0.455635480573046 None 0.281637123971289 None 0.138259661766539 None \n", 5945 "None 14 L None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5946 "None 15 R None N 1.58367544790673 None 1.58127411936947 None 1.61085209029811 None 1.59731540507347 None 1.59237108385522 None 1.58834866344307 None 1.2251048782537 None 0.938142786712004 None 1.03297495592991 None 0.683284686224254 None 0.594447788256641 None 0.383528609383686 None 0.262780814059893 None 0.133469839450564 None \n", 5947 "None 16 T None N 1.40984232256624 None 1.43947245672073 None 1.10299856647417 None 1.24811470332083 None 1.30521602599932 None 1.35302443831853 None 1.07923777467974 None 0.833345927788896 None 0.934350308974616 None 0.581325254389991 None 0.543659670184793 None 0.346238480454282 None 0.251454336191817 None 0.130436714663781 None \n", 5948 "None 17 L None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5949 "None 18 K None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5950 "None 19 S None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5951 "None 21 S None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5952 "None 24 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5953 "None 25 Q None N 1.81569700258844 None 1.77137827615015 None 2.23175875585624 None 2.04612705363098 None 1.9673155780155 None 1.89908711012298 None 1.44829660124856 None 1.11023386429581 None 1.18716091371256 None 0.877306975624962 None 0.677790118853413 None 0.447932002242236 None 0.279785379050945 None 0.137802891887767 None \n", 5954 "None 26 Q None N 1.61128821168674 None 1.60374392042003 None 1.69619923953765 None 1.65403989292986 None 1.63856717205868 None 1.62595755714564 None 1.24977859227795 None 0.956353494917591 None 1.04972090035774 None 0.702164059520172 None 0.603227813742091 None 0.390116910781037 None 0.264658552037535 None 0.133960994297096 None \n", 5955 "None 27 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5956 "None 28 Q None N 1.65182797011356 None 1.63676707684161 None 1.81830827892972 None 1.7365089711986 None 1.70601955220877 None 1.68102938663686 None 1.28685736157369 None 0.984047498595701 None 1.0749792109454 None 0.731585685663053 None 0.616577997665602 None 0.400219205533665 None 0.267471993812649 None 0.134690869499646 None \n", 5957 "None 29 V None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5958 "None 30 L None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5959 "None 31 N None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5960 "None 32 I None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5961 "None 33 L None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5962 "None 34 K None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5963 "None 35 S None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5964 "None 36 N None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5965 "None 38 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5966 "None 39 L None N 1.76426439181176 None 1.72885318885161 None 2.11826300085737 None 1.95430201082222 None 1.88794717058464 None 1.83172922971397 None 1.39549951193417 None 1.06783946148624 None 1.14997013232702 None 0.826128785942585 None 0.657105386950171 None 0.431542911580536 None 0.275725736430539 None 0.136791385554619 None \n", 5967 "None 40 M None N 1.5521741199158 None 1.55564594516135 None 1.51290906497298 None 1.53245929150759 None 1.53960430408466 None 1.54541832596591 None 1.19750223001929 None 0.917959090226757 None 1.01428385962747 None 0.662779584695967 None 0.584708929219264 None 0.376271266885303 None 0.260671619214194 None 0.132914250767089 None \n", 5968 "None 41 A None N 1.68339451828261 None 1.66252964414082 None 1.90911961276946 None 1.79959323497326 None 1.75801925517113 None 1.72370710837265 None 1.31646868936419 None 1.00647189763597 None 1.09525348649914 None 0.75605702767542 None 0.627395557358039 None 0.408481831044309 None 0.269716174238842 None 0.135267948387412 None \n", 5969 "None 42 A None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5970 "None 43 F None N 1.58506597154432 None 1.58240542750303 None 1.61517196062351 None 1.60017740004898 None 1.59469990835425 None 1.59024353162528 None 1.22633651794829 None 0.939047922181951 None 1.03380990731605 None 0.684214484755514 None 0.594884298549546 None 0.383855128702894 None 0.262874695048502 None 0.13349447283116 None \n", 5971 "None 44 I None N 1.57575471961837 None 1.57483015671791 None 1.58622388390755 None 1.58100758841935 None 1.57910319967536 None 1.57755415552211 None 1.21811077066835 None 0.933010299763027 None 1.02823520295828 None 0.67802911457195 None 0.591972285081647 None 0.381678892926696 None 0.262247347241724 None 0.133329708422379 None \n", 5972 "None 45 K None N 1.77147501495754 None 1.73479633022489 None 2.13509660780385 None 1.96751045408372 None 1.89924480319914 None 1.84124387452692 None 1.40277881643715 None 1.07361367582571 None 1.15506365550891 None 0.832963505534767 None 0.659913187081268 None 0.433751178249555 None 0.276282572106685 None 0.13693095791902 None \n", 5973 "None 46 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5974 "None 48 T None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5975 "None 49 A None N 2.00297059962685 None 1.92978318052058 None 2.53305709323468 None 2.33052197276846 None 2.22870514722639 None 2.13201782446864 None 1.6587904412969 None 1.29333162369472 None 1.34311052758116 None 1.12559033900783 None 0.770195063841652 None 0.524846264860003 None 0.296857751274362 None 0.141908833673671 None \n", 5976 "None 50 K None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5977 "None 51 Y None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5978 "None 52 V None N 1.82421571143794 None 1.77845404105203 None 2.24910726268822 None 2.06078232916932 None 1.98017451806059 None 1.91012195713554 None 1.45724107606646 None 1.11753869321304 None 1.19352234944057 None 0.886361068343012 None 0.681372607920812 None 0.450799407357501 None 0.280478735779163 None 0.137974257665877 None \n", 5979 "None 53 A None N 2.05019708195234 None 1.97089957318506 None 2.58789168363698 None 2.39027806684801 None 2.28731354878582 None 2.1872118539319 None 1.7165709935896 None 1.34832362477229 None 1.38879751095815 None 1.2085314357749 None 0.799450059125864 None 0.550583841461621 None 0.30195492609136 None 0.143090604877102 None \n", 5980 "None 54 N None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5981 "None 55 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5982 "None 57 G None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5983 "None 58 M None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 5984 "None 59 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n" 5985 ] 5986 # Check the created theta file. 5987 lines = theta_file.readlines() 5988 for i in range(len(lines)): 5989 # Test lines starting with # 5990 if theta_result[i][0] == "#": 5991 self.assertEqual(theta_result[i], lines[i]) 5992 # If the line is equal each other, make a line comparison. This should catch lines with None values. 5993 if theta_result[i] == lines[i]: 5994 self.assertEqual(theta_result[i], lines[i]) 5995 # If the line is not equal each other, make a slower comparison of values. 5996 else: 5997 # Print lines if they don't match. To help find differences. 5998 print(theta_result[i]) 5999 print(lines[i]) 6000 6001 # First test first 62 characters containing spin information 6002 self.assertEqual(theta_result[i][:62], lines[i][:62]) 6003 6004 # Make a string split after 62 characters. Select each second element, so None values are skipped. 6005 theta_result_s = theta_result[i][62:].split()[::2] 6006 print(theta_result_s ) 6007 lines_s = lines[i][62:].split()[::2] 6008 print(lines_s) 6009 # Loop over the value elements 6010 for j in range(len(lines_s)): 6011 print(theta_result_s[j], lines_s[j]) 6012 # Assume a precision to digits. 6013 self.assertAlmostEqual(float(theta_result_s[j]), float(lines_s[j]), 14) 6014 6015 # Close file 6016 theta_file.close() 6017 6018 w_eff_file = open(w_eff_filepath, 'r') 6019 w_eff_result = [ 6020 "# Parameter description: Effective field in rotating frame : ( w_eff = sqrt(Omega^2 + w_1^2) ) (rad.s^-1).\n", 6021 "#\n", 6022 "# mol_name res_num res_name spin_num spin_name r1rho_799.77739910_118.078_1341.110 sd(r1rho_799.77739910_118.078_1341.110) r1rho_799.77739910_118.078_1648.500 sd(r1rho_799.77739910_118.078_1648.500) r1rho_799.77739910_118.078_431.000 sd(r1rho_799.77739910_118.078_431.000) r1rho_799.77739910_118.078_651.200 sd(r1rho_799.77739910_118.078_651.200) r1rho_799.77739910_118.078_800.500 sd(r1rho_799.77739910_118.078_800.500) r1rho_799.77739910_118.078_984.000 sd(r1rho_799.77739910_118.078_984.000) r1rho_799.77739910_124.247_1341.110 sd(r1rho_799.77739910_124.247_1341.110) r1rho_799.77739910_130.416_1341.110 sd(r1rho_799.77739910_130.416_1341.110) r1rho_799.77739910_130.416_1648.500 sd(r1rho_799.77739910_130.416_1648.500) r1rho_799.77739910_130.416_800.500 sd(r1rho_799.77739910_130.416_800.500) r1rho_799.77739910_142.754_1341.110 sd(r1rho_799.77739910_142.754_1341.110) r1rho_799.77739910_142.754_800.500 sd(r1rho_799.77739910_142.754_800.500) r1rho_799.77739910_179.768_1341.110 sd(r1rho_799.77739910_179.768_1341.110) r1rho_799.77739910_241.459_1341.110 sd(r1rho_799.77739910_241.459_1341.110) \n", 6023 "None 5 I None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6024 "None 6 S None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6025 "None 8 S None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6026 "None 9 A None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6027 "None 10 L None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6028 "None 11 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6029 "None 12 D None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6030 "None 13 L None N 8737.12883908829 None 10612.1226552258 None 3558.93734069587 None 4698.27194621826 None 5534.46153956037 None 6599.82570817753 None 8467.62674839481 None 9318.00441649087 None 11095.2662520767 None 6412.33580591254 None 13279.9803044242 None 11430.254637056 None 30318.7268264644 None 61141.1080046448 None \n", 6031 "None 14 L None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6032 "None 15 R None N 8427.14155005377 None 10358.3995676635 None 2710.22680763322 None 4093.04942975722 None 5030.86065069262 None 6183.60685459024 None 8956.28403254202 None 10448.6627754369 None 12060.4428066937 None 7966.64282975241 None 15045.8392092364 None 13441.3586252373 None 32438.4764809909 None 63321.5201471181 None \n", 6033 "None 16 T None N 8536.7818857229 None 10447.792678989 None 3034.01707453628 None 4314.2767521567 None 5212.43600885913 None 6332.21319855067 None 9558.14311447582 None 11384.2336494604 None 12879.4604966293 None 9159.34604475399 None 16290.1746838959 None 14821.0200530829 None 33866.5933527757 None 64785.3205696403 None \n", 6034 "None 17 L None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6035 "None 18 K None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6036 "None 19 S None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6037 "None 21 S None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6038 "None 24 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6039 "None 25 Q None N 8685.60895531182 None 10569.7459677762 None 3430.51272680396 None 4601.75421490393 None 5452.76508815826 None 6531.46859076009 None 8490.06475886501 None 9406.58372902508 None 11169.7602637607 None 6540.38696356753 None 13437.7348017798 None 11613.1632549021 None 30514.0741594726 None 61342.4792156782 None \n", 6040 "None 26 Q None N 8433.35533683544 None 10363.4554631194 None 2729.48656005151 None 4105.82770792005 None 5041.26238350827 None 6192.07245313098 None 8880.08366342131 None 10312.6868786802 None 11942.8320576165 None 7787.44854491812 None 14853.4987024375 None 13225.7048162038 None 32213.6690023282 None 63090.7407990801 None \n", 6041 "None 27 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6042 "None 28 Q None N 8454.18308422202 None 10380.4112885894 None 2793.17494362899 None 4148.43953208179 None 5076.02756135055 None 6220.40920270029 None 8777.91538040813 None 10118.8737706315 None 11775.8792998529 None 7528.90766101027 None 14572.4015102398 None 12909.211050939 None 31882.8171856889 None 62750.9120842199 None \n", 6043 "None 29 V None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6044 "None 30 L None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6045 "None 31 N None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6046 "None 32 I None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6047 "None 33 L None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6048 "None 34 K None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6049 "None 35 S None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6050 "None 36 N None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6051 "None 38 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6052 "None 39 L None N 8586.6405431352 None 10488.5710521378 None 3171.59430904777 None 4412.11227722123 None 5293.69814015286 None 6399.27143075725 None 8557.58926327909 None 9617.45773774313 None 11347.9169998729 None 6840.20010813426 None 13795.1250622375 None 12024.9041436853 None 30951.651485352 None 61793.2130509111 None \n", 6053 "None 40 M None N 8427.90394711227 None 10359.0198301036 None 2712.59646573568 None 4094.61889210019 None 5032.13762965554 None 6184.6458240746 None 9049.68452800053 None 10607.7913029633 None 12198.5639821231 None 8174.23271685285 None 15266.4924700447 None 13687.9010998756 None 32694.9043143038 None 63584.6371927381 None \n", 6054 "None 41 A None N 8480.14299737436 None 10401.5648897003 None 2870.79081440785 None 4201.09083283266 None 5119.14733505123 None 6255.64579267482 None 8706.50768957471 None 9972.71017314947 None 11650.5225246067 None 7331.28858930568 None 14354.1616183112 None 12662.3378547029 None 31623.9195264738 None 62484.8290612112 None \n", 6055 "None 42 A None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6056 "None 43 F None N 8427.30062786474 None 10358.5289868368 None 2710.7214015056 None 4093.37694357637 None 5031.12711571215 None 6183.82364721878 None 8952.31975962078 None 10441.7375680915 None 12054.4435931163 None 7957.55789315654 None 15036.1316712316 None 13430.4914212645 None 32427.1596037519 None 63309.9050677925 None \n", 6057 "None 44 I None N 8426.54623319716 None 10357.9152496503 None 2708.3751705368 None 4091.82359712664 None 5029.86337809029 None 6182.79552045043 None 8979.12144335458 None 10488.2688526334 None 12094.7720286018 None 8018.51779989075 None 15101.1843990883 None 13503.2816173444 None 32502.9389163062 None 63387.6763306952 None \n", 6058 "None 45 K None N 8599.01176345321 None 10498.7013581079 None 3204.93649737055 None 4436.14046641897 None 5313.74138343704 None 6415.86177652694 None 8546.79665373249 None 9587.16245449134 None 11322.2529042385 None 6797.53838612575 None 13745.1536613763 None 11967.5433300612 None 30890.8603419261 None 61730.6213936947 None \n", 6059 "None 46 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6060 "None 48 T None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6061 "None 49 A None N 9279.63849130869 None 11063.0654625247 None 4737.11992391463 None 5643.40583860235 None 6356.45614406507 None 7302.87406141381 None 8459.17105047661 None 8761.54554569995 None 10632.2343488142 None 5572.92782399155 None 12102.1714908775 None 10037.6988885228 None 28806.6916858172 None 59579.0348769179 None \n", 6062 "None 50 K None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6063 "None 51 Y None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6064 "None 52 V None N 8704.45610117774 None 10585.2389163429 None 3477.9549539207 None 4637.22923167743 None 5482.73656118686 None 6556.5108895527 None 8481.06470969555 None 9372.86414918436 None 11141.3782476763 None 6491.79686536093 None 13378.2843939736 None 11544.3205736882 None 30440.62308788 None 61266.7742546508 None \n", 6065 "None 53 A None N 9497.02860450276 None 11246.0339326126 None 5149.96766581255 None 5994.15475647208 None 6669.81232845336 None 7577.19152075731 None 8516.77431951689 None 8639.36099840319 None 10531.7750336522 None 5378.79193153767 None 11752.8060152439 None 9613.59939949642 None 28334.9153747994 None 59090.2988815445 None \n", 6066 "None 54 N None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6067 "None 55 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6068 "None 57 G None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6069 "None 58 M None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n", 6070 "None 59 Q None N None None None None None None None None None None None None None None None None None None None None None None None None None None None None \n" 6071 ] 6072 # Check the created w_eff file. 6073 lines = w_eff_file.readlines() 6074 for i in range(len(lines)): 6075 # Test lines starting with # 6076 if w_eff_result[i][0] == "#": 6077 self.assertEqual(w_eff_result[i], lines[i]) 6078 # If the line is equal each other, make a line comparison. This should catch lines with None values. 6079 if w_eff_result[i] == lines[i]: 6080 self.assertEqual(w_eff_result[i], lines[i]) 6081 # If the line is not equal each other, make a slower comparison of values. 6082 else: 6083 # Print lines if they don't match. To help find differences. 6084 print(w_eff_result[i]) 6085 print(lines[i]) 6086 6087 # First test first 62 characters containing spin information 6088 self.assertEqual(w_eff_result[i][:62], lines[i][:62]) 6089 6090 # Make a string split after 62 characters. Select each second element, so None values are skipped. 6091 w_eff_result_s = w_eff_result[i][62:].split()[::2] 6092 print(w_eff_result_s ) 6093 lines_s = lines[i][62:].split()[::2] 6094 print(lines_s) 6095 # Loop over the value elements 6096 for j in range(len(lines_s)): 6097 print(w_eff_result_s[j], lines_s[j]) 6098 # Assume a precision to digits. 6099 self.assertAlmostEqual(float(w_eff_result_s[j]), float(lines_s[j]), 14) 6100 6101 # Close file 6102 w_eff_file.close()

Source Code for Module test_suite.system_tests.relax_disp