Source Code for Module auto_analyses.relax_fit

  1  ############################################################################### 
  2  #                                                                             # 
  3  # Copyright (C) 2004,2006-2008,2010-2012,2014-2015,2017 Edward d'Auvergne     # 
  4  # Copyright (C) 2010 Michael Bieri                                            # 
  5  # Copyright (C) 2014 Troels E. Linnet                                         # 
  6  #                                                                             # 
  7  # This file is part of the program relax (http://www.nmr-relax.com).          # 
  8  #                                                                             # 
  9  # This program is free software: you can redistribute it and/or modify        # 
 10  # it under the terms of the GNU General Public License as published by        # 
 11  # the Free Software Foundation, either version 3 of the License, or           # 
 12  # (at your option) any later version.                                         # 
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 14  # This program is distributed in the hope that it will be useful,             # 
 15  # but WITHOUT ANY WARRANTY; without even the implied warranty of              # 
 16  # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the               # 
 17  # GNU General Public License for more details.                                # 
 18  #                                                                             # 
 19  # You should have received a copy of the GNU General Public License           # 
 20  # along with this program.  If not, see <http://www.gnu.org/licenses/>.       # 
 21  #                                                                             # 
 22  ############################################################################### 
 23   
 24  # Module docstring. 
 25  """The automatic relaxation curve fitting protocol.""" 
 26   
 27  # Python module imports. 
 28  from os import sep 
 29  from time import time 
 30  import sys 
 31   
 32  # relax module imports. 
 33  from lib.errors import RelaxNoPipeError 
 34  from lib.plotting.grace import create_grace2images 
 35  from lib.text.sectioning import section, title 
 36  from lib.timing import print_elapsed_time 
 37  from pipe_control.mol_res_spin import spin_loop 
 38  from pipe_control.pipes import cdp_name, has_pipe, switch 
 39  from prompt.interpreter import Interpreter 
 40  from status import Status; status = Status() 
 41   
 42   
 43 -class Relax_fit: 
 44 -    def __init__(self, pipe_name=None, pipe_bundle=None, file_root='rx', results_dir=None, grid_inc=11, mc_sim_num=500, view_plots=True): 
 45          """Perform relaxation curve fitting. 
 46   
 47          To use this auto-analysis, a data pipe with all the required data needs to be set up.  This data pipe should contain the following: 
 48   
 49              - All the spins loaded. 
 50              - Unresolved spins deselected. 
 51              - All the peak intensities loaded and relaxation delay times set. 
 52              - Either the baseplane noise RMSD values should be set or replicated spectra loaded. 
 53   
 54          @keyword pipe_name:     The name of the data pipe containing all of the data for the analysis. 
 55          @type pipe_name:        str 
 56          @keyword pipe_bundle:   The data pipe bundle to associate all spawned data pipes with. 
 57          @type pipe_bundle:      str 
 58          @keyword file_root:     File root of the output filea. 
 59          @type file_root:        str 
 60          @keyword results_dir:   The directory where results files are saved. 
 61          @type results_dir:      str 
 62          @keyword grid_inc:      Number of grid search increments. 
 63          @type grid_inc:         int 
 64          @keyword mc_sim_num:    The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
 65          @type mc_sim_num:       int 
 66          @keyword view_plots:    Flag to automatically view grace plots after calculation. 
 67          @type view_plots:       bool 
 68          """ 
 69   
 70          # Initial printout. 
 71          title(file=sys.stdout, text="Relaxation curve-fitting auto-analysis") 
 72   
 73          # Safely execute the full protocol. 
 74          try: 
 75              # Execution lock. 
 76              status.exec_lock.acquire(pipe_bundle, mode='auto-analysis') 
 77   
 78              # Set up the analysis status object. 
 79              status.init_auto_analysis(pipe_bundle, type='relax_fit') 
 80              status.current_analysis = pipe_bundle 
 81   
 82              # Store the args. 
 83              self.pipe_name = pipe_name 
 84              self.pipe_bundle = pipe_bundle 
 85              self.file_root = file_root 
 86              self.results_dir = results_dir 
 87              if self.results_dir: 
 88                  self.grace_dir = results_dir + sep + 'grace' 
 89              else: 
 90                  self.grace_dir = 'grace' 
 91              self.mc_sim_num = mc_sim_num 
 92              self.grid_inc = grid_inc 
 93              self.view_plots = view_plots 
 94   
 95              # Data checks. 
 96              self.check_vars() 
 97   
 98              # Set the data pipe to the current data pipe. 
 99              if self.pipe_name != cdp_name(): 
100                  switch(self.pipe_name) 
101   
102              # Load the interpreter. 
103              self.interpreter = Interpreter(show_script=False, raise_relax_error=True) 
104              self.interpreter.populate_self() 
105              self.interpreter.on(verbose=False) 
106   
107              # Execute. 
108              self.run() 
109   
110          # Clean up. 
111          finally: 
112              # Final printout. 
113              title(file=sys.stdout, text="Completion of the relaxation curve-fitting auto-analysis") 
114              print_elapsed_time(time() - status.start_time) 
115   
116              # Finish and unlock execution. 
117              status.auto_analysis[self.pipe_bundle].fin = True 
118              status.current_analysis = None 
119              status.exec_lock.release() 
120   
121   
122 -    def run(self): 
123          """Set up and run the curve-fitting.""" 
124   
125          # Peak intensity error analysis. 
126          self.error_analysis() 
127   
128          # Grid search. 
129          self.interpreter.minimise.grid_search(inc=self.grid_inc) 
130   
131          # Minimise. 
132          self.interpreter.minimise.execute('newton', scaling=False, constraints=False) 
133   
134          # Monte Carlo simulations. 
135          self.interpreter.monte_carlo.setup(number=self.mc_sim_num) 
136          self.interpreter.monte_carlo.create_data() 
137          self.interpreter.monte_carlo.initial_values() 
138          self.interpreter.minimise.execute('newton', scaling=False, constraints=False) 
139          self.interpreter.monte_carlo.error_analysis() 
140   
141          # Determine the normalisation type and if the Iinf parameter exists. 
142          norm_type = 'last' 
143          iinf = True 
144          for spin in spin_loop(skip_desel=True): 
145              if spin.model not in ['sat', 'inv']: 
146                  norm_type = 'first' 
147                  iinf = False 
148                  break 
149   
150          # Save the relaxation rates and other parameter values. 
151          self.interpreter.value.write(param='i0', file='i0.out', dir=self.results_dir, force=True) 
152          if iinf: 
153              self.interpreter.value.write(param='iinf', file='iinf.out', dir=self.results_dir, force=True) 
154          self.interpreter.value.write(param='rx', file=self.file_root+'.out', dir=self.results_dir, force=True) 
155   
156          # Save the results. 
157          self.interpreter.results.write(file='results', dir=self.results_dir, force=True) 
158   
159          # Create Grace plots of the data. 
160          self.interpreter.grace.write(y_data_type='chi2', file='chi2.agr', dir=self.grace_dir, force=True)    # Minimised chi-squared value. 
161          self.interpreter.grace.write(y_data_type='i0', file='i0.agr', dir=self.grace_dir, force=True)    # Initial peak intensity. 
162          if iinf: 
163              self.interpreter.grace.write(y_data_type='iinf', file='iinf.agr', dir=self.grace_dir, force=True)    # Infinite peak intensity. 
164          self.interpreter.grace.write(y_data_type='rx', file=self.file_root+'.agr', dir=self.grace_dir, force=True)    # Relaxation rate. 
165          self.interpreter.grace.write(x_data_type='relax_times', y_data_type='peak_intensity', file='intensities.agr', dir=self.grace_dir, force=True)    # Average peak intensities. 
166          self.interpreter.grace.write(x_data_type='relax_times', y_data_type='peak_intensity', norm_type=norm_type, norm=True, file='intensities_norm.agr', dir=self.grace_dir, force=True)    # Average peak intensities (normalised). 
167   
168          # Create the Python "grace to PNG/EPS/SVG..." conversion script. 
169          create_grace2images(dir=self.grace_dir) 
170   
171          # Display the Grace plots if selected. 
172          if self.view_plots: 
173              self.interpreter.grace.view(file='chi2.agr', dir=self.grace_dir) 
174              self.interpreter.grace.view(file='i0.agr', dir=self.grace_dir) 
175              self.interpreter.grace.view(file=self.file_root+'.agr', dir=self.grace_dir) 
176              self.interpreter.grace.view(file='intensities.agr', dir=self.grace_dir) 
177              self.interpreter.grace.view(file='intensities_norm.agr', dir=self.grace_dir) 
178   
179          # Save the program state. 
180          self.interpreter.state.save(state='state', dir=self.results_dir, force=True) 
181   
182   
183 -    def error_analysis(self): 
184          """Perform an error analysis of the peak intensities.""" 
185   
186          # Printout. 
187          section(file=sys.stdout, text="Error analysis", prespace=2) 
188   
189          # Check if intensity errors have already been calculated by the user. 
190          precalc = True 
191          for spin in spin_loop(skip_desel=True): 
192              # No structure. 
193              if not hasattr(spin, 'peak_intensity_err'): 
194                  precalc = False 
195                  break 
196   
197              # Determine if a spectrum ID is missing from the list. 
198              for id in cdp.spectrum_ids: 
199                  if id not in spin.peak_intensity_err: 
200                      precalc = False 
201                      break 
202   
203          # Skip. 
204          if precalc: 
205              print("Skipping the error analysis as it has already been performed.") 
206              return 
207   
208          # Check if there is replicates, and the user has not specified them. 
209   
210          # Set flag for dublicates. 
211          has_dub = False 
212   
213          if not hasattr(cdp, 'replicates'): 
214              # Collect all times, and matching spectrum ID. 
215              all_times = [] 
216              all_id = [] 
217              for spectrum_id in cdp.relax_times: 
218                  all_times.append(cdp.relax_times[spectrum_id]) 
219                  all_id.append(spectrum_id) 
220   
221              # Get the dublicates. 
222              dublicates = [(val, [i for i in range(len(all_times)) if all_times[i] == val]) for val in all_times] 
223   
224              # Loop over the list of the mapping of times and duplications. 
225              list_dub_mapping = [] 
226              for i, dub in enumerate(dublicates): 
227                  # Get current spectum id. 
228                  cur_spectrum_id = all_id[i] 
229   
230                  # Get the tuple of time and indexes of duplications. 
231                  time, list_index_occur = dub 
232   
233                  # Collect mapping of index to id. 
234                  id_list = [] 
235                  if len(list_index_occur) > 1: 
236                      # There exist dublications. 
237                      has_dub = True 
238   
239                      for list_index in list_index_occur: 
240                          id_list.append(all_id[list_index]) 
241   
242                  # Store to list 
243                  list_dub_mapping.append((cur_spectrum_id, id_list)) 
244   
245          # If there is dublication, then assign them. 
246          if has_dub: 
247              # Assign dublicates. 
248              for spectrum_id, dub_pair in list_dub_mapping: 
249                  if len(dub_pair) > 0: 
250                      self.interpreter.spectrum.replicated(spectrum_ids=dub_pair) 
251   
252          # Run the error analysis. 
253          self.interpreter.spectrum.error_analysis() 
254   
255   
256 -    def check_vars(self): 
257          """Check that the user has set the variables correctly.""" 
258   
259          # The pipe name. 
260          if not has_pipe(self.pipe_name): 
261              raise RelaxNoPipeError(self.pipe_name) 
262