Source Code for Module specific_fns.hybrid

  1  ############################################################################### 
  2  #                                                                             # 
  3  # Copyright (C) 2006 Edward d'Auvergne                                        # 
  4  #                                                                             # 
  5  # This file is part of the program relax.                                     # 
  6  #                                                                             # 
  7  # relax is free software; you can redistribute it and/or modify               # 
  8  # it under the terms of the GNU General Public License as published by        # 
  9  # the Free Software Foundation; either version 2 of the License, or           # 
 10  # (at your option) any later version.                                         # 
 11  #                                                                             # 
 12  # relax is distributed in the hope that it will be useful,                    # 
 13  # but WITHOUT ANY WARRANTY; without even the implied warranty of              # 
 14  # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the               # 
 15  # GNU General Public License for more details.                                # 
 16  #                                                                             # 
 17  # You should have received a copy of the GNU General Public License           # 
 18  # along with relax; if not, write to the Free Software                        # 
 19  # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA   # 
 20  #                                                                             # 
 21  ############################################################################### 
 22   
 23   
 24 -class Hybrid: 
 25 -    def __init__(self, relax): 
 26          """Class containing function specific to hybrid models.""" 
 27   
 28          self.relax = relax 
 29   
 30   
 31 -    def duplicate_data(self, new_run=None, old_run=None, instance=None): 
 32          """Function for duplicating data.""" 
 33   
 34          # Test that the new run exists. 
 35          if not new_run in self.relax.data.run_names: 
 36              raise RelaxNoRunError, new_run 
 37   
 38          # Test that the old run exists. 
 39          if not old_run in self.relax.data.run_names: 
 40              raise RelaxNoRunError, old_run 
 41   
 42          # Test that the new run has no sequence loaded. 
 43          if self.relax.data.res.has_key(new_run): 
 44              raise RelaxSequenceError, new_run 
 45   
 46          # Reset the new run type to hybrid! 
 47          self.relax.data.run_types[self.relax.data.run_names.index(new_run)] = 'hybrid' 
 48   
 49          # Duplicate the hybrid run data structure. 
 50          self.relax.data.hybrid_runs[new_run] = self.relax.data.hybrid_runs[old_run] 
 51   
 52   
 53 -    def hybridise(self, hybrid=None, runs=None): 
 54          """Function for creating the hybrid run.""" 
 55   
 56          # Test if the hybrid run already exists. 
 57          if hybrid in self.relax.data.run_names: 
 58              raise RelaxRunError, hybrid 
 59   
 60          # Loop over the runs to be hybridised. 
 61          for run in runs: 
 62              # Test if the run exists. 
 63              if not run in self.relax.data.run_names: 
 64                  raise RelaxNoRunError, run 
 65   
 66              # Test if sequence data is loaded. 
 67              if not self.relax.data.res.has_key(run): 
 68                  raise RelaxNoSequenceError, run 
 69   
 70          # Check the sequence. 
 71          for i in xrange(len(self.relax.data.res[runs[0]])): 
 72              # Reassign the data structure. 
 73              data1 = self.relax.data.res[runs[0]][i] 
 74   
 75              # Loop over the rest of the runs. 
 76              for run in runs[1:]: 
 77                  # Reassign the data structure. 
 78                  data2 = self.relax.data.res[run][i] 
 79   
 80                  # Test if the sequence is the same. 
 81                  if data1.name != data2.name or data1.num != data2.num: 
 82                      raise RelaxError, "The residues '" + data1.name + " " + `data1.num` + "' of the run " + `runs[0]` + " and '" + data2.name + " " + `data2.num` + "' of the run " + `run` + " are not the same." 
 83   
 84          # Add the run and type to the runs list. 
 85          self.relax.data.run_names.append(hybrid) 
 86          self.relax.data.run_types.append('hybrid') 
 87   
 88          # Create the data structure of the runs which form the hybrid. 
 89          self.relax.data.hybrid_runs[hybrid] = runs 
 90   
 91   
 92 -    def model_statistics(self, run=None, instance=None, global_stats=None): 
 93          """Function for returning the values k, n, and chi2 of the hybrid. 
 94   
 95          k - number of parameters. 
 96          n - number of data points. 
 97          chi2 - the chi-squared value. 
 98          """ 
 99   
100          # Arguments. 
101          self.run = run 
102   
103          # Initialise. 
104          k_total = 0 
105          n_total = 0 
106          chi2_total = 0.0 
107   
108          # Specific setup. 
109          for run in self.relax.data.hybrid_runs[self.run]: 
110              # Function type. 
111              function_type = self.relax.data.run_types[self.relax.data.run_names.index(run)] 
112   
113              # Specific model statistics and number of instances functions. 
114              model_statistics = self.relax.specific_setup.setup('model_stats', function_type) 
115   
116              # Loop over the instances. 
117              for i in xrange(num): 
118                  # Get the statistics. 
119                  k, n, chi2 = model_statistics(run, instance=i, global_stats=global_stats) 
120   
121                  # Bad stats. 
122                  if k == None or n == None or chi2 == None: 
123                      continue 
124   
125                  # Sum the stats. 
126                  k_total = k_total + k 
127                  n_total = n_total + n 
128                  chi2_total = chi2_total + chi2 
129   
130          # Return the totals. 
131          return k_total, n_total, chi2_total 
132   
133   
134 -    def num_instances(self, run=None): 
135          """Function for returning the number of instances, which for hybrids is always 1.""" 
136   
137          return 1 
138   
139   
140 -    def skip_function(self, run=None, instance=None, min_instances=None, num_instances=None): 
141          """Dummy function.""" 
142   
143          return 
144