Source Code for Module specific_fns.setup

  1  ############################################################################### 
  2  #                                                                             # 
  3  # Copyright (C) 2004, 2006-2011 Edward d'Auvergne                             # 
  4  #                                                                             # 
  5  # This file is part of the program relax (http://www.nmr-relax.com).          # 
  6  #                                                                             # 
  7  # This program 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 3 of the License, or           # 
 10  # (at your option) any later version.                                         # 
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 12  # This program 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 this program.  If not, see <http://www.gnu.org/licenses/>.       # 
 19  #                                                                             # 
 20  ############################################################################### 
 21   
 22  # relax module imports. 
 23  from generic_fns import pipes 
 24  from specific_fns.consistency_tests import Consistency_tests 
 25  from specific_fns.frame_order import Frame_order 
 26  from specific_fns.hybrid import Hybrid 
 27  from specific_fns.jw_mapping import Jw_mapping 
 28  from specific_fns.model_free import Model_free 
 29  from specific_fns.n_state_model import N_state_model 
 30  from specific_fns.noe import Noe 
 31  from specific_fns.relax_fit import Relax_fit 
 32  from relax_errors import RelaxError, RelaxFuncSetupError 
 33   
 34   
 35  # Instantiate all classes. 
 36  consistency_tests_obj = Consistency_tests() 
 37  frame_order_obj = Frame_order() 
 38  hybrid_obj = Hybrid() 
 39  jw_mapping_obj = Jw_mapping() 
 40  model_free_obj = Model_free() 
 41  n_state_model_obj = N_state_model() 
 42  noe_obj = Noe() 
 43  relax_fit_obj = Relax_fit() 
 44   
 45   
 46  # The function for returning the requested specific function. 
 47 -def get_specific_fn(eqi, function_type=None, raise_error=True): 
 48      """The function for returning the requested specific function.""" 
 49   
 50      # Initialise. 
 51      function = None 
 52      if function_type == None: 
 53          function_type = pipes.get_type() 
 54   
 55      # Get the class instance corresponding to function_type. 
 56      inst = get_instance(function_type) 
 57   
 58      # Attempt to retrieve the function. 
 59      try: 
 60          # Back calculation of relaxation data. 
 61          if eqi == 'back_calc_ri': 
 62              function = inst.back_calc_ri 
 63   
 64          # Base data loop generator function. 
 65          if eqi == 'base_data_loop': 
 66              function = inst.base_data_loop 
 67   
 68          # BMRB NMR-STAR v3.1 reading function. 
 69          if eqi == 'bmrb_read': 
 70              function = inst.bmrb_read 
 71   
 72          # BMRB NMR-STAR v3.1 writing function. 
 73          if eqi == 'bmrb_write': 
 74              function = inst.bmrb_write 
 75   
 76          # Calculate function. 
 77          if eqi == 'calculate': 
 78              function = inst.calculate 
 79   
 80          # Create Monte Carlo data function. 
 81          if eqi == 'create_mc_data': 
 82              function = inst.create_mc_data 
 83   
 84          # Data structure initialisation function. 
 85          if eqi == 'data_init': 
 86              function = inst.data_init 
 87   
 88          # List of parameter names returning function. 
 89          if eqi == 'data_names': 
 90              function = inst.data_names 
 91   
 92          # The parameter type function. 
 93          if eqi == 'data_type': 
 94              function = inst.data_type 
 95   
 96          # Default parameter value returning function. 
 97          if eqi == 'default_value': 
 98              function = inst.default_value 
 99   
100          # Duplicate data function. 
101          if eqi == 'duplicate_data': 
102              function = inst.duplicate_data 
103   
104          # Eliminate models. 
105          if eqi == 'eliminate': 
106              function = inst.eliminate 
107   
108          # Parameter names function. 
109          if eqi == 'get_param_names': 
110              function = inst.get_param_names 
111   
112          # Parameter values function. 
113          if eqi == 'get_param_values': 
114              function = inst.get_param_values 
115   
116          # Grid search function. 
117          if eqi == 'grid_search': 
118              function = inst.grid_search 
119   
120          # Initial Monte Carlo parameter value search function. 
121          if eqi == 'init_sim_values': 
122              function = inst.sim_init_values 
123   
124          # Spin specific parameter determining function. 
125          if eqi == 'is_spin_param': 
126              function = inst.is_spin_param 
127   
128          # Map bounds function. 
129          if eqi == 'map_bounds': 
130              function = inst.map_bounds 
131   
132          # Minimise function. 
133          if eqi == 'minimise': 
134              function = inst.minimise 
135   
136          # Model loop. 
137          if eqi == 'model_desc': 
138              function = inst.model_desc 
139   
140          # Model loop. 
141          if eqi == 'model_loop': 
142              function = inst.model_loop 
143   
144          # Model statistics. 
145          if eqi == 'model_stats': 
146              function = inst.model_statistics 
147   
148          # Model type. 
149          if eqi == 'model_type': 
150              function = inst.model_type 
151   
152          # Molmol macro creation. 
153          if eqi == 'molmol_macro': 
154              function = inst.molmol_macro 
155   
156          # Number of instances. 
157          if eqi == 'num_instances': 
158              function = inst.num_instances 
159   
160          # Overfit deselect. 
161          if eqi == 'overfit_deselect': 
162              function = inst.overfit_deselect 
163   
164          # Pack Monte Carlo simulation data function. 
165          if eqi == 'pack_sim_data': 
166              function = inst.sim_pack_data 
167   
168          # Pymol macro creation. 
169          if eqi == 'pymol_macro': 
170              function = inst.pymol_macro 
171   
172          # Read results file function (Columnar format). 
173          if eqi == 'read_columnar_results': 
174              function = inst.read_columnar_results 
175   
176          # Read results file function (XML format). 
177          #if eqi == 'read_xml_results': 
178          #    function = inst.read_xml_results 
179   
180          # Data returning function. 
181          if eqi == 'return_data': 
182              function = inst.return_data 
183   
184          # Parameter description returning function. 
185          if eqi == 'return_data_desc': 
186              function = inst.return_data_desc 
187   
188          # Data or parameter name returning function. 
189          if eqi == 'return_data_name': 
190              function = inst.return_data_name 
191   
192          # Data error returning function. 
193          if eqi == 'return_error': 
194              function = inst.return_error 
195   
196          # Factor of conversion between different parameter units returning function. 
197          if eqi == 'return_conversion_factor': 
198              function = inst.return_conversion_factor 
199   
200          # Grace string returning function. 
201          if eqi == 'return_grace_string': 
202              function = inst.return_grace_string 
203   
204          # Selected simulation array returning function. 
205          if eqi == 'return_selected_sim': 
206              function = inst.sim_return_selected 
207   
208          # Simulation chi-squared array returning function. 
209          if eqi == 'return_sim_chi2': 
210              function = inst.sim_return_chi2 
211   
212          # Simulation parameter array returning function. 
213          if eqi == 'return_sim_param': 
214              function = inst.sim_return_param 
215   
216          # String of the external parameter units returning function. 
217          if eqi == 'return_units': 
218              function = inst.return_units 
219   
220          # Value and error returning function. 
221          if eqi == 'return_value': 
222              function = inst.return_value 
223   
224          # Set error function. 
225          if eqi == 'set_error': 
226              function = inst.set_error 
227   
228          # Set parameter values function. 
229          if eqi == 'set_param_values': 
230              function = inst.set_param_values 
231   
232          # Set the selected simulations array. 
233          if eqi == 'set_selected_sim': 
234              function = inst.set_selected_sim 
235   
236          # Set update function. 
237          if eqi == 'set_update': 
238              function = inst.set_update 
239   
240          # Skip function. 
241          if eqi == 'skip_function': 
242              function = inst.skip_function 
243   
244          # Deselection function. 
245          if eqi == 'deselect': 
246              function = inst.deselect 
247   
248      # Catch if the function is missing. 
249      except AttributeError: 
250          function = None 
251   
252      # Raise an error if the function doesn't exist. 
253      if raise_error and function == None: 
254          # Raise the error. 
255          raise RelaxFuncSetupError(get_string(function_type)) 
256   
257      # Return the function. 
258      return function 
259   
260   
261 -def get_instance(function_type): 
262      """Function for returning the class instance corresponding to the function type.""" 
263   
264      # Consistency testing. 
265      if function_type == 'ct': 
266          return consistency_tests_obj 
267   
268      # The Frame Order theories. 
269      if function_type == 'frame order': 
270          return frame_order_obj 
271   
272      # NOE calculation. 
273      if function_type == 'noe': 
274          return noe_obj 
275   
276      # The N-state model. 
277      if function_type == 'N-state': 
278          return n_state_model_obj 
279   
280      # Relaxation curve fitting. 
281      if function_type == 'relax_fit': 
282          return relax_fit_obj 
283   
284      # Reduced spectral density mapping. 
285      if function_type == 'jw': 
286          return jw_mapping_obj 
287   
288      # Model-free analysis. 
289      if function_type == 'mf': 
290          return model_free_obj 
291   
292      # Hybrid models. 
293      if function_type == 'hybrid': 
294          return hybrid_obj 
295   
296      # Unknown analysis. 
297      raise RelaxError("The function_type " + repr(function_type) + " is unknown.") 
298   
299   
300 -def get_string(function_type): 
301      """Function for returning a string corresponding to the function type.""" 
302   
303      # Consistency testing. 
304      if function_type == 'ct': 
305          return "consistency testing" 
306   
307      # The Frame Order theories. 
308      if function_type == 'frame order': 
309          return "Frame Order theories" 
310   
311      # NOE calculation. 
312      if function_type == 'noe': 
313          return "NOE calculations" 
314   
315      # The N-state model. 
316      if function_type == 'N-state': 
317          return "the N-state model" 
318   
319      # Relaxation curve fitting. 
320      if function_type == 'relax_fit': 
321          return "relaxation curve fitting" 
322   
323      # Reduced spectral density mapping. 
324      if function_type == 'jw': 
325          return "reduced spectral density mapping" 
326   
327      # Model-free analysis. 
328      if function_type == 'mf': 
329          return "Model-free analysis" 
330   
331      # Hybrid models. 
332      if function_type == 'hybrid': 
333          return "hybrid models" 
334   
335      # Unknown analysis. 
336      raise RelaxError("The function_type " + repr(function_type) + " is unknown.") 
337