r20329 - /branches/relax_disp/auto_analyses/relax_disp.py -- July 16, 2013 - 12:11

Author: bugman
Date: Tue Jul 16 12:11:53 2013
New Revision: 20329

URL: http://svn.gna.org/viewcvs/relax?rev=20329&view=rev
Log:
Added support for model nesting in the relaxation dispersion auto-analysis.

This involves copying the parameters from the simpler nested model rather 
than performing a full
grid search.  This is currently used to handle all models with R20A and R20B 
parameters where a
simpler model with the single R20 parameter is optimised first.


Modified:
    branches/relax_disp/auto_analyses/relax_disp.py

Modified: branches/relax_disp/auto_analyses/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/relax_disp/auto_analyses/relax_disp.py?rev=20329&r1=20328&r2=20329&view=diff
==============================================================================
--- branches/relax_disp/auto_analyses/relax_disp.py (original)
+++ branches/relax_disp/auto_analyses/relax_disp.py Tue Jul 16 12:11:53 2013
@@ -23,6 +23,7 @@
 """The automatic relaxation dispersion protocol."""
 
 # Python module imports.
+from copy import deepcopy
 from os import getcwd, sep
 import sys
 from warnings import warn
@@ -31,10 +32,11 @@
 from lib.list import unique_elements
 from lib.text.sectioning import title, subtitle
 from lib.warnings import RelaxWarning
+from pipe_control.mol_res_spin import return_spin, spin_loop
 from pipe_control.pipes import has_pipe
 from prompt.interpreter import Interpreter
 from specific_analyses.relax_disp.disp_data import loop_frq
-from specific_analyses.relax_disp.variables import CPMG_EXP, FIXED_TIME_EXP, 
MODEL_CR72, MODEL_DPL94, MODEL_IT99, MODEL_LIST_CPMG, MODEL_LIST_R1RHO, 
MODEL_LM63, MODEL_M61, MODEL_M61B, MODEL_R2EFF
+from specific_analyses.relax_disp.variables import CPMG_EXP, FIXED_TIME_EXP, 
MODEL_CR72, MODEL_CR72_RED, MODEL_DPL94, MODEL_IT99, MODEL_LIST_CPMG, 
MODEL_LIST_R1RHO, MODEL_LM63, MODEL_M61, MODEL_M61B, MODEL_NS_2SITE_STAR, 
MODEL_NS_2SITE_STAR_RED, MODEL_R2EFF
 from status import Status; status = Status()
 
 
@@ -138,11 +140,68 @@
             self.interpreter.spectrum.error_analysis(subset=ids)
 
 
-    def optimise(self):
-        """Optimise the model."""
+    def nesting(self, model=None):
+        """Support for model nesting.
+
+        If model nesting is detected, the optimised parameters from the 
simpler model will be used for the more complex model.  The method will then 
signal if the nesting condition is met for the model, allowing the grid 
search to be skipped.
+
+
+        @keyword model: The model to be optimised.
+        @type model:    str
+        @return:        True if the model is the more complex model in a 
nested pair and the parameters of the simpler model have been copied.  False 
otherwise.
+        @rtype:         bool
+        """
+
+        # The simpler model.
+        nested_pipe = None
+        if model == MODEL_CR72:
+            nested_pipe = MODEL_CR72_RED
+        if model == MODEL_NS_2SITE_STAR:
+            nested_pipe = MODEL_NS_2SITE_STAR_RED
+
+        # The more complex of nested models.
+        if nested_pipe:
+            # Printout.
+            print("Model nesting detected, copying the optimised parameters 
from the '%s' model rather than performing a grid search." % nested_pipe)
+
+            # Loop over the spins to copy the parameters.
+            for spin, spin_id in spin_loop(return_id=True):
+                # Get the nested spin.
+                nested_spin = return_spin(spin_id=spin_id, pipe=nested_pipe)
+
+                # The R20 parameters.
+                if hasattr(nested_spin, 'r2'):
+                    setattr(spin, 'r2a', deepcopy(nested_spin.r2))
+                    setattr(spin, 'r2b', deepcopy(nested_spin.r2))
+
+                # All other spin parameters.
+                for param in spin.params:
+                    if param in ['r2', 'r2a', 'r2b']:
+                        continue
+
+                    # Copy the parameter.
+                    setattr(spin, param, deepcopy(getattr(nested_spin, 
param)))
+
+            # Nesting.
+            return True
+
+        # No nesting.
+        return False
+
+
+    def optimise(self, model=None):
+        """Optimise the model, taking model nesting into account.
+
+        @keyword model: The model to be optimised.
+        @type model:    str
+        """
+
+        # Nested model simplification.
+        nested = self.nesting(model=model)
 
         # Grid search.
-        self.interpreter.grid_search(inc=self.grid_inc)
+        if not nested:
+            self.interpreter.grid_search(inc=self.grid_inc)
 
         # Minimise.
         self.interpreter.minimise('simplex', func_tol=self.opt_func_tol, 
max_iter=self.opt_max_iterations, constraints=True)
@@ -189,7 +248,7 @@
 
             # Optimise the model.
             else:
-                self.optimise()
+                self.optimise(model=model)
 
             # Write out the results.
             self.write_results(path=self.results_dir+sep+model, model=model)