r24832 - /branches/frame_order_cleanup/auto_analyses/frame_order.py -- July 30, 2014 - 14:26

Author: bugman
Date: Wed Jul 30 14:26:15 2014
New Revision: 24832

URL: http://svn.gna.org/viewcvs/relax?rev=24832&view=rev
Log:
The frame order auto-analysis Optimisation_settings object now handles the 
maximum iterations.

The new max_iter argument has been added to the add_min() method, and the new 
get_min_max_iter()
method added to fetch the value.  This is used in the auto-analysis to set 
the maximum number of
optimisation iterations in the minimise.execute user function calls.  
Limiting this will be of
greatest benefit for the test suite.


Modified:
    branches/frame_order_cleanup/auto_analyses/frame_order.py

Modified: branches/frame_order_cleanup/auto_analyses/frame_order.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/auto_analyses/frame_order.py?rev=24832&r1=24831&r2=24832&view=diff
==============================================================================
--- branches/frame_order_cleanup/auto_analyses/frame_order.py   (original)
+++ branches/frame_order_cleanup/auto_analyses/frame_order.py   Wed Jul 30 
14:26:15 2014
@@ -135,7 +135,7 @@
                 self.interpreter.monte_carlo.setup(number=self.mc_sim_num)
                 self.interpreter.monte_carlo.create_data()
                 self.interpreter.monte_carlo.initial_values()
-                self.interpreter.minimise.execute(opt.get_min_algor(0), 
func_tol=opt.get_min_func_tol(0))
+                self.interpreter.minimise.execute(opt.get_min_algor(0), 
func_tol=opt.get_min_func_tol(0), max_iter=opt.get_min_max_iter(0))
                 self.interpreter.eliminate()
                 self.interpreter.monte_carlo.error_analysis()
 
@@ -522,9 +522,7 @@
                     self.interpreter.frame_order.num_int_pts(num=num_int_pts)
 
                 # Perform the optimisation.
-                min_algor = opt.get_min_algor(i)
-                func_tol = opt.get_min_func_tol(i)
-                self.interpreter.minimise.execute(min_algor, 
func_tol=func_tol)
+                
self.interpreter.minimise.execute(min_algor=opt.get_min_algor(i), 
func_tol=opt.get_min_func_tol(i), max_iter=opt.get_min_max_iter(i))
 
             # Copy the PCS data.
             self.interpreter.pcs.copy(pipe_from=self.data_pipe_full, 
pipe_to=self.pipe_name_dict[model])
@@ -538,9 +536,7 @@
                     self.interpreter.frame_order.num_int_pts(num=num_int_pts)
 
                 # Perform the optimisation.
-                min_algor = opt.get_min_algor(i)
-                func_tol = opt.get_min_func_tol(i)
-                self.interpreter.minimise.execute(min_algor, 
func_tol=func_tol)
+                
self.interpreter.minimise.execute(min_algor=opt.get_min_algor(i), 
func_tol=opt.get_min_func_tol(i), max_iter=opt.get_min_max_iter(i))
 
             # Results printout.
             self.print_results()
@@ -621,9 +617,7 @@
                 self.interpreter.frame_order.num_int_pts(num=num_int_pts)
 
             # Perform the optimisation.
-            min_algor = opt.get_min_algor(i)
-            func_tol = opt.get_min_func_tol(i)
-            self.interpreter.minimise.execute(min_algor, func_tol=func_tol)
+            
self.interpreter.minimise.execute(min_algor=opt.get_min_algor(i), 
func_tol=opt.get_min_func_tol(i), max_iter=opt.get_min_max_iter(i))
 
         # Results printout.
         self.print_results()
@@ -826,6 +820,7 @@
         self._min_count = 0
         self._min_algor = []
         self._min_func_tol = []
+        self._min_max_iter = []
         self._min_num_int_pts = []
 
 
@@ -874,13 +869,15 @@
         self._grid_count += 1
 
 
-    def add_min(self, min_algor=None, func_tol=None, num_int_pts=None):
+    def add_min(self, min_algor='simplex', func_tol=1e-25, max_iter=1000000, 
num_int_pts=None):
         """Add an optimisation step.
 
         @keyword min_algor:     The optimisation technique.
         @type min_algor:        str
         @keyword func_tol:      The minimisation function tolerance cutoff 
to terminate optimisation (see the minimise.execute user function).
-        @type func_tol:         None or int
+        @type func_tol:         int
+        @keyword max_iter:      The maximum number of iterations for the 
optimisation.
+        @type max_iter:         int
         @keyword num_int_pts:   The list of the number of Sobol' points for 
the PCS numerical integration to use in the optimisations after the grid 
search.  If not supplied, then the previous value will be used.
         @type num_int_pts:      None or int
         """
@@ -888,11 +885,13 @@
         # Value checking, as this will be set up by a user.
         is_str(min_algor, name='min_algor', can_be_none=False)
         is_float(func_tol, name='func_tol', can_be_none=True)
+        is_int(max_iter, name='max_iter', can_be_none=True)
         is_int(num_int_pts, name='num_int_pts', can_be_none=True)
 
         # Store the values.
         self._min_algor.append(min_algor)
         self._min_func_tol.append(func_tol)
+        self._min_max_iter.append(max_iter)
         self._min_num_int_pts.append(num_int_pts)
 
         # Increment the count.
@@ -979,6 +978,22 @@
         return self._min_func_tol[i]
 
 
+    def get_min_max_iter(self, i):
+        """Return the maximum number of iterations for the optimisation for 
the given iteration.
+
+        @param i:   The minimisation iteration from the loop_min() method.
+        @type i:    int
+        @return:    The maximum number of iterations for the optimisation 
for the iteration.
+        @rtype:     int
+        """
+
+        # Check the index.
+        self._check_index(i, iter_type='min')
+
+        # Return the value.
+        return self._min_max_iter[i]
+
+
     def get_min_num_int_pts(self, i):
         """Return the number of numerical integration points for the given 
iteration.