Changeset 155

Timestamp:

07/26/09 14:02:38 (7 years ago)

Author:

altafang

Message:

Moved dn to Solve() to avoid repetitive code

File:

• branches/alta/mystic-0.1a2/mystic/snobfit_solver.py (modified) (4 diffs)

branches/alta/mystic-0.1a2/mystic/snobfit_solver.py

@@ -79 +79 @@
     """Snobfit optimization. """
 
-    def __init__(self, dim, NP):
+    def __init__(self, dim):
         """
 Takes two initial inputs: 
     dim      -- dimensionality of the problem
-    NP   -- size of the trial solution population. NP should be
-            len(x0) + numpy.maximum(dn, len(x0)/2) + 1
-            where len(x0) = dim, and dn is number of extra
-            data points (default dn= 5)
-        """
-
-        AbstractSolver.__init__(self,dim, npop=NP)
+        """
+
+        AbstractSolver.__init__(self,dim)
 
 
@@ -163 +159 @@
             numpy.random.seed( [seed] )
 
+        # Adjust if dn was passed as a parameter to Solve()
+        adjusted_dn = numpy.maximum(dn, self.nDim/2)
+        self.nPop = self.nDim/2 + adjusted_dn + 1
+
         # The number of safeguarded nearest neighbors
         self.snn = self.nPop - 1
@@ -171 +171 @@
         # Other initializations
         self.x = self._setInitRecommendedEvalPoints( x0 )
-        #self.x = numpy.asfarray(self.population)
         (self.f, self.df) = self._setInitial_fdf(func)
         self.nx = self.x.shape[0]
@@ -2466 +2465 @@
     from mystic.termination import SnobfitTermination
 
-    adjusted_dn = numpy.maximum(dn, len(x0)/2)
-    solver = SnobfitSolver(len(x0), len(x0)+adjusted_dn+1)
+    solver = SnobfitSolver(len(x0))
     solver.SetInitialPoints(x0)
     solver.enable_signal_handler()