Changeset 423

Timestamp:

09/10/10 09:49:46 (6 years ago)

Author:

mmckerns

Message:

added termination test suite (temporarily in wrong dir)
minor bugfixes to termination conditions

Location:

mystic

Files:

• _math/approx.py (modified) (1 diff)
• mystic/termination.py (modified) (6 diffs)
• mystic/test_termination.py (added)

mystic/_math/approx.py

@@ -1 +1 @@
 #!/usr/bin/env python
-
 """
 tools for measuring equality
 """
+#NOTE: need to comapre to numpy.allclose...
+
 def _float_approx_equal(x, y, tol=1e-18, rel=1e-7):
     if tol is rel is None:

mystic/mystic/termination.py

@@ -17 +17 @@
     """cost of last iteration is < tolerance:
 
-cost[-1] < tolerance"""
+cost[-1] <= tolerance"""
     def _VTR(inst):
          hist = inst.energy_history
-         return hist[-1] < tolerance
+         return hist[-1] <= tolerance
     return _VTR
 
@@ -26 +26 @@
     """change in cost is < tolerance over a number of generations:
 
-cost[-g] - cost[-1] < tolerance, where g=generations"""
+cost[-g] - cost[-1] <= tolerance, where g=generations"""
     def _ChangeOverGeneration(inst):
          hist = inst.energy_history
          lg = len(hist)
          if lg <= generations: return False
-         return (hist[-generations]-hist[-1]) < tolerance
+         return (hist[-generations]-hist[-1]) <= tolerance
     return _ChangeOverGeneration
 
@@ -47 +47 @@
     return _NormalizedChangeOverGeneration
               
-def CandidateRelativeTolerance(xtol=1e-4, ftol=1e-4):
+def CandidateRelativeTolerance(xtol = 1e-4, ftol = 1e-4):
     """absolute difference in candidates is < tolerance:
 
@@ -72 +72 @@
 sum(abs(last_params - current_params)) <= tolerance"""
     def _SolutionImprovement(inst):
-        update = inst.bestSolution - inst.trialSolution #XXX: if inf - inf ?
+        best = numpy.array(inst.bestSolution)
+        trial = numpy.array(inst.trialSolution)
+        update = best - trial #XXX: if inf - inf ?
         answer = numpy.add.reduce(abs(update)) <= tolerance
         return answer
@@ -90 +92 @@
              lg = len(hist)
              #XXX: throws error when hist is shorter than generations ?
-             return lg > generations and (hist[-generations]-hist[-1]) < 0
+             return lg > generations and (hist[-generations]-hist[-1]) <= 0
          if not generations and fval == None: return True
          return abs(inst.bestEnergy-fval) <= abs(tolerance * fval)
     return _NormalizedCostTarget
 
-def VTRChangeOverGenerations(ftol = 0.005, gtol = 1e-6, generations = 30):
+def VTRChangeOverGeneration(ftol = 0.005, gtol = 1e-6, generations = 30):
     """change in cost is < gtol over a number of generations,
 or cost of last iteration is < ftol:
 
-cost[-g] - cost[-1] < gtol, where g=generations *or* cost[-1] < ftol."""
-    def _VTRChangeOverGenerations(inst):
+cost[-g] - cost[-1] <= gtol, where g=generations *or* cost[-1] <= ftol."""
+    def _VTRChangeOverGeneration(inst):
          hist = inst.energy_history
          lg = len(hist)
          #XXX: throws error when hist is shorter than generations ?
-         return (lg > generations and (hist[-generations]-hist[-1]) < gtol)\
-                or ( hist[-1] < ftol )
-    return _VTRChangeOverGenerations
+         return (lg > generations and (hist[-generations]-hist[-1]) <= gtol)\
+                or ( hist[-1] <= ftol )
+    return _VTRChangeOverGeneration
 
-def PopulationSpread(tolerance=1e-6):
+def PopulationSpread(tolerance = 1e-6):
     """normalized absolute deviation from best candidate is < tolerance:
 
-abs(params - params[0]) < tolerance"""
+abs(params - params[0]) <= tolerance"""
     def _PopulationSpread(inst):
          sim = numpy.array(inst.population)
@@ -117 +119 @@
          #    print "Warning: Invalid termination condition (nPop < 2)"
          #    return True
-         return all(abs(sim - sim[0]) <= abs(tolerance * sim[0]))
+         return numpy.all(abs(sim - sim[0]) <= abs(tolerance * sim[0]))
     return _PopulationSpread
 
-def GradientNormTolerance(tolerance=1e-5, norm=Inf): 
+def GradientNormTolerance(tolerance = 1e-5, norm = Inf): 
     """gradient norm is < tolerance, given user-supplied norm:
 
-sum( abs(gradient)**norm )**(1.0/norm) < tolerance"""
+sum( abs(gradient)**norm )**(1.0/norm) <= tolerance"""
     def _GradientNormTolerance(inst):
         try: