Changeset 610 for branches

Timestamp:

12/13/12 12:43:16 (3 years ago)

Author:

mmckerns

Message:

added isbounded; minor documentation improvements; extended as_constraints test

Location:

branches/decorate

Files:

• constraints.py (modified) (1 diff)
• penalty.py (modified) (1 diff)
• test_penalty.py (modified) (6 diffs)
• wrapper.py (modified) (2 diffs)

branches/decorate/constraints.py

@@ +1 @@
+#!/usr/bin/env python
+
 # XXX: provide the below from measures, which from bounded?, and ...generic?
 # XXX: with_*** is a 'wrap' constraint, what about 'nested' constraints?

branches/decorate/penalty.py

@@ +1 @@
+#!/usr/bin/env python
+
+"""
+References:
+   [1] http://en.wikipedia.org/wiki/Penalty_method
+   [2] Applied Optimization with MATLAB Programming, by Venkataraman.
+       Wiley, 2nd edition, 2009.
+   [3] http://www.srl.gatech.edu/education/ME6103/Penalty-Barrier.ppt
+   [4] "An Augmented Lagrange Multiplier Based Method for Mixed Integer
+       Discrete Continuous Optimization and Its Applications to Mechanical
+       Design", by Kannan and Kramer. 1994.
+"""
 
 def with_penalty(ptype, *args, **kwds):

branches/decorate/test_penalty.py

@@ -19 +19 @@
     return abs(sum(x) - 5.0)
 
-  from mystic.solvers import fmin_powell
+  from mystic.solvers import fmin
   from numpy import array
   x = array([1,2,3,4,5])
-  y = fmin_powell(cost, x, penalty=penalty, disp=False)
+  y = fmin(cost, x, penalty=penalty, disp=False)
 
   assert round(mean(y)) == 5.0
@@ -82 +82 @@
 
   ndim = 3
-  constraints = as_constraint(penalty, solver='fmin_powell')
+  constraints = as_constraint(penalty, solver='fmin')
   #XXX: this is expensive to evaluate, as there are nested optimizations
 
@@ -91 +91 @@
   assert round(mean(_x)) == 5.0
   assert round(spread(_x)) == 5.0
+  assert round(penalty(_x)) == 0.0
 
   def cost(x):
@@ -96 +97 @@
 
   npop = ndim*3
-  from mystic.solvers import fmin_powell, diffev
+  from mystic.solvers import diffev
   y = diffev(cost, x, npop, constraints=constraints, disp=False, gtol=10)
 
@@ -122 +123 @@
     return abs(sum(x) - 5.0)
 
-  from mystic.solvers import fmin_powell
-  y = fmin_powell(cost, x, penalty=penalty, disp=False)
+  from mystic.solvers import fmin
+  y = fmin(cost, x, penalty=penalty, disp=False)
 
   assert round(mean(y)) == 5.0
@@ -140 +141 @@
     return abs(sum(x) - 5.0)
 
-  from mystic.solvers import fmin_powell
+  from mystic.solvers import fmin
   from numpy import array
   x = array([1,2,3,4,5])
-  y = fmin_powell(cost, x, penalty=penalty, disp=False)
+  y = fmin(cost, x, penalty=penalty, disp=False)
 
   assert round(mean(y)) == 5.0

branches/decorate/wrapper.py

@@ +1 @@
+#!/usr/bin/env python
+
 #XXX: be mindful if the decorators restrict to functions that expect arrays
 #     compare against the originals for restrictions
 
 #XXX: when_decorated registers methods to 'populate up' when is decorated ?
-
 
 from mystic.tools import Null
@@ -83 +84 @@
 
 
+def isbounded(func, x, min=None, max=None):
+    """return False if func(x) evaluates outside the bounds, True otherwise.
+
+Inputs:
+    func -- a function of x.
+    x -- a list of parameters.
+
+Additional Inputs:
+    min -- list of lower bounds on parameters.
+    max -- list of upper bounds on parameters.
+"""
+    #from numpy import clip, array   #XXX: numpy.clip doesn't need/use func
+    #return all(clip(x,min,max) == array(x))
+    bound = bounded(min,max)
+    wrapped = bound(func)
+    if wrapped(x) == inf:
+        return False    
+    return True
+
+
 def mixedin(scale=1.0, shift=0.0, mixin=lambda x:x, normalized=False):
   """build a function from the weighted sum of two functions