Changeset 591

Timestamp:

11/19/12 17:05:38 (3 years ago)

Author:

mmckerns

Message:

added decorator in wrapper to provide discrete input
added test for memoized*_archived

Location:

branches/decorate

Files:

• surrogate.py (modified) (1 diff)
• test_timed_monitor.py (modified) (1 diff)
• test_wrapper.py (modified) (2 diffs)
• wrapper.py (modified) (2 diffs)

branches/decorate/surrogate.py

@@ -64 +64 @@
 
 from memoize import memoized0_round, memoized0_nopickle_round
+from memoize import memoized0_archived, memoized0_nopickle_archived
 #@memoized0_round(0)         # slower, but more robust
-@memoized0_nopickle_round(0)
+#@memoized0_nopickle_round(0)
+#@memoized0_archived()       # slower, but more robust
+@memoized0_nopickle_archived()
 def marc_surr(x):
   """calculate perforation area using a tanh-based model surrogate

branches/decorate/test_timed_monitor.py

@@ -174 +174 @@
   print " upper bounds: %s" % upper_bounds
 # print " ..."
+  try: model.load('surrogate.pkl')
+  except: pass
   diameter = UQ(RVstart,RVend,lower_bounds,upper_bounds)
+  try: model.dump('surrogate.pkl')
+  except: pass
 
 # EOF

branches/decorate/test_wrapper.py

@@ -128 +128 @@
 
 
+def test_discrete():
+
+  @discrete([1.0, 3.5, 5.5, 7.0])
+  def discrete_squared(x):
+    return x**2
+
+  assert discrete_squared(5.6) == 5.5**2
+  assert discrete_squared([1, 3]) == asarray([1.0, 3.5])**2
+  discrete_squared.samples([1.0, 7.0])
+  assert discrete_squared(5.6) == 7.0**2
+
+
 
 if __name__ is '__main__':
@@ -138 +150 @@
   test_bounded()
   test_mixedin()
+  test_discrete()
 
 

branches/decorate/wrapper.py

@@ -50 +50 @@
 
 
-from numpy import asarray, any, inf
+from numpy import asarray, any, inf, vectorize
 def bounded(min=None, max=None):
     """impose an infinite barrier box constraint on a function
@@ -107 +107 @@
 
 
+#from random import sample, choice
+def discrete(samples):
+    """impose a discrete set of input values for the selected function
+
+The function's input will be mapped to the given discrete set
+
+>>> @decorate([1.0, 2.0])
+... def identity(x):
+...   return x
+
+>>> identity([0.123, 1.789, 4.000])
+[1.0, 2.0, 2.0]""" #FIXME: should return same type as input
+    samples = [asarray(samples)]
+    samples[0].sort()
+
+    #XXX: refactor to use points_factory(samples)
+    def _points(alist):
+        alist = asarray(alist)
+        alist.sort()
+        samples[0] = alist
+
+    #XXX: refactor to use argnear_factory(samples)
+    def _argnear(xi):
+        arghi = sum(xi > samples[0])
+        arglo = max(0, arghi - 1) # minimum = x[0]
+        if arghi == len(samples[0]): 
+            arghi = arglo         # maximum = x[-1]
+        return arglo, arghi
+
+    def _near(xi, lo, hi):
+        if hi - xi < xi - lo: 
+            return hi
+        return lo
+
+    argnear = vectorize(_argnear)
+    near = vectorize(_near)
+
+    def dec(f):
+        def func(x, *args, **kwds):
+            arglo, arghi = argnear(x)
+            xp = near(x, samples[0][arglo], samples[0][arghi])
+            return f(xp, *args, **kwds)
+        func.samples = _points
+        return func
+    return dec
+
+
 # EOF