Changeset 826

Timestamp:

09/18/15 09:44:18 (8 months ago)

Author:

mmckerns

Message:

remove old equals None; add suppressed and clipped; fix import in svctools

Location:

mystic

Files:

• examples_other/qld_svc1.py (moved) (moved from mystic/examples_other/test_svc1.py)
• examples_other/qld_svc2.py (moved) (moved from mystic/examples_other/test_svc2.py)
• mystic/forward_model.py (modified) (3 diffs)
• mystic/svctools.py (modified) (1 diff)
• mystic/termination.py (modified) (12 diffs)
• mystic/tools.py (modified) (2 diffs)

mystic/mystic/forward_model.py

@@ -118 +118 @@
     #XXX: addModelNew is a work in progress...
     '''
-    def addModelNew(self, model, name, outputFilter = Identity, inputChecker = NullChecker):
+    def addModelNew(self, model, name, outputFilter=Identity, inputChecker=NullChecker):
         """
 Adds a forward model factory to the cost factory.
@@ -199 +199 @@
         return _
 
-    def getCostFunction(self, evalpts, observations, sigma = None, metric = lambda x: sum(x*x)):
+    def getCostFunction(self, evalpts, observations, sigma=None, metric=lambda x: sum(x*x)):
         """
 Get a cost function that allows simultaneous evaluation of all forward models
@@ -249 +249 @@
                     x = x + ofilt(Gm(evalpts)) 
                 ind = ind+n
-            if sigma == None:
+            if sigma is None:
                 x = x - observations
             else:

mystic/mystic/svctools.py

@@ -26 +26 @@
 
 def SupportVectors(alpha, y=None, eps = 0):
-    import mystic.svmtools
-    sv = svmtools.SupportVectors(alpha,eps)
-    if y == None:
+    import mystic.svmtools as svm
+    sv = svm.SupportVectors(alpha,eps)
+    if y is None:
         return sv
     else:

mystic/mystic/termination.py

@@ -136 +136 @@
 
 # Factories that give termination conditions
-def VTR(tolerance = 0.005, target = 0.0):
+def VTR(tolerance=0.005, target=0.0):
     """cost of last iteration is < tolerance:
 
@@ -152 +152 @@
     return _VTR
 
-def ChangeOverGeneration(tolerance = 1e-6, generations = 30):
+def ChangeOverGeneration(tolerance=1e-6, generations=30):
     """change in cost is < tolerance over a number of generations:
 
@@ -169 +169 @@
     return _ChangeOverGeneration
 
-def NormalizedChangeOverGeneration(tolerance = 1e-4, generations = 10):
+def NormalizedChangeOverGeneration(tolerance=1e-4, generations=10):
     """normalized change in cost is < tolerance over number of generations:
 
@@ -188 +188 @@
     return _NormalizedChangeOverGeneration
               
-def CandidateRelativeTolerance(xtol = 1e-4, ftol = 1e-4):
+def CandidateRelativeTolerance(xtol=1e-4, ftol=1e-4):
     """absolute difference in candidates is < tolerance:
 
@@ -214 +214 @@
     return _CandidateRelativeTolerance
 
-def SolutionImprovement(tolerance = 1e-5):  
+def SolutionImprovement(tolerance=1e-5):  
     """sum of change in each parameter is < tolerance:
 
@@ -234 +234 @@
     return _SolutionImprovement
 
-def NormalizedCostTarget(fval = None, tolerance = 1e-6, generations = 30):
+def NormalizedCostTarget(fval=None, tolerance=1e-6, generations=30):
     """normalized absolute difference from given cost value is < tolerance:
 (if fval is not provided, then terminate when no improvement over g iterations)
@@ -248 +248 @@
         else: info = bool
         hist = inst.energy_history
-        if generations and fval == None:
+        if generations and fval is None:
             lg = len(hist)
             #XXX: throws error when hist is shorter than generations ?
@@ -254 +254 @@
                 return info(doc)
             return info(null)
-        if not generations and fval == None: return info(doc)
+        if not generations and fval is None: return info(doc)
         if abs(hist[-1]-fval) <= abs(tolerance * fval): return info(doc)
         return info(null)
@@ -260 +260 @@
     return _NormalizedCostTarget
 
-def VTRChangeOverGeneration(ftol = 0.005, gtol = 1e-6, generations = 30,
-                                                            target = 0.0):
+def VTRChangeOverGeneration(ftol=0.005, gtol=1e-6, generations=30, target=0.0):
     """change in cost is < gtol over a number of generations,
 or cost of last iteration is < ftol:
@@ -281 +280 @@
     return _VTRChangeOverGeneration
 
-def PopulationSpread(tolerance = 1e-6):
+def PopulationSpread(tolerance=1e-6):
     """normalized absolute deviation from best candidate is < tolerance:
 
@@ -299 +298 @@
     return _PopulationSpread
 
-def GradientNormTolerance(tolerance = 1e-5, norm = Inf): 
+def GradientNormTolerance(tolerance=1e-5, norm=Inf): 
     """gradient norm is < tolerance, given user-supplied norm:
 
@@ -326 +325 @@
     return _GradientNormTolerance
 
-def EvaluationLimits(generations = None, evaluations = None):
+def EvaluationLimits(generations=None, evaluations=None):
     """number of iterations is > generations,
 or number of function calls is > evaluations:

mystic/mystic/tools.py

@@ -35 +35 @@
     - partial: generate a function where some input has fixed values
     - insert_missing: return a sequence with the 'missing' elements inserted
+    - clipped: generate a function where values outside of bounds are clipped
+    - supressed: generate a function where values less than tol are supressed
+    - supress: supress small values less than tol
     - unpair: convert a 1D array of N pairs to two 1D arrays of N values
     - src: extract source code from a python code object
@@ -561 +564 @@
         func.__doc__ = f.__doc__
         func.mask = mask
+        return func
+    return dec
+
+
+def supress(x, tol=1e-8, clip=True):
+    """supress small values less than tol"""
+    from numpy import asarray, abs
+    x = asarray(list(x))
+    mask = abs(x) < tol
+    if not clip:
+        # preserve sum by spreading supressed values to the non-zero elements
+        x[mask==False] = (x + sum(x[mask])/(len(mask)-sum(mask)))[mask==False]
+    x[mask] = 0.0
+    return x.tolist()
+
+def supressed(tol=1e-8, exit=False, clip=True):
+    """generate a function, where values less than tol are supressed
+
+For example,
+    >>> @supressed(1e-8)
+    ... def square(x):
+    ...     return [i**2 for i in x]
+    ... 
+    >>> square([1e-8, 2e-8, 1e-9])
+    [1.00000000e-16, 4.00000000e-16, 0.00000000e+00]
+    >>> 
+    >>> from mystic.math.measures import normalize
+    >>> @supressed(1e-8, exit=True, clip=False)
+    ... def norm(x):
+    ...     return normalize(x, mass=1)
+    ... 
+    >>> norm([1e-8, 2e-8, 1e-16, 5e-9])
+    [0.28571428585034014, 0.5714285707482993, 0.0, 0.14285714340136055]
+    >>> sum(_)
+    1.0
+    """
+    def dec(f):
+        if exit:
+            def func(x, *args, **kwds):
+                return supress(f(x, *args, **kwds), tol, clip)
+        else:
+            def func(x, *args, **kwds):
+                return f(supress(x, tol, clip), *args, **kwds)
+        func.__wrapped__ = f
+        func.__doc__ = f.__doc__
+        return func
+    return dec
+
+def clipped(min=None, max=None, exit=False):
+    """generate a function, where values outside of bounds are clipped
+    """
+    from numpy import clip
+    def dec(f):
+        if exit:
+            def func(x, *args, **kwds):
+                return clip(f(x, *args, **kwds), min, max).tolist()
+        else:
+            def func(x, *args, **kwds):
+                return f(clip(x, min, max).tolist(), *args, **kwds)
+        func.__wrapped__ = f
+        func.__doc__ = f.__doc__
         return func
     return dec