Changeset 819

Timestamp:

08/12/15 08:26:54 (9 months ago)

Author:

mmckerns

Message:

use mystic.constraints.integers in integer_programming examples;
add docs to mystic.constraints.unique (and impose_unique)

Location:

mystic

Files:

• examples2/integer_programming.py (modified) (2 diffs)
• examples2/integer_programming_alt.py (modified) (2 diffs)
• mystic/constraints.py (modified) (5 diffs)

mystic/examples2/integer_programming.py

@@ -39 +39 @@
 pf = generate_penalty(generate_conditions(equations))
 
-from numpy import round as npround
+from mystic.constraints import integers
+
+@integers()
+def round(x):
+  return x
+
 
 if __name__ == '__main__':
@@ -46 +51 @@
     from mystic.math import almostEqual
 
-    result = diffev2(objective, x0=bounds, bounds=bounds, penalty=pf, constraints=npround, npop=20, gtol=50, disp=True, full_output=True)
+    result = diffev2(objective, x0=bounds, bounds=bounds, penalty=pf, constraints=round, npop=20, gtol=50, disp=True, full_output=True)
 
     print result[0]

mystic/examples2/integer_programming_alt.py

@@ -38 +38 @@
     return round(solver(x))
 
-from numpy import round as npround
+# better is to constrain to integers, penalize otherwise
+from mystic.constraints import integers
+
+@integers()
+def round(x):
+  return x
+
 
 if __name__ == '__main__':
@@ -45 +51 @@
     from mystic.math import almostEqual
 
-    result = diffev2(objective, x0=bounds, bounds=bounds, penalty=penalty, constraints=npround, npop=20, gtol=50, disp=True, full_output=True)
+    result = diffev2(objective, x0=bounds, bounds=bounds, penalty=penalty, constraints=round, npop=30, gtol=50, disp=True, full_output=True)
 
     print result[0]

mystic/mystic/constraints.py

@@ -243 +243 @@
 Input:
     constraints -- a constraints solver function or a penalty function
-    guess -- list of parameter values prposed to solve the constraints
+    guess -- list of parameter values proposed to solve the constraints
     tol -- residual error magnitude for which constraints are considered solved
+
+    For example:
+    >>> @normalized()
+    ... def constraint(x):
+    ...   return x
+    ... 
+    >>> constraint([.5,.5])
+    [0.5, 0.5]
+    >>> issolution(constraint, [.5,.5])
+    True
+    >>> 
+    >>> from mystic.penalty import quadratic_inequality
+    >>> @quadratic_inequality(lambda x: x[0] - x[1] + 10)
+    ... def penalty(x):
+    ...   return 0.0
+    ... 
+    >>> penalty([-10,.5])
+    0.0
+    >>> issolution(penalty, [-10,.5])
+    True
     """
     if hasattr(constraints, 'error'):
@@ -555 +575 @@
     range(min(seq),max(seq)). If full is a sequence (list or set), then
     unique values are selected from the given sequence. 
+
+    For example:
+    >>> unique([1,2,3,1,2,4], range(11))
+    [1, 2, 3, 9, 8, 4]
+    >>> unique([1,2,3,1,2,9], range(11))
+    [1, 2, 3, 8, 5, 9]
+    >>> try:
+    ...     unique([1,2,3,1,2,13], range(11))
+    ... except ValueError:
+    ...     pass
+    ...
+    >>>
+    >>> unique([1,2,3,1,2,4], {'min':0, 'max':11})
+    [1, 2, 3, 4.175187820357143, 2.5407265707465716, 4]
+    >>> mcon.unique([1,2,3,1,2,4], float)
+    [1, 2, 3, 1.012375036824941, 3.9821250727509905, 4]
+    >>> unique([1,2,3,1,2,10], int)
+    [1, 2, 3, 9, 6, 10]
+    >>> try:
+    ...     unique([1,2,3,1,2,4], int)
+    ... except ValueError:
+    ...     pass
+    ...
     """
     unique = set()
@@ -615 +658 @@
 
 def impose_unique(seq=None):
-    """ensure all values are unique and found in the given set"""
+    """ensure all values are unique and found in the given set
+
+    For example:
+    >>> @impose_unique(range(11))
+    ... def doit(x):
+    ...     return x
+    ... 
+    >>> doit([1,2,3,1,2,4])
+    [1, 2, 3, 9, 8, 4]
+    >>> doit([1,2,3,1,2,10])
+    [1, 2, 3, 8, 5, 10]
+    >>> try:
+    ...     doit([1,2,3,1,2,13])
+    ... except ValueError:
+    ...     print "Bad Input"
+    ...
+    Bad Input
+"""
     def dec(f):
         def func(x,*args,**kwds):
@@ -624 +684 @@
 
 #XXX: enable near_integers and has_unique on selected members of x?
+#FIXME: the following don't seem to belong in 'mystic.constraints'
 
 from numpy import round, abs
@@ -638 +699 @@
 
 # EOF
-
-# EOF