Source Code for Module park.optim.fitde

 1 -class FitDE(object): 
 2      """ 
 3      Differential evolution optimizer. 
 4   
 5      This implements `park.fit.Fitter`. 
 6      """ 
 7   
 8 -    def __init__(self): 
 9          """ 
10          Parameters are defined by `park.fitmc.fitmc`. 
11          """ 
12          pass 
13   
14 -    def fit(self, objective, handler): 
15          """ 
16          Run a monte carlo fit. 
17   
18          This procedure maps a local optimizer across a set of initial points. 
19          """ 
20          fitde(objective, self.localfit, self.start_points, handler) 
21   
22 -def fitde(fitness,n,handler): 
23      """ 
24      Run a differential evolution fit. 
25   
26      This procedure maps a local optimizer across a set of n initial points. 
27      The initial parameter value defined by the fitness parameters defines 
28      one initial point.  The remainder are randomly generated within the 
29      bounds of the problem. 
30   
31      localfit is the local optimizer to use.  It should be a bounded 
32      optimizer following the `park.fitmc.LocalFit` interface. 
33   
34      handler accepts updates to the current best set of fit parameters. 
35      See `park.fitresult.FitHandler` for details. 
36      """ 
37      P = fitutil.populate(fitness.fit_parameters(), radius=100, elitism=True) 
38      pmap.pmapreduce(MapMC(localfit,fitness), 
39                      CollectMC(n,handler), 
40                      P) 
41