source: sasview/park_integration/ParkFitting.py @ 70975f3

ESS_GUIESS_GUI_DocsESS_GUI_batch_fittingESS_GUI_bumps_abstractionESS_GUI_iss1116ESS_GUI_iss879ESS_GUI_iss959ESS_GUI_openclESS_GUI_orderingESS_GUI_sync_sascalccostrafo411magnetic_scattrelease-4.1.1release-4.1.2release-4.2.2release_4.0.1ticket-1009ticket-1094-headlessticket-1242-2d-resolutionticket-1243ticket-1249ticket885unittest-saveload
Last change on this file since 70975f3 was fadea71, checked in by Gervaise Alina <gervyh@…>, 16 years ago

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Line 
1"""
2    @organization: ParkFitting module contains SansParameter,Model,Data
3    FitArrange, ParkFit,Parameter classes.All listed classes work together to perform a
4    simple fit with park optimizer.
5"""
6import time
7import numpy
8import park
9from park import fit,fitresult
10from park import assembly
11from park.fitmc import FitSimplex, FitMC
12from sans.guitools.plottables import Data1D
13from Loader import Load
14from AbstractFitEngine import FitEngine,FitArrange,Model
15
16
17class ParkFit(FitEngine):
18    """
19        ParkFit performs the Fit.This class can be used as follow:
20        #Do the fit Park
21        create an engine: engine = ParkFit()
22        Use data must be of type plottable
23        Use a sans model
24       
25        Add data with a dictionnary of FitArrangeList where Uid is a key and data
26        is saved in FitArrange object.
27        engine.set_data(data,Uid)
28       
29        Set model parameter "M1"= model.name add {model.parameter.name:value}.
30        @note: Set_param() if used must always preceded set_model()
31             for the fit to be performed.
32        engine.set_param( model,"M1", {'A':2,'B':4})
33       
34        Add model with a dictionnary of FitArrangeList{} where Uid is a key and model
35        is save in FitArrange object.
36        engine.set_model(model,Uid)
37       
38        engine.fit return chisqr,[model.parameter 1,2,..],[[err1....][..err2...]]
39        chisqr1, out1, cov1=engine.fit({model.parameter.name:value},qmin,qmax)
40        @note: {model.parameter.name:value} is ignored in fit function since
41        the user should make sure to call set_param himself.
42    """
43    def __init__(self,data=[]):
44        """
45            Creates a dictionary (self.fitArrangeList={})of FitArrange elements
46            with Uid as keys
47        """
48        self.fitArrangeDict={}
49        self.paramList=[]
50       
51    def createAssembly(self):
52        """
53        Extract sansmodel and sansdata from self.FitArrangelist ={Uid:FitArrange}
54        Create parkmodel and park data ,form a list couple of parkmodel and parkdata
55        create an assembly self.problem=  park.Assembly([(parkmodel,parkdata)])
56        """
57        mylist=[]
58        listmodel=[]
59        i=0
60        for k,value in self.fitArrangeDict.iteritems():
61            parkmodel = value.get_model()
62            for p in parkmodel.parameterset:
63                if p.isfixed() and p._getname()in self.paramList:
64                    p.set([-numpy.inf,numpy.inf])
65            i+=1   
66            Ldata=value.get_data()
67            parkdata=self._concatenateData(Ldata)
68           
69            fitness=(parkmodel,parkdata)
70            mylist.append(fitness)
71   
72        self.problem =  park.Assembly(mylist)
73       
74   
75    def fit(self, qmin=None, qmax=None):
76        """
77            Performs fit with park.fit module.It can  perform fit with one model
78            and a set of data, more than two fit of  one model and sets of data or
79            fit with more than two model associated with their set of data and constraints
80           
81           
82            @param pars: Dictionary of parameter names for the model and their values.
83            @param qmin: The minimum value of data's range to be fit
84            @param qmax: The maximum value of data's range to be fit
85            @note:all parameter are ignored most of the time.Are just there to keep ScipyFit
86            and ParkFit interface the same.
87            @return result.fitness: Value of the goodness of fit metric
88            @return result.pvec: list of parameter with the best value found during fitting
89            @return result.cov: Covariance matrix
90        """
91       
92        self.createAssembly()
93        pars=self.problem.fit_parameters()
94        self.problem.eval()
95        localfit = FitSimplex()
96        localfit.ftol = 1e-8
97        fitter = FitMC(localfit=localfit)
98        list=self.problem[0]._parameterset()
99        #result = fit.fit(self.problem,
100        #             fitter=fitter,
101        #            handler= GuiUpdate(window))
102        result = fit.fit(self.problem,
103                         fitter=fitter,
104                         handler= fitresult.ConsoleUpdate(improvement_delta=0.1))
105
106       
107        if result !=None:
108            return result
109        else:
110            raise ValueError, "SVD did not converge"
111           
112       
113       
114   
115   
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