source: sasview/park_integration/test/testpark.py @ 1c94a9f1

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 1c94a9f1 was cf3b781, checked in by Gervaise Alina <gervyh@…>, 16 years ago

need more tests.but usecase 3 implemented

  • Property mode set to 100644
File size: 3.1 KB
Line 
1"""
2    Unit tests for fitting module
3"""
4import unittest
5from sans.guitools.plottables import Theory1D
6from sans.guitools.plottables import Data1D
7from sans.fit.ScipyFitting import Parameter
8import math
9class testFitModule(unittest.TestCase):
10   
11    def test2models2dataonconstraint(self):
12        """ test fitting for two set of data  and one model"""
13        from sans.fit.Loader import Load
14        load= Load()
15        #Load the first set of data
16        load.set_filename("testdata1.txt")
17        load.set_values()
18        data1 = Data1D(x=[], y=[],dx=None, dy=None)
19        load.load_data(data1)
20       
21        #Load the second set of data
22        load.set_filename("testdata2.txt")
23        load.set_values()
24        data2 = Data1D(x=[], y=[],dx=None, dy=None)
25        load.load_data(data2)
26       
27        #Importing the Fit module
28        from sans.fit.Fitting import Fit
29        fitter= Fit()
30        # Receives the type of model for the fitting
31        from sans.guitools.LineModel import LineModel
32        model1  = LineModel()
33        model2  = LineModel()
34        #set engine for scipy
35        fitter.fit_engine('park')
36        engine = fitter.returnEngine()
37        #Do the fit
38        engine.set_param( model1,"M1", {'A':2.5,'B':4})
39        engine.set_model(model1,1)
40        engine.set_data(data1,1)
41       
42        import numpy
43        #print engine.fit({'A':2,'B':1},None,None)
44        #engine.remove_data(2,data2)
45        #engine.remove_model(2)
46       
47        engine.set_param( model2,"M2", {'A':2.5,'B':4})
48        engine.set_model(model2,2)
49        engine.set_data(data2,2)
50        print engine.fit({'A':2,'B':1},None,None)
51
52        if True:
53            import pylab
54            x1 = engine.problem[0].data.x
55            x2 = engine.problem[1].data.x
56            y1 = engine.problem[0].data.y
57            y2 = engine.problem[1].data.y
58            fx1 = engine.problem[0].data.fx
59            fx2 = engine.problem[1].data.fx
60            pylab.plot(x1,y1,'xb',x1,fx1,'-b',x2,y2,'xr',x2,fx2,'-r')
61            pylab.show()
62        if False:
63            print "current"
64            print engine.problem.chisq
65            print engine.problem.residuals
66            print "M1.y",engine.problem[0].data.y
67            print "M1.fx",engine.problem[0].data.fx
68            print "M1 delta",numpy.asarray(engine.problem[0].data.y)-engine.problem[0].data.fx
69            print "M2.y",engine.problem[0].data.y
70            print "M2.fx",engine.problem[0].data.fx
71            print "M2 delta",numpy.asarray(engine.problem[1].data.y)-engine.problem[1].data.fx
72            print "target"
73            engine.problem(numpy.array([4,2.5,4,2.5]))
74            print engine.problem.chisq
75            print engine.problem.residuals
76            print "M1.y",engine.problem[0].data.y
77            print "M1.fx",engine.problem[0].data.fx
78            print "M1 delta",numpy.asarray(engine.problem[0].data.y)-engine.problem[0].data.fx
79            print "M2.y",engine.problem[0].data.y
80            print "M2.fx",engine.problem[0].data.fx
81            print "M2 delta",numpy.asarray(engine.problem[1].data.y)-engine.problem[1].data.fx
82           
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