source: sasview/test/sasfit/test/utest_fit_smeared.py @ 9f7fbd9

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 9f7fbd9 was 9f7fbd9, checked in by Paul Kienzle <pkienzle@…>, 9 years ago

rewrite slit smearing for usans

  • Property mode set to 100644
File size: 6.9 KB
Line 
1"""
2    Unit tests for fitting module
3    @author M. Doucet
4"""
5import unittest
6import math
7
8import numpy
9from sas.fit.AbstractFitEngine import Model
10from sas.fit.Fitting import Fit
11from sas.dataloader.loader import Loader
12from sas.models.qsmearing import smear_selection
13from sas.models.CylinderModel import CylinderModel
14from sas.models.SphereModel import SphereModel
15
16class testFitModule(unittest.TestCase):
17    """ test fitting """
18   
19    def test_without_resolution(self):
20        """ Simple cylinder model fit  """
21       
22        out=Loader().load("cyl_400_20.txt")
23        # This data file has not error, add them
24        #out.dy = out.y
25       
26        fitter = Fit('bumps')
27        fitter.set_data(out,1)
28       
29        # Receives the type of model for the fitting
30        model1  = CylinderModel()
31        model1.setParam("scale", 1.0)
32        model1.setParam("radius",18)
33        model1.setParam("length", 397)
34        model1.setParam("sldCyl",3e-006 )
35        model1.setParam("sldSolv",0.0 )
36        model1.setParam("background", 0.0)
37        model = Model(model1)
38        pars1 =['length','radius','scale']
39        fitter.set_model(model,1,pars1)
40       
41        # What the hell is this line for?
42        fitter.select_problem_for_fit(id=1,value=1)
43        result1, = fitter.fit()
44        #print "result1",result1
45
46        self.assert_(result1)
47        self.assertTrue(len(result1.pvec) > 0)
48        self.assertTrue(len(result1.stderr) > 0)
49       
50        self.assertTrue( math.fabs(result1.pvec[0]-400.0)/3.0 < result1.stderr[0] )
51        self.assertTrue( math.fabs(result1.pvec[1]-20.0)/3.0  < result1.stderr[1] )
52        self.assertTrue( math.fabs(result1.pvec[2]-1)/3.0   < result1.stderr[2] )
53        self.assertTrue( result1.fitness < 1.0 )
54
55    def test_dispersion(self):
56        """
57            Cylinder fit with dispersion
58        """
59        alg = 'lm'
60        from bumps import fitters
61        fitters.FIT_DEFAULT = alg
62        #fitters.FIT_OPTIONS[alg].options.update(opts)
63        fitters.FIT_OPTIONS[alg].options.update(monitors=[])
64        self._dispersion(fitter = Fit('bumps'))
65
66    def _dispersion(self, fitter):
67        # Load data
68        # This data is for a cylinder with
69        #   length=400, radius=20, radius disp=5, scale=1e-10
70        out=Loader().load("cyl_400_20_disp5r.txt")
71        out.dy = numpy.zeros(len(out.y))
72        for i in range(len(out.y)):
73            out.dy[i] = math.sqrt(out.y[i])
74       
75        # Receives the type of model for the fitting
76        model1  = CylinderModel()
77        model1.setParam("scale", 10.0)
78        model1.setParam("radius",18)
79        model1.setParam("length", 397)
80        model1.setParam("sldCyl",3e-006 )
81        model1.setParam("sldSolv",0.0 )
82        model1.setParam("background", 0.0)
83
84        # Dispersion parameters
85        model1.dispersion['radius']['width'] = 0.25
86        model1.dispersion['radius']['npts'] = 50
87
88        model = Model(model1)
89
90        pars1 =['length','radius','scale','radius.width']
91        fitter.set_data(out,1)
92        fitter.set_model(model,1,pars1)
93        fitter.select_problem_for_fit(id=1,value=1)
94        #import time; T0 = time.time()
95        result1, = fitter.fit()
96        #print "time",time.time()-T0,fitter._engine.__class__.__name__
97       
98        self.assert_(result1)
99        self.assertTrue(len(result1.pvec)>0)
100        self.assertTrue(len(result1.stderr)>0)
101
102        #print [z for z in zip(result1.param_list,result1.pvec,result1.stderr)]
103        self.assertTrue( math.fabs(result1.pvec[0]-399.8)/3.0 < result1.stderr[0] )
104        self.assertTrue( math.fabs(result1.pvec[1]-17.5)/3.0  < result1.stderr[1] )
105        self.assertTrue( math.fabs(result1.pvec[2]-11.1)/3.0   < result1.stderr[2] )
106        self.assertTrue( math.fabs(result1.pvec[3]-0.276)/3.0   < result1.stderr[3] )
107        self.assertTrue( result1.fitness < 1.0 )
108       
109       
110class smear_testdata(unittest.TestCase):
111    """
112        Test fitting with the smearing operations
113        The output of the fits should be compated to fits
114        done with IGOR for the same models and data sets.
115    """
116    def setUp(self):
117        data = Loader().load("latex_smeared.xml")
118        self.data_res = data[0]
119        self.data_slit = data[1]
120       
121        self.sphere = SphereModel()
122        self.sphere.setParam('background', 0)
123        self.sphere.setParam('radius', 5000.0)
124        self.sphere.setParam('scale', 0.4)
125        self.sphere.setParam('sldSolv',0)
126        self.sphere.setParam('sldSph',1e-6)
127        #self.sphere.setParam('radius.npts', 30)
128        #self.sphere.setParam('radius.width',50)
129
130    def test_reso(self):
131
132        # Let the data module find out what smearing the
133        # data needs
134        smear = smear_selection(self.data_res)
135        self.assertEqual(smear.__class__.__name__, 'QSmearer')
136
137        # Fit
138        fitter = Fit('bumps')
139       
140        # Data: right now this is the only way to set the smearer object
141        # We should improve that and have a way to get access to the
142        # data for a given fit.
143        fitter.set_data(self.data_res,1)
144        fitter._engine.fit_arrange_dict[1].data_list[0].smearer = smear
145
146        # Model: maybe there's a better way to do this.
147        # Ideally we should have to create a new model from our sas model.
148        fitter.set_model(Model(self.sphere),1, ['radius','scale', 'background'])
149       
150        # Why do we have to do this...?
151        fitter.select_problem_for_fit(id=1,value=1)
152
153        # Perform the fit (might take a while)
154        result1, = fitter.fit()
155       
156        #print "v",result1.pvec
157        #print "dv",result1.stderr
158        #print "chisq(v)",result1.fitness
159
160        self.assertTrue( math.fabs(result1.pvec[0]-5000) < 20 )
161        self.assertTrue( math.fabs(result1.pvec[1]-0.48) < 0.02 )
162        self.assertTrue( math.fabs(result1.pvec[2]-0.060)  < 0.002 )
163
164
165    def test_slit(self):
166        smear = smear_selection(self.data_slit)
167        #self.assertEqual(smear.__class__.__name__, 'SlitSmearer')
168        self.assertEqual(smear.__class__.__name__, 'PySlitSmearer')
169
170        fitter = Fit('bumps')
171       
172        # Data: right now this is the only way to set the smearer object
173        # We should improve that and have a way to get access to the
174        # data for a given fit.
175        fitter.set_data(self.data_slit,1)
176        fitter._engine.fit_arrange_dict[1].data_list[0].smearer = smear
177        fitter._engine.fit_arrange_dict[1].data_list[0].qmax = 0.003
178       
179        # Model
180        fitter.set_model(Model(self.sphere),1, ['radius','scale'])
181        fitter.select_problem_for_fit(id=1,value=1)
182       
183        result1, = fitter.fit()
184
185        #print "v",result1.pvec
186        #print "dv",result1.stderr
187        #print "chisq(v)",result1.fitness
188
189        numpy.testing.assert_allclose(result1.pvec, [2323.466,0.22137], rtol=0.001)
190
191if __name__ == '__main__':
192    unittest.main()
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