[5893cdb] | 1 | """ |
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| 2 | Unit tests for fitting module |
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[eb575b0] | 3 | @author M. Doucet |
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[5893cdb] | 4 | """ |
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| 5 | import unittest |
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| 6 | import math |
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| 7 | import numpy |
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[6c00702] | 8 | from sans.fit.AbstractFitEngine import Model |
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[5893cdb] | 9 | from sans.fit.Fitting import Fit |
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[6c00702] | 10 | from sans.dataloader.loader import Loader |
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| 11 | from sans.models.qsmearing import smear_selection |
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| 12 | from sans.models.CylinderModel import CylinderModel |
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| 13 | from sans.models.SphereModel import SphereModel |
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[5893cdb] | 14 | |
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| 15 | class testFitModule(unittest.TestCase): |
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| 16 | """ test fitting """ |
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| 17 | |
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| 18 | def test_scipy(self): |
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| 19 | """ Simple cylinder model fit (scipy) """ |
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| 20 | |
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| 21 | out=Loader().load("cyl_400_20.txt") |
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| 22 | # This data file has not error, add them |
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[76f132a] | 23 | #out.dy = out.y |
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[5893cdb] | 24 | |
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| 25 | fitter = Fit('scipy') |
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| 26 | fitter.set_data(out,1) |
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| 27 | |
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| 28 | # Receives the type of model for the fitting |
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| 29 | model1 = CylinderModel() |
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[76f132a] | 30 | model1.setParam("scale", 1.0) |
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| 31 | model1.setParam("radius",18) |
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| 32 | model1.setParam("length", 397) |
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| 33 | model1.setParam("sldCyl",3e-006 ) |
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| 34 | model1.setParam("sldSolv",0.0 ) |
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| 35 | model1.setParam("background", 0.0) |
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[5893cdb] | 36 | model = Model(model1) |
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| 37 | pars1 =['length','radius','scale'] |
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| 38 | fitter.set_model(model,1,pars1) |
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| 39 | |
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| 40 | # What the hell is this line for? |
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[6c00702] | 41 | fitter.select_problem_for_fit(id=1,value=1) |
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| 42 | result1, = fitter.fit() |
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[76f132a] | 43 | #print "result1",result1 |
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| 44 | |
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[5893cdb] | 45 | self.assert_(result1) |
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[76f132a] | 46 | self.assertTrue(len(result1.pvec) > 0) |
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| 47 | self.assertTrue(len(result1.stderr) > 0) |
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[5893cdb] | 48 | |
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| 49 | self.assertTrue( math.fabs(result1.pvec[0]-400.0)/3.0 < result1.stderr[0] ) |
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| 50 | self.assertTrue( math.fabs(result1.pvec[1]-20.0)/3.0 < result1.stderr[1] ) |
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[76f132a] | 51 | self.assertTrue( math.fabs(result1.pvec[2]-1)/3.0 < result1.stderr[2] ) |
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[5893cdb] | 52 | self.assertTrue( result1.fitness < 1.0 ) |
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[76f132a] | 53 | |
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| 54 | def test_park_dispersion(self): |
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| 55 | """ |
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| 56 | Cylinder fit with dispersion |
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| 57 | """ |
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| 58 | self._dispersion(fitter = Fit('park')) |
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| 59 | |
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| 60 | def test_bumps_dispersion(self): |
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| 61 | """ |
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| 62 | Cylinder fit with dispersion |
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| 63 | """ |
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| 64 | alg = 'amoeba' |
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| 65 | from bumps import fitters |
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| 66 | fitters.FIT_DEFAULT = alg |
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| 67 | #fitters.FIT_OPTIONS[alg].options.update(opts) |
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| 68 | fitters.FIT_OPTIONS[alg].options.update(monitors=[]) |
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| 69 | self._dispersion(fitter = Fit('bumps')) |
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| 70 | |
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[5893cdb] | 71 | def test_scipy_dispersion(self): |
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| 72 | """ |
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| 73 | Cylinder fit with dispersion |
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| 74 | """ |
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[76f132a] | 75 | self._dispersion(fitter = Fit('scipy')) |
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| 76 | |
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| 77 | def _dispersion(self, fitter): |
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[5893cdb] | 78 | # Load data |
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| 79 | # This data is for a cylinder with |
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| 80 | # length=400, radius=20, radius disp=5, scale=1e-10 |
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| 81 | out=Loader().load("cyl_400_20_disp5r.txt") |
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| 82 | out.dy = numpy.zeros(len(out.y)) |
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| 83 | for i in range(len(out.y)): |
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| 84 | out.dy[i] = math.sqrt(out.y[i]) |
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| 85 | |
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| 86 | # Receives the type of model for the fitting |
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| 87 | model1 = CylinderModel() |
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[76f132a] | 88 | model1.setParam("scale", 10.0) |
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| 89 | model1.setParam("radius",18) |
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| 90 | model1.setParam("length", 397) |
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| 91 | model1.setParam("sldCyl",3e-006 ) |
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| 92 | model1.setParam("sldSolv",0.0 ) |
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| 93 | model1.setParam("background", 0.0) |
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[6c00702] | 94 | |
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[5893cdb] | 95 | # Dispersion parameters |
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[76f132a] | 96 | model1.dispersion['radius']['width'] = 0.25 |
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| 97 | model1.dispersion['radius']['npts'] = 50 |
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| 98 | |
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[5893cdb] | 99 | model = Model(model1) |
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[76f132a] | 100 | |
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[5893cdb] | 101 | pars1 =['length','radius','scale','radius.width'] |
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| 102 | fitter.set_data(out,1) |
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| 103 | fitter.set_model(model,1,pars1) |
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[6c00702] | 104 | fitter.select_problem_for_fit(id=1,value=1) |
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| 105 | result1, = fitter.fit() |
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[5893cdb] | 106 | |
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| 107 | self.assert_(result1) |
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[76f132a] | 108 | self.assertTrue(len(result1.pvec)>0) |
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| 109 | self.assertTrue(len(result1.stderr)>0) |
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| 110 | |
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| 111 | self.assertTrue( math.fabs(result1.pvec[0]-399.8)/3.0 < result1.stderr[0] ) |
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| 112 | self.assertTrue( math.fabs(result1.pvec[1]-17.5)/3.0 < result1.stderr[1] ) |
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| 113 | self.assertTrue( math.fabs(result1.pvec[2]-11.1)/3.0 < result1.stderr[2] ) |
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| 114 | self.assertTrue( math.fabs(result1.pvec[3]-0.276)/3.0 < result1.stderr[3] ) |
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[5893cdb] | 115 | self.assertTrue( result1.fitness < 1.0 ) |
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| 116 | |
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| 117 | |
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| 118 | class smear_testdata(unittest.TestCase): |
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| 119 | """ |
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| 120 | Test fitting with the smearing operations |
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| 121 | The output of the fits should be compated to fits |
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| 122 | done with IGOR for the same models and data sets. |
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| 123 | """ |
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| 124 | def setUp(self): |
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| 125 | data = Loader().load("latex_smeared.xml") |
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| 126 | self.data_res = data[0] |
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| 127 | self.data_slit = data[1] |
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| 128 | |
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| 129 | self.sphere = SphereModel() |
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[76f132a] | 130 | self.sphere.setParam('background', 0) |
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[5893cdb] | 131 | self.sphere.setParam('radius', 5000.0) |
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[76f132a] | 132 | self.sphere.setParam('scale', 0.4) |
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| 133 | self.sphere.setParam('sldSolv',0) |
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| 134 | self.sphere.setParam('sldSph',1e-6) |
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| 135 | #self.sphere.setParam('radius.npts', 30) |
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| 136 | #self.sphere.setParam('radius.width',50) |
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| 137 | |
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[5893cdb] | 138 | def test_reso(self): |
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[6c00702] | 139 | |
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[5893cdb] | 140 | # Let the data module find out what smearing the |
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| 141 | # data needs |
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| 142 | smear = smear_selection(self.data_res) |
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| 143 | self.assertEqual(smear.__class__.__name__, 'QSmearer') |
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| 144 | |
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| 145 | # Fit |
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| 146 | fitter = Fit('scipy') |
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| 147 | |
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| 148 | # Data: right now this is the only way to set the smearer object |
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| 149 | # We should improve that and have a way to get access to the |
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| 150 | # data for a given fit. |
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| 151 | fitter.set_data(self.data_res,1) |
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[6c00702] | 152 | fitter._engine.fit_arrange_dict[1].data_list[0].smearer = smear |
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[76f132a] | 153 | |
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[5893cdb] | 154 | # Model: maybe there's a better way to do this. |
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| 155 | # Ideally we should have to create a new model from our sans model. |
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[76f132a] | 156 | fitter.set_model(Model(self.sphere),1, ['radius','scale', 'background']) |
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[5893cdb] | 157 | |
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| 158 | # Why do we have to do this...? |
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[6c00702] | 159 | fitter.select_problem_for_fit(id=1,value=1) |
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[76f132a] | 160 | |
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[5893cdb] | 161 | # Perform the fit (might take a while) |
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[6c00702] | 162 | result1, = fitter.fit() |
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[5893cdb] | 163 | |
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[76f132a] | 164 | #print "v",result1.pvec |
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| 165 | #print "dv",result1.stderr |
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| 166 | #print "chisq(v)",result1.fitness |
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| 167 | |
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| 168 | self.assertTrue( math.fabs(result1.pvec[0]-5000) < 20 ) |
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| 169 | self.assertTrue( math.fabs(result1.pvec[1]-0.48) < 0.02 ) |
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| 170 | self.assertTrue( math.fabs(result1.pvec[2]-0.060) < 0.002 ) |
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| 171 | |
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| 172 | |
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[5893cdb] | 173 | def test_slit(self): |
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| 174 | smear = smear_selection(self.data_slit) |
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| 175 | self.assertEqual(smear.__class__.__name__, 'SlitSmearer') |
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| 176 | |
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| 177 | fitter = Fit('scipy') |
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| 178 | |
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| 179 | # Data: right now this is the only way to set the smearer object |
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| 180 | # We should improve that and have a way to get access to the |
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| 181 | # data for a given fit. |
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| 182 | fitter.set_data(self.data_slit,1) |
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[6c00702] | 183 | fitter._engine.fit_arrange_dict[1].data_list[0].smearer = smear |
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| 184 | fitter._engine.fit_arrange_dict[1].data_list[0].qmax = 0.003 |
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[5893cdb] | 185 | |
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| 186 | # Model |
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| 187 | fitter.set_model(Model(self.sphere),1, ['radius','scale']) |
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[6c00702] | 188 | fitter.select_problem_for_fit(id=1,value=1) |
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[5893cdb] | 189 | |
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[6c00702] | 190 | result1, = fitter.fit() |
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[5893cdb] | 191 | |
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[76f132a] | 192 | #print "v",result1.pvec |
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| 193 | #print "dv",result1.stderr |
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| 194 | #print "chisq(v)",result1.fitness |
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[5893cdb] | 195 | |
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[76f132a] | 196 | self.assertTrue( math.fabs(result1.pvec[0]-2340) < 20 ) |
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| 197 | self.assertTrue( math.fabs(result1.pvec[1]-0.010) < 0.002 ) |
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| 198 | |
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[5893cdb] | 199 | if __name__ == '__main__': |
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| 200 | unittest.main() |
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