[5893cdb] | 1 | """ |
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| 2 | Unit tests for fitting module |
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| 3 | """ |
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| 4 | import unittest |
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| 5 | from sans.fit.AbstractFitEngine import Model |
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| 6 | import math |
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| 7 | import numpy |
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| 8 | from sans.fit.Fitting import Fit |
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| 9 | from DataLoader.loader import Loader |
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| 10 | |
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| 11 | class testFitModule(unittest.TestCase): |
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| 12 | """ test fitting """ |
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| 13 | |
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| 14 | def test_scipy(self): |
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| 15 | """ Simple cylinder model fit (scipy) """ |
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| 16 | |
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| 17 | out=Loader().load("cyl_400_20.txt") |
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| 18 | # This data file has not error, add them |
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| 19 | out.dy = out.y |
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| 20 | |
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| 21 | fitter = Fit('scipy') |
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| 22 | fitter.set_data(out,1) |
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| 23 | |
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| 24 | # Receives the type of model for the fitting |
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| 25 | from sans.models.CylinderModel import CylinderModel |
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| 26 | model1 = CylinderModel() |
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| 27 | model1.setParam('contrast', 1) |
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| 28 | model = Model(model1) |
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| 29 | model.set(scale=1e-10) |
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| 30 | pars1 =['length','radius','scale'] |
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| 31 | fitter.set_model(model,1,pars1) |
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| 32 | |
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| 33 | # What the hell is this line for? |
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| 34 | fitter.select_problem_for_fit(Uid=1,value=1) |
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| 35 | result1 = fitter.fit() |
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| 36 | |
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| 37 | self.assert_(result1) |
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| 38 | self.assertTrue(len(result1.pvec)>0 or len(result1.pvec)==0 ) |
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| 39 | self.assertTrue(len(result1.stderr)> 0 or len(result1.stderr)==0) |
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| 40 | |
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| 41 | self.assertTrue( math.fabs(result1.pvec[0]-400.0)/3.0 < result1.stderr[0] ) |
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| 42 | self.assertTrue( math.fabs(result1.pvec[1]-20.0)/3.0 < result1.stderr[1] ) |
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| 43 | self.assertTrue( math.fabs(result1.pvec[2]-9.0e-12)/3.0 < result1.stderr[2] ) |
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| 44 | self.assertTrue( result1.fitness < 1.0 ) |
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| 45 | |
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| 46 | def test_scipy_dispersion(self): |
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| 47 | """ |
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| 48 | Cylinder fit with dispersion |
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| 49 | """ |
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| 50 | # Load data |
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| 51 | # This data is for a cylinder with |
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| 52 | # length=400, radius=20, radius disp=5, scale=1e-10 |
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| 53 | out=Loader().load("cyl_400_20_disp5r.txt") |
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| 54 | out.dy = numpy.zeros(len(out.y)) |
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| 55 | for i in range(len(out.y)): |
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| 56 | out.dy[i] = math.sqrt(out.y[i]) |
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| 57 | |
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| 58 | # Set up the fit |
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| 59 | fitter = Fit('scipy') |
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| 60 | # Receives the type of model for the fitting |
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| 61 | from sans.models.CylinderModel import CylinderModel |
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| 62 | model1 = CylinderModel() |
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| 63 | model1.setParam('contrast', 1) |
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| 64 | |
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| 65 | # Dispersion parameters |
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| 66 | model1.dispersion['radius']['width'] = 0.001 |
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| 67 | model1.dispersion['radius']['npts'] = 50 |
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| 68 | |
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| 69 | model = Model(model1) |
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| 70 | |
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| 71 | pars1 =['length','radius','scale','radius.width'] |
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| 72 | fitter.set_data(out,1) |
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| 73 | model.set(scale=1e-10) |
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| 74 | fitter.set_model(model,1,pars1) |
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| 75 | fitter.select_problem_for_fit(Uid=1,value=1) |
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| 76 | result1 = fitter.fit() |
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| 77 | |
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| 78 | self.assert_(result1) |
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| 79 | self.assertTrue(len(result1.pvec)>0 or len(result1.pvec)==0 ) |
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| 80 | self.assertTrue(len(result1.stderr)> 0 or len(result1.stderr)==0) |
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| 81 | |
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| 82 | self.assertTrue( math.fabs(result1.pvec[0]-400.0)/3.0 < result1.stderr[0] ) |
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| 83 | self.assertTrue( math.fabs(result1.pvec[1]-20.0)/3.0 < result1.stderr[1] ) |
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| 84 | self.assertTrue( math.fabs(result1.pvec[2]-1.0e-10)/3.0 < result1.stderr[2] ) |
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| 85 | self.assertTrue( math.fabs(result1.pvec[3]-5.0)/3.0 < result1.stderr[3] ) |
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| 86 | self.assertTrue( result1.fitness < 1.0 ) |
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| 87 | |
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| 88 | |
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| 89 | class smear_testdata(unittest.TestCase): |
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| 90 | """ |
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| 91 | Test fitting with the smearing operations |
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| 92 | The output of the fits should be compated to fits |
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| 93 | done with IGOR for the same models and data sets. |
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| 94 | """ |
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| 95 | def setUp(self): |
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| 96 | print "TEST DONE WITHOUT PROPER OUTPUT CHECK:" |
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| 97 | print " ---> TEST NEEDS TO BE COMPLETED" |
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| 98 | from sans.models.SphereModel import SphereModel |
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| 99 | data = Loader().load("latex_smeared.xml") |
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| 100 | self.data_res = data[0] |
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| 101 | self.data_slit = data[1] |
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| 102 | |
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| 103 | self.sphere = SphereModel() |
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| 104 | self.sphere.setParam('radius', 5000.0) |
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| 105 | self.sphere.setParam('scale', 1.0e-13) |
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| 106 | self.sphere.setParam('radius.npts', 30) |
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| 107 | self.sphere.setParam('radius.width',500) |
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| 108 | |
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| 109 | def test_reso(self): |
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| 110 | from DataLoader.qsmearing import smear_selection |
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| 111 | |
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| 112 | # Let the data module find out what smearing the |
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| 113 | # data needs |
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| 114 | smear = smear_selection(self.data_res) |
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| 115 | self.assertEqual(smear.__class__.__name__, 'QSmearer') |
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| 116 | |
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| 117 | # Fit |
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| 118 | fitter = Fit('scipy') |
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| 119 | |
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| 120 | # Data: right now this is the only way to set the smearer object |
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| 121 | # We should improve that and have a way to get access to the |
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| 122 | # data for a given fit. |
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| 123 | fitter.set_data(self.data_res,1) |
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| 124 | fitter._engine.fitArrangeDict[1].dList[0].smearer = smear |
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[5fcfca4] | 125 | print "smear ",smear |
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[5893cdb] | 126 | # Model: maybe there's a better way to do this. |
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| 127 | # Ideally we should have to create a new model from our sans model. |
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| 128 | fitter.set_model(Model(self.sphere),1, ['radius','scale']) |
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| 129 | |
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| 130 | # Why do we have to do this...? |
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| 131 | fitter.select_problem_for_fit(Uid=1,value=1) |
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| 132 | |
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| 133 | # Perform the fit (might take a while) |
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| 134 | result1 = fitter.fit() |
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| 135 | |
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| 136 | # Replace this with proper test once we know what the |
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| 137 | # result should be |
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| 138 | print result1.pvec |
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| 139 | print result1.stderr |
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| 140 | |
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| 141 | def test_slit(self): |
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| 142 | from DataLoader.qsmearing import smear_selection |
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| 143 | |
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| 144 | smear = smear_selection(self.data_slit) |
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| 145 | self.assertEqual(smear.__class__.__name__, 'SlitSmearer') |
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| 146 | |
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| 147 | # Fit |
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| 148 | fitter = Fit('scipy') |
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| 149 | |
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| 150 | # Data: right now this is the only way to set the smearer object |
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| 151 | # We should improve that and have a way to get access to the |
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| 152 | # data for a given fit. |
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| 153 | fitter.set_data(self.data_slit,1) |
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| 154 | fitter._engine.fitArrangeDict[1].dList[0].smearer = smear |
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| 155 | fitter._engine.fitArrangeDict[1].dList[0].qmax = 0.003 |
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| 156 | |
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| 157 | # Model |
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| 158 | fitter.set_model(Model(self.sphere),1, ['radius','scale']) |
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| 159 | fitter.select_problem_for_fit(Uid=1,value=1) |
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| 160 | |
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| 161 | result1 = fitter.fit() |
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| 162 | |
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| 163 | # Replace this with proper test once we know what the |
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| 164 | # result should be |
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| 165 | print result1.pvec |
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| 166 | print result1.stderr |
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| 167 | |
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| 168 | |
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| 169 | |
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| 170 | if __name__ == '__main__': |
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| 171 | unittest.main() |
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