[4a0536a] | 1 | """ |
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| 2 | Unit tests for fitting module |
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| 3 | """ |
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[93c2ef2] | 4 | import unittest |
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[4a0536a] | 5 | from sans.guitools.plottables import Theory1D |
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| 6 | from sans.guitools.plottables import Data1D |
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[7705306] | 7 | from sans.fit.ScipyFitting import Parameter |
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[93c2ef2] | 8 | import math |
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[4a0536a] | 9 | class testFitModule(unittest.TestCase): |
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| 10 | """ test fitting """ |
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| 11 | def testLoader(self): |
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| 12 | """ |
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| 13 | test module Load |
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| 14 | """ |
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[7705306] | 15 | from sans.fit.Loader import Load |
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[4a0536a] | 16 | load= Load() |
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| 17 | |
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| 18 | load.set_filename("testdata_line.txt") |
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| 19 | self.assertEqual(load.get_filename(),"testdata_line.txt") |
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| 20 | load.set_values() |
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| 21 | x=[] |
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| 22 | y=[] |
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| 23 | dx=[] |
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| 24 | dy=[] |
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| 25 | |
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| 26 | x,y,dx,dy = load.get_values() |
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| 27 | |
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| 28 | # test that values have been loaded |
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| 29 | self.assertNotEqual(x, None) |
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| 30 | self.assertNotEqual(y, []) |
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| 31 | self.assertNotEqual(dy, None) |
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| 32 | self.assertEqual(len(x),len(y)) |
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| 33 | self.assertEqual(len(dy),len(y)) |
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| 34 | |
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| 35 | # test data the two plottables contained values loaded |
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| 36 | data1 = Theory1D(x=[], y=[], dy=None) |
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| 37 | data2 = Data1D(x=[], y=[],dx=None, dy=None) |
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| 38 | data1.name = "data1" |
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| 39 | data2.name = "data2" |
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| 40 | load.load_data(data1) |
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| 41 | load.load_data(data2) |
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| 42 | |
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| 43 | |
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| 44 | for i in range(len(x)): |
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| 45 | self.assertEqual(data2.x[i],x[i]) |
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| 46 | self.assertEqual(data1.y[i],y[i]) |
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| 47 | self.assertEqual(data2.y[i],y[i]) |
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| 48 | self.assertEqual(data1.dx[i],dx[i]) |
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| 49 | self.assertEqual(data2.dy[i],dy[i]) |
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| 50 | self.assertEqual(data1.x[i],data2.x[i]) |
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| 51 | self.assertEqual(data2.y[i],data2.y[i]) |
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| 52 | |
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| 53 | |
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[f24b8f4] | 54 | def testfit_1Data_1Model(self): |
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| 55 | """ test fitting for one data and one model""" |
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| 56 | #load data |
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[7705306] | 57 | from sans.fit.Loader import Load |
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[4a0536a] | 58 | load= Load() |
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| 59 | load.set_filename("testdata_line.txt") |
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| 60 | load.set_values() |
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| 61 | data1 = Data1D(x=[], y=[],dx=None, dy=None) |
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| 62 | load.load_data(data1) |
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[93c2ef2] | 63 | |
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[f24b8f4] | 64 | #Importing the Fit module |
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[7705306] | 65 | from sans.fit.Fitting import Fit |
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[3701620] | 66 | fitter= Fit() |
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| 67 | fitter.fit_engine('scipy') |
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| 68 | engine = fitter.returnEngine() |
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[4a0536a] | 69 | # Receives the type of model for the fitting |
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| 70 | from sans.guitools.LineModel import LineModel |
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[93c2ef2] | 71 | model = LineModel() |
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| 72 | |
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[3701620] | 73 | #Do the fit SCIPY |
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| 74 | engine.set_data(data1,1) |
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| 75 | engine.set_model(model,1) |
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[f24b8f4] | 76 | |
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[3701620] | 77 | chisqr1, out1, cov1=engine.fit({'A':2,'B':1},None,None) |
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| 78 | """ testing SCIPy results""" |
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| 79 | self.assert_(math.fabs(out1[1]-2.5)/math.sqrt(cov1[1][1]) < 2) |
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| 80 | self.assert_(math.fabs(out1[0]-4.0)/math.sqrt(cov1[0][0]) < 2) |
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| 81 | self.assert_(chisqr1/len(data1.x) < 2) |
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| 82 | # PARK |
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| 83 | fitter= Fit() |
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| 84 | fitter.fit_engine('park') |
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| 85 | engine = fitter.returnEngine() |
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[f24b8f4] | 86 | |
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[3701620] | 87 | #Do the fit |
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| 88 | engine.set_data(data1,1) |
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| 89 | engine.set_model(model,1) |
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| 90 | |
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| 91 | engine.fit({'A':2,'B':1},None,None) |
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| 92 | """ |
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| 93 | |
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| 94 | self.assert_(math.fabs(out2[1]-2.5)/math.sqrt(cov2[1][1]) < 2) |
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| 95 | self.assert_(math.fabs(out2[0]-4.0)/math.sqrt(cov2[0][0]) < 2) |
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| 96 | self.assert_(chisqr2/len(data1.x) < 2) |
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| 97 | |
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| 98 | self.assertEqual(out1[1], out2[1]) |
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| 99 | self.assertEquals(out1[0], out2[0]) |
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| 100 | self.assertEquals(cov1[0][0], cov2[0][0]) |
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| 101 | self.assertEquals(cov1[1][1], cov2[1][1]) |
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| 102 | self.assertEquals(chisqr1, chisqr2) |
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| 103 | """ |
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[f24b8f4] | 104 | def testfit_2Data_1Model(self): |
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[3701620] | 105 | """ test fitting for two set of data and one model""" |
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[7705306] | 106 | from sans.fit.Loader import Load |
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[f24b8f4] | 107 | load= Load() |
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| 108 | #Load the first set of data |
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| 109 | load.set_filename("testdata1.txt") |
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| 110 | load.set_values() |
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| 111 | data1 = Data1D(x=[], y=[],dx=None, dy=None) |
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| 112 | load.load_data(data1) |
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| 113 | |
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| 114 | #Load the second set of data |
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| 115 | load.set_filename("testdata2.txt") |
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| 116 | load.set_values() |
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| 117 | data2 = Data1D(x=[], y=[],dx=None, dy=None) |
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| 118 | load.load_data(data2) |
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| 119 | |
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| 120 | #Importing the Fit module |
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[7705306] | 121 | from sans.fit.Fitting import Fit |
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[3701620] | 122 | fitter= Fit() |
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[f24b8f4] | 123 | # Receives the type of model for the fitting |
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| 124 | from sans.guitools.LineModel import LineModel |
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| 125 | model = LineModel() |
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[3701620] | 126 | #set engine for scipy |
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| 127 | fitter.fit_engine('scipy') |
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| 128 | engine = fitter.returnEngine() |
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[f24b8f4] | 129 | #Do the fit |
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[3701620] | 130 | engine.set_model(model,1) |
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| 131 | engine.set_data(data1,1) |
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| 132 | engine.set_data(data2,1) |
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| 133 | |
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| 134 | |
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| 135 | chisqr1, out1, cov1= engine.fit({'A':2,'B':1},None,None) |
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| 136 | |
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| 137 | """ Testing results for SCIPY""" |
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| 138 | self.assert_(math.fabs(out1[1]-2.5)/math.sqrt(cov1[1][1]) < 2) |
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| 139 | self.assert_(math.fabs(out1[0]-4.0)/math.sqrt(cov1[0][0]) < 2) |
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| 140 | self.assert_(chisqr1/len(data1.x+data2.x) < 2) |
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| 141 | #self.assert_(chisqr1/len(data2.x) < 2) |
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| 142 | |
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| 143 | #set engine for park |
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| 144 | fitter= Fit() |
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| 145 | fitter.fit_engine('park') |
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| 146 | engine = fitter.returnEngine() |
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| 147 | #Do the fit |
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| 148 | engine.set_data(data1,1) |
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| 149 | engine.set_model(model,1) |
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| 150 | engine.set_data(data2,1) |
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| 151 | engine.fit({'A':2,'B':1},None,None) |
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| 152 | """ |
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| 153 | chisqr2, out2, cov2= engine.fit({'A':2,'B':1},None,None) |
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| 154 | |
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| 155 | |
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| 156 | self.assert_(math.fabs(out2[1]-2.5)/math.sqrt(cov2[1][1]) < 2) |
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| 157 | self.assert_(math.fabs(out2[0]-4.0)/math.sqrt(cov2[0][0]) < 2) |
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| 158 | self.assert_(chisqr2/len(data1.x) < 2) |
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| 159 | self.assert_(chisqr2/len(data2.x) < 2) |
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| 160 | |
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| 161 | self.assertEqual(out1[0],out2[0]) |
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| 162 | self.assertEqual(out1[1],out2[1]) |
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| 163 | self.assertEqual(chisqr1,chisqr2) |
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| 164 | self.assertEqual(cov1[0][0],cov2[0][0]) |
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| 165 | self.assertEqual(cov1[1][1],cov2[1][1]) |
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| 166 | """ |
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