1 | """ |
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2 | This software was developed by the University of Tennessee as part of the |
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3 | Distributed Data Analysis of Neutron Scattering Experiments (DANSE) |
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4 | project funded by the US National Science Foundation. |
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5 | |
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6 | See the license text in license.txt |
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7 | |
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8 | copyright 2010, University of Tennessee |
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9 | """ |
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10 | import unittest |
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11 | import numpy |
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12 | from DataLoader.loader import Loader |
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13 | from DataLoader.data_info import Data1D |
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14 | from sans.invariant import invariant |
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15 | |
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16 | class TestLinearFit(unittest.TestCase): |
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17 | """ |
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18 | Test Line fit |
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19 | """ |
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20 | def setUp(self): |
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21 | x = numpy.asarray([1.,2.,3.,4.,5.,6.,7.,8.,9.]) |
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22 | y = numpy.asarray([1.,2.,3.,4.,5.,6.,7.,8.,9.]) |
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23 | dy = y/10.0 |
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24 | |
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25 | self.data = Data1D(x=x,y=y,dy=dy) |
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26 | |
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27 | def test_fit_linear_data(self): |
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28 | """ |
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29 | Simple linear fit |
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30 | """ |
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31 | |
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32 | # Create invariant object. Background and scale left as defaults. |
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33 | fit = invariant.FitFunctor(data=self.data) |
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34 | a,b = fit.fit() |
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35 | |
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36 | # Test results |
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37 | self.assertAlmostEquals(a, 1.0, 5) |
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38 | self.assertAlmostEquals(b, 0.0, 5) |
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39 | |
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40 | def test_fit_linear_data_with_noise(self): |
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41 | """ |
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42 | Simple linear fit with noise |
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43 | """ |
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44 | import random, math |
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45 | |
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46 | for i in range(len(self.data.y)): |
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47 | self.data.y[i] = self.data.y[i]+.1*random.random() |
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48 | |
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49 | # Create invariant object. Background and scale left as defaults. |
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50 | fit = invariant.FitFunctor(data=self.data) |
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51 | a,b = fit.fit() |
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52 | |
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53 | # Test results |
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54 | self.assertTrue(math.fabs(a-1.0)<0.05) |
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55 | self.assertTrue(math.fabs(b)<0.05) |
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56 | |
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57 | |
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58 | class TestInvariantCalculator(unittest.TestCase): |
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59 | """ |
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60 | Test Line fit |
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61 | """ |
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62 | def setUp(self): |
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63 | self.data = Loader().load("latex_smeared.xml")[0] |
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64 | |
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65 | def test_initial_data_processing(self): |
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66 | """ |
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67 | Test whether the background and scale are handled properly |
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68 | when creating an InvariantCalculator object |
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69 | """ |
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70 | length = len(self.data.x) |
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71 | self.assertEqual(length, len(self.data.y)) |
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72 | inv = invariant.InvariantCalculator(self.data) |
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73 | |
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74 | self.assertEqual(length, len(inv._data.x)) |
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75 | self.assertEqual(inv._data.x[0], self.data.x[0]) |
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76 | |
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77 | # Now the same thing with a background value |
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78 | bck = 0.1 |
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79 | inv = invariant.InvariantCalculator(self.data, background=bck) |
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80 | self.assertEqual(inv._background, bck) |
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81 | |
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82 | self.assertEqual(length, len(inv._data.x)) |
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83 | self.assertEqual(inv._data.y[0]+bck, self.data.y[0]) |
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84 | |
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85 | # Now the same thing with a scale value |
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86 | scale = 0.1 |
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87 | inv = invariant.InvariantCalculator(self.data, scale=scale) |
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88 | self.assertEqual(inv._scale, scale) |
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89 | |
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90 | self.assertEqual(length, len(inv._data.x)) |
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91 | self.assertAlmostEqual(inv._data.y[0]/scale, self.data.y[0],7) |
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92 | |
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93 | |
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94 | def test_incompatible_data_class(self): |
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95 | """ |
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96 | Check that only classes that inherit from Data1D are allowed as data. |
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97 | """ |
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98 | class Incompatible(): |
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99 | pass |
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100 | self.assertRaises(ValueError, invariant.InvariantCalculator, Incompatible()) |
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101 | |
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102 | |
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