source: sasview/sansmodels/src/sans/models/test/utest_other_dispersity.py @ 7ef319e

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Last change on this file since 7ef319e was 26e4a24, checked in by Gervaise Alina <gervyh@…>, 15 years ago

reverse previous unittest
  • Property mode set to 100644
File size: 5.3 KB
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1"""
2    Unit tests for dispersion functionality of
3    C++ model classes
4"""
5
6import unittest, math, numpy
7
8class TestCylinder(unittest.TestCase):
9    """
10        Testing C++ Cylinder model
11    """
12    def setUp(self):
13        from sans.models.CylinderModel import CylinderModel
14        self.model= CylinderModel()
15       
16        self.model.setParam('scale', 1.0)
17        self.model.setParam('radius', 20.0)
18        self.model.setParam('length', 400.0)
19        self.model.setParam('contrast', 3.e-6)
20        self.model.setParam('background', 0.0)
21        self.model.setParam('cyl_theta', 0.0)
22        self.model.setParam('cyl_phi', 0.0)
23       
24    def test_simple(self):
25        self.assertAlmostEqual(self.model.run(0.001), 450.355, 3)
26        self.assertAlmostEqual(self.model.runXY([0.001,0.001]), 452.299, 3)
27       
28    def test_constant(self):
29        from sans.models.dispersion_models import DispersionModel
30        disp = DispersionModel()
31        self.model.setParam('scale', 10.0)
32        self.model.set_dispersion('radius', disp)
33        self.model.dispersion['radius']['width'] = 5.0
34        self.model.dispersion['radius']['npts'] = 100
35       
36        self.assertAlmostEqual(self.model.run(0.001), 4527.47250339, 3)
37        self.assertAlmostEqual(self.model.runXY([0.001, 0.001]), 4546.997777604715, 3)
38       
39    def test_gaussian(self):
40        from sans.models.dispersion_models import GaussianDispersion
41        disp = GaussianDispersion()
42        self.model.set_dispersion('radius', disp)
43        self.model.dispersion['radius']['width'] = 5.0
44        self.model.dispersion['radius']['npts'] = 100
45        self.model.setParam('scale', 10.0)
46       
47        self.assertAlmostEqual(self.model.run(0.001), 4723.32213339, 3)
48        self.assertAlmostEqual(self.model.runXY([0.001,0.001]), 4743.56, 2)
49       
50    def test_clone(self):
51        from sans.models.dispersion_models import GaussianDispersion
52        disp = GaussianDispersion()
53        self.model.set_dispersion('radius', disp)
54        self.model.dispersion['radius']['width'] = 5.0
55        self.model.dispersion['radius']['npts'] = 100
56        self.model.setParam('scale', 10.0)
57       
58        new_model = self.model.clone()
59        print "gaussian",self.model.run(0.001)
60        self.assertAlmostEqual(new_model.run(0.001), 4723.32213339, 3)
61        self.assertAlmostEqual(new_model.runXY([0.001,0.001]), 4743.56, 2)
62       
63    def test_schulz_zero(self):
64        from sans.models.dispersion_models import SchulzDispersion
65        disp = SchulzDispersion()
66        self.model.set_dispersion('radius', disp)
67        self.model.dispersion['radius']['width'] = 5.0
68        #self.model.dispersion['radius']['width'] = 0.0
69        self.model.dispersion['radius']['npts'] = 100
70        #self.model.setParam('scale', 1.0)
71        self.model.setParam('scale', 10.0)
72        print "schulz",self.model.run(0.001), self.model.dispersion
73        self.assertAlmostEqual(self.model.run(0.001), 450.355, 3)
74        self.assertAlmostEqual(self.model.runXY([0.001,0.001]), 452.299, 3)
75       
76    def test_lognormal_zero(self):
77        from sans.models.dispersion_models import LogNormalDispersion
78        disp = LogNormalDispersion()
79        self.model.set_dispersion('radius', disp)
80        self.model.dispersion['radius']['width'] = 5.0
81        #self.model.dispersion['radius']['width'] = 0.0
82        self.model.dispersion['radius']['npts'] = 100
83        #self.model.setParam('scale', 1.0)
84        self.model.setParam('scale', 10.0)
85        print "model dispersion",self.model.dispersion
86        print "lognormal",self.model.run(0.001)
87        self.assertAlmostEqual(self.model.run(0.001), 450.355, 3)
88        self.assertAlmostEqual(self.model.runXY([0.001,0.001]), 452.299, 3)
89       
90    def test_gaussian_zero(self):
91        from sans.models.dispersion_models import GaussianDispersion
92        disp = GaussianDispersion()
93        self.model.set_dispersion('radius', disp)
94        self.model.dispersion['radius']['width'] = 0.0
95        self.model.dispersion['radius']['npts'] = 100
96        self.model.setParam('scale', 1.0)
97       
98        self.assertAlmostEqual(self.model.run(0.001), 450.355, 3)
99        self.assertAlmostEqual(self.model.runXY([0.001,0.001]), 452.299, 3)
100       
101    def test_array(self):
102        """
103            Perform complete rotational average and
104            compare to 1D
105        """
106        from sans.models.dispersion_models import ArrayDispersion
107        disp_ph = ArrayDispersion()
108        disp_th = ArrayDispersion()
109       
110        values_ph = numpy.zeros(100)
111        values_th = numpy.zeros(100)
112        weights   = numpy.zeros(100)
113        for i in range(100):
114            values_ph[i]=(2.0*math.pi/99.0*i)
115            values_th[i]=(math.pi/99.0*i)
116            weights[i]=(1.0)
117       
118        disp_ph.set_weights(values_ph, weights)
119        disp_th.set_weights(values_th, weights)
120       
121        self.model.set_dispersion('cyl_theta', disp_th)
122        self.model.set_dispersion('cyl_phi', disp_ph)
123       
124        val_1d = self.model.run(math.sqrt(0.0002))
125        val_2d = self.model.runXY([0.01,0.01]) 
126       
127        self.assertTrue(math.fabs(val_1d-val_2d)/val_1d < 0.02)
128       
129
130if __name__ == '__main__':
131    unittest.main()
132   
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