class TestEllipticalCylinder(unittest.TestCase):
"""
Testing C++ Cylinder model
"""
def setUp(self):
from sas.models.EllipticalCylinderModel import EllipticalCylinderModel
self.model= EllipticalCylinderModel()
self.model.setParam('scale', 1.0)
self.model.setParam('r_minor', 20.0)
self.model.setParam('r_ratio', 1.5)
self.model.setParam('length', 400.0)
self.model.setParam('sldCyl', 4.0e-6)
self.model.setParam('sldSolv', 1.0e-6)
self.model.setParam('background', 0.0)
self.model.setParam('cyl_theta', 90)
self.model.setParam('cyl_phi', 0.0)
self.model.setParam('cyl_psi', 0.0)
def test_simple(self):
"""
Test simple 1D and 2D values
Numbers taken from model that passed validation, before
the update to C++ underlying class.
"""
self.assertAlmostEqual(self.model.run(0.001),
675.50440232504991, 3)
self.assertAlmostEqual(self.model.runXY([0.001,0.001]),
669.5173937622792, 0)
def test_dispersion(self):
"""
Test with dispersion
"""
from sas.models.DisperseModel import DisperseModel
disp = DisperseModel(self.model, ['r_minor', 'r_ratio', 'length'],
[5, 0.25, 50])
disp.setParam('n_pts', 10)
self.assertAlmostEqual(disp.run(0.001), 711.18048194151925, 3)
self.assertAlmostEqual(disp.runXY([0.001,0.001]), 704.63525988095705, 0)
def test_new_disp(self):
from sas.models.dispersion_models import GaussianDispersion
disp_rm = GaussianDispersion()
self.model.set_dispersion('r_minor', disp_rm)
self.model.dispersion['r_minor']['width'] = 0.25
self.model.dispersion['r_minor']['npts'] = 10
self.model.dispersion['r_minor']['nsigmas'] = 2
disp_rr = GaussianDispersion()
self.model.set_dispersion('r_ratio', disp_rr)
self.model.dispersion['r_ratio']['width'] = 0.25/1.5
self.model.dispersion['r_ratio']['npts'] = 10
self.model.dispersion['r_ratio']['nsigmas'] = 2
disp_len = GaussianDispersion()
self.model.set_dispersion('length', disp_len)
self.model.dispersion['length']['width'] = 50.0/400
self.model.dispersion['length']['npts'] = 10
self.model.dispersion['length']['nsigmas'] = 2
self.assertAlmostEqual(self.model.run(0.001),
1.23925910*711.18048194151925, 3)
self.assertAlmostEqual(self.model.runXY([0.001,0.001]),
1.238955*704.63525988095705, 0)
def test_array(self):
"""
Perform complete rotational average and
compare to 1D
"""
from sas.models.dispersion_models import ArrayDispersion
disp_ph = ArrayDispersion()
disp_th = ArrayDispersion()
disp_ps = ArrayDispersion()
values_ph = numpy.zeros(100)
values_th = numpy.zeros(100)
values_ps = numpy.zeros(100)
weights = numpy.zeros(100)
for i in range(100):
values_ps[i]=(360/99.0*i)
values_ph[i]=(360/99.0*i)
values_th[i]=(180/99.0*i)
weights[i]=(1.0)
disp_ph.set_weights(values_ph, weights)
disp_th.set_weights(values_th, weights)
disp_ps.set_weights(values_ps, weights)
self.model.set_dispersion('cyl_theta', disp_th)
self.model.set_dispersion('cyl_phi', disp_ph)
self.model.set_dispersion('cyl_psi', disp_ps)
val_1d = self.model.run(math.sqrt(0.0002))
val_2d = self.model.runXY([0.01,0.01])
self.assertTrue(math.fabs(val_1d-val_2d)/val_1d < 0.02)
