class TestFractal(unittest.TestCase):
""" Unit tests for Fractal model """
def setUp(self):
from sas.models.FractalModel import FractalModel
self.comp = FractalModel()
def test1D(self):
""" Test 1D model for a Fractal """
self.assertAlmostEqual(self.comp.run(0.001), 39.288146, 4)
def test1D_2(self):
""" Test 2D model for a Fractal """
self.assertAlmostEqual(self.comp.run([0.001, 1]), 39.288146, 4)
class TestFractal(unittest.TestCase):
""" Unit tests for Fractal model """
def setUp(self):
from sas.models.FractalModel import FractalModel
self.comp = FractalModel()
def test1D(self):
""" Test 1D model for a Fractal """
self.assertAlmostEqual(self.comp.run(0.001), 39.288146, 4)
def test1D_2(self):
""" Test 2D model for a Fractal """
self.assertAlmostEqual(self.comp.run([0.001, 1]), 39.288146, 4)
def setUp(self):
from sas.models.FractalModel import FractalModel
self.model= FractalModel()
self.r0 = 5.0
self.sldp = 2.0e-6
self.sldm = 6.35e-6
self.phi = 0.05
self.Df = 2
self.corr = 100.0
self.bck = 1.0
self.model.setParam('scale', self.phi)
self.model.setParam('radius', self.r0)
self.model.setParam('fractal_dim',self.Df)
self.model.setParam('cor_length', self.corr)
self.model.setParam('sldBlock', self.sldp)
self.model.setParam('sldSolv', self.sldm)
self.model.setParam('background', self.bck)
class TestFractalModel(unittest.TestCase):
"""
Unit tests for Number Density Fractal function
F(x)= P(x)*S(x) + bkd
The model has Seven parameters:
scale = Volume fraction
Radius = Block radius
Fdim = Fractal dimension
L = correlation Length
SDLB = SDL block
SDLS = SDL solvent
bkd = background
"""
def setUp(self):
from sas.models.FractalModel import FractalModel
self.model= FractalModel()
self.r0 = 5.0
self.sldp = 2.0e-6
self.sldm = 6.35e-6
self.phi = 0.05
self.Df = 2
self.corr = 100.0
self.bck = 1.0
self.model.setParam('scale', self.phi)
self.model.setParam('radius', self.r0)
self.model.setParam('fractal_dim',self.Df)
self.model.setParam('cor_length', self.corr)
self.model.setParam('sldBlock', self.sldp)
self.model.setParam('sldSolv', self.sldm)
self.model.setParam('background', self.bck)
def _func(self, x):
r0 = self.r0
sldp = self.sldp
sldm = self.sldm
phi = self.phi
Df = self.Df
corr = self.corr
bck = self.bck
pq = 1.0e8*phi*4.0/3.0*math.pi*r0*r0*r0*(sldp-sldm)*(sldp-sldm)*math.pow((3*(math.sin(x*r0) - x*r0*math.cos(x*r0))/math.pow((x*r0),3)),2);
sq = Df*math.exp(gammaln(Df-1.0))*math.sin((Df-1.0)*math.atan(x*corr));
sq /= math.pow((x*r0),Df) * math.pow((1.0 + 1.0/(x*corr)/(x*corr)),((Df-1.0)/2.0));
sq += 1.0;
#self.assertAlmostEqual(self.model._scatterRanDom(x), pq, 8 )
#self.assertEqual(self.model._Block(x),sq )
return sq*pq+bck
def test1D(self):
x = 0.001
iq = self._func(x)
self.assertEqual(self.model.run(x), iq)
self.assertEqual(self.model.runXY(x), iq)
def test2D(self):
x = 1.0
y = 2.0
r = math.sqrt(x**2 + y**2)
phi = math.atan2(y, x)
iq_x = self._func(x)
iq_y = self._func(y)
#self.assertEqual(self.model.run([r, phi]), iq_x*iq_y)
self.assertEqual(self.model.run([r, phi]), self.model.run(r))
#self.assertEqual(self.model.runXY([x,y]), iq_x*iq_y)
self.assertEqual(self.model.runXY([x,y]), self.model.run(r))
def setUp(self):
from sas.models.FractalModel import FractalModel
self.comp = FractalModel()
