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)
def testMultiplicationParam(self):
""" Test Multiplication """
## test details dictionary
## test parameters list
list3= self.model3.getParamList()
for item in self.model.getParamList():
#model3 parameters should not include scale*
if not 'scale' in item:
self.assert_(item in list3)
for item in self.model2.getParamList():
#model3 parameters should not include effect_radius*
if not 'effect_radius' in item:
self.assert_(item in list3)
## test set value for parameters and get paramaters
#self.model3.setParam("scale", 15)
#self.assertEqual(self.model3.getParam("scale"), 15)
self.model3.setParam("scale_factor", 0.1)
self.assertEqual(self.model3.getParam("scale_factor"), 0.1)
self.model3.setParam("radius", 20)
self.assertEqual(self.model3.getParam("radius"), 20)
self.model3.setParam("radius.width", 15)
self.assertEqual(self.model3.getParam("radius.width"), 15)
self.model3.setParam("scale_factor", 15)
self.assertEqual(self.model3.getParam("scale_factor"), 15)
self.assertEqual(self.model3.getParam("volfraction"), self.model.getParam("scale"))
## Dispersity
list3= self.model3.getDispParamList()
self.assertEqual(list3, ['radius.npts', 'radius.nsigmas', 'radius.width', 'length.npts', \
'length.nsigmas', 'length.width', 'cyl_theta.npts', 'cyl_theta.nsigmas', 'cyl_theta.width',\
'cyl_phi.npts', 'cyl_phi.nsigmas', 'cyl_phi.width'])
from sas.models.dispersion_models import ArrayDispersion
disp_th = ArrayDispersion()
values_th = numpy.zeros(100)
weights = numpy.zeros(100)
for i in range(100):
values_th[i]=(math.pi/99.0*i)
weights[i]=(1.0)
disp_th.set_weights(values_th, weights)
self.model3.set_dispersion('radius', disp_th)
model4= self.model3.clone()
self.assertEqual(model4.getParam("radius"), 20)
def testMultiplicationParam(self):
""" Test Multiplication """
## test details dictionary
## test parameters list
list3= self.model3.getParamList()
for item in self.model.getParamList():
#model3 parameters should not include scale*
if not 'scale' in item:
self.assert_(item in list3)
for item in self.model2.getParamList():
#model3 parameters should not include effect_radius*
if not 'effect_radius' in item:
self.assert_(item in list3)
## test set value for parameters and get paramaters
#self.model3.setParam("scale", 15)
#self.assertEqual(self.model3.getParam("scale"), 15)
self.model3.setParam("scale_factor", 0.1)
self.assertEqual(self.model3.getParam("scale_factor"), 0.1)
self.model3.setParam("radius", 20)
self.assertEqual(self.model3.getParam("radius"), 20)
self.model3.setParam("radius.width", 15)
self.assertEqual(self.model3.getParam("radius.width"), 15)
self.model3.setParam("scale_factor", 15)
self.assertEqual(self.model3.getParam("scale_factor"), 15)
self.assertEqual(self.model3.getParam("volfraction"), self.model.getParam("scale"))
## Dispersity
list3= self.model3.getDispParamList()
self.assertEqual(list3, ['radius.npts', 'radius.nsigmas', 'radius.width', 'length.npts', \
'length.nsigmas', 'length.width', 'cyl_theta.npts', 'cyl_theta.nsigmas', 'cyl_theta.width',\
'cyl_phi.npts', 'cyl_phi.nsigmas', 'cyl_phi.width'])
from sas.models.dispersion_models import ArrayDispersion
disp_th = ArrayDispersion()
values_th = numpy.zeros(100)
weights = numpy.zeros(100)
for i in range(100):
values_th[i]=(math.pi/99.0*i)
weights[i]=(1.0)
disp_th.set_weights(values_th, weights)
self.model3.set_dispersion('radius', disp_th)
model4= self.model3.clone()
self.assertEqual(model4.getParam("radius"), 20)
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()
values_ph = numpy.zeros(100)
values_th = numpy.zeros(100)
weights = numpy.zeros(100)
for i in range(100):
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)
self.model.set_dispersion('cyl_theta', disp_th)
self.model.set_dispersion('cyl_phi', disp_ph)
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)
def testMultiplicationParam(self):
""" Test Multiplication (check the parameters)"""
## test details dictionary
## test parameters list
list3= self.model3.getParamList()
for item in self.model.getParamList():
if not 'scale' in item:
self.assert_(item in list3)
for item in self.model2.getParamList():
#model3 parameters should not include effect_radius*
if not 'effect_radius' in item:
self.assert_(item in list3)
## test set value for parameters and get paramaters
self.model3.setParam("scale_factor", 15)
self.assertEqual(self.model3.getParam("scale_factor"), 15)
self.model3.setParam("radius", 20)
self.assertEqual(self.model3.getParam("radius"), 20)
self.model3.setParam("radius.width", 15)
self.assertEqual(self.model3.getParam("radius.width"), 15)
self.model3.setParam("scale_factor", 15)
self.assertEqual(self.model3.getParam("scale_factor"), 15)
self.assertEqual(self.model3.getParam("volfraction"), self.model.getParam("scale"))
## Dispersity
list3= self.model3.getDispParamList()
self.assertEqual(list3, ['radius.npts', 'radius.nsigmas', 'radius.width'])
from sas.models.dispersion_models import ArrayDispersion
disp_th = ArrayDispersion()
values_th = numpy.zeros(100)
weights = numpy.zeros(100)
for i in range(100):
values_th[i]=(math.pi/99.0*i)
weights[i]=(1.0)
disp_th.set_weights(values_th, weights)
self.model3.set_dispersion('radius', disp_th)
val_1d = self.model3.run(math.sqrt(0.0002))
val_2d = self.model3.runXY([0.01,0.01])
self.assertTrue(math.fabs(val_1d-val_2d)/val_1d < 0.02)
model4= self.model3.clone()
self.assertEqual(model4.getParam("radius"), 20)
def testMultiplicationParam(self):
""" Test Multiplication (check the parameters)"""
## test details dictionary
## test parameters list
list3= self.model3.getParamList()
for item in self.model.getParamList():
if not 'scale' in item:
self.assert_(item in list3)
for item in self.model2.getParamList():
#model3 parameters should not include effect_radius*
if not 'effect_radius' in item:
self.assert_(item in list3)
## test set value for parameters and get paramaters
self.model3.setParam("scale_factor", 15)
self.assertEqual(self.model3.getParam("scale_factor"), 15)
self.model3.setParam("radius", 20)
self.assertEqual(self.model3.getParam("radius"), 20)
self.model3.setParam("radius.width", 15)
self.assertEqual(self.model3.getParam("radius.width"), 15)
self.model3.setParam("scale_factor", 15)
self.assertEqual(self.model3.getParam("scale_factor"), 15)
self.assertEqual(self.model3.getParam("volfraction"), self.model.getParam("scale"))
## Dispersity
list3= self.model3.getDispParamList()
self.assertEqual(list3, ['radius.npts', 'radius.nsigmas', 'radius.width'])
from sas.models.dispersion_models import ArrayDispersion
disp_th = ArrayDispersion()
values_th = numpy.zeros(100)
weights = numpy.zeros(100)
for i in range(100):
values_th[i]=(math.pi/99.0*i)
weights[i]=(1.0)
disp_th.set_weights(values_th, weights)
self.model3.set_dispersion('radius', disp_th)
val_1d = self.model3.run(math.sqrt(0.0002))
val_2d = self.model3.runXY([0.01,0.01])
self.assertTrue(math.fabs(val_1d-val_2d)/val_1d < 0.02)
model4= self.model3.clone()
self.assertEqual(model4.getParam("radius"), 20)
