本文整理汇总了Python中sas.models.SphereModel.SphereModel.set_dispersion方法的典型用法代码示例。如果您正苦于以下问题：Python SphereModel.set_dispersion方法的具体用法？Python SphereModel.set_dispersion怎么用？Python SphereModel.set_dispersion使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sas.models.SphereModel.SphereModel的用法示例。
在下文中一共展示了SphereModel.set_dispersion方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: TestSphere
# 需要导入模块: from sas.models.SphereModel import SphereModel [as 别名]
# 或者: from sas.models.SphereModel.SphereModel import set_dispersion [as 别名]
class TestSphere(unittest.TestCase):
"""
Testing C++ Cylinder model
"""
def setUp(self):
from sas.models.SphereModel import SphereModel
self.model= SphereModel()
self.model.setParam('scale', 1.0)
self.model.setParam('radius', 60.0)
self.model.setParam('sldSph', 2.0)
self.model.setParam('sldSolv', 1.0)
self.model.setParam('background', 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.assertTrue(math.fabs(self.model.run(0.001)-90412744456148.094)<=50.0)
self.assertAlmostEqual(self.model.runXY([0.001,0.001]),
90347660670656.391, 1)
def test_dispersion(self):
"""
Test with dispersion
"""
from sas.models.DisperseModel import DisperseModel
disp = DisperseModel(self.model, ['radius'], [10])
disp.setParam('n_pts', 10)
disp.setParam('radius.npts', 10)
disp.setParam('radius.nsigmas', 2.5)
self.assertTrue(math.fabs(disp.run(0.001)-96795008379475.219<50.0))
def test_new_disp(self):
from sas.models.dispersion_models import GaussianDispersion
disp_rm = GaussianDispersion()
self.model.set_dispersion('radius', disp_rm)
self.model.dispersion['radius']['width'] = 0.1666666667
self.model.dispersion['radius']['npts'] = 10
self.model.dispersion['radius']['nsigmas'] = 2示例2: TestSphereGauss
# 需要导入模块: from sas.models.SphereModel import SphereModel [as 别名]
# 或者: from sas.models.SphereModel.SphereModel import set_dispersion [as 别名]
class TestSphereGauss(unittest.TestCase):
"""
Testing C++ Polydispersion w/ sphere comparing to IGOR/NIST computation
"""
def setUp(self):
loader = Loader()
## IGOR/NIST computation
self.output_gauss=loader.load('Gausssphere.txt')
self.output_shulz=loader.load('Schulzsphere.txt')
from sas.models.SphereModel import SphereModel
self.model= SphereModel()
self.model.setParam('scale', 0.01)
self.model.setParam('radius', 60.0)
self.model.setParam('sldSph', 1.e-6)
self.model.setParam('sldSolv', 3.e-6)
self.model.setParam('background', 0.001)
def test_gauss(self):
from sas.models.dispersion_models import GaussianDispersion
disp_g = GaussianDispersion()
self.model.set_dispersion('radius', disp_g)
self.model.dispersion['radius']['width'] = 0.2
self.model.dispersion['radius']['npts'] = 100
self.model.dispersion['radius']['nsigmas'] = 10
for ind in range(len(self.output_gauss.x)):
self.assertAlmostEqual(self.model.run(self.output_gauss.x[ind]),
self.output_gauss.y[ind], 2)
def test_shulz(self):
from sas.models.dispersion_models import SchulzDispersion
disp_s = SchulzDispersion()
self.model.set_dispersion('radius', disp_s)
self.model.dispersion['radius']['width'] = 0.2
self.model.dispersion['radius']['npts'] = 100
self.model.dispersion['radius']['nsigmas'] = 10
for ind in range(len(self.output_shulz.x)):
self.assertAlmostEqual(self.model.run(self.output_gauss.x[ind]),
self.output_shulz.y[ind], 3)