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 """ ## 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 (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)