""" Unit tests for fitting module @author M. Doucet """ import unittest import math import numpy from sans.fit.AbstractFitEngine import Model from sans.fit.Fitting import Fit from sans.dataloader.loader import Loader from sans.models.qsmearing import smear_selection from sans.models.CylinderModel import CylinderModel from sans.models.SphereModel import SphereModel class testFitModule(unittest.TestCase): """ test fitting """ def test_scipy(self): """ Simple cylinder model fit (scipy) """ out=Loader().load("cyl_400_20.txt") # This data file has not error, add them out.dy = out.y fitter = Fit('scipy') fitter.set_data(out,1) # Receives the type of model for the fitting model1 = CylinderModel() model1.setParam('sldCyl', 3.0e-6) model1.setParam('sldSolv', 0.0) model = Model(model1) model.set(scale=1e-10) pars1 =['length','radius','scale'] fitter.set_model(model,1,pars1) # What the hell is this line for? fitter.select_problem_for_fit(id=1,value=1) result1, = fitter.fit() self.assert_(result1) self.assertTrue(len(result1.pvec)>0 or len(result1.pvec)==0 ) self.assertTrue(len(result1.stderr)> 0 or len(result1.stderr)==0) self.assertTrue( math.fabs(result1.pvec[0]-400.0)/3.0 < result1.stderr[0] ) self.assertTrue( math.fabs(result1.pvec[1]-20.0)/3.0 < result1.stderr[1] ) self.assertTrue( math.fabs(result1.pvec[2]-9.0e-12)/3.0 < result1.stderr[2] ) self.assertTrue( result1.fitness < 1.0 ) def test_scipy_dispersion(self): """ Cylinder fit with dispersion """ # Load data # This data is for a cylinder with # length=400, radius=20, radius disp=5, scale=1e-10 out=Loader().load("cyl_400_20_disp5r.txt") out.dy = numpy.zeros(len(out.y)) for i in range(len(out.y)): out.dy[i] = math.sqrt(out.y[i]) # Set up the fit fitter = Fit('scipy') # Receives the type of model for the fitting model1 = CylinderModel() model1.setParam('sldCyl', 3.0e-6) model1.setParam('sldSolv', 0.0) # Dispersion parameters model1.dispersion['radius']['width'] = 0.001 model1.dispersion['radius']['npts'] = 50 model = Model(model1) pars1 =['length','radius','scale','radius.width'] fitter.set_data(out,1) model.set(scale=1e-10) fitter.set_model(model,1,pars1) fitter.select_problem_for_fit(id=1,value=1) result1, = fitter.fit() self.assert_(result1) self.assertTrue(len(result1.pvec)>0 or len(result1.pvec)==0 ) self.assertTrue(len(result1.stderr)> 0 or len(result1.stderr)==0) self.assertTrue( math.fabs(result1.pvec[0]-400.0)/3.0 < result1.stderr[0] ) self.assertTrue( math.fabs(result1.pvec[1]-20.0)/3.0 < result1.stderr[1] ) self.assertTrue( math.fabs(result1.pvec[2]-1.0e-10)/3.0 < result1.stderr[2] ) self.assertTrue( math.fabs(result1.pvec[3]-5.0)/3.0 < result1.stderr[3] ) self.assertTrue( result1.fitness < 1.0 ) class smear_testdata(unittest.TestCase): """ Test fitting with the smearing operations The output of the fits should be compated to fits done with IGOR for the same models and data sets. """ def setUp(self): print "TEST DONE WITHOUT PROPER OUTPUT CHECK:" print " ---> TEST NEEDS TO BE COMPLETED" data = Loader().load("latex_smeared.xml") self.data_res = data[0] self.data_slit = data[1] self.sphere = SphereModel() self.sphere.setParam('radius', 5000.0) self.sphere.setParam('scale', 1.0e-13) self.sphere.setParam('radius.npts', 30) self.sphere.setParam('radius.width',500) def test_reso(self): # Let the data module find out what smearing the # data needs smear = smear_selection(self.data_res) self.assertEqual(smear.__class__.__name__, 'QSmearer') # Fit fitter = Fit('scipy') # Data: right now this is the only way to set the smearer object # We should improve that and have a way to get access to the # data for a given fit. fitter.set_data(self.data_res,1) fitter._engine.fit_arrange_dict[1].data_list[0].smearer = smear print "smear ",smear # Model: maybe there's a better way to do this. # Ideally we should have to create a new model from our sans model. fitter.set_model(Model(self.sphere),1, ['radius','scale']) # Why do we have to do this...? fitter.select_problem_for_fit(id=1,value=1) # Perform the fit (might take a while) result1, = fitter.fit() # Replace this with proper test once we know what the # result should be print result1.pvec print result1.stderr def test_slit(self): smear = smear_selection(self.data_slit) self.assertEqual(smear.__class__.__name__, 'SlitSmearer') # Fit fitter = Fit('scipy') # Data: right now this is the only way to set the smearer object # We should improve that and have a way to get access to the # data for a given fit. fitter.set_data(self.data_slit,1) fitter._engine.fit_arrange_dict[1].data_list[0].smearer = smear fitter._engine.fit_arrange_dict[1].data_list[0].qmax = 0.003 # Model fitter.set_model(Model(self.sphere),1, ['radius','scale']) fitter.select_problem_for_fit(id=1,value=1) result1, = fitter.fit() # Replace this with proper test once we know what the # result should be print result1.pvec print result1.stderr if __name__ == '__main__': unittest.main()