def setUp(self): """ initialize data""" self.data1=Loader().load("cyl_400_20.txt") self.data2=Loader().load("cyl_400_40.txt") # Receives the type of model for the fitting from sas.models.CylinderModel import CylinderModel cyl1 = CylinderModel() cyl1.name = "C1" self.model1 = Model(cyl1) self.model1.set(scale= 1.0) self.model1.set(radius=18) self.model1.set(length=200) self.model1.set(sldCyl=3e-006, sldSolv=0.0) self.model1.set(background=0.0) cyl2 = CylinderModel() cyl2.name = "C2" self.model2 = Model(cyl2) self.model2.set(scale= 1.0) self.model2.set(radius=37) self.model2.set(length=300) self.model2.set(sldCyl=3e-006, sldSolv=0.0) self.model2.set(background=0.0)
def setUp(self): """ initialize data""" self.data1 = Loader().load("cyl_400_20.txt") self.data2 = Loader().load("cyl_400_40.txt") # Receives the type of model for the fitting from sas.models.CylinderModel import CylinderModel cyl1 = CylinderModel() cyl1.name = "C1" self.model1 = Model(cyl1) self.model1.set(scale=1.0) self.model1.set(radius=18) self.model1.set(length=200) self.model1.set(sldCyl=3e-006, sldSolv=0.0) self.model1.set(background=0.0) cyl2 = CylinderModel() cyl2.name = "C2" self.model2 = Model(cyl2) self.model2.set(scale=1.0) self.model2.set(radius=37) self.model2.set(length=300) self.model2.set(sldCyl=3e-006, sldSolv=0.0) self.model2.set(background=0.0)
def test2(self): """ fit 2 data and 2 model with no constrainst""" #load data l = Loader() data1 = l.load("testdata_line.txt") data1.name = data1.filename data2 = l.load("testdata_line1.txt") data2.name = data2.filename #Importing the Fit module fitter = Fit('bumps') # Receives the type of model for the fitting model11 = LineModel() model11.name = "M1" model22 = LineModel() model11.name = "M2" model1 = Model(model11, data1) model2 = Model(model22, data2) pars1 = ['A', 'B'] fitter.set_data(data1, 1) fitter.set_model(model1, 1, pars1) fitter.select_problem_for_fit(id=1, value=0) fitter.set_data(data2, 2) fitter.set_model(model2, 2, pars1) fitter.select_problem_for_fit(id=2, value=0) try: result1, = fitter.fit(handler=FitHandler()) except RuntimeError, msg: assert str(msg) == "Nothing to fit"
def fit_single(self, fitter_name, isdream=False): fitter = Fit(fitter_name) data = Loader().load("testdata_line.txt") data.name = data.filename fitter.set_data(data, 1) # Receives the type of model for the fitting model1 = LineModel() model1.name = "M1" model = Model(model1, data) pars1 = ['A', 'B'] fitter.set_model(model, 1, pars1) fitter.select_problem_for_fit(id=1, value=1) result1, = fitter.fit(handler=FitHandler()) # The target values were generated from the following statements p, s, fx = result1.pvec, result1.stderr, result1.fitness #print "p0,p1,s0,s1,fx = %g, %g, %g, %g, %g"%(p[0],p[1],s[0],s[1],fx) p0, p1, s0, s1, fx_ = 3.68353, 2.61004, 0.336186, 0.105244, 1.20189 if isdream: # Dream is not a minimizer: just check that the fit is within # uncertainty self.assertTrue(abs(p[0] - p0) <= s0) self.assertTrue(abs(p[1] - p1) <= s1) else: self.assertTrue(abs(p[0] - p0) <= 1e-5) self.assertTrue(abs(p[1] - p1) <= 1e-5) self.assertTrue(abs(fx - fx_) <= 1e-5)
def test_without_resolution(self): """ Simple cylinder model fit """ out=Loader().load("cyl_400_20.txt") # This data file has not error, add them #out.dy = out.y fitter = Fit() fitter.set_data(out,1) # Receives the type of model for the fitting model1 = CylinderModel() model1.setParam("scale", 1.0) model1.setParam("radius",18) model1.setParam("length", 397) model1.setParam("sldCyl",3e-006 ) model1.setParam("sldSolv",0.0 ) model1.setParam("background", 0.0) model = Model(model1) 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() #print "result1",result1 self.assert_(result1) self.assertTrue(len(result1.pvec) > 0) self.assertTrue(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)/3.0 < result1.stderr[2] ) self.assertTrue( result1.fitness < 1.0 )
def test4(self): """ fit 2 data concatenates with limited range of x and one model """ #load data l = Loader() data1 = l.load("testdata_line.txt") data1.name = data1.filename data2 = l.load("testdata_line1.txt") data2.name = data2.filename # Receives the type of model for the fitting model1 = LineModel() model1.name = "M1" model1.setParam("A", 1.0) model1.setParam("B", 1.0) model = Model(model1, data1) pars1 = ['A', 'B'] #Importing the Fit module fitter = Fit('bumps') fitter.set_data(data1, 1, qmin=0, qmax=7) fitter.set_model(model, 1, pars1) fitter.set_data(data2, 1, qmin=1, qmax=10) fitter.select_problem_for_fit(id=1, value=1) result2, = fitter.fit(handler=FitHandler()) self.assert_(result2) self.assertTrue( math.fabs(result2.pvec[0] - 4) / 3 <= result2.stderr[0]) self.assertTrue( math.fabs(result2.pvec[1] - 2.5) / 3 <= result2.stderr[1]) self.assertTrue(result2.fitness / len(data1.x) < 2)
def test_slit(self): smear = smear_selection(self.data_slit) #self.assertEqual(smear.__class__.__name__, 'SlitSmearer') #self.assertEqual(smear.__class__.__name__, 'PySmearer') fitter = Fit() # 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.fit_arrange_dict[1].data_list[0].smearer = smear fitter.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() #print "v",result1.pvec #print "dv",result1.stderr #print "chisq(v)",result1.fitness numpy.testing.assert_allclose(result1.pvec, [2323.466,0.22137], rtol=0.001)
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') #self.assertEqual(smear.__class__.__name__, 'PySmearer') # Fit fitter = Fit() # 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.fit_arrange_dict[1].data_list[0].smearer = smear # Model: maybe there's a better way to do this. # Ideally we should have to create a new model from our sas model. fitter.set_model(Model(self.sphere),1, ['radius','scale', 'background']) # 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() #print "v",result1.pvec #print "dv",result1.stderr #print "chisq(v)",result1.fitness self.assertTrue( math.fabs(result1.pvec[0]-5000) < 20 ) self.assertTrue( math.fabs(result1.pvec[1]-0.48) < 0.02 ) self.assertTrue( math.fabs(result1.pvec[2]-0.060) < 0.002 )
def test_slit(self): smear = smear_selection(self.data_slit) self.assertEqual(smear.__class__.__name__, 'SlitSmearer') fitter = Fit('bumps') # 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() #print "v",result1.pvec #print "dv",result1.stderr #print "chisq(v)",result1.fitness self.assertTrue(math.fabs(result1.pvec[0] - 2340) < 20) self.assertTrue(math.fabs(result1.pvec[1] - 0.010) < 0.002)
def test_constraints(self): """ fit 2 data and 2 model with 1 constrainst""" #load data l = Loader() data1= l.load("testdata_line.txt") data1.name = data1.filename data2= l.load("testdata_cst.txt") data2.name = data2.filename # Receives the type of model for the fitting model11 = LineModel() model11.name= "line" model11.setParam("A", 1.0) model11.setParam("B",1.0) model22 = Constant() model22.name= "cst" model22.setParam("value", 1.0) model1 = Model(model11,data1) model2 = Model(model22,data2) model1.set(A=4) model1.set(B=3) # Constraint the constant value to be equal to parameter B (the real value is 2.5) #model2.set(value='line.B') pars1= ['A','B'] pars2= ['value'] #Importing the Fit module fitter = Fit() fitter.set_data(data1,1) fitter.set_model(model1,1,pars1) fitter.set_data(data2,2,smearer=None) fitter.set_model(model2,2,pars2,constraints=[("value","line.B")]) fitter.select_problem_for_fit(id=1,value=1) fitter.select_problem_for_fit(id=2,value=1) R1,R2 = fitter.fit(handler=FitHandler()) self.assertTrue( math.fabs(R1.pvec[0]-4.0)/3. <= R1.stderr[0]) self.assertTrue( math.fabs(R1.pvec[1]-2.5)/3. <= R1.stderr[1]) self.assertTrue( R1.fitness/(len(data1.x)+len(data2.x)) < 2)
def test_constraints(self): """ fit 2 data and 2 model with 1 constrainst""" #load data l = Loader() data1 = l.load("testdata_line.txt") data1.name = data1.filename data2 = l.load("testdata_cst.txt") data2.name = data2.filename # Receives the type of model for the fitting model11 = LineModel() model11.name = "line" model11.setParam("A", 1.0) model11.setParam("B", 1.0) model22 = Constant() model22.name = "cst" model22.setParam("value", 1.0) model1 = Model(model11, data1) model2 = Model(model22, data2) model1.set(A=4) model1.set(B=3) # Constraint the constant value to be equal to parameter B (the real value is 2.5) #model2.set(value='line.B') pars1 = ['A', 'B'] pars2 = ['value'] #Importing the Fit module fitter = Fit('bumps') fitter.set_data(data1, 1) fitter.set_model(model1, 1, pars1) fitter.set_data(data2, 2, smearer=None) fitter.set_model(model2, 2, pars2, constraints=[("value", "line.B")]) fitter.select_problem_for_fit(id=1, value=1) fitter.select_problem_for_fit(id=2, value=1) R1, R2 = fitter.fit(handler=FitHandler()) self.assertTrue(math.fabs(R1.pvec[0] - 4.0) / 3. <= R1.stderr[0]) self.assertTrue(math.fabs(R1.pvec[1] - 2.5) / 3. <= R1.stderr[1]) self.assertTrue(R1.fitness / (len(data1.x) + len(data2.x)) < 2)
def test_bad_pars(self): fitter = Fit('bumps') data = Loader().load("testdata_line.txt") data.name = data.filename fitter.set_data(data, 1) model1 = LineModel() model1.name = "M1" model = Model(model1, data) pars1 = ['param1', 'param2'] try: fitter.set_model(model, 1, pars1) except ValueError, exc: #print "ValueError was correctly raised: "+str(msg) assert str(exc).startswith('parameter param1')
def _dispersion(self, fitter): # 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]) # Receives the type of model for the fitting model1 = CylinderModel() model1.setParam("scale", 10.0) model1.setParam("radius", 18) model1.setParam("length", 397) model1.setParam("sldCyl", 3e-006) model1.setParam("sldSolv", 0.0) model1.setParam("background", 0.0) # Dispersion parameters model1.dispersion['radius']['width'] = 0.25 model1.dispersion['radius']['npts'] = 50 model = Model(model1) pars1 = ['length', 'radius', 'scale', 'radius.width'] fitter.set_data(out, 1) fitter.set_model(model, 1, pars1) fitter.select_problem_for_fit(id=1, value=1) #import time; T0 = time.time() result1, = fitter.fit() #print "time",time.time()-T0,fitter._engine.__class__.__name__ self.assert_(result1) self.assertTrue(len(result1.pvec) > 0) self.assertTrue(len(result1.stderr) > 0) #print [z for z in zip(result1.param_list,result1.pvec,result1.stderr)] self.assertTrue( math.fabs(result1.pvec[0] - 399.8) / 3.0 < result1.stderr[0]) self.assertTrue( math.fabs(result1.pvec[1] - 17.5) / 3.0 < result1.stderr[1]) self.assertTrue( math.fabs(result1.pvec[2] - 11.1) / 3.0 < result1.stderr[2]) self.assertTrue( math.fabs(result1.pvec[3] - 0.276) / 3.0 < result1.stderr[3]) self.assertTrue(result1.fitness < 1.0)
def test_cyl_times_square(self): """ Simple cylinder model fit """ out = Loader().load("cyl_400_20.txt") data = Data1D(x=out.x, y=out.y, dx=out.dx, dy=out.dy) # Receives the type of model for the fitting model1 = MultiplicationModel(CylinderModel(), SquareWellStructure()) model1.setParam('background', 0.0) model1.setParam('sldCyl', 3e-006) model1.setParam('sldSolv', 0.0) model1.setParam('length', 420) model1.setParam('radius', 40) model1.setParam('scale_factor', 2) model1.setParam('volfraction', 0.04) model1.setParam('welldepth', 1.5) model1.setParam('wellwidth', 1.2) model = Model(model1) pars1 = ['length', 'radius', 'scale_factor'] fitter = Fit('bumps') fitter.set_data(data, 1) 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) self.assertTrue(len(result1.stderr) >= 0) #print "results",list(zip(result1.pvec, result1.stderr)) self.assertTrue( math.fabs(result1.pvec[0] - 612) / 3.0 <= result1.stderr[0]) self.assertTrue( math.fabs(result1.pvec[1] - 20.3) / 3.0 <= result1.stderr[1]) self.assertTrue( math.fabs(result1.pvec[2] - 25) / 3.0 <= result1.stderr[2]) self.assertTrue(result1.fitness / len(data.x) < 1.0)
class TestSimultaneousFit(unittest.TestCase): """ test simultaneous fitting """ def setUp(self): """ initialize data""" self.data1=Loader().load("cyl_400_20.txt") self.data2=Loader().load("cyl_400_40.txt") # Receives the type of model for the fitting from sas.models.CylinderModel import CylinderModel cyl1 = CylinderModel() cyl1.name = "C1" self.model1 = Model(cyl1) self.model1.set(scale= 1.0) self.model1.set(radius=18) self.model1.set(length=200) self.model1.set(sldCyl=3e-006, sldSolv=0.0) self.model1.set(background=0.0) cyl2 = CylinderModel() cyl2.name = "C2" self.model2 = Model(cyl2) self.model2.set(scale= 1.0) self.model2.set(radius=37) self.model2.set(length=300) self.model2.set(sldCyl=3e-006, sldSolv=0.0) self.model2.set(background=0.0) def test_constrained_bumps(self): """ Simultaneous cylinder model fit """ self._run_fit(Fit('bumps')) #@unittest.skip("") def _run_fit(self, fitter): result1, result2 = self._fit(fitter) self.assert_(result1) self.assertTrue(len(result1.pvec)>0) self.assertTrue(len(result1.stderr)>0) for n, v, dv in zip(result1.param_list, result1.pvec, result1.stderr): #print "%s M1.%s = %s +/- %s"%(fitter._engine.__class__.__name__,n,v,dv) if n == "length": self.assertTrue( math.fabs(v-400.0)/3.0 < dv ) elif n=='radius': self.assertTrue( math.fabs(v-20.0)/3.0 < dv ) elif n=='scale': self.assertTrue( math.fabs(v-1.0)/3.0 < dv ) for n, v, dv in zip(result2.param_list, result2.pvec, result2.stderr): #print "%s M2.%s = %s +/- %s"%(fitter._engine.__class__.__name__,n,v,dv) if n=='radius': self.assertTrue( math.fabs(v-40.0)/3.0 < dv ) elif n=='scale': self.assertTrue( math.fabs(v-1.0)/3.0 < dv ) def _fit(self, fitter): """ return fit result """ fitter.set_data(self.data1,1) fitter.set_model(self.model1, 1, ['length','radius','scale']) fitter.set_data(self.data2,2) fitter.set_model(self.model2, 2, ['length','radius','scale'], constraints=[("length","C1.length")]) fitter.select_problem_for_fit(id=1,value=1) fitter.select_problem_for_fit(id=2,value=1) return fitter.fit()
class TestSimultaneousFit(unittest.TestCase): """ test simultaneous fitting """ def setUp(self): """ initialize data""" self.data1 = Loader().load("cyl_400_20.txt") self.data2 = Loader().load("cyl_400_40.txt") # Receives the type of model for the fitting from sas.models.CylinderModel import CylinderModel cyl1 = CylinderModel() cyl1.name = "C1" self.model1 = Model(cyl1) self.model1.set(scale=1.0) self.model1.set(radius=18) self.model1.set(length=200) self.model1.set(sldCyl=3e-006, sldSolv=0.0) self.model1.set(background=0.0) cyl2 = CylinderModel() cyl2.name = "C2" self.model2 = Model(cyl2) self.model2.set(scale=1.0) self.model2.set(radius=37) self.model2.set(length=300) self.model2.set(sldCyl=3e-006, sldSolv=0.0) self.model2.set(background=0.0) def test_constrained_bumps(self): """ Simultaneous cylinder model fit """ self._run_fit(Fit()) # @unittest.skip("") def _run_fit(self, fitter): result1, result2 = self._fit(fitter) self.assert_(result1) self.assertTrue(len(result1.pvec) > 0) self.assertTrue(len(result1.stderr) > 0) for n, v, dv in zip(result1.param_list, result1.pvec, result1.stderr): if n == "length": self.assertTrue(math.fabs(v - 400.0) / 3.0 < dv) elif n == "radius": self.assertTrue(math.fabs(v - 20.0) / 3.0 < dv) elif n == "scale": self.assertTrue(math.fabs(v - 1.0) / 3.0 < dv) for n, v, dv in zip(result2.param_list, result2.pvec, result2.stderr): if n == "radius": self.assertTrue(math.fabs(v - 40.0) / 3.0 < dv) elif n == "scale": self.assertTrue(math.fabs(v - 1.0) / 3.0 < dv) def _fit(self, fitter): """ return fit result """ fitter.set_data(self.data1, 1) fitter.set_model(self.model1, 1, ["length", "radius", "scale"]) fitter.set_data(self.data2, 2) fitter.set_model(self.model2, 2, ["length", "radius", "scale"], constraints=[("length", "C1.length")]) fitter.select_problem_for_fit(id=1, value=1) fitter.select_problem_for_fit(id=2, value=1) return fitter.fit()