Changeset 48882d1 in sasview for park_integration/test/testfitting.py

Timestamp:

Aug 22, 2008 5:51:05 PM (16 years ago)

Author:

Gervaise Alina <gervyh@…>

Branches:

master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.1.1, release-4.1.2, release-4.2.2, release_4.0.1, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

3c404d3

Parents:

d6513cd

Message:

park fitting with new model and new data

File:

• park_integration/test/testfitting.py (modified) (7 diffs)

park_integration/test/testfitting.py

@@ -5 +5 @@
 from sans.guitools.plottables import Theory1D
 from sans.guitools.plottables import Data1D
-
+from sans.fit.AbstractFitEngine import Data, Model
 import math
 class testFitModule(unittest.TestCase):
@@ -15 +15 @@
         from sans.fit.Loader import Load
         load= Load()
-        
         load.set_filename("testdata_line.txt")
         self.assertEqual(load.get_filename(),"testdata_line.txt")
@@ -23 +22 @@
         dx=[]
         dy=[]
-        
         x,y,dx,dy = load.get_values()
-        
         # test that values have been loaded
         self.assertNotEqual(x, None)
@@ -59 +56 @@
         load.set_filename("testdata_line.txt")
         load.set_values()
-        data1 = Data1D(x=[], y=[],dx=None, dy=None)
-        load.load_data(data1)
+        data11 = Data1D(x=[], y=[],dx=None, dy=None)
+        load.load_data(data11)
         
         #Importing the Fit module
@@ -68 +65 @@
         # Receives the type of model for the fitting
         from sans.guitools.LineModel import LineModel
-        model1  = LineModel()
-        model2  = LineModel()
+        model11  = LineModel()
+        model22  = LineModel()
         
         #Do the fit SCIPY
-        model1.setParam( 'A', 2)
-        model1.setParam( 'B', 1)
+        model11.setParam( 'A', 2)
+        model11.setParam( 'B', 1)
+        data1=Data(sans_data=data11)
+        model1 =Model(model11)
+        model2 =Model(model22)
+      
         fitter.set_data(data1,1)
         fitter.set_model(model1,"M1",1,['A','B'])
         
-        chisqr1, out1, cov1=fitter.fit()
+        result= fitter.fit()
+        out1=result.pvec
+        chisqr1=result.fitness
+        cov1=result.cov
+        print "scipy",chisqr1, out1, cov1
         """ testing SCIPy results"""
         self.assert_(math.fabs(out1[1]-2.5)/math.sqrt(cov1[1][1]) < 2)
@@ -87 +92 @@
         #Do the fit
         fitter.set_data(data1,1)
-        model2.setParam( 'A', 2)
-        model2.setParam( 'B', 1)
+        model2.setParams( [2,1])
+    
         fitter.set_model(model2,"M1",1,['A','B'])
        
-        chisqr2, out2, cov2,result=fitter.fit(None,None)
-        
+        result2=fitter.fit(None,None)
+        out2=result2.pvec
+        chisqr2=result2.fitness
+        cov2=result2.cov
         self.assert_(math.fabs(out2[1]-2.5)/math.sqrt(cov2[1][1]) < 2)
         self.assert_(math.fabs(out2[0]-4.0)/math.sqrt(cov2[0][0]) < 2)
@@ -103 +110 @@
         self.assertAlmostEquals(cov1[1][1], cov2[1][1],1)
         self.assertAlmostEquals(chisqr1, chisqr2)
+         
+    def testfit_1Data_1Model(self):
+        """ test fitting for one data and one model cipy"""
+        #load data
+        from sans.fit.Loader import Load
+        load= Load()
+        load.set_filename("testdata_line.txt")
+        load.set_values()
+        data11 = Data1D(x=[], y=[],dx=None, dy=None)
+        load.load_data(data11)
+        data1=Data(sans_data=data11)
+    
+        #Importing the Fit module
+        from sans.fit.Fitting import Fit
+        fitter= Fit('scipy')
+        
+        # Receives the type of model for the fitting
+        from sans.guitools.LineModel import LineModel
+        model1  = LineModel()
+        model =Model(model1)
+        
+        #Do the fit SCIPY
+        fitter.set_data(data1,1)
+        import math
        
+        pars1=['A','B']
+        pars1.sort()
+        fitter.set_model(model,"M1",1,pars1)
+        result=fitter.fit()
+        print "scipy",result.fitness,result.cov, result.pvec
+    
+        self.assert_(result.fitness)
+        
+       
+