Changeset 792db7d5 in sasview for park_integration/test/testpark.py

Timestamp:

Jul 8, 2008 11:48:38 AM (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:

6e0f53a

Parents:

1c94a9f1

Message:

more tests added …most of them are failing because of uncertainty , scipy result and park resuls also little bit different

File:

• park_integration/test/testpark.py (modified) (3 diffs)

park_integration/test/testpark.py

@@ -13 +13 @@
         from sans.fit.Loader import Load
         load= Load()
-        #Load the first set of data
+        #Load the first data
         load.set_filename("testdata1.txt")
         load.set_values()
@@ -19 +19 @@
         load.load_data(data1)
         
-        #Load the second set of data
+        #Load the second data
         load.set_filename("testdata2.txt")
         load.set_values()
         data2 = Data1D(x=[], y=[],dx=None, dy=None)
         load.load_data(data2)
+        
+        #Load the third data
+        load.set_filename("testdata_line.txt")
+        load.set_values()
+        data3 = Data1D(x=[], y=[],dx=None, dy=None)
+        load.load_data(data3)
         
         #Importing the Fit module
@@ -40 +46 @@
         engine.set_data(data1,1)
         
-        import numpy
-        #print engine.fit({'A':2,'B':1},None,None)
-        #engine.remove_data(2,data2)
-        #engine.remove_model(2)
-        
-        engine.set_param( model2,"M2", {'A':2.5,'B':4})
+        engine.set_param( model2,"M2", {'A':2,'B':4})
         engine.set_model(model2,2)
         engine.set_data(data2,2)
-        print engine.fit({'A':2,'B':1},None,None)
-
-        if True:
-            import pylab
-            x1 = engine.problem[0].data.x
-            x2 = engine.problem[1].data.x
-            y1 = engine.problem[0].data.y
-            y2 = engine.problem[1].data.y
-            fx1 = engine.problem[0].data.fx
-            fx2 = engine.problem[1].data.fx
-            pylab.plot(x1,y1,'xb',x1,fx1,'-b',x2,y2,'xr',x2,fx2,'-r')
-            pylab.show()
-        if False:
-            print "current"
-            print engine.problem.chisq
-            print engine.problem.residuals
-            print "M1.y",engine.problem[0].data.y
-            print "M1.fx",engine.problem[0].data.fx
-            print "M1 delta",numpy.asarray(engine.problem[0].data.y)-engine.problem[0].data.fx
-            print "M2.y",engine.problem[0].data.y
-            print "M2.fx",engine.problem[0].data.fx
-            print "M2 delta",numpy.asarray(engine.problem[1].data.y)-engine.problem[1].data.fx
-            print "target"
-            engine.problem(numpy.array([4,2.5,4,2.5]))
-            print engine.problem.chisq
-            print engine.problem.residuals
-            print "M1.y",engine.problem[0].data.y
-            print "M1.fx",engine.problem[0].data.fx
-            print "M1 delta",numpy.asarray(engine.problem[0].data.y)-engine.problem[0].data.fx
-            print "M2.y",engine.problem[0].data.y
-            print "M2.fx",engine.problem[0].data.fx
-            print "M2 delta",numpy.asarray(engine.problem[1].data.y)-engine.problem[1].data.fx
-            
+        
+        chisqr1, out1, cov1= engine.fit({'A':2,'B':1},None,None)
+        
+        self.assert_(math.fabs(out1[1]-2.5)/math.sqrt(cov1[1][1]) < 2)
+        print math.fabs(out1[0]-4.0)/math.sqrt(cov1[0][0])
+        #self.assert_(math.fabs(out1[0]-4.0)/math.sqrt(cov1[0][0]) < 2)
+        self.assert_(math.fabs(out1[3]-2.5)/math.sqrt(cov1[3][3]) < 2)
+        self.assert_(math.fabs(out1[2]-4.0)/math.sqrt(cov1[2][2]) < 2)
+        print chisqr1/len(data1.x)
+        #self.assert_(chisqr1/len(data1.x) < 2)
+        print chisqr1/len(data2.x)
+        #self.assert_(chisqr2/len(data2.x) < 2)
+        
+        
+        engine.set_data(data3,1)
+        chisqr2, out2, cov2= engine.fit({'A':2,'B':1},None,None)
+        self.assert_(math.fabs(out2[1]-2.5)/math.sqrt(cov2[1][1]) < 2)
+        print math.fabs(out2[0]-4.0)/math.sqrt(cov2[0][0])
+        #self.assert_(math.fabs(out1[0]-4.0)/math.sqrt(cov1[0][0]) < 2)
+        self.assert_(math.fabs(out2[3]-2.5)/math.sqrt(cov2[3][3]) < 2)
+        self.assert_(math.fabs(out2[2]-4.0)/math.sqrt(cov2[2][2]) < 2)
+        print chisqr2/len(data1.x)
+        #self.assert_(chisqr1/len(data1.x) < 2)
+        print chisqr2/len(data2.x)
+        #self.assert_(chisqr2/len(data2.x) < 2)
+        
+        
+        
+        engine.remove_Fit_Problem(2)
+        chisqr3, out3, cov3= engine.fit({'A':2,'B':1},None,None)
+        #print "park",chisqr3, out3, cov3
+        self.assert_(math.fabs(out1[1]-2.5)/math.sqrt(cov1[1][1]) < 2)
+        print math.fabs(out1[0]-4.0)
+        #self.assert_(math.fabs(out1[0]-4.0)/math.sqrt(cov1[0][0]) < 2)
+        print chisqr1/len(data1.x)
+        #self.assert_(chisqr1/len(data1.x) < 2)
+        #self.assert_(chisqr1/len(data2.x) < 2)
+        #failing at 7 place
+        self.assertAlmostEquals(out3[1],out1[1])
+        self.assertAlmostEquals(out3[0],out1[0])
+        self.assertAlmostEquals(cov3[1][1],cov1[1][1])
+        self.assertAlmostEquals(cov3[0][0],cov1[0][0])
+        
+        self.assertAlmostEquals(out2[1],out1[1])
+        self.assertAlmostEquals(out2[0],out1[0])
+        self.assertAlmostEquals(cov2[1][1],cov1[1][1])
+        self.assertAlmostEquals(cov2[0][0],cov1[0][0])
+        
+        self.assertAlmostEquals(out2[1],out3[1])
+        self.assertAlmostEquals(out2[0],out3[0])
+        self.assertAlmostEquals(cov2[1][1],cov3[1][1])
+        self.assertAlmostEquals(cov2[0][0],cov3[0][0])
+        print chisqr1,chisqr2,chisqr3
+        #self.assertAlmostEquals(chisqr1,chisqr2)