Index: park_integration/AbstractFitEngine.py
===================================================================
--- park_integration/AbstractFitEngine.py	(revision 37d9521c19ce24d81fa059f1bdb35b421967f5ab)
+++ park_integration/AbstractFitEngine.py	(revision d53bc338cd87dedc3780e7ca774441b3057a9684)
@@ -46,5 +46,5 @@
             
         """
-        print "fitting parmater",pars
+        print "AbstractFitEngine:  fitting parmater",pars
         temp=[]
         if pars !={}:
@@ -60,5 +60,5 @@
                     temp.append(key)
             self.paramList.append(temp)
-            print "self.paramList2", self.paramList
+            print "AbstractFitEngine: self.paramList2", self.paramList
             #A fitArrange is already created but contains dList only at Uid
             if self.fitArrangeList.has_key(Uid):
Index: park_integration/test/cyl_testdata1.txt
===================================================================
--- park_integration/test/cyl_testdata1.txt	(revision d53bc338cd87dedc3780e7ca774441b3057a9684)
+++ park_integration/test/cyl_testdata1.txt	(revision d53bc338cd87dedc3780e7ca774441b3057a9684)
@@ -0,0 +1,54 @@
+0.007778 1.78E+14 13335629 
+0.015556 8.79E+13 9373745 
+0.023333 5.32E+13 7293888 
+0.031111 3.40E+13 5833464 
+0.038889 2.18E+13 4673821 
+0.046667 1.36E+13 3694509 
+0.054444 8.21E+12 2864896 
+0.062222 4.61E+12 2147159 
+0.07 2.35E+12 1533773 
+0.077778 1.05E+12 1023851 
+0.085556 3.92E+11 626398.4 
+0.093333 1.47E+11 383624.8 
+0.101111 1.19E+11 344493.8 
+0.108889 1.65E+11 405782 
+0.116667 2.33E+11 483191.5 
+0.124444 2.58E+11 507633.7 
+0.132222 2.44E+11 493743.9 
+0.14 2.12E+11 459920.6 
+0.147778 1.64E+11 404771.5 
+0.155556 1.22E+11 348706.2 
+0.163333 8.30E+10 288011.8 
+0.171111 5.79E+10 240564.5 
+0.178889 4.41E+10 209959 
+0.186667 4.02E+10 200480.7 
+0.194444 4.33E+10 208129.5 
+0.202222 5.33E+10 230891.5 
+0.21 4.99E+10 223441.9 
+0.217778 4.67E+10 216061.1 
+0.225556 3.93E+10 198298 
+0.233333 2.86E+10 169135.2 
+0.241111 1.79E+10 133639.4 
+0.248889 1.43E+10 119445.4 
+0.256667 9.39E+09 96907.02 
+0.264444 1.03E+10 101270.9 
+0.272222 1.03E+10 101272.4 
+0.28 9.56E+09 97788.34 
+0.287778 1.12E+10 105765.8 
+0.295556 1.05E+10 102300 
+0.303333 7.95E+09 89146.17 
+0.311111 5.42E+09 73599.25 
+0.318889 5.14E+09 71675.17 
+0.326667 5.81E+09 76192.06 
+0.334444 7.92E+09 89019.55 
+0.342222 9.75E+09 98739.25 
+0.35 7.84E+09 88553.99 
+0.357778 9.78E+09 98905.86 
+0.365556 1.66E+10 128748.6 
+0.373333 9.66E+09 98285.04 
+0.381111 6.74E+09 82088.98 
+0.388889 6.26E+09 79142.34 
+0.396667 7.47E+09 86426.79 
+0.404444 7.92E+09 88987.75 
+0.412222 7.04E+09 83895.53 
+0.42 4.67E+09 68340.98 
Index: park_integration/test/test_large_model.py
===================================================================
--- park_integration/test/test_large_model.py	(revision cfe97ea0b428b0187f4d80a432800b8dea085a37)
+++ park_integration/test/test_large_model.py	(revision d53bc338cd87dedc3780e7ca774441b3057a9684)
@@ -10,4 +10,51 @@
     """ test fitting """
     def testfit_1Data_1Model(self):
+        """ test fitting for one data and one model park vs scipy"""
+        #load data
+        from sans.fit.Loader import Load
+        load= Load()
+        load.set_filename("cyl_testdata.txt")
+        load.set_values()
+        data1 = Data1D(x=[], y=[],dx=None, dy=None)
+        load.load_data(data1)
+       
+        
+        #Importing the Fit module
+        from sans.fit.Fitting import Fit
+        fitter= Fit('scipy')
+        
+        # Receives the type of model for the fitting
+        from sans.models.CylinderModel import CylinderModel
+        model1  = CylinderModel()
+      
+        
+        #Do the fit SCIPY
+        fitter.set_data(data1,1)
+        import math
+        pars1={'background':0,'contrast':3*math.pow(10, -6),\
+                'cyl_phi':1,'cyl_theta':1,'length':400,'radius':20,'scale':1}
+        fitter.set_model(model1,"M1",1,pars1)
+       
+        
+        chisqr1, out1, cov1=fitter.fit()
+        print "scipy1",chisqr1, out1, cov1
+        pars2={'background':1.0,'contrast':400,\
+                'cyl_phi':20,'cyl_theta':0.0,'length':1.0,\
+                'radius':3*math.pow(10, -6),'scale':1.0}
+        fitter.set_model(model1,"M1",1,pars2)
+        chisqr2, out2, cov2=fitter.fit()
+        print "scipy2",chisqr2, out2, cov2
+        
+        pars3={'background':5.85693826,'contrast': 5.86071451,\
+                'cyl_phi':1.04547760*math.pow(10,-5),'cyl_theta':1.0,'length':0.0,\
+                'radius':1.39397013*math.pow(10, 3),'scale':20}
+        fitter.set_model(model1,"M1",1,pars3)
+        chisqr3, out3, cov3=fitter.fit()
+        print "scipy3",chisqr3, out3, cov3
+        self.assert_(chisqr1)
+        
+       
+      
+    def testfit_11Data_1Model(self):
         """ test fitting for one data and one model park vs scipy"""
         #load data
