Changeset 95d58d3 in sasview for test/park_integration

Timestamp:

Apr 10, 2014 8:05:28 PM (11 years ago)

Author:

pkienzle

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:

90f49a8

Parents:

6fe5100

Message:

fix fit line test for bumps/scipy/park and enable it as part of test suite

File:

• test/park_integration/test/utest_fit_line.py (moved) (moved from test/park_integration/test/test_fit_line.py) (11 diffs)

test/park_integration/test/utest_fit_line.py

@@ -6 +6 @@
 import math
 
-from sans.fit.AbstractFitEngine import Model
+from sans.fit.AbstractFitEngine import Model, FitHandler
 from sans.dataloader.loader import Loader
 from sans.fit.Fitting import Fit
@@ -14 +14 @@
 class testFitModule(unittest.TestCase):
     """ test fitting """
-   
-    def test1(self):
-        """ Fit 1 data (testdata_line.txt)and 1 model(lineModel) """
-        #load data
+
+    def test_bad_pars(self):
+        fitter = Fit('bumps')
+
         data = Loader().load("testdata_line.txt")
         data.name = data.filename
-        #Importing the Fit module
-        from bumps import fitters
-        fitters.FIT_DEFAULT = 'dream'
-        print fitters.FIT_OPTIONS['dream'].__dict__
-        fitter = Fit('bumps')
+        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('wrong parameter')
+        else:
+            raise AssertionError("No error raised for scipy fitting with wrong parameters name 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()
@@ -30 +46 @@
         model = Model(model1,data)
         #fit with scipy test
-        
-        pars1= ['param1','param2']
-        fitter.set_data(data,1)
-        try:fitter.set_model(model,1,pars1)
-        except ValueError,exc:
-            #print "ValueError was correctly raised: "+str(msg)
-            assert str(exc).startswith('wrong parameter')
-        else: raise AssertionError("No error raised for scipy fitting with wrong parameters name to fit")
+
         pars1= ['A','B']
         fitter.set_model(model,1,pars1)
         fitter.select_problem_for_fit(id=1,value=1)
-        result1, = fitter.fit()
-
-        self.assertTrue( math.fabs(result1.pvec[0]-4)/3 <= result1.stderr[0] )
-        self.assertTrue( math.fabs(result1.pvec[1]-2.5)/3 <= result1.stderr[1])
-        self.assertTrue( result1.fitness/len(data.x) < 2 )
-
-        return
-        #fit with park test
-        fitter = Fit('park')
-        fitter.set_data(data,1)
-        fitter.set_model(model,1,pars1)
-        fitter.select_problem_for_fit(id=1,value=1)
-        result2, = fitter.fit()
-        
-        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(data.x) < 2)
-        # compare fit result result for scipy and park
-        self.assertAlmostEquals( result1.pvec[0], result2.pvec[0] )
-        self.assertAlmostEquals( result1.pvec[1],result2.pvec[1] )
-        self.assertAlmostEquals( result1.stderr[0],result2.stderr[0] )
-        self.assertAlmostEquals( result1.stderr[1],result2.stderr[1] )
-        self.assertAlmostEquals( result1.fitness,
-                                 result2.fitness/len(data.x),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-2 )
+
+    def fit_bumps(self, alg, **opts):
+        #Importing the Fit module
+        from bumps import fitters
+        fitters.FIT_DEFAULT = alg
+        fitters.FIT_OPTIONS[alg].options.update(opts)
+        fitters.FIT_OPTIONS[alg].options.update(monitors=[])
+        #print "fitting",alg,opts
+        #kprint "options",fitters.FIT_OPTIONS[alg].__dict__
+        self.fit_single('bumps', isdream=(alg=='dream'))
+
+    def test_bumps_de(self):
+        self.fit_bumps('de')
+
+    def test_bumps_dream(self):
+        self.fit_bumps('dream', burn=500, steps=100)
+
+    def test_bumps_amoeba(self):
+        self.fit_bumps('amoeba')
+
+    def test_bumps_newton(self):
+        self.fit_bumps('newton')
+
+    def test_scipy(self):
+        #print "fitting scipy"
+        self.fit_single('scipy')
+
+    def test_park(self):
+        #print "fitting park"
+        self.fit_single('park')
+
         
     def test2(self):
@@ -97 +127 @@
         fitter.select_problem_for_fit(id=2,value=0)
         
-        try: result1, = fitter.fit()
+        try: result1, = fitter.fit(handler=FitHandler())
         except RuntimeError,msg:
            assert str(msg)=="No Assembly scheduled for Scipy fitting."
@@ -103 +133 @@
         fitter.select_problem_for_fit(id=1,value=1)
         fitter.select_problem_for_fit(id=2,value=1)
-        try: result1, = fitter.fit()
+        try: result1, = fitter.fit(handler=FitHandler())
         except RuntimeError,msg:
            assert str(msg)=="Scipy can't fit more than a single fit problem at a time."
         else: raise AssertionError,"No error raised for scipy fitting with more than 2 models"
 
-        return
         #fit with park test
         fitter = Fit('park')
@@ -117 +146 @@
         fitter.select_problem_for_fit(id=1,value=1)
         fitter.select_problem_for_fit(id=2,value=1)
-        R1,R2 = fitter.fit()
+        R1,R2 = fitter.fit(handler=FitHandler())
         
         self.assertTrue( math.fabs(R1.pvec[0]-4)/3 <= R1.stderr[0] )
@@ -126 +155 @@
     def test3(self):
         """ fit 2 data and 2 model with 1 constrainst"""
-        return
         #load data
         l = Loader()
@@ -163 +191 @@
         fitter.select_problem_for_fit(id=2,value=1)
         
-        R1,R2 = fitter.fit()
+        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])
@@ -194 +222 @@
         fitter.select_problem_for_fit(id=1,value=1)
         
-        result1, = fitter.fit()
+        result1, = fitter.fit(handler=FitHandler())
         #print(result1)
         self.assert_(result1)
@@ -202 +230 @@
         self.assertTrue( result1.fitness/len(data1.x) < 2 )
 
-        return
         #fit with park test
         fitter = Fit('park')
@@ -209 +236 @@
         fitter.set_data(data2,1,qmin=1,qmax=10)
         fitter.select_problem_for_fit(id=1,value=1)
-        result2, = fitter.fit()
+        result2, = fitter.fit(handler=FitHandler())
         
         self.assert_(result2)