implemented with unittest #43

1 files changed, 96 insertions, 52 deletions

diff --git a/Wrappers/Python/test/run_test.py b/Wrappers/Python/test/run_test.py
index 19af0ec..04bbd40 100644
--- a/Wrappers/Python/test/run_test.py
+++ b/Wrappers/Python/test/run_test.py
@@ -9,7 +9,11 @@ def rmse(im1, im2):
     return rmse
 
 class TestRegularisers(unittest.TestCase):
-    def __init__(self):
+    
+    def setUp(self):
+        pass
+
+    def test_cpu_regularisers(self):
         filename = os.path.join(".." , ".." , ".." , "data" ,"lena_gray_512.tif")
         
         # read noiseless image
@@ -17,89 +21,129 @@ class TestRegularisers(unittest.TestCase):
         Im = np.asarray(Im, dtype='float32')
 
         Im = Im/255
-        self.u0 = Im
-        self.Im = Im
-        self.tolerance = 1e-05
-        self.rms_rof_exp = 0.006812507 #expected value for ROF model
-        self.rms_fgp_exp = 0.019152347 #expected value for FGP model
+        tolerance = 1e-05
+        rms_rof_exp = 0.006812507 #expected value for ROF model
+        rms_fgp_exp = 0.019152347 #expected value for FGP model
         
         # set parameters for ROF-TV
-        self.pars_rof_tv = {'algorithm': ROF_TV, \
-        'input' : self.u0,\
-        'regularisation_parameter':0.04,\
-        'number_of_iterations': 50,\
-        'time_marching_parameter': 0.0025
-        }
+        pars_rof_tv = {'algorithm': ROF_TV, \
+                            'input' : Im,\
+                            'regularisation_parameter':0.04,\
+                            'number_of_iterations': 50,\
+                            'time_marching_parameter': 0.0025
+                            }
         # set parameters for FGP-TV
-        self.pars_fgp_tv = {'algorithm' : FGP_TV, \
-        'input' : self.u0,\
-        'regularisation_parameter':0.04, \
-        'number_of_iterations' :50 ,\
-        'tolerance_constant':1e-08,\
-        'methodTV': 0 ,\
-        'nonneg': 0 ,\
-        'printingOut': 0 
-        }
-    def test_cpu_regularisers(self):
+        pars_fgp_tv = {'algorithm' : FGP_TV, \
+                            'input' : Im,\
+                            'regularisation_parameter':0.04, \
+                            'number_of_iterations' :50 ,\
+                            'tolerance_constant':1e-08,\
+                            'methodTV': 0 ,\
+                            'nonneg': 0 ,\
+                            'printingOut': 0 
+                            }
         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
         print ("_________testing ROF-TV (2D, CPU)__________")
         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
-        rof_cpu = ROF_TV(self.pars_rof_tv['input'],
-             self.pars_rof_tv['regularisation_parameter'],
-             self.pars_rof_tv['number_of_iterations'],
-             self.pars_rof_tv['time_marching_parameter'],'cpu')
-        rms_rof = rmse(self.Im, rof_cpu)
+        res = True
+        rof_cpu = ROF_TV(pars_rof_tv['input'],
+             pars_rof_tv['regularisation_parameter'],
+             pars_rof_tv['number_of_iterations'],
+             pars_rof_tv['time_marching_parameter'],'cpu')
+        rms_rof = rmse(Im, rof_cpu)
         # now compare obtained rms with the expected value
+        self.assertLess(abs(rms_rof-rms_rof_exp) , tolerance)
+        """
         if abs(rms_rof-self.rms_rof_exp) > self.tolerance:
             raise TypeError('ROF-TV (2D, CPU) test FAILED')
         else:
             print ("test PASSED")
+        """
         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
         print ("_________testing FGP-TV (2D, CPU)__________")
         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
-        fgp_cpu = FGP_TV(self.pars_fgp_tv['input'], 
-              self.pars_fgp_tv['regularisation_parameter'],
-              self.pars_fgp_tv['number_of_iterations'],
-              self.pars_fgp_tv['tolerance_constant'], 
-              self.pars_fgp_tv['methodTV'],
-              self.pars_fgp_tv['nonneg'],
-              self.pars_fgp_tv['printingOut'],'cpu')  
-        rms_fgp = rmse(self.Im, fgp_cpu)
+        fgp_cpu = FGP_TV(pars_fgp_tv['input'], 
+              pars_fgp_tv['regularisation_parameter'],
+              pars_fgp_tv['number_of_iterations'],
+              pars_fgp_tv['tolerance_constant'], 
+              pars_fgp_tv['methodTV'],
+              pars_fgp_tv['nonneg'],
+              pars_fgp_tv['printingOut'],'cpu')  
+        rms_fgp = rmse(Im, fgp_cpu)
         # now compare obtained rms with the expected value
+        self.assertLess(abs(rms_fgp-rms_fgp_exp) , tolerance)
+        """
         if abs(rms_fgp-self.rms_fgp_exp) > self.tolerance:
             raise TypeError('FGP-TV (2D, CPU) test FAILED')
         else:
             print ("test PASSED")
+        """
+        self.assertTrue(res)
     def test_gpu_regularisers(self):
+        filename = os.path.join(".." , ".." , ".." , "data" ,"lena_gray_512.tif")
+        
+        # read noiseless image
+        Im = plt.imread(filename)
+        Im = np.asarray(Im, dtype='float32')
+
+        Im = Im/255
+        tolerance = 1e-05
+        rms_rof_exp = 0.006812507 #expected value for ROF model
+        rms_fgp_exp = 0.019152347 #expected value for FGP model
+        
+        # set parameters for ROF-TV
+        pars_rof_tv = {'algorithm': ROF_TV, \
+                            'input' : Im,\
+                            'regularisation_parameter':0.04,\
+                            'number_of_iterations': 50,\
+                            'time_marching_parameter': 0.0025
+                            }
+        # set parameters for FGP-TV
+        pars_fgp_tv = {'algorithm' : FGP_TV, \
+                            'input' : Im,\
+                            'regularisation_parameter':0.04, \
+                            'number_of_iterations' :50 ,\
+                            'tolerance_constant':1e-08,\
+                            'methodTV': 0 ,\
+                            'nonneg': 0 ,\
+                            'printingOut': 0 
+                            }
         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
         print ("_________testing ROF-TV (2D, GPU)__________")
         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
-        rof_gpu = ROF_TV(self.pars_rof_tv['input'],
-             self.pars_rof_tv['regularisation_parameter'],
-             self.pars_rof_tv['number_of_iterations'],
-             self.pars_rof_tv['time_marching_parameter'],'gpu')
-        rms_rof = rmse(self.Im, rof_gpu)
+        res = True
+        rof_gpu = ROF_TV(pars_rof_tv['input'],
+             pars_rof_tv['regularisation_parameter'],
+             pars_rof_tv['number_of_iterations'],
+             pars_rof_tv['time_marching_parameter'],'gpu')
+        rms_rof = rmse(Im, rof_gpu)
         # now compare obtained rms with the expected value
+        self.assertLess(abs(rms_rof-rms_rof_exp) , tolerance)
+        """
         if abs(rms_rof-self.rms_rof_exp) > self.tolerance:
             raise TypeError('ROF-TV (2D, GPU) test FAILED')
         else:
             print ("test PASSED")
+        """
         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
         print ("_________testing FGP-TV (2D, GPU)__________")
         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
-        fgp_gpu = FGP_TV(self.pars_fgp_tv['input'], 
-              self.pars_fgp_tv['regularisation_parameter'],
-              self.pars_fgp_tv['number_of_iterations'],
-              self.pars_fgp_tv['tolerance_constant'], 
-              self.pars_fgp_tv['methodTV'],
-              self.pars_fgp_tv['nonneg'],
-              self.pars_fgp_tv['printingOut'],'gpu')  
-        rms_fgp = rmse(self.Im, fgp_gpu)
+        fgp_gpu = FGP_TV(pars_fgp_tv['input'], 
+              pars_fgp_tv['regularisation_parameter'],
+              pars_fgp_tv['number_of_iterations'],
+              pars_fgp_tv['tolerance_constant'], 
+              pars_fgp_tv['methodTV'],
+              pars_fgp_tv['nonneg'],
+              pars_fgp_tv['printingOut'],'gpu')  
+        rms_fgp = rmse(Im, fgp_gpu)
+        # now compare obtained rms with the expected value
+        self.assertLess(abs(rms_fgp-rms_fgp_exp) , tolerance)
+        """
         if abs(rms_fgp-self.rms_fgp_exp) > self.tolerance:
             raise TypeError('FGP-TV (2D, GPU) test FAILED')
         else:
             print ("test PASSED")
-        # now compare obtained rms with the expected value
-        #self.assertLess(...)
-#if __name__ == '__main__':
-    #unittest.main()
\ No newline at end of file
+        """
+        self.assertTrue(res)
+if __name__ == '__main__':
+    unittest.main()
\ No newline at end of file