tests fixed

1 files changed, 19 insertions, 38 deletions

diff --git a/Wrappers/Python/conda-recipe/run_test.py b/Wrappers/Python/conda-recipe/run_test.py
index 99ef239..398ef60 100755
--- a/Wrappers/Python/conda-recipe/run_test.py
+++ b/Wrappers/Python/conda-recipe/run_test.py
@@ -1,5 +1,4 @@
 import unittest

-import sys

 import numpy as np

 import os

 import timeit

@@ -58,7 +57,6 @@ class TestRegularisers(unittest.TestCase):
         u0 = u0.astype('float32')

         u_ref = u_ref.astype('float32')

         

-        #%%

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

         print ("____________ROF-TV bench___________________")

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

@@ -124,7 +122,6 @@ class TestRegularisers(unittest.TestCase):
         u0 = u0.astype('float32')

         u_ref = u_ref.astype('float32')

         

-        #%%

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

         print ("____________FGP-TV bench___________________")

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

@@ -280,7 +277,6 @@ class TestRegularisers(unittest.TestCase):
         u0 = u0.astype('float32')

         u_ref = u_ref.astype('float32')

         

-        #%%

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

         print ("____________TGV bench___________________")

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

@@ -355,7 +351,6 @@ class TestRegularisers(unittest.TestCase):
         u0 = u0.astype('float32')

         u_ref = u_ref.astype('float32')

         

-        #%%

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

         print ("____________LLT-ROF bench___________________")

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

@@ -405,7 +400,7 @@ class TestRegularisers(unittest.TestCase):
         diff_im[diff_im > tolerance] = 1

         self.assertLessEqual(diff_im.sum(), 1)

 

-    def test_Diff4th_CPU_vs_GPU(self):

+    def test_NDF_CPU_vs_GPU(self):

         filename = os.path.join("lena_gray_512.tif")

         plt = TiffReader()

         # read image

@@ -426,8 +421,6 @@ class TestRegularisers(unittest.TestCase):
         u0 = u0.astype('float32')

         u_ref = u_ref.astype('float32')

         

-

-        #%%

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

         print ("_______________NDF bench___________________")

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

@@ -509,12 +502,12 @@ class TestRegularisers(unittest.TestCase):
         

         # set parameters

         pars = {'algorithm' : DIFF4th, \

-                'input' : u0,\

-                'regularisation_parameter':3.5, \

-                'edge_parameter':0.02,\

-                'number_of_iterations' :500 ,\

-                'time_marching_parameter':0.001

-                }

+        'input' : u0,\

+        'regularisation_parameter':3.5, \

+        'edge_parameter':0.02,\

+        'number_of_iterations' :500 ,\

+        'time_marching_parameter':0.001

+        }

         

         print ("#############Diff4th CPU####################")

         start_time = timeit.default_timer()

@@ -550,7 +543,7 @@ class TestRegularisers(unittest.TestCase):
         diff_im = abs(diff4th_cpu - diff4th_gpu)

         diff_im[diff_im > tolerance] = 1

         self.assertLessEqual(diff_im.sum() , 1)

-        #%%

+

     def test_FDGdTV_CPU_vs_GPU(self):

         filename = os.path.join("lena_gray_512.tif")

         plt = TiffReader()

@@ -632,7 +625,6 @@ class TestRegularisers(unittest.TestCase):
         diff_im = abs(fgp_dtv_cpu - fgp_dtv_gpu)

         diff_im[diff_im > tolerance] = 1

         self.assertLessEqual(diff_im.sum(), 1)

-        #%%

 

     def test_cpu_ROF_TV(self):

         #filename = os.path.join(".." , ".." , ".." , "data" ,"testLena.npy")

@@ -643,18 +635,16 @@ class TestRegularisers(unittest.TestCase):
         # read image

         Im = plt.imread(filename)                     

         Im = np.asarray(Im, dtype='float32')

+        Im = Im/255

         

         """

         # 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,\

@@ -665,12 +655,12 @@ class TestRegularisers(unittest.TestCase):
         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

         print ("_________testing ROF-TV (2D, CPU)__________")

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

-        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)

     def test_cpu_FGP_TV(self):

@@ -682,23 +672,20 @@ class TestRegularisers(unittest.TestCase):
         # read image

         Im = plt.imread(filename)                     

         Im = np.asarray(Im, dtype='float32')

-        

+        Im = Im/255

         """

         # 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

         

         pars_fgp_tv = {'algorithm' : FGP_TV, \

                             'input' : Im,\

                             'regularisation_parameter':0.04, \

                             'number_of_iterations' :50 ,\

-                            'tolerance_constant':1e-08,\

+                            'tolerance_constant':1e-06,\

                             'methodTV': 0 ,\

                             'nonneg': 0 ,\

                             'printingOut': 0 

@@ -723,15 +710,12 @@ class TestRegularisers(unittest.TestCase):
 

         plt = TiffReader()

         # read image

-        Im = plt.imread(filename)                     

+        Im = plt.imread(filename)

         Im = np.asarray(Im, dtype='float32')

+        Im = Im/255

         

-        

-

-        #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, \

@@ -743,7 +727,6 @@ class TestRegularisers(unittest.TestCase):
         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

         print ("_________testing ROF-TV (2D, GPU)__________")

         print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")

-        res = True

         rof_gpu = ROF_TV(pars_rof_tv['input'],

              pars_rof_tv['regularisation_parameter'],

              pars_rof_tv['number_of_iterations'],

@@ -751,6 +734,7 @@ class TestRegularisers(unittest.TestCase):
         rms_rof = rmse(Im, rof_gpu)

         # now compare obtained rms with the expected value

         self.assertLess(abs(rms_rof-rms_rof_exp) , tolerance)

+    

     def test_gpu_FGP(self):

         #filename = os.path.join(".." , ".." , ".." , "data" ,"testLena.npy")

         filename = os.path.join("lena_gray_512.tif")

@@ -759,12 +743,9 @@ class TestRegularisers(unittest.TestCase):
         # read image

         Im = plt.imread(filename)                     

         Im = np.asarray(Im, dtype='float32')

-        

-        

-

-        #Im = Im/255

+        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 FGP-TV

@@ -772,7 +753,7 @@ class TestRegularisers(unittest.TestCase):
                             'input' : Im,\

                             'regularisation_parameter':0.04, \

                             'number_of_iterations' :50 ,\

-                            'tolerance_constant':1e-08,\

+                            'tolerance_constant':1e-06,\

                             'methodTV': 0 ,\

                             'nonneg': 0 ,\

                             'printingOut': 0