From c7653a276a3670585f5e781cd4e5847233a75fc2 Mon Sep 17 00:00:00 2001
From: Daniil Kazantsev <dkazanc@hotmail.com>
Date: Sat, 2 Jun 2018 10:47:00 +0100
Subject: tests fixed
---
Wrappers/Python/conda-recipe/run_test.py | 57 +++++++++++---------------------
1 file changed, 19 insertions(+), 38 deletions(-)
(limited to 'Wrappers/Python')
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
--
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