From 4af4096096af9f478e2a3d463b9dfcfc200454ff Mon Sep 17 00:00:00 2001
From: Daniil Kazantsev <dkazanc@hotmail.com>
Date: Wed, 19 Dec 2018 11:21:16 +0000
Subject: fixes issues in tests

---
 Readme.md                                |  2 +-
 Wrappers/Python/conda-recipe/run_test.py | 16 ++++++++--------
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/Readme.md b/Readme.md
index 089c9fe..f574f5f 100644
--- a/Readme.md
+++ b/Readme.md
@@ -88,7 +88,7 @@ conda install ccpi-regulariser -c ccpi -c conda-forge
 
 #### Python (conda-build)
 ```
-	export CIL_VERSION=0.10.2
+	export CIL_VERSION=0.10.3
 	conda build Wrappers/Python/conda-recipe --numpy 1.12 --python 3.5 
 	conda install ccpi-regulariser=${CIL_VERSION} --use-local --force
 	cd demos/
diff --git a/Wrappers/Python/conda-recipe/run_test.py b/Wrappers/Python/conda-recipe/run_test.py
index abc3e1b..cfb3f53 100755
--- a/Wrappers/Python/conda-recipe/run_test.py
+++ b/Wrappers/Python/conda-recipe/run_test.py
@@ -37,7 +37,7 @@ class TestRegularisers(unittest.TestCase):
     
 
     def test_ROF_TV_CPU_vs_GPU(self):
-        print ("tomas debug test function")
+        #print ("tomas debug test function")
         print(__name__)
         filename = os.path.join("lena_gray_512.tif")
         plt = TiffReader()
@@ -65,11 +65,11 @@ class TestRegularisers(unittest.TestCase):
         
         # set parameters
         pars = {'algorithm': ROF_TV, \
-                'input' : u0,\
-                'regularisation_parameter':0.04,\
-                'number_of_iterations': 1000,\
-                'time_marching_parameter': 0.0001
-                }
+        'input' : u0,\
+        'regularisation_parameter':0.04,\
+        'number_of_iterations': 2500,\
+        'time_marching_parameter': 0.00002
+        }
         print ("#############ROF TV CPU####################")
         start_time = timeit.default_timer()
         rof_cpu = ROF_TV(pars['input'],
@@ -607,8 +607,8 @@ class TestRegularisers(unittest.TestCase):
                 'input' : u0,\
                 'refdata' : u_ref,\
                 'regularisation_parameter':0.04, \
-                'number_of_iterations' :2000 ,\
-                'tolerance_constant':1e-06,\
+                'number_of_iterations' :1000 ,\
+                'tolerance_constant':1e-07,\
                 'eta_const':0.2,\
                 'methodTV': 0 ,\
                 'nonneg': 0 ,\
-- 
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