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-rw-r--r--Wrappers/Python/wip/Demos/PDHG_TGV_Tomo2D.py2
-rw-r--r--Wrappers/Python/wip/Demos/PDHG_TV_Denoising_Poisson.py2
-rw-r--r--Wrappers/Python/wip/Demos/PDHG_Tikhonov_Denoising.py2
-rw-r--r--Wrappers/Python/wip/Demos/PDHG_Tikhonov_Tomo2D.py2
4 files changed, 4 insertions, 4 deletions
diff --git a/Wrappers/Python/wip/Demos/PDHG_TGV_Tomo2D.py b/Wrappers/Python/wip/Demos/PDHG_TGV_Tomo2D.py
index 26578bb..49d4db6 100644
--- a/Wrappers/Python/wip/Demos/PDHG_TGV_Tomo2D.py
+++ b/Wrappers/Python/wip/Demos/PDHG_TGV_Tomo2D.py
@@ -51,7 +51,7 @@ detectors = N
angles = np.linspace(0, np.pi, N, dtype=np.float32)
ag = AcquisitionGeometry('parallel','2D',angles, detectors)
-Aop = AstraProjectorSimple(ig, ag, 'cpu')
+Aop = AstraProjectorSimple(ig, ag, 'gpu')
sin = Aop.direct(data)
# Create noisy data. Apply Poisson noise
diff --git a/Wrappers/Python/wip/Demos/PDHG_TV_Denoising_Poisson.py b/Wrappers/Python/wip/Demos/PDHG_TV_Denoising_Poisson.py
index 58978ae..4903c44 100644
--- a/Wrappers/Python/wip/Demos/PDHG_TV_Denoising_Poisson.py
+++ b/Wrappers/Python/wip/Demos/PDHG_TV_Denoising_Poisson.py
@@ -48,7 +48,7 @@ noisy_data = ImageData(n1)
# Regularisation Parameter
alpha = 2
-method = '0'
+method = '1'
if method == '0':
diff --git a/Wrappers/Python/wip/Demos/PDHG_Tikhonov_Denoising.py b/Wrappers/Python/wip/Demos/PDHG_Tikhonov_Denoising.py
index 3f275e2..041d4ee 100644
--- a/Wrappers/Python/wip/Demos/PDHG_Tikhonov_Denoising.py
+++ b/Wrappers/Python/wip/Demos/PDHG_Tikhonov_Denoising.py
@@ -47,7 +47,7 @@ noisy_data = ImageData(n1)
# Regularisation Parameter
alpha = 4
-method = '1'
+method = '0'
if method == '0':
diff --git a/Wrappers/Python/wip/Demos/PDHG_Tikhonov_Tomo2D.py b/Wrappers/Python/wip/Demos/PDHG_Tikhonov_Tomo2D.py
index 5c03362..f17c4fe 100644
--- a/Wrappers/Python/wip/Demos/PDHG_Tikhonov_Tomo2D.py
+++ b/Wrappers/Python/wip/Demos/PDHG_Tikhonov_Tomo2D.py
@@ -43,7 +43,7 @@ detectors = N
angles = np.linspace(0, np.pi, N, dtype=np.float32)
ag = AcquisitionGeometry('parallel','2D',angles, detectors)
-Aop = AstraProjectorSimple(ig, ag, 'cpu')
+Aop = AstraProjectorSimple(ig, ag, 'gpu')
sin = Aop.direct(data)
# Create noisy data. Apply Gaussian noise