diff options
Diffstat (limited to 'Wrappers')
| -rwxr-xr-x | Wrappers/Python/wip/pdhg_TV_denoising.py | 38 |
1 files changed, 18 insertions, 20 deletions
diff --git a/Wrappers/Python/wip/pdhg_TV_denoising.py b/Wrappers/Python/wip/pdhg_TV_denoising.py index 3819de5..a8e721f 100755 --- a/Wrappers/Python/wip/pdhg_TV_denoising.py +++ b/Wrappers/Python/wip/pdhg_TV_denoising.py @@ -19,10 +19,12 @@ from ccpi.optimisation.functions import ZeroFun, L2NormSquared, \ from skimage.util import random_noise + + # ############################################################################ # Create phantom for TV denoising -N = 200 +N = 600 data = np.zeros((N,N)) data[round(N/4):round(3*N/4),round(N/4):round(3*N/4)] = 0.5 data[round(N/8):round(7*N/8),round(3*N/8):round(5*N/8)] = 1 @@ -38,7 +40,7 @@ noisy_data = ImageData(n1) #%% # Regularisation Parameter -alpha = 200 +alpha = 2 #method = input("Enter structure of PDHG (0=Composite or 1=NotComposite): ") method = '0' @@ -79,31 +81,27 @@ print ("normK", normK) sigma = 1 tau = 1/(sigma*normK**2) +pdhg = PDHG(f=f,g=g,operator=operator, tau=tau, sigma=sigma) +pdhg.max_iteration = 2000 +pdhg.update_objective_interval = 10 + +pdhg.run(2000) -#%% -## Number of iterations -opt = {'niter':2000} -## -### Run algorithm -result, total_time, objective = PDHG(f, g, operator, \ - tau = tau, sigma = sigma, opt = opt) -#%% -###Show results -if isinstance(result, BlockDataContainer): - sol = result.get_item(0).as_array() -else: - sol = result.as_array() + +sol = pdhg.get_output().as_array() #sol = result.as_array() # +fig = plt.figure() +plt.subplot(1,2,1) +plt.imshow(noisy_data.as_array()) +#plt.colorbar() +plt.subplot(1,2,2) plt.imshow(sol) -plt.colorbar() +#plt.colorbar() plt.show() # -### -plt.imshow(noisy_data.as_array()) -plt.colorbar() -plt.show() + ## plt.plot(np.linspace(0,N,N), data[int(N/2),:], label = 'GTruth') plt.plot(np.linspace(0,N,N), sol[int(N/2),:], label = 'Recon') |