diff options
Diffstat (limited to 'Wrappers/Python')
| -rw-r--r-- | Wrappers/Python/demos/PDHG_examples/GatherAll/PDHG_TV_Denoising_2D_time.py | 79 |
1 files changed, 65 insertions, 14 deletions
diff --git a/Wrappers/Python/demos/PDHG_examples/GatherAll/PDHG_TV_Denoising_2D_time.py b/Wrappers/Python/demos/PDHG_examples/GatherAll/PDHG_TV_Denoising_2D_time.py index 14608db..febe76d 100644 --- a/Wrappers/Python/demos/PDHG_examples/GatherAll/PDHG_TV_Denoising_2D_time.py +++ b/Wrappers/Python/demos/PDHG_examples/GatherAll/PDHG_TV_Denoising_2D_time.py @@ -18,8 +18,24 @@ # limitations under the License. # #========================================================================= +""" -from ccpi.framework import ImageData, ImageGeometry, AcquisitionGeometry, AcquisitionData +Total Variation (Dynamic) Denoising using PDHG algorithm and Tomophantom: + + +Problem: min_{x} \alpha * ||\nabla x||_{2,1} + \frac{1}{2} * || x - g ||_{2}^{2} + + \alpha: Regularization parameter + + \nabla: Gradient operator + + g: 2D Dynamic noisy data with Gaussian Noise + + K = \nabla + +""" + +from ccpi.framework import ImageData, ImageGeometry import numpy as np import numpy @@ -28,7 +44,7 @@ import matplotlib.pyplot as plt from ccpi.optimisation.algorithms import PDHG from ccpi.optimisation.operators import BlockOperator, Gradient, Identity -from ccpi.optimisation.functions import ZeroFunction, L2NormSquared, \ +from ccpi.optimisation.functions import ZeroFunction, L2NormSquared, \ MixedL21Norm, BlockFunction from ccpi.astra.ops import AstraProjectorMC @@ -41,11 +57,9 @@ from tomophantom import TomoP2D model = 102 # note that the selected model is temporal (2D + time) N = 128 # set dimension of the phantom -# one can specify an exact path to the parameters file -# path_library2D = '../../../PhantomLibrary/models/Phantom2DLibrary.dat' + path = os.path.dirname(tomophantom.__file__) path_library2D = os.path.join(path, "Phantom2DLibrary.dat") -#This will generate a N_size x N_size x Time frames phantom (2D + time) phantom_2Dt = TomoP2D.ModelTemporal(model, N, path_library2D) plt.close('all') @@ -58,16 +72,17 @@ for sl in range(0,np.shape(phantom_2Dt)[0]): # plt.pause(.1) # plt.draw - +# Setup geometries ig = ImageGeometry(voxel_num_x = N, voxel_num_y = N, channels = np.shape(phantom_2Dt)[0]) data = ImageData(phantom_2Dt, geometry=ig) ag = ig -# Create Noisy data. Add Gaussian noise +# Create noisy data. Apply Gaussian noise np.random.seed(10) noisy_data = ImageData( data.as_array() + np.random.normal(0, 0.25, size=ig.shape) ) -tindex = [3, 6, 10] +# time-frames index +tindex = [8, 16, 24] fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(10, 10)) plt.subplot(1,3,1) @@ -88,15 +103,12 @@ fig.subplots_adjust(bottom=0.1, top=0.9, left=0.1, right=0.8, plt.show() -#%% # Regularisation Parameter alpha = 0.3 # Create operators -#op1 = Gradient(ig) op1 = Gradient(ig, correlation='Space') op2 = Gradient(ig, correlation='SpaceChannels') - op3 = Identity(ig, ag) # Create BlockOperator @@ -138,7 +150,7 @@ pdhg2.run(2000) #%% -tindex = [3, 6, 10] +tindex = [8, 16, 24] fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(10, 8)) plt.subplot(3,3,1) @@ -177,7 +189,7 @@ plt.subplot(3,3,9) plt.imshow(pdhg2.get_output().as_array()[tindex[2],:,:]) plt.axis('off') -#%% + im = plt.imshow(pdhg1.get_output().as_array()[tindex[0],:,:]) @@ -186,7 +198,46 @@ fig.subplots_adjust(bottom=0.1, top=0.9, left=0.1, right=0.8, cb_ax = fig.add_axes([0.83, 0.1, 0.02, 0.8]) cbar = fig.colorbar(im, cax=cb_ax) +plt.show() + +#%% +import matplotlib.animation as animation +fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(10, 30)) +ims1 = [] +ims2 = [] +ims3 = [] +for sl in range(0,np.shape(phantom_2Dt)[0]): + + plt.subplot(1,3,1) + im1 = plt.imshow(phantom_2Dt[sl,:,:], animated=True) + + plt.subplot(1,3,2) + im2 = plt.imshow(pdhg1.get_output().as_array()[sl,:,:]) + + plt.subplot(1,3,3) + im3 = plt.imshow(pdhg2.get_output().as_array()[sl,:,:]) + + ims1.append([im1]) + ims2.append([im2]) + ims3.append([im3]) + + +ani1 = animation.ArtistAnimation(fig, ims1, interval=500, + repeat_delay=10) + +ani2 = animation.ArtistAnimation(fig, ims2, interval=500, + repeat_delay=10) + +ani3 = animation.ArtistAnimation(fig, ims3, interval=500, + repeat_delay=10) +plt.show() +# plt.pause(0.25) +# plt.show() + + + + + -plt.show() |