Commit 34a9882d by markus.meier01

### Fixed some errors in CDP_candes

parent 771ed8f3
 from numpy.random import randn, random_sample from numpy.matlib import repmat from numpy.linalg import norm from numpy import sqrt, conj, reshape from numpy.fft import fft2, ifft2 from numpy import sqrt, conj, reshape, mean import matplotlib.pyplot as plt import numpy as np import random ... ... @@ -22,7 +21,7 @@ def CDP_Candes(config): ## Make image n1 = 128, n2 = 256, x = randn(n1,n2) + 1j*andn(n1,n2) x = randn(n1,n2) + 1j*randn(n1,n2) # Make masks and linear sampling operators ... ... @@ -40,8 +39,8 @@ def CDP_Candes(config): # Make linear operators; A is forward map and # At its scaled adjoint (At(Y)*numel(Y) is the adjoint) A = lambda I: fft2(conj(Masks)*reshape(repmat(I, 1, L), np.size(I,1), np.size(I,2), L)) # Input is n1 x n2 image, output is n1 x n2 x L array At = lambda Y: mean(Masks*ifft2,3) # Input is n1 x n2 X L array, output is n1 x n2 image A = lambda I: fft2(conj(Masks)*reshape(tile(I, [1,L]), [I.shape[0], I.shape[1], L])) # Input is n1 x n2 image, output is n1 x n2 x L array At = lambda Y: mean(Masks*ifft2,axis=1) # Input is n1 x n2 X L array, output is n1 x n2 image # Data ... ...
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!