Fixed some errors in CDP_candes

proxtoolbox/Problems/Phase/CDP_candes.py

 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