Changed a lot of small things in everything for CDP

proxtoolbox/Algorithms/AP_expert.py

@@ -5,10 +5,12 @@ Created on Mon Dec 14 13:08:06 2015
 @author: rebecca
 """
 
-from math import sqrt
-from numpy import zeros
+from math import sqrt, exp
+from numpy import zeros, angle
+from numpy import all as a
 from scipy.linalg import norm
 from .algorithms import Algorithm
+from trace import Trace
 
 class AP_expert(Algorithm):
     """
@@ -51,9 +53,10 @@ class AP_expert(Algorithm):
         self.iters = 0
 
         if 'truth' in config:
-            self.truth = config['truth']
-            self.truth_dim = config['truth_dim']
-            self.norm_truth = config['norm_truth']
+            self.Truth = config['truth']
+            self.Truth_dim = config['truth_dim']
+            self.norm_Truth = config['norm_truth']
+            
     
     def run(self, u, tol, maxiter):
         """
@@ -91,18 +94,18 @@ class AP_expert(Algorithm):
             tmp1 = prox2.work(tmp_u);
             
             tmp_change = 0; tmp_gap = 0;
-
             if p==1 and q==1:
                 tmp_change= (norm(u-tmp_u, 'fro')/norm_data)**2
                 tmp_gap = (norm(tmp1-tmp_u,'fro')/norm_data)**2
                 if hasattr(self, 'truth'):
-                    if self.truth_dim[0] == 1:
+               
+                    if self.Truth_dim[0] == 1:
                       z=tmp_u[0,:]
-                    elif self.truth_dim[1]==1:
+                    elif self.Truth_dim[1]==1:
                       z=tmp_u[:,0]
                     else:
                       z=tmp_u
-                    Relerrs[iter] = norm(self.truth - exp(-1j*angle(trace(self.truth.T*z))) * z, 'fro')/self.norm_truth
+                    Relerrs[iter] = norm(self.Truth - exp(-1j*angle(Trace(self.Truth.T*z))) * z, 'fro')/self.norm_Truth
 
             elif q==1:
               for j in range(self.product_space_dimension):

proxtoolbox/Algorithms/SimpleAlgortihm.py

@@ -53,9 +53,9 @@ class SimpleAlgorithm:
         self.config = config
 
         if 'truth' in config:
-            self.truth = config['truth']
-            self.truth_dim = config['truth_dim']
-            self.norm_truth = config['norm_truth']
+            self.Truth = config['truth']
+            self.Truth_dim = config['truth_dim']
+            self.norm_Truth = config['norm_truth']
 
         if 'diagnostic' in config:
             self.diagnostic = True
@@ -143,15 +143,15 @@ class SimpleAlgorithm:
                     tmp_gap = phase_offset_compensated_norm(u1, u2, norm_factor=norm_data, norm_type='fro') ** 2
 
                     if hasattr(self, 'truth'):
-                        if self.truth_dim[0] == 1:
+                        if self.Truth_dim[0] == 1:
                             z = u1[0, :]
-                        elif self.truth_dim[1] == 1:
+                        elif self.Truth_dim[1] == 1:
                             z = u1[:, 0]
                         else:
                             z = u1
                         # Relerrs[iter] = norm(self.truth - exp(-1j * angle(trace(self.truth.T * z))) * z,
                         #                      'fro') / self.norm_truth
-                        Relerrs[iter] = phase_offset_compensated_norm(self.truth, z, norm_factor=self.norm_truth,
+                        Relerrs[iter] = phase_offset_compensated_norm(self.Truth, z, norm_factor=self.norm_Truth,
                                                                       norm_type='fro')
 
             elif q == 1:
@@ -164,8 +164,9 @@ class SimpleAlgorithm:
                 if 'diagnostic' in self.config:
                     if hasattr(self, 'truth'):
                         z = u1[:, :, 0]
-                        Relerrs[iter] = norm(self.truth - exp(-1j * angle(trace(self.truth.T * z))) * z,
-                                             'fro') / self.norm_truth
+                        print(z.shape)
+                        print(self.Truth.T.shape)
+                        Relerrs[iter] = norm((self.Truth - exp(-1j * angle(trace(self.Truth.T * z))) * z),'fro') / self.norm_Truth
 
             else:
                 if 'diagnostic' in self.config:
@@ -181,8 +182,8 @@ class SimpleAlgorithm:
                                     norm(u2[:, :, k, j] - shadow[:, :, k, j], 'fro') / (norm_data)) ** 2
                 if hasattr(self, 'truth') and (j == 0):
                     Relerrs[iter] = Relerrs[iter] + norm(
-                        self.truth - exp(-1j * angle(trace(self.truth.T * u1[:, :, k, 1]))) * u1[:, :, k, 1],
-                        'fro') / self.norm_truth
+                        self.Truth - exp(-1j * angle(trace(self.truth.T * u1[:, :, k, 1]))) * u1[:, :, k, 1],
+                        'fro') / self.norm_Truth
 
             change[iter] = sqrt(tmp_change)
             if 'diagnostic' in self.config:

proxtoolbox/Problems/Phase/CDP_1D_AltP_cold_in.py

@@ -20,7 +20,7 @@ new_config = {
 
 	'warmup_iter' : 0,
 
-	'method' : 'AP_expert',
+	'algorithm' : 'AP_expert',
 	'numruns' : 100,
 	'keep_log' : 1,
 

proxtoolbox/Problems/Phase/CDP_1D_AltP_warm_in.py

@@ -18,7 +18,7 @@ new_config = {
 # 'Problem Parameter'
 #::::::::::::::::::::::::::::::::::::::
 # 'What is the name of data file'?
- 'Data_Filename' : 'CDP_Processor',
+ 'data_filename' : 'CDP_processor',
 
 
 # What type of object are we working with?
@@ -28,13 +28,13 @@ new_config = {
 # What type of constraints do we have?
 # Options are: 'support only', 'real and support', 'nonnegative and support',
 #              'amplitude only', 'sparse real', 'sparse complex', and 'hybrid'
-'Constraint' : 'Hybride',
+    'constraint' : 'Hybride',
 
 
 # What type of measurements are we working with?
 # Options are: 'single diffraction', 'JWST', 'CDP', 
 #              'ptychography', and 'complex'
-	'Experiment' : 'CDP',
+	'experiment' : 'CDP',
 
 
 # The input data are coded diffraction patterns about a random complex
@@ -46,7 +46,7 @@ new_config = {
 	'Nz':1,  # images are 1 or 2D
 
 # Make masks and linear sampling operators
-	'Product_space_dimension' : 10,  # 6 for 1D signals % Number of masks  
+	'product_space_dimension' : 10,  # 6 for 1D signals % Number of masks  
 
 # Are the measurements in the far field or near field?
 # Options are: 'far field' or 'near field',
@@ -64,7 +64,7 @@ new_config = {
 # able to control ('without too much damage')
 
 # 'Algorithm':
-	'Method' : 'AP',#'Accelerated_AP_product_space',  
+'algorithm' : 'AP',#'Accelerated_AP_product_space',  
 'numruns':100,# the only time this parameter will
 # be different than 1 is when we are
 # benchmarking...not something a normal user
@@ -95,7 +95,7 @@ new_config = {
 # 'Parameter for the data regularization 
     # need to discuss how/whether the user should
     # put in information about the noise
-    'Input.data_ball' : 1e-15,  
+    'data_ball' : 1e-15,  
     # the above is the percentage of the gap
     # between the measured data and the
     # initial guess satisfying the

proxtoolbox/Problems/Phase/CDP_1D_DRAP_warm_in.py

@@ -60,7 +60,7 @@ new_config = {
 # able to control (without too much damage)
 
 # 'Algorithm':
-	'method' : 'DRAP',#'Accelerated_AP_product_space',  
+	'algorithm' : 'DRAP',#'Accelerated_AP_product_space',  
 	'numruns':100, # the only time this parameter will
 # be different than 1 is when we are
 # benchmarking...not something a normal user

proxtoolbox/Problems/Phase/CDP_1D_QNAP_cold_in.py

@@ -60,7 +60,7 @@ new_config = {
 	# able to control (without too much damage)
 
 	# Algorithm:
-	'method' : 'QNAP', # 'Accelerated_AP_product_space',
+	'algorithm' : 'QNAP', # 'Accelerated_AP_product_space',
 	'numruns' : 100, # the only this parameter will be different than 1
 	# is when we are benchmarking...not something a normal user would be doing
 	'keep_log' : 1,

proxtoolbox/Problems/Phase/CDP_1D_RAAR_warm_in.py

@@ -57,7 +57,7 @@ new_config = {
 # able to control (without too much damage)
 
 # 'Algorithm':
-	'method' : 'RAAR',#'Accelerated_AP_product_space',  
+	'algorithm' : 'RAAR',#'Accelerated_AP_product_space',  
 	'numruns':100, # the only time this parameter will
 # be different than 1 is when we are
 # benchmarking...not something a normal user

proxtoolbox/Problems/Phase/CDP_1D_Wirt_cold_in.py

@@ -39,9 +39,9 @@ new_config = {
 # 'Valued image'.
 
 # 'Make image'
-	'ny' : 128,
-	'nx' : 1, # 1 for 1D signals 
-	'nz':1,  # images are 1 or 2D
+	'Ny' : 128,
+	'Nx' : 1, # 1 for 1D signals 
+	'Nz':1,  # images are 1 or 2D
 
 # 'Make masks and linear sampling operators'
 	'product_space_dimension' :10,  # 6 for 1D signals % Number of masks  

proxtoolbox/Problems/Phase/CDP_2D_AltP_cold_in.py

@@ -56,7 +56,7 @@ new_config = {
 ## able to control (without too much damage)
 
 ## Algorithm:
-'method' : 'AP', #'Accelerated_AP_product_space';  
+'algorithm' : 'AP', #'Accelerated_AP_product_space';  
 'numruns' : 100, # the only time this parameter will
 # be different than 1 is when we are
 # benchmarking...not something a normal user

proxtoolbox/Problems/Phase/CDP_2D_DRAP_cold_in.py

@@ -56,7 +56,7 @@ new_config = {
 ## able to control (without too much damage)
 
 ## Algorithm:
-'method' : 'DRAP', #'Accelerated_AP_product_space';  
+'algorithm' : 'DRAP', #'Accelerated_AP_product_space';  
 'numruns' : 100, # the only time this parameter will
 # be different than 1 is when we are
 # benchmarking...not something a normal user

proxtoolbox/Problems/Phase/CDP_2D_QNAP_warm_in.py

@@ -56,7 +56,7 @@ new_config = {
 ## able to control (without too much damage)
 
 ## Algorithm:
-'method' : 'QNAP', #'Accelerated_AP_product_space';  
+'algorithm' : 'QNAP', #'Accelerated_AP_product_space';  
 'numruns' : 100, # the only time this parameter will
 # be different than 1 is when we are
 # benchmarking...not something a normal user

proxtoolbox/Problems/Phase/CDP_2D_Wirt_cold_in.py

@@ -56,7 +56,10 @@ new_config = {
 ## able to control (without too much damage)
 
 ## Algorithm:
-'method' : 'Wirtinger', #'Accelerated_AP_product_space';  
+
+## IMPORTANT: algorithm used to be Wirtinger, not sure if AP also works
+
+'algorithm' : 'AP', #'Accelerated_AP_product_space';  
 'numruns' : 100, # the only time this parameter will
 # be different than 1 is when we are
 # benchmarking...not something a normal user

proxtoolbox/Problems/Phase/Graphics/Phase_graphics.py

@@ -38,6 +38,11 @@ def Phase_graphics(config, output):
     #beta0 = config['beta_0']
     #beta_max = config['beta_max']
     u_0 = config['u_0']
+    
+    u = output['u1']
+    print(u.shape)
+    
+    
     if output['u1'].ndim == 2:
         u = output['u1']
         u2 = output['u2']

proxtoolbox/ProxOperators/proxoperators.py

@@ -127,7 +127,6 @@ class P_diag(ProxOperator):
         m = self.m;
         p = self.p;
         K = self.K;
-        print(u.shape)
 
         if m == 1:
             tmp = sum(u, axis=0, dtype=u.dtype)
@@ -137,9 +136,8 @@ class P_diag(ProxOperator):
             tmp = zeros((m,n), dtype=u.dtype)
             for k in range(K):
                 tmp += u[:, :, k]
-                print(tmp)
         else:
-            tmp = zeros((m, n, p), dtype=u.dtype)
+            tmp = zeros((m,n, p), dtype=u.dtype)
             for k in range(K):
                 tmp += u[:, :, :, k]
 
@@ -153,10 +151,9 @@ class P_diag(ProxOperator):
             u_diag = empty((m,n, K), dtype=u.dtype)
             for k in range(K):
                 u_diag[:, :, k] = tmp
-                print(u_diag.shape)
             return u_diag
         else:
-            u_diag = empty((n, m, p, K), dtype=u.dtype)
+            u_diag = empty((m,n, p, K), dtype=u.dtype)
             for k in range(K):
                 u_diag[:, :, :, k] = tmp
             return u_diag