removed FBPD

3 files changed, 0 insertions, 85 deletions

diff --git a/Wrappers/Python/ccpi/optimisation/algorithms/FBPD.py b/Wrappers/Python/ccpi/optimisation/algorithms/FBPD.py
deleted file mode 100644
index 269438c..0000000
--- a/Wrappers/Python/ccpi/optimisation/algorithms/FBPD.py
+++ /dev/null
@@ -1,82 +0,0 @@
-# -*- coding: utf-8 -*-
-#   This work is part of the Core Imaging Library developed by
-#   Visual Analytics and Imaging System Group of the Science Technology
-#   Facilities Council, STFC
-
-#   Copyright 2019 Edoardo Pasca
-
-#   Licensed under the Apache License, Version 2.0 (the "License");
-#   you may not use this file except in compliance with the License.
-#   You may obtain a copy of the License at
-
-#       http://www.apache.org/licenses/LICENSE-2.0
-
-#   Unless required by applicable law or agreed to in writing, software
-#   distributed under the License is distributed on an "AS IS" BASIS,
-#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#   See the License for the specific language governing permissions and
-#   limitations under the License.
-"""
-Created on Thu Feb 21 11:09:03 2019
-
-@author: ofn77899
-"""
-
-from ccpi.optimisation.algorithms import Algorithm
-from ccpi.optimisation.functions import ZeroFunction
-        
-class FBPD(Algorithm):
-    '''FBPD Algorithm
-    
-    Parameters:
-      x_init: initial guess
-      f: constraint
-      g: data fidelity
-      h: regularizer
-      opt: additional algorithm 
-    '''
-    def __init__(self, **kwargs):
-        super(FBPD, self).__init__()
-        self.f = kwargs.get('f', None)
-        self.g = kwargs.get('g', ZeroFunction())
-        self.g = kwargs.get('h', ZeroFunction())
-        self.operator = kwargs.get('operator', None)
-        self.x_init = kwargs.get('x_init',None)
-        if self.x_init is not None and self.operator is not None:
-            self.set_up(self.x_init, self.operator, self.f, self.g, self.h)
-
-    def set_up(self, x_init, operator, constraint, data_fidelity, 
-               regulariser, opt=None):
-
-        
-        # algorithmic parameters
-        
-        
-        # step-sizes
-        self.tau   = 2 / (data_fidelity.L + 2)
-        self.sigma = (1/self.tau - data_fidelity.L/2) / regulariser.L
-        
-        self.inv_sigma = 1/self.sigma
-    
-        # initialization
-        self.x = x_init
-        self.y = operator.direct(self.x)
-        self.update_objective()
-        self.configured = True
-        
-    
-    def update(self):
-    
-        # primal forward-backward step
-        x_old = self.x
-        self.x = self.x - self.tau * ( self.g.gradient(self.x) + self.operator.adjoint(self.y) )
-        self.x = self.f.proximal(self.x, self.tau)
-    
-        # dual forward-backward step
-        self.y += self.sigma * self.operator.direct(2*self.x - x_old);
-        self.y -= self.sigma * self.h.proximal(self.inv_sigma*self.y, self.inv_sigma)   
-
-        # time and criterion
-
-    def update_objective(self):
-        self.loss.append(self.f(self.x) + self.g(self.x) + self.h(self.operator.direct(self.x)))
diff --git a/Wrappers/Python/ccpi/optimisation/algorithms/__init__.py b/Wrappers/Python/ccpi/optimisation/algorithms/__init__.py
index 2dbacfc..8f255f3 100644
--- a/Wrappers/Python/ccpi/optimisation/algorithms/__init__.py
+++ b/Wrappers/Python/ccpi/optimisation/algorithms/__init__.py
@@ -27,7 +27,5 @@ from .CGLS import CGLS
 from .SIRT import SIRT
 from .GradientDescent import GradientDescent
 from .FISTA import FISTA
-from .FBPD import FBPD
 from .PDHG import PDHG
-from .PDHG import PDHG_old
 
diff --git a/Wrappers/Python/test/test_algorithms.py b/Wrappers/Python/test/test_algorithms.py
index 4121358..8c398f4 100755
--- a/Wrappers/Python/test/test_algorithms.py
+++ b/Wrappers/Python/test/test_algorithms.py
@@ -18,7 +18,6 @@ from ccpi.optimisation.functions import Norm2Sq, ZeroFunction, \
 from ccpi.optimisation.algorithms import GradientDescent
 from ccpi.optimisation.algorithms import CGLS
 from ccpi.optimisation.algorithms import FISTA
-from ccpi.optimisation.algorithms import FBPD