comparison ABSexact.py @ 13:a2d881253324

In working, not debugged yet

+# -*- coding: utf-8 -*-
+"""
+Created on Fri Mar 09 14:06:13 2012
+
+@author: ncleju
+"""
+
+import numpy
+import pyCSalgos.BP.l1eq_pd
+import pyCSalgos.OMP.omp_QR
+import pyCSalgos.SL0.SL0
+import pyCSalgos.TST.RecommendedTST
+
+def bp(y,M,Omega,x0, lbtol=1e-3, mu=10, cgtol=1e-8, cgmaxiter=200, verbose=False):
+
+  N,n = Omega.shape
+  D = numpy.linalg.pinv(Omega)
+  U,S,Vt = numpy.linalg.svd(D)
+  Aextra = Vt[-(N-n):,:]
+  
+  # Create aggregate problem
+  Atilde = numpy.vstack((numpy.dot(M,D), Aextra))
+  ytilde = numpy.concatenate((y,numpy.zeros(N-n)))
+
+  return numpy.dot(D , pyCSalgos.BP.l1eq_pd.l1eq_pd(x0,Atilde,Atilde.T,ytilde, lbtol, mu, cgtol, cgmaxiter, verbose))
+
+def ompeps(y,M,Omega,epsilon):
+  
+  N,n = Omega.shape
+  D = numpy.linalg.pinv(Omega)
+  U,S,Vt = numpy.linalg.svd(D)
+  Aextra = Vt[-(N-n):,:]
+  
+  # Create aggregate problem
+  Atilde = numpy.vstack((numpy.dot(M,D), Aextra))
+  ytilde = numpy.concatenate((y,numpy.zeros(N-n)))
+  
+  opts = dict()
+  opts['stopCrit'] = 'mse'
+  opts['stopTol'] = epsilon
+  return numpy.dot(D , pyCSalgos.OMP.omp_QR.greed_omp_qr(aggy,aggD,aggD.shape[1],opts)[0])
+
+def ompk(y,M,Omega,k):
+  
+  N,n = Omega.shape
+  D = numpy.linalg.pinv(Omega)
+  U,S,Vt = numpy.linalg.svd(D)
+  Aextra = Vt[-(N-n):,:]
+  
+  # Create aggregate problem
+  Atilde = numpy.vstack((numpy.dot(M,D), Aextra))
+  ytilde = numpy.concatenate((y,numpy.zeros(N-n)))
+  
+  opts = dict()
+  opts['stopTol'] = k
+  return numpy.dot(D , pyCSalgos.OMP.omp_QR.greed_omp_qr(aggy,aggD,aggD.shape[1],opts)[0])
+
+def sl0(y,M,Omega, sigma_min, sigma_decrease_factor=0.5, mu_0=2, L=3, true_s=None):
+  
+  N,n = Omega.shape
+  D = numpy.linalg.pinv(Omega)
+  U,S,Vt = numpy.linalg.svd(D)
+  Aextra = Vt[-(N-n):,:]
+  
+  # Create aggregate problem
+  Atilde = numpy.vstack((numpy.dot(M,D), Aextra))
+  ytilde = numpy.concatenate((y,numpy.zeros(N-n)))
+  
+  return numpy.dot(D, pyCSalgos.SL0.SL0.SL0(Atilde,ytilde,sigma_min,sigma_decrease_factor,mu_0,L,true_s))
+
+def tst_recom(y,M,Omega, nsweep=300, tol=0.00001, xinitial=None, ro=None):
+  
+  N,n = Omega.shape
+  D = numpy.linalg.pinv(Omega)
+  U,S,Vt = numpy.linalg.svd(D)
+  Aextra = Vt[-(N-n):,:]
+  
+  # Create aggregate problem
+  Atilde = numpy.vstack((numpy.dot(M,D), Aextra))
+  ytilde = numpy.concatenate((y,numpy.zeros(N-n)))
+  
+  return numpy.dot(D, pyCSalgos.RecomTST.RecommendedTST.RecommendedTST(Atilde, ytilde, nsweep, tol, xinitial, ro))
+