UQTk: Uncertainty Quantification Toolkit  3.1.1
bcs.h
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30 
31 #ifndef BCS_H
32 #define BCS_H
33 
34 #include "Array1D.h"
35 #include "Array2D.h"
36 
37 
38 #define MAX_IT 1000
39 
40 
41 
64 void WBCS(Array2D<double> &PHI, Array1D<double> &y, double &sigma2,
65  double eta, Array1D<double> &lambda_init,
66  int adaptive, int optimal, double scale, int verbose,
67  Array1D<double> &weights, Array1D<int> &used,
68  Array1D<double> &errbars, Array1D<double> &basis,
69  Array1D<double> &alpha, Array2D<double> &Sig);
70 
71 
72 
75 void BCS(Array2D<double> &PHI, Array1D<double> &y, double &sigma2,
76  double eta, Array1D<double> &lambda_init,
77  int adaptive, int optimal, double scale, int verbose,
78  Array1D<double> &weights, Array1D<int> &used,
79  Array1D<double> &errbars, Array1D<double> &basis,
80  Array1D<double> &alpha, double &lambda) ;
81 
82 
83 
84 #endif // BCS_H
1D Array class for any type T
2D Array class for any type T
Array1D< double > scale(Array1D< double > &x, double alpha)
Returns 1D Arrays scaled by a double.
Definition: arraytools.cpp:1828
void WBCS(Array2D< double > &PHI, Array1D< double > &y, double &sigma2, double eta, Array1D< double > &lambda_init, int adaptive, int optimal, double scale, int verbose, Array1D< double > &weights, Array1D< int > &used, Array1D< double > &errbars, Array1D< double > &basis, Array1D< double > &alpha, Array2D< double > &Sig)
Implements weighted version of the original Bayesian Compressive Sensing algorithm.
Definition: bcs.cpp:61
void BCS(Array2D< double > &PHI, Array1D< double > &y, double &sigma2, double eta, Array1D< double > &lambda_init, int adaptive, int optimal, double scale, int verbose, Array1D< double > &weights, Array1D< int > &used, Array1D< double > &errbars, Array1D< double > &basis, Array1D< double > &alpha, double &lambda)
Essentially same functionality as WBCS, but slightly altered I/O.
Definition: bcs.cpp:478
Definition: Array1D.h:472
Definition: Array1D.h:262