/*************************************************************************
* L-BFGS algorithm results
*
* Called after MinLBFGSIteration() returned False.
*
* INPUT PARAMETERS:
* State - algorithm state (used by MinLBFGSIteration).
*
* OUTPUT PARAMETERS:
* X - array[0..N-1], solution
* Rep - optimization report:
* Rep.TerminationType completetion code:
* -2 rounding errors prevent further improvement.
* X contains best point found.
* -1 incorrect parameters were specified
* 1 relative function improvement is no more than
* EpsF.
* 2 relative step is no more than EpsX.
* 4 gradient norm is no more than EpsG
* 5 MaxIts steps was taken
* 7 stopping conditions are too stringent,
* further improvement is impossible
* Rep.IterationsCount contains iterations count
* NFEV countains number of function calculations
*
* -- ALGLIB --
* Copyright 02.04.2010 by Bochkanov Sergey
*************************************************************************/
public static void minlbfgsresults(ref minlbfgsstate state,
ref double[] x,
ref minlbfgsreport rep)
{
int i_ = 0;
x = new double[state.n - 1 + 1];
for (i_ = 0; i_ <= state.n - 1; i_++)
{
x[i_] = state.x[i_];
}
rep.iterationscount = state.repiterationscount;
rep.nfev = state.repnfev;
rep.terminationtype = state.repterminationtype;
}
/*************************************************************************
L-BFGS algorithm results
Buffered implementation of MinLBFGSResults which uses pre-allocated buffer
to store X[]. If buffer size is too small, it resizes buffer. It is
intended to be used in the inner cycles of performance critical algorithms
where array reallocation penalty is too large to be ignored.
-- ALGLIB --
Copyright 20.08.2010 by Bochkanov Sergey
*************************************************************************/
public static void minlbfgsresultsbuf(minlbfgsstate state,
ref double[] x,
minlbfgsreport rep)
{
int i_ = 0;
if( alglib.ap.len(x)<state.n )
{
x = new double[state.n];
}
for(i_=0; i_<=state.n-1;i_++)
{
x[i_] = state.x[i_];
}
rep.iterationscount = state.repiterationscount;
rep.nfev = state.repnfev;
rep.varidx = state.repvaridx;
rep.terminationtype = state.repterminationtype;
}
/*************************************************************************
L-BFGS algorithm results
INPUT PARAMETERS:
State - algorithm state
OUTPUT PARAMETERS:
X - array[0..N-1], solution
Rep - optimization report:
* Rep.TerminationType completetion code:
* -8 internal integrity control detected infinite
or NAN values in function/gradient. Abnormal
termination signalled.
* -7 gradient verification failed.
See MinLBFGSSetGradientCheck() for more information.
* -2 rounding errors prevent further improvement.
X contains best point found.
* -1 incorrect parameters were specified
* 1 relative function improvement is no more than
EpsF.
* 2 relative step is no more than EpsX.
* 4 gradient norm is no more than EpsG
* 5 MaxIts steps was taken
* 7 stopping conditions are too stringent,
further improvement is impossible
* 8 terminated by user who called minlbfgsrequesttermination().
X contains point which was "current accepted" when
termination request was submitted.
* Rep.IterationsCount contains iterations count
* NFEV countains number of function calculations
-- ALGLIB --
Copyright 02.04.2010 by Bochkanov Sergey
*************************************************************************/
public static void minlbfgsresults(minlbfgsstate state,
ref double[] x,
minlbfgsreport rep)
{
x = new double[0];
minlbfgsresultsbuf(state, ref x, rep);
}
public override alglib.apobject make_copy()
{
minlbfgsreport _result = new minlbfgsreport();
_result.iterationscount = iterationscount;
_result.nfev = nfev;
_result.varidx = varidx;
_result.terminationtype = terminationtype;
return _result;
}
/*************************************************************************
L-BFGS algorithm results
Buffered implementation of MinLBFGSResults which uses pre-allocated buffer
to store X[]. If buffer size is too small, it resizes buffer. It is
intended to be used in the inner cycles of performance critical algorithms
where array reallocation penalty is too large to be ignored.
-- ALGLIB --
Copyright 20.08.2010 by Bochkanov Sergey
*************************************************************************/
public static void minlbfgsresultsbuf(minlbfgsstate state, ref double[] x, minlbfgsreport rep)
{
minlbfgs.minlbfgsresultsbuf(state.innerobj, ref x, rep.innerobj);
return;
}
/*************************************************************************
L-BFGS algorithm results
INPUT PARAMETERS:
State - algorithm state
OUTPUT PARAMETERS:
X - array[0..N-1], solution
Rep - optimization report:
* Rep.TerminationType completetion code:
* -2 rounding errors prevent further improvement.
X contains best point found.
* -1 incorrect parameters were specified
* 1 relative function improvement is no more than
EpsF.
* 2 relative step is no more than EpsX.
* 4 gradient norm is no more than EpsG
* 5 MaxIts steps was taken
* 7 stopping conditions are too stringent,
further improvement is impossible
* Rep.IterationsCount contains iterations count
* NFEV countains number of function calculations
-- ALGLIB --
Copyright 02.04.2010 by Bochkanov Sergey
*************************************************************************/
public static void minlbfgsresults(minlbfgsstate state, out double[] x, out minlbfgsreport rep)
{
x = new double[0];
rep = new minlbfgsreport();
minlbfgs.minlbfgsresults(state.innerobj, ref x, rep.innerobj);
return;
}
/*************************************************************************
L-BFGS algorithm results
Called after MinLBFGSIteration() returned False.
INPUT PARAMETERS:
State - algorithm state (used by MinLBFGSIteration).
OUTPUT PARAMETERS:
X - array[0..N-1], solution
Rep - optimization report:
* Rep.TerminationType completetion code:
* -2 rounding errors prevent further improvement.
X contains best point found.
* -1 incorrect parameters were specified
* 1 relative function improvement is no more than
EpsF.
* 2 relative step is no more than EpsX.
* 4 gradient norm is no more than EpsG
* 5 MaxIts steps was taken
* 7 stopping conditions are too stringent,
further improvement is impossible
* Rep.IterationsCount contains iterations count
* NFEV countains number of function calculations
-- ALGLIB --
Copyright 02.04.2010 by Bochkanov Sergey
*************************************************************************/
public static void minlbfgsresults(ref minlbfgsstate state,
ref double[] x,
ref minlbfgsreport rep)
{
int i_ = 0;
x = new double[state.n-1+1];
for(i_=0; i_<=state.n-1;i_++)
{
x[i_] = state.x[i_];
}
rep.iterationscount = state.repiterationscount;
rep.nfev = state.repnfev;
rep.terminationtype = state.repterminationtype;
}
