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use an enum for status reporting

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This commit is contained in:
Thomas Capricelli
2009-08-25 19:48:53 +02:00
parent d59cc0ad82
commit d38d4709bc
2 changed files with 147 additions and 181 deletions
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118
unsupported/Eigen/src/NonLinear/HybridNonLinearSolver.h
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@@ -6,11 +6,22 @@ public:
HybridNonLinearSolver(const FunctorType &_functor)
: functor(_functor) {}
int solve(
enum Status {
Running = -1,
ImproperInputParameters = 0,
RelativeErrorTooSmall = 1,
TooManyFunctionEvaluation = 2,
TolTooSmall = 3,
NotMakingProgressJacobian = 4,
NotMakingProgressIterations = 5,
UserAksed = 6
};
Status solve(
Matrix< Scalar, Dynamic, 1 > &x,
const Scalar tol = ei_sqrt(epsilon<Scalar>())
);
int solve(
Status solve(
Matrix< Scalar, Dynamic, 1 > &x,
int &nfev, int &njev,
Matrix< Scalar, Dynamic, 1 > &diag,
@@ -20,11 +31,11 @@ public:
const Scalar xtol = ei_sqrt(epsilon<Scalar>())
);
int solveNumericalDiff(
Status solveNumericalDiff(
Matrix< Scalar, Dynamic, 1 > &x,
const Scalar tol = ei_sqrt(epsilon<Scalar>())
);
int solveNumericalDiff(
Status solveNumericalDiff(
Matrix< Scalar, Dynamic, 1 > &x,
int &nfev,
Matrix< Scalar, Dynamic, 1 > &diag,
@@ -48,23 +59,24 @@ private:
template<typename FunctorType, typename Scalar>
int HybridNonLinearSolver<FunctorType,Scalar>::solve(
typename HybridNonLinearSolver<FunctorType,Scalar>::Status
HybridNonLinearSolver<FunctorType,Scalar>::solve(
Matrix< Scalar, Dynamic, 1 > &x,
const Scalar tol
)
{
const int n = x.size();
int info, nfev=0, njev=0;
int nfev=0, njev=0;
Matrix< Scalar, Dynamic, 1> diag;
/* check the input parameters for errors. */
if (n <= 0 || tol < 0.) {
printf("HybridNonLinearSolver::solve() bad args : n,tol,...");
return 0;
return ImproperInputParameters;
}
diag.setConstant(n, 1.);
info = solve(
return solve(
x,
nfev, njev,
diag,
@@ -73,13 +85,13 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
100.,
tol
);
return (info==5)?4:info;
}
template<typename FunctorType, typename Scalar>
int HybridNonLinearSolver<FunctorType,Scalar>::solve(
typename HybridNonLinearSolver<FunctorType,Scalar>::Status
HybridNonLinearSolver<FunctorType,Scalar>::solve(
Matrix< Scalar, Dynamic, 1 > &x,
int &nfev,
int &njev,
@@ -115,10 +127,8 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
int nslow1, nslow2;
int ncfail;
Scalar actred, prered;
int info;
/* Function Body */
info = 0;
iflag = 0;
nfev = 0;
njev = 0;
@@ -126,18 +136,18 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
/* check the input parameters for errors. */
if (n <= 0 || xtol < 0. || maxfev <= 0 || factor <= 0. )
goto algo_end;
return RelativeErrorTooSmall;
if (mode == 2)
for (j = 0; j < n; ++j)
if (diag[j] <= 0.) goto algo_end;
if (diag[j] <= 0.)
return RelativeErrorTooSmall;
/* evaluate the function at the starting point */
/* and calculate its norm. */
iflag = functor.f(x, fvec);
nfev = 1;
if (iflag < 0)
goto algo_end;
if (iflag < 0) return UserAksed;
fnorm = fvec.stableNorm();
/* initialize iteration counter and monitors. */
@@ -158,7 +168,7 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
iflag = functor.df(x, fjac);
++njev;
if (iflag < 0)
break;
return UserAksed;
/* compute the qr factorization of the jacobian. */
@@ -247,8 +257,7 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
iflag = functor.f(wa2, wa4);
++nfev;
if (iflag < 0)
goto algo_end;
if (iflag < 0) return UserAksed;
fnorm1 = wa4.stableNorm();
/* compute the scaled actual reduction. */
@@ -321,28 +330,24 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
/* test for convergence. */
if (delta <= xtol * xnorm || fnorm == 0.)
info = 1;
if (info != 0)
goto algo_end;
return RelativeErrorTooSmall;
/* tests for termination and stringent tolerances. */
if (nfev >= maxfev)
info = 2;
return TooManyFunctionEvaluation;
/* Computing MAX */
if (Scalar(.1) * std::max(Scalar(.1) * delta, pnorm) <= epsilon<Scalar>() * xnorm)
info = 3;
return TolTooSmall;
if (nslow2 == 5)
info = 4;
return NotMakingProgressJacobian;
if (nslow1 == 10)
info = 5;
if (info != 0)
goto algo_end;
return NotMakingProgressIterations;
/* criterion for recalculating jacobian. */
if (ncfail == 2)
break;
break; // leave inner loop and go for the next outer loop iteration
/* calculate the rank one modification to the jacobian */
/* and update qtf if necessary. */
@@ -367,33 +372,30 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
}
/* end of the outer loop. */
}
algo_end:
/* termination, either normal or user imposed. */
if (iflag < 0)
info = iflag;
return info;
assert(false); // should never be reached
}
template<typename FunctorType, typename Scalar>
int HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
typename HybridNonLinearSolver<FunctorType,Scalar>::Status
HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
Matrix< Scalar, Dynamic, 1 > &x,
const Scalar tol
)
{
const int n = x.size();
int info, nfev=0;
int nfev=0;
Matrix< Scalar, Dynamic, 1> diag;
/* check the input parameters for errors. */
if (n <= 0 || tol < 0.) {
printf("HybridNonLinearSolver::solve() bad args : n,tol,...");
return 0;
return ImproperInputParameters;
}
diag.setConstant(n, 1.);
info = solveNumericalDiff(
return solveNumericalDiff(
x,
nfev,
diag,
@@ -403,12 +405,12 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
100.,
tol, Scalar(0.)
);
return (info==5)?4:info;
}
template<typename FunctorType, typename Scalar>
int HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
typename HybridNonLinearSolver<FunctorType,Scalar>::Status
HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
Matrix< Scalar, Dynamic, 1 > &x,
int &nfev,
Matrix< Scalar, Dynamic, 1 > &diag,
@@ -448,21 +450,20 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
int nslow1, nslow2;
int ncfail;
Scalar actred, prered;
int info;
/* Function Body */
info = 0;
iflag = 0;
nfev = 0;
/* check the input parameters for errors. */
if (n <= 0 || xtol < 0. || maxfev <= 0 || nb_of_subdiagonals < 0 || nb_of_superdiagonals < 0 || factor <= 0. )
goto algo_end;
return RelativeErrorTooSmall;
if (mode == 2)
for (j = 0; j < n; ++j)
if (diag[j] <= 0.) goto algo_end;
if (diag[j] <= 0.)
return RelativeErrorTooSmall;
/* evaluate the function at the starting point */
/* and calculate its norm. */
@@ -470,7 +471,7 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
iflag = functor.f(x, fvec);
nfev = 1;
if (iflag < 0)
goto algo_end;
return UserAksed;
fnorm = fvec.stableNorm();
/* determine the number of calls to fcn needed to compute */
@@ -498,7 +499,7 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
nb_of_subdiagonals, nb_of_superdiagonals, epsfcn);
nfev += msum;
if (iflag < 0)
break;
return UserAksed;
/* compute the qr factorization of the jacobian. */
@@ -587,8 +588,7 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
iflag = functor.f(wa2, wa4);
++nfev;
if (iflag < 0)
goto algo_end;
if (iflag < 0) return UserAksed;
fnorm1 = wa4.stableNorm();
/* compute the scaled actual reduction. */
@@ -661,29 +661,25 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
/* test for convergence. */
if (delta <= xtol * xnorm || fnorm == 0.)
info = 1;
if (info != 0)
goto algo_end;
return RelativeErrorTooSmall;
/* tests for termination and stringent tolerances. */
if (nfev >= maxfev)
info = 2;
return TooManyFunctionEvaluation;
/* Computing MAX */
if (Scalar(.1) * std::max(Scalar(.1) * delta, pnorm) <= epsilon<Scalar>() * xnorm)
info = 3;
return TolTooSmall;
if (nslow2 == 5)
info = 4;
return NotMakingProgressJacobian;
if (nslow1 == 10)
info = 5;
if (info != 0)
goto algo_end;
return NotMakingProgressIterations;
/* criterion for recalculating jacobian approximation */
/* by forward differences. */
if (ncfail == 2)
break;
break; // leave inner loop and go for the next outer loop iteration
/* calculate the rank one modification to the jacobian */
/* and update qtf if necessary. */
@@ -708,10 +704,6 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
}
/* end of the outer loop. */
}
algo_end:
/* termination, either normal or user imposed. */
if (iflag < 0)
info = iflag;
return info;
assert(false); // should never be reached
}