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authorGravatar Jitse Niesen <jitse@maths.leeds.ac.uk>2013-02-02 22:04:42 +0000
committerGravatar Jitse Niesen <jitse@maths.leeds.ac.uk>2013-02-02 22:04:42 +0000
commit14e2ab02b58ba07e2be6b003bc178a0ec5e1015b (patch)
treedcddfd386dd5b428beaee6ef14803b4eb00de212
parent35647b01334370d0ddfd5d2d3376d4200947b007 (diff)
Replace assert() by eigen_assert() (fixes bug #548).
-rw-r--r--Eigen/src/Eigenvalues/ComplexEigenSolver.h2
-rw-r--r--Eigen/src/Eigenvalues/ComplexSchur_MKL.h2
-rw-r--r--Eigen/src/Eigenvalues/EigenSolver.h2
-rw-r--r--Eigen/src/Eigenvalues/HessenbergDecomposition.h2
-rw-r--r--Eigen/src/Eigenvalues/RealQZ.h2
-rw-r--r--Eigen/src/Eigenvalues/RealSchur.h6
-rw-r--r--Eigen/src/Eigenvalues/RealSchur_MKL.h2
-rw-r--r--Eigen/src/LU/Determinant.h2
-rw-r--r--unsupported/Eigen/src/IterativeSolvers/DGMRES.h4
-rw-r--r--unsupported/Eigen/src/IterativeSolvers/MINRES.h4
-rw-r--r--unsupported/Eigen/src/IterativeSolvers/Scaling.h4
-rw-r--r--unsupported/Eigen/src/LevenbergMarquardt/LMcovar.h2
-rw-r--r--unsupported/Eigen/src/LevenbergMarquardt/LMonestep.h4
-rw-r--r--unsupported/Eigen/src/LevenbergMarquardt/LMpar.h4
-rw-r--r--unsupported/Eigen/src/LevenbergMarquardt/LevenbergMarquardt.h2
-rw-r--r--unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h18
-rw-r--r--unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h6
-rw-r--r--unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h8
-rw-r--r--unsupported/Eigen/src/NonLinearOptimization/covar.h2
-rw-r--r--unsupported/Eigen/src/NonLinearOptimization/dogleg.h6
-rw-r--r--unsupported/Eigen/src/NonLinearOptimization/fdjac1.h2
-rw-r--r--unsupported/Eigen/src/NonLinearOptimization/lmpar.h10
-rw-r--r--unsupported/Eigen/src/NonLinearOptimization/r1updt.h8
-rw-r--r--unsupported/Eigen/src/NonLinearOptimization/rwupdt.h2
-rw-r--r--unsupported/Eigen/src/NumericalDiff/NumericalDiff.h4
-rw-r--r--unsupported/Eigen/src/Polynomials/PolynomialSolver.h4
-rw-r--r--unsupported/Eigen/src/Polynomials/PolynomialUtils.h2
-rw-r--r--unsupported/Eigen/src/SparseExtra/MarketIO.h6
28 files changed, 61 insertions, 61 deletions
diff --git a/Eigen/src/Eigenvalues/ComplexEigenSolver.h b/Eigen/src/Eigenvalues/ComplexEigenSolver.h
index 95c70aecb..238e08925 100644
--- a/Eigen/src/Eigenvalues/ComplexEigenSolver.h
+++ b/Eigen/src/Eigenvalues/ComplexEigenSolver.h
@@ -252,7 +252,7 @@ ComplexEigenSolver<MatrixType>&
ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
{
// this code is inspired from Jampack
- assert(matrix.cols() == matrix.rows());
+ eigen_assert(matrix.cols() == matrix.rows());
// Do a complex Schur decomposition, A = U T U^*
// The eigenvalues are on the diagonal of T.
diff --git a/Eigen/src/Eigenvalues/ComplexSchur_MKL.h b/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
index ada7a24e3..91496ae5b 100644
--- a/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
+++ b/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
@@ -49,7 +49,7 @@ ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matri
typedef MatrixType::RealScalar RealScalar; \
typedef std::complex<RealScalar> ComplexScalar; \
\
- assert(matrix.cols() == matrix.rows()); \
+ eigen_assert(matrix.cols() == matrix.rows()); \
\
m_matUisUptodate = false; \
if(matrix.cols() == 1) \
diff --git a/Eigen/src/Eigenvalues/EigenSolver.h b/Eigen/src/Eigenvalues/EigenSolver.h
index 43d0ffa76..a80f88eb0 100644
--- a/Eigen/src/Eigenvalues/EigenSolver.h
+++ b/Eigen/src/Eigenvalues/EigenSolver.h
@@ -366,7 +366,7 @@ EigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvect
{
using std::sqrt;
using std::abs;
- assert(matrix.cols() == matrix.rows());
+ eigen_assert(matrix.cols() == matrix.rows());
// Reduce to real Schur form.
m_realSchur.compute(matrix, computeEigenvectors);
diff --git a/Eigen/src/Eigenvalues/HessenbergDecomposition.h b/Eigen/src/Eigenvalues/HessenbergDecomposition.h
index b8378b08a..ebd8ae908 100644
--- a/Eigen/src/Eigenvalues/HessenbergDecomposition.h
+++ b/Eigen/src/Eigenvalues/HessenbergDecomposition.h
@@ -291,7 +291,7 @@ template<typename _MatrixType> class HessenbergDecomposition
template<typename MatrixType>
void HessenbergDecomposition<MatrixType>::_compute(MatrixType& matA, CoeffVectorType& hCoeffs, VectorType& temp)
{
- assert(matA.rows()==matA.cols());
+ eigen_assert(matA.rows()==matA.cols());
Index n = matA.rows();
temp.resize(n);
for (Index i = 0; i<n-1; ++i)
diff --git a/Eigen/src/Eigenvalues/RealQZ.h b/Eigen/src/Eigenvalues/RealQZ.h
index dcaa9fbd6..5706eeebe 100644
--- a/Eigen/src/Eigenvalues/RealQZ.h
+++ b/Eigen/src/Eigenvalues/RealQZ.h
@@ -559,7 +559,7 @@ namespace Eigen {
const Index dim = A_in.cols();
- assert (A_in.rows()==dim && A_in.cols()==dim
+ eigen_assert (A_in.rows()==dim && A_in.cols()==dim
&& B_in.rows()==dim && B_in.cols()==dim
&& "Need square matrices of the same dimension");
diff --git a/Eigen/src/Eigenvalues/RealSchur.h b/Eigen/src/Eigenvalues/RealSchur.h
index 7680f9929..a770b3187 100644
--- a/Eigen/src/Eigenvalues/RealSchur.h
+++ b/Eigen/src/Eigenvalues/RealSchur.h
@@ -245,7 +245,7 @@ template<typename _MatrixType> class RealSchur
template<typename MatrixType>
RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix, bool computeU)
{
- assert(matrix.cols() == matrix.rows());
+ eigen_assert(matrix.cols() == matrix.rows());
Index maxIters = m_maxIters;
if (maxIters == -1)
maxIters = m_maxIterationsPerRow * matrix.rows();
@@ -467,8 +467,8 @@ inline void RealSchur<MatrixType>::initFrancisQRStep(Index il, Index iu, const V
template<typename MatrixType>
inline void RealSchur<MatrixType>::performFrancisQRStep(Index il, Index im, Index iu, bool computeU, const Vector3s& firstHouseholderVector, Scalar* workspace)
{
- assert(im >= il);
- assert(im <= iu-2);
+ eigen_assert(im >= il);
+ eigen_assert(im <= iu-2);
const Index size = m_matT.cols();
diff --git a/Eigen/src/Eigenvalues/RealSchur_MKL.h b/Eigen/src/Eigenvalues/RealSchur_MKL.h
index 960ec3c76..ad9736460 100644
--- a/Eigen/src/Eigenvalues/RealSchur_MKL.h
+++ b/Eigen/src/Eigenvalues/RealSchur_MKL.h
@@ -48,7 +48,7 @@ RealSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<E
typedef MatrixType::Scalar Scalar; \
typedef MatrixType::RealScalar RealScalar; \
\
- assert(matrix.cols() == matrix.rows()); \
+ eigen_assert(matrix.cols() == matrix.rows()); \
\
lapack_int n = matrix.cols(), sdim, info; \
lapack_int lda = matrix.outerStride(); \
diff --git a/Eigen/src/LU/Determinant.h b/Eigen/src/LU/Determinant.h
index d862c5d77..bb8e78a8a 100644
--- a/Eigen/src/LU/Determinant.h
+++ b/Eigen/src/LU/Determinant.h
@@ -91,7 +91,7 @@ template<typename Derived> struct determinant_impl<Derived, 4>
template<typename Derived>
inline typename internal::traits<Derived>::Scalar MatrixBase<Derived>::determinant() const
{
- assert(rows() == cols());
+ eigen_assert(rows() == cols());
typedef typename internal::nested<Derived,Base::RowsAtCompileTime>::type Nested;
return internal::determinant_impl<typename internal::remove_all<Nested>::type>::run(derived());
}
diff --git a/unsupported/Eigen/src/IterativeSolvers/DGMRES.h b/unsupported/Eigen/src/IterativeSolvers/DGMRES.h
index 952aba15e..2ea0eccf1 100644
--- a/unsupported/Eigen/src/IterativeSolvers/DGMRES.h
+++ b/unsupported/Eigen/src/IterativeSolvers/DGMRES.h
@@ -38,7 +38,7 @@ struct traits<DGMRES<_MatrixType,_Preconditioner> >
template <typename VectorType, typename IndexType>
void sortWithPermutation (VectorType& vec, IndexType& perm, typename IndexType::Scalar& ncut)
{
- assert(vec.size() == perm.size());
+ eigen_assert(vec.size() == perm.size());
typedef typename IndexType::Scalar Index;
typedef typename VectorType::Scalar Scalar;
Index n = vec.size();
@@ -525,4 +525,4 @@ struct solve_retval<DGMRES<_MatrixType, _Preconditioner>, Rhs>
} // end namespace internal
} // end namespace Eigen
-#endif \ No newline at end of file
+#endif
diff --git a/unsupported/Eigen/src/IterativeSolvers/MINRES.h b/unsupported/Eigen/src/IterativeSolvers/MINRES.h
index 6bc1b8f5d..0e56342a8 100644
--- a/unsupported/Eigen/src/IterativeSolvers/MINRES.h
+++ b/unsupported/Eigen/src/IterativeSolvers/MINRES.h
@@ -52,7 +52,7 @@ namespace Eigen {
VectorType w_new(precond.solve(v_new)); // initialize w_new
// RealScalar beta; // will be initialized inside loop
RealScalar beta_new2(v_new.dot(w_new));
- assert(beta_new2 >= 0 && "PRECONDITIONER IS NOT POSITIVE DEFINITE");
+ eigen_assert(beta_new2 >= 0 && "PRECONDITIONER IS NOT POSITIVE DEFINITE");
RealScalar beta_new(sqrt(beta_new2));
const RealScalar beta_one(beta_new);
v_new /= beta_new;
@@ -91,7 +91,7 @@ namespace Eigen {
v_new -= alpha*v; // overwrite v_new
w_new = precond.solve(v_new); // overwrite w_new
beta_new2 = v_new.dot(w_new); // compute beta_new
- assert(beta_new2 >= 0 && "PRECONDITIONER IS NOT POSITIVE DEFINITE");
+ eigen_assert(beta_new2 >= 0 && "PRECONDITIONER IS NOT POSITIVE DEFINITE");
beta_new = sqrt(beta_new2); // compute beta_new
v_new /= beta_new; // overwrite v_new for next iteration
w_new /= beta_new; // overwrite w_new for next iteration
diff --git a/unsupported/Eigen/src/IterativeSolvers/Scaling.h b/unsupported/Eigen/src/IterativeSolvers/Scaling.h
index ed4ee48c8..4fd439202 100644
--- a/unsupported/Eigen/src/IterativeSolvers/Scaling.h
+++ b/unsupported/Eigen/src/IterativeSolvers/Scaling.h
@@ -73,7 +73,7 @@ class IterScaling
{
int m = mat.rows();
int n = mat.cols();
- assert((m>0 && m == n) && "Please give a non - empty matrix");
+ eigen_assert((m>0 && m == n) && "Please give a non - empty matrix");
m_left.resize(m);
m_right.resize(n);
m_left.setOnes();
@@ -182,4 +182,4 @@ class IterScaling
int m_maxits; // Maximum number of iterations allowed
};
}
-#endif \ No newline at end of file
+#endif
diff --git a/unsupported/Eigen/src/LevenbergMarquardt/LMcovar.h b/unsupported/Eigen/src/LevenbergMarquardt/LMcovar.h
index 3210587e4..32d3ad518 100644
--- a/unsupported/Eigen/src/LevenbergMarquardt/LMcovar.h
+++ b/unsupported/Eigen/src/LevenbergMarquardt/LMcovar.h
@@ -33,7 +33,7 @@ void covar(
const Index n = r.cols();
const Scalar tolr = tol * abs(r(0,0));
Matrix< Scalar, Dynamic, 1 > wa(n);
- assert(ipvt.size()==n);
+ eigen_assert(ipvt.size()==n);
/* form the inverse of r in the full upper triangle of r. */
l = -1;
diff --git a/unsupported/Eigen/src/LevenbergMarquardt/LMonestep.h b/unsupported/Eigen/src/LevenbergMarquardt/LMonestep.h
index aa0c02668..51ade866c 100644
--- a/unsupported/Eigen/src/LevenbergMarquardt/LMonestep.h
+++ b/unsupported/Eigen/src/LevenbergMarquardt/LMonestep.h
@@ -26,7 +26,7 @@ LevenbergMarquardt<FunctorType>::minimizeOneStep(FVectorType &x)
RealScalar temp, temp1,temp2;
RealScalar ratio;
RealScalar pnorm, xnorm, fnorm1, actred, dirder, prered;
- assert(x.size()==n); // check the caller is not cheating us
+ eigen_assert(x.size()==n); // check the caller is not cheating us
temp = 0.0; xnorm = 0.0;
/* calculate the jacobian matrix. */
@@ -176,4 +176,4 @@ LevenbergMarquardt<FunctorType>::minimizeOneStep(FVectorType &x)
} // end namespace Eigen
-#endif // EIGEN_LMONESTEP_H \ No newline at end of file
+#endif // EIGEN_LMONESTEP_H
diff --git a/unsupported/Eigen/src/LevenbergMarquardt/LMpar.h b/unsupported/Eigen/src/LevenbergMarquardt/LMpar.h
index dc60ca05a..af76a9799 100644
--- a/unsupported/Eigen/src/LevenbergMarquardt/LMpar.h
+++ b/unsupported/Eigen/src/LevenbergMarquardt/LMpar.h
@@ -45,8 +45,8 @@ namespace internal {
/* Function Body */
const Scalar dwarf = (std::numeric_limits<Scalar>::min)();
const Index n = qr.matrixQR().cols();
- assert(n==diag.size());
- assert(n==qtb.size());
+ eigen_assert(n==diag.size());
+ eigen_assert(n==qtb.size());
VectorType wa1, wa2;
diff --git a/unsupported/Eigen/src/LevenbergMarquardt/LevenbergMarquardt.h b/unsupported/Eigen/src/LevenbergMarquardt/LevenbergMarquardt.h
index e45e73ab5..bf2423ef0 100644
--- a/unsupported/Eigen/src/LevenbergMarquardt/LevenbergMarquardt.h
+++ b/unsupported/Eigen/src/LevenbergMarquardt/LevenbergMarquardt.h
@@ -257,7 +257,7 @@ LevenbergMarquardt<FunctorType>::minimizeInit(FVectorType &x)
// m_fjac.reserve(VectorXi::Constant(n,5)); // FIXME Find a better alternative
if (!m_useExternalScaling)
m_diag.resize(n);
- assert( (!m_useExternalScaling || m_diag.size()==n) || "When m_useExternalScaling is set, the caller must provide a valid 'm_diag'");
+ eigen_assert( (!m_useExternalScaling || m_diag.size()==n) || "When m_useExternalScaling is set, the caller must provide a valid 'm_diag'");
m_qtf.resize(n);
/* Function Body */
diff --git a/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h b/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h
index 166393f00..b00e5e921 100644
--- a/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h
+++ b/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h
@@ -237,7 +237,7 @@ void MatrixLogarithmAtomic<MatrixType>::computePade3(MatrixType& result, const M
0.8872983346207416885179265399782400L };
const RealScalar weights[] = { 0.2777777777777777777777777777777778L, 0.4444444444444444444444444444444444L,
0.2777777777777777777777777777777778L };
- assert(degree <= maxPadeDegree);
+ eigen_assert(degree <= maxPadeDegree);
MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
result.setZero(T.rows(), T.rows());
for (int k = 0; k < degree; ++k)
@@ -253,7 +253,7 @@ void MatrixLogarithmAtomic<MatrixType>::computePade4(MatrixType& result, const M
0.6699905217924281324013328795516223L, 0.9305681557970262876119732444464048L };
const RealScalar weights[] = { 0.1739274225687269286865319746109997L, 0.3260725774312730713134680253890003L,
0.3260725774312730713134680253890003L, 0.1739274225687269286865319746109997L };
- assert(degree <= maxPadeDegree);
+ eigen_assert(degree <= maxPadeDegree);
MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
result.setZero(T.rows(), T.rows());
for (int k = 0; k < degree; ++k)
@@ -271,7 +271,7 @@ void MatrixLogarithmAtomic<MatrixType>::computePade5(MatrixType& result, const M
const RealScalar weights[] = { 0.1184634425280945437571320203599587L, 0.2393143352496832340206457574178191L,
0.2844444444444444444444444444444444L, 0.2393143352496832340206457574178191L,
0.1184634425280945437571320203599587L };
- assert(degree <= maxPadeDegree);
+ eigen_assert(degree <= maxPadeDegree);
MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
result.setZero(T.rows(), T.rows());
for (int k = 0; k < degree; ++k)
@@ -289,7 +289,7 @@ void MatrixLogarithmAtomic<MatrixType>::computePade6(MatrixType& result, const M
const RealScalar weights[] = { 0.0856622461895851725201480710863665L, 0.1803807865240693037849167569188581L,
0.2339569672863455236949351719947755L, 0.2339569672863455236949351719947755L,
0.1803807865240693037849167569188581L, 0.0856622461895851725201480710863665L };
- assert(degree <= maxPadeDegree);
+ eigen_assert(degree <= maxPadeDegree);
MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
result.setZero(T.rows(), T.rows());
for (int k = 0; k < degree; ++k)
@@ -309,7 +309,7 @@ void MatrixLogarithmAtomic<MatrixType>::computePade7(MatrixType& result, const M
0.1909150252525594724751848877444876L, 0.2089795918367346938775510204081633L,
0.1909150252525594724751848877444876L, 0.1398526957446383339507338857118898L,
0.0647424830844348466353057163395410L };
- assert(degree <= maxPadeDegree);
+ eigen_assert(degree <= maxPadeDegree);
MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
result.setZero(T.rows(), T.rows());
for (int k = 0; k < degree; ++k)
@@ -329,7 +329,7 @@ void MatrixLogarithmAtomic<MatrixType>::computePade8(MatrixType& result, const M
0.1568533229389436436689811009933007L, 0.1813418916891809914825752246385978L,
0.1813418916891809914825752246385978L, 0.1568533229389436436689811009933007L,
0.1111905172266872352721779972131204L, 0.0506142681451881295762656771549811L };
- assert(degree <= maxPadeDegree);
+ eigen_assert(degree <= maxPadeDegree);
MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
result.setZero(T.rows(), T.rows());
for (int k = 0; k < degree; ++k)
@@ -351,7 +351,7 @@ void MatrixLogarithmAtomic<MatrixType>::computePade9(MatrixType& result, const M
0.1651196775006298815822625346434870L, 0.1561735385200014200343152032922218L,
0.1303053482014677311593714347093164L, 0.0903240803474287020292360156214564L,
0.0406371941807872059859460790552618L };
- assert(degree <= maxPadeDegree);
+ eigen_assert(degree <= maxPadeDegree);
MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
result.setZero(T.rows(), T.rows());
for (int k = 0; k < degree; ++k)
@@ -373,7 +373,7 @@ void MatrixLogarithmAtomic<MatrixType>::computePade10(MatrixType& result, const
0.1477621123573764350869464973256692L, 0.1477621123573764350869464973256692L,
0.1346333596549981775456134607847347L, 0.1095431812579910219977674671140816L,
0.0747256745752902965728881698288487L, 0.0333356721543440687967844049466659L };
- assert(degree <= maxPadeDegree);
+ eigen_assert(degree <= maxPadeDegree);
MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
result.setZero(T.rows(), T.rows());
for (int k = 0; k < degree; ++k)
@@ -397,7 +397,7 @@ void MatrixLogarithmAtomic<MatrixType>::computePade11(MatrixType& result, const
0.1314022722551233310903444349452546L, 0.1165968822959952399592618524215876L,
0.0931451054638671257130488207158280L, 0.0627901847324523123173471496119701L,
0.0278342835580868332413768602212743L };
- assert(degree <= maxPadeDegree);
+ eigen_assert(degree <= maxPadeDegree);
MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
result.setZero(T.rows(), T.rows());
for (int k = 0; k < degree; ++k)
diff --git a/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h b/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
index b190827b3..5b24b4619 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
@@ -150,7 +150,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveInit(FVectorType &x)
fjac.resize(n, n);
if (!useExternalScaling)
diag.resize(n);
- assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
+ eigen_assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
/* Function Body */
nfev = 0;
@@ -187,7 +187,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(FVectorType &x)
{
using std::abs;
- assert(x.size()==n); // check the caller is not cheating us
+ eigen_assert(x.size()==n); // check the caller is not cheating us
Index j;
std::vector<JacobiRotation<Scalar> > v_givens(n), w_givens(n);
@@ -390,7 +390,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffInit(FVectorType &
fvec.resize(n);
if (!useExternalScaling)
diag.resize(n);
- assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
+ eigen_assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
/* Function Body */
nfev = 0;
diff --git a/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h b/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
index 4b1a2d0fb..3d0a9c8fc 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
@@ -172,7 +172,7 @@ LevenbergMarquardt<FunctorType,Scalar>::minimizeInit(FVectorType &x)
fjac.resize(m, n);
if (!useExternalScaling)
diag.resize(n);
- assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
+ eigen_assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
qtf.resize(n);
/* Function Body */
@@ -209,7 +209,7 @@ LevenbergMarquardt<FunctorType,Scalar>::minimizeOneStep(FVectorType &x)
using std::abs;
using std::sqrt;
- assert(x.size()==n); // check the caller is not cheating us
+ eigen_assert(x.size()==n); // check the caller is not cheating us
/* calculate the jacobian matrix. */
Index df_ret = functor.df(x, fjac);
@@ -391,7 +391,7 @@ LevenbergMarquardt<FunctorType,Scalar>::minimizeOptimumStorageInit(FVectorType
fjac.resize(n, n);
if (!useExternalScaling)
diag.resize(n);
- assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
+ eigen_assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
qtf.resize(n);
/* Function Body */
@@ -429,7 +429,7 @@ LevenbergMarquardt<FunctorType,Scalar>::minimizeOptimumStorageOneStep(FVectorTyp
using std::abs;
using std::sqrt;
- assert(x.size()==n); // check the caller is not cheating us
+ eigen_assert(x.size()==n); // check the caller is not cheating us
Index i, j;
bool sing;
diff --git a/unsupported/Eigen/src/NonLinearOptimization/covar.h b/unsupported/Eigen/src/NonLinearOptimization/covar.h
index c2fb79441..68260d191 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/covar.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/covar.h
@@ -20,7 +20,7 @@ void covar(
const Index n = r.cols();
const Scalar tolr = tol * abs(r(0,0));
Matrix< Scalar, Dynamic, 1 > wa(n);
- assert(ipvt.size()==n);
+ eigen_assert(ipvt.size()==n);
/* form the inverse of r in the full upper triangle of r. */
l = -1;
diff --git a/unsupported/Eigen/src/NonLinearOptimization/dogleg.h b/unsupported/Eigen/src/NonLinearOptimization/dogleg.h
index 57dbc8bfb..4210958e7 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/dogleg.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/dogleg.h
@@ -24,9 +24,9 @@ void dogleg(
/* Function Body */
const Scalar epsmch = NumTraits<Scalar>::epsilon();
const Index n = qrfac.cols();
- assert(n==qtb.size());
- assert(n==x.size());
- assert(n==diag.size());
+ eigen_assert(n==qtb.size());
+ eigen_assert(n==x.size());
+ eigen_assert(n==diag.size());
Matrix< Scalar, Dynamic, 1 > wa1(n), wa2(n);
/* first, calculate the gauss-newton direction. */
diff --git a/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h b/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h
index 05947936e..bb7cf267b 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h
@@ -27,7 +27,7 @@ DenseIndex fdjac1(
/* Function Body */
const Scalar epsmch = NumTraits<Scalar>::epsilon();
const Index n = x.size();
- assert(fvec.size()==n);
+ eigen_assert(fvec.size()==n);
Matrix< Scalar, Dynamic, 1 > wa1(n);
Matrix< Scalar, Dynamic, 1 > wa2(n);
diff --git a/unsupported/Eigen/src/NonLinearOptimization/lmpar.h b/unsupported/Eigen/src/NonLinearOptimization/lmpar.h
index 834407c5a..4c17d4cdf 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/lmpar.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/lmpar.h
@@ -29,9 +29,9 @@ void lmpar(
/* Function Body */
const Scalar dwarf = (std::numeric_limits<Scalar>::min)();
const Index n = r.cols();
- assert(n==diag.size());
- assert(n==qtb.size());
- assert(n==x.size());
+ eigen_assert(n==diag.size());
+ eigen_assert(n==qtb.size());
+ eigen_assert(n==x.size());
Matrix< Scalar, Dynamic, 1 > wa1, wa2;
@@ -187,8 +187,8 @@ void lmpar2(
/* Function Body */
const Scalar dwarf = (std::numeric_limits<Scalar>::min)();
const Index n = qr.matrixQR().cols();
- assert(n==diag.size());
- assert(n==qtb.size());
+ eigen_assert(n==diag.size());
+ eigen_assert(n==qtb.size());
Matrix< Scalar, Dynamic, 1 > wa1, wa2;
diff --git a/unsupported/Eigen/src/NonLinearOptimization/r1updt.h b/unsupported/Eigen/src/NonLinearOptimization/r1updt.h
index 55fae5ae8..f28766061 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/r1updt.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/r1updt.h
@@ -24,10 +24,10 @@ void r1updt(
// r1updt had a broader usecase, but we dont use it here. And, more
// importantly, we can not test it.
- assert(m==n);
- assert(u.size()==m);
- assert(v.size()==n);
- assert(w.size()==n);
+ eigen_assert(m==n);
+ eigen_assert(u.size()==m);
+ eigen_assert(v.size()==n);
+ eigen_assert(w.size()==n);
/* move the nontrivial part of the last column of s into w. */
w[n-1] = s(n-1,n-1);
diff --git a/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h b/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h
index 9ce079e22..6ebf8563f 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h
@@ -12,7 +12,7 @@ void rwupdt(
typedef DenseIndex Index;
const Index n = r.cols();
- assert(r.rows()>=n);
+ eigen_assert(r.rows()>=n);
std::vector<JacobiRotation<Scalar> > givens(n);
/* Local variables */
diff --git a/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h b/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h
index 7ee30e18c..ea5d8bc27 100644
--- a/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h
+++ b/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h
@@ -86,7 +86,7 @@ public:
// do nothing
break;
default:
- assert(false);
+ eigen_assert(false);
};
// Function Body
@@ -112,7 +112,7 @@ public:
jac.col(j) = (val2-val1)/(2*h);
break;
default:
- assert(false);
+ eigen_assert(false);
};
}
return nfev;
diff --git a/unsupported/Eigen/src/Polynomials/PolynomialSolver.h b/unsupported/Eigen/src/Polynomials/PolynomialSolver.h
index fba8fc910..ad486f08e 100644
--- a/unsupported/Eigen/src/Polynomials/PolynomialSolver.h
+++ b/unsupported/Eigen/src/Polynomials/PolynomialSolver.h
@@ -344,7 +344,7 @@ class PolynomialSolver : public PolynomialSolverBase<_Scalar,_Deg>
template< typename OtherPolynomial >
void compute( const OtherPolynomial& poly )
{
- assert( Scalar(0) != poly[poly.size()-1] );
+ eigen_assert( Scalar(0) != poly[poly.size()-1] );
internal::companion<Scalar,_Deg> companion( poly );
companion.balance();
m_eigenSolver.compute( companion.denseMatrix() );
@@ -376,7 +376,7 @@ class PolynomialSolver<_Scalar,1> : public PolynomialSolverBase<_Scalar,1>
template< typename OtherPolynomial >
void compute( const OtherPolynomial& poly )
{
- assert( Scalar(0) != poly[poly.size()-1] );
+ eigen_assert( Scalar(0) != poly[poly.size()-1] );
m_roots[0] = -poly[0]/poly[poly.size()-1];
}
diff --git a/unsupported/Eigen/src/Polynomials/PolynomialUtils.h b/unsupported/Eigen/src/Polynomials/PolynomialUtils.h
index 5a9ab110e..27d4e9f91 100644
--- a/unsupported/Eigen/src/Polynomials/PolynomialUtils.h
+++ b/unsupported/Eigen/src/Polynomials/PolynomialUtils.h
@@ -78,7 +78,7 @@ typename NumTraits<typename Polynomial::Scalar>::Real cauchy_max_bound( const Po
typedef typename Polynomial::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real Real;
- assert( Scalar(0) != poly[poly.size()-1] );
+ eigen_assert( Scalar(0) != poly[poly.size()-1] );
const Scalar inv_leading_coeff = Scalar(1)/poly[poly.size()-1];
Real cb(0);
diff --git a/unsupported/Eigen/src/SparseExtra/MarketIO.h b/unsupported/Eigen/src/SparseExtra/MarketIO.h
index de958de9f..7aafce928 100644
--- a/unsupported/Eigen/src/SparseExtra/MarketIO.h
+++ b/unsupported/Eigen/src/SparseExtra/MarketIO.h
@@ -116,7 +116,7 @@ inline bool getMarketHeader(const std::string& filename, int& sym, bool& iscompl
std::string line;
// The matrix header is always the first line in the file
- std::getline(in, line); assert(in.good());
+ std::getline(in, line); eigen_assert(in.good());
std::stringstream fmtline(line);
std::string substr[5];
@@ -200,11 +200,11 @@ bool loadMarketVector(VectorType& vec, const std::string& filename)
int n(0), col(0);
do
{ // Skip comments
- std::getline(in, line); assert(in.good());
+ std::getline(in, line); eigen_assert(in.good());
} while (line[0] == '%');
std::istringstream newline(line);
newline >> n >> col;
- assert(n>0 && col>0);
+ eigen_assert(n>0 && col>0);
vec.resize(n);
int i = 0;
Scalar value;