Split the implementation of i?amax/min into two. Based on PR-627 by Sameer Agarwal.
Like the Netlib reference implementation, I*AMAX now uses the L1-norm instead of the L2-norm for each element. Changed I*MIN accordingly.
diff --git a/blas/level1_cplx_impl.h b/blas/level1_cplx_impl.h
index 4ac4571..6c7edd7 100644
--- a/blas/level1_cplx_impl.h
+++ b/blas/level1_cplx_impl.h
@@ -36,6 +36,28 @@
else return make_vector(x,*n,std::abs(*incx)).unaryExpr<scalar_norm1_op>().sum();
}
+int EIGEN_CAT(i, EIGEN_BLAS_FUNC(amax))(int *n, RealScalar *px, int *incx)
+{
+ if(*n<=0) return 0;
+ Scalar* x = reinterpret_cast<Scalar*>(px);
+
+ DenseIndex ret;
+ if(*incx==1) make_vector(x,*n).unaryExpr<scalar_norm1_op>().maxCoeff(&ret);
+ else make_vector(x,*n,std::abs(*incx)).unaryExpr<scalar_norm1_op>().maxCoeff(&ret);
+ return int(ret)+1;
+}
+
+int EIGEN_CAT(i, EIGEN_BLAS_FUNC(amin))(int *n, RealScalar *px, int *incx)
+{
+ if(*n<=0) return 0;
+ Scalar* x = reinterpret_cast<Scalar*>(px);
+
+ DenseIndex ret;
+ if(*incx==1) make_vector(x,*n).unaryExpr<scalar_norm1_op>().minCoeff(&ret);
+ else make_vector(x,*n,std::abs(*incx)).unaryExpr<scalar_norm1_op>().minCoeff(&ret);
+ return int(ret)+1;
+}
+
// computes a dot product of a conjugated vector with another vector.
int EIGEN_BLAS_FUNC(dotcw)(int *n, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar* pres)
{
diff --git a/blas/level1_impl.h b/blas/level1_impl.h
index d3ee034..71bd534 100644
--- a/blas/level1_impl.h
+++ b/blas/level1_impl.h
@@ -51,28 +51,6 @@
return 0;
}
-int EIGEN_CAT(i, EIGEN_BLAS_FUNC(amax))(int *n, RealScalar *px, int *incx)
-{
- if(*n<=0) return 0;
- Scalar* x = reinterpret_cast<Scalar*>(px);
-
- DenseIndex ret;
- if(*incx==1) make_vector(x,*n).cwiseAbs().maxCoeff(&ret);
- else make_vector(x,*n,std::abs(*incx)).cwiseAbs().maxCoeff(&ret);
- return int(ret)+1;
-}
-
-int EIGEN_CAT(i, EIGEN_BLAS_FUNC(amin))(int *n, RealScalar *px, int *incx)
-{
- if(*n<=0) return 0;
- Scalar* x = reinterpret_cast<Scalar*>(px);
-
- DenseIndex ret;
- if(*incx==1) make_vector(x,*n).cwiseAbs().minCoeff(&ret);
- else make_vector(x,*n,std::abs(*incx)).cwiseAbs().minCoeff(&ret);
- return int(ret)+1;
-}
-
int EIGEN_BLAS_FUNC(rotg)(RealScalar *pa, RealScalar *pb, RealScalar *pc, RealScalar *ps)
{
using std::sqrt;
diff --git a/blas/level1_real_impl.h b/blas/level1_real_impl.h
index 02586d5..c587711 100644
--- a/blas/level1_real_impl.h
+++ b/blas/level1_real_impl.h
@@ -23,6 +23,28 @@
else return make_vector(x,*n,std::abs(*incx)).cwiseAbs().sum();
}
+int EIGEN_CAT(i, EIGEN_BLAS_FUNC(amax))(int *n, RealScalar *px, int *incx)
+{
+ if(*n<=0) return 0;
+ Scalar* x = reinterpret_cast<Scalar*>(px);
+
+ DenseIndex ret;
+ if(*incx==1) make_vector(x,*n).cwiseAbs().maxCoeff(&ret);
+ else make_vector(x,*n,std::abs(*incx)).cwiseAbs().maxCoeff(&ret);
+ return int(ret)+1;
+}
+
+int EIGEN_CAT(i, EIGEN_BLAS_FUNC(amin))(int *n, RealScalar *px, int *incx)
+{
+ if(*n<=0) return 0;
+ Scalar* x = reinterpret_cast<Scalar*>(px);
+
+ DenseIndex ret;
+ if(*incx==1) make_vector(x,*n).cwiseAbs().minCoeff(&ret);
+ else make_vector(x,*n,std::abs(*incx)).cwiseAbs().minCoeff(&ret);
+ return int(ret)+1;
+}
+
// computes a vector-vector dot product.
Scalar EIGEN_BLAS_FUNC(dot)(int *n, RealScalar *px, int *incx, RealScalar *py, int *incy)
{
