2 files changed, 98 insertions, 141 deletions

diff --git a/packages/base/src/Internal/C/lapack-aux.c b/packages/base/src/Internal/C/lapack-aux.c
index 1018126..ca60846 100644
--- a/packages/base/src/Internal/C/lapack-aux.c
+++ b/packages/base/src/Internal/C/lapack-aux.c
@@ -314,22 +314,19 @@ int svd_l_Cdd(OCMAT(a),OCMAT(u), DVEC(s),OCMAT(v)) {
     }
     double *rwk = (double*)malloc(lrwk*sizeof(double));;
     CHECK(!rwk,MEM);
-    //printf("%s %ld %d\n",jobz,q,lrwk);
     integer lwk = -1;
     integer res;
     // ask for optimal lwk
     doublecomplex ans;
     zgesdd_ (jobz,&m,&n,ap,&m,sp,up,&m,vp,&ldvt,&ans,&lwk,rwk,iwk,&res);
     lwk = ans.r;
-    //printf("lwk = %ld\n",lwk);
     doublecomplex * workv = (doublecomplex*)malloc(lwk*sizeof(doublecomplex));
     CHECK(!workv,MEM);
     zgesdd_ (jobz,&m,&n,ap,&m,sp,up,&m,vp,&ldvt,workv,&lwk,rwk,iwk,&res);
-    //printf("res = %ld\n",res);
     CHECK(res,res);
-    free(workv); // printf("freed workv\n");
-    free(rwk);   // printf("freed rwk\n");
-    free(iwk);   // printf("freed iwk\n");
+    free(workv);
+    free(rwk);
+    free(iwk);
     OK
 }
 
@@ -498,80 +495,72 @@ int eig_l_H(int wantV,DVEC(s),OCMAT(v)) {
 
 //////////////////// general real linear system ////////////
 
-/* Subroutine */ int dgesv_(integer *n, integer *nrhs, doublereal *a, integer
+int dgesv_(integer *n, integer *nrhs, doublereal *a, integer
         *lda, integer *ipiv, doublereal *b, integer *ldb, integer *info);
 
-int linearSolveR_l(KODMAT(a),KODMAT(b),ODMAT(x)) {
+int linearSolveR_l(ODMAT(a),ODMAT(b)) {
     integer n = ar;
     integer nhrs = bc;
     REQUIRES(n>=1 && ar==ac && ar==br,BAD_SIZE);
     DEBUGMSG("linearSolveR_l");
-    double*AC = (double*)malloc(n*n*sizeof(double));
-    memcpy(AC,ap,n*n*sizeof(double));
-    memcpy(xp,bp,n*nhrs*sizeof(double));
     integer * ipiv = (integer*)malloc(n*sizeof(integer));
     integer res;
     dgesv_  (&n,&nhrs,
-             AC, &n,
+             ap, &n,
              ipiv,
-             xp, &n,
+             bp, &n,
              &res);
     if(res>0) {
         return SINGULAR;
     }
     CHECK(res,res);
     free(ipiv);
-    free(AC);
     OK
 }
 
 //////////////////// general complex linear system ////////////
 
-/* Subroutine */ int zgesv_(integer *n, integer *nrhs, doublecomplex *a,
+int zgesv_(integer *n, integer *nrhs, doublecomplex *a,
         integer *lda, integer *ipiv, doublecomplex *b, integer *ldb, integer *
         info);
 
-int linearSolveC_l(KOCMAT(a),KOCMAT(b),OCMAT(x)) {
+int linearSolveC_l(OCMAT(a),OCMAT(b)) {
     integer n = ar;
     integer nhrs = bc;
     REQUIRES(n>=1 && ar==ac && ar==br,BAD_SIZE);
     DEBUGMSG("linearSolveC_l");
-    doublecomplex*AC = (doublecomplex*)malloc(n*n*sizeof(doublecomplex));
-    memcpy(AC,ap,n*n*sizeof(doublecomplex));
-    memcpy(xp,bp,n*nhrs*sizeof(doublecomplex));
     integer * ipiv = (integer*)malloc(n*sizeof(integer));
     integer res;
     zgesv_  (&n,&nhrs,
-             AC, &n,
+             ap, &n,
              ipiv,
-             xp, &n,
+             bp, &n,
              &res);
     if(res>0) {
         return SINGULAR;
     }
     CHECK(res,res);
     free(ipiv);
-    free(AC);
     OK
 }
 
 //////// symmetric positive definite real linear system using Cholesky ////////////
 
-/* Subroutine */ int dpotrs_(char *uplo, integer *n, integer *nrhs,
+int dpotrs_(char *uplo, integer *n, integer *nrhs,
         doublereal *a, integer *lda, doublereal *b, integer *ldb, integer *
         info);
 
-int cholSolveR_l(KODMAT(a),KODMAT(b),ODMAT(x)) {
+int cholSolveR_l(KODMAT(a),ODMAT(b)) {
     integer n = ar;
+    integer lda = aXc;
     integer nhrs = bc;
     REQUIRES(n>=1 && ar==ac && ar==br,BAD_SIZE);
     DEBUGMSG("cholSolveR_l");
-    memcpy(xp,bp,n*nhrs*sizeof(double));
     integer res;
     dpotrs_ ("U",
              &n,&nhrs,
-             (double*)ap, &n,
-             xp, &n,
+             (double*)ap, &lda,
+             bp, &n,
              &res);
     CHECK(res,res);
     OK
@@ -579,21 +568,21 @@ int cholSolveR_l(KODMAT(a),KODMAT(b),ODMAT(x)) {
 
 //////// Hermitian positive definite real linear system using Cholesky ////////////
 
-/* Subroutine */ int zpotrs_(char *uplo, integer *n, integer *nrhs,
+int zpotrs_(char *uplo, integer *n, integer *nrhs,
         doublecomplex *a, integer *lda, doublecomplex *b, integer *ldb,
         integer *info);
 
-int cholSolveC_l(KOCMAT(a),KOCMAT(b),OCMAT(x)) {
+int cholSolveC_l(KOCMAT(a),OCMAT(b)) {
     integer n = ar;
+    integer lda = aXc;
     integer nhrs = bc;
     REQUIRES(n>=1 && ar==ac && ar==br,BAD_SIZE);
     DEBUGMSG("cholSolveC_l");
-    memcpy(xp,bp,n*nhrs*sizeof(doublecomplex));
     integer res;
     zpotrs_  ("U",
              &n,&nhrs,
-             (doublecomplex*)ap, &n,
-             xp, &n,
+             (doublecomplex*)ap, &lda,
+             bp, &n,
              &res);
     CHECK(res,res);
     OK
@@ -601,41 +590,30 @@ int cholSolveC_l(KOCMAT(a),KOCMAT(b),OCMAT(x)) {
 
 //////////////////// least squares real linear system ////////////
 
-/* Subroutine */ int dgels_(char *trans, integer *m, integer *n, integer *
+int dgels_(char *trans, integer *m, integer *n, integer *
         nrhs, doublereal *a, integer *lda, doublereal *b, integer *ldb,
         doublereal *work, integer *lwork, integer *info);
 
-int linearSolveLSR_l(KODMAT(a),KODMAT(b),ODMAT(x)) {
+int linearSolveLSR_l(ODMAT(a),ODMAT(b)) {
     integer m = ar;
     integer n = ac;
     integer nrhs = bc;
-    integer ldb = xr;
-    REQUIRES(m>=1 && n>=1 && ar==br && xr==MAX(m,n) && xc == bc, BAD_SIZE);
+    integer ldb = bXc;
+    REQUIRES(m>=1 && n>=1 && br==MAX(m,n), BAD_SIZE);
     DEBUGMSG("linearSolveLSR_l");
-    double*AC = (double*)malloc(m*n*sizeof(double));
-    memcpy(AC,ap,m*n*sizeof(double));
-    if (m>=n) {
-        memcpy(xp,bp,m*nrhs*sizeof(double));
-    } else {
-        int k;
-        for(k = 0; k<nrhs; k++) {
-            memcpy(xp+ldb*k,bp+m*k,m*sizeof(double));
-        }
-    }
     integer res;
     integer lwork = -1;
     double ans;
     dgels_  ("N",&m,&n,&nrhs,
-             AC,&m,
-             xp,&ldb,
+             ap,&m,
+             bp,&ldb,
              &ans,&lwork,
              &res);
     lwork = ceil(ans);
-    //printf("ans = %d\n",lwork);
     double * work = (double*)malloc(lwork*sizeof(double));
     dgels_  ("N",&m,&n,&nrhs,
-             AC,&m,
-             xp,&ldb,
+             ap,&m,
+             bp,&ldb,
              work,&lwork,
              &res);
     if(res>0) {
@@ -643,47 +621,35 @@ int linearSolveLSR_l(KODMAT(a),KODMAT(b),ODMAT(x)) {
     }
     CHECK(res,res);
     free(work);
-    free(AC);
     OK
 }
 
 //////////////////// least squares complex linear system ////////////
 
-/* Subroutine */ int zgels_(char *trans, integer *m, integer *n, integer *
+int zgels_(char *trans, integer *m, integer *n, integer *
         nrhs, doublecomplex *a, integer *lda, doublecomplex *b, integer *ldb,
         doublecomplex *work, integer *lwork, integer *info);
 
-int linearSolveLSC_l(KOCMAT(a),KOCMAT(b),OCMAT(x)) {
+int linearSolveLSC_l(OCMAT(a),OCMAT(b)) {
     integer m = ar;
     integer n = ac;
     integer nrhs = bc;
-    integer ldb = xr;
-    REQUIRES(m>=1 && n>=1 && ar==br && xr==MAX(m,n) && xc == bc, BAD_SIZE);
+    integer ldb = bXc;
+    REQUIRES(m>=1 && n>=1 && br==MAX(m,n), BAD_SIZE);
     DEBUGMSG("linearSolveLSC_l");
-    doublecomplex*AC = (doublecomplex*)malloc(m*n*sizeof(doublecomplex));
-    memcpy(AC,ap,m*n*sizeof(doublecomplex));
-    if (m>=n) {
-        memcpy(xp,bp,m*nrhs*sizeof(doublecomplex));
-    } else {
-        int k;
-        for(k = 0; k<nrhs; k++) {
-            memcpy(xp+ldb*k,bp+m*k,m*sizeof(doublecomplex));
-        }
-    }
     integer res;
     integer lwork = -1;
     doublecomplex ans;
     zgels_  ("N",&m,&n,&nrhs,
-             AC,&m,
-             xp,&ldb,
+             ap,&m,
+             bp,&ldb,
              &ans,&lwork,
              &res);
     lwork = ceil(ans.r);
-    //printf("ans = %d\n",lwork);
     doublecomplex * work = (doublecomplex*)malloc(lwork*sizeof(doublecomplex));
     zgels_  ("N",&m,&n,&nrhs,
-             AC,&m,
-             xp,&ldb,
+             ap,&m,
+             bp,&ldb,
              work,&lwork,
              &res);
     if(res>0) {
@@ -691,52 +657,40 @@ int linearSolveLSC_l(KOCMAT(a),KOCMAT(b),OCMAT(x)) {
     }
     CHECK(res,res);
     free(work);
-    free(AC);
     OK
 }
 
 //////////////////// least squares real linear system using SVD ////////////
 
-/* Subroutine */ int dgelss_(integer *m, integer *n, integer *nrhs,
+int dgelss_(integer *m, integer *n, integer *nrhs,
         doublereal *a, integer *lda, doublereal *b, integer *ldb, doublereal *
         s, doublereal *rcond, integer *rank, doublereal *work, integer *lwork,
          integer *info);
 
-int linearSolveSVDR_l(double rcond,KODMAT(a),KODMAT(b),ODMAT(x)) {
+int linearSolveSVDR_l(double rcond,ODMAT(a),ODMAT(b)) {
     integer m = ar;
     integer n = ac;
     integer nrhs = bc;
-    integer ldb = xr;
-    REQUIRES(m>=1 && n>=1 && ar==br && xr==MAX(m,n) && xc == bc, BAD_SIZE);
+    integer ldb = bXc;
+    REQUIRES(m>=1 && n>=1 && br==MAX(m,n), BAD_SIZE);
     DEBUGMSG("linearSolveSVDR_l");
-    double*AC = (double*)malloc(m*n*sizeof(double));
     double*S = (double*)malloc(MIN(m,n)*sizeof(double));
-    memcpy(AC,ap,m*n*sizeof(double));
-    if (m>=n) {
-        memcpy(xp,bp,m*nrhs*sizeof(double));
-    } else {
-        int k;
-        for(k = 0; k<nrhs; k++) {
-            memcpy(xp+ldb*k,bp+m*k,m*sizeof(double));
-        }
-    }
     integer res;
     integer lwork = -1;
     integer rank;
     double ans;
     dgelss_  (&m,&n,&nrhs,
-             AC,&m,
-             xp,&ldb,
+             ap,&m,
+             bp,&ldb,
              S,
              &rcond,&rank,
              &ans,&lwork,
              &res);
     lwork = ceil(ans);
-    //printf("ans = %d\n",lwork);
     double * work = (double*)malloc(lwork*sizeof(double));
     dgelss_  (&m,&n,&nrhs,
-             AC,&m,
-             xp,&ldb,
+             ap,&m,
+             bp,&ldb,
              S,
              &rcond,&rank,
              work,&lwork,
@@ -747,57 +701,43 @@ int linearSolveSVDR_l(double rcond,KODMAT(a),KODMAT(b),ODMAT(x)) {
     CHECK(res,res);
     free(work);
     free(S);
-    free(AC);
     OK
 }
 
 //////////////////// least squares complex linear system using SVD ////////////
 
-// not in clapack.h
-
 int zgelss_(integer *m, integer *n, integer *nhrs,
     doublecomplex *a, integer *lda, doublecomplex *b, integer *ldb, doublereal *s,
     doublereal *rcond, integer* rank,
     doublecomplex *work, integer* lwork, doublereal* rwork,
     integer *info);
 
-int linearSolveSVDC_l(double rcond, KOCMAT(a),KOCMAT(b),OCMAT(x)) {
+int linearSolveSVDC_l(double rcond, OCMAT(a),OCMAT(b)) {
     integer m = ar;
     integer n = ac;
     integer nrhs = bc;
-    integer ldb = xr;
-    REQUIRES(m>=1 && n>=1 && ar==br && xr==MAX(m,n) && xc == bc, BAD_SIZE);
+    integer ldb = bXc;
+    REQUIRES(m>=1 && n>=1 && br==MAX(m,n), BAD_SIZE);
     DEBUGMSG("linearSolveSVDC_l");
-    doublecomplex*AC = (doublecomplex*)malloc(m*n*sizeof(doublecomplex));
     double*S = (double*)malloc(MIN(m,n)*sizeof(double));
     double*RWORK = (double*)malloc(5*MIN(m,n)*sizeof(double));
-    memcpy(AC,ap,m*n*sizeof(doublecomplex));
-    if (m>=n) {
-        memcpy(xp,bp,m*nrhs*sizeof(doublecomplex));
-    } else {
-        int k;
-        for(k = 0; k<nrhs; k++) {
-            memcpy(xp+ldb*k,bp+m*k,m*sizeof(doublecomplex));
-        }
-    }
     integer res;
     integer lwork = -1;
     integer rank;
     doublecomplex ans;
     zgelss_  (&m,&n,&nrhs,
-             AC,&m,
-             xp,&ldb,
+             ap,&m,
+             bp,&ldb,
              S,
              &rcond,&rank,
              &ans,&lwork,
              RWORK,
              &res);
     lwork = ceil(ans.r);
-    //printf("ans = %d\n",lwork);
     doublecomplex * work = (doublecomplex*)malloc(lwork*sizeof(doublecomplex));
     zgelss_  (&m,&n,&nrhs,
-             AC,&m,
-             xp,&ldb,
+             ap,&m,
+             bp,&ldb,
              S,
              &rcond,&rank,
              work,&lwork,
@@ -810,7 +750,6 @@ int linearSolveSVDC_l(double rcond, KOCMAT(a),KOCMAT(b),OCMAT(x)) {
     free(work);
     free(RWORK);
     free(S);
-    free(AC);
     OK
 }
 
diff --git a/packages/base/src/Internal/LAPACK.hs b/packages/base/src/Internal/LAPACK.hs
index c91cddd..13340f2 100644
--- a/packages/base/src/Internal/LAPACK.hs
+++ b/packages/base/src/Internal/LAPACK.hs
@@ -349,57 +349,75 @@ eigOnlyH = vrev . fst. eigSHAux (zheev 0) "eigH'"
 vrev = flatten . flipud . reshape 1
 
 -----------------------------------------------------------------------------
-foreign import ccall unsafe "linearSolveR_l" dgesv :: TMMM R
-foreign import ccall unsafe "linearSolveC_l" zgesv :: TMMM C
-foreign import ccall unsafe "cholSolveR_l" dpotrs  :: TMMM R
-foreign import ccall unsafe "cholSolveC_l" zpotrs  :: TMMM C
+foreign import ccall unsafe "linearSolveR_l" dgesv :: R ::> R ::> Ok
+foreign import ccall unsafe "linearSolveC_l" zgesv :: C ::> C ::> Ok
 
 linearSolveSQAux g f st a b
     | n1==n2 && n1==r = unsafePerformIO . g $ do
-        s <- createMatrix ColumnMajor r c
-        f # a # b # s #| st
+        a' <- copy ColumnMajor a
+        s  <- copy ColumnMajor b
+        f # a' # s #| st
         return s
     | otherwise = error $ st ++ " of nonsquare matrix"
   where
     n1 = rows a
     n2 = cols a
     r  = rows b
-    c  = cols b
 
 -- | Solve a real linear system (for square coefficient matrix and several right-hand sides) using the LU decomposition, based on LAPACK's /dgesv/. For underconstrained or overconstrained systems use 'linearSolveLSR' or 'linearSolveSVDR'. See also 'lusR'.
 linearSolveR :: Matrix Double -> Matrix Double -> Matrix Double
-linearSolveR a b = linearSolveSQAux id dgesv "linearSolveR" (fmat a) (fmat b)
+linearSolveR a b = linearSolveSQAux id dgesv "linearSolveR" a b
 
 mbLinearSolveR :: Matrix Double -> Matrix Double -> Maybe (Matrix Double)
-mbLinearSolveR a b = linearSolveSQAux mbCatch dgesv "linearSolveR" (fmat a) (fmat b)
+mbLinearSolveR a b = linearSolveSQAux mbCatch dgesv "linearSolveR" a b
 
 
 -- | Solve a complex linear system (for square coefficient matrix and several right-hand sides) using the LU decomposition, based on LAPACK's /zgesv/. For underconstrained or overconstrained systems use 'linearSolveLSC' or 'linearSolveSVDC'. See also 'lusC'.
 linearSolveC :: Matrix (Complex Double) -> Matrix (Complex Double) -> Matrix (Complex Double)
-linearSolveC a b = linearSolveSQAux id zgesv "linearSolveC" (fmat a) (fmat b)
+linearSolveC a b = linearSolveSQAux id zgesv "linearSolveC" a b
 
 mbLinearSolveC :: Matrix (Complex Double) -> Matrix (Complex Double) -> Maybe (Matrix (Complex Double))
-mbLinearSolveC a b = linearSolveSQAux mbCatch zgesv "linearSolveC" (fmat a) (fmat b)
+mbLinearSolveC a b = linearSolveSQAux mbCatch zgesv "linearSolveC" a b
+
+--------------------------------------------------------------------------------
+foreign import ccall unsafe "cholSolveR_l" dpotrs  :: R ::> R ::> Ok
+foreign import ccall unsafe "cholSolveC_l" zpotrs  :: C ::> C ::> Ok
+
+
+linearSolveSQAux2 g f st a b
+    | n1==n2 && n1==r = unsafePerformIO . g $ do
+        s <- copy ColumnMajor b
+        f # a # s #| st
+        return s
+    | otherwise = error $ st ++ " of nonsquare matrix"
+  where
+    n1 = rows a
+    n2 = cols a
+    r  = rows b
 
 -- | Solves a symmetric positive definite system of linear equations using a precomputed Cholesky factorization obtained by 'cholS'.
 cholSolveR :: Matrix Double -> Matrix Double -> Matrix Double
-cholSolveR a b = linearSolveSQAux id dpotrs "cholSolveR" (fmat a) (fmat b)
+cholSolveR a b = linearSolveSQAux2 id dpotrs "cholSolveR" (fmat a) b
 
 -- | Solves a Hermitian positive definite system of linear equations using a precomputed Cholesky factorization obtained by 'cholH'.
 cholSolveC :: Matrix (Complex Double) -> Matrix (Complex Double) -> Matrix (Complex Double)
-cholSolveC a b = linearSolveSQAux id zpotrs "cholSolveC" (fmat a) (fmat b)
+cholSolveC a b = linearSolveSQAux2 id zpotrs "cholSolveC" (fmat a) b
 
 -----------------------------------------------------------------------------------
 
-foreign import ccall unsafe "linearSolveLSR_l" dgels :: TMMM R
-foreign import ccall unsafe "linearSolveLSC_l" zgels :: TMMM C
-foreign import ccall unsafe "linearSolveSVDR_l" dgelss :: Double -> TMMM R
-foreign import ccall unsafe "linearSolveSVDC_l" zgelss :: Double -> TMMM C
-
-linearSolveAux f st a b = unsafePerformIO $ do
-    r <- createMatrix ColumnMajor (max m n) nrhs
-    f # a # b # r #| st
-    return r
+foreign import ccall unsafe "linearSolveLSR_l"   dgels ::           R ::> R ::> Ok
+foreign import ccall unsafe "linearSolveLSC_l"   zgels ::           C ::> C ::> Ok
+foreign import ccall unsafe "linearSolveSVDR_l" dgelss :: Double -> R ::> R ::> Ok
+foreign import ccall unsafe "linearSolveSVDC_l" zgelss :: Double -> C ::> C ::> Ok
+
+linearSolveAux f st a b
+    | m == rows b = unsafePerformIO $ do
+        a' <- copy ColumnMajor a
+        r  <- createMatrix ColumnMajor (max m n) nrhs
+        setRect 0 0 b r
+        f # a' # r #| st
+        return r
+    | otherwise = error $ "different number of rows in linearSolve ("++st++")"
   where
     m = rows a
     n = cols a
@@ -408,12 +426,12 @@ linearSolveAux f st a b = unsafePerformIO $ do
 -- | Least squared error solution of an overconstrained real linear system, or the minimum norm solution of an underconstrained system, using LAPACK's /dgels/. For rank-deficient systems use 'linearSolveSVDR'.
 linearSolveLSR :: Matrix Double -> Matrix Double -> Matrix Double
 linearSolveLSR a b = subMatrix (0,0) (cols a, cols b) $
-                     linearSolveAux dgels "linearSolverLSR" (fmat a) (fmat b)
+                     linearSolveAux dgels "linearSolverLSR" a b
 
 -- | Least squared error solution of an overconstrained complex linear system, or the minimum norm solution of an underconstrained system, using LAPACK's /zgels/. For rank-deficient systems use 'linearSolveSVDC'.
 linearSolveLSC :: Matrix (Complex Double) -> Matrix (Complex Double) -> Matrix (Complex Double)
 linearSolveLSC a b = subMatrix (0,0) (cols a, cols b) $
-                     linearSolveAux zgels "linearSolveLSC" (fmat a) (fmat b)
+                     linearSolveAux zgels "linearSolveLSC" a b
 
 -- | Minimum norm solution of a general real linear least squares problem Ax=B using the SVD, based on LAPACK's /dgelss/. Admits rank-deficient systems but it is slower than 'linearSolveLSR'. The effective rank of A is determined by treating as zero those singular valures which are less than rcond times the largest singular value. If rcond == Nothing machine precision is used.
 linearSolveSVDR :: Maybe Double   -- ^ rcond
@@ -421,8 +439,8 @@ linearSolveSVDR :: Maybe Double   -- ^ rcond
                 -> Matrix Double  -- ^ right hand sides (as columns)
                 -> Matrix Double  -- ^ solution vectors (as columns)
 linearSolveSVDR (Just rcond) a b = subMatrix (0,0) (cols a, cols b) $
-                                   linearSolveAux (dgelss rcond) "linearSolveSVDR" (fmat a) (fmat b)
-linearSolveSVDR Nothing a b = linearSolveSVDR (Just (-1)) (fmat a) (fmat b)
+                                   linearSolveAux (dgelss rcond) "linearSolveSVDR" a b
+linearSolveSVDR Nothing a b = linearSolveSVDR (Just (-1)) a b
 
 -- | Minimum norm solution of a general complex linear least squares problem Ax=B using the SVD, based on LAPACK's /zgelss/. Admits rank-deficient systems but it is slower than 'linearSolveLSC'. The effective rank of A is determined by treating as zero those singular valures which are less than rcond times the largest singular value. If rcond == Nothing machine precision is used.
 linearSolveSVDC :: Maybe Double            -- ^ rcond
@@ -430,8 +448,8 @@ linearSolveSVDC :: Maybe Double            -- ^ rcond
                 -> Matrix (Complex Double) -- ^ right hand sides (as columns)
                 -> Matrix (Complex Double) -- ^ solution vectors (as columns)
 linearSolveSVDC (Just rcond) a b = subMatrix (0,0) (cols a, cols b) $
-                                   linearSolveAux (zgelss rcond) "linearSolveSVDC" (fmat a) (fmat b)
-linearSolveSVDC Nothing a b = linearSolveSVDC (Just (-1)) (fmat a) (fmat b)
+                                   linearSolveAux (zgelss rcond) "linearSolveSVDC" a b
+linearSolveSVDC Nothing a b = linearSolveSVDC (Just (-1)) a b
 
 -----------------------------------------------------------------------------------