diff --git a/lapack/eigenvalues.inc b/lapack/eigenvalues.inc
index 921c515..62192f4 100644
--- a/lapack/eigenvalues.inc
+++ b/lapack/eigenvalues.inc
@@ -11,52 +11,53 @@
 #include <Eigen/Eigenvalues>
 
 // computes eigen values and vectors of a general N-by-N matrix A
-EIGEN_LAPACK_FUNC(syev,(char *jobz, char *uplo, int* n, Scalar* a, int *lda, Scalar* w, Scalar* /*work*/, int* lwork, int *info))
-{
+EIGEN_LAPACK_FUNC(syev, (char* jobz, char* uplo, int* n, Scalar* a, int* lda, Scalar* w, Scalar* /*work*/, int* lwork,
+                         int* info)) {
   // TODO exploit the work buffer
-  bool query_size = *lwork==-1;
-  
+  bool query_size = *lwork == -1;
+
   *info = 0;
-        if(*jobz!='N' && *jobz!='V')                    *info = -1;
-  else  if(UPLO(*uplo)==INVALID)                        *info = -2;
-  else  if(*n<0)                                        *info = -3;
-  else  if(*lda<std::max(1,*n))                         *info = -5;
-  else  if((!query_size) && *lwork<std::max(1,3**n-1))  *info = -8;
-    
-  if(*info!=0)
-  {
+  if (*jobz != 'N' && *jobz != 'V')
+    *info = -1;
+  else if (UPLO(*uplo) == INVALID)
+    *info = -2;
+  else if (*n < 0)
+    *info = -3;
+  else if (*lda < std::max(1, *n))
+    *info = -5;
+  else if ((!query_size) && *lwork < std::max(1, 3 * *n - 1))
+    *info = -8;
+
+  if (*info != 0) {
     int e = -*info;
-    return xerbla_(SCALAR_SUFFIX_UP"SYEV ", &e, 6);
+    return xerbla_(SCALAR_SUFFIX_UP "SYEV ", &e, 6);
   }
-  
-  if(query_size)
-  {
+
+  if (query_size) {
     *lwork = 0;
     return 0;
   }
-  
-  if(*n==0)
-    return 0;
-  
-  PlainMatrixType mat(*n,*n);
-  if(UPLO(*uplo)==UP) mat = matrix(a,*n,*n,*lda).adjoint();
-  else                mat = matrix(a,*n,*n,*lda);
-  
-  bool computeVectors = *jobz=='V' || *jobz=='v';
-  SelfAdjointEigenSolver<PlainMatrixType> eig(mat,computeVectors?ComputeEigenvectors:EigenvaluesOnly);
-  
-  if(eig.info()==NoConvergence)
-  {
-    make_vector(w,*n).setZero();
-    if(computeVectors)
-      matrix(a,*n,*n,*lda).setIdentity();
+
+  if (*n == 0) return 0;
+
+  PlainMatrixType mat(*n, *n);
+  if (UPLO(*uplo) == UP)
+    mat = matrix(a, *n, *n, *lda).adjoint();
+  else
+    mat = matrix(a, *n, *n, *lda);
+
+  bool computeVectors = *jobz == 'V' || *jobz == 'v';
+  SelfAdjointEigenSolver<PlainMatrixType> eig(mat, computeVectors ? ComputeEigenvectors : EigenvaluesOnly);
+
+  if (eig.info() == NoConvergence) {
+    make_vector(w, *n).setZero();
+    if (computeVectors) matrix(a, *n, *n, *lda).setIdentity();
     //*info = 1;
     return 0;
   }
-  
-  make_vector(w,*n) = eig.eigenvalues();
-  if(computeVectors)
-    matrix(a,*n,*n,*lda) = eig.eigenvectors();
-  
+
+  make_vector(w, *n) = eig.eigenvalues();
+  if (computeVectors) matrix(a, *n, *n, *lda) = eig.eigenvectors();
+
   return 0;
 }