update example code

README.md

@@ -102,15 +102,15 @@ int main()
  DenseSymMatProd<double> op(M);
 
  // Construct eigen solver object, requesting the largest three eigenvalues
- SymEigsSolver< double, LARGEST_ALGE, DenseSymMatProd<double> > eigs(&op, 3, 6);
+ SymEigsSolver<double, DenseSymMatProd<double>> eigs(op, 3, 6);
 
  // Initialize and compute
  eigs.init();
- int nconv = eigs.compute();
+ int nconv = eigs.compute(SortRule::LargestAlge);
 
  // Retrieve results
  Eigen::VectorXd evalues;
- if(eigs.info() == SUCCESSFUL)
+ if(eigs.info() == CompInfo::Successful)
   evalues = eigs.eigenvalues();
 
  std::cout << "Eigenvalues found:\n" << evalues << std::endl;
@@ -150,15 +150,15 @@ int main()
  SparseGenMatProd<double> op(M);
 
  // Construct eigen solver object, requesting the largest three eigenvalues
- GenEigsSolver< double, LARGEST_MAGN, SparseGenMatProd<double> > eigs(&op, 3, 6);
+ GenEigsSolver<double, SparseGenMatProd<double>> eigs(op, 3, 6);
 
  // Initialize and compute
  eigs.init();
- int nconv = eigs.compute();
+ int nconv = eigs.compute(SortRule::LargestMagn);
 
  // Retrieve results
  Eigen::VectorXcd evalues;
- if(eigs.info() == SUCCESSFUL)
+ if(eigs.info() == CompInfo::Successful)
   evalues = eigs.eigenvalues();
 
  std::cout << "Eigenvalues found:\n" << evalues << std::endl;
@@ -183,7 +183,7 @@ public:
  int rows() { return 10; }
  int cols() { return 10; }
  // y_out = M * x_in
- void perform_op(const double *x_in, double *y_out)
+ void perform_op(const double *x_in, double *y_out) const
  {
  for(int i = 0; i < rows(); i++)
  {
@@ -195,10 +195,10 @@ public:
 int main()
 {
  MyDiagonalTen op;
- SymEigsSolver<double, LARGEST_ALGE, MyDiagonalTen> eigs(&op, 3, 6);
+ SymEigsSolver<double, MyDiagonalTen> eigs(op, 3, 6);
  eigs.init();
- eigs.compute();
- if(eigs.info() == SUCCESSFUL)
+ eigs.compute(SortRule::LargestAlge);
+ if(eigs.info() == CompInfo::Successful)
  {
   Eigen::VectorXd evalues = eigs.eigenvalues();
   std::cout << "Eigenvalues found:\n" << evalues << std::endl;
@@ -235,9 +235,9 @@ More information can be found in the project page [https://spectralib.org](https
 An optional CMake installation is supported, if you have CMake with at least v3.10 installed. You can install the headers using the following commands:
 
 ```bash
- mkdir build && cd build
- cmake .. -DCMAKE_INSTALL_PREFIX='intended installation directory' -DCMAKE_PREFIX_PATH='path where the installation of Eigen3 can be found' -DBUILD_TESTS=TRUE
- make all && make tests && make install
+mkdir build && cd build
+cmake .. -DCMAKE_INSTALL_PREFIX='intended installation directory' -DCMAKE_PREFIX_PATH='path where the installation of Eigen3 can be found' -DBUILD_TESTS=TRUE
+make all && make tests && make install
 ```
 
 By installing Spectra in this way, you also create a CMake target 'Spectra::Spectra' that can be used in subsequent build procedures for other programs.