Update documents

README.md

@@ -22,12 +22,18 @@ It provides similar interfaces as Numpy and Scipy in Python.
 
 ### For document generation
 
-- Doxygen (< 1.8.12)
+- Doxygen (>= 1.9.1)
 
 ## How to Use
 
 1. Build and install mptensor library
 
+        # Modern CMake (>= 3.15)
+        cmake -B build
+        cmake --build build
+        sudo cmake --install build
+
+        # Traditional way
         mkdir build
         cd build
         cmake ../
@@ -39,9 +45,12 @@ It provides similar interfaces as Numpy and Scipy in Python.
 
 The default install directory is `/usr/local`. It can be changed by `-DCMAKE_INSTALL_PREFIX` option.
 
-    $ cmake -DCMAKE_INSTALL_PREFIX=/home/smorita/.local ../
+    # Modern CMake
+    cmake --install build --prefix your_install_prefix
+    # Traditional way
+    cmake -DCMAKE_INSTALL_PREFIX=your_install_path ../
 
-See also the [cmake page](https://cmake.org/cmake/help/v3.6/variable/CMAKE_INSTALL_PREFIX.html).
+See also the [CMake documentation](https://cmake.org/cmake/help/latest/manual/cmake.1.html).
 
 ## Documents
 

include/mptensor/tensor.hpp

@@ -58,13 +58,16 @@ class Tensor {
   typedef typename Matrix<C>::comm_type comm_type;  //!< type of communicator.
   /*!< \c MPI_Comm or \c int. */
 
+  //! \ingroup TensorConstructor
+  //! \{
   Tensor();
   explicit Tensor(const Shape &);
   explicit Tensor(const comm_type &);
   Tensor(const comm_type &, const Shape &);
   Tensor(const comm_type &, const Shape &, size_t upper_rank);
   Tensor(const comm_type &, const Tensor<lapack::Matrix, C> &);
   Tensor(const comm_type &, const std::vector<C> &);
+  //! \}
 
   const Shape &shape() const;
   size_t rank() const;

include/mptensor/tensor_impl.hpp

@@ -187,6 +187,12 @@ inline size_t Tensor<Matrix, C>::get_upper_rank() const {
 };
 
 //! Map of axes for lazy evaluation of transpose
+/*!
+  `axes_map` stores an index mapping from a before-transposed tensor to an after-transposed tensor.
+
+  Let `V` a 3-leg tensor with `shape=[10, 20, 30]` and `axes_map=[0, 1, 2]`.
+  When we transpose `V` as `T = V.transpose(Axes(1, 2, 0));`, `T` has `shape=[20, 30, 10]` and `axes_map=[2, 0, 1]`. Thus, `axes_map` satisfies `axes_map[iV] = iT`.
+*/
 template <template <typename> class Matrix, typename C>
 inline const Axes &Tensor<Matrix, C>::get_axes_map() const {
   return axes_map;