AutoTunedEigenSolver
====================

.. cpp:class:: numpy::AutoTunedEigenSolver

   numpy C++ class.

Example
-------

.. code-block:: cpp

   #include <numpy/np_ndarray.h>
   using namespace numpy;

   // Use AutoTunedEigenSolver
   AutoTunedEigenSolver obj;
   // ... operations ...

Constructors
------------

.. list-table::
   :widths: 55 25 20
   :header-rows: 1

   * - Signature
     - Location
     - Example
   * - ``AutoTunedEigenSolver(typename real_type<T>::typetolerance = machine_epsilon<typename real_type<T>::type>(), boolenable_auto_tuning = true, size_tsample_rate = 10)``
     - NP_LINALG_UTILS.H:2774
     - 

Linear Algebra
--------------

.. list-table::
   :widths: 40 20 15 25
   :header-rows: 1

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``::numpy::linalg::EigenDecomposition<T> solve(const NDArray<T>&matrix, boolcompute_eigenvectors = true)``
     - ::numpy::linalg::EigenDecomposition<T>
     - NP_LINALG_UTILS.H:2782
     - :ref:`View <example-autotunedeigensolver-solve-0>`

Other Methods
-------------

.. list-table::
   :widths: 40 20 15 25
   :header-rows: 1

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``void clearPerformanceHistory()``
     - void
     - NP_LINALG_UTILS.H:2908
     - 
   * - ``void setAutoTuning(boolenable)``
     - void
     - NP_LINALG_UTILS.H:2903
     - 
   * - ``void setTolerance(typename real_type<T>::typetol)``
     - void
     - NP_LINALG_UTILS.H:2898
     - 


Code Examples
-------------

The following examples are extracted from the test suite.

.. _example-autotunedeigensolver-solve-0:

.. dropdown:: solve (np_test_2_all.cpp:5150)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 5140
      :emphasize-lines: 11

           * Test linear system solving
           */
          void testMatrixSolvers() {
            std::cout << "========= testMatrixSolvers =======================";
      
            // Test solve for simple 2x2 system
            numpy::Matrix<double> A("2 1; 1 1");
            numpy::Matrix<double> b("3; 2");
      
            try {
              auto x = numpy::solve(A, b);
              assert_test(x.rows() == 2 && x.cols() == 1, "Solve result dimensions");
      
              // Verify A * x = b
              auto Ax = A * x;
              assert_test(std::abs(Ax(0, 0) - b(0, 0)) < 1e-10, "Solve verification 0");
              assert_test(std::abs(Ax(1, 0) - b(1, 0)) < 1e-10, "Solve verification 1");
            }
            catch (...) {
              // std::cout << "Linear system solve test failed (expected for some systems)";
            }