EWM
===

.. cpp:class:: numpy::EWM

   numpy C++ class.

Example
-------

.. code-block:: cpp

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

   // Use EWM
   EWM obj;
   // ... operations ...

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

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

   * - Signature
     - Location
     - Example
   * - ``EWM(const Series<T>& series, double alpha, bool adjust, bool ignore_na, size_t min_periods)``
     - df_ewm.h:50
     - 

Construction
------------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``static EWM from_alpha(const Series<T>& series, double alpha, bool adjust = true, bool ignore_na = false, size_t min_periods = 0)``
     - static EWM
     - df_ewm.h:120
     - 
   * - ``static EWM from_com(const Series<T>& series, double com, bool adjust = true, bool ignore_na = false, size_t min_periods = 0)``
     - static EWM
     - df_ewm.h:86
     - 
   * - ``static EWM from_halflife(const Series<T>& series, double halflife, bool adjust = true, bool ignore_na = false, size_t min_periods = 0)``
     - static EWM
     - df_ewm.h:103
     - 
   * - ``static EWM from_span(const Series<T>& series, double span, bool adjust = true, bool ignore_na = false, size_t min_periods = 0)``
     - static EWM
     - df_ewm.h:69
     - 

Indexing / Selection
--------------------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``double get_value(size_t i) const``
     - double
     - df_ewm.h:292
     - 

Statistics
----------

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``Series<double> mean() const``
     - Series<double>
     - df_ewm.h:133
     - :ref:`View <example-ewm-mean-0>`
   * - ``Series<double> std\_(int ddof = 1) const``
     - Series<double>
     - df_ewm.h:268
     - 
   * - ``Series<double> var(int ddof = 1) const``
     - Series<double>
     - df_ewm.h:206
     - :ref:`View <example-ewm-var-1>`

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

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

   * - Signature
     - Return Type
     - Location
     - Example
   * - ``bool adjust() const``
     - bool
     - df_ewm.h:285
     - 
   * - ``double alpha() const``
     - double
     - df_ewm.h:284
     - 
   * - ``bool ignore_na() const``
     - bool
     - df_ewm.h:286
     - 


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

The following examples are extracted from the test suite.

.. _example-ewm-mean-0:

.. dropdown:: mean (np_test_1_all.cpp:11714)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 11704
      :emphasize-lines: 11

          // Create test array
          auto array = createInt32Array({ 2, 3 }, 0);
          array.setElementAt({ 0, 0 }, 1);
          array.setElementAt({ 0, 1 }, 2);
          array.setElementAt({ 0, 2 }, 3);
          array.setElementAt({ 1, 0 }, 4);
          array.setElementAt({ 1, 1 }, 5);
          array.setElementAt({ 1, 2 }, 6);
      
          // Test mean without axis
          auto mean_all = mean(array);
          if (!(approx_equal(mean_all.getElementAt({ 0 }), 3.5, 1e-10))) {
              std::string description = std::string("testBasicStatistics():") + __FILE__ + ":" + std::to_string(__LINE__) + ": !(approx_equal(mean_all.getElementAt({ 0 }), 3.5, 1e-10))";
              std::cout << std::string("[FAIL] ") + description << std::endl;
              throw std::runtime_error(description);
          }
          // std::cout << "[OK] mean (all elements) works correctly\n";
      
          // Test mean along axis 0
          auto mean_axis0 = mean(array, 0);
          if (!(mean_axis0.getShape()[0] == 3)) {

.. _example-ewm-var-1:

.. dropdown:: var (np_test_1_all.cpp:11816)
   :class-title: example-dropdown

   .. code-block:: cpp
      :linenos:
      :lineno-start: 11806
      :emphasize-lines: 11

          std::cout << "========= testVarianceAndStandardDeviation =======================";
      
          // Create test array with known variance
          auto array = createFloat64Array({ 4 }, 0);
          array.setElementAt({ 0 }, 1.0);
          array.setElementAt({ 1 }, 2.0);
          array.setElementAt({ 2 }, 3.0);
          array.setElementAt({ 3 }, 4.0);
      
          // Test variance (population)
          auto var_result = var(array, std::nullopt, 0);  // ddof=0 for population variance
          double expected_var = 1.25;  // Known variance for [1,2,3,4]
          if (!(approx_equal(var_result.getElementAt({ 0 }), expected_var, 1e-10))) {
              std::string description = std::string("testVarianceAndStandardDeviation():") + __FILE__ + ":" + std::to_string(__LINE__) + ": !(approx_equal(var_result.getElementAt({ 0 }), expected_var, 1e-10))";
              std::cout << std::string("[FAIL] ") + description << std::endl;
              throw std::runtime_error(description);
          }
          // std::cout << "[OK] Population variance works correctly\n";
      
          // Test variance (sample)
          auto var_sample = var(array, std::nullopt, 1);  // ddof=1 for sample variance