EWM

class numpy::EWM

numpy C++ class.

Example

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

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

Constructors

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

Construction

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

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

Statistics

Signature	Return Type	Location	Example
Series<double> mean() const	Series<double>	df_ewm.h:133	View
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	View

Other Methods

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.

mean (np_test_1_all.cpp:11714)

    // 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)) {

var (np_test_1_all.cpp:11816)

    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