Signature Description Parameters
#include <DataFrame/DataFrameFinancialVisitors.h>

template<typename T, typename I = unsigned long>
struct DoubleCrossOver;

// -------------------------------------

template<typename T, typename I = unsigned long>
using dco_v = DoubleCrossOver<T, I>;
        
This is a “single action visitor”, meaning it is passed the whole data vector in one call and you must use the single_act_visit() interface.

This functor class calculates the crossover of a data vector with two of its moving averages. It could be used to generate signals within financial applications.
The constructor takes the two adopters:
    DoubleCrossOver(S_RT &&short_moving, L_RT &&long_moving)
        
There are 3 methods that give you the results:
  1. const result_type &get_raw_to_short_term() const – Returns a vector of data column minus short moving average
  2. const result_type &get_raw_to_long_term() const – Returns a vector of data column minus long moving average
  3. const result_type &get_short_term_to_long_term () const – Returns a vector of short term moving average minus long moving average
S_RT: A short term moving average adopter. For example, a simple moving adopter using a geometric mean
L_RT: A longer term moving average adopter. For example, an exponential moving adopter using a simple mean
T: Column data type
I: Index type
static void test_DoubleCrossOver()  {

    std::cout << "\nTesting DoubleCrossOver{ } ..." << std::endl;

    MyDataFrame::set_thread_level(10);

    std::vector<unsigned long>  idx =
        { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
          21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 };
    std::vector<double> d1 =
        { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
          19, 18, 17, 17, 16, 15, 14, 13, 14, 13, 12, 11, 12, 10, 9, 8, 7, 6, 7, 5 };
    MyDataFrame         df;

    df.load_data(std::move(idx), std::make_pair("col_1", d1));

    using geo_mean_t = GeometricMeanVisitor<double>;
    using mean_t = MeanVisitor<double>;
    using short_roller_t = SimpleRollAdopter<geo_mean_t, double>;
    using long_roller_t = ExponentialRollAdopter<mean_t, double>;
    using double_cross_t = DoubleCrossOver<short_roller_t, long_roller_t, double>;

    double_cross_t  visitor(short_roller_t(geo_mean_t(), 3), long_roller_t(mean_t(), 4, exponential_decay_spec::span, 1.5));

    df.single_act_visit<double>("col_1", visitor);

    auto    &raw_to_short = visitor.get_raw_to_short_term();
    auto    &raw_to_long = visitor.get_raw_to_long_term();
    auto    &short_to_long = visitor.get_short_term_to_long_term();

    assert(raw_to_short.size() == 40);
    assert(std::isnan(raw_to_short[1]));
    assert(fabs(raw_to_short[8] - 1.04189) < 0.00001);
    assert(fabs(raw_to_short[12] - 1.02784) < 0.00001);
    assert(fabs(raw_to_short[39] - -0.943922) < 0.00001);
    assert(fabs(raw_to_short[38] - 0.3506) < 0.00001);

    assert(raw_to_long.size() == 40);
    assert(std::isnan(raw_to_long[2]));
    assert(fabs(raw_to_long[8] - 0.2504) < 0.00001);
    assert(fabs(raw_to_long[12] - 0.250001) < 0.00001);
    assert(fabs(raw_to_long[39] - -0.370008) < 0.00001);
    assert(fabs(raw_to_long[38] - 0.149962) < 0.00001);

    assert(short_to_long.size() == 40);
    assert(std::isnan(short_to_long[0]));
    assert(fabs(short_to_long[8] - -0.791486) < 0.00001);
    assert(fabs(short_to_long[12] - -0.777842) < 0.00001);
    assert(fabs(short_to_long[39] - 0.573914) < 0.00001);
    assert(fabs(short_to_long[38] - -0.200639) < 0.00001);

    MyDataFrame::set_thread_level(0);
}