Signature | Description | Parameters |
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#include <DataFrame/DataFrameFinancialVisitors.h> template<typename T, typename I = unsigned long, std::size_t A = 0> struct RollingMidValueVisitor; // ------------------------------------- template<typename T, typename I = unsigned long, std::size_t A = 0> using mid_val_v = RollingMidValueVisitor<T, I, A>; |
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 visitor calculates the rolling averages of the lowest values of the first time-series and highest values of the second time-series rolling window. For example the first time-series could be low or bid prices of stocks and the second time-series could be high or ask prices of stocks The result is a vector of values with same number of items as the given column. The first roll_count items, in the result, will be NAN. explicit RollingMidValueVisitor(size_t roll_count); |
T: Column data type I: Index type A: Memory alignment boundary for vectors. Default is system default alignment |
static void test_RollingMidValueVisitor() { std::cout << "\nTesting RollingMidValueVisitor{ } ..." << std::endl; std::vector<unsigned long> idx = { 123450, 123451, 123452, 123453, 123454, 123455, 123456, 123457, 123458, 123459, 123460, 123461, 123462, 123466, 123467, 123468, 123469, 123470, 123471, 123472, 123473, }; std::vector<double> high = { 121, 122, 124, 124.5, 135.5, 132, 128, 127, 126, 125, 126.5, 127, 120, 117, 116, 116.5, 114, 112, 109, 109.5, 111, }; std::vector<double> low = { 118, 121, 121.5, 122, 129, 127, 126, 124, 125, 123, 124, 125, 116, 114, 112, 115, 111, 110, 105, 106, 107, }; MyDataFrame df; df.load_data(std::move(idx), std::make_pair("high", high), std::make_pair("low", low)); RollingMidValueVisitor<double> rmv_v (5); df.single_act_visit<double, double>("low", "high", rmv_v); assert(rmv_v.get_result().size() == 21); assert(std::isnan(rmv_v.get_result()[0])); assert(std::isnan(rmv_v.get_result()[1])); assert(std::isnan(rmv_v.get_result()[3])); assert(rmv_v.get_result()[4] == 126.75); assert(rmv_v.get_result()[5] == 128.25); assert(rmv_v.get_result()[10] == 125.5); assert(rmv_v.get_result()[11] == 125); assert(rmv_v.get_result()[20] == 109.5); assert(rmv_v.get_result()[19] == 110.75); }