mirror of
https://gitee.com/fasiondog/hikyuu.git
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197 lines
6.6 KiB
C++
197 lines
6.6 KiB
C++
/*
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* Copyright (c) 2023 hikyuu.org
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*
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* Created on: 2023-10-10
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* Author: fasiondog
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*/
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#include <hikyuu/analysis/combinate.h>
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#include <hikyuu/analysis/analysis_sys.h>
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#include "pybind_utils.h"
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using namespace hku;
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namespace py = pybind11;
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static py::list combinate_index(py::object seq) {
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size_t total = len(seq);
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std::vector<size_t> index_list(total);
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for (size_t i = 0; i < total; ++i) {
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index_list[i] = i;
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}
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py::list result;
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std::vector<std::vector<size_t>> comb = combinateIndex(index_list);
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for (size_t i = 0, count = comb.size(); i < count; i++) {
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py::list tmp = vector_to_python_list<size_t>(comb[i]);
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result.append(tmp);
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}
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return result;
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}
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static py::list combinate_indicator(const py::sequence& seq, int n) {
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size_t total = len(seq);
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std::vector<Indicator> inds(total);
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for (size_t i = 0; i < total; ++i) {
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inds[i] = seq[i].cast<Indicator>();
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}
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auto comb = combinateIndicator(inds, n);
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return vector_to_python_list(comb);
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}
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static py::dict combinate_ind_analysis(const Stock& stk, const KQuery& query, TradeManagerPtr tm,
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SystemPtr sys, py::sequence buy_inds, py::sequence sell_inds,
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int n) {
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std::vector<Indicator> c_buy_inds;
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for (size_t i = 0, total = len(buy_inds); i < total; i++) {
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c_buy_inds.emplace_back(buy_inds[i].cast<Indicator>());
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}
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std::vector<Indicator> c_sell_inds;
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for (size_t i = 0, total = len(sell_inds); i < total; i++) {
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c_sell_inds.emplace_back(sell_inds[i].cast<Indicator>());
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}
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py::dict result;
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auto pers = combinateIndicatorAnalysis(stk, query, tm, sys, c_buy_inds, c_sell_inds, n);
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for (auto iter = pers.begin(); iter != pers.end(); ++iter) {
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result[iter->first.c_str()] = std::move(iter->second);
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}
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return result;
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}
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static py::dict combinate_ind_analysis_with_block(const Block& blk, const KQuery& query,
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TradeManagerPtr tm, SystemPtr sys,
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const py::sequence& buy_inds,
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const py::sequence& sell_inds, int n) {
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std::vector<Indicator> c_buy_inds;
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for (size_t i = 0, total = len(buy_inds); i < total; i++) {
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c_buy_inds.emplace_back(buy_inds[i].cast<Indicator>());
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}
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std::vector<Indicator> c_sell_inds;
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for (size_t i = 0, total = len(sell_inds); i < total; i++) {
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c_sell_inds.emplace_back(sell_inds[i].cast<Indicator>());
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}
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auto records =
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combinateIndicatorAnalysisWithBlock(blk, query, tm, sys, c_buy_inds, c_sell_inds, n);
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std::vector<py::list> tmp;
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StringList names{"组合名称", "证券代码", "证券名称"};
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Performance per;
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auto keys = per.names();
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for (const auto& key : keys) {
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names.emplace_back(key);
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}
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for (size_t i = 0, len = names.size(); i < len; i++) {
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tmp.emplace_back(py::list());
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}
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for (size_t i = 0, total = records.size(); i < total; i++) {
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CombinateAnalysisOutput& record = records[i];
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tmp[0].append(record.combinateName);
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tmp[1].append(record.market_code);
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tmp[2].append(record.name);
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HKU_WARN_IF(names.size() != record.values.size() + 3, "lenght invalid: {} {}", names.size(),
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record.values.size());
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for (size_t j = 3, len = names.size(); j < len; j++) {
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tmp[j].append(record.values[j - 3]);
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}
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}
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py::dict result;
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for (size_t i = 0, total = names.size(); i < total; i++) {
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result[names[i].c_str()] = tmp[i];
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}
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return result;
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}
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static py::dict analysis_sys_list(const py::object& pystk_list, const KQuery& query,
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SystemPtr sys_proto) {
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HKU_CHECK(sys_proto, "sys_proto is null!");
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sys_proto->forceResetAll();
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SystemList sys_list;
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StockList stk_list;
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if (py::isinstance<Block>(pystk_list)) {
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const auto& blk = pystk_list.cast<Block&>();
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for (const auto& stk : blk) {
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sys_list.emplace_back(std::move(sys_proto->clone()));
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stk_list.emplace_back(stk);
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}
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} else if (py::isinstance<StockManager>(pystk_list)) {
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const auto& blk = pystk_list.cast<StockManager&>();
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for (const auto& stk : blk) {
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sys_list.emplace_back(std::move(sys_proto->clone()));
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stk_list.emplace_back(stk);
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}
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} else if (py::isinstance<py::sequence>(pystk_list)) {
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auto pyseq = pystk_list.cast<py::sequence>();
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for (const auto& obj : pyseq) {
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sys_list.emplace_back(std::move(sys_proto->clone()));
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stk_list.emplace_back(obj.cast<Stock&>());
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}
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}
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vector<AnalysisSystemWithBlockOut> records;
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{
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py::gil_scoped_release release;
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records = analysisSystemList(sys_list, stk_list, query);
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}
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Performance per;
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auto keys = per.names();
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std::vector<py::list> tmp(keys.size() + 2);
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for (size_t i = 0, total = records.size(); i < total; i++) {
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const auto& record = records[i];
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if (record.values.size() != keys.size()) {
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continue;
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}
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tmp[0].append(record.market_code);
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tmp[1].append(record.name);
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for (size_t j = 0, len = keys.size(); j < len; j++) {
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tmp[j + 2].append(record.values[j]);
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}
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}
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py::dict result;
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result["证券代码"] = tmp[0];
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result["证券名称"] = tmp[1];
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for (size_t i = 0, total = keys.size(); i < total; i++) {
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if (!tmp[i + 2].empty()) {
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result[keys[i].c_str()] = tmp[i + 2];
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}
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}
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return result;
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}
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void export_analysis(py::module& m) {
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m.def("combinate_index", combinate_index, R"(combinate_index(seq)
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获取序列组合的下标索引, 输入序列的长度最大不超过15，否则抛出异常
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:param inds: list 或 tuple 等可使用索引的可迭代对象
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:return: 返回组合的索引，可用于获取输入中相应索引位置的值
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:rtype: list)");
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m.def("combinate_ind", combinate_indicator, py::arg("inds"), py::arg("n") = 7,
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R"(combinate_ind(inds[, n=7])
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对输入的指标序列进行组合, 如输入为 [ind1, ind2], 输出为 [EXIST(ind1,n), EXIST(ind2,n),
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EXIST(ind1,n)&EXIST(ind2,n)]
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:param list|tuple|seq inds: 待组合的指标列表
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:param int n: 指标在 n 周期内存在
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:return: 组合后的指标列表
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:rtype: list)");
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m.def("inner_combinate_ind_analysis", combinate_ind_analysis);
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m.def("inner_combinate_ind_analysis_with_block", combinate_ind_analysis_with_block);
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m.def("inner_analysis_sys_list", analysis_sys_list);
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} |