087a2f0d74
Move the pricing engine sources out of src/ into cpp/, add the closed-form engine and pybind wiring, and align tests/build targets with the new project layout. Made-with: Cursor
94 lines
3.3 KiB
C++
94 lines
3.3 KiB
C++
/**
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* @file Pybind.cpp
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* @brief pybind11 module @c qengine exposing @ref BSWrapper::bs_price_wrapper overloads.
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*/
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#include <pybind11/numpy.h>
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#include <pybind11/pybind11.h>
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#include <pybind11/stl.h>
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#include <cstdint>
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#include <stdexcept>
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#include <string>
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#include <vector>
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#include "BSWrapper.hpp"
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namespace py = pybind11;
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namespace {
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std::vector<double> to_vector_double(const py::array_t<double> &a) {
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py::buffer_info info = a.request();
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if (info.ndim != 1) {
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throw std::runtime_error("expected 1-D ndarray for S, K, T, r, sigma");
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}
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const auto *p = static_cast<const double *>(info.ptr);
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const ssize_t n = info.shape[0];
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return std::vector<double>(p, p + n);
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}
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std::vector<bool> to_vector_bool_1d(const py::array_t<bool> &a) {
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py::buffer_info info = a.request();
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if (info.ndim != 1) {
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throw std::runtime_error("expected 1-D ndarray for is_call");
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}
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if (info.itemsize != 1) {
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throw std::runtime_error("is_call: expected a boolean ndarray (dtype=bool)");
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}
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const ssize_t n = info.shape[0];
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const auto *p = static_cast<const std::uint8_t *>(info.ptr);
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std::vector<bool> out(static_cast<size_t>(n));
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for (ssize_t i = 0; i < n; ++i) {
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out[static_cast<size_t>(i)] = (p[i] != 0);
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}
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return out;
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}
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void check_same_length(size_t n, size_t k, const char *name) {
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if (n != k) {
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throw std::runtime_error(std::string("length mismatch for ") + name);
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}
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}
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} // namespace
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PYBIND11_MODULE(qengine, m) {
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m.doc() = "Binding for the Black Scholes model";
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m.def(
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"bs_price",
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[](double S, double K, double T, double r, double sigma, bool is_call) {
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return BSWrapper::bs_price_wrapper(S, K, T, r, sigma, is_call);
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},
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py::arg("S"), py::arg("K"), py::arg("T"), py::arg("r"), py::arg("sigma"), py::arg("is_call"));
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m.def(
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"bs_price",
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[](py::array_t<double> S, py::array_t<double> K, py::array_t<double> T, py::array_t<double> r,
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py::array_t<double> sigma, py::array_t<bool> is_call) {
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std::vector<double> vS = to_vector_double(S);
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std::vector<double> vK = to_vector_double(K);
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std::vector<double> vT = to_vector_double(T);
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std::vector<double> vr = to_vector_double(r);
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std::vector<double> vsig = to_vector_double(sigma);
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std::vector<bool> vC = to_vector_bool_1d(is_call);
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const size_t n = vS.size();
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check_same_length(n, vK.size(), "K");
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check_same_length(n, vT.size(), "T");
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check_same_length(n, vr.size(), "r");
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check_same_length(n, vsig.size(), "sigma");
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check_same_length(n, vC.size(), "is_call");
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return BSWrapper::batch_bs_price_wrapper(vS, vK, vT, vr, vsig, vC);
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},
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py::arg("S"), py::arg("K"), py::arg("T"), py::arg("r"), py::arg("sigma"), py::arg("is_call"));
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m.def(
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"bs_price",
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[](const std::vector<double> &S, const std::vector<double> &K, const std::vector<double> &T,
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const std::vector<double> &r, const std::vector<double> &sigma, const std::vector<bool> &is_call) {
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return BSWrapper::batch_bs_price_wrapper(S, K, T, r, sigma, is_call);
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},
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py::arg("S"), py::arg("K"), py::arg("T"), py::arg("r"), py::arg("sigma"), py::arg("is_call"));
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}
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