Restructure C++ core into cpp module and package bindings.

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

cpp/ImpliedVolatility/Pybind.cpp

@@ -0,0 +1,93 @@
+/**
+ * @file Pybind.cpp
+ * @brief pybind11 module @c qengine exposing @ref BSWrapper::bs_price_wrapper overloads.
+ */
+
+#include <pybind11/numpy.h>
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>
+
+#include <cstdint>
+#include <stdexcept>
+#include <string>
+#include <vector>
+
+#include "BSWrapper.hpp"
+
+namespace py = pybind11;
+
+namespace {
+
+std::vector<double> to_vector_double(const py::array_t<double> &a) {
+    py::buffer_info info = a.request();
+    if (info.ndim != 1) {
+        throw std::runtime_error("expected 1-D ndarray for S, K, T, r, sigma");
+    }
+    const auto *p = static_cast<const double *>(info.ptr);
+    const ssize_t n = info.shape[0];
+    return std::vector<double>(p, p + n);
+}
+
+std::vector<bool> to_vector_bool_1d(const py::array_t<bool> &a) {
+    py::buffer_info info = a.request();
+    if (info.ndim != 1) {
+        throw std::runtime_error("expected 1-D ndarray for is_call");
+    }
+    if (info.itemsize != 1) {
+        throw std::runtime_error("is_call: expected a boolean ndarray (dtype=bool)");
+    }
+    const ssize_t n = info.shape[0];
+    const auto *p = static_cast<const std::uint8_t *>(info.ptr);
+    std::vector<bool> out(static_cast<size_t>(n));
+    for (ssize_t i = 0; i < n; ++i) {
+        out[static_cast<size_t>(i)] = (p[i] != 0);
+    }
+    return out;
+}
+
+void check_same_length(size_t n, size_t k, const char *name) {
+    if (n != k) {
+        throw std::runtime_error(std::string("length mismatch for ") + name);
+    }
+}
+
+} // namespace
+
+PYBIND11_MODULE(qengine, m) {
+    m.doc() = "Binding for the Black Scholes model";
+
+    m.def(
+        "bs_price",
+        [](double S, double K, double T, double r, double sigma, bool is_call) {
+            return BSWrapper::bs_price_wrapper(S, K, T, r, sigma, is_call);
+        },
+        py::arg("S"), py::arg("K"), py::arg("T"), py::arg("r"), py::arg("sigma"), py::arg("is_call"));
+
+    m.def(
+        "bs_price",
+        [](py::array_t<double> S, py::array_t<double> K, py::array_t<double> T, py::array_t<double> r,
+            py::array_t<double> sigma, py::array_t<bool> is_call) {
+            std::vector<double> vS = to_vector_double(S);
+            std::vector<double> vK = to_vector_double(K);
+            std::vector<double> vT = to_vector_double(T);
+            std::vector<double> vr = to_vector_double(r);
+            std::vector<double> vsig = to_vector_double(sigma);
+            std::vector<bool> vC = to_vector_bool_1d(is_call);
+            const size_t n = vS.size();
+            check_same_length(n, vK.size(), "K");
+            check_same_length(n, vT.size(), "T");
+            check_same_length(n, vr.size(), "r");
+            check_same_length(n, vsig.size(), "sigma");
+            check_same_length(n, vC.size(), "is_call");
+            return BSWrapper::batch_bs_price_wrapper(vS, vK, vT, vr, vsig, vC);
+        },
+        py::arg("S"), py::arg("K"), py::arg("T"), py::arg("r"), py::arg("sigma"), py::arg("is_call"));
+
+    m.def(
+        "bs_price",
+        [](const std::vector<double> &S, const std::vector<double> &K, const std::vector<double> &T,
+            const std::vector<double> &r, const std::vector<double> &sigma, const std::vector<bool> &is_call) {
+            return BSWrapper::batch_bs_price_wrapper(S, K, T, r, sigma, is_call);
+        },
+        py::arg("S"), py::arg("K"), py::arg("T"), py::arg("r"), py::arg("sigma"), py::arg("is_call"));
+}