Move more methods into their own namespace

include/teqp/derivs.hpp

@@ -62,48 +62,45 @@ typename ContainerType::value_type derivrhoi(const FuncType& f, TType T, const C
     return f(T, rhocom).imag() / h;
 }
 
+enum class ADBackends { autodiff, multicomplex, complex_step };
 
+template<typename Model, typename Scalar = double, typename VectorType = Eigen::ArrayXd>
+struct TDXDerivatives {
 
-
-
-template <typename Model, typename TType, typename RhoType, typename ContainerType>
-typename ContainerType::value_type get_Ar10(const Model& model, const TType T, const RhoType &rho, const ContainerType& molefrac) {
-    double h = 1e-100;
-    return -T*model.alphar(std::complex<TType>(T, h), rho, molefrac).imag()/h; // Complex step derivative
-}
-
-enum class ADBackends { autodiff, multicomplex, complex_step } ;
-
-template <ADBackends be = ADBackends::autodiff, typename Model, typename TType, typename RhoType, typename MoleFracType>
-auto get_Ar01(const Model& model, const TType &T, const RhoType &rho, const MoleFracType& molefrac) {
-    if constexpr(be == ADBackends::complex_step){
+    static auto get_Ar10(const Model& model, const Scalar &T, const Scalar &rho, const VectorType& molefrac) {
         double h = 1e-100;
-        auto der = model.alphar(T, std::complex<double>(rho, h), molefrac).imag() / h;
-        return der*rho;
+        return -T*model.alphar(std::complex<Scalar>(T, h), rho, molefrac).imag()/h; // Complex step derivative
     }
-    else if constexpr(be == ADBackends::multicomplex){
-        using fcn_t = std::function<mcx::MultiComplex<double>(const mcx::MultiComplex<double>&)>;
-        bool and_val = true;
-        fcn_t f = [&model, &T, &molefrac](const auto& rho_) { return model.alphar(T, rho_, molefrac); };
-        auto ders = diff_mcx1(f, rho, 1, and_val);
-        return ders[1] * rho;
+
+    template<ADBackends be = ADBackends::autodiff>
+    static auto get_Ar01(const Model& model, const Scalar&T, const Scalar &rho, const VectorType& molefrac) {
+        if constexpr(be == ADBackends::complex_step){
+            double h = 1e-100;
+            auto der = model.alphar(T, std::complex<Scalar>(rho, h), molefrac).imag() / h;
+            return der*rho;
+        }
+        else if constexpr(be == ADBackends::multicomplex){
+            using fcn_t = std::function<mcx::MultiComplex<Scalar>(const mcx::MultiComplex<Scalar>&)>;
+            bool and_val = true;
+            fcn_t f = [&model, &T, &molefrac](const auto& rho_) { return model.alphar(T, rho_, molefrac); };
+            auto ders = diff_mcx1(f, rho, 1, and_val);
+            return ders[1] * rho;
+        }
+        else if constexpr(be == ADBackends::autodiff){
+            autodiff::dual rhodual = rho;
+            auto f = [&model, &T, &molefrac](const auto& rho_) { return eval(model.alphar(T, rho_, molefrac)); };
+            auto der = derivative(f, wrt(rhodual), at(rhodual));
+            return der * rho;
+        }
     }
-    else if constexpr(be == ADBackends::autodiff){
-        autodiff::dual rhodual = rho;
+
+    static auto get_Ar02(const Model& model, const Scalar& T, const Scalar& rho, const VectorType& molefrac) {
+        autodiff::dual2nd rhodual = rho;
         auto f = [&model, &T, &molefrac](const auto& rho_) { return eval(model.alphar(T, rho_, molefrac)); };
-        auto der = derivative(f, wrt(rhodual), at(rhodual));
-        return der * rho;
+        auto ders = derivatives(f, wrt(rhodual), at(rhodual));
+        return ders[2]*rho*rho;
     }
-}
-
-template <typename Model, typename TType, typename RhoType, typename MoleFracType>
-auto get_Ar02(const Model& model, const TType& T, const RhoType& rho, const MoleFracType& molefrac) {
-    autodiff::dual2nd rhodual = rho;
-    auto f = [&model, &T, &molefrac](const auto& rho_) { return eval(model.alphar(T, rho_, molefrac)); };
-    auto ders = derivatives(f, wrt(rhodual), at(rhodual));
-    return ders[2]*rho*rho;
-}
-
+};
 
 template<typename Model, typename Scalar = double, typename VectorType = Eigen::ArrayXd>
 struct VirialDerivatives {

interface/pybind11_wrapper.cpp

@@ -9,6 +9,15 @@
 
 namespace py = pybind11;
 
+template<typename Model>
+void add_TDx_derivatives(py::module& m) {
+    using id = TDXDerivatives<Model, double, Eigen::Array<double, Eigen::Dynamic, 1> >;
+    //m.def("get_Ar00", &id::get_Ar00, py::arg("model"), py::arg("T"), py::arg("rho"), py::arg("molefrac"));
+    m.def("get_Ar10", &id::get_Ar10, py::arg("model"), py::arg("T"), py::arg("rho"), py::arg("molefrac"));
+    m.def("get_Ar01", &id::get_Ar01<ADBackends::autodiff>, py::arg("model"), py::arg("T"), py::arg("rho"), py::arg("molefrac"));
+    m.def("get_Ar02", &id::get_Ar02, py::arg("model"), py::arg("T"), py::arg("rho"), py::arg("molefrac"));
+}
+
 template<typename Model>
 void add_virials(py::module& m) {
     using vd = VirialDerivatives<Model>;
@@ -30,6 +39,7 @@ void add_derivatives(py::module &m) {
     m.def("build_Psir_gradient_autodiff", &id::build_Psir_gradient_autodiff, py::arg("model"), py::arg("T"), py::arg("rho"));
 
     add_virials<Model>(m);
+    add_TDx_derivatives<Model>(m);
 }