Set active variables

Author: wgledbetter

include/boost/math/differentiation/autodiff_eigen.hpp

@@ -49,21 +49,23 @@ BOOST_AUTODIFF_EIGEN_SCALAR_TRAITS(unsigned int);
 BOOST_AUTODIFF_EIGEN_SCALAR_TRAITS(long);
 BOOST_AUTODIFF_EIGEN_SCALAR_TRAITS(unsigned long);
 
-template <typename RealType, size_t Order, typename RealType2, size_t Order2,
-          typename BinaryOp>
-struct ScalarBinaryOpTraits<
-    boost::math::differentiation::autodiff_v1::detail::template fvar<RealType,
-                                                                     Order>,
-    boost::math::differentiation::autodiff_v1::detail::template fvar<RealType2,
-                                                                     Order2>,
-    BinaryOp> {
-  typedef ScalarBinaryOpTraits<RealType, RealType2, BinaryOp>::ReturnType
-      RealReturn;
-  const size_t ReturnOrder = (Order > Order2) ? Order : Order2;
-  typedef boost::math::differentiation::autodiff_v1::detail::template fvar<
-      RealReturn, ReturnOrder>
-      ReturnType;
-};
+// template <typename RealType, size_t Order, typename RealType2, size_t Order2,
+//           typename BinaryOp>
+// struct ScalarBinaryOpTraits<
+//     boost::math::differentiation::autodiff_v1::detail::template
+//     fvar<RealType,
+//                                                                      Order>,
+//     boost::math::differentiation::autodiff_v1::detail::template
+//     fvar<RealType2,
+//                                                                      Order2>,
+//     BinaryOp> {
+//   typedef ScalarBinaryOpTraits<RealType, RealType2, BinaryOp>::ReturnType
+//       RealReturn;
+//   const size_t ReturnOrder = (Order > Order2) ? Order : Order2;
+//   typedef boost::math::differentiation::autodiff_v1::detail::template fvar<
+//       RealReturn, ReturnOrder>
+//       ReturnType;
+// };
 }  // namespace Eigen
 
 #endif  // BOOST_MATH_DIFFERENTIATION_AUTODIFF_EIGEN_HPP

test/test_autodiff_9.cpp

@@ -46,10 +46,10 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_general, T, all_float_types) {
 
   typedef typename fvar<T, n> fTn;
   Eigen::Matrix<fTn, dim, 1> x;
-  x[0] = -1;
-  x[1] = 0;
-  x[2] = 1;
-  x[3] = 5;
+  x[0] = make_fvar<T, n>(-1);
+  x[1] = make_fvar<T, n>(0);
+  x[2] = make_fvar<T, n>(1);
+  x[3] = make_fvar<T, n>(5);
 
   Eigen::Matrix<fTn, dim, 1> y1, y2, y3, y4, y5;
   y1 = sin(x);
@@ -132,7 +132,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_scalar, T, all_float_types) {
   constexpr size_t n = 4;
 
   typedef typename fvar<T, n> fTn;
-  fTn x = 4;
+  fTn x = make_fvar<T, n>(4);
   Eigen::Matrix<fTn, dim, 1> X;
   Eigen::Matrix<fTn, dim, 1> Z;
   Eigen::Matrix<fTn, dim, dim> I = Eigen::Matrix<fTn, dim, dim>::Identity();
@@ -171,7 +171,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_vector, T, all_float_types) {
   constexpr size_t n = 4;
 
   typedef typename fvar<T, n> fTn;
-  fTn x = 5;
+  fTn x = make_fvar<T, n>(5);
   T xD0 = x.derivative(0);
   Eigen::Matrix<fTn, dim, 1> X;
   X[0] = 1;
@@ -231,7 +231,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_determinant, T, all_float_types) {
   constexpr size_t n = 1;
 
   typedef typename fvar<T, n> fTn;
-  fTn x = 3;
+  fTn x = make_fvar<T, n>(3);
   T xD0 = x.derivative(0);
   Eigen::Matrix<fTn, dim, dim> M = 10 * Eigen::Matrix<fTn, dim, dim>::Random();
   M(0, 3) = x;