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debug eigen tests
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match parentheses


Set active variables


still debugging


using


no typename


catch all typename
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@wgledbetter
wgledbetter committed Sep 1, 2020
1 parent 441024f commit 5c5fcc4
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Showing 2 changed files with 93 additions and 53 deletions.
76 changes: 44 additions & 32 deletions include/boost/math/differentiation/autodiff_eigen.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -20,40 +20,52 @@ struct NumTraits<boost::math::differentiation::autodiff_v1::detail::
};
};

template <typename RealType, size_t Order, typename BinaryOp, typename A>
struct ScalarBinaryOpTraits<boost::math::differentiation::autodiff_v1::detail::
template fvar<RealType, Order>,
A, BinaryOp> {
typedef boost::math::differentiation::autodiff_v1::detail::template fvar<
RealType, Order>
ReturnType;
};
// #define BOOST_AUTODIFF_EIGEN_SCALAR_TRAITS(A) \
// template <class Scalar, size_t Order, typename BinaryOp> \
// struct ScalarBinaryOpTraits<boost::math::differentiation::autodiff_v1:: \
// detail::template fvar<Scalar, Order>, \
// A, BinaryOp> { \
// typedef boost::math::differentiation::autodiff_v1::detail::template fvar< \
// Scalar, Order> \
// ReturnType; \
// }; \
// template <class Scalar, size_t Order, typename BinaryOp> \
// struct ScalarBinaryOpTraits<A, \
// boost::math::differentiation::autodiff_v1:: \
// detail::template fvar<Scalar, Order>, \
// BinaryOp> { \
// typedef boost::math::differentiation::autodiff_v1::detail::template fvar< \
// Scalar, Order> \
// ReturnType; \
// };

template <typename RealType, size_t Order, typename BinaryOp, typename A>
struct ScalarBinaryOpTraits<A,
boost::math::differentiation::autodiff_v1::detail::
template fvar<RealType, Order>,
BinaryOp> {
typedef boost::math::differentiation::autodiff_v1::detail::template fvar<
RealType, Order>
ReturnType;
};
// BOOST_AUTODIFF_EIGEN_SCALAR_TRAITS(float);
// BOOST_AUTODIFF_EIGEN_SCALAR_TRAITS(double);
// BOOST_AUTODIFF_EIGEN_SCALAR_TRAITS(long double);
// BOOST_AUTODIFF_EIGEN_SCALAR_TRAITS(short);
// BOOST_AUTODIFF_EIGEN_SCALAR_TRAITS(unsigned short);
// BOOST_AUTODIFF_EIGEN_SCALAR_TRAITS(int);
// 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
70 changes: 49 additions & 21 deletions test/test_autodiff_9.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -5,11 +5,13 @@

BOOST_AUTO_TEST_SUITE(test_autodiff_9)

using boost::math::differentiation::autodiff_v1::detail::fvar;

BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_init, T, all_float_types) {
constexpr int size = 5;

constexpr std::size_t n = 5;
typedef typename fvar<T, n> fTn;
typedef fvar<T, n> fTn;
Eigen::Matrix<fTn, size, 1> x;
x[0] = fTn(1.5);
x[1] = make_fvar<T, n - 1>(2.5);
Expand All @@ -18,7 +20,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_init, T, all_float_types) {
x[4] = 5.5;

constexpr std::size_t m = 2;
typedef typename fvar<T, n> fTm;
typedef fvar<T, n> fTm;
Eigen::Matrix<fTm, size, 1> y;
y = x.template cast<fTn>();
BOOST_CHECK_EQUAL(x[0].derivative(0), y[0].derivative(0));
Expand All @@ -28,7 +30,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_init, T, all_float_types) {
BOOST_CHECK_EQUAL(x[4].derivative(0), y[4].derivative(0));

constexpr std::size_t p = 3;
typedef typename fvar<T, p> fTp;
typedef fvar<T, p> fTp;
Eigen::Matrix<fTp, 1, size> z =
Eigen::Matrix<fTn, size, 1>::Random().transpose().template cast<fTp>();
}
Expand All @@ -44,12 +46,12 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_general, T, all_float_types) {
constexpr std::size_t n = 2;
constexpr double p = 3.456;

typedef typename fvar<T, n> fTn;
typedef 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);
Expand Down Expand Up @@ -119,20 +121,20 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_general, T, all_float_types) {
(p - 1) * p * pow(x[3].derivative(0), p - 2));

// Check log
BOOST_CHECK_EQUAL(y5[2].derivative(0), log(x[0].derivative(0));
BOOST_CHECK_EQUAL(y5[3].derivative(0), log(x[3].derivative(0));
BOOST_CHECK_EQUAL(y5[2].derivative(1), 1/x[2].derivative(0));
BOOST_CHECK_EQUAL(y5[3].derivative(1), 1/x[3].derivative(0));
BOOST_CHECK_EQUAL(y5[2].derivative(2), -1/pow(x[2].derivative(0), 2));
BOOST_CHECK_EQUAL(y5[3].derivative(2), -1/pow(x[3].derivative(0), 2));
BOOST_CHECK_EQUAL(y5[2].derivative(0), log(x[0].derivative(0)));
BOOST_CHECK_EQUAL(y5[3].derivative(0), log(x[3].derivative(0)));
BOOST_CHECK_EQUAL(y5[2].derivative(1), 1 / x[2].derivative(0));
BOOST_CHECK_EQUAL(y5[3].derivative(1), 1 / x[3].derivative(0));
BOOST_CHECK_EQUAL(y5[2].derivative(2), -1 / pow(x[2].derivative(0), 2));
BOOST_CHECK_EQUAL(y5[3].derivative(2), -1 / pow(x[3].derivative(0), 2));
}

BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_scalar, T, all_float_types) {
constexpr int dim = 4;
constexpr size_t n = 4;

typedef typename fvar<T, n> fTn;
fTn x = 4;
typedef fvar<T, n> fTn;
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();
Expand Down Expand Up @@ -170,8 +172,8 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_vector, T, all_float_types) {
constexpr int dim = 3;
constexpr size_t n = 4;

typedef typename fvar<T, n> fTn;
fTn x = 5;
typedef fvar<T, n> fTn;
fTn x = make_fvar<T, n>(5);
T xD0 = x.derivative(0);
Eigen::Matrix<fTn, dim, 1> X;
X[0] = 1;
Expand Down Expand Up @@ -224,6 +226,32 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_vector, T, all_float_types) {
xD0 * sin(xD0) - 4 * cos(xD0));
}

// BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_determinant, T, all_float_types) {
// constexpr int dim = 4;
// }
BOOST_AUTO_TEST_CASE_TEMPLATE(eigen_determinant, T, all_float_types) {
using std::cos;
using std::sin;
constexpr int dim = 4;
constexpr size_t n = 1;

typedef fvar<T, n> fTn;
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;
M(1, 0) = 3 * x;
M(1, 2) = 1 / x;
M(2, 2) = x * x;
M(3, 1) = sin(x);
fTn y = M.determinant();

Eigen::Matrix<T, dim, dim> dMdx = Eigen::Matrix<T, dim, dim>::Zero();
dMdx(0, 3) = 1;
dMdx(1, 0) = 3;
dMdx(1, 2) = -1 / (xD0 * xD0);
dMdx(2, 2) = 2 * xD0;
dMdx(3, 1) = cos(xD0);

T ans = y.derivative(0) * (M.inverse() * dMdx).trace();
BOOST_CHECK_EQUAL(y.derivative(1), ans);
}

BOOST_AUTO_TEST_SUITE_END()

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