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[wpimath] Upgrade to Eigen 3.3.9 (#2910)

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It fixes some compilation errors with C++20.
This commit is contained in:
Tyler Veness
2020-12-05 20:03:47 -08:00
committed by GitHub
parent 0075e4b391
commit b8c4f603db
41 changed files with 545 additions and 302 deletions
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28
wpimath/src/main/native/include/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h
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@@ -453,6 +453,24 @@ struct auto_diff_special_op<_DerType, false>
void operator+() const;
};
template<typename BinOp, typename A, typename B, typename RefType>
void make_coherent_expression(CwiseBinaryOp<BinOp,A,B> xpr, const RefType &ref)
{
make_coherent(xpr.const_cast_derived().lhs(), ref);
make_coherent(xpr.const_cast_derived().rhs(), ref);
}
template<typename UnaryOp, typename A, typename RefType>
void make_coherent_expression(const CwiseUnaryOp<UnaryOp,A> &xpr, const RefType &ref)
{
make_coherent(xpr.nestedExpression().const_cast_derived(), ref);
}
// needed for compilation only
template<typename UnaryOp, typename A, typename RefType>
void make_coherent_expression(const CwiseNullaryOp<UnaryOp,A> &, const RefType &)
{}
template<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols, typename B>
struct make_coherent_impl<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols>, B> {
typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> A;
@@ -462,6 +480,10 @@ struct make_coherent_impl<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows,
a.resize(b.size());
a.setZero();
}
else if (B::SizeAtCompileTime==Dynamic && a.size()!=0 && b.size()==0)
{
make_coherent_expression(b,a);
}
}
};
@@ -474,13 +496,17 @@ struct make_coherent_impl<A, Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRo
b.resize(a.size());
b.setZero();
}
else if (A::SizeAtCompileTime==Dynamic && b.size()!=0 && a.size()==0)
{
make_coherent_expression(a,b);
}
}
};
template<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols,
typename B_Scalar, int B_Rows, int B_Cols, int B_Options, int B_MaxRows, int B_MaxCols>
struct make_coherent_impl<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols>,
Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> > {
Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> > {
typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> A;
typedef Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> B;
static void run(A& a, B& b) {

2
wpimath/src/main/native/include/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
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@@ -412,7 +412,7 @@ template<typename Derived> struct MatrixExponentialReturnValue
inline void evalTo(ResultType& result) const
{
const typename internal::nested_eval<Derived, 10>::type tmp(m_src);
internal::matrix_exp_compute(tmp, result, internal::is_exp_known_type<typename Derived::Scalar>());
internal::matrix_exp_compute(tmp, result, internal::is_exp_known_type<typename Derived::RealScalar>());
}
Index rows() const { return m_src.rows(); }

18
wpimath/src/main/native/include/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h
View File

@@ -253,18 +253,19 @@ struct matrix_sqrt_compute
template <typename MatrixType>
struct matrix_sqrt_compute<MatrixType, 0>
{
typedef typename MatrixType::PlainObject PlainType;
template <typename ResultType>
static void run(const MatrixType &arg, ResultType &result)
{
eigen_assert(arg.rows() == arg.cols());
// Compute Schur decomposition of arg
const RealSchur<MatrixType> schurOfA(arg);
const MatrixType& T = schurOfA.matrixT();
const MatrixType& U = schurOfA.matrixU();
const RealSchur<PlainType> schurOfA(arg);
const PlainType& T = schurOfA.matrixT();
const PlainType& U = schurOfA.matrixU();
// Compute square root of T
MatrixType sqrtT = MatrixType::Zero(arg.rows(), arg.cols());
PlainType sqrtT = PlainType::Zero(arg.rows(), arg.cols());
matrix_sqrt_quasi_triangular(T, sqrtT);
// Compute square root of arg
@@ -278,18 +279,19 @@ struct matrix_sqrt_compute<MatrixType, 0>
template <typename MatrixType>
struct matrix_sqrt_compute<MatrixType, 1>
{
typedef typename MatrixType::PlainObject PlainType;
template <typename ResultType>
static void run(const MatrixType &arg, ResultType &result)
{
eigen_assert(arg.rows() == arg.cols());
// Compute Schur decomposition of arg
const ComplexSchur<MatrixType> schurOfA(arg);
const MatrixType& T = schurOfA.matrixT();
const MatrixType& U = schurOfA.matrixU();
const ComplexSchur<PlainType> schurOfA(arg);
const PlainType& T = schurOfA.matrixT();
const PlainType& U = schurOfA.matrixU();
// Compute square root of T
MatrixType sqrtT;
PlainType sqrtT;
matrix_sqrt_triangular(T, sqrtT);
// Compute square root of arg