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Eigen support for special matrix objects

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Functions returning specialized Eigen matrices like Eigen::DiagonalMatrix and
Eigen::SelfAdjointView--which inherit from EigenBase but not
DenseBase--isn't currently allowed; such classes are explicitly copyable
into a Matrix (by definition), and so we can support functions that
return them by copying the value into a Matrix then casting that
resulting dense Matrix into a numpy.ndarray.  This commit does exactly
that.
This commit is contained in:
Jason Rhinelander
2016-08-04 15:24:41 -04:00
parent 19637536ac
commit 9ffb3dda5f
5 changed files with 84 additions and 5 deletions
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35
include/pybind11/eigen.h
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@@ -61,6 +61,19 @@ public:
static constexpr bool value = decltype(test(std::declval<T>()))::value;
};
// Test for objects inheriting from EigenBase<Derived> that aren't captured by the above. This
// basically covers anything that can be assigned to a dense matrix but that don't have a typical
// matrix data layout that can be copied from their .data(). For example, DiagonalMatrix and
// SelfAdjointView fall into this category.
template <typename T> class is_eigen_base {
private:
template<typename Derived> static std::true_type test(const Eigen::EigenBase<Derived> &);
static std::false_type test(...);
public:
static constexpr bool value = !is_eigen_dense<T>::value && !is_eigen_sparse<T>::value &&
decltype(test(std::declval<T>()))::value;
};
template<typename Type>
struct type_caster<Type, typename std::enable_if<is_eigen_dense<Type>::value && !is_eigen_ref<Type>::value>::type> {
typedef typename Type::Scalar Scalar;
@@ -164,11 +177,10 @@ protected:
template<typename Type>
struct type_caster<Type, typename std::enable_if<is_eigen_dense<Type>::value && is_eigen_ref<Type>::value>::type> {
private:
protected:
using Derived = typename std::remove_const<typename is_eigen_ref<Type>::Derived>::type;
using DerivedCaster = type_caster<Derived>;
DerivedCaster derived_caster;
protected:
std::unique_ptr<Type> value;
public:
bool load(handle src, bool convert) { if (derived_caster.load(src, convert)) { value.reset(new Type(derived_caster.operator Derived&())); return true; } return false; }
@@ -182,6 +194,25 @@ public:
template <typename _T> using cast_op_type = pybind11::detail::cast_op_type<_T>;
};
// type_caster for special matrix types (e.g. DiagonalMatrix): load() is not supported, but we can
// cast them into the python domain by first copying to a regular Eigen::Matrix, then casting that.
template <typename Type>
struct type_caster<Type, typename std::enable_if<is_eigen_base<Type>::value && !is_eigen_ref<Type>::value>::type> {
protected:
using Matrix = Eigen::Matrix<typename Type::Scalar, Eigen::Dynamic, Eigen::Dynamic>;
using MatrixCaster = type_caster<Matrix>;
public:
[[noreturn]] bool load(handle, bool) { pybind11_fail("Unable to load() into specialized EigenBase object"); }
static handle cast(const Type &src, return_value_policy policy, handle parent) { return MatrixCaster::cast(Matrix(src), policy, parent); }
static handle cast(const Type *src, return_value_policy policy, handle parent) { return MatrixCaster::cast(Matrix(*src), policy, parent); }
static PYBIND11_DESCR name() { return MatrixCaster::name(); }
[[noreturn]] operator Type*() { pybind11_fail("Loading not supported for specialized EigenBase object"); }
[[noreturn]] operator Type&() { pybind11_fail("Loading not supported for specialized EigenBase object"); }
template <typename _T> using cast_op_type = pybind11::detail::cast_op_type<_T>;
};
template<typename Type>
struct type_caster<Type, typename std::enable_if<is_eigen_sparse<Type>::value>::type> {
typedef typename Type::Scalar Scalar;