Eigen support for special matrix objects
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.
diff --git a/docs/advanced.rst b/docs/advanced.rst
index 3ebf83e..27df2d8 100644
--- a/docs/advanced.rst
+++ b/docs/advanced.rst
@@ -1098,6 +1098,14 @@
1. Static and dynamic Eigen dense vectors and matrices to instances of
``numpy.ndarray`` (and vice versa).
+1. Returned matrix expressions such as blocks (including columns or rows) and
+ diagonals will be converted to ``numpy.ndarray`` of the expression
+ values.
+
+1. Returned matrix-like objects such as Eigen::DiagonalMatrix or
+ Eigen::SelfAdjointView will be converted to ``numpy.ndarray`` containing the
+ expressed value.
+
1. Eigen sparse vectors and matrices to instances of
``scipy.sparse.csr_matrix``/``scipy.sparse.csc_matrix`` (and vice versa).
@@ -1107,10 +1115,13 @@
.. code-block:: cpp
- /* The Python bindings of this function won't replicate
- the intended effect of modifying the function argument */
+ /* The Python bindings of these functions won't replicate
+ the intended effect of modifying the function arguments */
void scale_by_2(Eigen::Vector3f &v) {
- v *= 2;
+ v *= 2;
+ }
+ void scale_by_2(Eigen::Ref<Eigen::MatrixXd> &v) {
+ v *= 2;
}
To see why this is, refer to the section on :ref:`opaque` (although that
diff --git a/example/eigen.cpp b/example/eigen.cpp
index 9c33c55..c88bee2 100644
--- a/example/eigen.cpp
+++ b/example/eigen.cpp
@@ -66,6 +66,22 @@
return x.block(start_row, start_col, block_rows, block_cols);
});
+ // Returns a DiagonalMatrix with diagonal (1,2,3,...)
+ m.def("incr_diag", [](int k) {
+ Eigen::DiagonalMatrix<int, Eigen::Dynamic> m(k);
+ for (int i = 0; i < k; i++) m.diagonal()[i] = i+1;
+ return m;
+ });
+
+ // Returns a SelfAdjointView referencing the lower triangle of m
+ m.def("symmetric_lower", [](const Eigen::MatrixXi &m) {
+ return m.selfadjointView<Eigen::Lower>();
+ });
+ // Returns a SelfAdjointView referencing the lower triangle of m
+ m.def("symmetric_upper", [](const Eigen::MatrixXi &m) {
+ return m.selfadjointView<Eigen::Upper>();
+ });
+
m.def("fixed_r", [mat]() -> FixedMatrixR {
return FixedMatrixR(mat);
});
diff --git a/example/eigen.py b/example/eigen.py
index 04078b9..5f7ec51 100644
--- a/example/eigen.py
+++ b/example/eigen.py
@@ -14,6 +14,7 @@
from example import cholesky1, cholesky2, cholesky3, cholesky4, cholesky5, cholesky6
from example import diagonal, diagonal_1, diagonal_n
from example import block
+from example import incr_diag, symmetric_upper, symmetric_lower
try:
import numpy as np
import scipy
@@ -88,3 +89,20 @@
print("block(2,1,3,3) %s" % ("OK" if (block(ref, 2, 1, 3, 3) == ref[2:5, 1:4]).all() else "FAILED"))
print("block(1,4,4,2) %s" % ("OK" if (block(ref, 1, 4, 4, 2) == ref[1:, 4:]).all() else "FAILED"))
print("block(1,4,3,2) %s" % ("OK" if (block(ref, 1, 4, 3, 2) == ref[1:4, 4:]).all() else "FAILED"))
+
+print("incr_diag %s" % ("OK" if (incr_diag(7) == np.diag([1,2,3,4,5,6,7])).all() else "FAILED"))
+
+asymm = np.array([
+ [1, 2, 3, 4],
+ [5, 6, 7, 8],
+ [9, 10,11,12],
+ [13,14,15,16]])
+symm_lower = np.array(asymm)
+symm_upper = np.array(asymm)
+for i in range(4):
+ for j in range(i+1, 4):
+ symm_lower[i,j] = symm_lower[j,i]
+ symm_upper[j,i] = symm_upper[i,j]
+
+print("symmetric_lower %s" % ("OK" if (symmetric_lower(asymm) == symm_lower).all() else "FAILED"))
+print("symmetric_upper %s" % ("OK" if (symmetric_upper(asymm) == symm_upper).all() else "FAILED"))
diff --git a/example/eigen.ref b/example/eigen.ref
index 8ccd1f4..755012f 100644
--- a/example/eigen.ref
+++ b/example/eigen.ref
@@ -50,3 +50,6 @@
block(2,1,3,3) OK
block(1,4,4,2) OK
block(1,4,3,2) OK
+incr_diag OK
+symmetric_lower OK
+symmetric_upper OK
diff --git a/include/pybind11/eigen.h b/include/pybind11/eigen.h
index 16ccaa8..9c531fa 100644
--- a/include/pybind11/eigen.h
+++ b/include/pybind11/eigen.h
@@ -61,6 +61,19 @@
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 @@
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 @@
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;