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/*
pybind11/eigen.h: Transparent conversion for dense and sparse Eigen matrices
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "numpy.h"
#if defined(__INTEL_COMPILER)
# pragma warning(disable: 1682) // implicit conversion of a 64-bit integral type to a smaller integral type (potential portability problem)
#elif defined(__GNUG__) || defined(__clang__)
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Wconversion"
# pragma GCC diagnostic ignored "-Wdeprecated-declarations"
#endif
#include <Eigen/Core>
#include <Eigen/SparseCore>
#if defined(__GNUG__) || defined(__clang__)
# pragma GCC diagnostic pop
#endif
#if defined(_MSC_VER)
#pragma warning(push)
#pragma warning(disable: 4127) // warning C4127: Conditional expression is constant
#endif
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
template <typename T> using is_eigen_dense = is_template_base_of<Eigen::DenseBase, T>;
template <typename T> using is_eigen_sparse = is_template_base_of<Eigen::SparseMatrixBase, T>;
template <typename T> using is_eigen_ref = is_template_base_of<Eigen::RefBase, T>;
// 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> using is_eigen_base = bool_constant<
is_template_base_of<Eigen::EigenBase, T>::value
&& !is_eigen_dense<T>::value && !is_eigen_sparse<T>::value
>;
template<typename Type>
struct type_caster<Type, enable_if_t<is_eigen_dense<Type>::value && !is_eigen_ref<Type>::value>> {
typedef typename Type::Scalar Scalar;
static constexpr bool rowMajor = Type::Flags & Eigen::RowMajorBit;
static constexpr bool isVector = Type::IsVectorAtCompileTime;
bool load(handle src, bool) {
auto buf = array_t<Scalar>::ensure(src);
if (!buf)
return false;
if (buf.ndim() == 1) {
typedef Eigen::InnerStride<> Strides;
if (!isVector &&
!(Type::RowsAtCompileTime == Eigen::Dynamic &&
Type::ColsAtCompileTime == Eigen::Dynamic))
return false;
if (Type::SizeAtCompileTime != Eigen::Dynamic &&
buf.shape(0) != (size_t) Type::SizeAtCompileTime)
return false;
Strides::Index n_elts = (Strides::Index) buf.shape(0);
Strides::Index unity = 1;
value = Eigen::Map<Type, 0, Strides>(
buf.mutable_data(),
rowMajor ? unity : n_elts,
rowMajor ? n_elts : unity,
Strides(buf.strides(0) / sizeof(Scalar))
);
} else if (buf.ndim() == 2) {
typedef Eigen::Stride<Eigen::Dynamic, Eigen::Dynamic> Strides;
if ((Type::RowsAtCompileTime != Eigen::Dynamic && buf.shape(0) != (size_t) Type::RowsAtCompileTime) ||
(Type::ColsAtCompileTime != Eigen::Dynamic && buf.shape(1) != (size_t) Type::ColsAtCompileTime))
return false;
value = Eigen::Map<Type, 0, Strides>(
buf.mutable_data(),
typename Strides::Index(buf.shape(0)),
typename Strides::Index(buf.shape(1)),
Strides(buf.strides(rowMajor ? 0 : 1) / sizeof(Scalar),
buf.strides(rowMajor ? 1 : 0) / sizeof(Scalar))
);
} else {
return false;
}
return true;
}
static handle cast(const Type &src, return_value_policy /* policy */, handle /* parent */) {
if (isVector) {
return array(
{ (size_t) src.size() }, // shape
{ sizeof(Scalar) * static_cast<size_t>(src.innerStride()) }, // strides
src.data() // data
).release();
} else {
return array(
{ (size_t) src.rows(), // shape
(size_t) src.cols() },
{ sizeof(Scalar) * static_cast<size_t>(src.rowStride()), // strides
sizeof(Scalar) * static_cast<size_t>(src.colStride()) },
src.data() // data
).release();
}
}
PYBIND11_TYPE_CASTER(Type, _("numpy.ndarray[") + npy_format_descriptor<Scalar>::name() +
_("[") + rows() + _(", ") + cols() + _("]]"));
protected:
template <typename T = Type, enable_if_t<T::RowsAtCompileTime == Eigen::Dynamic, int> = 0>
static PYBIND11_DESCR rows() { return _("m"); }
template <typename T = Type, enable_if_t<T::RowsAtCompileTime != Eigen::Dynamic, int> = 0>
static PYBIND11_DESCR rows() { return _<T::RowsAtCompileTime>(); }
template <typename T = Type, enable_if_t<T::ColsAtCompileTime == Eigen::Dynamic, int> = 0>
static PYBIND11_DESCR cols() { return _("n"); }
template <typename T = Type, enable_if_t<T::ColsAtCompileTime != Eigen::Dynamic, int> = 0>
static PYBIND11_DESCR cols() { return _<T::ColsAtCompileTime>(); }
};
// Eigen::Ref<Derived> satisfies is_eigen_dense, but isn't constructable, so it needs a special
// type_caster to handle argument copying/forwarding.
template <typename CVDerived, int Options, typename StrideType>
struct type_caster<Eigen::Ref<CVDerived, Options, StrideType>> {
protected:
using Type = Eigen::Ref<CVDerived, Options, StrideType>;
using Derived = typename std::remove_const<CVDerived>::type;
using DerivedCaster = type_caster<Derived>;
DerivedCaster derived_caster;
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; }
static handle cast(const Type &src, return_value_policy policy, handle parent) { return DerivedCaster::cast(src, policy, parent); }
static handle cast(const Type *src, return_value_policy policy, handle parent) { return DerivedCaster::cast(*src, policy, parent); }
static PYBIND11_DESCR name() { return DerivedCaster::name(); }
operator Type*() { return value.get(); }
operator Type&() { if (!value) pybind11_fail("Eigen::Ref<...> value not loaded"); return *value; }
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, enable_if_t<is_eigen_base<Type>::value && !is_eigen_ref<Type>::value>> {
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, enable_if_t<is_eigen_sparse<Type>::value>> {
typedef typename Type::Scalar Scalar;
typedef typename std::remove_reference<decltype(*std::declval<Type>().outerIndexPtr())>::type StorageIndex;
typedef typename Type::Index Index;
static constexpr bool rowMajor = Type::Flags & Eigen::RowMajorBit;
bool load(handle src, bool) {
if (!src)
return false;
auto obj = reinterpret_borrow<object>(src);
object sparse_module = module::import("scipy.sparse");
object matrix_type = sparse_module.attr(
rowMajor ? "csr_matrix" : "csc_matrix");
if (obj.get_type() != matrix_type.ptr()) {
try {
obj = matrix_type(obj);
} catch (const error_already_set &) {
return false;
}
}
auto values = array_t<Scalar>((object) obj.attr("data"));
auto innerIndices = array_t<StorageIndex>((object) obj.attr("indices"));
auto outerIndices = array_t<StorageIndex>((object) obj.attr("indptr"));
auto shape = pybind11::tuple((pybind11::object) obj.attr("shape"));
auto nnz = obj.attr("nnz").cast<Index>();
if (!values || !innerIndices || !outerIndices)
return false;
value = Eigen::MappedSparseMatrix<Scalar, Type::Flags, StorageIndex>(
shape[0].cast<Index>(), shape[1].cast<Index>(), nnz,
outerIndices.mutable_data(), innerIndices.mutable_data(), values.mutable_data());
return true;
}
static handle cast(const Type &src, return_value_policy /* policy */, handle /* parent */) {
const_cast<Type&>(src).makeCompressed();
object matrix_type = module::import("scipy.sparse").attr(
rowMajor ? "csr_matrix" : "csc_matrix");
array data((size_t) src.nonZeros(), src.valuePtr());
array outerIndices((size_t) (rowMajor ? src.rows() : src.cols()) + 1, src.outerIndexPtr());
array innerIndices((size_t) src.nonZeros(), src.innerIndexPtr());
return matrix_type(
std::make_tuple(data, innerIndices, outerIndices),
std::make_pair(src.rows(), src.cols())
).release();
}
PYBIND11_TYPE_CASTER(Type, _<(Type::Flags & Eigen::RowMajorBit) != 0>("scipy.sparse.csr_matrix[", "scipy.sparse.csc_matrix[")
+ npy_format_descriptor<Scalar>::name() + _("]"));
};
NAMESPACE_END(detail)
NAMESPACE_END(pybind11)
#if defined(_MSC_VER)
#pragma warning(pop)
#endif
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