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rAKA/src/common/aka_types_eigen_matrix_base_plugin.hh
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aka_types_eigen_matrix_base_plugin.hh
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template <bool _is_vector = IsVectorAtCompileTime,
std::enable_if_t<_is_vector> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
MatrixBase(std::initializer_list<Scalar> list)
: MatrixBase() {
Index i = 0;
for (auto val : list) {
this->operator()(i++) = val;
}
}
template <bool _is_vector = IsVectorAtCompileTime,
std::enable_if_t<not _is_vector> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
MatrixBase(std::initializer_list<std::initializer_list<Scalar>> list)
: MatrixBase() {
static_assert(std::is_trivially_copyable<Scalar>{},
"Cannot create a tensor on non trivial types");
Index m = list.size();
Index n = 0;
for (auto row : list) {
n = std::max(n, row.size());
}
if (RowsAtCompileTime != -1 and RowsAtCompileTime != m) {
AKANTU_EXCEPTION(
"The size of the matrix does not correspond to the initializer_list");
}
if (ColsAtCompileTime != -1 and ColsAtCompileTime != n) {
AKANTU_EXCEPTION(
"The size of the matrix does not correspond to the initializer_list");
}
if (RowsAtCompileTime != -1 or ColsAtCompileTime != -1) {
this->resize(m, n);
}
Index i = 0, j = 0;
for (auto & row : list) {
for (auto & val : row) {
this->operator()(i, j++) = val;
}
++i;
j = 0;
}
}
template <bool _is_vector = IsVectorAtCompileTime,
std::enable_if_t<not _is_vector> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE auto operator()(Index c) {
auto & d = this->derived();
return Map<Matrix<Scalar, RowsAtCompileTime, 1>>(
d.data() + c * d.outerStride(), d.outerStride());
}
template <bool _is_vector = IsVectorAtCompileTime,
std::enable_if_t<not _is_vector> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE auto operator()(Index c) const {
const auto & d = this->derived();
return d.col(c);
}
template <bool _is_vector = IsVectorAtCompileTime,
std::enable_if_t<_is_vector> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) operator()(Index c) {
return Base::operator()(c);
}
template <bool _is_vector = IsVectorAtCompileTime,
std::enable_if_t<_is_vector> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) operator()(Index c) const {
return Base::operator()(c);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) operator()(Index i,
Index j) {
return Base::operator()(i, j);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) operator()(Index i,
Index j) const {
return Base::operator()(i, j);
}
template <
typename ED = Derived,
typename T = std::remove_reference_t<decltype(*std::declval<ED>().data())>,
std::enable_if_t<not std::is_const<T>::value and
ED::IsVectorAtCompileTime> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) begin();
template <
typename ED = Derived,
typename T = std::remove_reference_t<decltype(*std::declval<ED>().data())>,
std::enable_if_t<not std::is_const<T>::value and
ED::IsVectorAtCompileTime> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) end();
template <typename ED = Derived,
std::enable_if_t<ED::IsVectorAtCompileTime> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) begin() const;
template <typename ED = Derived,
std::enable_if_t<ED::IsVectorAtCompileTime> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) end() const;
template <
typename ED = Derived,
typename T = std::remove_reference_t<decltype(*std::declval<ED>().data())>,
std::enable_if_t<not std::is_const<T>::value and
not ED::IsVectorAtCompileTime> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) begin();
template <
typename ED = Derived,
typename T = std::remove_reference_t<decltype(*std::declval<ED>().data())>,
std::enable_if_t<not std::is_const<T>::value and
not ED::IsVectorAtCompileTime> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) end();
template <typename ED = Derived,
std::enable_if_t<not ED::IsVectorAtCompileTime> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) begin() const;
template <typename ED = Derived,
std::enable_if_t<not ED::IsVectorAtCompileTime> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE decltype(auto) end() const;
// clang-format off
[[deprecated("use data instead to be stl compatible")]]
Scalar * storage() {
return this->data();
}
[[deprecated("use data instead to be stl compatible")]]
const Scalar * storage() const {
return this->data();
}
// clang-format on
template <bool _is_vector = IsVectorAtCompileTime,
std::enable_if_t<_is_vector> * = nullptr>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE auto size() const {
return this->cols();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE auto size(Index i) const {
AKANTU_DEBUG_ASSERT(i < 1, "This tensor has only " << 1 << " dimensions, not "
<< (i + 1));
return this->cols();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void set(const Scalar & t) {
this->fill(t);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void clear() { this->fill(Scalar()); };
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE auto
distance(const MatrixBase<OtherDerived> & other) const {
return (*this - other).norm();
}
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar
doubleDot(const MatrixBase<OtherDerived> & other) const {
Scalar sum = 0;
eigen_assert(rows() == cols() and rows() == other.rows() and
cols() == other.cols());
for (Index i = 0; i < rows(); ++i) {
for (Index j = 0; j < cols(); ++j) {
sum += coeff(i, j) * other.coeff(i, j);
}
}
}
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void
eig(MatrixBase<OtherDerived> & other);
template <typename D1, typename D2>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void eig(MatrixBase<D1> & values,
MatrixBase<D2> & vectors);
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void
eigh(MatrixBase<OtherDerived> & other);
template <typename D1, typename D2>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void eigh(MatrixBase<D1> & values,
MatrixBase<D2> & vectors);
/*
public:
*/
// template <bool ip, typename R = T,
// std::enable_if_t<std::is_floating_point<R>::value, int> = 0>
// inline bool equal(const VectorBase<R, ip> & v,
// R tolerance = Math::getTolerance()) const {
// T * a = this->data();
// T * b = v.data();
// idx_t i = 0;
// while (i < this->_size && (std::abs(*(a++) - *(b++)) < tolerance))
// ++i;
// return i == this->_size;
// }
// template <bool ip, typename R = T,
// std::enable_if_t<std::is_floating_point<R>::value, int> = 0>
// inline short compare(const TensorBase<R, 1, ip> & v,
// Real tolerance = Math::getTolerance()) const {
// T * a = this->data();
// T * b = v.data();
// for (UInt i(0); i < this->_size; ++i, ++a, ++b) {
// if (std::abs(*a - *b) > tolerance)
// return (((*a - *b) > tolerance) ? 1 : -1);
// }
// return 0;
// }
// template <bool ip, typename R = T,
// std::enable_if_t<not std::is_floating_point<R>::value, int> = 0>
// inline bool equal(const TensorBase<R, 1, ip> & v) const {
// return std::equal(this->values, this->values + this->_size, v.data());
// }
// template <bool ip, typename R = T,
// std::enable_if_t<not std::is_floating_point<R>::value, int> = 0>
// inline short compare(const TensorBase<R, 1, ip> & v) const {
// T * a = this->data();
// T * b = v.data();
// for (idx_t i(0); i < this->_size; ++i, ++a, ++b) {
// if (*a > *b)
// return 1;
// else if (*a < *b)
// return -1;
// }
// return 0;
// }
template <typename OtherDerived>
inline bool operator<=(const MatrixBase<OtherDerived> & v) const {
return this->isMuchSmallerThan(v);
}
template <typename OtherDerived>
inline bool operator>=(const MatrixBase<OtherDerived> & v) const {
return v.isMuchSmallerThan(*this);
}
template <typename OtherDerived>
inline bool operator<(const MatrixBase<OtherDerived> & v) const {
return (*this <= v) and (*this != v);
}
template <typename OtherDerived>
inline bool operator>(const MatrixBase<OtherDerived> & v) const {
return (*this >= v) and (*this != v);
}
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