xarray_adaptor¶

Defined in xtensor/xarray.hpp

template<class EC, layout_type L, class SC, class Tag> class xarray_adaptor : public xt::xstrided_container<xarray_adaptor<EC, L, SC, Tag>>, public xt::xcontainer_semantic<xarray_adaptor<EC, L, SC, Tag>>, public extension::xarray_adaptor_base_t<EC, L, SC, Tag>¶

Dense multidimensional container adaptor with tensor semantic.

The xarray_adaptor class implements a dense multidimensional container adaptor with tensor semantic. It is used to provide a multidimensional container semantic and a tensor semantic to stl-like containers.

adapt¶

Defined in xtensor/xadapt.hpp

template<layout_type L = ::xt::layout_type::row_major, class C, class SC> inline auto xt::adapt(C &&container, const SC &shape, layout_type l = L)¶

Constructs:

an xarray_adaptor if SC is not an array type
an xtensor_adaptor if SC is an array type

from the given stl-like container or pointer, with the specified shape and layout. If the adaptor is built from a pointer, it does not take its ownership.

Parameters

container – the container or pointer to adapt
shape – the shape of the adaptor
l – the layout_type of the adaptor

template<class C, class SC, class SS> inline auto xt::adapt(C &&container, SC &&shape, SS &&strides)¶

Constructs:

an xarray_adaptor if SC is not an array type
an xtensor_adaptor if SC is an array type

from the given stl-like container with the specified shape and strides.

Parameters

container – the container to adapt
shape – the shape of the adaptor
strides – the strides of the adaptor

template<layout_type L = ::xt::layout_type::row_major, class P, class O, class SC, class A = detail::default_allocator_for_ptr_t<P>> inline auto xt::adapt(P &&pointer, typename A::size_type size, O ownership, const SC &shape, layout_type l = L, const A &alloc = A())¶

Constructs:

an xarray_adaptor if SC is not an array type
an xtensor_adaptor if SC is an array type

of the given dynamically allocated C array, with the specified shape and layout.

Parameters

pointer – the pointer to the beginning of the dynamic array
size – the size of the dynamic array
ownership – indicates whether the adaptor takes ownership of the array. Possible values are no_ownership() or acquire_ownership()
shape – the shape of the adaptor
l – the layout_type of the adaptor
alloc – the allocator used for allocating / deallocating the dynamic array

template<class P, class O, class SC, class SS, class A = detail::default_allocator_for_ptr_t<P>> inline auto xt::adapt(P &&pointer, typename A::size_type size, O ownership, SC &&shape, SS &&strides, const A &alloc = A())¶

Constructs:

an xarray_adaptor if SC is not an array type
an xtensor_adaptor if SC is an array type

of the given dynamically allocated C array, with the specified shape and strides.

Parameters

pointer – the pointer to the beginning of the dynamic array
size – the size of the dynamic array
ownership – indicates whether the adaptor takes ownership of the array. Possible values are no_ownership() or acquire_ownership()
shape – the shape of the adaptor
strides – the strides of the adaptor
alloc – the allocator used for allocating / deallocating the dynamic array

template<layout_type L = ::xt::layout_type::row_major, class T, std::size_t N, class SC> inline auto xt::adapt(T (&c_array)[N], const SC &shape, layout_type l = L)¶

Contructs:

an xarray_adaptor if SC is not an array type
an xtensor_adaptor if SC is an array type

of the given C array allocated on the stack, with the specified shape and layout.

Parameters

c_array – the C array allocated on the stack
shape – the shape of the adaptor
l – the layout_type of the adaptor

template<class T, std::size_t N, class SC, class SS> inline auto xt::adapt(T (&c_array)[N], SC &&shape, SS &&strides)¶

Contructs:

an xarray_adaptor if SC is not an array type
an xtensor_adaptor if SC is an array type

of the given C array allocated on the stack, with the specified shape and strides.

Parameters

c_array – the C array allocated on the stack
shape – the shape of the adaptor
strides – the strides of the adaptor

template<layout_type L = ::xt::layout_type::row_major, class C, std::size_t... X> inline auto xt::adapt(C &&pointer, const fixed_shape<X...>&)¶

Constructs an non-owning xtensor_fixed_adaptor from a pointer with the specified shape and layout.

Parameters

pointer – the pointer to adapt
shape – the shape of the xtensor_fixed_adaptor

template<layout_type L = ::xt::layout_type::row_major, class C> inline xtensor_adaptor<C, 1, L> xt::adapt(C &&container, layout_type l = L)¶

Constructs a 1-D xtensor_adaptor of the given stl-like container, with the specified layout_type.

Parameters

container – the container to adapt
l – the layout_type of the xtensor_adaptor

template<layout_type L = ::xt::layout_type::row_major, class P, class O, class A = detail::default_allocator_for_ptr_t<P>> inline xtensor_adaptor<xbuffer_adaptor<xtl::closure_type_t<P>, O, A>, 1, L> xt::adapt(P &&pointer, typename A::size_type size, O ownership, layout_type l = L, const A &alloc = A())¶

Constructs a 1-D xtensor_adaptor of the given dynamically allocated C array, with the specified layout.

Parameters

pointer – the pointer to the beginning of the dynamic array
size – the size of the dynamic array
ownership – indicates whether the adaptor takes ownership of the array. Possible values are no_ownership() or acquire_ownership()
l – the layout_type of the xtensor_adaptor
alloc – the allocator used for allocating / deallocating the dynamic array

template<layout_type L = ::xt::layout_type::row_major, class P, class SC, xtl::check_concept<detail::not_an_array<std::decay_t<SC>>> = 0> auto xt::adapt_smart_ptr(P &&smart_ptr, const SC &shape, layout_type l = L)¶

Adapt a smart pointer to a typed memory block (unique_ptr or shared_ptr)

#include <xtensor/xadapt.hpp>
#include <xtensor/xio.hpp>

std::shared_ptr<double> sptr(new double[8], std::default_delete<double[]>());
sptr.get()[2] = 321.;
std::vector<size_t> shape = {4, 2};
auto xptr = adapt_smart_ptr(sptr, shape);
xptr(1, 3) = 123.;
std::cout << xptr;

Parameters

smart_ptr – a smart pointer to a memory block of T[]
shape – The desired shape
l – The desired memory layout

Returns

xarray_adaptor for memory

template<layout_type L = ::xt::layout_type::row_major, class P, class SC, class D, xtl::check_concept<detail::not_an_array<std::decay_t<SC>>, detail::not_a_layout<std::decay_t<D>>> = 0> auto xt::adapt_smart_ptr(P &&data_ptr, const SC &shape, D &&smart_ptr, layout_type l = L)¶

Adapt a smart pointer (shared_ptr or unique_ptr)

This function allows to automatically adapt a shared or unique pointer to a given shape and operate naturally on it. Memory will be automatically handled by the smart pointer implementation.

#include <xtensor/xadapt.hpp>
#include <xtensor/xio.hpp>

struct Buffer {
    Buffer(std::vector<double>& buf) : m_buf(buf) {}
    ~Buffer() { std::cout << "deleted" << std::endl; }
    std::vector<double> m_buf;
};

auto data = std::vector<double>{1,2,3,4,5,6,7,8};
auto shared_buf = std::make_shared<Buffer>(data);
auto unique_buf = std::make_unique<Buffer>(data);

std::cout << shared_buf.use_count() << std::endl;
{
    std::vector<size_t> shape = {2, 4};
    auto obj = adapt_smart_ptr(shared_buf.get()->m_buf.data(),
                               shape, shared_buf);
    // Use count increased to 2
    std::cout << shared_buf.use_count() << std::endl;
    std::cout << obj << std::endl;
}
// Use count reset to 1
std::cout << shared_buf.use_count() << std::endl;

{
    std::vector<size_t> shape = {2, 4};
    auto obj = adapt_smart_ptr(unique_buf.get()->m_buf.data(),
                               shape, std::move(unique_buf));
    std::cout << obj << std::endl;
}

Parameters

data_ptr – A pointer to a typed data block (e.g. double*)
shape – The desired shape
smart_ptr – A smart pointer to move or copy, in order to manage memory
l – The desired memory layout

Returns

xarray_adaptor on the memory

template<layout_type L = ::xt::layout_type::row_major, class P, class I, std::size_t N> auto xt::adapt_smart_ptr(P &&smart_ptr, const I (&shape)[N], layout_type l = L)¶

Adapt a smart pointer to a typed memory block (unique_ptr or shared_ptr)

#include <xtensor/xadapt.hpp>
#include <xtensor/xio.hpp>

std::shared_ptr<double> sptr(new double[8], std::default_delete<double[]>());
sptr.get()[2] = 321.;
auto xptr = adapt_smart_ptr(sptr, {4, 2});
xptr(1, 3) = 123.;
std::cout << xptr;

Parameters

smart_ptr – a smart pointer to a memory block of T[]
shape – The desired shape
l – The desired memory layout

Returns

xtensor_adaptor for memory

template<layout_type L = ::xt::layout_type::row_major, class P, class I, std::size_t N, class D, xtl::check_concept<detail::not_a_layout<std::decay_t<D>>> = 0> auto xt::adapt_smart_ptr(P &&data_ptr, const I (&shape)[N], D &&smart_ptr, layout_type l = L)¶

Adapt a smart pointer (shared_ptr or unique_ptr)

This function allows to automatically adapt a shared or unique pointer to a given shape and operate naturally on it. Memory will be automatically handled by the smart pointer implementation.

#include <xtensor/xadapt.hpp>
#include <xtensor/xio.hpp>

struct Buffer {
    Buffer(std::vector<double>& buf) : m_buf(buf) {}
    ~Buffer() { std::cout << "deleted" << std::endl; }
    std::vector<double> m_buf;
};

auto data = std::vector<double>{1,2,3,4,5,6,7,8};
auto shared_buf = std::make_shared<Buffer>(data);
auto unique_buf = std::make_unique<Buffer>(data);

std::cout << shared_buf.use_count() << std::endl;
{
    auto obj = adapt_smart_ptr(shared_buf.get()->m_buf.data(),
                               {2, 4}, shared_buf);
    // Use count increased to 2
    std::cout << shared_buf.use_count() << std::endl;
    std::cout << obj << std::endl;
}
// Use count reset to 1
std::cout << shared_buf.use_count() << std::endl;

{
    auto obj = adapt_smart_ptr(unique_buf.get()->m_buf.data(),
                               {2, 4}, std::move(unique_buf));
    std::cout << obj << std::endl;
}

Parameters

data_ptr – A pointer to a typed data block (e.g. double*)
shape – The desired shape
smart_ptr – A smart pointer to move or copy, in order to manage memory
l – The desired memory layout

Returns

xtensor_adaptor on the memory