# Views

Views are used to adapt the shape of an `xexpression` without changing it, nor copying it. xtensor provides two kinds of views.

## Sliced views

Sliced views consist of the combination of the `xexpression` to adapt, and a list of `slice` s that specify how the shape must be adapted. Sliced views are implemented by the `xview` class. Objects of this type should not be instantiated directly, but though the `view` helper function.

Slices can be specified in the following ways:

- selection in a dimension by specifying an index (unsigned integer)
- `range(min, max)`, a slice representing an interval
- `range(min, max, step)`, a slice representing a stepped interval
- `all()`, a slice representing all the elements of a dimension
- `newaxis()`, a slice representing an additional dimension of length one

    #include <vector>
    #include "xtensor/xarray.hpp"
    #include "xtensor/xview.hpp"

    std::vector<size_t> shape = {3, 2, 4};
    xt::xarray<int> a(shape);

    // View with same number of dimensions
    auto v1 = xt::view(a, xt::range(1, 3), xt::all(), xt::range(1, 3));
    // => v1.shape() = { 2, 2, 2 }
    // => v1(0, 0, 0) = a(1, 0, 1)
    // => v1(1, 1, 1) = a(2, 1, 2)

    // View reducing the number of dimensions
    auto v2 = xt::view(a, 1, xt::all(), xt::range(0, 4, 2));
    // => v2.shape() = { 2, 2 }
    // => v2(0, 0) = a(1, 0, 0)
    // => v2(1, 1) = a(1, 1, 2)

    // View increasing the number of dimensions
    auto v3 = xt::view(a, xt::all(), xt::all(), xt::newaxis(), xt::all());
    // => v3.shape() = { 3, 2, 1, 4 }
    // => v3(0, 0, 0, 0) = a(0, 0, 0)

`xview` does not perform a copy of the underlying expression. This means if you modify an element of the `xview`, you are actually also altering the underlying expression.

    #include <vector>
    #include "xtensor/xarray.hpp"
    #include "xtensor/xview.hpp"

    std::vector<size_t> shape = {3, 2, 4};
    xt::xarray<int> a(shape, 0);

    auto v1 = xt::view(a, 1, xt::all(), xt::range(1, 3));
    v1(0, 0) = 1;
    // => a(1, 0, 1) = 1

## Index views

Index views are one-dimensional views of an `xexpression`, containing the elements whose positions are specified by a list of indices. Like for sliced views, the elements of the underlying `xexpression` are not copied. Index views should be built with the `index_view` helper function.

    #include "xtensor/xarray.hpp"
    #include "xtensor/xindexview.hpp"

    xt::xarray<double> a = {{1, 5, 3}, {4, 5, 6}};
    auto b = xt::index_view(a, {{0,0}, {1, 0}, {0, 1}});
    // => b = { 1, 4, 5 }
    b += 100;
    // => a = {{101, 5, 3}, {104, 105, 6}}

## Filter views

Filters are one-dimensional views holding elements of an `xexpression` that verify a given condition. Like for other views, the elements of the underlying `xexpression` are not copied. Filters should be built with the `filter` helper function.

    #include "xtensor/xarray.hpp"
    #include "xtensor/xindexview.hpp"

    xt::xarray<double> a = {{1, 5, 3}, {4, 5, 6}};
    auto v = xt::filter(a, a >= 5);
    // => v = { 5, 5, 6 }
    v += 100;
    // => a = {{1, 105, 3}, {4, 105, 106}}

## Filtration

Sometimes, the only thing you want to do with a filter is to assign it a scalar. Though this can be done as shown in the previous section, this is not the optimal way to do it. xtensor provides a specially optimized mechanism for that, called filtration. A filtration IS NOT an `xexpression`, the only methods it provides are scalar and computed scalar assignments.

    #include "xtensor/xarray.hpp"
    #include "xtensor/xindexview.hpp"

    xt::xarray<double> a = {{1, 5, 3}, {4, 5, 6}};
    filtration(a, a >= 5) += 100;
    // => a = {{1, 105, 3}, {4, 105, 106}}

## Broadcasting views

Another type of view provided by xtensor is broadcasting view. Such a view broadcast an expression to the specified shape. As long as the view is not assigned to an array, no memory allocation or copy occurs. Broadcasting views should be built with the `broadcast` helper function.

    #include <vector>
    #include "xtensor/xarray.hpp"
    #include "xtensor/xbroadcast.hpp"

    std::vector<size_t> s1 = { 2, 3 };
    std::vector<size_t> s2 = { 3, 2, 3 };

    xt::xarray<int> a1(s1);
    auto bv = xt::broadcast(a1, s2);
    // => bv(0, 0, 0) = bv(1, 0, 0) = bv(2, 0, 0) = a(0, 0)

## Complex views

In the case of tensor containing complex numbers, xtensor provides views returning `xexpression` corresponding to the real and imaginary parts of the complex numbers. Like for other views, the elements of the underlying `xexpression` are not copied.

Functions `xt::real` and `xt::imag` respectively return views on the real and imaginary part of a complex expression. The returned value is an expression holding a closure on the passed argument.

- The constness and value category (rvalue / lvalue) of `real(a)` is the same as that of `a`. Hence, if `a` is a non-const lvalue, `real(a)` is an non-const lvalue reference, to which one can assign a real expression.
- If `a` has complex values, the same holds for `imag(a)`. The constness and value category of `imag(a)` is the same as that of `a`.
- If `a` has real values, `imag(a)` returns `zeros(a.shape())`.

    #include <complex>
    #include "xtensor/xarray.hpp"
    #include "xtensor/xcomplex.hpp"

    using namespace std::complex_literals;

    xarray<std::complex<double>> e =
        {{1.0       , 1.0 + 1.0i},
         {1.0 - 1.0i, 1.0       }};

    real(e) = zeros<double>({2, 2});
    // => e = {{0.0, 0.0 + 1.0i}, {0.0 - 1.0i, 0.0}};