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.. Copyright (c) 2016, Johan Mabille, Sylvain Corlay and Wolf Vollprecht
Distributed under the terms of the BSD 3-Clause License.
The full license is in the file LICENSE, distributed with this software.
Builders
========
Most of *xtensor* builders return unevaluated expressions (see :ref:`lazy-evaluation`
for more details) that can be assigned to any kind of *xtensor* container.
Ones
----
.. code::
// Lazy version
auto e = xt::ones<double>({2, 3});
std::cout << e < std::endl;
// Outputs {{1., 1., 1.}, {1., 1., 1.}}
// Evaluated versions
using fixed_tensor = xt::xtensor_fixed<double, xt::xshape<2, 3>>;
xt::xarray<double> a0 = xt::ones<double>({2, 3});
xt::xtensor<double, 2> a1 = xt::ones<double>({2, 3});
fixed_tensor a2 = xt::ones<double>({2, 3});
Zeros
-----
.. code::
// Lazy version
auto e = xt::zeros<double>({2, 3});
std::cout << e << std::endl;
// Outputs {{0., 0., 0.}, {0., 0., 0.}}
// Evaluated versions
using fixed_tensor = xt::xtensor_fixed<double, xt::xshape<2, 3>>;
xt::xarray<double> a0 = xt::zeros<double>({2, 3});
xt::xtensor<double, 2> a1 = xt::zeros<double>({2, 3});
fixed_tensor a2 = xt::zeros<double>({2, 3});
Empty
-----
``xt::empty`` creates a container of uninitialized values. It selects the best container
match from the supplied shape:
.. code::
xt::xarray<double>::shape_type sh0 = {2, 3};
auto a0 = xt::empty<double>(sh0);
// a0 is xt::xarray<double>
xt::xtensor<double, 2>::shape_type sh1 = {2, 3};
auto a1 = xt::empty<double>(sh1);
// a1 is xt::xtensor<double, 2>
xt::xshape<2, 3> sh2;
auto a2 = xt::empty<double>(sh2);
// a2 is xt::xtensor_fixed<double, xt::xshape<2, 3>>
Full like
---------
``xt::full_like`` returns a container with the same shape as the input expression, and
filled with the specified value:
.. code::
xt::xarray<double> a0 = {{1., 2., 3.}, {4., 5., 6.}};
auto b0 = xt::full_like(a0, 3.);
std::cout << b0 << std::endl;
// Outputs {{3., 3., 3.}, {3., 3., 3.}}
// b0 is an xt::xarray<double>
xt::xtensor<double, 2> a1 = {{1., 2., 3.}, {4., 5., 6.}};
auto b1 = xt::full_like(a1, 3.);
std::cout << b1 << std::endl;
// Outputs {{3., 3., 3.}, {3., 3., 3.}}
// b1 is an xt::xtensor<double, 2>
xt::xtensor_fixed<double, xt::xshape<2, 3>> a2 = {{1., 2., 3.}, {4., 5., 6.}};
auto b2 = xt::full_like(a2, 3.);
std::cout << b2 << std::endl;
// Outputs {{3., 3., 3.}, {3., 3., 3.}}
// b2 is an xt::xtensor_fixed<double, xt::xshape<2, 3>>
Ones like
---------
``ones_like(e)`` is equivalent to ``full_like(e, 1.)``.
Zeros like
----------
``zeros_like(e)`` is equivalent to ``full_like(e, 0.)``.
Eye
---
Generates an array with ones on the specified diagonal:
.. code::
auto a = xt::eye<double>({2, 3}, 1);
std::cout << a << std::endl;
// Outputs {{O, 1, 0}, {0, 0, 1}}
auto b = xt::eye<double>({3, 2}, -1);
std::cout << b << std::endl;
// Outputs {{0, 0}, {1, 0}, {0, 1}}
aut c = xt::eye<double>(3, 1);
std::cout << c << std::endl;
// Outputs {{O, 1, 0}, {0, 0, 1}, {0, 0, 0}}
Arange
------
Generates evenly spaced numbers:
.. code::
auto e = xt::arange<double>(0., 10., 2);
std::cout << e << std::endl;
// Outputs {0., 2., 4., 6., 8.}
A common pattern is to use ``arange`` followed by reshape to initialize
a tensor with an arbitrary number of dimensions:
.. code::
xt::xarray<double> a = xt::arange<double>(0., 6.).reshape({2, 3});
std::cout << a << std::endl;
// Outputs {{0., 1., 2.}, {3., 4., 5.}}
Linspace
--------
.. code::
auto a = xt::linspace<double>(0., 10., 5);
std::cout << a << std::endl;
// Outputs {0., 2.5, 5., 7.5, 10.}
Logspace
--------
Similar to ``linspace`` but numbers are evenly space on a log scale.
Concatenate
-----------
.. code::
xt::xarray<double> a = {{1, 2, 3}};
xt::xarray<double> b = {{2, 3, 4}};
auto c0 = xt::concatenate(xt::xtuple(a, b));
std::cout << c0 << std::endl;
// Outputs {{1, 2, 3}, {2, 3, 4}}
auto c1 = xt::concatenate(xt::xtuple(a, b), 1);
std::cout << c1 << std::endl;
// Outputs {1, 2, 3, 2, 3, 4}
Stack
-----
``stack`` always creates a new dimension along which elements are stacked:
.. code::
xt::xarray<double> a = {1, 2, 3};
xt::xarray<double> b = {5, 6, 7};
auto s0 = xt::stack(xt::xtuple(a, b));
std::cout << s0 << std::endl;
// Outputs {{1, 2, 3}, {5, 6, 7}}
auto s1 = xt::stack(xt::xtuple(a, b), 1);
std::cout << s1 << std::endl;
// Outputs {{1, 5}, {2, 6}, {3, 7}}
HStack
------
.. code::
xt::xarray<double> a0 = {{1, 2, 3}, {4, 5, 6}};
xt::xarray<double> b0 = {{7, 8}, {9, 10}};
auto c0 = xt::hstack(xt::xtuple(a0, b0));
std::cout << c0 << std:endl;
// Outputs {{1, 2, 3, 7, 8}, {4, 5, 6, 0, 10}}
xt::xarray<double> a1 = {1, 2, 3};
xt::xarray<double> b1 = {2, 3 ,4};
auto c1 = xt::hstack(xt::xtuple(a1, b1));
std::cout << c1 << std::endl;
// Outputs {1, 2, 3, 2, 3, 4}
VStack
------
.. code::
xt::xarray<double> a0 = {1, 2, 3};
xt::xarray<double> b0 = {2, 3, 4};
auto c0 = xt::vstack(xt::xtuple(a0, b0));
std::cout << c0 << std::endl;
// Outputs {{1, 2, 3}, {2, 3 ,4}}
xt::xarray<double> a1 = {{1, 2, 3}, {4, 5 ,6}, {7, 8, 9}};
xt::xarray<double> b1 = {{10, 11, 12}};
auto c1 = xt::vstack(xt::xtuple(a1, b1));
std::cout << c1 << std::endl;
// Outputs {{1, 2, 3}, {4, 5 ,6}, {7, 8, 9}, {10, 11, 12}}
Diag
----
Returns a 2D-expression using the input value as its diagonal:
.. code::
xt::xarray<double> a = {1, 5, 7};
auto b = xt::diag(a);
std::cout << b << std::endl;
// Outputs {{1, 0, 0} {0, 5, 0}, {0, 0, 7}}
Diagonal
--------
Returns the elements on the diagonal of the expression
.. code::
xt::xarray<double> a = {{1, 2, 3},
{4, 5, 6},
{7, 8, 9}};
auto d = xt::diagonal(a);
std::cout << d << std::endl;
// Outputs {1, 5, 9}
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