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getting_started.rst
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			Getting Started
			===============

			Building ``Akantu``
			--------------------

			Dependencies
			````````````

			In order to compile ``Akantu`` any compiler supporting fully C++14 should work.
			In addition some libraries are required:

			- CMake (>= 3.5.1)
			- Boost (preprocessor and Spirit)
			- zlib
			- blas/lapack

			For the python interface:

			- Python (>=3 is recommended)
			- pybind11 (if not present the build system will try to download it)

			To run parallel simulations:

			- MPI
			- Scotch

			To use the static or implicit dynamic solvers at least one of the following libraries is needed:

			- MUMPS (since this is usually compiled in static you also need MUMPS dependencies)
			- PETSc

			To compile the tests and examples:

			- Gmsh
			- google-test (if not present the build system will try to download it)

			Configuring and compilation
			```````````````````````````

			``Akantu`` is a `CMake <https://cmake.org/>`_ project, so to configure it, you can either
			follow the usual way::

			> cd akantu
			> mkdir build
			> cd build
			> ccmake ..
			[ Set the options that you need ]
			> make
			> make install

			Using the python interface
			--------------------------

			You can install ``Akantu`` using pip::

			> pip install akantu

			You can then import the package in a python script as::

			import akantu

			The python API is similar to the C++ one, see :ref:`reference` . If you encouter any problem with the python interface, you are welcome to do a merge request or post an issue on `GitLab <https://gitlab.com/akantu/akantu/-/issues>`_ .

			Tutorials with the python interface
			```````````````````````````````````

			To help getting started, several tutorials using the python interface
			are available as notebooks with pre-installed version of ``Akantu`` on Binder.
			The following tutorials are currently available:

			`Plate whith a hole loaded <https://mybinder.org/v2/git/https%3A%2F%2Fgitlab.com%2Fakantu%2Ftutorials.git/HEAD?filepath=plate-hole/plate-hole.ipynb>`_

			`Loaded cohesive crack <https://mybinder.org/v2/git/https%3A%2F%2Fgitlab.com%2Fakantu%2Ftutorials.git/HEAD?filepath=cohesive-fracture/cohesive-fracture.ipynb>`_

			`Making your constitutive law in python <https://mybinder.org/v2/git/https%3A%2F%2Fgitlab.com%2Fakantu%2Ftutorials.git/HEAD?filepath=constitutive-laws/python_constitutive_law.ipynb>`_


			Writing a ``main`` function
			---------------------------

			``Akantu`` first needs to be initialized. The memory management included in the
			core library handles the correct allocation and de-allocation of vectors,
			structures and/or objects. Moreover, in parallel computations, the
			initialization procedure performs the communication setup. This is achieved by
			the function :cpp:func:`initialize <akantu::initialize>` that is used as
			follows::

			#include "aka_common.hh"
			#include "..."

			using namespace akantu;

			int main(int argc, char *argv[]) {
			initialize("input_file.dat", argc, argv);

			// your code ...

			}

			The :cpp:func:`initialize <akantu::initialize>` function takes the text inpute
			file and the program parameters which can be parsed by ``Akantu`` in due form
			(see sect:parser). Obviously it is necessary to include all files needed in
			main. In this manual all provided code implies the usage of ``akantu`` as
			namespace.

			Compiling your simulation
			-------------------------

			The easiest way to compile your simulation is to create a ``cmake`` project by
			putting all your code in some directory of your choosing. Then, make sure that
			you have ``cmake`` installed and create a ``CMakeLists.txt`` file. An example of
			a minimal ``CMakeLists.txt`` file would look like this:

			.. code-block:: cmake

			project(my_simu)
			cmake_minimum_required(VERSION 3.0.0)

			find_package(Akantu REQUIRED)

			add_akantu_simulation(my_simu my_simu.cc)

			Then create a directory called ``build`` and inside it execute ``cmake
			-DAkantu_DIR=<path_to_akantu> -DCMAKE_BUILD_TYPE=RelWithDebInfo ..``. If you
			installed ``Akantu`` in a standard directory such as ``/usr/local`` (using
			``make install``), you can omit the ``-DAkantu_DIR=<path_to_akantu>`` option.

			Other why ``path_to_akantu`` is either the folder where you built ``Akantu`` if
			you did not do a ``make install``, or if you installed ``Akantu`` in
			``CMAKE_INSTALL_PREFIX`` it is ``<CMAKE_INSTALL_PREFIX>/share/cmake/Akantu``.

			Once ``cmake`` managed to configure and generate a ``makefile`` you can just do
			``make``


			.. _loading_mesh:

			Creating and Loading a Mesh
			---------------------------

			In its current state, ``Akantu`` supports three types of meshes: Gmsh, Abaqus and
			Diana. Once a :cpp:class:`akantu::Mesh` object is created with a given spatial
			dimension, it can be filled by reading a mesh input file. The method
			:cpp:func:`read <akantu::Mesh::read>` of the class :cpp:class:`Mesh
			<akantu::Mesh>` infers the mesh type from the file extension. If a non-standard
			file extension is used, the mesh type has to be specified. ::

			UInt spatial_dimension = 2;
			Mesh mesh(spatial_dimension);

			// Reading Gmsh files
			mesh.read("my_gmsh_mesh.msh");
			mesh.read("my_gmsh_mesh", _miot_gmsh);

			The Gmsh reader adds the geometrical and physical tags as mesh data. The
			physical values are stored as a :cpp:type:`UInt <akantu::UInt>` data called
			``tag_0``, if a string name is provided it is stored as a ``std::string`` data
			named ``physical_names``. The geometrical tag is stored as a :cpp:type:`UInt
			<akantu::UInt>` data named ``tag_1``.

			Using Arrays
			------------

			Data in ``Akantu`` can be stored in data containers implemented by the
			:cpp:class:`akantu::Array` class. In its most basic usage, the :cpp:class:`Array
			<akantu::Array>` class implemented in \akantu is similar to the ``std::vector``
			class of the Standard Template Library (STL) for C++. A simple :cpp:class:`Array
			<akantu::Array>` containing a sequence of ``nb_element`` values (of a given
			type) can be generated with::

			Array<type> example_array(nb_element);

			where ``type`` usually is :cpp:type:`Real <akantu::Real>`, :cpp:type:`Int
			<akantu::Int>`, :cpp:type:`UInt <akantu::UInt>` or ``bool``. Each value is
			associated to an index, so that data can be accessed by typing::

			auto & val = example_array(index);

			``Arrays`` can also contain tuples of values for each index. In that case, the
			number of components per tuple must be specified at the :cpp:class:`Array
			<akantu::Array>` creation. For example, if we want to create an
			:cpp:class:`Array <akantu::Array>` to store the coordinates (sequences of three
			values) of ten nodes, the appropriate code is the following::

			UInt nb_nodes = 10;
			UInt spatial_dimension = 3;

			Array<Real> position(nb_nodes, spatial_dimension);

			In this case the :math:`x` position of the eighth node number will be given
			by ``position(7, 0)`` (in C++, numbering starts at 0 and not 1). If
			the number of components for the sequences is not specified, the
			default value of 1 is used. Here is a list of some basic operations
			that can be performed on :cpp:class:`Array <akantu::Array>`:

			- :cpp:func:`resize(size) <akantu::ArrayDataLayer::resize>` change the size of
			the :cpp:class:`Array <akantu::Array>`.
			- :cpp:func:`clear <akantu::Array::clear>` reset the size of the
			:cpp:class:`Array <akantu::Array>` to zero. (warning this changed in >
			v4.0)
			- :cpp:func:`set(t) <akantu::Array::set>` set all entries of the
			:cpp:class:`Array <akantu::Array>` to ``t``.
			- :cpp:func:`copy(const Array & other) <akantu::Array::copy>` copy another
			:cpp:class:`Array <akantu::Array>` into the current one. The two
			:cpp:class:`Arrays <akantu::Array>` should have the same number of
			components.
			- :cpp:func:`push_back(tuple) <akantu::Array::push_back>` append a tuple with
			the correct number of components at the end of the :cpp:class:`Array <akantu::Array>`.
			- :cpp:func:`erase(i) <akantu::Array::erase>` erase the value at the i-th position.
			- :cpp:func:`find(value) <akantu::Array::find>` search ``value`` in the
			current :cpp:class:`Array <akantu::Array>`. Return position index of the
			first occurence or -1 if not found.
			- :cpp:func:`storage() <akantu::Array::storage>` Return the address of the
			allocated memory of the :cpp:class:`Array <akantu::Array>`.

			Array iterators
			---------------

			It is very common in ``Akantu`` to loop over arrays to perform a specific treatment.
			This ranges from geometric calculation on nodal quantities to tensor algebra (in
			constitutive laws for example). The :cpp:class:`Array <akantu::Array>` object
			has the possibility to request iterators in order to make the writing of loops
			easier and enhance readability. For instance, a loop over the nodal coordinates
			can be performed like::

			// accessing the nodal coordinates Array
			// with spatial_dimension components
			const auto & nodes = mesh.getNodes();

			for (const auto & coords : make_view(nodes, spatial_dimension)) {
			// do what you need ....
			}

			In that example, each ``coords`` is a :cpp:class:`Vector\<Real\> <akantu::Vector>`
			containing geometrical array of size ``spatial_dimension`` and the iteration is
			conveniently performed by the :cpp:class:`Array <akantu::Array>` iterator.

			The :cpp:class:`Array <akantu::Array>` object is intensively used to store
			second order tensor values. In that case, it should be specified that the
			returned object type is a matrix when constructing the iterator. This is done
			when calling the :cpp:func:`make_view <akantu::make_view>`. For instance,
			assuming that we have a :cpp:class:`Array <akantu::Array>` storing stresses, we
			can loop over the stored tensors by::

			for (const auto & stress :
			make_view(stresses, spatial_dimension, spatial_dimension)) {
			// stress is of type `const Matrix<Real>&`
			}

			In that last example, the :cpp:class:`Matrix\<Real\> <akantu::Matrix>` objects are
			``spatial_dimension`` :math:`\times` ``spatial_dimension`` matrices. The light
			objects :cpp:class:`Matrix\<T\> <akantu::Matrix>` and
			:cpp:class:`Vector\<T\> <akantu::Vector>` can be used and combined to do most
			common linear algebra. If the number of component is 1, it is possible to use
			:cpp:func:`make_view <akantu::make_view>` to this effect.


			In general, a mesh consists of several kinds of elements. Consequently, the
			amount of data to be stored can differ for each element type. The
			straightforward example is the connectivity array, namely the sequences of nodes
			belonging to each element (linear triangular elements have fewer nodes than,
			say, rectangular quadratic elements etc.). A particular data structure called
			:cpp:class:`ElementTypeMapArray\<T\> <akantu::ElementTypeMapArray>` is provided
			to easily manage this kind of data. It consists of a group of ``Arrays``, each
			associated to an element type. The following code can retrieve the
			:cpp:class:`ElementTypeMapArray\<UInt\> <akantu::ElementTypeMapArray>` which
			stores the connectivity arrays for a mesh::

			const ElementTypeMapArray<UInt> & connectivities =
			mesh.getConnectivities();

			Then, the specific array associated to a given element type can be obtained by::

			const Array<UInt> & connectivity_triangle =
			connectivities(_triangle_3);

			where the first order 3-node triangular element was used in the presented piece
			of code.

			Vector & Matrix
			```````````````

			The :cpp:class:`Array\<T\> <akantu::Array>` iterators as presented in the previous
			section can be shaped as :cpp:class:`Vector\<T\> <akantu::Vector>` or
			:cpp:class:`Matrix\<T\> <akantu::Matrix>`. This objects represent 1st and 2nd order
			tensors. As such they come with some functionalities that we will present a bit
			more into detail in this here.


			``Vector<T>``
			'''''''''''''

			- Accessors:

			- :cpp:func:`v(i) <akantu::Vector::operator()>` gives the ``i`` -th
			component of the vector ``v``
			- :cpp:func:`v[i] <akantu::Vector::operator[]>` gives the ``i`` -th
			component of the vector ``v``
			- :cpp:func:`v.size() <akantu::Vector::size>` gives the number of component

			- Level 1: (results are scalars)

			- :cpp:func:`v.norm() <akantu::Vector::norm>` returns the geometrical norm
			(:math:`L_2`)
			- :cpp:func:`v.norm\<N\>() <akantu::Vector::norm<>>` returns the :math:`L_N`
			norm defined as :math:`\left(\sum_i \|v(i)\|^N\right)^{1/N}`. N can take any
			positive integer value. There are also some particular values for the most
			commonly used norms, ``L_1`` for the Manhattan norm, ``L_2`` for the
			geometrical norm and ``L_inf`` for the norm infinity.
			- :cpp:func:`v.dot(x) <akantu::Vector::dot>` return the dot product of
			``v`` and ``x``
			- :cpp:func:`v.distance(x) <akantu::Vector::distance>` return the
			geometrical norm of :math:`v - x`

			- Level 2: (results are vectors)

			- :cpp:func:`v += s <akantu::Vector::operator+=>`,
			:cpp:func:`v -= s <akantu::Vector::operator-=>`,
			:cpp:func:`v = s <akantu::Vector::operator=>`,
			:cpp:func:`v /= s <akantu::Vector::operator/=>` those are element-wise
			operators that sum, substract, multiply or divide all the component of ``v``
			by the scalar ``s``
			- :cpp:func:`v += x <akantu::Vector::operator+=>`, :cpp:func:`v -= x
			<akantu::Vector::operator-=>` sums or substracts the vector ``x`` to/from
			``v``
			- :cpp:func:`v.mul(A, x, alpha) <akantu::Vector::mul>` stores the result of
			:math:`\alpha \boldsymbol{A} \vec{x}` in ``v``, :math:`\alpha` is equal to 1
			by default
			- :cpp:func:`v.solve(A, b) <akantu::Vector::solve>` stores the result of
			the resolution of the system :math:`\boldsymbol{A} \vec{x} = \vec{b}` in ``v``
			- :cpp:func:`v.crossProduct(v1, v2) <akantu::Vector::crossProduct>`
			computes the cross product of ``v1`` and ``v2`` and stores the result in
			``v``

			``Matrix<T>``
			'''''''''''''

			- Accessors:

			- :cpp:func:`A(i, j) <akantu::Matrix::operator()>` gives the component
			:math:`A_{ij}` of the matrix ``A``
			- :cpp:func:`A(i) <akantu::Matrix::operator()>` gives the :math:`i^{th}`
			column of the matrix as a ``Vector``
			- :cpp:func:`A[k] <akantu::Matrix::operator[]>` gives the :math:`k^{th}`
			component of the matrix, matrices are stored in a column major way, which
			means that to access :math:`A_{ij}`, :math:`k = i + j M`
			- :cpp:func:`A.rows() <akantu::Matrix::rows>` gives the number of rows of
			``A`` (:math:`M`)
			- :cpp:func:`A.cols() <akantu::Matrix::cols>` gives the number of columns
			of ``A`` (:math:`N`)
			- :cpp:func:`A.size() <akantu::Matrix::size>` gives the number of component
			in the matrix (:math:`M \times N`)

			- Level 1: (results are scalars)

			- :cpp:func:`A.norm() <akantu::Matrix::norm>` is equivalent to
			``A.norm<L_2>()``
			- :cpp:func:`A.norm\<N\>() <akantu::Matrix::norm<>>` returns the :math:`L_N`
			norm defined as :math:`\left(\sum_i\sum_j \|A(i,j)\|^N\right)^{1/N}`. N can take
			any positive integer value. There are also some particular values for the most
			commonly used norms, ``L_1`` for the Manhattan norm, ``L_2`` for the
			geometrical norm and ``L_inf`` for the norm infinity.
			- :cpp:func:`A.trace() <akantu::Matrix::trace>` return the trace of ``A``
			- :cpp:func:`A.det() <akantu::Matrix::det>` return the determinant of ``A``
			- :cpp:func:`A.doubleDot(B) <akantu::Matrix::doubleDot>` return the double
			dot product of ``A`` and ``B``, :math:`\mat{A}:\mat{B}`

			- Level 3: (results are matrices)

			- :cpp:func:`A.eye(s) <akantu::Matrix::eye>`, ``Matrix<T>::eye(s)``
			fills/creates a matrix with the :math:`s\mat{I}` with :math:`\mat{I}` the
			identity matrix
			- :cpp:func:`A.inverse(B) <akantu::Matrix::inverse>` stores
			:math:`\mat{B}^{-1}` in ``A``
			- :cpp:func:`A.transpose() <akantu::Matrix::transpose>` returns
			:math:`\mat{A}^{t}`
			- :cpp:func:`A.outerProduct(v1, v2) <akantu::Matrix::outerProduct>` stores
			:math:`\vec{v_1} \vec{v_2}^{t}` in ``A``
			- :cpp:func:`C.mul\<t_A, t_B\>(A, B, alpha) <akantu::Matrix::mul>`: stores
			the result of the product of ``A`` and code{B} time the scalar ``alpha`` in
			``C``. ``t_A`` and ``t_B`` are boolean defining if ``A`` and ``B`` should be
			transposed or not.

			+----------+----------+--------------+
			\|``t_A`` \|``t_B`` \|result \|
			\| \| \| \|
			+----------+----------+--------------+
			\|false \|false \|:math:`\mat{C}\|
			\| \| \|= \alpha \|
			\| \| \|\mat{A} \|
			\| \| \|\mat{B}` \|
			\| \| \| \|
			+----------+----------+--------------+
			\|false \|true \|:math:`\mat{C}\|
			\| \| \|= \alpha \|
			\| \| \|\mat{A} \|
			\| \| \|\mat{B}^t` \|
			\| \| \| \|
			+----------+----------+--------------+
			\|true \|false \|:math:`\mat{C}\|
			\| \| \|= \alpha \|
			\| \| \|\mat{A}^t \|
			\| \| \|\mat{B}` \|
			\| \| \| \|
			+----------+----------+--------------+
			\|true \|true \|:math:`\mat{C}\|
			\| \| \|= \alpha \|
			\| \| \|\mat{A}^t \|
			\| \| \|\mat{B}^t` \|
			+----------+----------+--------------+

			- :cpp:func:`A.eigs(d, V) <akantu::Matrix::eigs>` this method computes the
			eigenvalues and eigenvectors of ``A`` and store the results in ``d`` and
			``V`` such that :math:`d(i) = \lambda_i` and :math:`V(i) = \vec{v_i}` with
			:math:`\mat{A}\vec{v_i} = \lambda_i\vec{v_i}` and :math:`\lambda_1 > ... >
			\lambda_i > ... > \lambda_N`


			.. _sect-common-groups:

			Mesh
			----



			Manipulating group of nodes and/or elements
			```````````````````````````````````````````

			``Akantu`` provides the possibility to manipulate subgroups of elements and
			nodes. Any :cpp:class:`ElementGroup <akantu::ElementGroup>` and/or
			:cpp:class:`NodeGroup <akantu::NodeGroup>` must be managed by a
			:cpp:class:`GroupManager <akantu::GroupManager>`. Such a manager has the role to
			associate group objects to names. This is a useful feature, in particular for
			the application of the boundary conditions, as will be demonstrated in section
			:ref:`sect-smm-boundary`. To most general group manager is the :cpp:class:`Mesh
			<akantu::Mesh>` class which inherits from :cpp:class:`GroupManager
			<akantu::GroupManager>`.

			For instance, the following code shows how to request an element group
			to a mesh:

			.. code-block:: c++

			// request creation of a group of nodes
			NodeGroup & my_node_group = mesh.createNodeGroup("my_node_group");
			// request creation of a group of elements
			ElementGroup & my_element_group = mesh.createElementGroup("my_element_group");

			/* fill and use the groups */


			The ``NodeGroup`` object
			''''''''''''''''''''''''

			A group of nodes is stored in :cpp:class:`NodeGroup <akantu::NodeGroup>`
			objects. They are quite simple objects which store the indexes of the selected
			nodes in a :cpp:class:`Array\<UInt\> <akantu::Array>`. Nodes are selected by
			adding them when calling :cpp:func:`add <akantu::NodeGroup::add>`. For instance
			you can select nodes having a positive :math:`X` coordinate with the following
			code:

			.. code-block:: c++

			const auto & nodes = mesh.getNodes();
			auto & group = mesh.createNodeGroup("XpositiveNode");

			for (auto && data : enumerate(make_view(nodes, spatial_dimension))){
			auto node = std::get<0>(data);
			const auto & position = std::get<1>(data);
			if (position(0) > 0) group.add(node);
			}


			The ``ElementGroup`` object
			'''''''''''''''''''''''''''

			A group of elements is stored in :cpp:class:`ElementGroup
			<akantu::ElementGroup>` objects. Since a group can contain elements of various
			types the :cpp:class:`ElementGroup <akantu::ElementGroup>` object stores indexes
			in a :cpp:class:`ElementTypeMapArray\<UInt\> <akantu::ElementTypeMapArray>`
			object. Then elements can be added to the group by calling :cpp:func:`add
			<akantu::ElementGroup::add>`.

			For instance, selecting the elements for which the barycenter of the
			nodes has a positive :math:`X` coordinate can be made with:

			.. code-block:: c++

			auto & group = mesh.createElementGroup("XpositiveElement");
			Vector<Real> barycenter(spatial_dimension);

			for_each_element(mesh, [&](auto && element) {
			mesh.getBarycenter(element, barycenter);
			if (barycenter(_x) > 0.) { group.add(element); }
			});

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