Commit ec8e2dc9 authored by Samuel GAIST's avatar Samuel GAIST

Merge branch 'docedit' into 'master'

[doc] fixed external and internal links

See merge request !80
parents fee7ca1b f248d4b0
Pipeline #31573 passed with stage
in 15 minutes and 40 seconds
......@@ -72,8 +72,7 @@ Docker Setup
Make sure you have the ``docker`` command available on your system. For certain
operating systems, it is necessary to install ``docker`` via an external
virtual machine (a.k.a. the *docker machine*). Follow the instructions at `the
docker website <https://docs.docker.com/engine/installation/>` before trying to
virtual machine (a.k.a. the *docker machine*). Follow the instructions at `the docker website`_ before trying to
execute algorithms or experiments.
We use specific docker images to run user algorithms. Download the following
......@@ -101,7 +100,7 @@ To run an experiment using docker you should specify the docker image when defin
$ beat experiment run --docker <experiment name>
You can find more information about running experiments locally using different executors in `here <https://www.idiap.ch/software/beat/docs/beat/docs/master/beat.cmdline/doc/experiments.html#how-to-run-an-experiment>`_.
You can find more information about running experiments locally using different executors in the "Experiments" section of "beat.cmdline" in `BEAT documentation`_.
Documentation
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......@@ -37,7 +37,7 @@
Introduction
==============
A typical BEAT experiment is composed of several building blocks. Datasets that provide data to the system, algorithms that handles the functions introduced by user, analyzers that is in charge of interpreting the output result and producing the appropriate results and figures, and toolchains that determines the data flow between the blocks from datasets to the final results. In addition, each block accepts specific data formats and the data is synchronized between blocks neatly without users need to interfere. These basic functionalities that are introduced in `Getting Started with BEAT`_ are all defined and managed by ``beat.core``. For example, as it is explained in `Algorithms`_, algorithm objects should be derived from the class
A typical BEAT experiment is composed of several building blocks. Datasets that provide data to the system, algorithms that handles the functions introduced by user, analyzers that is in charge of interpreting the output result and producing the appropriate results and figures, and toolchains that determines the data flow between the blocks from datasets to the final results. In addition, each block accepts specific data formats and the data is synchronized between blocks neatly without users need to interfere. These basic functionalities that are introduced in the "Getting Started with BEAT" section in `BEAT documentation`_ are all defined and managed by ``beat.core``. For example, as it is explained in the "Algorithms" section of "Getting Started with BEAT" in `BEAT documentation`_, algorithm objects should be derived from the class
``Algorithm`` when using Python or in case of C++, they should be derived from ``IAlgorithmLagacy``, ``IAlgorithmSequential``, or ``IAlgorithmAutonomous`` depending of the algorithm type. All these parent classes are defined in ``beat.core`` package.
The rest of this document includes information about the backend api used to handle data through the BEAT ecosystem. For developers and advanced user there is information for local development of the package.
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......@@ -49,5 +49,5 @@
.. _python bindings: http://zeromq.org/bindings:python
.. _markdown: http://daringfireball.net/projects/markdown/
.. _restructuredtext: http://docutils.sourceforge.net/rst.html
.. _Getting Started with BEAT: https://www.idiap.ch/software/beat/docs/beat/docs/master/beat/introduction.html
.. _Algorithms: https://www.idiap.ch/software/beat/docs/beat/docs/master/beat/algorithms.html
.. _BEAT documentation: https://www.idiap.ch/software/beat/documentation
.. _the docker website: https://docs.docker.com/engine/installation/
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