rapids/docs/usage/introduction.rst

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Quick Introduction
==================
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The goal of this pipeline is to standardize the data cleaning, feature extraction, analysis, and evaluation of mobile sensing projects. It leverages Conda_, Cookiecutter_, SciPy_, Snakemake_, Sphinx_, and R_ to create an end-to-end reproducible environment that can be published along with research papers.
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At the moment, mobile data can be collected using different sensing frameworks (AWARE_, Beiwe_) and hardware (Fitbit_). The pipeline is agnostic to these data sources and can unify their analysis. The current implementation only handles data collected with AWARE_ and Fitbit_. However, it can be easily extended to other providers.
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We recommend reading Snakemake_ docs, but the main idea behind the pipeline is that every link in the analysis chain is a rule with an input and an output. Input and output are files, which can be manipulated using any programming language (although Snakemake_ has wrappers for Julia_, Python_, and R_ that can make development slightly more comfortable). Snakemake_ also allows the pipeline rules to be executed in parallel on multiple cores without any code changes. This can drastically reduce the time needed to complete an analysis.
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Available features:
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- :ref:`accelerometer-sensor-doc`
- :ref:`applications-foreground-sensor-doc`
- :ref:`battery-sensor-doc`
- :ref:`bluetooth-sensor-doc`
- :ref:`wifi-sensor-doc`
- :ref:`call-sensor-doc`
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- :ref:`activity-recognition-sensor-doc`
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- :ref:`light-doc`
- :ref:`location-sensor-doc`
- :ref:`screen-sensor-doc`
- :ref:`sms-sensor-doc`
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- :ref:`fitbit-sleep-sensor-doc`
- :ref:`fitbit-heart-rate-sensor-doc`
- :ref:`fitbit-steps-sensor-doc`
We are updating these docs constantly, but if you think something needs clarification, feel free to reach out or submit a pull request on GitHub.
.. _Conda: https://docs.conda.io/en/latest/
.. _Cookiecutter: http://drivendata.github.io/cookiecutter-data-science/
.. _SciPy: https://www.scipy.org/index.html
.. _Snakemake: https://snakemake.readthedocs.io/en/stable/
.. _Sphinx: https://www.sphinx-doc.org/en/master/
.. _R: https://www.r-project.org/
.. _AWARE: https://awareframework.com/what-is-aware/
.. _Beiwe: https://www.beiwe.org/
.. _Fitbit: https://www.fitbit.com/us/home
.. _Python: https://www.python.org/
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.. _Julia: https://julialang.org/