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Minor improvements to documentation
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docs/contributing.rst

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Contributing
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------------
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If you're looking to contribute to this package: welcome!
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Please check the open `issues <https://github.com/AutoTuningAssociation/autotuning_methodology/issues>`_ and `pull requests <https://github.com/AutoTuningAssociation/autotuning_methodology/pulls>`_ to avoid duplicate work.
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Setup
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^^^^^
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Testing
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^^^^^^^
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Before contributing a pull request, please run ``nox`` and ensure it has no errors. This will test against all Python versions explicitely supported by this package, and will check whether the correct formatting has been applied.
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Before contributing a pull request, please run ``nox`` and ensure it has no errors.
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This will test against all Python versions explicitely supported by this package, and will check whether the correct formatting has been applied.
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Upon submitting a pull request or pushing to main, these same checks will be ran remotely via GitHub Actions.

docs/getting_started.rst

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Defining an experiment
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^^^^^^^^^^^^^^^^^^^^^^
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To get started, all you need is an experiments file.
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This is a `json` file that describes the details of your comparison: which algorithms to use, which programs to tune on which devices, the graphs to output and so on.
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A simple example experiments file is as follows:
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Running experiments
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^^^^^^^^^^^^^^^^^^^
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To use these experiment files, two entry points are defined: ``autotuning_experiment`` and ``autotuning_visualize``.
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Both entrypoints take one argument: the path to the experiments file.
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The first runs the experiment and saves the results, the second visualizes the results.
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A note on file references
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^^^^^^^^^^^^^^^^^^^^^^^^^
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File references in experiments files are relative to the location of the experiment file itself.
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File references in tuning scripts are relative to the location of the tuning script itself. Tuning scripts need to have the global literals `file_path_results` and `file_path_metadata` for this package to know where to get the results.
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Plots outputted by this package are placed in a folder called `generated_plots` relative to the current working directory.
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Processing Pipeline
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^^^^^^^^^^^^^^^^^^^
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To clarify the complex process of this package to obtain the results and visualize, the flowcharts below illustrate this pipeline.
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.. image:: source/flowchart_performance_curve_generation.png

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