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doc/development/development.rst

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@@ -61,7 +61,7 @@ for the :code:`spikeinterface.extractors` module, you can use the following comm
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The markers are located in the :code:`pyproject.toml` file in the root of the repository.
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Note that you should install the package before running the tests. You can do this by running the following command:
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Note that you should install spikeinterface before running the tests. You can do this by running the following command:
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.. code-block:: bash
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@@ -72,7 +72,7 @@ You can change the :code:`[test,extractors,full]` to install only the dependenci
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The specific environment for the CI is specified in the :code:`.github/actions/build-test-environment/action.yml` and you can
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find the full tests in the :code:`.github/workflows/full_test.yml` file.
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The extractor tests require datalad for some of the tests. Here are instructions for installing datalad:
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Some of the extractor tests require datalad. Here are instructions for installing datalad:
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Installing Datalad
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------------------
@@ -87,13 +87,13 @@ Stylistic conventions
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SpikeInterface maintains a consistent coding style across the project. This helps to ensure readability and
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maintainability of the code, making it easier for contributors to collaborate. To facilitate code style
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for the developer we use the follwing tools and conventions:
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for the developer we use the following tools and conventions:
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Install Black and pre-commit
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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We use the python formatter Black, with defaults set in the :code:`pyproject.toml`. This allows for
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We use the Python formatter Black, with defaults set in the :code:`pyproject.toml`. This allows for
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easy local formatting of code.
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To install Black, you can use pip, the Python package installer. Run the following command in your terminal:
@@ -218,7 +218,7 @@ Adding new documentation
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Documentation can be added as a
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`sphinx-gallery <https://sphinx-gallery.github.io/stable/index.html>`_
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python file ('tutorials')
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Python file ('tutorials')
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or a
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`sphinx rst <https://sphinx-tutorial.readthedocs.io/step-1/>`_
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file (all other sections).
@@ -242,7 +242,7 @@ To run code coverage locally, you can use the following command:
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This will run the tests and generate a report in the :code:`htmlcov` folder. You can open the :code:`index.html` file in your browser to see the report.
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Note, however, that the running time of the command above will be slow. If you want to run the tests for a specific module, you can use the following command:
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Note, however, that the running time of the command above will be quite long. If you want to run the tests for a specific module, you can use the following command:
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.. code-block:: bash
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@@ -252,21 +252,21 @@ Implement a new extractor
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-------------------------
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SpikeInterface already supports over 30 file formats, but the acquisition system you use might not be among the
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supported formats list (***ref***). Most of the extractors rely on the `NEO <https://github.com/NeuralEnsemble/python-neo>`_
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supported formats list (****ref****). Most of the extractors rely on the `NEO <https://github.com/NeuralEnsemble/python-neo>`_
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package to read information from files.
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Therefore, to implement a new extractor to handle the unsupported format, we recommend making a new :code:`neo.rawio.BaseRawIO` class (see `example <https://github.com/NeuralEnsemble/python-neo/blob/master/neo/rawio/examplerawio.py#L44>`_).
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Once that is done, the new class can be easily wrapped into SpikeInterface as an extension of the
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:py:class:`~spikeinterface.extractors.neoextractors.neobaseextractors.NeoBaseRecordingExtractor`
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(for :py:class:`~spikeinterface.core.BaseRecording` objects) or
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:py:class:`~spikeinterface.extractors.neoextractors.neobaseextractors.NeoBaseRecordingExtractor`
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(for :py:class:`~spikeinterface.core.BaseSorting` objects) or with a few lines of
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code (e.g., see reader for `SpikeGLX <https://github.com/SpikeInterface/spikeinterface/blob/0.96.1/spikeinterface/extractors/neoextractors/spikeglx.py>`_
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or `Neuralynx <https://github.com/SpikeInterface/spikeinterface/blob/0.96.1/spikeinterface/extractors/neoextractors/neuralynx.py>`_).
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code (e.g., see reader for `SpikeGLX <https://github.com/SpikeInterface/spikeinterface/blob/main/src/spikeinterface/extractors/neoextractors/spikeglx.py>`_
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or `Neuralynx <https://github.com/SpikeInterface/spikeinterface/blob/main/src/spikeinterface/extractors/neoextractors/neuralynx.py>`_).
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**NOTE:** implementing a `neo.rawio` Class is not required, but recommended. Several extractors (especially) for :code:`Sorting`
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**NOTE:** implementing a `neo.rawio` class is not required, but recommended. Several extractors (especially) for :code:`Sorting`
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objects are implemented directly in SpikeInterface and inherit from the base classes.
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As examples, see the `CompressedBinaryIblExtractor <https://github.com/SpikeInterface/spikeinterface/blob/0.96.1/spikeinterface/extractors/cbin_ibl.py>`_
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for a :py:class:`~spikeinterface.core.BaseRecording` object, or the `SpykingCircusSortingExtractor <https://github.com/SpikeInterface/spikeinterface/blob/0.96.1/spikeinterface/extractors/spykingcircusextractors.py>`_
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As examples, see the `IblRecordingExtractor <https://github.com/SpikeInterface/spikeinterface/blob/main/src/spikeinterface/extractors/iblextractors.py>`_
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for a :py:class:`~spikeinterface.core.BaseRecording` object, or the `SpykingCircusSortingExtractor <https://github.com/SpikeInterface/spikeinterface/blob/main/src/spikeinterface/extractors/spykingcircusextractors.py>`_
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for a a :py:class:`~spikeinterface.core.BaseSorting` object.
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@@ -309,7 +309,7 @@ Then, you can start creating a new class:
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class MySpikeSorter(BaseSorter):
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"""
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Brief description (optional)
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Brief description
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"""
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sorter_name = 'myspikesorter'
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def _check_apply_filter_in_params(cls, params):
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return False
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#  optional
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# optional
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# can be implemented in subclass to check if the filter will be applied
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@@ -388,10 +388,12 @@ Now you can start filling out the required methods:
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return sorting
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When your spike sorter class is implemented, you have to add it to the list of available spike sorters in the
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`sorterlist.py`. Then you need to write a test in **tests/test_myspikesorter.py**. In order to be tested, you can
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install the required packages by changing the **pyproject.toml**. Note that MATLAB based tests cannot be run at the moment,
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but we recommend testing the implementation locally.
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`sorterlist.py <https://github.com/SpikeInterface/spikeinterface/blob/main/src/spikeinterface/sorters/sorterlist.py>`_ .
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Then you need to write a test in **tests/test_myspikesorter.py**. In order to be tested, you can
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install the required packages by changing the `pyproject.toml <https://github.com/SpikeInterface/spikeinterface/blob/main/pyproject.toml>`_.
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Note that MATLAB based tests cannot be run at the moment,but we recommend testing the implementation locally.
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After this you need to add a block in **doc/sorters_info.rst** to describe your sorter.
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After this you need to add a block in `Install Sorters <https://github.com/SpikeInterface/spikeinterface/blob/main/doc/get_started/install_sorters.rst>`_
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to describe your sorter.
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Finally, make a pull request so we can review the code and incorporate into the sorters module of SpikeInterface!

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