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Copy file name to clipboardExpand all lines: docs/index.rst
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HED Python tools
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================
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Python HEDTools
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===============
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Welcome to the HED Python tools documentation. This package provides comprehensive tools for working with Hierarchical Event Descriptors (HED) in Python.
Welcome to the Python HEDTools documentation! This package provides comprehensive tools for working with **Hierarchical Event Descriptors (HED)** - a standardized framework for annotating events and experimental metadata in neuroscience and beyond.
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What is HED?
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------------
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HED is a standardized vocabulary and annotation framework designed to systematically describe events experimental data, particularly neuroimaging and behavioral data. It's integrated into major neuroimaging standards:
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* `BIDS <https://bids.neuroimaging.io/>`_ (Brain Imaging Data Structure)
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* `NWB <https://www.nwb.org/>`_ (Neurodata Without Borders)
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Key features
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------------
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* **Validation**: Verify HED annotations against official schemas
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* **Analysis**: Search, filter, and summarize HED-annotated data
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* **BIDS integration**: Full support for BIDS dataset validation and processing
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* **NWB support**: Read and write HED annotations in NWB files using `ndx-hed <https://www.hedtags.org/ndx-hed>`_
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* **Multiple formats**: Work with JSON sidecars, TSV files, Excel spreadsheets
Copy file name to clipboardExpand all lines: examples/extract_json_template.ipynb
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"General strategy for machine-actionable annotation using HED in BIDS is to create a single `events.json` sidecar file in the BIDS dataset root directory.\n",
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"Ideally, this sidecar will contain all the annotations needed for users to understand and analyze the data.\n",
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"(See the [**BIDS annotation quickstart**](https://www.hed-resources.org/en/latest/BidsAnnotationQuickstart.html) for additional information on this strategy.)\n",
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"(See the [**BIDS annotation quickstart**](https://www.hedtags.org/hed-resources) for additional information on this strategy.)\n",
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"\n",
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"This notebook shows how to create a JSON sidecar template from the information in all the event files in a BIDS dataset. To use this notebook, substitute the specifics of your BIDS dataset for the following variables:\n",
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"Typical `skip_columns` include the `onset`, `duration`, and `sample` columns, which have well-defined meanings according to BIDS. The `value_columns` just require a single annotation, applicable to each value in the column.\n",
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"For additional information see the tutorial [**Create a JSON template**](https://www.hed-resources.org/en/latest/BidsAnnotationQuickstart.html#create-a-json-template) which illustrates the creation of a template from a single event file using the online tools.\n",
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"For additional information see the tutorial [**Create a JSON template**](https://hedtags.org/hed-resources/BidsAnnotationQuickstart.html#create-a-json-template) which illustrates the creation of a template from a single event file using the online tools.\n",
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"\n",
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"Additional information about this notebook can be found in [**Extract JSON template**](https://www.hed-resources.org/en/latest/HedPythonTools.html#extract-json-template) in the Python HEDTools user guide."
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"See [**Sidecar template extraction**](https://www.hedtags.org/hed-python/user_guide.html#sidecar-template-extraction) in the HEDTools documentation for an example of how to directly extract a template using command line tools."
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