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        "author": "Ben Dichter",
        "author_email": "ben.dichter@catalystneuro.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Framework :: Jupyter",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7"
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        "description": "# NWB Widgets\nA library of widgets for visualization NWB data in a Jupyter notebook (or lab). The widgets allow you to navigate through the hierarchical structure of the NWB file and visualize specific data elements. It is designed to work out-of-the-box with NWB 2.0 files and to be easy to extend. \n\n[![PyPI version](https://badge.fury.io/py/nwbwidgets.svg)](https://badge.fury.io/py/nwbwidgets)\n[![codecov](https://codecov.io/gh/NeurodataWithoutBorders/nwb-jupyter-widgets/branch/master/graph/badge.svg)](https://codecov.io/gh/NeurodataWithoutBorders/nwb-jupyter-widgets)\n[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/NeurodataWithoutBorders/nwb-jupyter-widgets/master?filepath=examples%2FNWBWidgets-modality-demos.ipynb)\n\n\n## Installation\n```bash\npip install nwbwidgets\n```\n\n## Usage\n```python\nfrom pynwb import NWBHDF5IO\nfrom nwbwidgets import nwb2widget\n\nio = NWBHDF5IO('path/to/file.nwb', mode='r')\nnwb = io.read()\n\nnwb2widget(nwb)\n```\n\n## Demo\n![](https://drive.google.com/uc?export=download&id=1JtI2KtT8MielIMvvtgxRzFfBTdc41LiE)\n\n## How it works\nAll visualizations are controlled by the dictionary `neurodata_vis_spec`. The keys of this dictionary are pynwb neurodata types, and the values are functions that take as input that neurodata_type and output a visualization. The visualizations may be of type `Widget` or `matplotlib.Figure`. When you enter a neurodata_type instance into `nwb2widget`, it searches the `neurodata_vis_spec` for that instance's neurodata_type, progressing backwards through the parent classes of the neurodata_type to find the most specific neurodata_type in `neurodata_vis_spec`. Some of these types are containers for other types, and create accordian UI elements for its contents, which are then passed into the `neurodata_vis_spec` and rendered accordingly. \n\nInstead of supplying a function for the value of the `neurodata_vis_spec` dict, you may provide a `dict` or `OrderedDict` with string keys and function values. In this case, a tab structure is rendered, with each of the key/value pairs as an individual tab. All accordian and tab structures are rendered lazily- they are only called with that tab is selected. As a result, you can provide may tabs for a single data type without a worry. They will only be run if they are selected.\n\n## Extending\nTo extend NWBWidgets, all you need to a function that takes as input an instance of a specific neurodata_type class, and outputs a matplotlib figure or a jupyter widget.\n\n## Used in\n* [giocomo-lab-to-nwb](https://github.com/ben-dichter-consulting/giocomo-lab-to-nwb)\n* [buffalo-lab-data-to-nwb](https://github.com/ben-dichter-consulting/buffalo-lab-data-to-nwb)\n* [axel-lab-to-nwb](https://github.com/ben-dichter-consulting/axel-lab-to-nwb)\n\n\n",
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