Developer’s guide
All 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 object. The visualizations may be of type ipywidgets.widgets.widget.Widget
, matplotlib.Figure
or plotly.graph_objects.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 accordion UI elements for its contents, which are then passed into the neurodata_vis_spec
and rendered accordingly.
Instead 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 accordion 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.
Extending and creating new Widgets
To 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