Widget TimeSeries

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Source code: [[https:~~/~~/github.com/the-virtual-brain/tvb-widgets>>url:https://github.com/the-virtual-brain/tvb-widgets]]

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This is part of a Pypi release: [[https:~~/~~/pypi.org/project/tvb-widgets/>>url:https://pypi.org/project/tvb-widgets/]]

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//**tvb-widgets**// is also already installed in the official image released for EBRAINS lab, where you can test it directly.

== Purpose ==

It is a Jupyter Widget intended for the visualization of brain signals represented as time series.

== Backends ==

Starting with //**tvb-widgets 1.5.0**, //the TS widget comes in 2 forms, corresponding to the 2 different libraries (we called them backends) used for plotting: **matplotlib **and **plotly**. The matplotlib backend, build on top of the **mne** library, offers more advanced scientifical features, while the plotly backend has a more appealing look and moves faster when talking about the basic interactions.

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Below you can see the TS widget with each backend option (first one using the matplotlib backend, the second one using the plotly backend).

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[[image:matplotlib.png]]

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[[image:plotly.png]]

== Inputs ==

Time series can be given as inputs in two forms:

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* TVB TimeSeries datatype

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* Numpy arrays

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This widget supports 2D, 3D, and 4D arrays. In all three cases, there is a fixed shape that the TimeSeries widget expects:

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* for **2D**: (no_timepoints, no_channels)

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* for **3D**: (no_timepoints, state_variable/mode, no_channels)

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* for **4D**: (no_timepoints, state_variable, no_channels, mode)

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~* Note that the TVB TimeSeries datatype is always 4D and already has the expected shape.

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== Requirements and installation ==

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Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and Jupyter extensions should be installed:

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* **Libraries:**

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** [[mne>>https://mne.tools/0.24/install/index.html]] version 0.24

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** [[ipympl>>https://github.com/matplotlib/ipympl#installation]]

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**Extensions:**

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jupyter labextension install @jupyter-widgets/jupyterlab-manager

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jupyter labextension install jupyter-matplotlib

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Then, to install the tvb-widgets library, just type:

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pip install tvb-widgets

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== API usage ==

First, the correct matplotlib backend must be set, which enables the interaction with the TimeSeries widget, by running the following command:

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%matplotlib widget

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Then, the **TimeSeriesWidget** (from the tvb-widgets API) and the **//display//** function should be imported:

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from tvbwidgets.api import TimeSeriesWidget

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from IPython.core.display_functions import display

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Assuming that the user has already created or imported a valid input, this is how the widget can be initialized and how an input can be assigned to it, using the //**add_datatype** //method (example below assumes that **//tsr// **is a TVB TimeSeries datatype):

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tsw = TimeSeriesWidget()

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tsw.add_datatype(tsr)

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)))

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