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1		-XWiki.ldomide
	1	+XWiki.rominabaila

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1		-! pip install -i tvb-widgets
	1	+Source code: [[https:~~/~~/github.com/the-virtual-brain/tvb-widgets>>url:https://github.com/the-virtual-brain/tvb-widgets]]
2	2
3		-from tvbwidgets.api import TimeseriesWidget
	3	+This is part of a Pypi release: [[https:~~/~~/pypi.org/project/tvb-widgets/>>url:https://pypi.org/project/tvb-widgets/]]
4	4
	5	+//**tvb-widgets**// is also already installed in the official image released for EBRAINS lab, where you can test it directly.
	6	+
	7	+== Purpose ==
	8	+
	9	+It is a Jupyter Widget intended for the visualization of brain signals represented as time series.
	10	+
	11	+== Inputs ==
	12	+
	13	+Time series can be given as inputs in two forms:
	14	+
	15	+* TVB TimeSeries datatype
	16	+* Numpy arrays
	17	+
	18	+This widget supports 2D, 3D, and 4D arrays. In all three cases, there is a fixed shape that the TimeSeries widget expects:
	19	+
	20	+* for **2D**: (no_timepoints, no_channels)
	21	+* for **3D**: (no_timepoints, state_variable/mode, no_channels)
	22	+* for **4D**: (no_timepoints, state_variable, no_channels, mode)
	23	+
	24	+~* Note that the TVB TimeSeries datatype is always 4D and already has the expected shape.
	25	+
	26	+== Requirements and installation ==
	27	+
	28	+Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and Jupyter extensions should be installed:
	29	+
	30	+* **Libraries:**
	31	+** [[mne>>https://mne.tools/0.24/install/index.html]] version 0.24
	32	+** [[ipympl>>https://github.com/matplotlib/ipympl#installation]]
	33	+* (((
	34	+**Extensions:**
	35	+
	36	+(% class="box" %)
	37	+(((
	38	+jupyter labextension install @jupyter-widgets/jupyterlab-manager
	39	+
	40	+jupyter labextension install jupyter-matplotlib
	41	+)))
	42	+)))
	43	+
	44	+Then, to install the tvb-widgets library, just type:
	45	+
	46	+(% class="box" %)
	47	+(((
	48	+pip install tvb-widgets
	49	+)))
	50	+
	51	+== API usage ==
	52	+
	53	+First, the correct matplotlib backend must be set, which enables the interaction with the TimeSeries widget, by running the following command:
	54	+
	55	+(% class="box" %)
	56	+(((
	57	+%matplotlib widget
	58	+)))
	59	+
	60	+ Then, the **TimeSeriesWidget** (from the tvb-widgets API) and the **//display//** function should be imported:
	61	+
	62	+(% class="box" %)
	63	+(((
	64	+from tvbwidgets.api import TimeSeriesWidget
5	5	from IPython.core.display_functions import display
	66	+)))
6	6
7		-tw = TimeseriesWidget(...)
	68	+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):
8	8
9		-{{{display(tw.get_widget())}}}
	70	+(% class="box" %)
	71	+(((
	72	+tsw = TimeSeriesWidget()
	73	+tsw.add_datatype(tsr)
	74	+)))
10	10
11		-{{{
12		- }}}
	76	+Finally, to display and interact with the TimeSeries widget, the **//get_widget//**// //method is used inside the //**display **//function:
13	13
14		-
	78	+(% class="box" %)
	79	+(((
	80	+display(tsw)
	81	+)))
	82	+
	83	+{{html}}
	84	+<iframe width="840" height="480" src="https://www.youtube.com/embed/VmueiXMxbVk" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
	85	+{{/html}}

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