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Author

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1		-XWiki.ldomide
	1	+XWiki.rominabaila

Content

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1		-Source code: [[https:~~/~~/github.com/the-virtual-brain/tvb-widgets>>url:https://github.com/the-virtual-brain/tvb-widgets]]
	1	+== Purpose ==
2	2
3		-Immediate testing here: [[https:~~/~~/lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20Widgets/REPO/tvb-widgets/notebooks>>url:https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20Widgets/REPO/tvb-widgets/notebooks]]
	3	+It is a Jupyter widget intended for the visualization of brain signals represented as time series.
4	4
5		-=== Purpose ===
6	6
7		-It is a Jupyter Widget intended for the visualization of brain signals represented as time series.
8		-
9	9	== Inputs ==
10	10
11		-Time series can be given as inputs in two forms:
	8	+It supports time series inputs of two types:
12	12
13	13	* TVB TimeSeries datatype
14	14	* Numpy arrays
15	15
16		-This widget supports 2D, 3D, and 4D arrays. In all three cases, there is a fixed shape that the TimeSeries widget expects:
	13	+The widget supports 2-, 3-, and 4-dimensional arrays. In all three cases, there is a fixed shape that the TimeSeries widget expects:
17	17
18	18	* for **2D**: (no_timepoints, no_channels)
19	19	* for **3D**: (no_timepoints, state_variable/mode, no_channels)
20	20	* for **4D**: (no_timepoints, state_variable, no_channels, mode)
21	21
22		-~* Note that the TVB TimeSeries datatype is always 4D and already has the expected shape.
	19	+~* Note that the TVB TimeSeries datatype is always is always 4D and already has the expected shape.
23	23
	21	+
24	24	== Requirements and installation ==
25	25
26		-Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and Jupyter extensions should be installed:
	24	+Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and  Jupyter Notebook extensions should be installed:
27	27
28	28	* **Libraries:**
29		-** [[mne>>https://mne.tools/0.24/install/index.html]] version 0.24
30	30	** [[ipympl>>https://github.com/matplotlib/ipympl#installation]]
31	31	* (((
32		-**Extensions:**
	29	+**Extensions:***
33	33
34	34	(% class="box" %)
35	35	(((
36	36	jupyter labextension install @jupyter-widgets/jupyterlab-manager
	34	+)))
37	37
	36	+* (% class="box" %)
	37	+(((
38	38	jupyter labextension install jupyter-matplotlib
39	39	)))
40	40	)))
41	41
42		-Then, to install the tvb-widgets library, just type:
	42	+Then, to install the tvb-widgets library just type:
43	43
44	44	(% class="box" %)
45	45	(((
46	46	pip install tvb-widgets
47	47	)))
48		-
49		-== API usage ==
50		-
51		-First, the correct matplotlib backend must be set, which enables the interaction with the TimeSeries widget, by running the following command:
52		-
53		-(% class="box" %)
54		-(((
55		-%matplotlib widget
56		-)))
57		-
58		- Then, the **TimeSeriesWidget** (from the tvb-widgets API) and the **//display//** function should be imported:
59		-
60		-(% class="box" %)
61		-(((
62		-from tvbwidgets.api import TimeSeriesWidget
63		-from IPython.core.display_functions import display
64		-)))
65		-
66		-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):
67		-
68		-(% class="box" %)
69		-(((
70		-tsw = TimeSeriesWidget()
71		-tsw.add_datatype(tsr)
72		-)))
73		-
74		-Finally, to display and interact with the TimeSeries widget, the **//get_widget//**// //method is used inside the //**display **//function:
75		-
76		-(% class="box" %)
77		-(((
78		-display(tsw)
79		-)))
80		-
81		-{{html}}
82		-<iframe src="https://drive.google.com/file/d/1g4ryY1VIFMUD14Mb6Dq_KVb0b2_XU4VX/preview" width="840" height="480" allow="autoplay"></iframe>
83		-{{/html}}