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  • matplotlib.png
  • plotly.png

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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]]
	2	+
	3	+This is part of a Pypi release: [[https:~~/~~/pypi.org/project/tvb-widgets/>>url:https://pypi.org/project/tvb-widgets/]]
	4	+
	5	+//**tvb-widgets**// is also already installed in the official image released for EBRAINS lab, where you can test it directly.
	6	+
1	1	== Purpose ==
2	2
3		-It is a Jupyter widget intended for the visualization of brain signals represented as time series.
	9	+It is a JupyterLab Widget intended for the visualization of brain signals represented as time series.
4	4
	11	+== Backends ==
	12	+
	13	+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.
	14	+
	15	+Below you can see the TS widget with each backend option (first one using the matplotlib backend, second one using the plotly backend).
	16	+
	17	+(% style="text-align:center" %)
	18	+[[image:matplotlib.png]]
	19	+
	20	+(% style="text-align:center" %)
	21	+[[image:plotly.png]]
	22	+
5	5	== Inputs ==
6	6
7	7	Time series can be given as inputs in two forms:
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19	19
20	20	== Requirements and installation ==
21	21
	40	+
22	22	Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and Jupyter extensions should be installed:
23	23
24	24	* **Libraries:**
25		-** mne, [[ipympl>>https://github.com/matplotlib/ipympl#installation]]
	44	+** [[mne>>https://mne.tools/stable/index.html]] >= 1.0
	45	+** [[matplotlib>>https://matplotlib.org/3.5.0/index.html]]
	46	+** [[plotly>>https://plotly.com/python/]] == 5.14.0
	47	+** [[ipywidgets>>https://ipywidgets.readthedocs.io/en/7.x/]] == 7.7.2
	48	+** [[ipympl>>https://github.com/matplotlib/ipympl#installation]] >= 0.8.5
26	26	* (((
27	27	**Extensions:**
28	28
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31	31	jupyter labextension install @jupyter-widgets/jupyterlab-manager
32	32
33	33	jupyter labextension install jupyter-matplotlib
	57	+
	58	+jupyter labextension install jupyterlab-plotly
34	34	)))
35	35	)))
36	36
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50	50	%matplotlib widget
51	51	)))
52	52
53		- Then, the **TimeSeriesWidget** (from the tvb-widgets API) and the **//display//** function should be imported:
	78	+Then, simply import the **plot_timeseries** method, which gives you access to the TS widget:
54	54
55	55	(% class="box" %)
56	56	(((
57		-from tvbwidgets.api import TimeSeriesWidget
58		-from IPython.core.display_functions import display
	82	+from tvbwidgets.api import plot_timeseries
59	59	)))
60	60
61		-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):
62	62
	86	+Assuming that the user has already created or imported a valid input, this is how the widget can be initialized and displayed (example below assumes that **tsr  **is a TVB TimeSeries datatype):
	87	+
63	63	(% class="box" %)
64	64	(((
65		-tsw = TimeSeriesWidget()
66		-tsw.add_datatype(tsr)
	90	+backend = 'plotly' # change to 'matplotlib' to see the other TS widget
	91	+
	92	+plot_timeseries(data=tsr, backend=backend)
67	67	)))
68	68
69		-Finally, to display and interact with the TimeSeries widget, the **//get_widget//**// //method is used inside the //**display **//function:
	95	+After running the code from above into a Jupyter cell, you should see the TS widget corresponding to the backend you selected.
70	70
71		-(% class="box" %)
72		-(((
73		-display(tsw)
74		-)))
	97	+== 1. TS Widget with matplotlib and mne ==
75	75
	99	+As it was already mentioned, the matplotlib widget offers more advanced scientifical fearures. In the video below, you can see some of the functionalities that this backend provides, like: increasing/decreasing signal amplitude, selecting/deselecting certain signals, selecting different dimensions (state variable/mode) from the input data, navigating through the timeline, etc.
	100	+
76	76	{{html}}
77		-<iframe src="https://drive.google.com/file/d/1g4ryY1VIFMUD14Mb6Dq_KVb0b2_XU4VX/preview" width="840" height="480" allow="autoplay"></iframe>
	102	+<iframe width="840" height="480" src="https://www.youtube.com/embed/hozEkVhkWeA" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
78	78	{{/html}}
	104	+
	105	+== 2. TS Widget with plotly ==
	106	+
	107	+Starting with //**tvb-widgets version 1.5.0**//, we introduced a second TS Widget, which uses the **plotly.py** library to create the interactive plot. Below you can watch small tutorials on how to use and interact with this widget.
	108	+
	109	+=== 2.1. Moving through the timeline and channels list ===
	110	+
	111	+{{html}}
	112	+<iframe width="840" height="480" src="https://www.youtube.com/embed/nZYZxHui-Ao" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
	113	+{{/html}}
	114	+
	115	+== 2. TS Widget with plotly ==
	116	+
	117	+Starting with //**tvb-widgets version 1.5.0**//, we introduced a second TS Widget, which uses the **plotly.py** library to create the interactive plot. Below you can watch small tutorials on how to use and interact with this widget.
	118	+
	119	+=== 2.1. Moving through the timeline and channels list ===

matplotlib.png

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