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  • plotly.png

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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 Jupyter Widget intended for the visualization of brain signals represented as time series.
4	4
	11	+== Backends ==
5	5
	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, the 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	+
6	6	== Inputs ==
7	7
8		-It supports time series inputs of two types:
	25	+Time series can be given as inputs in two forms:
9	9
10	10	* TVB TimeSeries datatype
11	11	* Numpy arrays
12	12
13		-The widget supports 2-, 3-, and 4-dimensional arrays. In all three cases, there is a fixed shape that the TimeSeries widget expects:
	30	+This widget supports 2D, 3D, and 4D arrays. In all three cases, there is a fixed shape that the TimeSeries widget expects:
14	14
15	15	* for **2D**: (no_timepoints, no_channels)
16	16	* for **3D**: (no_timepoints, state_variable/mode, no_channels)
17	17	* for **4D**: (no_timepoints, state_variable, no_channels, mode)
18	18
19		-~* Note that the TVB TimeSeries datatype is always is always 4D and already has the expected shape.
	36	+~* Note that the TVB TimeSeries datatype is always 4D and already has the expected shape.
20	20
21		-
22	22	== Requirements and installation ==
23	23
24		-Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and  Jupyter Notebook extensions should be installed:
25	25
	41	+Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and Jupyter extensions should be installed:
	42	+
26	26	* **Libraries:**
27		-** [[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
28	28	* (((
29	29	**Extensions:**
30	30
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33	33	jupyter labextension install @jupyter-widgets/jupyterlab-manager
34	34
35	35	jupyter labextension install jupyter-matplotlib
	57	+
	58	+jupyter labextension install jupyterlab-plotly
36	36	)))
37	37	)))
38	38
39		-Then, to install the tvb-widgets library just type:
	62	+Then, to install the tvb-widgets library, just type:
40	40
41	41	(% class="box" %)
42	42	(((
43	43	pip install tvb-widgets
44	44	)))
	68	+
	69	+== API usage ==
	70	+
	71	+First, the correct matplotlib backend must be set, which enables the interaction with the TimeSeries widget, by running the following command:
	72	+
	73	+(% class="box" %)
	74	+(((
	75	+%matplotlib widget
	76	+)))
	77	+
	78	+Then, simply import the **plot_timeseries** method, which gives you access to the TS widget:
	79	+
	80	+(% class="box" %)
	81	+(((
	82	+from tvbwidgets.api import plot_timeseries
	83	+)))
	84	+
	85	+
	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	+
	88	+(% class="box" %)
	89	+(((
	90	+backend = 'plotly' # change to 'matplotlib' to see the other TS widget
	91	+
	92	+plot_timeseries(data=tsr, backend=backend)
	93	+)))
	94	+
	95	+After running the code from above into a Jupyter cell, you should see the TS widget corresponding to the backend you selected.
	96	+
	97	+
	98	+{{html}}
	99	+<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>
	100	+{{/html}}

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