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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		-
7	7	== Purpose ==
8	8
9		-It is a JupyterLab Widget intended for the visualization of brain signals represented as time series.
	3	+It is a Jupyter widget intended for the visualization of brain signals represented as time series.
10	10
11		-== Backends ==
12	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, 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		-
23	23	== Inputs ==
24	24
25		-Time series can be given as inputs in two forms:
	8	+It supports time series inputs of two types:
26	26
27	27	* TVB TimeSeries datatype
28	28	* Numpy arrays
29	29
30		-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:
31	31
32	32	* for **2D**: (no_timepoints, no_channels)
33	33	* for **3D**: (no_timepoints, state_variable/mode, no_channels)
34	34	* for **4D**: (no_timepoints, state_variable, no_channels, mode)
35	35
36		-~* 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.
37	37
	21	+
38	38	== Requirements and installation ==
39	39
	24	+Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and  Jupyter Notebook extensions should be installed:
40	40
41		-Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and Jupyter extensions should be installed:
42		-
43	43	* **Libraries:**
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
	27	+** [[ipympl>>https://github.com/matplotlib/ipympl#installation]]
49	49	* (((
50	50	**Extensions:**
51	51
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54	54	jupyter labextension install @jupyter-widgets/jupyterlab-manager
55	55
56	56	jupyter labextension install jupyter-matplotlib
57		-
58		-jupyter labextension install jupyterlab-plotly
59	59	)))
60	60	)))
61	61
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66	66	pip install tvb-widgets
67	67	)))
68	68
	46	+
69	69	== API usage ==
70	70
71	71	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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75	75	%matplotlib widget
76	76	)))
77	77
78		-Then, simply import the **plot_timeseries** method, which gives you access to the TS widget:
	56	+ Then, the TimeSeries widget (from the tvb-widgets API) and the display function should be imported:
79	79
80	80	(% class="box" %)
81	81	(((
82		-from tvbwidgets.api import plot_timeseries
	60	+from tvbwidgets.api import TimeSeriesWidget
	61	+from IPython.core.display_functions import display
83	83	)))
84	84
	64	+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):
85	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	88	(% class="box" %)
89	89	(((
90		-backend = 'plotly' # change to 'matplotlib' to see the other TS widget
91		-
92		-plot_timeseries(data=tsr, backend=backend)
	68	+tsw = TimeSeriesWidget()
	69	+tsw.add_datatype(tsr)
93	93	)))
94	94
95		-After running the code from above into a Jupyter cell, you should see the TS widget corresponding to the backend you selected.
	72	+Finally, to display and interact with the TimeSeries widget, the **//get_widget//**// //method is used inside the //**display **//function:
96	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}}
	74	+(% class="box" %)
	75	+(((
	76	+display(tsw.get_widget())
	77	+)))

matplotlib.png

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plotly.png

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