Wiki source code of Widget TimeSeries
Version 34.1 by rominabaila on 2023/05/15 11:24
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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 | == Purpose == | ||
8 | |||
9 | It is a Jupyter Widget intended for the visualization of brain signals represented as time series. | ||
10 | |||
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, 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 | == Inputs == | ||
24 | |||
25 | Time series can be given as inputs in two forms: | ||
26 | |||
27 | * TVB TimeSeries datatype | ||
28 | * Numpy arrays | ||
29 | |||
30 | This widget supports 2D, 3D, and 4D arrays. In all three cases, there is a fixed shape that the TimeSeries widget expects: | ||
31 | |||
32 | * for **2D**: (no_timepoints, no_channels) | ||
33 | * for **3D**: (no_timepoints, state_variable/mode, no_channels) | ||
34 | * for **4D**: (no_timepoints, state_variable, no_channels, mode) | ||
35 | |||
36 | ~* Note that the TVB TimeSeries datatype is always 4D and already has the expected shape. | ||
37 | |||
38 | == Requirements and installation == | ||
39 | |||
40 | |||
41 | Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and Jupyter extensions should be installed: | ||
42 | |||
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 | ||
49 | * ((( | ||
50 | **Extensions:** | ||
51 | |||
52 | (% class="box" %) | ||
53 | ((( | ||
54 | jupyter labextension install @jupyter-widgets/jupyterlab-manager | ||
55 | |||
56 | jupyter labextension install jupyter-matplotlib | ||
57 | |||
58 | jupyter labextension install jupyterlab-plotly | ||
59 | ))) | ||
60 | ))) | ||
61 | |||
62 | Then, to install the tvb-widgets library, just type: | ||
63 | |||
64 | (% class="box" %) | ||
65 | ((( | ||
66 | pip install tvb-widgets | ||
67 | ))) | ||
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}} |