Wiki source code of Widget TimeSeries
Version 32.1 by rominabaila on 2023/05/15 10:51
Hide last authors
| author | version | line-number | content |
|---|---|---|---|
 |
22.1 | 1 | Source code: [[https:~~/~~/github.com/the-virtual-brain/tvb-widgets>>url:https://github.com/the-virtual-brain/tvb-widgets]] |
| |
21.1 | 2 | |
| |
25.1 | 3 | This is part of a Pypi release: [[https:~~/~~/pypi.org/project/tvb-widgets/>>url:https://pypi.org/project/tvb-widgets/]] |
| |
21.1 | 4 | |
| |
25.1 | 5 | //**tvb-widgets**// is also already installed in the official image released for EBRAINS lab, where you can test it directly. |
| 6 | |||
| |
23.1 | 7 | == Purpose == |
| |
1.1 | 8 | |
| |
22.1 | 9 | It is a Jupyter Widget intended for the visualization of brain signals represented as time series. |
| |
5.1 | 10 | |
| |
32.1 | 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 | |||
| |
5.1 | 23 | == Inputs == |
| 24 | |||
| |
17.1 | 25 | Time series can be given as inputs in two forms: |
| |
6.1 | 26 | |
| 27 | * TVB TimeSeries datatype | ||
| 28 | * Numpy arrays | ||
| 29 | |||
| |
17.1 | 30 | This widget supports 2D, 3D, and 4D arrays. In all three cases, there is a fixed shape that the TimeSeries widget expects: |
| |
6.1 | 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 | |||
| |
17.1 | 36 | ~* Note that the TVB TimeSeries datatype is always 4D and already has the expected shape. |
| |
7.1 | 37 | |
| 38 | == Requirements and installation == | ||
| 39 | |||
| |
17.1 | 40 | Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and Jupyter extensions should be installed: |
| |
7.1 | 41 | |
| 42 | * **Libraries:** | ||
| |
20.1 | 43 | ** [[mne>>https://mne.tools/0.24/install/index.html]] version 0.24 |
| 44 | ** [[ipympl>>https://github.com/matplotlib/ipympl#installation]] | ||
| |
7.1 | 45 | * ((( |
| |
11.1 | 46 | **Extensions:** |
| |
7.1 | 47 | |
| 48 | (% class="box" %) | ||
| 49 | ((( | ||
| |
8.1 | 50 | jupyter labextension install @jupyter-widgets/jupyterlab-manager |
| |
7.1 | 51 | |
| |
8.1 | 52 | jupyter labextension install jupyter-matplotlib |
| |
7.1 | 53 | ))) |
| 54 | ))) | ||
| 55 | |||
| |
12.1 | 56 | Then, to install the tvb-widgets library, just type: |
| |
7.1 | 57 | |
| 58 | (% class="box" %) | ||
| 59 | ((( | ||
| 60 | pip install tvb-widgets | ||
| 61 | ))) | ||
| |
13.1 | 62 | |
| 63 | == API usage == | ||
| 64 | |||
| 65 | First, the correct matplotlib backend must be set, which enables the interaction with the TimeSeries widget, by running the following command: | ||
| 66 | |||
| 67 | (% class="box" %) | ||
| 68 | ((( | ||
| 69 | %matplotlib widget | ||
| 70 | ))) | ||
| 71 | |||
| |
17.1 | 72 | Then, the **TimeSeriesWidget** (from the tvb-widgets API) and the **//display//** function should be imported: |
| |
13.1 | 73 | |
| 74 | (% class="box" %) | ||
| 75 | ((( | ||
| 76 | from tvbwidgets.api import TimeSeriesWidget | ||
| 77 | from IPython.core.display_functions import display | ||
| 78 | ))) | ||
| 79 | |||
| 80 | 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): | ||
| 81 | |||
| 82 | (% class="box" %) | ||
| 83 | ((( | ||
| 84 | tsw = TimeSeriesWidget() | ||
| 85 | tsw.add_datatype(tsr) | ||
| 86 | ))) | ||
| 87 | |||
| 88 | Finally, to display and interact with the TimeSeries widget, the **//get_widget//**// //method is used inside the //**display **//function: | ||
| 89 | |||
| 90 | (% class="box" %) | ||
| 91 | ((( | ||
| |
19.1 | 92 | display(tsw) |
| |
13.1 | 93 | ))) |
| |
15.1 | 94 | |
| 95 | {{html}} | ||
| |
27.1 | 96 | <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> |
| |
15.1 | 97 | {{/html}} |