Wiki source code of Widget TimeSeries
Version 15.1 by rominabaila on 2022/04/12 11:31
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| author | version | line-number | content |
|---|---|---|---|
| 1 | == Purpose == | ||
| 2 | |||
| 3 | It is a Jupyter widget intended for the visualization of brain signals represented as time series. | ||
| 4 | |||
| 5 | |||
| 6 | == Inputs == | ||
| 7 | |||
| 8 | It supports time series inputs of two types: | ||
| 9 | |||
| 10 | * TVB TimeSeries datatype | ||
| 11 | * Numpy arrays | ||
| 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: | ||
| 14 | |||
| 15 | * for **2D**: (no_timepoints, no_channels) | ||
| 16 | * for **3D**: (no_timepoints, state_variable/mode, no_channels) | ||
| 17 | * for **4D**: (no_timepoints, state_variable, no_channels, mode) | ||
| 18 | |||
| 19 | ~* Note that the TVB TimeSeries datatype is always is always 4D and already has the expected shape. | ||
| 20 | |||
| 21 | |||
| 22 | == Requirements and installation == | ||
| 23 | |||
| 24 | Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and Jupyter Notebook extensions should be installed: | ||
| 25 | |||
| 26 | * **Libraries:** | ||
| 27 | ** [[ipympl>>https://github.com/matplotlib/ipympl#installation]] | ||
| 28 | * ((( | ||
| 29 | **Extensions:** | ||
| 30 | |||
| 31 | (% class="box" %) | ||
| 32 | ((( | ||
| 33 | jupyter labextension install @jupyter-widgets/jupyterlab-manager | ||
| 34 | |||
| 35 | jupyter labextension install jupyter-matplotlib | ||
| 36 | ))) | ||
| 37 | ))) | ||
| 38 | |||
| 39 | Then, to install the tvb-widgets library, just type: | ||
| 40 | |||
| 41 | (% class="box" %) | ||
| 42 | ((( | ||
| 43 | pip install tvb-widgets | ||
| 44 | ))) | ||
| 45 | |||
| 46 | |||
| 47 | == API usage == | ||
| 48 | |||
| 49 | First, the correct matplotlib backend must be set, which enables the interaction with the TimeSeries widget, by running the following command: | ||
| 50 | |||
| 51 | (% class="box" %) | ||
| 52 | ((( | ||
| 53 | %matplotlib widget | ||
| 54 | ))) | ||
| 55 | |||
| 56 | Then, the TimeSeries widget (from the tvb-widgets API) and the display function should be imported: | ||
| 57 | |||
| 58 | (% class="box" %) | ||
| 59 | ((( | ||
| 60 | from tvbwidgets.api import TimeSeriesWidget | ||
| 61 | from IPython.core.display_functions import display | ||
| 62 | ))) | ||
| 63 | |||
| 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): | ||
| 65 | |||
| 66 | (% class="box" %) | ||
| 67 | ((( | ||
| 68 | tsw = TimeSeriesWidget() | ||
| 69 | tsw.add_datatype(tsr) | ||
| 70 | ))) | ||
| 71 | |||
| 72 | Finally, to display and interact with the TimeSeries widget, the **//get_widget//**// //method is used inside the //**display **//function: | ||
| 73 | |||
| 74 | (% class="box" %) | ||
| 75 | ((( | ||
| 76 | display(tsw.get_widget()) | ||
| 77 | ))) | ||
| 78 | |||
| 79 | {{html}} | ||
| 80 | <iframe src="https://drive.google.com/file/d/1g4ryY1VIFMUD14Mb6Dq_KVb0b2_XU4VX/preview" width="840" height="480" allow="autoplay"></iframe> | ||
| 81 | {{/html}} |