Changes for page Widget TimeSeries
Last modified by ldomide on 2023/05/23 14:34
From version 37.1
edited by rominabaila
on 2023/05/15 13:58
on 2023/05/15 13:58
Change comment:
There is no comment for this version
To version 33.1
edited by rominabaila
on 2023/05/15 11:06
on 2023/05/15 11:06
Change comment:
There is no comment for this version
Summary
-
Page properties (1 modified, 0 added, 0 removed)
Details
- Page properties
-
- Content
-
... ... @@ -6,13 +6,13 @@ 6 6 7 7 == Purpose == 8 8 9 -It is a Jupyter LabWidget 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. 10 10 11 11 == Backends == 12 12 13 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 14 15 -Below you can see the TS widget with each backend option (first one using the matplotlib backend, second one using the plotly backend). 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 16 17 17 (% style="text-align:center" %) 18 18 [[image:matplotlib.png]] ... ... @@ -75,35 +75,29 @@ 75 75 %matplotlib widget 76 76 ))) 77 77 78 -Then, simply importthe **plot_timeseries** method,whichgivesyouaccesstotheTS widget:78 + Then, the **TimeSeriesWidget** (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 82 +from tvbwidgets.api import TimeSeriesWidget 83 +from IPython.core.display_functions import display 83 83 ))) 84 84 86 +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) 90 +tsw = TimeSeriesWidget() 91 +tsw.add_datatype(tsr) 93 93 ))) 94 94 95 - After runningthe codefromaboveinto a Jupyterell,you shouldseethe TS widgetcorrespondingothebackendyouselected.94 +Finally, to display and interact with the TimeSeries widget, the **//get_widget//**// //method is used inside the //**display **//function: 96 96 97 -== 1. TS widget with matplotlib and mne == 96 +(% class="box" %) 97 +((( 98 +display(tsw) 99 +))) 98 98 99 -As it was already mentioned, the matplotlib widget offers more advanced scientifical fearures. In the video below, you can see some of the functionalities that this backend provides, like: increasing/decreasing signal amplitude, selecting/deselecting certain signals, selecting different dimensions (state variable/mode) from the input data, navigating through the timeline, etc. 100 - 101 101 {{html}} 102 -<iframe width="840" height="480" src="https://www.youtube.com/embed/ hozEkVhkWeA" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>102 +<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> 103 103 {{/html}} 104 - 105 - 106 - 107 -== 1. TS widget with matplotlib and mne == 108 - 109 -As it was already mentioned, the matplotlib widget offers more advanced scientifical fearures. In the video below, you can see some of the functionalities that this backend provides, like increasing/decreasing signal amplitude, selecting/deselecting certain signals, selecting different dimensions (state variable/mode) from the input data, navigating through the timeline, etc.