Summary

• Page properties (2 modified, 0 added, 0 removed)
• Attachments (0 modified, 2 added, 0 removed)
  • matplotlib.png
  • plotly.png

Details

Page properties

Author

...	...	@@ -1,1 +1,1 @@
1		-XWiki.ldomide
	1	+XWiki.rominabaila

Content

...	...	@@ -1,11 +1,25 @@
1	1	Source code: [[https:~~/~~/github.com/the-virtual-brain/tvb-widgets>>url:https://github.com/the-virtual-brain/tvb-widgets]]
2	2
3		-Immediate testing: [[https:~~/~~/lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20Widgets/REPO/tvb-widgets/notebooks/TimeSeriesTVB.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20Widgets/REPO/tvb-widgets/notebooks/TimeSeriesTVB.ipynb]] or here: [[https:~~/~~/lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20Widgets/REPO/tvb-widgets/notebooks/TimeSeriesArray.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20Widgets/REPO/tvb-widgets/notebooks/TimeSeriesArray.ipynb]]
	3	+This is part of a Pypi release: [[https:~~/~~/pypi.org/project/tvb-widgets/>>url:https://pypi.org/project/tvb-widgets/]]
4	4
	5	+//**tvb-widgets**// is also already installed in the official image released for EBRAINS lab, where you can test it directly.
	6	+
5	5	== Purpose ==
6	6
7	7	It is a Jupyter Widget intended for the visualization of brain signals represented as time series.
8	8
	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	+
9	9	== Inputs ==
10	10
11	11	Time series can be given as inputs in two forms:
...	...	@@ -23,11 +23,15 @@
23	23
24	24	== Requirements and installation ==
25	25
	40	+
26	26	Before installing the tvb-widgets library containing the TimeSeries widget, the following python libraries and Jupyter extensions should be installed:
27	27
28	28	* **Libraries:**
29		-** [[mne>>https://mne.tools/0.24/install/index.html]] version 0.24
30		-** [[ipympl>>https://github.com/matplotlib/ipympl#installation]]
	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
31	31	* (((
32	32	**Extensions:**
33	33
...	...	@@ -36,6 +36,8 @@
36	36	jupyter labextension install @jupyter-widgets/jupyterlab-manager
37	37
38	38	jupyter labextension install jupyter-matplotlib
	57	+
	58	+jupyter labextension install jupyterlab-plotly
39	39	)))
40	40	)))
41	41
...	...	@@ -55,29 +55,26 @@
55	55	%matplotlib widget
56	56	)))
57	57
58		- Then, the **TimeSeriesWidget** (from the tvb-widgets API) and the **//display//** function should be imported:
	78	+Then, simply import the **plot_timeseries** method, which gives you access to the TS widget:
59	59
60	60	(% class="box" %)
61	61	(((
62		-from tvbwidgets.api import TimeSeriesWidget
63		-from IPython.core.display_functions import display
	82	+from tvbwidgets.api import plot_timeseries
64	64	)))
65	65
66		-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):
67	67
	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	+
68	68	(% class="box" %)
69	69	(((
70		-tsw = TimeSeriesWidget()
71		-tsw.add_datatype(tsr)
	90	+backend = 'plotly' # change to 'matplotlib' to see the other TS widget
	91	+
	92	+plot_timeseries(data=tsr, backend=backend)
72	72	)))
73	73
74		-Finally, to display and interact with the TimeSeries widget, the **//get_widget//**// //method is used inside the //**display **//function:
	95	+After running the code from above into a Jupyter cell, you should see the TS widget corresponding to the backend you selected.
75	75
76		-(% class="box" %)
77		-(((
78		-display(tsw)
79		-)))
80	80
81	81	{{html}}
82		-<iframe src="https://drive.google.com/file/d/1g4ryY1VIFMUD14Mb6Dq_KVb0b2_XU4VX/preview" width="840" height="480" allow="autoplay"></iframe>
	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>
83	83	{{/html}}

matplotlib.png

Author

...	...	@@ -1,0 +1,1 @@
	1	+XWiki.rominabaila

Size

...	...	@@ -1,0 +1,1 @@
	1	+184.9 KB

Content

plotly.png

Author

...	...	@@ -1,0 +1,1 @@
	1	+XWiki.rominabaila

Size

...	...	@@ -1,0 +1,1 @@
	1	+351.7 KB

Content