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1		-TODO
2		-! pip install -i tvb-widgets
3		-from tvbwidgets.api import SurfaceWidget
4		-from IPython.core.display_functions import display
5		-w3d = SurfaceWidget(...)
6		-display(w3d)
7		-
8		-{{html}}<iframe src=" https://drive.google.com/file/d/1PXsxLqydNDDORIK85cQaEgGt9QdWLcC7/preview" width="840" height="480" allow="autoplay"></iframe>{{/html}}
	1	+NOTE - Not yet released, but testable here
	2	+
	3	+[[https:~~/~~/lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20Widgets/REPO/tvb-widgets/notebooks>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20Widgets/REPO/tvb-widgets/notebooks]]
	4	+
	5	+== Purpose ==
	6	+
	7	+It is a Jupyter widget intended for visualization of the 3D data available for a patient:
	8	+
	9	+* surfaces of different types (cortex, face, skull, etc)
	10	+* connectivity region centers
	11	+* sensors locations (SEEG, MEG, EEG)
	12	+
	13	+== Inputs ==
	14	+
	15	+It supports the above data in the form of their corresponding TVB datatypes:
	16	+
	17	+* Surface (CorticalSurface, FaceSurface, etc)
	18	+* Connectivity
	19	+* Sensors (SensorsInternal, SensorsMEG, SensorsEEG)
	20	+
	21	+== Installation ==
	22	+
	23	+(% class="box" %)
	24	+(((
	25	+pip install tvb-widgets
	26	+)))
	27	+
	28	+== API usage ==
	29	+
	30	+We need to first import the widget __API from tvbwidgets__// //package, together with the __TVB API __and the __display__ function:
	31	+
	32	+(% class="box" %)
	33	+(((
	34	+import tvbwidgets.api as api
	35	+
	36	+from tvb.simulator.lab import *
	37	+
	38	+from IPython.core.display_functions import display
	39	+)))
	40	+
	41	+Then, we instantiate the **SurfaceWidget** and a **FaceSurface** datatype that we want to visualize. Using the //**add_datatype**// method we add the surface to our widget and __display__ the widget:
	42	+
	43	+(% class="box" %)
	44	+(((
	45	+widget = api.SurfaceWidget()
	46	+
	47	+face = surfaces.FaceSurface().from_file()
	48	+
	49	+face.configure()
	50	+
	51	+widget.add_datatype(face)
	52	+display(widget)
	53	+)))
	54	+
	55	+{{html}}
	56	+<iframe src="https://drive.google.com/file/d/1Egp9Lk-HGMATc9em6Kw_jSHmybTD2vzM/preview" width="840" height="480" allow="autoplay"></iframe>
	57	+{{/html}}
	58	+
	59	+Next, we can continue adding other datatypes to this widget, by calling //**add_datatype**// multiple times. A maximum of 10 datatypes are supported by this widget.
	60	+
	61	+The **Config** object can be used to tweak the display options for each datatype.
	62	+
	63	+In the code below, we add a **Connectivity** and SEEG **Sensors:**
	64	+
	65	+(% class="box" %)
	66	+(((
	67	+conn = connectivity.Connectivity().from_file()
	68	+
	69	+conn.configure()
	70	+
	71	+widget.add_datatype(conn)
	72	+
	73	+
	74	+seeg = sensors.SensorsInternal().from_file()
	75	+
	76	+seeg.configure()
	77	+
	78	+widget.add_datatype(seeg, api.SurfaceWidgetConfig(name='SEEG'))
	79	+)))
	80	+
	81	+{{html}}
	82	+<iframe src="https://drive.google.com/file/d/1vFqqzXle8VGcHaLB-OdE-6BdetK9aJ1T/preview" width="840" height="480" allow="autoplay"></iframe>
	83	+{{/html}}
	84	+
	85	+We can also provide a **RegionMapping** to be used as colormap for a surface:
	86	+
	87	+(% class="box" %)
	88	+(((
	89	+reg_map = region_mapping.RegionMapping.from_file()
	90	+
	91	+config = api.SurfaceWidgetConfig(name='Cortex')
	92	+
	93	+config.add_region_mapping_as_cmap(reg_map)
	94	+
	95	+
	96	+cortex = surfaces.CorticalSurface().from_file()
	97	+
	98	+cortex.configure()
	99	+
	100	+widget.add_datatype(cortex, config)
	101	+)))
	102	+
	103	+{{html}}
	104	+<iframe src="https://drive.google.com/file/d/1z2yEuQWUT2Poxh63adYbBdhKPcWGskex/preview" width="840" height="480" allow="autoplay"></iframe>
	105	+{{/html}}