Changes for page Widget 3D Head
Last modified by paulapopa on 2025/05/30 15:03
Summary
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Page properties (2 modified, 0 added, 0 removed)
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... ... @@ -1,18 +1,25 @@ 1 - TODO - Notyetreleased!1 +Source code: [[https:~~/~~/github.com/the-virtual-brain/tvb-widgets>>https://github.com/the-virtual-brain/tvb-widgets]] 2 2 3 +This is part of a Pypi release: [[https:~~/~~/pypi.org/project/tvb-widgets/>>https://pypi.org/project/tvb-widgets/]] 4 + 5 +//**tvb-widgets**// is also already installed in the official image released for EBRAINS lab, where you can test it directly. 6 + 3 3 == Purpose == 4 4 5 -It is a Jupyter widget intended for visualization of the 3D data available for a patient: 9 +It is a Jupyter widget intended for visualization of the 3D Head data available for a patient: 6 6 7 7 * surfaces of different types (cortex, face, skull, etc) 8 -* connectivity region centers 12 +* connectivity region centers and edges 9 9 * sensors locations (SEEG, MEG, EEG) 10 10 15 +On cortical surfaces, it can also display region parcellation. 16 + 11 11 == Inputs == 12 12 13 13 It supports the above data in the form of their corresponding TVB datatypes: 14 14 15 15 * Surface (CorticalSurface, FaceSurface, etc) 22 +* Parcellation (RegionMapping) 16 16 * Connectivity 17 17 * Sensors (SensorsInternal, SensorsMEG, SensorsEEG) 18 18 ... ... @@ -27,77 +27,77 @@ 27 27 28 28 We need to first import the widget __API from tvbwidgets__// //package, together with the __TVB API __and the __display__ function: 29 29 30 -(% class="box" %) 31 -((( 37 +{{code language="python" layout="LINENUMBERS"}} 32 32 import tvbwidgets.api as api 33 - 34 34 from tvb.simulator.lab import * 40 +from IPython.core.display_functions import display 41 +{{/code}} 35 35 36 -from IPython.core.display_functions import display 37 -))) 43 +Then, there are 2 options to work with the widget: 38 38 39 -Then, we instantiate the **ThreeDWidget** 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: 45 +1. Use a file browser to load the data and automatically display it 46 +1. Use directly the API to load the data and display it 40 40 41 -(% class="box" %) 42 -((( 43 -widget_3d = api.ThreeDWidget() 48 +For the first option, you have to run the following 2 lines of code in a notebook cell and then just use the UI controls: 44 44 45 -face = surfaces.FaceSurface().from_file() 50 +{{code language="python" layout="LINENUMBERS"}} 51 +widget = api.HeadBrowser() 52 +display(widget) 53 +{{/code}} 46 46 47 -face.configure() 48 48 49 -widget_3d.add_datatype(face) 50 -display(widget_3d) 51 -))) 56 +For the second option, the API is described below: 52 52 53 -{{html}} 54 -<iframe src="https://drive.google.com/file/d/1Egp9Lk-HGMATc9em6Kw_jSHmybTD2vzM/preview" width="840" height="480" allow="autoplay"></iframe> 55 -{{/html}} 58 +In a cell, we load the data using the TVB API: 56 56 57 -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 +{{code language="python" layout="LINENUMBERS"}} 61 +surface = surfaces.Surface.from_file() 62 +surface.configure() 58 58 59 -The **Config** object can be used to tweak the display options for each datatype. 64 +face = surfaces.Surface.from_file('face_8614.zip') 65 +face.configure() 60 60 61 - In thecodebelow, weadd a **Connectivity**and SEEG **Sensors:**67 +reg_map = region_mapping.RegionMapping.from_file() 62 62 63 -(% class="box" %) 64 -((( 65 -conn = connectivity.Connectivity().from_file() 66 - 69 +conn = connectivity.Connectivity.from_file() 67 67 conn.configure() 68 68 69 -widget_3d.add_datatype(conn) 72 +seeg = sensors.SensorsInternal.from_file() 73 +seeg.configure() 74 +{{/code}} 70 70 76 +Then we prepare the **HeadWidget** for display: 71 71 72 -seeg = sensors.SensorsInternal().from_file() 78 +{{code language="python" layout="LINENUMBERS"}} 79 +widget = api.HeadWidget([face, conn, seeg]) 80 +display(widget) 81 +{{/code}} 73 73 74 - seeg.configure()83 +[[image:head.png]] 75 75 76 -widget_3d.add_datatype(seeg, api.Config(name='SEEG')) 77 -))) 85 +Next, we can continue adding other datatypes to this widget, by calling //**add_datatype**// multiple times. 78 78 79 -{{html}} 80 -<iframe src="https://drive.google.com/file/d/1vFqqzXle8VGcHaLB-OdE-6BdetK9aJ1T/preview" width="840" height="480" allow="autoplay"></iframe> 81 -{{/html}} 87 +In the code below, we add the **CorticalSurface** with a **RegionMapping** as parcellation**:** 82 82 83 -We can also provide a **RegionMapping** to be used as colormap for a surface: 89 +{{code language="python" layout="LINENUMBERS"}} 90 +widget.add_datatype(surface, reg_map) 91 +{{/code}} 84 84 85 -(% class="box" %) 86 -((( 87 -reg_map = region_mapping.RegionMapping.from_file() 93 +[[image:cort.png]] 88 88 89 -config = api.Config(name='Cortex') 90 90 91 -con fig.add_region_mapping_as_cmap(reg_map)96 +In the upper-right corner, a menu is displayed. This will allow us to control what we want to visualize. For example, I can hide the head in order to get a better view of the cortical surface: 92 92 93 93 94 -cortex = surfaces.CorticalSurface().from_file() 95 95 96 -c ortex.configure()100 +I can rotate the surface and zoom in/out: 97 97 98 -widget_3d.add_datatype(cortex, config) 99 -))) 102 +[[image:parcel.png]] 100 100 101 -{{html}} 102 -<iframe src="https://drive.google.com/file/d/1z2yEuQWUT2Poxh63adYbBdhKPcWGskex/preview" width="840" height="480" allow="autoplay"></iframe> 103 -{{/html}} 104 +I could also make it transparent to visualize the connectivity centers and their edges: 105 + 106 +[[image:conncenters.png]] 107 + 108 +Also, I can hide the connectivity and display only the SEEG sensors: 109 + 110 +[[image:seeg.png]]
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