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| author | version | line-number | content |
|---|---|---|---|
| 1 | TODO | ||
| 2 | |||
| 3 | == Purpose == | ||
| 4 | |||
| 5 | It is a Jupyter widget intended for visualization of the 3D data available for a patient: | ||
| 6 | |||
| 7 | * surfaces of different types (cortex, face, skull, etc) | ||
| 8 | * connectivity region centers | ||
| 9 | * sensors locations (SEEG, MEG, EEG) | ||
| 10 | |||
| 11 | == Inputs == | ||
| 12 | |||
| 13 | It supports the above data in the form of their corresponding TVB datatypes: | ||
| 14 | |||
| 15 | * Surface (CorticalSurface, FaceSurface, etc) | ||
| 16 | * Connectivity | ||
| 17 | * Sensors (SensorsInternal, SensorsMEG, SensorsEEG) | ||
| 18 | |||
| 19 | == Installation == | ||
| 20 | |||
| 21 | (% class="box" %) | ||
| 22 | ((( | ||
| 23 | pip install tvb-widgets | ||
| 24 | ))) | ||
| 25 | |||
| 26 | == API usage == | ||
| 27 | |||
| 28 | We need to first import the widget __API from tvbwidgets__// //package, together with the __TVB API __and the __display__ function: | ||
| 29 | |||
| 30 | (% class="box" %) | ||
| 31 | ((( | ||
| 32 | import tvbwidgets.api as api | ||
| 33 | |||
| 34 | from tvb.simulator.lab import * | ||
| 35 | |||
| 36 | from IPython.core.display_functions import display | ||
| 37 | ))) | ||
| 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: | ||
| 40 | |||
| 41 | (% class="box" %) | ||
| 42 | ((( | ||
| 43 | widget_3d = api.ThreeDWidget() | ||
| 44 | |||
| 45 | face = surfaces.FaceSurface().from_file() | ||
| 46 | |||
| 47 | face.configure() | ||
| 48 | |||
| 49 | widget_3d.add_datatype(face) | ||
| 50 | display(widget_3d) | ||
| 51 | ))) | ||
| 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}} | ||
| 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. | ||
| 58 | |||
| 59 | The **Config** object can be used to tweak the display options for each datatype. | ||
| 60 | |||
| 61 | In the code below, we add a **Connectivity** and SEEG **Sensors:** | ||
| 62 | |||
| 63 | (% class="box" %) | ||
| 64 | ((( | ||
| 65 | conn = connectivity.Connectivity().from_file() | ||
| 66 | |||
| 67 | conn.configure() | ||
| 68 | |||
| 69 | widget_3d.add_datatype(conn) | ||
| 70 | |||
| 71 | |||
| 72 | seeg = sensors.SensorsInternal().from_file() | ||
| 73 | |||
| 74 | seeg.configure() | ||
| 75 | |||
| 76 | widget_3d.add_datatype(seeg, api.Config(name='SEEG')) | ||
| 77 | ))) | ||
| 78 | |||
| 79 | We can also provide a **RegionMapping** to be used as colormap for a surface: | ||
| 80 | |||
| 81 | (% class="box" %) | ||
| 82 | ((( | ||
| 83 | reg_map = region_mapping.RegionMapping.from_file() | ||
| 84 | |||
| 85 | config = api.Config(name='Cortex') | ||
| 86 | |||
| 87 | config.add_region_mapping_as_cmap(reg_map) | ||
| 88 | |||
| 89 | |||
| 90 | cortex = surfaces.CorticalSurface().from_file() | ||
| 91 | |||
| 92 | cortex.configure() | ||
| 93 | |||
| 94 | widget_3d.add_datatype(cortex, config) | ||
| 95 | |||
| 96 | {{html}} | ||
| 97 | <iframe src=" https://drive.google.com/file/d/1PXsxLqydNDDORIK85cQaEgGt9QdWLcC7/preview" width="840" height="480" allow="autoplay"></iframe> | ||
| 98 | {{/html}} | ||
| 99 | ))) |