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@jourdain
jourdain committed Feb 3, 2021
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Expand Up @@ -440,7 +440,7 @@ Then we have the standard representation set or properties with their defaults:

### PointCloudRepresentation

The __PointCloudRepresentation__ is just a helper using the following structure to streamline rendering a point cloud dataset.
The __PointCloudRepresentation__ is just a helper using the following structure to streamline rendering a point cloud dataset. The code snippet below is not fully accurate but it should provide you with some understanding of the kind of simplification that is happening under the hood.

```python
def PointCloudRepresentation(**kwargs):
Expand Down Expand Up @@ -475,38 +475,39 @@ The set of convinient properties are as follow:

### VolumeDataRepresentation

The __VolumeDataRepresentation__ is just a helper using the following structure to streamline rendering a volume.

```html
<VolumeRepresentation
id={props.id}
colorMapPreset={props.colorMapPreset}
colorDataRange={props.colorDataRange}
property={props.property}
mapper={props.mapper}
volume={props.volume}
>
{props.volumeController && (
<VolumeController
rescaleColorMap={props.rescaleColorMap}
size={props.controllerSize}
/>
)}
<ImageData
dimensions={props.dimensions}
origin={props.origin}
spacing={props.spacing}
>
<PointData>
<DataArray
registration='setScalars'
numberOfComponents={nbComponents}
values={values}
type={type}
/>
</PointData>
</ImageData>
</VolumeRepresentation>
The __VolumeDataRepresentation__ is just a helper using the following structure to streamline rendering a volume. The code snippet below is not fully accurate but it should provide you with some understanding of the kind of simplification that is happening under the hood.

```python
def VolumeDataRepresentation(**kwargs):
return dash_vtk.VolumeRepresentation(
id=kwargs.get('id'),
colorMapPreset=kwargs.get('colorMapPreset'),
colorDataRange=kwargs.get('colorDataRange'),
property=kwargs.get('property'),
mapper=kwargs.get('mapper'),
volume=kwargs.get('volume'),
children=[
dash_vtk.VolumeController(
rescaleColorMap=kwargs.get('rescaleColorMap'),
size=kwargs.get('size'),
),
dash_vtk.ImageData(
dimensions=kwargs.get('dimensions'),
origin=kwargs.get('origin'),
spacing=kwargs.get('spacing'),
children=[
dash_vtk.PointData([
dash_vtk.DataArray(
registration='setScalars',
values=kwargs.get('scalars'),
)
])
],
),
],
)
],
)
```

The set of convinient properties are as follow:
Expand All @@ -529,12 +530,18 @@ The set of convinient properties are as follow:

This element is a helper on top of __PolyData__ which has a Python helper function that goes with it which will help you map a __vtkDataSet__ into a single property of the __Mesh__ element.

```html
<PolyData {...props.state.mesh}>
<{props.state.field.location}>
<DataArray {...props.state.field} />
</{props.state.field.location}>
</PolyData>
```py
def Mesh(**kwargs):
return dash_vtk.PolyData(
**kwargs.get('state').get('mesh'),
children=[
dash_vtk.[kwargs.get('state').get('field').get('location')]([
dash_vtk.DataArray(
**kwargs.get('state').get('field'),
)
])
]
)
```

The __Mesh__ element expect a single __state__ property that is internaly split into 2 elements to represent the geometry and the field that you want to optionally attach to your mesh. The structure could be defined as follow:
Expand All @@ -558,12 +565,18 @@ The __Mesh__ element expect a single __state__ property that is internaly split

This element is a helper on top of __ImageData__ which has a Python helper function that goes with it which will help you map a __vtkImageData__ into a single property of the __Volume__ element.

```html
<ImageData {...props.state.image}>
<PointData>
<DataArray {...props.state.field} />
</PointData>
</ImageData>
```py
def Volume(**kwargs):
return dash_vtk.ImageData(
**kwargs.get('state').get('image'),
children=[
dash_vtk.PointData([
dash_vtk.DataArray(
**kwargs.get('state').get('field'),
)
])
]
)
```

The __Volume__ element expect a single __state__ property that is internaly split into 2 elements to represent the geometry and the field that you want to optionally attach to your mesh. The structure could be defined as follow:
Expand Down Expand Up @@ -797,32 +810,32 @@ Then we made several example using plain VTK for both a CFD example and some med

[dash_vtk](https://github.com/plotly/dash-vtk/blob/master/demos/pyvista-point-cloud/app.py) | [PyVista](https://docs.pyvista.org/examples/00-load/create-point-cloud.html)

![Preview](../../demos/pyvista-point-cloud/demo.jpg)
![Preview](../demos/pyvista-point-cloud/demo.jpg)

### Terrain following mesh

[dash_vtk](https://github.com/plotly/dash-vtk/blob/master/demos/pyvista-terrain-following-mesh/app.py) | [PyVista](https://docs.pyvista.org/examples/00-load/terrain-mesh.html)
![Preview](../../demos/pyvista-terrain-following-mesh/demo.jpg)
![Preview](../demos/pyvista-terrain-following-mesh/demo.jpg)

### VTK dynamic streamlines Example

This example leverage plain VTK on the server side while providing UI controls in __dash__ and leverage __dash_vtk__ to enable local rendering of dynamically computed streamlines inside a wind-tunnel.

[dash_vtk](https://github.com/plotly/dash-vtk/blob/master/demos/usage-vtk-cfd/app.py)

![CFD Preview](../../demos/usage-vtk-cfd/demo.jpg)
![CFD Preview](../demos/usage-vtk-cfd/demo.jpg)

### Medical examples

[Real medical image](https://github.com/plotly/dash-vtk/blob/master/demos/volume-rendering/app.py)

![Real medical image](../../demos/volume-rendering/demo.jpg)
![Real medical image](../demos/volume-rendering/demo.jpg)


[Randomly generated volume](https://github.com/plotly/dash-vtk/blob/master/demos/synthetic-volume-rendering/app.py)

![Randomly generated volume](../../demos/synthetic-volume-rendering/demo.jpg)
![Randomly generated volume](../demos/synthetic-volume-rendering/demo.jpg)

[Multi-View with slicing](https://github.com/plotly/dash-vtk/blob/master/demos/slice-rendering/app.py)

![Multi-View with slicing](../../demos/slice-rendering/demo.jpg)
![Multi-View with slicing](../demos/slice-rendering/demo.jpg)

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