This repository includes experiments of ways to display multiple volumes in volume renderings using OpenGL with VisPy.
This implements a MultiVolumeVisual and a MultiVolume class for
VisPy which allows multiple volumes to be shown
simultaneously.
Simply use the MultiVolume class as you would use the Volume class in
VisPy, but instead of passing the volume data,
clim, and cmap as separate arguments, the first argument should be a
list of tuples, where each tuple contains (data, clim, cmap).
In future it should be possible to also add extra tuples to the volumes
attribute of the MultiVolume on-the-fly.
You can try the two examples in the repository by running:
python medical.py
and
python astrocube.py
The approach here is to make it so that the vertex shader includes variables
for separate volumes and colormaps, and the color averaging is done in the
shader itself. The MultiVolumeVisual class then includes a list of volumes
that is a callback-enabled list: every time an item is added or removed from
the list, the OpenGL data buffer for that item is updated.
Pros: when adding a new volume, we don't have to resend all the data, we simply add the new volume data, and update the volume counter in OpenGL. In addition, the averaging is done on-the-fly in OpenGL and seems to be very fast.
Cons: the fragment shader code has to be generated for a fixed maximum number of volumes. We could consider making it so that when more than this value of volumes are added, we update the fragment shader code, but this is not ideal.
This implements a RGBAVolumeVisual and a RGBAVolume class for
VisPy which allows a cube with arbitrary colors in each
pixel to be shown. This in turn can then be used to show multiple volumes,
since we can pre-compute the full final RGBA cube in Python before passing it
to VisPy.
This works by simply setting u_volumetex to an actual 4-d RGBA cube instead
of a 3-d array, and then using these values without mapping with a colormap.
You can try the two examples in the repository by running:
python medical_rgba.py
and
python astrocube_rgba.py
Pros: could actually be implemented in VisPy with minimal effort (a few lines) on top of the existing Volume.
Cons: combining the volumes has to be done in Python, and may therefore be slower.