Transfer Functions

You can change a visualization’s appearance by accessing and modifying its transfer function.

import example_utils
from vapor import session, renderer, dataset, camera, transferfunction
from vapor.utils import histogram

ses = session.Session()
data = example_utils.OpenExampleDataset(ses)

ren = data.NewRenderer(renderer.VolumeRenderer)
ses.GetCamera().LookAt((32, 120, 120), (32, 32, 32))
ses.Show()

Warning: sysroot "/Applications/Xcode_12.4.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk" not found (ignoring for now).

Vapor 3.9.3
Python 3.9.19 (/opt/anaconda3/envs/vapor)
OpenGL 4.1 Metal - 83.1

UNSUPPORTED (log once): POSSIBLE ISSUE: unit 3 GLD_TEXTURE_INDEX_3D is unloadable and bound to sampler type (Float) - using zero texture because texture unloadable

../_images/e0612cb8ca7a0ecba2e349f8b3d281f77ef161e55f9415c5776077c5a5b7e960.png

Changing Opacities

We created a volume rendering however it is fully opaque. We can use a transfer function to adjust the visible portions. Before we adjust the opacity map of the TF, we get a histogram to help us determine what we want to hide.

histogram.ShowMatPlotLibHistogram(ses, ren)

../_images/9996235b994e2413a963f3c5dcaf7e815ee7665dcad94acc7fc770b3e82d3bf4.png

Usually we want to hide the most common value so below we construct an opacity map that accomplishes this.

# List of x,y pairs where x is the data value and y is the opacity for that data value
opacities = [(-0.3, 1), (-0.1, 0), (0.1, 0), (0.3, 1)]

We can get the matplotlib histogram plot and add our opacity map to it to compare.

plt = histogram.GetMatPlotLibHistogram(ses, ren)
plt.plot(*zip(*opacities))
plt.show()

../_images/b7191fd7c490c8f5163acf3c5c1a2f5e8df20510f3cf6cbe80ce63eb3c64b612.png

Now we apply the map to the transfer function

# Renderers can have multiple transfer functions.
# GetPrimaryTransferFunction returns the one that is usually the most useful.
# You can use `tf.GetTransferFunction(var_name)` to get other transfer functions.
tf = ren.GetPrimaryTransferFunction()
tf.SetOpacityControlPoints(opacities)
ses.Show()

../_images/a99e7785df071fdca34f57b23ada7010809ad4a6cb9f89e8da31b32e5452f654.png

You can adjust the colormap in a similar fashion. Use help(tf) for more information. Vapor includes a list of built-in colormaps and these can be applied with tf.LoadBuiltinColormap(name)

Builtin Colormaps

tf.LoadBuiltinColormap("Sequential/BlackBodyExtended")
ses.Show()

../_images/9e0aad32a7f67d201b97538801082c6021185e88a5f12b8e143ef3370b1bb416.png

List of All Builtin Colormaps

ses.DeleteRenderer(ren)
ren = data.NewRenderer(renderer.TwoDDataRenderer)
tf = ren.GetPrimaryTransferFunction()

for cmap in transferfunction.TransferFunction.ListBuiltinColormaps():
    tf.LoadBuiltinColormap(cmap)

    print(cmap)
    tf.ShowMatPlotLibColorbar()