def load_labelled_volume(data, vmin=0, alpha=1, **kwargs):
"""
Load volume image from .nrrd file.
It assume that voxels with value = 0 are empty while voxels with values > 0
are labelles (e.g. to indicate the location of a brain region in a reference atlas)
:param data: str, path to file with volume data or 3d numpy array
:param vmin: float, values below this numner will be assigned an alpha=0 and not be visualized
:param **kwargs: kwargs to pass to the Volume class from vtkplotter
:param alpha: float in range [0, 1], transparency [for the part of volume with value > vmin]
"""
# Load/check volumetric data
if isinstance(data, str): # load from file
if not os.path.isfile(data):
raise FileNotFoundError(f'Volume data file {data} not found')
try:
data = brainio.load_any(data)
except:
raise ValueError(f"Could not load volume data from file: {data}")
elif not isinstance(data, np.ndarray):
raise ValueError(
f"Data should be a filepath or np array, not: {data.__type__}")
# Create volume and set transparency range
vol = Volume(data, alpha=alpha, **kwargs)
otf = vol.GetProperty().GetScalarOpacity()
otf.RemoveAllPoints()
otf.AddPoint(vmin, 0) # set to transparent
otf.AddPoint(vmin + .1, alpha) # set to opaque
otf.AddPoint(data.max(), alpha)
return vol
"""Modify a Volume dataset and colorize voxels individually """ from vtkplotter import Text2D, Volume, show import numpy as np vol = Volume(shape=(10,11,12), mode=0) vol.alpha(0.8).jittering(False) vol.interpolation(0) # nearest neighbour interpolation type # Overwrite the (sofar empty) voxel data with new data vol.imagedata().AllocateScalars(3, 4) # type 3 corresponds to np.uint8 arr = vol.getPointArray() arr[:] = np.random.randint(0,255, (10*11*12,4)).astype(np.uint8) # For 4 component data, the first 3 directly represent RGB, no lookup table. # (see https://vtk.org/doc/nightly/html/classvtkVolumeProperty.html): vol.GetProperty().IndependentComponentsOff() show(vol, Text2D(__doc__), axes=1)