"""Create a Volume from a numpy array""" import numpy as np data_matrix = np.zeros([75, 75, 75], dtype=np.uint8) # all voxels have value zero except: data_matrix[0:35, 0:35, 0:35] = 1 data_matrix[35:55, 35:55, 35:55] = 2 data_matrix[55:74, 55:74, 55:74] = 3 from vtkplotter import Volume, show vol = Volume(data_matrix, c=['white', 'b', 'g', 'r']) vol.addScalarBar3D() show(vol, __doc__, axes=1)
reader.Update()
img = reader.GetOutput() # vtkImageData object
vol1 = Volume(img, mode=0) # mode=0, composite rendering
# --- NB: THE ABOVE LINES COULD BE REDUCED TO:
#vol1 = load(datadir+"vase.vti")
# -------------------------------------------
# can set colors and transparencies along the scalar range
# from minimum to maximum value. In this example voxels with
# the smallest value will be completely transparent (and white)
# while voxels with highest value of the scalar will get alpha=0.8
# and color will be=(0,0,1)
vol1.color(["white", "fuchsia", "dg", (0, 0, 1)])
#vol1.color('jet') # a matplotlib colormap name is also accepted
vol1.alpha([0.0, 0.2, 0.3, 0.8])
# a transparency for the GRADIENT of the scalar can also be set:
# in this case when the scalar is ~constant the gradient is ~zero
# and the voxel are made transparent:
vol1.alphaGradient([0.0, 0.5, 0.9])
vol1.addScalarBar3D(title='composite rendering').scale(0.8).x(20)
# mode = 1 is maximum-projection volume rendering
vol2 = load(datadir + "vase.vti").mode(1).addPos(60, 0, 0)
vol2.addScalarBar3D(title='maximum-projection').scale(0.8).x(160)
# show command creates and returns an instance of class Plotter
show(vol1, vol2, __doc__, axes=1)