def plot_err_field_vedo(X, Y, Z, scalar_field, fig_name):
isomin = 1. * scalar_field.min()
isomax = 1. * scalar_field.max()
# isomin = 10
# isomax = 11
vol = Volume(scalar_field)
# vol.addScalarBar3D()
vol.addScalarBar3D(sy=1.5, title='height is the scalar')
# generate an isosurface the volume for each thresholds
ts = np.linspace(isomin, isomax, 6)
# ts = [10.1, 10.25, 10.4]
# Use c=None to use the default vtk color map. isos is of type Mesh
isos = Volume(scalar_field).isosurface(threshold=ts).opacity(0.4)
text1 = Text2D(f'Make a Volume from numpy.mgrid', c='blue')
text2 = Text2D(f'its isosurface representation\nvmin={isomin:.2e}, vmax={isomax:.2e}', c='dr')
print('numpy array from Volume:',
vol.getPointArray().shape,
vol.getDataArray().shape)
# show([(vol, text1), (isos, text2)], N=2, azimuth=10, zoom=1.3)
destination_path = os.path.join(plot_dir, fig_name)
write(vol, destination_path)
print(f'zapisano w: {destination_path}')
"""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 vedo import Volume, show vol = Volume(data_matrix, c=['white', 'b', 'g', 'r']) vol.addScalarBar3D() show(vol, __doc__, axes=1)
mode=0, composite rendering
mode=1, maximum-projection rendering"""
from vedo import dataurl, Volume, show
vol1 = Volume(dataurl + "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]).addScalarBar3D(title='composite shade',
c='k')
vol1.scalarbar.scale(0.8).x(20)
# mode = 1 is maximum-projection volume rendering
vol2 = Volume(dataurl + "vase.vti").mode(1).shift(60, 0, 0)
vol2.addScalarBar3D(title='maximum-projection', c='k')
vol2.scalarbar.scale(0.8).x(160)
# show command creates and returns an instance of class Plotter
show(vol1, vol2, __doc__, size=(800, 600), zoom=1.5).close()
"""A Volume can have multiple
scalars associated to each voxel"""
from vedo import dataurl, Volume, printc, show
import numpy as np
vol = Volume(dataurl + 'vase.vti')
nx, ny, nz = vol.dimensions()
r0, r1 = vol.scalarRange()
vol.addScalarBar3D(title='original voxel scalars')
# create a set of scalars and add it to the Volume
vol.pointdata["myscalars1"] = np.linspace(r0, r1, num=nx * ny * nz)
# create another set of scalars and add it to the Volume
vol.pointdata["myscalars2"] = np.random.randint(-100, +100, nx * ny * nz)
# make SLCImage scalars the active array (can set 0, to pick the first):
printc('Arrays in Volume are:\n', vol.pointdata.keys(), invert=True)
vol.pointdata.select(
"SLCImage") # select the first data array as the active one
# Build the isosurface of the active scalars,
# but use testscals1 to colorize this isosurface, and then smooth it
iso1 = vol.isosurface().cmap('jet', 'myscalars1').smooth().lw(0.1)
iso1.addScalarBar3D(title='myscalars1')
iso2 = vol.isosurface().cmap('viridis', 'myscalars2')
iso2.addScalarBar3D(title='myscalars2')
show([
(vol, __doc__),
"""Custom color and transparency maps for Volumes"""
from vedo import Volume, dataurl, show
from vedo.pyplot import CornerHistogram
# Build a Volume object.
# A set of color/transparency values - of any length - can be passed
# to define the transfer function in the range of the scalar.
# E.g.: setting alpha=[0, 0, 0, 1, 0, 0, 0] would make visible
# only voxels with value close to center of the range (see histogram).
vol = Volume(dataurl + 'embryo.slc')
vol.color([
(0, "green"),
(49, "green"),
(50, "blue"),
(109, "blue"),
(110, "red"),
(180, "red"),
])
# vol.mode('max-projection')
vol.alpha([0., 1.])
vol.alphaUnit(8) # absorption unit, higher factors = higher transparency
vol.addScalarBar3D(title='color~\dot~alpha transfer function', c='k')
ch = CornerHistogram(vol, logscale=True, pos='bottom-left')
# show both Volume and Mesh
show(vol, ch, __doc__, axes=1, zoom=1.2).close()
