Interpolate scalar data on mesh#
import numpy as np
from vedo import dataurl, Mesh, Points, show, settings
from vedo.pyplot import plot
settings.default_backend = "vtk" # or k3d, ipyvtk, or 2d
# Load a mesh of a mouse limb at 12 days of development
msh = Mesh(dataurl + "290.vtk")
msh
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vedo.mesh.Mesh (....embl.es/examples/data/290.vtk)
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# Pick 100 points where we measure the value of a gene expression
ids = np.random.randint(0, msh.npoints, 100)
pts = msh.points()[ids] # slice the numpy array
x = pts[:, 0] # x coordinates of the points
gene = np.sin((x+150)/500)**2 # we are making this up!
# Create a set of points with those values
points = Points(pts, r=10).cmap("Greens", gene)
# Interpolate the gene data onto the mesh, by averaging the 5 closest points
msh.interpolate_data_from(points, n=5).cmap("Greens").add_scalarbar()
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vedo.mesh.Mesh (....embl.es/examples/data/290.vtk)
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# Create a graph of the gene expression as function of x-position
gene_plot = plot(x, gene, lw=0, title="Gene expression").as2d(scale=0.5)
# Show the mesh, the points and the graph
show(msh, points, gene_plot).close()