Add Cell Connectivity To Points
This filter will add linear cell connectivity between scattered points.
You have the option to add
VTK_LINE connectivity makes a straight line between the points in order
(either in the order by index or using a nearest neighbor calculation).
VTK_POLYLINE adds polyline connectivity between all points as one
spline (either in the order by index or using a nearest neighbor calculation).
sphinx_gallery_thumbnail_number = 2
import numpy as np import pyvista from PVGeo import points_to_poly_data from PVGeo.filters import AddCellConnToPoints
First, lets generate some points which we’d like to connect
def path1(y): """Equation: x = a(y-h)^2 + k""" a = -110.0 / 160.0**2 x = a * y**2 + 110.0 idxs = np.argwhere(x > 0) return x[idxs][:, 0], y[idxs][:, 0] x, y = path1(np.arange(0.0, 200.0, 25.0)) zo = np.linspace(9.0, 11.0, num=len(y)) coords = np.vstack((x, y, zo)).T # Shuffle points to demonstrate value of Nearest Neighbor np.random.shuffle(coords) # Make a VTK data object for the filter to use vtkPoints = points_to_poly_data(coords)
Apply the Filter
Now that you have the points generated, lets go ahead and apply the Add Cell Connectivity To Points filter from Filters->PVGeo: General Filters->Add Cell Connectivity To Points. The output data should look really wacky and incorrectly built like the image below; this is good.
line = AddCellConnToPoints().apply(vtkPoints) p = pyvista.Plotter() p.add_mesh(line, line_width=5, point_size=10) p.show()
Remember that in the script given above we shuffle the points to demonstrate
that the points make a usable line but we need to reconstruct the order of the
points. We do this by using the Use Nearest Nbr Approx checkbox; this will
ensure that a usable path is generate from the points.
Go ahead and use the
nearest_nbr argument for the algorithm.
Now it looks good (see image below)!
# Use the filter: Here is vtkPolyData containing the connected line: line_o = AddCellConnToPoints(nearest_nbr=True).apply(vtkPoints) p = pyvista.Plotter() p.add_mesh(line_o, line_width=5, point_size=10) p.show()
Total running time of the script: ( 0 minutes 2.234 seconds)