UnstructuredGridFilters.delaunay_2d

UnstructuredGridFilters.delaunay_2d(

*,

tol=1e-05,

alpha=0.0,

offset=1.0,

bound: bool = False,

inplace: bool = False,

edge_source=None,

progress_bar: bool = False,

)

Apply a 2D Delaunay filter along the best fitting plane.

This filter can be used to generate a 2d surface from a set of points on a plane. If you want to create a surface from a point cloud, see pyvista.PolyDataFilters.reconstruct_surface().

Parameters:

tolfloat, default: 1e-05

Specify a tolerance to control discarding of closely spaced points. This tolerance is specified as a fraction of the diagonal length of the bounding box of the points.

alphafloat, default: 0.0

Specify alpha (or distance) value to control output of this filter. For a non-zero alpha value, only edges or triangles contained within a sphere centered at mesh vertices will be output. Otherwise, only triangles will be output.

offsetfloat, default: 1.0

Specify a multiplier to control the size of the initial, bounding Delaunay triangulation.

boundbool, default: False

Boolean controls whether bounding triangulation points and associated triangles are included in the output. These are introduced as an initial triangulation to begin the triangulation process. This feature is nice for debugging output.

inplacebool, default: False

If True, overwrite this mesh with the triangulated mesh.

edge_sourcepyvista.PolyData, optional

Specify the source object used to specify constrained edges and loops. If set, and lines/polygons are defined, a constrained triangulation is created. The lines/polygons are assumed to reference points in the input point set (that is, point ids are identical in the input and source).

progress_barbool, default: False

Display a progress bar to indicate progress.

Returns:

pyvista.PolyData

Mesh from the 2D Delaunay filter.

Examples

Download Python source code | Download Jupyter notebook

First, generate 30 points on circle and plot them.

>>> import pyvista as pv
>>> points = pv.Polygon(n_sides=30).points
>>> circle = pv.PolyData(points)
>>> circle.plot(show_edges=True, point_size=15)

Static Scene

Interactive Scene

Use delaunay_2d() to fill the interior of the circle.

>>> filled_circle = circle.delaunay_2d()
>>> filled_circle.plot(show_edges=True, line_width=5)

Static Scene

Interactive Scene

Use the edge_source parameter to create a constrained Delaunay triangulation and plot it.

>>> squar = pv.Polygon(n_sides=4, radius=8, fill=False)
>>> squar = squar.rotate_z(45, inplace=False)
>>> circ0 = pv.Polygon(center=(2, 3, 0), n_sides=30, radius=1)
>>> circ1 = pv.Polygon(center=(-2, -3, 0), n_sides=30, radius=1)
>>> comb = circ0.append_polydata(circ1, squar)
>>> tess = comb.delaunay_2d(edge_source=comb)
>>> tess.plot(cpos='xy', show_edges=True)

Static Scene

Interactive Scene