- paraview.simple.Delaunay3D(*input, **params)¶
Delaunay3D is a filter that constructs a 3D Delaunay triangulation from a list of input points. These points may be represented by any dataset of type vtkPointSet and subclasses. The output of the filter is an unstructured grid dataset. Usually the output is a tetrahedral mesh, but if a non-zero alpha distance value is specified (called the “alpha” value), then only tetrahedra, triangles, edges, and vertices lying within the alpha radius are output. In other words, non-zero alpha values may result in arbitrary combinations of tetrahedra, triangles, lines, and vertices. (The notion of alpha value is derived from Edelsbrunner’s work on “alpha shapes”.) The 3D Delaunay triangulation is defined as the triangulation that satisfies the Delaunay criterion for n-dimensional simplexes (in this case n=3 and the simplexes are tetrahedra). This criterion states that a circumsphere of each simplex in a triangulation contains only the n+1 defining points of the simplex. (See text for more information.) While in two dimensions this translates into an “optimal” triangulation, this is not true in 3D, since a measurement for optimality in 3D is not agreed on. Delaunay triangulations are used to build topological structures from unorganized (or unstructured) points. The input to this filter is a list of points specified in 3D. (If you wish to create 2D triangulations see Delaunay2D.) The output is an unstructured grid. The Delaunay triangulation can be numerically sensitive. To prevent problems, try to avoid injecting points that will result in triangles with bad aspect ratios (1000:1 or greater). In practice this means inserting points that are “widely dispersed”, and enables smooth transition of triangle sizes throughout the mesh. (You may even want to add extra points to create a better point distribution.) If numerical problems are present, you will see a warning message to this effect at the end of the triangulation process. Warning: Points arranged on a regular lattice (termed degenerate cases) can be triangulated in more than one way (at least according to the Delaunay criterion). The choice of triangulation (as implemented by this algorithm) depends on the order of the input points. The first four points will form a tetrahedron; other degenerate points (relative to this initial tetrahedron) will not break it. Points that are coincident (or nearly so) may be discarded by the algorithm. This is because the Delaunay triangulation requires unique input points. You can control the definition of coincidence with the “Tolerance” instance variable. The output of the Delaunay triangulation is supposedly a convex hull. In certain cases this implementation may not generate the convex hull. This behavior can be controlled by the Offset instance variable. Offset is a multiplier used to control the size of the initial triangulation. The larger the offset value, the more likely you will generate a convex hull; and the more likely you are to see numerical problems. The implementation of this algorithm varies from the 2D Delaunay algorithm (i.e., Delaunay2D) in an important way. When points are injected into the triangulation, the search for the enclosing tetrahedron is quite different. In the 3D case, the closest previously inserted point point is found, and then the connected tetrahedra are searched to find the containing one. (In 2D, a “walk” towards the enclosing triangle is performed.) If the triangulation is Delaunay, then an enclosing tetrahedron will be found. However, in degenerate cases an enclosing tetrahedron may not be found and the point will be rejected.
This property specifies the alpha (or distance) value to control the output of this filter. For a non-zero alpha value, only edges, faces, or tetra contained within the circumsphere (of radius alpha) will be output. Otherwise, only tetrahedra will be output.
This boolean controls whether lines which satisfy the alpha criterion output when alpha is non-zero.
This boolean controls whether tetrahedrons which satisfy the alpha criterion output when alpha is non-zero.
This boolean controls whether triangles which satisfy the alpha criterion output when alpha is non-zero.
This boolean controls whether vertices which satisfy the alpha criterion are output when alpha is non-zero.
This 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.)
This property specifies the input dataset to the Delaunay 3D filter.
This property specifies a multiplier to control the size of the initial, bounding Delaunay triangulation.
This property specifies 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.
Data Descriptors inherited from Proxy¶
dictionary for instance variables (if defined)
list of weak references to the object (if defined)
Initialize = aInitialize(self, connection=None, update=True)
Methods inherited from SourceProxy¶
Called when the filename of a source proxy is changed.
Returns the associated cell data information.
- GetDataInformation(self, idx=None)
This method returns a DataInformation wrapper around a vtkPVDataInformation
Returns the associated cell data information.
Returns the associated point data information.
- UpdatePipeline(self, time=None)
This method updates the server-side VTK pipeline and the associated data information. Make sure to update a source to validate the output meta-data.
This method updates the meta-data of the server-side VTK pipeline and the associated information properties
- __getitem__(self, idx)
Given a slice, int or string, returns the corresponding output port
Methods inherited from Proxy¶
- GetProperty(self, name)
Given a property name, returns the property object.
- GetPropertyValue(self, name)
Returns a scalar for properties with 1 elements, the property itself for vectors.
- InitializeFromProxy(self, aProxy, update=True)
Constructor. Assigns proxy to self.SMProxy, updates the server object as well as register the proxy in _pyproxies dictionary.
Returns a list of all property names on this proxy.
- SetPropertyWithName(self, pname, arg)
Generic method for setting the value of a property.
Destructor. Cleans up all observers as well as remove the proxy from the _pyproxies dictionary
- __eq__(self, other)
Returns true if the underlying SMProxies are the same.
- __getattr__(self, name)
With the exception of a few overloaded methods, returns the SMProxy method
- __init__(self, **args)
Default constructor. It can be used to initialize properties by passing keyword arguments where the key is the name of the property. In addition registrationGroup and registrationName (optional) can be specified (as keyword arguments) to automatically register the proxy with the proxy manager.
Creates an iterator for the properties.
- __ne__(self, other)
Returns false if the underlying SMProxies are the same.
- __setattr__(self, name, value)
Implement setattr(self, name, value).
add_attribute(self, name, value)
For the full list of servermanager proxies, please refer to Available readers, sources, writers, filters and animation cues