- paraview.simple.Delaunay2D(*input, **params)¶
Delaunay2D is a filter that constructs a 2D 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 a polygonal dataset containing a triangle mesh. The 2D Delaunay triangulation is defined as the triangulation that satisfies the Delaunay criterion for n-dimensional simplexes (in this case n=2 and the simplexes are triangles). This criterion states that a circumsphere of each simplex in a triangulation contains only the n+1 defining points of the simplex. In two dimensions, this translates into an optimal triangulation. That is, the maximum interior angle of any triangle is less than or equal to that of any possible triangulation. 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, even though the triangulation is 2D. Thus the triangulation is constructed in the x-y plane, and the z coordinate is ignored (although carried through to the output). You can use the option ProjectionPlaneMode in order to compute the best-fitting plane to the set of points, project the points and that plane and then perform the triangulation using their projected positions and then use it as the plane in which the triangulation is performed. The Delaunay triangulation can be numerically sensitive in some cases. 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 three points will form a triangle; other degenerate points will not break this triangle. Points that are coincident (or nearly so) may be discarded by the algorithm. This is because the Delaunay triangulation requires unique input points. The output of the Delaunay triangulation is supposedly a convex hull. In certain cases this implementation may not generate the convex hull.
The value of this property controls the 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.
If this property is set to 1, 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 2D filter.
This property is a multiplier to control the size of the initial, bounding Delaunay triangulation.
This property determines type of projection plane to use in performing the 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