_compute_dof(self, kind, dz=None)

Parameters

kind : {'min_E', 'geom', 'user'}

Choice of the _DOF_estimator subclass to estimate the gradient.

dz : tuple of array-likes (dzdx, dzdy), optional

Used only if *kind*=user; in this case passed to the _DOF_estimator_user .

Returns

array-like, shape (npts, 2)

Estimation of the gradient at triangulation nodes (stored as degree of freedoms of reduced-HCT triangle elements).

Compute and return nodal dofs according to kind.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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File: /matplotlib/tri/triinterpolate.py#449
type: <class 'function'>
Commit: