matplotlib 3.5.1

compute_dz(self)

self.df is computed as weighted average of _triangles sharing a common node. On each triangle itri f is first assumed linear (= ~f), which allows to compute d~f[itri] Then the following approximation of df nodal values is then proposed: f[ipt] = SUM ( w[itri] x d~f[itri] , for itri sharing apex ipt) The weighted coeff. w[itri] are proportional to the angle of the triangle itri at apex ipt

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


File: /matplotlib/tri/triinterpolate.py#1077
type: <class 'function'>
Commit: