The Jacobian matrix is diagonal and is tuned on each iteration.
This algorithm may be useful for specific problems, but whether it will work may depend strongly on the problem.
Initial Jacobian approximation is (-1/alpha).
The entries of the diagonal Jacobian are kept in the range [alpha, alphamax]
.
Find a root of a function, using a tuned diagonal Jacobian approximation.
root
Interface to root finding algorithms for multivariate functions. See method=='excitingmixing'
in particular.
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