sigpy.alg.NewtonsMethod

class sigpy.alg.NewtonsMethod(gradf, inv_hessf, x, beta=1, f=None, max_iter=10, tol=0)

Newton’s Method.

Parameters:

• gradf (function) - A function gradf(x) – x -> gradient of f at x.
• inv_hessf (function) - A function H(x) – x -> inverse Hessian of f at x, which is another function: y -> inverse Hessian of f at x times y.
• x (function) –
• beta (scalar) – backtracking linesearch factor. Enables backtracking when beta < 1.
• f (function or None) – function to compute \(f\) for backtracking line-search.
• max_iter (int) – maximum number of iterations.
• tol (float) – Tolerance for stopping condition.

__init__(gradf, inv_hessf, x, beta=1, f=None, max_iter=10, tol=0)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(gradf, inv_hessf, x[, beta, f, …])	Initialize self.
done()	Return whether the algorithm is done.
update()	Perform one update step.