Util

Surrogate Hessian accelerated parallel line-search: utilities

class stalk.util.ArgsContainer(**args)

Bases: object

property args: dict

get_updated(new_args: dict) → dict

class stalk.util.FunctionCaller(func, args: dict = {}, **kwargs)

Bases: ArgsContainer

property func

stalk.util.bipolyfit(X, Y, Z, nx, ny): Fit to a bipolynomial set of variables

stalk.util.bipolynomials(X, Y, nx, ny)

Construct a bipolynomial expansion of variables

XYp = x**0 y**0, x**0 y**1, x**0 y**2, … courtesy of Jaron Krogel

stalk.util.bipolyval(p, X, Y, nx, ny): Evaluate based on a bipolynomial set of variables

stalk.util.directorize(path: str): If missing, add ‘/’ to the end of path

stalk.util.get_fraction_error(data, fraction, both=False): Estimate uncertainty from a distribution based on a percentile fraction

stalk.util.match_to_tol(val1, val2, tol=1e-08): Match the values of two vectors. True if all match, False if not.

stalk.util.morse(p, r)