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@mbaudin47 mbaudin47 released this 05 Jan 14:39
· 2 commits to main since this release

Added

  • New ShiXieXuanNocedalForward.
  • New ShiXieXuanNocedalGeneral.
  • New benchmark_method.
  • DumontetVignes: new get_ell_min_max.
  • DumontetVignes, SteplemanWinarsky, GillMurraySaundersWright: new get_step_history.
  • New SteplemanWinarkyInitialize: compute initial step for SteplemanWinarsky.

Changes

  • DumontetVignes, SteplemanWinarsky, GillMurraySaundersWright: Renamed compute_step into find_step to avoid confusion.
  • Removed SteplemanWinarsky.search_step_with_bisection: please use SteplemanWinarkyInitialize.find_initial_step().
  • DerivativeBenchmark: new print and pretty-print.
  • DerivativeBenchmark: create any problem from the test point and the interval. This can be useful to create a list of test points depending on each problem.
  • ScaledExponentialProblem: change parametrization.
  • DumontetVignes: parametrize depending on ell3 and ell4 instead of ell1 and ell2.
  • GillMurraySaundersWright: Changed parametrization from relative precision
    of the function value into absolute precision to enable a zero function value.
  • Set relative_precision to 1.0e-15 in all algorithms
  • Set iteration_maximum to 53 in all algorithms
  • PolynomialProblem: Fixed higher derivatives for alpha different from 2.
  • DumontetVignes: Added a separate absolute precision parameter to manage cases where f(x) = 0.

Documentation

  • DumontetVignes, SteplemanWinarsky, GillMurraySaundersWright: briefly introduce the method and its criteria.

Full Changelog: https://github.com/mbaudin47/numericalderivative/commits/v0.3