c

scalation.minima

CoordinateDescent

class CoordinateDescent extends Minimizer with Error

The CoordinateDescent class solves unconstrained Non-Linear Programming (NLP) problems using the Coordinate Descent algorithm. Given a function 'f' and a starting point 'x0', the algorithm picks coordinate directions (cyclically) and takes steps in the those directions. The algorithm iterates until it converges.

dir_k = kth coordinate direction

minimize f(x)

Linear Supertypes
Error, Minimizer, AnyRef, Any
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  1. CoordinateDescent
  2. Error
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new CoordinateDescent(f: FunctionV2S, exactLS: Boolean = true)

    f

    the vector-to-scalar objective function

    exactLS

    whether to use exact (e.g., GoldenLS) or inexact (e.g., WolfeLS) Line Search

Type Members

  1. type Pair = (VectorD, VectorD)
    Definition Classes
    Minimizer

Value Members

  1. def fg(x: VectorD): Double

    The objective function 'f' plus a weighted penalty based on the constraint function 'g'.

    The objective function 'f' plus a weighted penalty based on the constraint function 'g'. Override for constrained optimization and ignore for unconstrained optimization.

    x

    the coordinate values of the current point

    Definition Classes
    Minimizer
  2. final def flaw(method: String, message: String): Unit
    Definition Classes
    Error
  3. def lineSearch(x: VectorD, dir: VectorD, step: Double = STEP): Double

    Perform an exact 'GoldenSectionLS' or inexact 'WolfeLS' line search.

    Perform an exact 'GoldenSectionLS' or inexact 'WolfeLS' line search. Search in direction 'dir', returning the distance 'z' to move in that direction.

    x

    the current point

    dir

    the direction to move in

    step

    the initial step size

    Definition Classes
    CoordinateDescent → Minimizer
  4. def solve(x0: VectorD, step: Double = STEP, toler: Double = EPSILON): VectorD

    Solve the Non-Linear Programming (NLP) problem using the Coordinate Descent algorithm.

    Solve the Non-Linear Programming (NLP) problem using the Coordinate Descent algorithm.

    x0

    the starting point

    step

    the initial step size

    toler

    the tolerance

    Definition Classes
    CoordinateDescent → Minimizer