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# (NelderMeadConfiguration).Vars

Defined in github.com/Workiva/go-datastructures/numerics/optimization/nelder_mead.go

## Description

Vars is a guess and will determine what other vertices will be used. By convention, since this guess will contain as many numbers as the target function requires, the len of Vars determines the dimension of this problem.

## Examples

bestGuess := results.vertices[0] sigma := calculateSigma(len(results.config.Vars), len(results.vertices)) results.pbs.calculateProbabilities(bestGuess, sigma) results.pbs.sort()

func (nm *nelderMead) evaluate() { vertices := nm.results.grab(len(nm.config.Vars) + 1) // if the initial guess provided is not good, then // we are going to die early, leave it up to the user

} nm.results.reSort(vertices[0]) vertices = nm.results.grab(len(nm.config.Vars) + 1) } }

## Vars is referenced in 1 repository

**github.com/Workiva/go-datastructures**

- 7 references in numerics/optimization/nelder_mead_test.go
- 3 references in numerics/optimization/nelder_mead.go
- 1 reference in numerics/optimization/global.go