A number of standard optimization functions for R along with sampling methods.
There is a unified interface to sampling the functions. One can run
`sample.func("rosenbrok", n=250, k=5, method="lhs.sampling")`

to get a 250
sample Latin hypercube in 5D of the rosenbrock function.

The following multi-D scalar functions are implemented. They are all defined on an arbitrary number of inputs.

- ackley
- rosenbrock
- schwefel
- sinc
- spherical
- zakharov

The following sampling methods are supported with their internal names in
parenthesis. With the exception of `hexagonal.sample`

these are all defined
on an arbitrary number of dimensions.

- Latin hypercube (
`lh.sample`

) - Uniform random (
`random.sample`

) - Cartesian lattice (
`cartesian.sample`

) - Hexagonal lattice (
`hexagonal.sample`

) - Toroidal sampling (
`torus.sample`

) - Sobol sequence (
`sobol.sample`

) - Halton sequence (
`halton.sample`

)

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