Metasampler, MultiBatchSampler, SamplerControler

[HenriDeh]

Hello,

Following the discussion in #13, I made this PR to add 3 things

• MetaSampler: a wrapper for a namedtuple of samplers. This allows to combine multiple samplers when needed in algorithm design. It returns a named tuple with the same keys as the wrapped one, and its values are sampled batches.
• MultiBatchSampler: a wrapper for a sampler that, when sampled, will sample n times instead of once. It thus returns a collection of n batches. This allows to combine samplers in a metasampler that are not meant to be sampled the same number of time.
• InsertSampleController: it's an alternative to the ratio controller that will stop after a fixed number of samples. I first tried to implement the nothing controller you proposed in How do we deal with metasampler ? #13 but this lead to infinite sampling because the loop has no end condition.
• I also fixed the spelling of controller (it has two L's apparently, full disclosure I just discovered that while writing this).

This should be enough to close #13 and will allow to easily refactor old algorithms using Trajectories.jl.

[codecov-commenter]

Codecov Report

Merging #15 (efffb6a) into main (c2db98d) will increase coverage by 3.37%.
The diff coverage is 97.77%.

@@            Coverage Diff             @@
##             main      #15      +/-   ##
==========================================
+ Coverage   30.06%   33.43%   +3.37%     
==========================================
  Files           9        9              
  Lines         316      332      +16     
==========================================
+ Hits           95      111      +16     
  Misses        221      221              

Impacted Files	Coverage Δ
src/rendering.jl	0.00% <ø> (ø)
src/trajectory.jl	91.66% <93.75%> (ø)
src/controllers.jl	100.00% <100.00%> (ø)
src/samplers.jl	100.00% <100.00%> (ø)

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[findmyway]

LGTM