Sumtree sampling

[CasBex]

For all the lofty talk about numerical rounding errors in #59, they are unavoidable even with the improved method. This fix simply checks whether the sampled priority happens to be zero, and if so it walks backwards over the leafs until it finds a nonzero priority node. If the backwards walk has not found anything, it performs a forward walk instead.

This has been tested against the JuliaRL_PrioritizedDQN_CartPole experiment in ReinforcementLearningExperiments.jl with 30 different seeds.

[jeremiahpslewis]

Looks good! Can you add a test to this?

[CasBex]

Tests have been added. Feel free to change the tolerances/number of iterations... in case they take too long though. The first test checks that priority zero is never sampled; the second test checks that the pdf of samples is what we would expect. The latter however requires many samples so I've added some multithreading to speed it up. Both tests are run with 100 different seeds for the rng.

[CasBex]

Sorry for the confusion with the tests. Should be good to go now

[jeremiahpslewis]

Thanks for adding the test! One more question and a couple of minor details

[codecov]

Codecov Report

Merging #60 (3f3e99f) into main (85de617) will increase coverage by 0.32%.
The diff coverage is 53.33%.

@@            Coverage Diff             @@
##             main      #60      +/-   ##
==========================================
+ Coverage   73.21%   73.54%   +0.32%     
==========================================
  Files          15       15              
  Lines         743      756      +13     
==========================================
+ Hits          544      556      +12     
- Misses        199      200       +1     

Files Changed	Coverage Δ
src/common/sum_tree.jl	81.60% <53.33%> (+1.87%)	⬆️

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[findmyway]

LGTM

Changes were included.

[HenriDeh]

@CasBex I'll let you merge in case you want to make a last minute change.

[CasBex]

I don't have permissions to merge @HenriDeh. Could you merge?