Finite Discrete Measure

[davibarreira]

This PR has the implementation of the FiniteDiscreteMesure struct which I talked about in #92. It is similar to the DiscreteNonParametric type in Distributions.jl. It contains a supportand a p (for probability), allowing the user to store the empirical distributions. This would allow use to write functions such as sinkhorn2(c, mu::FiniteDiscreteMeasure, nu::FiniteDiscreteMeasure), without having to pass both support and probabilities separately.

p.s: I don't feel strongly about the FiniteDiscreteMeasure naming. Feel free to give better suggestions. I just don't think DiscreteMeasure is a good name, because our variable cannot have infinite support, like a Poisson distribution.
SimpleMeasure is another option and would be theoretically correct. EmpiricalMeasureand SampleMeasure are another option, but they are kind of ambiguous, since the measure does not need necessarily to be either empirical or from a sampling process.

[coveralls]

Pull Request Test Coverage Report for Build 914791279

• 9 of 9 (100.0%) changed or added relevant lines in 1 file are covered.
• No unchanged relevant lines lost coverage.
• Overall coverage increased (+0.1%) to 94.672%

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Totals
Change from base Build 911721124:	0.1%
Covered Lines:	462
Relevant Lines:	488

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💛 - Coveralls

[codecov-commenter]

Codecov Report

Merging #95 (d5d57c7) into master (24ecf5d) will decrease coverage by 0.21%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master      #95      +/-   ##
==========================================
- Coverage   94.88%   94.67%   -0.22%     
==========================================
  Files           6        7       +1     
  Lines         430      488      +58     
==========================================
+ Hits          408      462      +54     
- Misses         22       26       +4     

Impacted Files	Coverage Δ
src/utils.jl	100.00% <100.00%> (ø)
src/entropic.jl
src/entropic/sinkhorn.jl	97.98% <0.00%> (ø)
src/entropic/sinkhorn_stabilized.jl	94.33% <0.00%> (ø)

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[davibarreira]

There is some compatibility issue, but I cannot reproduce in my machine. It seems to be related to KernelFunctions, which I used in the test.

[devmotion]

KernelFunctions requires Julia >= 1.3 (this is one reason for why we want to extract ColVecs and RowVecs to a separate package). It seems ArraysOfArrays also supports Julia 1.0, so it would be better to use it in the tests until ColVecs and RowVecs are compatible with Julia 1.0.

[davibarreira]

If there are no more proposed changes, I think this is ready to be merged :D

[devmotion]

OK, let's merge this and see how we can make use of it. Since it's not exported we can iterate freely until we reach a good design 🙂

[davibarreira]

KernelFunctions requires Julia >= 1.3 (this is one reason for why we want to extract ColVecs and RowVecs to a separate package). It seems ArraysOfArrays also supports Julia 1.0, so it would be better to use it in the tests until ColVecs and RowVecs are compatible with Julia 1.0.

@devmotion would you know if the ColVecs and RowVecs have been moved to another package? I'm writing some extra documentation on the 1D case, and I remembered this.

[coveralls]

Pull Request Test Coverage Report for Build 911924330

Warning: This coverage report may be inaccurate.

This pull request's base commit is no longer the HEAD commit of its target branch. This means it includes changes from outside the original pull request, including, potentially, unrelated coverage changes.

• For more information on this, see Tracking coverage changes with pull request builds.
• To avoid this issue with future PRs, see these Recommended CI Configurations.
• For a quick fix, rebase this PR at GitHub. Your next report should be accurate.

Details

• 9 of 9 (100.0%) changed or added relevant lines in 1 file are covered.
• No unchanged relevant lines lost coverage.
• Overall coverage decreased (-0.2%) to 94.672%

---

Totals
Change from base Build 910296728:	-0.2%
Covered Lines:	462
Relevant Lines:	488

---

💛 - Coveralls