readInCSVFile
transformToFidelity
fitTheFidelities
convertAndProject
projectSimplex
marginalise
covarianceMatrix
correlationMatrix
mutualInformation(p1,p2,p)
relativeEntropy(P,Q)
JSD(dist1,dist2)
conditionalMutualInfo(X,Y,Z,p)
gibbsRandomField
gibbsRandomField(pps,constraints::Array{Array{Array{Any,1},1},1})
getGrainedP(ϕ,tomatch,graining)
reconstruct(dist,constraints)
reconstructedJS(distribution,constraints)
marginaliseFromRawData