Bayesian calculation of unspecified probabilities from priors

[cmungall]

The functionality for this may go in sssom-py but it seems logical to put anything involving probabilistic calculations into an issue here

currently boomer assumes the user specifies priors for all 4 possibilities

What if we have a file which we have a mapping with a probability specified for only one interpretation? In this case we should use standard probability axioms to calculate other probabilities based on priors of probability of any mapping having a particular interp

E.g. assuming global priors

P(equiv) = 0.8
P(sub) = 0.05
P(sup) = 0.05
P(sib) = 0.1

assume sssom contains equiv statement with confidence 0.4

P(sub | equiv) = 0.0
P(sub | NOTequiv) = P(NOTequiv | sub) . P(sub)
                            ----
                            P(NOTequiv)

                  = 1 * 0.05
                      ---
                      0.2

                  = 0.25

therefore posterior p(sub) = 0.4*0 + 0.6 * .25 = 0.15

all posterior

p(equiv) = 0.4
p(sub) = 0.15
p(sup) = 0.15
p(sub) = 0.3