biaslab / ForneyLab.jl

Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.
MIT License
149 stars 33 forks source link

Transition Mixture Node #180

Closed ThijsvdLaar closed 3 years ago

ThijsvdLaar commented 3 years ago

This PR implements a transition mixture node that models a mixture of discrete transitions under selected transition probability matrices.

codecov-commenter commented 3 years ago

Codecov Report

Merging #180 (a8b143e) into master (5d9110e) will increase coverage by 0.72%. The diff coverage is 99.50%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master     #180      +/-   ##
==========================================
+ Coverage   85.57%   86.29%   +0.72%     
==========================================
  Files          83       95      +12     
  Lines        4061     4785     +724     
==========================================
+ Hits         3475     4129     +654     
- Misses        586      656      +70     
Impacted Files Coverage Δ
src/ForneyLab.jl 100.00% <ø> (ø)
src/factor_nodes/transition_mixture.jl 95.65% <95.65%> (ø)
...c/engines/julia/update_rules/transition_mixture.jl 100.00% <100.00%> (ø)
src/factor_nodes/contingency.jl 87.50% <100.00%> (+5.14%) :arrow_up:
src/update_rules/transition_mixture.jl 100.00% <100.00%> (ø)
src/engines/julia/update_rules/probit.jl 82.08% <0.00%> (-10.42%) :arrow_down:
src/factor_nodes/bernoulli.jl 84.61% <0.00%> (-5.71%) :arrow_down:
src/factor_nodes/categorical.jl 77.19% <0.00%> (-2.81%) :arrow_down:
src/engines/julia/update_rules/sample_list.jl 87.50% <0.00%> (-2.50%) :arrow_down:
src/update_rules/nonlinear_sampling.jl 98.82% <0.00%> (-1.18%) :arrow_down:
... and 22 more

Continue to review full report at Codecov.

Legend - Click here to learn more Δ = absolute <relative> (impact), ø = not affected, ? = missing data Powered by Codecov. Last update 5d9110e...a8b143e. Read the comment docs.