Releases | Open Source Science

HiddenMarkovModels.jl - v0.7.0

HiddenMarkovModels v0.7.0

Diff since v0.6.3

Breaking changes

Shift temporal effect of control on transition matrix (https://github.com/gdalle/HiddenMarkovModels.jl/pull/138). The control variable $ut$ used to influence the transition matrix from $xt$ to $x{t+1}$, now it influences the transition from $x{t-1}$ to $x_t$ (which is more coherent with the observation process). Models without controls are not affected by this change.

Merged pull requests: - BREAKING CHANGE: Shift temporal effect of control on transition matrix (#138) (@gdalle)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] 8 months ago

HiddenMarkovModels.jl - v0.6.3

HiddenMarkovModels v0.6.3

Diff since v0.6.2

Merged pull requests: - Skip broken alloc test on 1.11 (#128) (@gdalle) - Add precompilation workload (#133) (@gdalle) - Revert "Add precompilation workload" (#135) (@gdalle) - Format (#136) (@gdalle) - Bump (#137) (@gdalle)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] 8 months ago

HiddenMarkovModels.jl - v0.6.2

HiddenMarkovModels v0.6.2

Diff since v0.6.1

Merged pull requests: - Add citation to README (#124) (@gdalle) - Don't error if the loglikelihood isn't finite (#127) (@gdalle)

Closed issues: - HDP priors? (#118)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] 10 months ago

HiddenMarkovModels.jl - v0.6.1

HiddenMarkovModels v0.6.1

Diff since v0.6.0

Merged pull requests: - Clarify discrete aspect in README (#117) (@adannenberg) - Functional API for applying transition matrix (#121) (@gdalle) - Restrict single-threading to single sequence (#122) (@gdalle)

Closed issues: - Linear memory Baum-Welch? (#7)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] about 1 year ago

HiddenMarkovModels.jl - v0.6.0

HiddenMarkovModels v0.6.0

Breaking changes

In-place single-sequence routines were hidden from the public API. Most user code will not be affected.

Performance improvements

Multithreading is now deactivated if seq_ends is passed as an NTuple. This helps remove overhead for very few sequences (especially for a single one).

Diff since v0.5.4

Merged pull requests: - Decompose forward function into initialize, predict, update (#105) (@THargreaves) - Update inference routines (#116) (@gdalle)

Closed issues: - Stop testing against HMMBase (#109) - Avoid @threads for a single sequence (#110)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] over 1 year ago

HiddenMarkovModels.jl - v0.5.4

HiddenMarkovModels v0.5.4

Diff since v0.5.3

Merged pull requests: - Minor optimizations and simd (#108) (@gdalle) - Make HMMBase optional in the test suite (#111) (@gdalle) - Fix loglikelihood increase check in Baum-Welch (#112) (@gdalle) - Disable multithreading when seq_ends is passed as a tuple (#113) (@gdalle) - Bump version to 0.5.4 (#114) (@gdalle) - Improve code coverage (#115) (@gdalle)

Closed issues: - Avoid repeated transposition when using time-homogenous transition matrix (#106)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] over 1 year ago

HiddenMarkovModels.jl - v0.5.3

HiddenMarkovModels v0.5.3

Diff since v0.5.2

Merged pull requests: - Allow heterogeneous distributions (#102) (@gdalle)

Closed issues: - Allow dist to be a Vector{Distribution{Univariate, Continuous}} in Baum Welch (#101)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] over 1 year ago

HiddenMarkovModels.jl - v0.5.2

HiddenMarkovModels v0.5.2

Diff since v0.5.1

Merged pull requests: - Add JOSS citation (#98) (@gdalle) - Allow different types for elementwise log (#100) (@gdalle)

Closed issues: - Allow different types for transition matrix and elementwise log (#99)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] over 1 year ago

HiddenMarkovModels.jl - v0.5.1

HiddenMarkovModels v0.5.1

Diff since v0.5.0

Merged pull requests: - Final benchmarks (#94) (@gdalle) - Fix benchmark reproducibility (#95) (@gdalle) - Remove precompilation (#97) (@gdalle)

Closed issues: - Benchmarks (#2) - Porting issues from HMMBase.jl (#92)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] almost 2 years ago

HiddenMarkovModels.jl - v0.5.0

HiddenMarkovModels v0.5.0

Diff since v0.4.1

See #93 for the user-facing changes

Merged pull requests: - Fix benchmarks (#90) (@gdalle) - Speed up viterbi (#93) (@gdalle)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] almost 2 years ago

HiddenMarkovModels.jl - v0.4.1

HiddenMarkovModels v0.4.1

Diff since v0.4.0

Merged pull requests: - Document fit! (#88) (@gdalle)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] almost 2 years ago

HiddenMarkovModels.jl - v0.4.0

HiddenMarkovModels v0.4.0

Diff since v0.3.1

Breaking changes

See the API reference for more details

Multiple sequences:

Revamped multiple sequence formatting: multiple sequences are concatenated for the input and for the output

Removals:

Removed alias HMMs for the package name
Removed everything related to (Abstract)MarkovChain
Removed PermutedHMM

Renamings:

initial_distribution(hmm) became initialization(hmm)
obs_distribution(hmm, i) became obs_distributions(hmm)
in baum_welch, check_loglikelihood_increasing became loglikelihood_increasing

Storage:

in ForwardBackwardStorage, ξ is now a vector of abstract matrices instead of a 3-dimensional array

Method signatures:

Revamped multiple sequence formatting: algorithm(hmm, obs_seqs, nb_seqs) became algorithm(hmm, obs_seq, [control_seq]; seq_ends).
Modified the arguments for in-place fitting: fit!(hmm, init_count, trans_count, obs_seq, state_marginals) became fit!(hmm, fb_storage, obs_seq, control_seq; seq_ends)

Return types;

Revamped multiple sequence formatting: results are now concatenated, and loglikelihoods are computed sequencewise

Merged pull requests: - Stdlib compat + Documenter v1 + bump to 0.3.1 (#54) (@gdalle) - Add TagBot workflow (#55) (@gdalle) - Move Python deps from pip to conda (#57) (@gdalle) - Fix docs benchmark (#58) (@gdalle) - Complete revamp (#59) (@gdalle) - Minor fixes (#60) (@gdalle) - Reactivate multithreaded BW (#62) (@gdalle) - Put benchmarks inside HMMBenchmark subpackage (#63) (@gdalle) - Move DependaBot (#64) (@gdalle) - Split (#66) (@gdalle) - Simplify docstrings (#67) (@gdalle) - Typo (#68) (@gdalle) - Benchmarks with Python updated (#69) (@gdalle) - More benchmarks (#70) (@gdalle) - Don't tune forward (#71) (@gdalle) - Threads (#72) (@gdalle) - Remove deps and fix Enzyme (#73) (@gdalle) - Remove pre 1.9 stuff (#74) (@gdalle) - Switch to StableRNGs (#75) (@gdalle) - Clean up benchmarks (#77) (@gdalle) - Add multithreading (#78) (@gdalle) - 1 OpenBLAS thread (#79) (@gdalle) - Parallelize fitting (#80) (@gdalle) - Fairer Python benchmarks (#82) (@gdalle) - Format (#83) (@gdalle) - Correct benchmarks (#84) (@gdalle) - Add codecov token and documenter key (#85) (@gdalle) - Better docs and numerical stability (#87) (@gdalle)

Closed issues: - Chain rule (#3) - Benchmarks on different distributions (#8) - Add SIMD (#9) - Add links to (and comparisons with) other related packages (#14) - Make modification to allow support for Heterogeneous (Periodic) Hidden Markov Models (#52) - Clarify docs on the arguments of fit! (#53) - Fix benchmarks (#61) - MethodError Using baum_welch with MvLogNormal Emission Distributions (#76) - Test numerical stability (#86)

Scientific Software - Peer-reviewed - Julia
Published by github-actions[bot] almost 2 years ago

HiddenMarkovModels.jl - v0.3.1

What's Changed

Local benchmarks leveraging parallelism by @gdalle in https://github.com/gdalle/HiddenMarkovModels.jl/pull/50
Stdlib compat + Documenter v1 + bump to 0.3.1 by @gdalle in https://github.com/gdalle/HiddenMarkovModels.jl/pull/54

Full Changelog: https://github.com/gdalle/HiddenMarkovModels.jl/compare/v0.3.0...v0.3.1

Scientific Software - Peer-reviewed - Julia
Published by gdalle about 2 years ago