Releases: issp-center-dev/PHYSBO
Releases · issp-center-dev/PHYSBO
v2.1.0
v2.0.2
v2.0.1
v2.0.0
Important Notice
From v2.0.0, PHYSBO is distributed under the Mozilla Public License (MPL) v2.
v2.0.0より、 PHYSBO は Mozilla Public License (MPL) v2 のもとで公開・頒布されます。
This change makes it clear that code importing PHYSBO will not be affected by copyleft. However, if you modify and redistribute PHYSBO itself, copyleft will still apply, and you will need to redistribute it under MPL v2.
これにより、PHYSBO を import するコードについては、コピーレフトの影響を受けないことが明確になりました。一方、PHYSBO そのものを修正して再頒布する場合には、これまでと同様にコピーレフトが働き、MPL v2 の下で再頒布する必要があります。
What's Changed
Full Changelog: v1.1.1...v2.0.0
v1.1.1
Changed from v1.1.0
- Bug fixes
- Use numpy<1.20 for installing physbo for python<=3.9 (#49)
- This solves the problem of mismatches of the size of numpy objects
get_post_fmean
,get_post_fcov
, andget_score
now work just afterpolicy.write
(interactive mode) (#42, #51)- Remove evaluated actions from loaded policy (#44, #45)
- Remove actions on writing history (
policy.write
) (#43, #46)- Thanks @k-kitai for making a PR!
- Use numpy<1.20 for installing physbo for python<=3.9 (#49)
Full Changelog: v1.1.0...v1.1.1
v1.1.0
Changed from v1.0.1
- New feature
- Now
history
stores elapsed times (#28, #40)time_total
: total time in stepstime_update_predictor
: time for updating model, e.g., learning hyper parameterstime_get_action
: time for suggesting next actions (candidates)time_run_simulator
: time for evaluating objective functions
is_disp
argument ofbayes_search
now can suppress the message in the hyper-parameter learning process (#41)- NOTE: Previously, users had to set
config.learning.is_disp = False
in order to suppress.
- NOTE: Previously, users had to set
- Now
- Bug fixes
Full Changelog: v1.0.1...v1.1.0
v1.0.1
Release notes
Changes from v1.0.0
v1.0.0
Release note
Changes from v0.3.x
New features
policy.get_post_fmean(xs)
(#17)- mean values of the trained predictor (the post-distribution of the Guassian process) at points
xs
- mean values of the trained predictor (the post-distribution of the Guassian process) at points
policy.get_post_fcov(xs)
(#17)- covariance of the trained predictor (the post-distribution of the Guassian process) at points
xs
- covariance of the trained predictor (the post-distribution of the Guassian process) at points
policy.get_score(mode, xs_or_actions)
(#16)- score (acquisition function) at points xs or actions
Changes
- Move
physbo.search.discrete.policy_mo
tophysbo.search.discrete_multi.policy
(#13)
Fixes
Documents
- English manual is uploaded.
v0.3.0
Release note
Changes from v0.2.x
New features
- Multi-objective optimization (Pareto optimization)
- Initialize
policy
(model) with pre-evaluated training datasets - Parallelization for evaluating acquisition function (score) on each candidate (EXPERIMENTAL)
Documents
- Tutorials are updated
- Multi-objective optimization
- Initialize with pre-evaluated data
Others
pip install
from the local source code is enabled