Releases: sbi-dev/sbi
Releases · sbi-dev/sbi
v0.24.0
✨ Highlights
- feat: add
CategoricalMADEby @jnsbck in #1269 (Major New Feature) - tests:
mini-sbibmby @manuelgloeckler in #1335 (Major New Feature) - feat: Score-based iid sampling by @manuelgloeckler in #1381 (Major New Feature)
- Drop python3.9 support, fix ci by @janfb in #1412 (Python Version Support Change)
- additional features for NPSE by @gmoss13 in #1370 (Enhancement)
🐛 Bug Fixes
- fix: leakage correction breaks consistency of log prob vs log prob batched by @manuelgloeckler in #1355
- fix #1343 device handling in mog_log_prob by @janfb in #1356
- Fix failing tutorials, change MNLE default for log_transform to False by @janfb in #1367
- Fix conditional posterior shape and device bugs. by @janfb in #1373
- fix: type fix in VI subclasses. xfail pymc tests. by @janfb in #1390
- Temporary Wrappers to fix MADE by @gmoss13 in #1398
- Fix mnle tests, MCMC init pbar, sir batch size. by @janfb in #1410
- fix mnle tests by @janfb in #1415
- fix: protocol and refactor for custom potential by @janfb in #1409
- fix docs workflow by @janfb in #1419
- fix: gpu-handling for CategoricalMADE by @janfb in #1448
🛠️ Maintenance & Improvements
- increase tutorial test timeout by @janfb in #1360
- add nan check to _loss method. by @janfb in #1361
- Update and pin pre commit and ruff to recent version. by @janfb in #1358
- add nan handling in diagnostics by @janfb in #1359
- Improve tests to detect circular imports and resolve all of them by @manuelgloeckler in #1357
- docs: add details about zuko density estimators by @janfb in #1387
- fix: duplication of 'large number' in warning by @turnmanh in #1391
- improve PR and issue templates by @janfb in #1399
- perf: speed up CI with uv by @janfb in #1400
- tests: add pytest testmon plugin to speed up CI by @janfb in #1402
- small fixes to score methods by @janfb in #1404
- docs: Corrected python version in installation document (Revised) by @VijaySamant4368 in #1423
- docs: Markdown formatting compliant to Markdown Linter (solves #1434) by @nMaax in #1443
🎉 New Contributors
- @VijaySamant4368 made their first contribution in #1423
- @nMaax made their first contribution in #1443
Full Changelog: v0.23.3...v0.24.0
Contributors
janfb, turnmanh, and 5 other contributors
Assets 2
v0.23.3
v0.23.3
Highlights 🤩
- docs: Add conda-forge install instructions by @matthewfeickert in #1340
- feat:
NLEwith multiple iid conditions by @janfb in #1331
What's Changed 🚧
- fix: Correted typo in y-axis label by @turnmanh in #1296
- docs: update embedding networks notebook by @emmanuel-ferdman in #1297
- fix pickle issues in MCMC posterior + test by @manuelgloeckler in #1291
- Minor fix for EnsemblePosterior weights.setter by @CompiledAtBirth in #1299
- Remove deprecated neural_net access from
utilsby @tvwenger in #1302 - [test] add tests for ensemble posterior weights by @samadpls in #1307
- Clarify last round behavior of SNPE-A by @michaeldeistler in #1323
- expose batched sampling option; error handling by @janfb in #1321
- Fix #1316: remove sample_dim docstring for condition. by @janfb in #1338
- docs: fix tutorial typos by @janfb in #1341
- docs: run and seed SBC tutorial by @manuel-morales-a in #1336
New Contributors 🎉
- @emmanuel-ferdman made their first contribution in #1297
- @CompiledAtBirth made their first contribution in #1299
- @tvwenger made their first contribution in #1302
- @matthewfeickert made their first contribution in #1340
- @manuel-morales-a made their first contribution in #1336
Full Changelog: v0.23.2...v0.23.3
Contributors
matthewfeickert, tvwenger, and 8 other contributors
Assets 2
v0.23.2
Bug Fixes
- fixup for failing hmc test by @michaeldeistler (#1247)
- fix: make RestrictedPrior a distribution to enable log_prob @janfb (#1257)
- fix: npe iid handling by @janfb (#1262)
- fix: tutorials test error handling, fix bugs in tutorials by @janfb (#1264)
- fix #1260: include points in plotting limits by @janfb (#1265)
- fix: conditioned potential error handling by @janfb, @michaeldeistler (#1275, #1289)
- fix: Allow 1D pytorch distributions by @michaeldeistler (#1286)
Documentation
- Rename SNPE to NPE in the README by @michaeldeistler (#1248)
- update pickling FAQ by @michaeldeistler (#1255)
- Adding example for custom DataLoader to tutorial 18 by @psteinb (#1256)
- docs: add readme intro to docs landing page by @janfb (#1272)
- Change sampling method for LC2ST to
sample_batched()by @JuliaLinhart (#1279)
Maintenance
- Refactor simulate_for_sbi location by @samadpls (#1253)
- build: devcontainer update by @janfb (#1252)
- fix: docker notebook python version by @janfb (#1258)
- refactor: remove outputs except plots from tutorials. by @janfb (#1266)
- build: automatic nb stripping and pypi upload by @janfb (#1267)
- refactor: remove deprecated x_shape where not needed by @janfb (#1271)
- more explicit error message for CNN shapes by @Ankush7890 (#1281)
Contributors
psteinb, janfb, and 4 other contributors
Assets 2
v0.23.1
v0.23.0
Announcements
- Re-licensing: license change from
AGPLv3 to
Apache-2.0 (see #997 for
details) sbiis now affiliated withNumFOCUS🎉- New contributors 🎉: @anastasiakrouglova, @theogruner, @felixp8, @Matthijspals,
@jsvetter, @pfuhr, @turnmanh, @fariedabuzaid, @augustes, @zinaStef, @Baschdl,
@danielmk, @lisahaxel, @janko-petkovic, @samadpls, @ThomasGesseyJonesPX, @schroedk
Major Changes
- internal renaming of all inference classes from, e.g.,
SNPEtoNPE(i.e., we
removed theSprefix). The functionality of the classes remains the same. The NPE
class handles both the amortized and sequential versions of neural posterior
estimation. An alias for SNPE (and other sequential methods) still exists for
backwards compatibility (#1238) (@michaeldeistler). - change
sbidefault parameters:training_batch_size=200,num_chains=20(#1221)
(@janfb) - change imports of
posterior_nn,likelihood_nn, andclassifier_nn. They should
now be imported fromsbi.neural_nets, not fromsbi.utils(#994) (@famura) - big refactoring of plotting utilities, new tutorial (#1084) (@Matthijspals)
- improved tutorials and website documentation (#1012, #1051, #1073) (@augustes,
@zinaStef, @lisahaxel, @psteinb) - improved website structure and contribution guides (#1019) (@tomMoral, @janfb)
- drop support for python3.8 and torch1.12 (#1233)
- refactor folder structure and naming of
neural_nets(#1237) (@michaeldeistler)
New Features
- full flexibility over the training loop (#983) (@michaeldeistler)
- unified density estimator classes (#952, #965, #979, #1151) (@michaeldeistler,
@gmoss13, @tomMoral, @manualgloeckler) - vectorized sampling and log_prob for
(S)NPEgiven batches of x (#1153)
(@manuelgloeckler, @michaeldeistler) - batched sampling for vectorized MCMC samplers (#1176, #1210) (@gmoss13, @janfb)
- support @Zuko as a backend for normalizing flows (#1088, #1116)
(@anastasiakrouglova) - local c2st metric (#1109) (@JuliaLinhart)
- tarp coverage metric (#1106) (@psteinb)
- add interface for @pymc samplers (#1053) (@famura, @felixp8)
- flow matching density estimators (#1049) (@turnmanh, @fariedabuzaid, @janfb)
- score matching density estimators (#1015) (@rdgao, @jsvetter, @pfuhr,
@manuelgloeckler, @michaeldeistler, @janfb) - ABC methods for trial-based data using statistical distances (#1104)
(@theogruner) - support Apple MPS as gpu device (#912) (@janfb)
- dev container for using
sbiin codespaces on GitHub (#1070) (@turnmanh) - enable importance sampling for likelihood-based estimators (#1183) (@manuelgloeckler)
- refactoring and unified shape handling for
RatioEstimator(#1097) (@bkmi) - faster sbc and tarp calibration checks via batched sampling (#1196) (@janfb)
- batched sampling and embedding net support for
MNLE(#1203) (@janfb) - adapt
MNLEto new densitye stimator abstraction (#1089) (@coschroeder) - better plotting options for coverage plots (#1039, #1212) (@janfb)
- allow for potential_fn to be a Callable (#943) (@michaeldeistler)
Bug Fixes
- bugfix for embedding net tutorial (#1159) (@Deismic)
- Fixup for process_x in EnsemblePosterior (#1148) (@Deismic)
- fixed notebook by changing MCMC parameters (#1058) (@zinaStef)
- fix: add NeuralPosteriorEnsemble to utils.init (#1002) (@jnsbck)
- fix: print_false_positive_rate (#976) (@danielmk)
- fix: make VIPosterior pickable (#951) (@manuelgloeckler)
- fix: bug in importance sampled posterior (#1081) (@max-dax)
- fix: embedding device and warning handling (#1186) (@janfb)
- fix: c2st with constant features (#1204) (@janfb)
- fix: erroneous warnings about different devices (#1225, @ThomasGesseyJonesPX)
- fix: type annotation in class
ConditionedPotential(#1222) (@schroedk)
Maintenance and other changes
- add pre-commit hooks (#955) (@janfb)
- add ruff to replace
isort,black,flake(#960, #978, #1113) (@janfb) - switch to
pyproject.tomlfor package specification (#941) (@janfb) - Split the GitHub workflow in CI and CD (#1063) (@famura)
- split linting process from the CI/CD workflow (#1164) (@tomMoral)
- Switch to the newest
pyrightand fix all typing errors (#1045, #1108) (@Baschdl) - introduce two docs versions:
latestpointing to latest release at
https://sbi-dev.github.io/sbi/latest/ anddevpointing to the latest version on
mainhttps://sbi-dev.github.io/sbi/dev/
Contributors
Zuko, psteinb, and 31 other contributors
Assets 2
v0.22.0
API change
- We have moved
sbito an new github organization:https://github.com/sbi-dev/sbi - We have changed the website of the
sbidocs:https://sbi-dev.github.io/sbi/. sbi.analysis.pairplot:upperwas replaced byoffdiagand will be deprecated in a future release.
Features and enhancements
- size-invariant embedding nets for amortized inference with iid-data (@janfb, #808)
- option for new using MAF with rational quadratic splines (thanks to @ImahnShekhzadeh, #819)
- improved docstring for
process_prior(thanks to @musoke, #813) - extended tutorial for SBI with iid data (@janfb, #857)
- new tutorial for SBI with experimental conditions and mixed data (@janfb, #829)
- New options for
pairplot:upperis now calledoffdiagto match other kwargs.- alternating colors for
samplesandpoints - option to add a
legendand passkwargsfor the legend.
Bug fixes
- fixed memory leak in in
append_simulations(thanks to @VictorSven, #803) - bug fix for CNRE (thanks to @bkmi, #815)
- bug fix for iid-inference with posterior ensembles (@janfb, #826)
- bug fix for simulation-based calibration with VI posteriors (@janfb, #834, #838)
- bug fix for BoxUniform device handling (@janfb, #854, #856)
- bug fix for MAP estimates with independent priors (@janfb, #867)
- bug fix for tutorial on SBC (@michaeldeistler, #891)
- fix spurious seeding for
simulate_for_sbi(@jan-matthis, #876) - bump python version of github action tests to
3.9.13(@michaeldeistler, #888, #900)
Contributors
jan-matthis, janfb, and 4 other contributors
Assets 2
v0.21.0
- implementation of "Contrastive Neural Ratio Estimation" (thanks to @bkmi, #787)
- implementation of "Balanced Neural Ratio Estimation" (thanks to @ADelau, #779)
- bugfixes for SBC, device handling and handling of iid-observations (#793, #789, #780)
Contributors
bkmi and ADelau
Assets 2
v0.20.0
Major changes and bug fixes
- implementation of "Truncated proposals for scalable and hassle-free sbi" (#754)
- sample-based expected coverage tests (#754)
- permutation invariant embedding to allow iid data in SNPE (thanks @coschroeder, #751)
- convolutional neural network embedding (thanks @coschroeder, #745, #751, #769)
- disallow invalid simulations when using SNLE, SNRE, or atomic SNPE-C (#768)
Enhancements
Contributors
coschroeder