v0.23.0

Announcements

• Re-licensing: license change from
  AGPLv3 to
  Apache-2.0 (see #997 for
  details)
• sbi is now affiliated with NumFOCUS 🎉
• 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., SNPE to NPE (i.e., we
  removed the S prefix). 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 sbi default parameters: training_batch_size=200, num_chains=20 (#1221)
  (@janfb)
• change imports of posterior_nn, likelihood_nn, and classifier_nn. They should
  now be imported from sbi.neural_nets, not from sbi.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)NPE given 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 sbi in 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 MNLE to 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.toml for 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 pyright and fix all typing errors (#1045, #1108) (@Baschdl)
• introduce two docs versions: latest pointing to latest release at
  https://sbi-dev.github.io/sbi/latest/ and dev pointing to the latest version on
  main https://sbi-dev.github.io/sbi/dev/