0.11.0

What's Changed

Breaking changes

• Drop tensorflow backend by @frazane in #122
• Drop support for Python 3.11 by @frazane in #121

New features

• NaN-handling for ensemble CRPS by @frazane in #118

Documentation

• Improvements to math rendering in docs by @frazane in #120
• Add CONTRIBUTING with release runbook and CI overview by @frazane in #129

CI / tooling

• CI: workflow hygiene + coverage fold by @frazane in #124
• Add Dependabot for GitHub Actions updates by @frazane in #125
• ci: bump the actions group with 4 updates by @dependabot[bot] in #126
• Harden release workflow: build-once + OIDC trusted publishing by @frazane in #127
• Add contributor templates, PR labeler, and release-note categories by @frazane in #128
• Consolidate release-note labels onto GitHub defaults by @frazane in #130

New Contributors

• @dependabot[bot] made their first contribution in #126

Full Changelog: v0.10.0...0.11.0

v0.10.0

What's Changed

Highlight: ensemble-based functions now accept optional weighting for members of the ensemble.

• Add DSS to Docs by @simon-hirsch in #108
• Issue 107 return types by @simon-hirsch in #109
• Drop support for Python 3.10 by @frazane in #111
• Allow testing backends separately by @frazane in #112
• No longer require positional-only arguments in top-level API by @frazane in #113
• Add utility functions and refactor score function interface by @sallen12 in #115
• Add option to have ensemble weights by @sallen12 in #117

Full Changelog: v0.9.0...v0.10.0

v0.9.0

What's Changed

• Make crps_t robust by @sallen12 in #96
• Lazy compilation for numba gufuncs by @frazane in #103
• Dawid-Sebastiani score by @sallen12 in #104
• Extend availability of ensemble score estimators by @sallen12 in #102
• Add crps_csg0 for 0-censored shifted gamma distribution by @tobiasbiegert in #97

New Contributors

• @tobiasbiegert made their first contribution in #97

Full Changelog: v0.8.0...v0.9.0

v0.8.0

Important

This release contains breaking changes, including renaming of some function arguments. After this, we expect the API to remain relatively stable as we approach the v1.0 release.

What's Changed

• Refactor tests and increase coverage by @frazane in #87
• allow batched implementation of censored and truncated distributions by @sallen12 in #92
• Bugfix for normal mixture CRPS on GPU (Torch) by @cbuelt in #100
• Extend documentation by @sallen12, @nicholasloveday and @frazane in #94

New Contributors

• @cbuelt made their first contribution in #100

Full Changelog: v0.7.1...v0.8.0

v0.7.1

Important

We advise all users using v0.7.0 to upgrade to this release as it comes with critical bug fixes.

What's Changed

• Add quantile score by @frazane in #78
• Preserve autograd history in torch backend by @frazane in #79
• Refactor interval scores and improve testing by @frazane in #82
• Bugfix for numba CRPS estimators check by @frazane in #85

Full Changelog: v0.7.0...v0.7.1

v0.7.0

This release adds several new scores. Big thanks to @sallen12 !

What's Changed

• Add log score for laplace distributions by @sallen12 in #63
• Add log scores for beta, exponential and two-piece distributions by @sallen12 in #64
• Add log score for negative binomial distribution by @sallen12 in #65
• Add log score for gev and gpd distributions by @sallen12 in #66
• Add crps and log score for mixture of normal distributions by @sallen12 in #73
• Add log score for ensemble forecasts by @sallen12 in #74
• Add Gaussian kernel score for ensemble forecasts by @sallen12 in #70
• Add ranked probability score by @sallen12 in #71
• Add the log score and ranked logarithmic score by @sallen12 in #72
• Add censored and conditional likelihood scores by @sallen12 in #76
• Add weighted versions of the Gaussian kernel score by @sallen12 in #77

Full Changelog: v0.6.1...v0.7.0

v0.6.1

Fixed missing imports.

Full Changelog: v0.6.0...v0.6.1

v0.6.0

This release focuses on the implementation of closed forms of the CRPS for several new distributions.

What's Changed

• Brier score: Correct order of arguments in pass-through to core score function by @simon-hirsch in #31
• improved examples in crps docs by @nicholasloveday in #33
• Add CRPS for beta distribution by @frazane in #37
• Add CRPS for the exponentialM distribution by @frazane in #39
• Add CRPS for binomial distribution by @frazane in #38
• Add CRPS for the gamma distribution by @frazane in #40
• Add CRPS for GEV distribution by @frazane in #42
• Add CRPS for generalized pareto distribution by @frazane in #43
• Add CRPS for the hypergeometric distribution by @frazane in #44
• Add CRPS for the Laplace distribution by @frazane in #45
• Add CRPS for the log-Laplace distribution by @frazane in #46
• Add CRPS for the loglogistic distribution by @frazane in #47
• Add CRPS for the generalised truncated and censored normal distribution by @sallen12 in #49
• Add CRPS for the uniform distribution by @sallen12 in #50
• Add CRPS for the generalised truncated and censored logistic distribution by @sallen12 in #48
• Add CRPS for the Poisson distribution by @sallen12 in #51
• Add CRPS for Student's t distribution by @sallen12 in #52
• Add CRPS for the generalised truncated and censored t distribution by @sallen12 in #53
• Use uv package management tool by @frazane in #54
• Add CRPS for two piece exponential distribution by @sallen12 in #57
• Update CI workflow by @frazane in #58
• Fix coverage report upload to codecov by @frazane in #59
• Add CRPS for the negative binomial distribution by @sallen12 in #55
• add crps for twopiece normal distribution by @sallen12 in #56
• Add log scores for some parametric distributions by @sallen12 in #61
• Add log score for the truncated logistic, normal and t distributions by @sallen12 in #62
• Wrap numba imports in try-except blocks by @frazane in #69

New Contributors

• @nicholasloveday made their first contribution in #33

Full Changelog: v0.5.3...v0.6.0

v0.5.3

Added support for python 3.12

v0.5.2

This minor release adds another parametric form of the CRPS and a new type of scoring rule: the interval-based Winkler score. Additionally, we start to widen the scope of the library by introducing the first graphical verification tool, the reliability diagram. In the future, we plan to add other graphical tools to diagnose calibration as they are important to complement scoring rules.

New features

• Closed-form CRPS for the exponential distribution in #27 by @sallen12 and @frazane
• CORP reliability diagram in #23 by @frazane
• Interval/Winkler Score in #24 by @simon-hirsch