diff --git a/.zenodo.json b/.zenodo.json index 450823e..81596d6 100644 --- a/.zenodo.json +++ b/.zenodo.json @@ -1,8 +1,8 @@ { "description": "pyhf plug-in for spey package", "license": "MIT", - "title": "SpeysideHEP/spey-pyhf: v0.1.7", - "version": "v0.1.7", + "title": "SpeysideHEP/spey-pyhf: v0.1.8", + "version": "v0.1.8", "upload_type": "software", "creators": [ { @@ -29,7 +29,7 @@ }, { "scheme": "url", - "identifier": "https://github.com/SpeysideHEP/spey-pyhf/tree/v0.1.7", + "identifier": "https://github.com/SpeysideHEP/spey-pyhf/tree/v0.1.8", "relation": "isSupplementTo" }, { diff --git a/docs/releases/changelog-v0.1.md b/docs/releases/changelog-v0.1.md index 7121bc2..ea16cc7 100644 --- a/docs/releases/changelog-v0.1.md +++ b/docs/releases/changelog-v0.1.md @@ -42,6 +42,9 @@ [#5](https://github.com/SpeysideHEP/spey-pyhf/issues/5). ([#2](https://github.com/SpeysideHEP/spey-pyhf/pull/2)) +* Bugfix in uncertainty quantification for full statistical model mapping on effective sigma + ([#15](https://github.com/SpeysideHEP/spey-pyhf/pull/15)) + ## Contributors This release contains contributions from (in alphabetical order): diff --git a/setup.py b/setup.py index f42c304..67ca780 100644 --- a/setup.py +++ b/setup.py @@ -37,7 +37,7 @@ }, download_url=f"https://github.com/SpeysideHEP/spey-pyhf/archive/refs/tags/v{version}.tar.gz", author="Jack Y. Araz", - author_email=("jackaraz@jlab.org"), + author_email=("jack.araz@stonybrook.edu"), license="MIT", package_dir={"": "src"}, packages=find_packages(where="src"), diff --git a/src/spey_pyhf/_version.py b/src/spey_pyhf/_version.py index 0e31141..8dc4389 100644 --- a/src/spey_pyhf/_version.py +++ b/src/spey_pyhf/_version.py @@ -1,3 +1,3 @@ """Version of the spey - pyhf plugin""" -__version__ = "0.1.7" +__version__ = "0.1.8" diff --git a/src/spey_pyhf/simplify.py b/src/spey_pyhf/simplify.py index 0b01d10..0600861 100644 --- a/src/spey_pyhf/simplify.py +++ b/src/spey_pyhf/simplify.py @@ -428,8 +428,12 @@ def __call__( elif convert_to == "default_pdf.effective_sigma": # Get 68% quantiles q = (1.0 - (norm.cdf(1.0) - norm.cdf(-1.0))) / 2.0 + # upper and lower uncertainties absolute_uncertainty_envelops = np.stack( - [np.quantile(samples, q, axis=0), np.quantile(samples, 1 - q, axis=0)], + [ + np.abs(np.quantile(samples, 1 - q, axis=0) - background_yields), + np.abs(background_yields - np.quantile(samples, q, axis=0)), + ], axis=1, ) save_kwargs.update(