git: 74a3ce7db549 - main - math/py-iminuit: Update 2.12.0 -> 2.15.2
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Date: Sun, 07 Aug 2022 05:46:41 UTC
The branch main has been updated by yuri: URL: https://cgit.FreeBSD.org/ports/commit/?id=74a3ce7db549e9af545bb125f04dfd489972f85f commit 74a3ce7db549e9af545bb125f04dfd489972f85f Author: Yuri Victorovich <yuri@FreeBSD.org> AuthorDate: 2022-08-07 05:45:58 +0000 Commit: Yuri Victorovich <yuri@FreeBSD.org> CommitDate: 2022-08-07 05:46:36 +0000 math/py-iminuit: Update 2.12.0 -> 2.15.2 --- math/py-iminuit/Makefile | 6 ++++-- math/py-iminuit/distinfo | 6 +++--- math/py-iminuit/pkg-descr | 2 +- 3 files changed, 8 insertions(+), 6 deletions(-) diff --git a/math/py-iminuit/Makefile b/math/py-iminuit/Makefile index 16353cbec67c..30fa8e07e442 100644 --- a/math/py-iminuit/Makefile +++ b/math/py-iminuit/Makefile @@ -1,5 +1,5 @@ PORTNAME= iminuit -DISTVERSION= 2.12.0 +DISTVERSION= 2.15.2 CATEGORIES= math python MASTER_SITES= CHEESESHOP PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX} @@ -14,6 +14,8 @@ BUILD_DEPENDS= cmake:devel/cmake RUN_DEPENDS= ${PYNUMPY} USES= compiler:c++14-lang python:3.6+ -USE_PYTHON= distutils autoplist +USE_PYTHON= distutils autoplist pytest # 2 tests are known to fail, see https://github.com/scikit-hep/iminuit/issues/779 + +TEST_ENV= ${MAKE_ENV} PYTHONPATH=${STAGEDIR}${PYTHONPREFIX_SITELIBDIR} .include <bsd.port.mk> diff --git a/math/py-iminuit/distinfo b/math/py-iminuit/distinfo index 5c4c67968301..419ede957f2c 100644 --- a/math/py-iminuit/distinfo +++ b/math/py-iminuit/distinfo @@ -1,3 +1,3 @@ -TIMESTAMP = 1656211070 -SHA256 (iminuit-2.12.0.tar.gz) = cd0e3cb751302c066984eab30612c5d2419a54317febe51b50be1fa21afc51a9 -SIZE (iminuit-2.12.0.tar.gz) = 420687 +TIMESTAMP = 1659850085 +SHA256 (iminuit-2.15.2.tar.gz) = 60ac7d2fe9405c9206675229273f401611d3f5dfa22942541646c4625b59f1ea +SIZE (iminuit-2.15.2.tar.gz) = 429553 diff --git a/math/py-iminuit/pkg-descr b/math/py-iminuit/pkg-descr index 45edce711d9d..dae39a4ae443 100644 --- a/math/py-iminuit/pkg-descr +++ b/math/py-iminuit/pkg-descr @@ -5,4 +5,4 @@ It can be used as a general robust function minimisation method, but is most commonly used for likelihood fits of models to data, and to get model parameter error estimates from likelihood profile analysis. -WWW: https://github.com/scikit-hep/iminuit +WWW: https://iminuit.readthedocs.io/en/stable/