diff options
Diffstat (limited to 'math/py-spvcm')
| -rw-r--r-- | math/py-spvcm/Makefile | 31 | ||||
| -rw-r--r-- | math/py-spvcm/distinfo | 3 | ||||
| -rw-r--r-- | math/py-spvcm/pkg-descr | 6 |
3 files changed, 0 insertions, 40 deletions
diff --git a/math/py-spvcm/Makefile b/math/py-spvcm/Makefile deleted file mode 100644 index 731ff1b7e83e..000000000000 --- a/math/py-spvcm/Makefile +++ /dev/null @@ -1,31 +0,0 @@ -PORTNAME= spvcm -PORTVERSION= 0.3.0 -PORTREVISION= 2 -CATEGORIES= math python -MASTER_SITES= PYPI -PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX} - -MAINTAINER= sunpoet@FreeBSD.org -COMMENT= Fit spatial multilevel models and diagnose convergence -WWW= https://github.com/pysal/spvcm - -LICENSE= BSD3CLAUSE - -DEPRECATED= Upstream repository has been archived on Jul 9, 2024 -EXPIRATION_DATE=2025-04-30 - -BUILD_DEPENDS= ${PYTHON_PKGNAMEPREFIX}setuptools>=0:devel/py-setuptools@${PY_FLAVOR} \ - ${PYTHON_PKGNAMEPREFIX}wheel>=0:devel/py-wheel@${PY_FLAVOR} -RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}libpysal>=0:science/py-libpysal@${PY_FLAVOR} \ - ${PYTHON_PKGNAMEPREFIX}numpy>=0,1:math/py-numpy@${PY_FLAVOR} \ - ${PYTHON_PKGNAMEPREFIX}pandas>=0,1:math/py-pandas@${PY_FLAVOR} \ - ${PYTHON_PKGNAMEPREFIX}scipy>=0:science/py-scipy@${PY_FLAVOR} \ - ${PYTHON_PKGNAMEPREFIX}seaborn>=0:math/py-seaborn@${PY_FLAVOR} \ - ${PYTHON_PKGNAMEPREFIX}spreg>=0:math/py-spreg@${PY_FLAVOR} - -USES= python -USE_PYTHON= autoplist concurrent pep517 - -NO_ARCH= yes - -.include <bsd.port.mk> diff --git a/math/py-spvcm/distinfo b/math/py-spvcm/distinfo deleted file mode 100644 index 6c43139a755b..000000000000 --- a/math/py-spvcm/distinfo +++ /dev/null @@ -1,3 +0,0 @@ -TIMESTAMP = 1609598753 -SHA256 (spvcm-0.3.0.tar.gz) = ce331bd5d6bcb64a07c4393093f3978763cfc8764ad0737e1866f3905e6cceae -SIZE (spvcm-0.3.0.tar.gz) = 5724408 diff --git a/math/py-spvcm/pkg-descr b/math/py-spvcm/pkg-descr deleted file mode 100644 index 094ee77cf74d..000000000000 --- a/math/py-spvcm/pkg-descr +++ /dev/null @@ -1,6 +0,0 @@ -Gibbs sampling for spatially-correlated variance-components - -This is a package to estimate spatially-correlated variance components -models/varying intercept models. In addition to a general toolkit to conduct -Gibbs sampling in Python, the package also provides an interface to PyMC3 and -CODA. |