Date: Fri, 6 Dec 2013 15:42:33 +0000 (UTC) From: Mathieu Arnold <mat@FreeBSD.org> To: ports-committers@freebsd.org, svn-ports-all@freebsd.org, svn-ports-head@freebsd.org Subject: svn commit: r335765 - head/math/py-pymc Message-ID: <201312061542.rB6FgXAw017932@svn.freebsd.org>
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Author: mat Date: Fri Dec 6 15:42:33 2013 New Revision: 335765 URL: http://svnweb.freebsd.org/changeset/ports/335765 Log: - Update to 2.3,1 - Add license - Add matplotlib dependency as per docs/INSTALL.rst - Add DOCS option - Add stage support maintainer timeout. PR: ports/183951 Submitted by: Johannes Jost Meixner Deleted: head/math/py-pymc/pkg-plist Modified: head/math/py-pymc/Makefile head/math/py-pymc/distinfo head/math/py-pymc/pkg-descr Modified: head/math/py-pymc/Makefile ============================================================================== --- head/math/py-pymc/Makefile Fri Dec 6 15:35:13 2013 (r335764) +++ head/math/py-pymc/Makefile Fri Dec 6 15:42:33 2013 (r335765) @@ -2,8 +2,7 @@ # $FreeBSD$ PORTNAME= pymc -PORTVERSION= 2.0 -PORTREVISION= 1 +PORTVERSION= 2.3 PORTEPOCH= 1 CATEGORIES= math python MASTER_SITES= CHEESESHOP @@ -12,11 +11,37 @@ PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX} MAINTAINER= wenheping@gmail.com COMMENT= Markov Chain Monte Carlo Sampling Toolkit -BUILD_DEPENDS= ${PYNUMPY} -RUN_DEPENDS:= ${BUILD_DEPENDS} +LICENSE= AFL +LICENSE_NAME= Academic Free License +LICENSE_FILE= ${WRKSRC}/LICENSE +LICENSE_PERMS= auto-accept dist-mirror dist-sell pkg-mirror pkg-sell + +BUILD_DEPENDS= ${PYNUMPY} \ + ${PYTHON_PKGNAMEPREFIX}matplotlib>0:${PORTSDIR}/math/py-matplotlib \ + ${PYTHON_PKGNAMEPREFIX}scipy>0:${PORTSDIR}/science/py-scipy +LIB_DEPENDS= liblapack.so:${PORTSDIR}/math/lapack \ + libblas.so:${PORTSDIR}/math/blas +RUN_DEPENDS= ${PYNUMPY} \ + ${PYTHON_PKGNAMEPREFIX}matplotlib>0:${PORTSDIR}/math/py-matplotlib \ + ${PYTHON_PKGNAMEPREFIX}scipy>0:${PORTSDIR}/science/py-scipy + +OPTIONS_DEFINE= DOCS +DOCSDIR= ${PREFIX}/share/doc/py-${PORTNAME} USE_PYTHON= yes USE_PYDISTUTILS= yes +PYDISTUTILS_AUTOPLIST= yes +PORTDOCS= * + +post-install: + ${STRIP_CMD} ${STAGEDIR}${PYTHON_SITELIBDIR}/${PORTNAME}/flib.so + ${STRIP_CMD} ${STAGEDIR}${PYTHON_SITELIBDIR}/${PORTNAME}/gp/cov_funs/distances.so + ${STRIP_CMD} ${STAGEDIR}${PYTHON_SITELIBDIR}/${PORTNAME}/gp/cov_funs/isotropic_cov_funs.so + ${STRIP_CMD} ${STAGEDIR}${PYTHON_SITELIBDIR}/${PORTNAME}/gp/incomplete_chol.so + ${STRIP_CMD} ${STAGEDIR}${PYTHON_SITELIBDIR}/${PORTNAME}/gp/linalg_utils.so + ${STRIP_CMD} ${STAGEDIR}${PYTHON_SITELIBDIR}/${PORTNAME}/Container_values.so + ${STRIP_CMD} ${STAGEDIR}${PYTHON_SITELIBDIR}/${PORTNAME}/LazyFunction.so + ${MKDIR} ${STAGEDIR}${DOCSDIR} + ${INSTALL_DATA} ${WRKSRC}/docs/*.rst ${STAGEDIR}${DOCSDIR} -NO_STAGE= yes .include <bsd.port.mk> Modified: head/math/py-pymc/distinfo ============================================================================== --- head/math/py-pymc/distinfo Fri Dec 6 15:35:13 2013 (r335764) +++ head/math/py-pymc/distinfo Fri Dec 6 15:42:33 2013 (r335765) @@ -1,2 +1,2 @@ -SHA256 (pymc-2.0.tar.gz) = 15bbf1e0df9e080d367d639462c4b2b9290826ca069a76ac2bc79d795fe6e653 -SIZE (pymc-2.0.tar.gz) = 1200416 +SHA256 (pymc-2.3.tar.gz) = db029c59d6a04f0c97d88993151c4ee58c76b9ad5c71ead7ee250088ba4cce0d +SIZE (pymc-2.3.tar.gz) = 13080085 Modified: head/math/py-pymc/pkg-descr ============================================================================== --- head/math/py-pymc/pkg-descr Fri Dec 6 15:35:13 2013 (r335764) +++ head/math/py-pymc/pkg-descr Fri Dec 6 15:42:33 2013 (r335765) @@ -1,11 +1,9 @@ -Bayesian estimation, particularly using Markov chain Monte -Carlo (MCMC), is an increasingly relevant approach to -statistical estimation. However, few statistical software -packages implement MCMC samplers, and they are non-trivial - to code by hand. pymc is a python package that implements -the Metropolis-Hastings algorithm as a python class, and is -extremely flexible and applicable to a large suite of problems. -pymc includes methods for summarizing output, plotting, -goodness-of-fit and convergence diagnostics. +Bayesian estimation, particularly using Markov chain Monte Carlo (MCMC), is an +increasingly relevant approach to statistical estimation. However, few +statistical software packages implement MCMC samplers, and they are non-trivial +to code by hand. pymc is a python package that implements the +Metropolis-Hastings algorithm as a python class, and is extremely flexible and +applicable to a large suite of problems. pymc includes methods for summarizing +output, plotting, goodness-of-fit and convergence diagnostics. -WWW: https://pypi.python.org/pypi/pymc/ +WWW: http://pypi.python.org/pypi/pymc/
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