kpriv/freebsd-ports
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity
freebsd-ports/math/py-pymc/Makefile

43 lines
1.4 KiB
Makefile
Raw Normal View History

Add NO_STAGE all over the place in preparation for the staging support (cat: math)
2013-09-20 22:55:04 +02:00
# Created by: Wen Heping <wenheping@gmail.com>
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: http://pypi.python.org/pypi/pymc/ PR: ports/129567 Submitted by: Wen Heping <wenheping at gmail.com>
2008-12-14 11:37:39 +01:00
# $FreeBSD$
PORTNAME= pymc
- Update to 2.3.6 [1] - Update my email PR: 205561 [1] Submitted by: yuri@rawbw.com [1]
2015-12-25 07:05:17 +01:00
PORTVERSION= 2.3.6
- Update to 2.0 PR: ports/130225 Submitted by: Wen Heping <wenheping AT gmail.com> (maintainer)
2009-03-05 19:56:03 +01:00
PORTEPOCH= 1
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: http://pypi.python.org/pypi/pymc/ PR: ports/129567 Submitted by: Wen Heping <wenheping at gmail.com>
2008-12-14 11:37:39 +01:00
CATEGORIES= math python
MASTER_SITES= CHEESESHOP
PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
- Update to 2.3.6 [1] - Update my email PR: 205561 [1] Submitted by: yuri@rawbw.com [1]
2015-12-25 07:05:17 +01:00
MAINTAINER= wen@FreeBSD.org
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: http://pypi.python.org/pypi/pymc/ PR: ports/129567 Submitted by: Wen Heping <wenheping at gmail.com>
2008-12-14 11:37:39 +01:00
COMMENT= Markov Chain Monte Carlo Sampling Toolkit
- 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
2013-12-06 16:42:33 +01:00
LICENSE= AFL
LICENSE_NAME= Academic Free License
LICENSE_FILE= ${WRKSRC}/LICENSE
Canonicalize a few LICENSE_PERMS With hat: portmgr
2014-08-22 09:20:30 +02:00
LICENSE_PERMS= dist-mirror dist-sell pkg-mirror pkg-sell auto-accept
- 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
2013-12-06 16:42:33 +01:00
BUILD_DEPENDS= ${PYNUMPY} \
Remove ${PORTSDIR}/ from dependencies, categories m, n, o, and p. With hat: portmgr Sponsored by: Absolight
2016-04-01 16:16:16 +02:00
${PYTHON_PKGNAMEPREFIX}matplotlib>0:math/py-matplotlib \
${PYTHON_PKGNAMEPREFIX}scipy>0:science/py-scipy
LIB_DEPENDS= liblapack.so:math/lapack \
libblas.so:math/blas
- 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
2013-12-06 16:42:33 +01:00
RUN_DEPENDS= ${PYNUMPY} \
Remove ${PORTSDIR}/ from dependencies, categories m, n, o, and p. With hat: portmgr Sponsored by: Absolight
2016-04-01 16:16:16 +02:00
${PYTHON_PKGNAMEPREFIX}matplotlib>0:math/py-matplotlib \
${PYTHON_PKGNAMEPREFIX}scipy>0:science/py-scipy
- 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
2013-12-06 16:42:33 +01:00
- Remove everything related to DOCS as not documentation is actually installed - Sort USE_PYTHON PR: 200620 Submitted by: amdmi3 Approved by: maintainer timeout (wenheping@gmail.com, 3 months)
2015-09-03 12:28:15 +02:00
USES= python
USE_PYTHON= autoplist distutils
- 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
2013-12-06 16:42:33 +01:00
Fix compilation after recent numpy patch. Patch by thierry@FreeBSD.org, pointed out by antoine.
2014-10-23 17:23:27 +02:00
LDFLAGS+= -shared
- 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
2013-12-06 16:42:33 +01:00
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
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: http://pypi.python.org/pypi/pymc/ PR: ports/129567 Submitted by: Wen Heping <wenheping at gmail.com>
2008-12-14 11:37:39 +01:00
.include <bsd.port.mk>
Reference in a new issue Copy permalink