kpriv/freebsd-ports
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity
freebsd-ports/science/py-scikit-learn/Makefile

33 lines
796 B
Makefile
Raw Normal View History

Add NO_STAGE all over the place in preparation for the staging support (cat: science)
2013-09-21 00:48:30 +02:00
# Created by: Dmitry Sivachenko <demon@FreeBSD.org>
scikit-learn is a Python module integrating classic machine learning algorithms in the tightly-knit scientific Python world (numpy, scipy, matplotlib). It aims to provide simple and efficient solutions to learning problems, accessible to everybody and reusable in various contexts: machine-learning as a versatile tool for science and engineering. WWW: http://scikit-learn.org/ Feature safe: yes
2012-10-19 14:24:00 +02:00
# $FreeBSD$
PORTNAME= scikit-learn
science/py-scikit-learn: Update 0.19.2 -> 0.20.1 Port changes: * Use DISTVERSION * Add LIB_DEPENDS * Add workaround for the wrong element in plist PR: 233555 Approved by: demon (maintainer)
2018-11-27 18:21:37 +01:00
DISTVERSION= 0.20.1
Bump PORTREVISION for ports depending on the canonical version of GCC defined via Mk/bsd.default-versions.mk which has moved from GCC 7.4 t GCC 8.2 under most circumstances. This includes ports - with USE_GCC=yes or USE_GCC=any, - with USES=fortran, - using Mk/bsd.octave.mk which in turn features USES=fortran, and - with USES=compiler specifying openmp, nestedfct, c11, c++0x, c++11-lang, c++11-lib, c++14-lang, c++17-lang, or gcc-c++11-lib plus, as a double check, everything INDEX-11 showed depending on lang/gcc7. PR: 231590
2018-12-12 02:35:33 +01:00
PORTREVISION= 1
scikit-learn is a Python module integrating classic machine learning algorithms in the tightly-knit scientific Python world (numpy, scipy, matplotlib). It aims to provide simple and efficient solutions to learning problems, accessible to everybody and reusable in various contexts: machine-learning as a versatile tool for science and engineering. WWW: http://scikit-learn.org/ Feature safe: yes
2012-10-19 14:24:00 +02:00
CATEGORIES= science python
MASTER_SITES cleanup. - Replace ${MASTER_SITE_FOO} with FOO. - Merge MASTER_SITE_SUBDIR into MASTER_SITES when possible. (This means 99.9% of the time.) - Remove occurrences of MASTER_SITE_LOCAL when no subdirectory was present and no hint of what it should be was present. - Fix some logic. - And generally, make things more simple and easy to understand. While there, add magic values to the FESTIVAL, GENTOO, GIMP, GNUPG, QT and SAMBA macros. Also, replace some EXTRACT_SUFX occurences with USES=tar:*. Checked by: make fetch-urlall-list With hat: portmgr Sponsored by: Absolight
2015-05-14 12:15:04 +02:00
MASTER_SITES= CHEESESHOP
scikit-learn is a Python module integrating classic machine learning algorithms in the tightly-knit scientific Python world (numpy, scipy, matplotlib). It aims to provide simple and efficient solutions to learning problems, accessible to everybody and reusable in various contexts: machine-learning as a versatile tool for science and engineering. WWW: http://scikit-learn.org/ Feature safe: yes
2012-10-19 14:24:00 +02:00
PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
MAINTAINER= demon@FreeBSD.org
COMMENT= Machine learning algorithms for python
- Add LICENSE Approved by: portmgr blanket
2018-10-30 10:00:15 +01:00
LICENSE= BSD3CLAUSE
LICENSE_FILE= ${WRKSRC}/COPYING
Update to version 0.16.0; Inherit blas dependency from py-numpy.
2015-04-04 16:08:45 +02:00
BUILD_DEPENDS= ${PYNUMPY} \
Use PY_FLAVOR for dependencies. FLAVOR is the current port's flavor, it should not be used outside of this scope. Sponsored by: Absolight
2018-06-20 19:05:41 +02:00
${PYTHON_SITELIBDIR}/scipy/version.py:science/py-scipy@${PY_FLAVOR}
science/py-scikit-learn: Update 0.19.2 -> 0.20.1 Port changes: * Use DISTVERSION * Add LIB_DEPENDS * Add workaround for the wrong element in plist PR: 233555 Approved by: demon (maintainer)
2018-11-27 18:21:37 +01:00
LIB_DEPENDS= libcblas.so:math/cblas
Pet portlint.
2015-04-04 16:19:43 +02:00
RUN_DEPENDS:= ${BUILD_DEPENDS}
scikit-learn is a Python module integrating classic machine learning algorithms in the tightly-knit scientific Python world (numpy, scipy, matplotlib). It aims to provide simple and efficient solutions to learning problems, accessible to everybody and reusable in various contexts: machine-learning as a versatile tool for science and engineering. WWW: http://scikit-learn.org/ Feature safe: yes
2012-10-19 14:24:00 +02:00
- Convert ports of science/ and security to new USES=python Approved by: portmgr (implicit)
2014-10-24 18:50:42 +02:00
USES= fortran python
Explicitly link with libblas to avoid errors like import sklearn.decomposition.pca ImportError: /usr/local/lib/libcblas.so.2: Undefined symbol "cgemv_" due to it trying to import pairwise_fast.so PR: 194683 Update to version 0.15.2.
2014-10-30 12:52:48 +01:00
USE_PYTHON= distutils autoplist
Allow to choose between cblas and atlas ports. Submitted by: glebius
2014-02-18 09:30:53 +01:00
Update to version 0.16.0; Inherit blas dependency from py-numpy.
2015-04-04 16:08:45 +02:00
LDFLAGS+= -shared
Pet portlint.
2015-04-04 16:19:43 +02:00
science/py-scikit-learn: Update 0.19.2 -> 0.20.1 Port changes: * Use DISTVERSION * Add LIB_DEPENDS * Add workaround for the wrong element in plist PR: 233555 Approved by: demon (maintainer)
2018-11-27 18:21:37 +01:00
POST_PLIST= fix-plist
fix-plist: # https://github.com/scikit-learn/scikit-learn/issues/12681
@${REINPLACE_CMD} -e "s|lib/python.*/sklearn/datasets/tests/data/openml$$||" ${TMPPLIST}
scikit-learn is a Python module integrating classic machine learning algorithms in the tightly-knit scientific Python world (numpy, scipy, matplotlib). It aims to provide simple and efficient solutions to learning problems, accessible to everybody and reusable in various contexts: machine-learning as a versatile tool for science and engineering. WWW: http://scikit-learn.org/ Feature safe: yes
2012-10-19 14:24:00 +02:00
.include <bsd.port.mk>
Reference in a new issue Copy permalink