Machine Learning PY (mlpy) is a high-performance Python package for
predictive modeling. It makes extensive use of numpy (http://scipy.org)
to provide fast N-dimensional array manipulation and easy integration of
C code. mlpy provides high level procedures that support, with few lines
of code, the design of rich Data Analysis Protocols (DAPs) for
preprocessing, clustering, predictive classification and feature
selection. Methods are available for feature weighting and ranking, data
resampling, error evaluation and experiment landscaping.The package
includes tools to measure stability in sets of ranked feature lists.
WWW: http://mlpy.sourceforge.net/
Remove deprecated ports:
2020-08-15 archivers/py-backports.lzma: Uses deprecated version of python
2020-08-15 archivers/py-bup: Uses deprecated version of python
2020-08-15 archivers/py-librtfcomp: Uses deprecated version of python
2020-08-15 audio/blop-lv2: Uses deprecated version of python
2020-08-15 audio/bs2b-lv2: Uses deprecated version of python
2020-08-15 audio/py-gmusicproxy: Uses deprecated version of python
2020-08-15 audio/py-karaoke: Uses deprecated version of python
2020-08-15 audio/py-openal: Uses deprecated version of python
2020-08-15 audio/py-py-jack: Uses deprecated version of python
2020-08-15 audio/py-xmms2: Uses deprecated version of python
2020-08-15 audio/triceratops-lv2: Uses deprecated version of python
2020-08-15 biology/py-biom-format: Uses deprecated version of python
2020-08-15 comms/py-bulksms: Uses deprecated version of python
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math/gsl: update to 2.6
- math/p5-Math-GSL does not seem to have any upstream activity to make it work
with this version -> mark it broken
- this also breaks the two consumers of this port
- biology/gemma: has a conflict with cblas, and is makred broken.
PR: 241363
Exp-run by: antoine
Bump PORTREVISION for ports depending on the canonical version of GCC
as defined in Mk/bsd.default-versions.mk which has moved from GCC 8.3
to GCC 9.1 under most circumstances now after revision 507371.
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, everything INDEX-11 shows with a dependency on lang/gcc9 now.
PR: 238330
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
Convert Python ports to FLAVORS.
Ports using USE_PYTHON=distutils are now flavored. They will
automatically get flavors (py27, py34, py35, py36) depending on what
versions they support.
There is also a USE_PYTHON=flavors for ports that do not use distutils
but need FLAVORS to be set. A USE_PYTHON=noflavors can be set if
using distutils but flavors are not wanted.
A new USE_PYTHON=optsuffix that will add PYTHON_PKGNAMESUFFIX has been
added to cope with Python ports that did not have the Python
PKGNAMEPREFIX but are flavored.
USES=python now also exports a PY_FLAVOR variable that contains the
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Update math/gsl to 2.3
This release introduces some new features and fixes several bugs:
http://savannah.gnu.org/forum/forum.php?forum_id=8751
* update to 2.3 and take maintainership
* update math/py-gsl to 2.2.0 for gsl2 support
* update math/rubygem-rb-gsl to 2.1.0.2 for gsl2 support
PR: 218952
Exp-run by: antoine
Reviewed by: mat, rakuco
Approved by: rakuco (mentor)
Differential Revision: https://reviews.freebsd.org/D10522
Update the default version of GCC in the Ports Collection from GCC 4.7.4
to GCC 4.8.3.
Part II, Bump PORTREVISIONs.
PR: 192025
Tested by: antoine (-exp runs)
Approved by: portmgr (implicit)
Update the default version of GCC used in the Ports Collection from
GCC 4.6.4 to GCC 4.7.3. This entails updating the lang/gcc port as
well as changing the default in Mk/bsd.default-versions.mk.
Part II, Bump PORTREVISIONs.
PR: 182136
Supported by: Christoph Moench-Tegeder <cmt@burggraben.net> (fixing many ports)
Tested by: bdrewery (two -exp runs)
Update to libmpc version 1.0.1 which brings the following fixes:
- Switched to automake 1.11.6, see CVE-2012-3386.
- #14669: Fixed extraction of CC from gmp.h.
- Fixed case of intermediate zero real or imaginary part in mpc_fma,
found by hydra with GMP_CHECK_RANDOMIZE=1346362345.
This is on top of the following changes from version 1.0
- Licence change towards LGPLv3+ for the code and GFDLv1.3+ (with no
invariant sections) for the documentation.
- 100% of all lines are covered by tests
- Renamed functions
. mpc_mul_2exp to mpc_mul_2ui
. mpc_div_2exp to mpc_div_2ui
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At the moment 1385 ports use BUILD_DEPENDS= ${RUN_DEPENDS} and 450
ports use BUILD_DEPENDS:= ${RUN_DEPENDS}. This patch fixes ports that are
currently broken. This is a temporary measure until we organically stop using
:= or someone(s) spend a lot of time changing all the ports over.
Explicit duplication > := > = and this just moves ports one step to the left
Approved by: portmgr
- Add LDFLAGS to CONFIGURE_ENV and MAKE_ENV (as it was done with LDFLAGS)
- Fix all ports that add {CPP,LD}FLAGS to *_ENV to modify flags instead
PR: 157936
Submitted by: myself
Exp-runs by: pav
Approved by: pav
Machine Learning PY (mlpy) is a high-performance Python package for
predictive modeling. It makes extensive use of numpy (http://scipy.org)
to provide fast N-dimensional array manipulation and easy integration of
C code. mlpy provides high level procedures that support, with few lines
of code, the design of rich Data Analysis Protocols (DAPs) for
preprocessing, clustering, predictive classification and feature
selection. Methods are available for feature weighting and ranking, data
resampling, error evaluation and experiment landscaping.The package
includes tools to measure stability in sets of ranked feature lists.
WWW: http://mlpy.fbk.eu/
PR: ports/133932
Submitted by: Wen Heping <wenheping at gmail.com>
