5 files changed, 125 insertions, 0 deletions

diff --git a/science/Makefile b/science/Makefile
index 029dc3d7ec8d..ebcbfad69d07 100644
--- a/science/Makefile
+++ b/science/Makefile
@@ -106,6 +106,7 @@
     SUBDIR += psychopy
     SUBDIR += py-hcluster
     SUBDIR += py-mdp
+    SUBDIR += py-mlpy
     SUBDIR += py-netCDF4
     SUBDIR += py-openbabel
     SUBDIR += py-paida
diff --git a/science/py-mlpy/Makefile b/science/py-mlpy/Makefile
new file mode 100644
index 000000000000..0769e7e13f53
--- /dev/null
+++ b/science/py-mlpy/Makefile
@@ -0,0 +1,29 @@
+# New ports collection makefile for:	py-mlpy
+# Date created:		18 April, 2009
+# Whom:			Wen Heping <wenheping@gmail.com>
+#
+# $FreeBSD$
+#
+
+PORTNAME=	mlpy
+PORTVERSION=	2.0.0
+CATEGORIES=	science python
+MASTER_SITES=	https://mlpy.fbk.eu/download/src/
+PKGNAMEPREFIX=	${PYTHON_PKGNAMEPREFIX}
+DISTNAME=	MLPY-${PORTVERSION}
+
+MAINTAINER=	wenheping@gmail.com
+COMMENT=	High performance Python package for predictive modeling
+
+BUILD_DEPENDS=	${PYTHON_SITELIBDIR}/numpy:${PORTSDIR}/math/py-numpy
+RUN_DEPENDS=	${BUILD_DEPENDS}
+LIB_DEPENDS=	gsl.13:${PORTSDIR}/math/gsl
+
+CFLAGS+=	-I${LOCALBASE}/include
+LDFLAGS+=	-L${LOCALBASE}/lib
+MAKE_ENV+=	CFLAGS="${CFLAGS}" LDFLAGS="${LDFLAGS}"
+USE_PYTHON=	yes
+USE_PYDISTUTILS=	yes
+PYDISTUTILS_PKGNAME=	MLPY
+
+.include <bsd.port.mk>
diff --git a/science/py-mlpy/distinfo b/science/py-mlpy/distinfo
new file mode 100644
index 000000000000..4b887b59ed2e
--- /dev/null
+++ b/science/py-mlpy/distinfo
@@ -0,0 +1,3 @@
+MD5 (MLPY-2.0.0.tar.gz) = 2f2b33f97849cba7d469926a7724e770
+SHA256 (MLPY-2.0.0.tar.gz) = f58fd590df0c22310cda4e1770a3ea4a195c552c8e33db01c168d2d10bcebf74
+SIZE (MLPY-2.0.0.tar.gz) = 118326
diff --git a/science/py-mlpy/pkg-descr b/science/py-mlpy/pkg-descr
new file mode 100644
index 000000000000..a3ac58b890cc
--- /dev/null
+++ b/science/py-mlpy/pkg-descr
@@ -0,0 +1,11 @@
+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/
diff --git a/science/py-mlpy/pkg-plist b/science/py-mlpy/pkg-plist
new file mode 100644
index 000000000000..67d09b920783
--- /dev/null
+++ b/science/py-mlpy/pkg-plist
@@ -0,0 +1,81 @@
+bin/irelief-sigma
+bin/srda-landscape
+bin/svm-landscape
+bin/fda-landscape
+bin/knn-landscape
+bin/pda-landscape
+bin/dlda-landscape
+bin/borda
+bin/canberra
+bin/canberraq
+%%PYTHON_SITELIBDIR%%/mlpy/__init__.py
+%%PYTHON_SITELIBDIR%%/mlpy/__init__.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/__init__.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_bmetrics.py
+%%PYTHON_SITELIBDIR%%/mlpy/_bmetrics.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_bmetrics.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_borda.py
+%%PYTHON_SITELIBDIR%%/mlpy/_borda.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_borda.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_canberra.py
+%%PYTHON_SITELIBDIR%%/mlpy/_canberra.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_canberra.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_ci.py
+%%PYTHON_SITELIBDIR%%/mlpy/_ci.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_ci.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_cwt.py
+%%PYTHON_SITELIBDIR%%/mlpy/_cwt.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_cwt.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_data.py
+%%PYTHON_SITELIBDIR%%/mlpy/_data.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_data.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_dlda.py
+%%PYTHON_SITELIBDIR%%/mlpy/_dlda.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_dlda.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_dwt.so
+%%PYTHON_SITELIBDIR%%/mlpy/_dwtfs.py
+%%PYTHON_SITELIBDIR%%/mlpy/_dwtfs.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_dwtfs.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_fda.py
+%%PYTHON_SITELIBDIR%%/mlpy/_fda.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_fda.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_hcluster.py
+%%PYTHON_SITELIBDIR%%/mlpy/_hcluster.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_hcluster.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_irelief.py
+%%PYTHON_SITELIBDIR%%/mlpy/_irelief.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_irelief.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_knn.py
+%%PYTHON_SITELIBDIR%%/mlpy/_knn.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_knn.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_pda.py
+%%PYTHON_SITELIBDIR%%/mlpy/_pda.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_pda.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_ranking.py
+%%PYTHON_SITELIBDIR%%/mlpy/_ranking.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_ranking.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_resampling.py
+%%PYTHON_SITELIBDIR%%/mlpy/_resampling.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_resampling.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_srda.py
+%%PYTHON_SITELIBDIR%%/mlpy/_srda.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_srda.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_svm.py
+%%PYTHON_SITELIBDIR%%/mlpy/_svm.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_svm.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/_wavelet.py
+%%PYTHON_SITELIBDIR%%/mlpy/_wavelet.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/_wavelet.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/canberracore.so
+%%PYTHON_SITELIBDIR%%/mlpy/cwb.so
+%%PYTHON_SITELIBDIR%%/mlpy/gslpy.so
+%%PYTHON_SITELIBDIR%%/mlpy/hccore.so
+%%PYTHON_SITELIBDIR%%/mlpy/nncore.so
+%%PYTHON_SITELIBDIR%%/mlpy/progressbar.py
+%%PYTHON_SITELIBDIR%%/mlpy/progressbar.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/progressbar.pyo
+%%PYTHON_SITELIBDIR%%/mlpy/svmcore.so
+%%PYTHON_SITELIBDIR%%/mlpy/version.py
+%%PYTHON_SITELIBDIR%%/mlpy/version.pyc
+%%PYTHON_SITELIBDIR%%/mlpy/version.pyo
+@dirrm %%PYTHON_SITELIBDIR%%/mlpy