[89215] trunk/dports/math
hum at macports.org
hum at macports.org
Sat Jan 21 03:36:58 PST 2012
Revision: 89215
http://trac.macports.org/changeset/89215
Author: hum at macports.org
Date: 2012-01-21 03:36:57 -0800 (Sat, 21 Jan 2012)
Log Message:
-----------
New port: mallet @2.0.7 - MAchine Learning for LanguagE Toolkit.
Added Paths:
-----------
trunk/dports/math/mallet/
trunk/dports/math/mallet/Portfile
trunk/dports/math/mallet/files/
trunk/dports/math/mallet/files/patch-mallet.diff
Added: trunk/dports/math/mallet/Portfile
===================================================================
--- trunk/dports/math/mallet/Portfile (rev 0)
+++ trunk/dports/math/mallet/Portfile 2012-01-21 11:36:57 UTC (rev 89215)
@@ -0,0 +1,47 @@
+# -*- coding: utf-8; mode: tcl; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- vim:fenc=utf-8:ft=tcl:et:sw=4:ts=4:sts=4
+# $Id$
+
+PortSystem 1.0
+
+name mallet
+version 2.0.7
+categories math java
+maintainers hum openmaintainer
+
+description MAchine Learning for LanguagE Toolkit (MALLET)
+long_description MALLET is a Java-based package for statistical natural \
+ language processing, document classification, clustering, \
+ topic modeling, information extraction, and other machine \
+ learning applications to text.
+
+homepage http://mallet.cs.umass.edu/
+platforms darwin
+supported_archs noarch
+license CPL-1.0
+
+master_sites http://mallet.cs.umass.edu/dist/
+checksums rmd160 083f76b447521dbaa1d3b5747278a41e9b9ba741 \
+ sha256 bf34241b0589be2d28d57a4b369b4d722f273591cb28bf428d0167f58f91f161
+
+patchfiles patch-mallet.diff
+
+use_configure no
+
+build {}
+
+destroot {
+ set malletdir ${prefix}/share/java/${distname}
+ set mallet_dest ${destroot}${malletdir}
+ xinstall -m 755 ${worksrcpath}/bin/mallet ${destroot}${prefix}/bin
+ reinplace "s|@malletdir@|${malletdir}|" ${destroot}${prefix}/bin/mallet
+ xinstall -m 755 -d ${mallet_dest}
+ xinstall -m 644 ${worksrcpath}/LICENSE ${mallet_dest}
+ foreach d {dist sample-data} {
+ copy ${worksrcpath}/${d} ${mallet_dest}
+ system "chmod -R a+rx ${mallet_dest}/${d}"
+ }
+}
+
+livecheck.type regex
+livecheck.url http://mallet.cs.umass.edu/download.php
+livecheck.regex ${name}-(\[\\d\\.\]+)\\.tar
Property changes on: trunk/dports/math/mallet/Portfile
___________________________________________________________________
Added: svn:keywords
+ Id
Added: svn:eol-style
+ native
Added: trunk/dports/math/mallet/files/patch-mallet.diff
===================================================================
--- trunk/dports/math/mallet/files/patch-mallet.diff (rev 0)
+++ trunk/dports/math/mallet/files/patch-mallet.diff 2012-01-21 11:36:57 UTC (rev 89215)
@@ -0,0 +1,39 @@
+--- bin/mallet.orig 2012-01-20 22:48:27.000000000 +0900
++++ bin/mallet 2012-01-21 13:35:34.000000000 +0900
+@@ -1,10 +1,9 @@
+ #!/bin/bash
+
+
+-malletdir=`dirname $0`
+-malletdir=`dirname $malletdir`
++malletdir=@malletdir@
+
+-cp=$malletdir/class:$malletdir/lib/mallet-deps.jar:$CLASSPATH
++cp=$malletdir/dist/mallet.jar:$malletdir/dist/mallet-deps.jar:$CLASSPATH
+ #echo $cp
+
+ MEMORY=1g
+@@ -26,12 +25,15 @@
+ classify-dir classify data from a single file with a saved classifier
+ classify-file classify the contents of a directory with a saved classifier
+ classify-svmlight classify data from a single file in SVMLight format
++ tag train, test, or run a generic CRF-based tagger
+ train-topics train a topic model from Mallet data files
+ infer-topics use a trained topic model to infer topics for new documents
+ evaluate-topics estimate the probability of new documents under a trained model
+ hlda train a topic model using Hierarchical LDA
+ prune remove features based on frequency or information gain
+ split divide data into testing, training, and validation portions
++ buld-load import large amounts of text into Mallet format
++ run run the main method of the specified class
+
+ Include --help with any option for more information
+ EOF
+@@ -47,6 +49,7 @@
+ classify-dir) CLASS=cc.mallet.classify.tui.Text2Classify;;
+ classify-file) CLASS=cc.mallet.classify.tui.Csv2Classify;;
+ classify-svmlight) CLASS=cc.mallet.classify.tui.SvmLight2Classify;;
++ tag) CLASS=cc.mallet.fst.SimpleTagger;;
+ train-topics) CLASS=cc.mallet.topics.tui.Vectors2Topics;;
+ infer-topics) CLASS=cc.mallet.topics.tui.InferTopics;;
+ evaluate-topics) CLASS=cc.mallet.topics.tui.EvaluateTopics;;
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