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| author | Marcelo Araujo <araujo@FreeBSD.org> | 2016-04-18 05:31:57 +0000 |
|---|---|---|
| committer | Marcelo Araujo <araujo@FreeBSD.org> | 2016-04-18 05:31:57 +0000 |
| commit | f050cb454909dd14e40907fe537710e06e086f4a (patch) | |
| tree | 0110531c779f464627caa5c0273abe332a6ce435 /math | |
| parent | 61d69ef66b69bd41c82f3a2acb027017cecb909f (diff) | |
| download | ports-f050cb454909dd14e40907fe537710e06e086f4a.tar.gz ports-f050cb454909dd14e40907fe537710e06e086f4a.zip | |
Notes
Diffstat (limited to 'math')
| -rw-r--r-- | math/py-luminol/Makefile | 23 | ||||
| -rw-r--r-- | math/py-luminol/distinfo | 2 | ||||
| -rw-r--r-- | math/py-luminol/pkg-descr | 5 |
3 files changed, 30 insertions, 0 deletions
diff --git a/math/py-luminol/Makefile b/math/py-luminol/Makefile new file mode 100644 index 000000000000..ff4ea9676ec9 --- /dev/null +++ b/math/py-luminol/Makefile @@ -0,0 +1,23 @@ +# $FreeBSD$ + +PORTNAME= luminol +PORTVERSION= 0.3.1 +DISTVERSIONPREFIX= v +CATEGORIES= math python +PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX} + +MAINTAINER= araujo@FreeBSD.org +COMMENT= Light weight python library for time series data analysis + +LICENSE= APACHE20 +LICENSE_FILE= ${WRKSRC}/LICENSE + +RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}scipy>0:science/py-scipy \ + ${PYTHON_PKGNAMEPREFIX}numpy>=1.6.2:math/py-numpy + +USES= python +USE_PYTHON= autoplist distutils +USE_GITHUB= yes +GH_ACCOUNT= linkedin + +.include <bsd.port.mk> diff --git a/math/py-luminol/distinfo b/math/py-luminol/distinfo new file mode 100644 index 000000000000..18a91583b2df --- /dev/null +++ b/math/py-luminol/distinfo @@ -0,0 +1,2 @@ +SHA256 (linkedin-luminol-v0.3.1_GH0.tar.gz) = 31c2c5697dffa0e4b9c3468189b2a4f25e5dd2c59ee351f51fdbf5a770fe8c7b +SIZE (linkedin-luminol-v0.3.1_GH0.tar.gz) = 141854 diff --git a/math/py-luminol/pkg-descr b/math/py-luminol/pkg-descr new file mode 100644 index 000000000000..fa66fe1317a0 --- /dev/null +++ b/math/py-luminol/pkg-descr @@ -0,0 +1,5 @@ +Luminol is a light weight python library for time series data analysis. +The two major functionalities it supports are anomaly detection and +correlation. It can be used to investigate possible causes of anomaly. + +WWW: https://github.com/linkedin/luminol |