Date: Mon, 12 Oct 2020 23:15:19 +0000 (UTC) From: Yuri Victorovich <yuri@FreeBSD.org> To: ports-committers@freebsd.org, svn-ports-all@freebsd.org, svn-ports-head@freebsd.org Subject: svn commit: r552155 - in head/math: . py-ssm Message-ID: <202010122315.09CNFJJG035637@repo.freebsd.org>
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Author: yuri Date: Mon Oct 12 23:15:19 2020 New Revision: 552155 URL: https://svnweb.freebsd.org/changeset/ports/552155 Log: New port: math/py-ssm: Bayesian learning and inference for state space models Added: head/math/py-ssm/ head/math/py-ssm/Makefile (contents, props changed) head/math/py-ssm/distinfo (contents, props changed) head/math/py-ssm/pkg-descr (contents, props changed) Modified: head/math/Makefile Modified: head/math/Makefile ============================================================================== --- head/math/Makefile Mon Oct 12 22:31:08 2020 (r552154) +++ head/math/Makefile Mon Oct 12 23:15:19 2020 (r552155) @@ -837,6 +837,7 @@ SUBDIR += py-snuggs SUBDIR += py-spectral SUBDIR += py-spot + SUBDIR += py-ssm SUBDIR += py-statsmodels SUBDIR += py-statsmodels010 SUBDIR += py-svgmath Added: head/math/py-ssm/Makefile ============================================================================== --- /dev/null 00:00:00 1970 (empty, because file is newly added) +++ head/math/py-ssm/Makefile Mon Oct 12 23:15:19 2020 (r552155) @@ -0,0 +1,32 @@ +# $FreeBSD$ + +PORTNAME= ssm +DISTVERSION= 0.0.1 +CATEGORIES= math python +MASTER_SITES= CHEESESHOP +PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX} + +MAINTAINER= yuri@FreeBSD.org +COMMENT= Bayesian learning and inference for state space models + +LICENSE= MIT + +PY_DEPENDS= ${PYNUMPY} \ + ${PYTHON_PKGNAMEPREFIX}autograd>0:math/py-autograd@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}future>0:devel/py-future@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}matplotlib>0:math/py-matplotlib@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}numba>0:devel/py-numba@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}scipy>0:science/py-scipy@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}scikit-learn>0:science/py-scikit-learn@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}seaborn>0:math/py-seaborn@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}tqdm>0:misc/py-tqdm@${PY_FLAVOR} +BUILD_DEPENDS= ${PY_DEPENDS} +RUN_DEPENDS= ${PY_DEPENDS} + +USES= python +USE_PYTHON= distutils cython concurrent autoplist + +post-install: + ${STRIP_CMD} ${STAGEDIR}${PYTHONPREFIX_SITELIBDIR}/${PORTNAME}/*.so + +.include <bsd.port.mk> Added: head/math/py-ssm/distinfo ============================================================================== --- /dev/null 00:00:00 1970 (empty, because file is newly added) +++ head/math/py-ssm/distinfo Mon Oct 12 23:15:19 2020 (r552155) @@ -0,0 +1,3 @@ +TIMESTAMP = 1602537377 +SHA256 (ssm-0.0.1.tar.gz) = b3eca53d3049306097de5977bb5c663f0c5f11db14e77ad7515c2902067f0458 +SIZE (ssm-0.0.1.tar.gz) = 309185 Added: head/math/py-ssm/pkg-descr ============================================================================== --- /dev/null 00:00:00 1970 (empty, because file is newly added) +++ head/math/py-ssm/pkg-descr Mon Oct 12 23:15:19 2020 (r552155) @@ -0,0 +1,21 @@ +This package has fast and flexible code for simulating, learning, and performing +inference in a variety of state space models. Currently, it supports: +* Hidden Markov Models (HMM) +* Auto-regressive HMMs (ARHMM) +* Input-output HMMs (IOHMM) +* Hidden Semi-Markov Models (HSMM) +* Linear Dynamical Systems (LDS) +* Switching Linear Dynamical Systems (SLDS) +* Recurrent SLDS (rSLDS) +* Hierarchical extensions of the above +* Partial observations and missing data + +It supports the following observation models: +* Gaussian +* Student's +* Bernoulli +* Poisson +* Categorical +* Von Mises + +WWW: https://github.com/lindermanlab/ssm
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