1
0
mirror of https://git.FreeBSD.org/ports.git synced 2024-11-19 00:13:33 +00:00

Add py-cma 2.6.0

pycma is a Python implementation of CMA-ES and a few related numerical
optimization tools.

The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a stochastic
derivative-free numerical optimization algorithm for difficult (non-convex,
ill-conditioned, multi-modal, rugged, noisy) optimization problems in continuous
search spaces.

WWW: https://github.com/CMA-ES/pycma
This commit is contained in:
Sunpoet Po-Chuan Hsieh 2019-01-17 19:21:19 +00:00
parent b93cbf2342
commit bde795881f
Notes: svn2git 2021-03-31 03:12:20 +00:00
svn path=/head/; revision=490585
4 changed files with 36 additions and 0 deletions

View File

@ -692,6 +692,7 @@
SUBDIR += py-bottleneck
SUBDIR += py-cdecimal
SUBDIR += py-chaospy
SUBDIR += py-cma
SUBDIR += py-colormath
SUBDIR += py-cryptominisat
SUBDIR += py-cvxopt

23
math/py-cma/Makefile Normal file
View File

@ -0,0 +1,23 @@
# Created by: Po-Chuan Hsieh <sunpoet@FreeBSD.org>
# $FreeBSD$
PORTNAME= cma
PORTVERSION= 2.6.0
CATEGORIES= math python
MASTER_SITES= CHEESESHOP
PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
MAINTAINER= sunpoet@FreeBSD.org
COMMENT= CMA-ES for non-linear numerical optimization in Python
LICENSE= BSD3CLAUSE
LICENSE_FILE= ${WRKSRC}/LICENSE
RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}numpy>=0:math/py-numpy@${PY_FLAVOR}
USES= python
USE_PYTHON= autoplist concurrent distutils
NO_ARCH= yes
.include <bsd.port.mk>

3
math/py-cma/distinfo Normal file
View File

@ -0,0 +1,3 @@
TIMESTAMP = 1547723709
SHA256 (cma-2.6.0.tar.gz) = ef9e21fd821485518341fe1b96be4d127f8b78e60aeb6a286d602dc98f25eab6
SIZE (cma-2.6.0.tar.gz) = 213116

9
math/py-cma/pkg-descr Normal file
View File

@ -0,0 +1,9 @@
pycma is a Python implementation of CMA-ES and a few related numerical
optimization tools.
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a stochastic
derivative-free numerical optimization algorithm for difficult (non-convex,
ill-conditioned, multi-modal, rugged, noisy) optimization problems in continuous
search spaces.
WWW: https://github.com/CMA-ES/pycma