Tinyarrays are similar to NumPy arrays, but optimized for small

sizes. Common operations on very small arrays are to 3-7 times
faster than with NumPy (with NumPy 1.6 it used to be up to 35
times), and 3 times less memory is used to store them. Tinyarrays
are useful if you need many small arrays of numbers, and cannot
combine them into a few large ones. (The resulting code is still
much slower than C, but it may now be fast enough.)

WWW: https://gitlab.kwant-project.org/kwant/tinyarray
This commit is contained in:
Wen Heping 2016-02-26 01:59:43 +00:00
parent 09c17e7c67
commit 779669bb6d
Notes: svn2git 2021-03-31 03:12:20 +00:00
svn path=/head/; revision=409572
4 changed files with 32 additions and 0 deletions

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@ -4395,6 +4395,7 @@
SUBDIR += py-tgMochiKit
SUBDIR += py-thrift
SUBDIR += py-timelib
SUBDIR += py-tinyarray
SUBDIR += py-tipper
SUBDIR += py-total-ordering
SUBDIR += py-tox

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@ -0,0 +1,20 @@
# Created by: Wen Heping<wenheping@gmail.com>
# $FreeBSD$
PORTNAME= tinyarray
PORTVERSION= 1.1.0
CATEGORIES= devel python
MASTER_SITES= CHEESESHOP
PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
MAINTAINER= wen@FreeBSD.org
COMMENT= Arrays of numbers for Python, optimized for small sizes
LICENSE= BSD2CLAUSE
BUILD_DEPENDS= ${PYTHON_PKGNAMEPREFIX}nose>=0:${PORTSDIR}/devel/py-nose
USES= python
USE_PYTHON= autoplist distutils
.include <bsd.port.mk>

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@ -0,0 +1,2 @@
SHA256 (tinyarray-1.1.0.tar.gz) = d8c9c5f69c5be8ac00713eea3e82cf9f57353f09e1713be18f689efe08515f38
SIZE (tinyarray-1.1.0.tar.gz) = 31712

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Tinyarrays are similar to NumPy arrays, but optimized for small
sizes. Common operations on very small arrays are to 3-7 times
faster than with NumPy (with NumPy 1.6 it used to be up to 35
times), and 3 times less memory is used to store them. Tinyarrays
are useful if you need many small arrays of numbers, and cannot
combine them into a few large ones. (The resulting code is still
much slower than C, but it may now be fast enough.)
WWW: https://gitlab.kwant-project.org/kwant/tinyarray