this removes the python2.1 FLAVOR as it is pretty useless, set
MODPY_VERSION in case you need to compile this with python 2.1
no in-tree port requires this
MAINTAINER timeout, from Andrew Dalgleish <openbsd@ajd.net.au>
* Introducing basic and scientific mode.
* Number base, angle unit and notation mode are remembered on exit.
No defaults anymore.
* Updates to binary mode.
* New functions (asinh, acosh, atanh) and a new operation (percent).
* Bug fixes: crash on bracket closing, remember display value, GUI.
* Japanese translation, translation updates.
The MCL algorithm is short for the Markov Cluster Algorithm,
a fast and scalable cluster algorithm for graphs based on
simulation of (stochastic) flow in graphs. The algorithm was
developed by Stijn van Dongen at the Centre for Mathematics and
Computer Science (also known as CWI) in the Netherlands.
The MCL algorithm is very fast, very scalable, and has a number
of attractive properties causing it to deliver high-quality
clusterings.
WWW: http://micans.org/mcl/
from Andreas Kahari <andreas.kahari@unix.net>
galculator is a GTK2-based scientific calculator with ordinary
notation/reverse polish notation, different number bases (DEC, HEX,
OCT, BIN) and different units of angular measure (DEG, RAD, GRAD).
Maxima is a descendant of DOE Macsyma, which had its origins in the
late 1960s at MIT. It is the only system based on that effort still
publicly available and with an active user community, thanks to its
open source nature. Macsyma was the first of a new breed of computer
algebra systems, leading the way for programs such as Maple and
Mathematica. Maxima itself is reasonably feature complete at this
stage, with abilities such as symbolic integration, 3D plotting, and
an ODE solver, but there is a lot of work yet to be done in terms of
bug fixing, cleanup, and documentation.
WWW: http://maxima.sourceforge.net/
Submitted by rich@cannings.org with minor tweaks by me
--
This module implements some algorithms for calculating Fast Fourier
Transforms for one-dimensional data sets of size 2^n. The data,
assumed to arise from a constant sampling rate, is represented by
an array reference, which is then used to create a Math::FFT object.
Available methods include complex and real discrete fourier transforms,
convolution, power spectra and windowing functions, as well as some
statistical utilities.
