nixpkgs/pkgs/development/octave-modules/queueing/default.nix
Silvan Mosberger 4f0dadbf38 treewide: format all inactive Nix files
After final improvements to the official formatter implementation,
this commit now performs the first treewide reformat of Nix files using it.
This is part of the implementation of RFC 166.

Only "inactive" files are reformatted, meaning only files that
aren't being touched by any PR with activity in the past 2 months.
This is to avoid conflicts for PRs that might soon be merged.
Later we can do a full treewide reformat to get the rest,
which should not cause as many conflicts.

A CI check has already been running for some time to ensure that new and
already-formatted files are formatted, so the files being reformatted here
should also stay formatted.

This commit was automatically created and can be verified using

    nix-build a08b3a4d19.tar.gz \
      --argstr baseRev b32a094368
    result/bin/apply-formatting $NIXPKGS_PATH
2024-12-10 20:26:33 +01:00

34 lines
1.2 KiB
Nix

{
buildOctavePackage,
lib,
fetchurl,
}:
buildOctavePackage rec {
pname = "queueing";
version = "1.2.7";
src = fetchurl {
url = "mirror://sourceforge/octave/${pname}-${version}.tar.gz";
sha256 = "1yhw277i1qgmddf6wbfb6a4zrfhvplkmfr20q1l15z4xi8afnm6d";
};
meta = with lib; {
homepage = "https://octave.sourceforge.io/queueing/index.html";
license = licenses.gpl3Plus;
maintainers = with maintainers; [ KarlJoad ];
description = "Provides functions for queueing networks and Markov chains analysis";
longDescription = ''
The queueing package provides functions for queueing networks and Markov
chains analysis. This package can be used to compute steady-state
performance measures for open, closed and mixed networks with single or
multiple job classes. Mean Value Analysis (MVA), convolution, and various
bounding techniques are implemented. Furthermore, several transient and
steady-state performance measures for Markov chains can be computed, such
as state occupancy probabilities, mean time to absorption, time-averaged
sojourn times and so forth. Discrete- and continuous-time Markov chains
are supported.
'';
};
}