How to Install and Uninstall libmath-random-mt-perl Package on Ubuntu 21.04 (Hirsute Hippo)

Last updated: May 17,2024

1. Install "libmath-random-mt-perl" package

In this section, we are going to explain the necessary steps to install libmath-random-mt-perl on Ubuntu 21.04 (Hirsute Hippo)

$ sudo apt update $ sudo apt install libmath-random-mt-perl

2. Uninstall "libmath-random-mt-perl" package

This is a short guide on how to uninstall libmath-random-mt-perl on Ubuntu 21.04 (Hirsute Hippo):

$ sudo apt remove libmath-random-mt-perl $ sudo apt autoclean && sudo apt autoremove

3. Information about the libmath-random-mt-perl package on Ubuntu 21.04 (Hirsute Hippo)

Package: libmath-random-mt-perl
Architecture: amd64
Version: 1.17-1build6
Priority: optional
Section: universe/perl
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Perl Group
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 52
Depends: perl (>= 5.32.0-4), perlapi-5.32.0, libc6 (>= 2.2.5)
Filename: pool/universe/libm/libmath-random-mt-perl/libmath-random-mt-perl_1.17-1build6_amd64.deb
Size: 13036
MD5sum: d48376c913c30d160e37e1be6c0c830f
SHA1: f3e3f4c47c86b7703c913631ba6eb0a745400831
SHA256: f3f1d9dcad9e327b66cef97939b7afd89e0ab519a42a613be09bb7b9600b3742
SHA512: db9fb54109bb5dd9cbf530a4b8e9146c5f3bdc04e976f2830bf23caa1d4ce17410d2ef813d537f3d080f49df554dc6f393e4fc9e4a8cd53531399433d44127c6
Homepage: https://metacpan.org/release/Math-Random-MT
Description-en: Perl implementation of the Mersenne Twister algorithm
Math::Random::MT provides an implementation of the Mersenne Twister
pseudorandom number generator algorithm developed by Makoto Matsumoto
and Takuji Nishimura.
.
It is related to but a different algorithm than a previous work by
the same authors - the TT800 algorithm, which keeps less state data
(MT uses 624 numbers compared to TT800's 25). Consequently, the
period is much larger - 2^19937-1 compared to TT800's 2^800-1. For
comparison, ISAAC's period is 2^8295 values on average.
.
For more information, peruse M. Matsumoto and T. Nishimura's paper:
.
Description-md5: ebdfc64a41c3239a7ebb6bee6083379e