Ubuntu
uncertainties package

uncertainties 3.1.7-1.1 source package in Ubuntu

Changelog

uncertainties (3.1.7-1.1) unstable; urgency=medium

  * Non-maintainer upload: patch out extraneous python3-future.

 -- Alexandre Detiste <email address hidden>  Fri, 15 Dec 2023 21:00:36 +0100

Upload details

Uploaded by:
Federico Ceratto
Uploaded to:
Sid
Original maintainer:
Federico Ceratto
Architectures:
all
Section:
python
Urgency:
Medium Urgency

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Builds

Noble: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
uncertainties_3.1.7-1.1.dsc 2.3 KiB d83f5210d99598e4e6609a276019cf5ce3fc3e8fc3d110e0195b0ba01ddf67b3
uncertainties_3.1.7.orig.tar.gz 147.1 KiB e3acf18300e1f2c598d98636394a02820301e2b799df9b0ffcf9c9335c7a67f3
uncertainties_3.1.7-1.1.debian.tar.xz 6.1 KiB 4cef8b3a3817e3873371ccaa6e6480c82231329fed5a4a32ea8b032934190907

Available diffs

No changes file available.

Binary packages built by this source

python-uncertainties-doc: Python3 module for calculations with uncertainties: documentation

 uncertainties is a Python3 module, which allows calculations such as
 .
   (0.2 +/- 0.01) * 2 = 0.4 +/- 0.02
 .
 to be performed transparently; much more complex mathematical expressions
 involving numbers with uncertainties can also be evaluated transparently.
 .
 Correlations between expressions are correctly taken into account; x-x is
 thus exactly zero, for instance. The uncertainties produced by this module
 are what is predicted by error propagation theory.
 .
 This package contains documentation for the python3-uncertainties package

python3-uncertainties: Python3 module for calculations with uncertainties

 uncertainties is a Python3 module, which allows calculations such as
 .
   (0.2 +/- 0.01) * 2 = 0.4 +/- 0.02
 .
 to be performed transparently; much more complex mathematical expressions
 involving numbers with uncertainties can also be evaluated transparently.
 .
 Correlations between expressions are correctly taken into account; x-x is
 thus exactly zero, for instance. The uncertainties produced by this module
 are what is predicted by error propagation theory.