uncertainties 3.1.7-2 source package in Ubuntu

Changelog

uncertainties (3.1.7-2) unstable; urgency=medium

  * Team upload.

  [ Federico Ceratto ]
  * Set Debian Python Modules Team as maintainer

  [ Andreas Tille ]
  * Move git repository to DPT
  * Update maintainer email for merge of DPMT and PAPT.
  * Remove sphinx doc from debian/html
    Closes: #1046237

 -- Andreas Tille <email address hidden>  Wed, 14 Feb 2024 15:30:02 +0100

Upload details

Uploaded by:
Debian Python Team
Uploaded to:
Sid
Original maintainer:
Debian Python Team
Architectures:
all
Section:
python
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Noble release universe python

Builds

Noble: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
uncertainties_3.1.7-2.dsc 2.3 KiB fa5a60bf8c48680dbb3cfa989e7f29ab573062b613e2a9cb11b1c0a142da7873
uncertainties_3.1.7.orig.tar.gz 147.1 KiB e3acf18300e1f2c598d98636394a02820301e2b799df9b0ffcf9c9335c7a67f3
uncertainties_3.1.7-2.debian.tar.xz 6.2 KiB 83010629b13622f49bfcdf6e0acc6ff34559c06ff0b2b5477c9c8582b4430bf7

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.