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Source: uncertainties
Maintainer: Debian Python Team <team+python@tracker.debian.org>
Uploaders: Federico Ceratto <federico@debian.org>,
David Paleino <dapal@debian.org>
Section: python
Priority: optional
Build-Depends: debhelper-compat (= 13)
Build-Depends-Indep: dh-sequence-numpy3,
dh-sequence-python3,
dh-sequence-sphinxdoc <!nodoc>,
pybuild-plugin-pyproject,
python3-all,
python3-pytest,
python3-pytest-cov,
python3-numpy,
python3-setuptools,
python3-setuptools-scm,
python3-sphinx,
python3-sphinx-copybutton,
Standards-Version: 4.7.2
Vcs-Browser: https://salsa.debian.org/python-team/packages/python-uncertainties
Vcs-Git: https://salsa.debian.org/python-team/packages/python-uncertainties.git
Homepage: https://packages.python.org/uncertainties/
Rules-Requires-Root: no
Testsuite: autopkgtest-pkg-pybuild
Package: python3-uncertainties
Architecture: all
Multi-Arch: foreign
Depends: ${misc:Depends},
${python3:Depends}
Recommends: python3-numpy
Breaks: python3-lmfit (<< 1.3.3-3~), python3-pymatgen (<< 2025.2.18+dfsg1-5~)
Suggests: python-uncertainties-doc
Provides: ${python3:Provides}
Description: 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.
Package: python-uncertainties-doc
Architecture: all
Multi-Arch: foreign
Section: doc
Depends: ${misc:Depends},
${sphinxdoc:Depends},
node-mathjax-full,
Suggests: python3-uncertainties
Description: 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
|
