scippuncertainty


Namescippuncertainty JSON
Version 23.11.0 PyPI version JSON
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SummaryAdvanced uncertainty propagation with Scipp
upload_time2023-11-20 15:09:24
maintainer
docs_urlNone
authorScipp contributors
requires_python>=3.9
licenseBSD 3-Clause License Copyright (c) 2023, Scipp contributors (https://github.com/scipp) All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
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# scippuncertainty

## About

Advanced uncertainty propagation with Scipp

[Scipp](https://scipp.github.io/) provides a basic facility for storing and propagating variances.
It can, however, not take correlations into account.
ScippUncertainty provides tools to this end.

## Installation

```sh
python -m pip install scippuncertainty
```

            

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