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Python library for dealing with uncertainties and upper/lower limits

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# RichValues &nbsp; <img src="logo.png" width=30>

Python 3 library for dealing with numeric values with uncertainties, upper/lower limits and finite intervals, which may be called _rich values_.

With it, one can import rich values written in plain text documents in an easily readable format, operate with them propagating the uncertainties automatically, and export them in the same formatting style as the import. It also allows to easily plot rich values and to make fits to any function taking into account the uncertainties and upper/lower limits or finite intervals. Correlations between variables (that is, variables which are not independent) are taken into account when performing calculations with rich values. Rich values of integer nature and rich values containing complex numbers are also supported. Lastly, rich values can be defined using a probability density function (PDF) instead of giving a main value with uncertainties or an upper/lower limit or a finite interval.

The libraries NumPy, Pandas, SciPy and Matplotlib are required.

You can read the user guide ([`userguide.pdf`](https://github.com/andresmegias/richvalues/blob/main/userguide.pdf)) to learn how to use this library. You can also test with the tutorials and example scripts located in the [examples](https://github.com/andresmegias/richvalues/blob/main/examples/) folder.

## Installation

To install RichValues, you can use the Python package installer to download it from the Python Package Index (PyPI). To do so, run from the terminal the following command:
~~~
pip3 install richvalues
~~~
Alternatively, you can use the Conda package installer:
~~~
conda install richvalues -c richvalues
~~~

## Tutorials
You can check this [quick tutorial](https://github.com/andresmegias/richvalues/blob/main/examples/quick-tutorial.ipynb) to learn the basics of this library. Afterwards, you can check the rest of tutorials and example scripts in the [examples](https://github.com/andresmegias/richvalues/blob/main/examples/) folder.

## Links
- Project page on PyPI: https://pypi.org/project/richvalues/.
- Project page on Anaconda website: https://anaconda.org/richvalues/richvalues/.

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