PyErri

PyErri is a Python library designed for calculating and analyzing error propagation in scientific and engineering contexts. It allows users to define variables with associated uncertainties and then propagate these uncertainties through mathematical operations and user-defined functions. The library aims to simplify the often complex process of determining the uncertainty of a calculated result based on the uncertainties of its input parameters.

The core functionality of PyErri revolves around its uncertainty object. Users can create these objects by specifying a central value and a measure of its uncertainty, such as a standard deviation. These objects can then be combined using standard arithmetic operators like addition, subtraction, multiplication, and division. PyErri automatically applies the rules of error propagation to compute the resulting value and its uncertainty. Beyond basic arithmetic, the library supports more complex operations and the propagation of uncertainties through custom Python functions, enabling its use in a wide range of applications.

PyErri is particularly useful for researchers, engineers, and students who need to quantify the reliability of their experimental results or model outputs. By providing a programmatic way to handle uncertainty, it helps ensure that the limitations and precision of measurements are correctly accounted for in subsequent calculations. This can lead to more robust scientific conclusions and more reliable engineering designs. The library is available as an open-source project, facilitating its adoption and further development within the scientific community.