Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.
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Updated
May 16, 2024 - Python
Error (or uncertainty) propagation is the practice of analyzing and accounting for the effect of numeric quantities' uncertainties on the results of functions that involve them.
When variables used in a function or mathematical operation have errors (due to measurement uncertainties, random fluctuations, sample variance, etc.), error propagation can be used to determine the resulting error of the function's output.
Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.
Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration.
Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
Error propagation and statistical analysis for Markov chain Monte Carlo simulations in lattice QCD and statistical mechanics using autograd
Uncertainty Propagation for R Vectors
Tools for uncertainty propagation and measurement unit conversion — Outils pour la propagation des incertitudes et la conversion d'unités de mesure
Numerical derivatives for Python
A package for handling numeric quantities with asymmetric uncertainties.
pure Julia package for optimal histogram binning, based on piecewise constant model.
C++ header library for first- and second-order uncertainty propagation
Toolkit for studying numerical analysis and floating point algebra round-off
Error propagation with covariant variables
Dimensional analysis and error propagation packages to make science easier.
Propagation of uncertainty calculator. It can export and import a session for later usage.
Lightweight automatic differentiation and error propagation library
Propagate error in an equation symbolically
Calculating values with error intervals
When determining equilibrium constants of multi-substrate / multi-product reactions, their ratios affect the uncertainty of the result.
The source code used in the B.Sc Thesis: "Experimental study of swirl flow and heat transfer in concentric cylinders with tangential inlet flow". A summary of this work's results was presented at the Proceedings of the 10th IC-SCCE, held in Athens during 6th-9th July 2022.