An algorithm to select unique values in arrays of imprecise floating-point data within a given tolerance, written in different languages. Given an array of numbers, the algorithm returns its largest subset in which no pairs of elements are approximately equal. Here two numbers x and y are said to be "approximately equal" within an absolute tolerance atol or a relative tolerance rtol if and only if |x - y| ≤ max(atol, rtol∙max(|x|, |y|)).
A stable version for 1D arrays has been completed in several languages (although certain optimization steps remain). Out of these, the C++ implementation is the fastest. Right now, the algorithm finishes running within a reasonable time frame (less than a minute) on arrays of up to 2 million doubles in all implemented languages. I am currently adding functionality for operating along specified axes of multidimensional arrays and packaging the project into language-specific libraries.
This project was inspired by the uniquetol function in MATLAB and NumPy's unique function in Python.
(WORK IN PROGRESSS)