NaNtolerant

NaNtolerant is an open-source software library designed to enhance numerical stability and robustness in computational workflows, particularly in scientific and engineering applications. The library focuses on handling and mitigating issues related to floating-point arithmetic, such as division by zero, overflow, underflow, and most notably, the representation of indeterminate forms like "Not a Number" (NaN). NaN values arise in floating-point calculations when operations produce undefined or unrepresentable results, such as 0/0 or √(-1), which can disrupt computations and lead to incorrect conclusions if left unaddressed.

Developed with a focus on clarity and extensibility, NaNtolerant provides utilities to detect, filter, and replace NaN values with meaningful defaults or interpolated estimates. It supports integration with popular numerical libraries like NumPy, SciPy, and TensorFlow, making it accessible for users working in data science, machine learning, and high-performance computing. The library also includes tools for validating numerical inputs and outputs, ensuring data integrity in simulations and analytical models.

NaNtolerant is distributed under an open-source license, allowing for community contributions and customization. Its modular design enables users to implement tailored strategies for handling numerical inconsistencies, such as adaptive thresholding or domain-specific fallback mechanisms. While primarily intended for researchers and developers, the library’s simplicity makes it suitable for educational purposes as well, fostering awareness of floating-point precision challenges in computational mathematics.