Abstract
In recent years, transforming a time series into visibility network has emerged as a powerful tool of data analysis, with applications in many pure and applied domains of statistical physics and non-linear dynamics. The algorithms available for this transform are either very slow or consume copious amount of memory resorting to recursive calls. Here we propose an efficient non-recursive algorithm for constructing natural visibility graph from time series data. In comparison to the recursive method, the new algorithm offers safer and more optimized use of memory space without sacrificing its speed. Performance of this algorithm is tested with a variety of synthetic and experimental time series data-sets.
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