Abstract
Traffic Weaver is a Python package developed to generate a semi-synthetic signal (time series) with finer granularity, based on averaged time series, in a manner that, upon averaging, closely matches the original signal provided. The key components utilized to generate the signal encompass oversampling, recreating from average with a given strategy, stretching to match the integral of the original time series, interpolating, smoothing, repeating, applying trend, and adding noise. The primary motivation behind Traffic Weaver is to furnish semi-synthetic time-varying traffic in telecommunication networks, facilitating the development and validation of traffic prediction models, as well as aiding in the deployment of network optimization algorithms tailored for time-varying traffic.
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