Abstract
GNSS_Vel_95CI.py is an open-source Python-3 module for calculating the 95% confidence interval (95% CI) for the site velocity derived from global navigation satellite systems (GNSS) daily positions, which are often affected by time-correlated noises. The detailed methodology for calculating the 95% CI is documented in a recent article (Wang 2022) and initially programmed in Fortran. However, few young researchers (e.g., graduate students) are familiar with Fortran now. In an effort to support a broader user community, we have realized the method in the Python programming language, which has been commonly taught in current college curriculums. Through the use of this module, researchers and engineers can focus on the applications of GNSS time series, rather than on coding and data processing. In particular, the module has the option to output the autocorrelation function (ACF) and the GNSS time-series decomposition results: the linear, nonlinear, seasonal, and residual components, which allow students and researchers having little coding experience to conduct advanced GNSS time-series analysis. The module is versatile, easy to install through the pip installer and GitHub, and simple to use. An example Python program is provided to illustrate the use of this module.
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