Software to build dynamical systems models from time series with chaotic behavior

In physics and other sciences there are dynamic systems that exhibit chaotic behavior. Understanding and predicting the behavior of these systems depends on the ability to build models of them. That is why software written in the python language is being developed that allows us to experiment numerically in an agile and precise way with different models of the dynamics of a time series that presents chaotic behavior. This software has a graphical interface divided into three sections. The first section has tools that allow you to interact with the built models. The second section has tools that allow you to establish whether a time series can exhibit chaotic behavior. The third section has tools that allow models to be built from time series. Finally, using the Lorenz system, an example of the use and utility of this software for the construction of models from time series and its possible usefulness in real data is presented. (paper)