champsproject / ldds

Python package for computing and visualizing Lagrangian Descriptors in Dynamical Systems
BSD 3-Clause "New" or "Revised" License
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StochasticLDs implementation #48

Closed broncio123 closed 3 years ago

broncio123 commented 3 years ago

Modified code for discrete systems to accept time-dependent iterative maps.

This was done so that the Euler-Maruyama solver could be used to construct forward and backward iterative maps for computation of SLDs, which allows taking advantage of pre-existing code for calculation of LDs of discrete systems.

Vector fields and Euler-Maruyama solver were simply added to pre-existing modules.

vkrajnak commented 3 years ago

Code and functionality seem all good to me.

Small reservation with respect to the nomenclature, I'm not sure how understandable are statements such as _time of next iteration with a default timestep equal to 1 and the fact that an Euler-Maruyama step function has to be created by the user. Personally I'd prefer a wapper for compute_lagrangian_descriptor that does it internally, but this is up to you/discussion.

Otherwise go ahead.