ldds
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Python package for computing and visualizing Lagrangian Descriptors in Dynamical Systems
Guidelines https://packaging.python.org/tutorials/packaging-projects/
For the future, this can be done by defining our own filters, OR Use other filters implemented by other Python libraries for image-processing.
Justification: - now if one trajectory crashes, all crash - parallelisation
Storing the gradient data from LDs....for example for a section x=1 with px>0 to store the data for (y, py, gradient(LDs)) .
This seems a very useful feature for user-experience, to visualize how trajectories seat in phase-space alongside manifolds. By default, they shouldn't be stored, as the main objective is to compute...