Hello Sympy developers, I am Animesh, a First-Year student studying Computational Natural Sciences (A dual degree in Computer Science and Natural Science) in International Institute of Information Technology, Hyderabad, India. I have been writing code in Python and C++ for over 6 years now, and in this duration I have written a couple Django websites, tried a few Artificial Intelligence courses, and some other things most of which you can find on my GitHub profile (github.com/AnimeshSinha1309).
In college I use Scipy, Numpy, Sympy combo everyday as my course is oriented around Computational techniques to solve Physics and Math problems. Having just finished a course in *Classical Mechanics* this semester, pulls my interests in that domain in the Physics module of the Sympy project. I am relatively new to Sympy development, and have managed about 5 Pull requests <https://github.com/sympy/sympy/pulls?utf8=%E2%9C%93&q=is%3Apr+author%3AAnimeshSinha1309>. Currently, I am trying to work on Hamiltonian dynamics along with attempting to put together a GSoC project on Efficiently Generating Equations of Motion with Python using the Featherstone-Jain method. Here I would really need some help, for I understand what we are trying to do, and I know the Lagrange and Kane methods by hand, I am *really unable to find any good resources on the Featherstone-Jain method* that has been described in the Idea document. Any advice on how I can make progress will be appreciated. Thanks a lot to everyone. Sincerely yours, Animesh Sinha. -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to sympy+unsubscr...@googlegroups.com. To post to this group, send email to sympy@googlegroups.com. Visit this group at https://groups.google.com/group/sympy. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/a62d4365-d649-4ae3-a4fa-be72bada44b6%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
