Hello Sympy Community,
I hope you’re doing well. Myself Monu kumar, and I’ve been exploring SymPy’s current support for partial differential equations as part of my preparation for open-source contributions and GSoC. While studying sympy.solvers.pde, I noticed that although pdsolve supports some first-order PDEs, there is no explicit implementation of classical methods like *Lagrange’s auxiliary equations* and *Charpit’s method* for first-order PDEs. I wanted to ask whether adding structured support for these methods would be a valuable contribution to SymPy. My initial idea is to: - Implement *Lagrange’s method* for linear first-order PDEs of the form P(x,y,z)p + Q(x,y,z)q = R(x,y,z) - Add a *restricted but extensible implementation of Charpit’s method* for nonlinear first-order PDEs - Keep the implementation modular under sympy/solvers/pde, with proper tests and documentation - Eventually integrate method selection into pdsolve once the core functionality is stable Before proceeding further, I would really appreciate your feedback on: 1. Whether this aligns with SymPy’s current PDE roadmap 2. Any design considerations or limitations I should be aware of 3. Whether you’d recommend starting with a smaller scoped subset Thank you for your time and guidance. I’d be very happy to refine the idea based on your suggestions. Best regards, Monu kumar -- 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 [email protected]. To view this discussion visit https://groups.google.com/d/msgid/sympy/3068df5d-9aeb-48b5-b424-88b4f6d2b0den%40googlegroups.com.
