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This is an excellent tool, I really thought SymPy was capable of this sort of thing. However for more advanced equations, like differential equations, it does not exactly work, if I describe something like the time - independent - schroedinger - equation I dont have a way of putting it in, even if it cant do all the operations, would it work to maybe take the stringified version of the SymPy data e.g Eq(-hbar**2*Derivative(psi(x), (x, 2))/(2*m) + V(x)*psi(x), E*psi(x)) this can maybe be walked like an AST? Treat unknowns as functions?
Just a suggestion:
It looks like you are doing your own parsing, which is commendable, but maybe something like atoms() or free_symbols() would work better? Maybe specifying operations and their inverses in its own base-database (e.g derivative being the inverse of integral (noting that constants can be lost)?
The text was updated successfully, but these errors were encountered:
This is an excellent tool, I really thought SymPy was capable of this sort of thing. However for more advanced equations, like differential equations, it does not exactly work, if I describe something like the time - independent - schroedinger - equation I dont have a way of putting it in, even if it cant do all the operations, would it work to maybe take the stringified version of the SymPy data e.g
Eq(-hbar**2*Derivative(psi(x), (x, 2))/(2*m) + V(x)*psi(x), E*psi(x))
this can maybe be walked like an AST? Treat unknowns as functions?Just a suggestion:
It looks like you are doing your own parsing, which is commendable, but maybe something like atoms() or free_symbols() would work better? Maybe specifying operations and their inverses in its own base-database (e.g derivative being the inverse of integral (noting that constants can be lost)?
The text was updated successfully, but these errors were encountered: