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Ideally, a user should be able to define (and compile) an ODEProblem directly in julia, and then provide that DiffEqPy. This shouldn't be a major lift, but will require some additional utilities.
Also, because the current julianumpy backend represents symbolic arrays as arrays of symbolics, compile times can be prohibitively long for large or high dimensional systems. Defining and compiling an ODEProblem in julia directly should be the easiest way to sidestep compile-time issues.
The text was updated successfully, but these errors were encountered:
Ideally, a user should be able to define (and compile) an
ODEProblem
directly injulia
, and then provide thatDiffEqPy
. This shouldn't be a major lift, but will require some additional utilities.Also, because the current
julianumpy
backend represents symbolic arrays as arrays of symbolics, compile times can be prohibitively long for large or high dimensional systems. Defining and compiling anODEProblem
in julia directly should be the easiest way to sidestep compile-time issues.The text was updated successfully, but these errors were encountered: