For most problems (especially vanderpol) it would be nice to support arbitrary data types. Here are some of the issues and things to consider
If a parameter is of a certain type, should Y0, TimeSpan, and other parameters be cast to the same data type? Sometimes this cannot be deduced or there are multiple parameters with different types.
cast is the most reasonable function to do this but functionality is limited in Octave. Critically, cast(x, 'sym') does not work.
Numbers with more than ~16 digits have to be broken up before casting.
Octave does not support the like name value pair used in functions like zeros and cast.
When we create differentiation matrices, the type needs to be consistent.
Initial condition checks in solveExactly may be fragile with arbitrary data types.
For most problems (especially
vanderpol) it would be nice to support arbitrary data types. Here are some of the issues and things to considerY0,TimeSpan, and other parameters be cast to the same data type? Sometimes this cannot be deduced or there are multiple parameters with different types.castis the most reasonable function to do this but functionality is limited in Octave. Critically,cast(x, 'sym')does not work.Octave does not support thelikename value pair used in functions likezerosandcast.solveExactlymay be fragile with arbitrary data types.