If you add Arrow RecordBatch or Table output to CVODE with arrow-cpp, e.g. Dask can zero-copy buffers to Python (pyarrow, pandas.DataFrame(dtype_backend=arrow), or narwhals) when it needs to gather / fan in at a computational barrier in a process-parallel workflow.
Is sklearn-deap useful with scikits.odes and sundials (and dask or not)?
scikits.odes supports CVODE: scikits.odes.sundials.cvode: https://bmcage.github.io/odes/master/api/compat.html#module-....
sckits.odes docs > Choosing a Solver: https://scikits-odes.readthedocs.io/en/latest/solvers.html
scipy.integrate.solve_ivp has Radau, BDF, and LSODA for stiff ODEs, in Python: https://docs.scipy.org/doc/scipy/reference/generated/scipy.i...
If you add Arrow RecordBatch or Table output to CVODE with arrow-cpp, e.g. Dask can zero-copy buffers to Python (pyarrow, pandas.DataFrame(dtype_backend=arrow), or narwhals) when it needs to gather / fan in at a computational barrier in a process-parallel workflow.
Is sklearn-deap useful with scikits.odes and sundials (and dask or not)?