> Numerical Jacobian calculation is not so bad in terms of coding effort
The issue is that, if I understand correctly, GEGL's current "pure"
demand-driven structure means that resamplers have no information
whatsoever about what other nearby locations are being resampled, and
consequently there would need to be major changes to make this info
available for arbitrary transformations (with, most likely, serious
speed impact). Once you have it, sure, computing approximate Jacobian
matrices is no big deal (provided you make sure that you stay from
Hence my pragmatic choice to reserve the use of the "novel" (not so
sure anymore that it's really new) method for tasks for which the
jacobian is easy to compute and pass on. (This is the: "ask people who
know better" part.)
Does this make sense to you?
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