[MITgcm-devel] optim_numbmod: parameters in data.optim

[Martin Losch]

Hi there,

I would like to add a new parameter to data.optim.
Rather than specifying the expected optimized cost function value "fmin", I'd like to be able to specify a relative reduction, i.e. have something like dfmin = 0.1 for an expected decrease of 10%. This, to my mind, is much easier to do, especially, if you look at a series of optimization runs, where the initial cost function value is different between experiments by orders of  magnitude. Don't worry, fmin, will still be there and usable, I just want to add this option.

Now, for this to work I need the cost function value as computed by the model. This value is both in ecco_cost_* and ecco_ctrl_*, and it's read by optim_readdata.F (fileff), and optim_readdata is called from optim_numbmod, which would give me an easy way of computed fmin=(1-dfmin)*ff.
But unfortunately only for the "costname"-file, ff is returned as ff=fileff, for the ctrlname-file ff=0. I was wondering, if this is really necessary, or whether I can just return ff=fileff each time optim_readdata is called. I could also choose to return it whenever lheaderonly=.true. (as it is the case when called from optim_numbmod). I have the impression, from the output of optim.x, that neither of these changes, changes the output. Would you expect any changes in the results if ff=fileff is returned to optim_numbmod?

Martin