I have committed some changes for NLP/NSP solver ralg (some ones to speedup and some ones for better handling NaNs, if x is outside of dom objFunc or dom of some non-linear constraints).
Another one parameter (mostly for NLP/NSP) have been added: isNaNInConstraintsAllowed (default False). This one means is nan (not a number) allowed in non-linear constraints for optim point (mostly for inequalities: p.c(r.xf)).
Non-default value True is encountered very seldom, for very special cases.
Also, some code cleanup for ralg and some examples, + some changes for tests/chain.py.
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