Add more options to control NLP scaling #649
Merged
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In this PR, the following user parameters are introduced:
scaling_max_obj_grad
: If a positive value is given, the objective of user's NLP will be scaled so that the inf-norm of its gradient is equal to the given value. This value overwrites the value given byscaling_max_grad
. Default value is 0scaling_max_con_grad
: If a positive value is given, the constraints of user's NLP will be scaled so that the inf-norm of its gradient is equal to the given value. This value overwrites the value given byscaling_max_grad
. Default value is 0scaling_min_grad
: If a positive value is given, it is used as the lower bound for the scaling factors. This option has a priority, i.e., the final scaling factor computed must greater or equal to this value, even thought it may violate the values given inscaling_max_grad
,scaling_max_obj_grad
andscaling_max_con_grad
. Default value is 1e-8CLOSE #648