Automatic gradient check: ready!

here's an example of usage:
let's consider the NLP problem that I published 2 days ago (see here), and let's add the following lines:
p.check.df = 1
p.check.dc = 1
p.check.dh = 1
#also you may add/modify these ones:
prob.diffInt = 1e-07# default value is 1e-7
prob.check.maxViolation = 1e-05 #default value is 1e-5

(diffInt is ised in numerical gradient/subgradient obtaining;
lines where difference between user-supplied and OO-obtained (numerically) gradients are less than prob.check.maxViolation will not be shown)

Run this example and check your output with mine (that is attached in comment to the message)