enhanced iterfcn connection for scipy fmin_cobyla

I have connected changes related to handling of scipy_cobyla iterfcn, so now instead of direct line (as before) it looks like this:

Of course, adequate text output is provided as well:

solver: scipy_cobyla   problem: unnamed   goal: minimum
iter    objFunVal    log10(maxResidual)
 0  6.115e+01               2.13
10  2.015e+01              -2.82
20  2.029e+01              -6.46
30  2.030e+01              -7.60
40  2.032e+01              -8.70
50  2.032e+01             -10.30
60  2.033e+01              -9.78
70  2.033e+01             -13.41
80  2.033e+01             -15.58
90  2.033e+01             -12.50
96  2.033e+01             -21.03
istop:  1000
Solver:   Time Elapsed = 0.72     CPU Time Elapsed = 0.69
Plotting: Time Elapsed = 6.72     CPU Time Elapsed = 5.31
objFunValue: 20.329368 (feasible, max constraint =  9.3314e-22)

Also, fEnough, maxTime, maxCPUTime and some other stop criteria work (for scipy_cobyla).

Initially users had to connect iterfcn by themselves (to df, dc, dh etc), then it had been done automatically by default to df, now (with latest changes) it is for f and df only and automatically.

Now NLP instance has parameter f_iter (default is max(nVars,4)), so when number of called objective function exceeds p.f_iter (for scipy_cobyla and other solvers w/o iterfcn connected and gradient using), OO iterfcn function is called (and hence user-supplied callback functions(s) if any are declared).

Also, for those solvers who hasn't native connection to OO iterfcn and use derivatives (algencan, ipopt, scipy_slsqp, some unconstrained and box-bounded ones) there is parameter df_iter, default True (use iterfcn each call for df); if positive integer s(s>1, 1 is same to default True) - use iterfcn each s-th objective function gradient call.

Mb I'll change "f_iter" and "df_iter" to more appropriate field names till next OO release.