Some changes for oofun

Some changes for oofun:

• oolin now can handle matrices: oolin(C) creates oofun that returns numpy.dot(C, inp_array); oolin(C, d) yields oofun that returns numpy.dot(C, x) + d. See updated oolin example.
  
• add fixed variables handling for oovars. Now you can declare v.fixed = True or just v = oovar(..., fixed = True). So all oofuns that recursively depend on fixed oovars only will be calculated only once, and derivatives will be all-zero (hence no calculations will be required for those parts of code that depend on fixed oofuns only). In future it will be good to have inner fixed coords for oovars, like this: v.fixed = [0, 1, 15] (i.e. positions of fixed coords inside the oovar). See the fixed oovars example.
  

However, let me remember you that currently oolin(anything) is considered as non-linear code, i.e. it goes to non-linear constraints and objective function only. In future it should be implemented oolin(some_oovars) -> general linear constraints (Ax <= b, Aeq x = beq). As for lb <= x <= ub, they are handled correctly from oovar fields.