Work around the nan gradient problem

The problem is still there:
After imposing a maximum on the norm of the
gradient, the minimizer still ends in state with
huge amplitude returning a nan gradient.
So the minimizer stops and return the huge valued
state with nan gradient.
When that happen, we want the previous state as
analysis.
what if retall==False?
minor error correction
renamed B_sqrt -> B_sqrt_isoHomo
B_sqrt_str_op (structure function covariances)

not ready yet!
strct. func. model covariance: better, but not yet

B=(sig*v)(sig*v^T) simple to implement, but a big difference with the spectral treatment of the isotrope and homogeneous case is that since there is no going and back to spectral case, the phasing becomes important and it wreck the action of B^{1/2}^T...
added a obs. space scalar product
new plotting routines for StaticObs
plotting method for TWObs adjustments
removed default color from plotObs
added rndSampling and coeffCorr
move degradTraj as Trajectory.degrad()
new module: observ (observability)
removed default color from plotObs
Redefined correlation coefficient
StaticObs.correlation() and norm wrt B^{-1} todo
added correlation option to plotObs()
added dVar.make_BisoHomo_args()
minor modif
minor correction in plotObs()