Modified L1, logisitc ELL and GetStat

Changed method of generating and sampling spikes, and generating
sufficient statistics. Now sampled spikes are zero if not observed (not
NaN as before), and observations (a binary array) indicate were do we
have sampling. This seems to speed up GetStat, though may take more
memory for large spike arrays (Maybe sparse matrices can improve here?
Didn't noticed an improvment so far).

EstimateA_L1_logistic - added a correction to quadratic form of the
approximated logistic regression.
EstimateA_L1_logistic_known_b - if bias is known, this gives an estimate
of the weight matrix, if we assume that quadratic form has the
linearized form of logistic MLE. Sometimes work better (but does not
work well if b is estimated... so not useful).
logistic_ELL - applies Liam's logistic ELL approximation in order to
correct amplitude and bias of weights. Sometimes improves...
networ_simulation_Poisson - added an option to simulate network with
Poisson firing patterns