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Displays an error message when the model contains pound expressions and 'bytecode' or 'block' options are present

347ab4d0 and corrects the earlier
ordering problem.

cosmetic: simplify jacobianHelper, hessianHelper and sparseHelper functions and fix spacing in dynamic file

  + the number of static, lag, lead and both variables,
  + the lead_lag_incidence matrix for variables related to previous blocks
  + the index of reordered policy rule
for each block during the preprocessing step
- correct a bug in the comment related to first order derivatives in _dynamic.m file for a block decomposed model without bytcode
- avoid simplification of the Jacobian matrix (setting to zero all elements below the cutoff) for  estimated or stochastically simulated models: the cutoff option is set to 0.

renamed ramsey_policy_discount_factor by optimal_policy_discount_factor because it is also used by discretionary_policy

Correct a bug when the model contains deterministic exogenous variables and bytecode option is used.
Note that stochastic simulations do not work for the moment with block option.

put *_params_derivs.m and identification code in conformity with additional steady state argument in *_dynamics.m

new correction for steady_state operator bug. Steady_state vector is passed as argument to *_dynamic model function. As a result, bytecode is currently broken.

The derivatives with respect to endogenous variables of the previous blocks are corrected for a block-decomposed model without bytecode option

- Adds a "lead_lag_incidence" matrix in each block for the endogenous variables belonging to previous blocks (other_endo)

fixed bug: end _dynamic and _static and getPowerDeriv functions with "end" tags to comply with commit d8dbc68e

Bugfix at order 3 (hopefully was not affecting final results, thanks to Pablo Winant for spotting this):
- in the 3rd derivatives matrix, among symmetric elements, the first one had
the right values but the following ones were set to zero
- moreover, the k-order DLL was trying to add all the symmetric elements in the
folded tensor, instead of only keeping one value among all the symmetric ones
- hopefully, Ondra's tensor library was (silently) refusing to add symmetric
elements after the first (and right) value had been added
- so the final result was correct

and corrects the computation of the number of column in the jacobian matrices in a block decomposed model without bytecode
- Identical corrections for models using bytecode without block decomposition

Preprocessor: max lead/lags in the model are no longer affected by lead/lags on parameters (closes #153)

- Add wrapper needed to compute the steady-state using bytecode and solve_algo = 0, ..., 4