When creating the sparse matrix (in MATLAB or C mode), since storage is in
column-major order, output the first column, then the second, then the third.
This gives a significant performance boost in use_dll mode (at both compilation
and runtime), because it facilitates memory accesses and expression reusage.
New options "mexext" and "matlabroot" are introduced, so that the preprocessor
knows where to find MATLAB and which architecture to compile for.
Only recent gcc is now supported. A set of optimization flags is used so that
compilation goes reasonably fast on large models.
Consequently, options "msvc", "mingw" and "cygwin" have been removed.
In particular, it is necessary to turn back DataTree::AddVariable() into a
non-virtual method, because it is called from DataTree's constructor. Enforcing
the absence of leads/lags is now done using a new boolean DataTree::is_static.
Take advantage of the new copy constructor for handling
PlannerObjectiveStatement more elegantly.
Unfortunately it is not possible to implement *move* constructor / assigment
operators, because the reference ExprNode::datatree is not mutable.
This facilitates switching variable types on the fly. In particular, this
allows removing the hack in DynamicModel::updateAfterVariableChange() that way
basically recreating all the nodes after the type change.
This mimicks the structure of M-functions (though the logic for filling the
temporary terms vector is a bit different).
This change implied a modification in the way we compute the checksum in case
of block decomposition (the temporary terms for the C output are not correctly
computed in that case).
Given a previously declared var_model, the var_expectation_model statement is
used to declare a way of forming expectations with this VAR (possibly using a
finite or infinite discounted sum). The var_expectation operator now takes a
single argument, the name of the var_expectation_model.
For the moment, this only works when the var_model is using equations
explicitly declared in the model block.
aux_equations only contain the definition of auxiliary variables, and
may diverge from those in the main model (equations), if other model
transformations applied subsequently. This is not a problem, since
aux_equations is only used for regenerating the values of auxiliaries
given the others.
For example, such a divergence appears when there is an expectation
operator in a ramsey model, see
tests/optimal_policy/nk_ramsey_expectation.mod */
This table serves no useful purpose. It is better to append auxiliary equations
at the time they are created, to avoid messing with the recursive ordering.
Ensure that all diff operators appear once with their argument at current
period (i.e. maxLag=0).
If it is not the case, generate the corresponding expressions.
This is necessary to avoid lags of more than one in the auxiliary
equation, which would then be modified by subsequent transformations
(removing lags > 1), which in turn would break the recursive ordering
of auxiliary equations.
See McModelTeam/McModelProject/issues/95 for an example.
In the absence of this option, if a var_model statement(s) is present, then aux vars/eqs are created for the same types of unary operators but only for equations specified in the var_model statement
In the absence of both this option and var_model statements, no unary op auxiliary variables are created
diffs continue to be substituted everywhere; for the moment auxiliary variables are created for diffs of expressions. A forthcoming change will allow auxiliary variables created for diffs of expressions to be linked with their lagged expressions as is currently the case for diffs of variables
More precisely, remove those variants where temporary_terms can be specified
without temporary_terms_idxs, in order to make clear that the latter is
expected. For situations where the tt_idxs are not needed (C, block MATLAB), an
empty map has to be explicitly given.
The version with no temporary_terms_idxs argument needs not be virtual, since
it is the same implementation in all derived classes. Rather move it at the
level of the base ExprNode class.
In the presence of MLVs, the temporary terms indexing was corrupted. The code
was using the implicit assumption that the ExprNodeLess ordering was giving the
same ordering as the temporary terms indexes ordering. But MLVs can be higher
in ExprNodeLess ordering than some other temporary terms, while they have the
lowest temporary terms index, hence the bug.
Fix this by no longer relying on the ExprNodeLess ordering, and rather use a
full map<ExprNode *, int> for ModelTree::temporary_terms_idxs. By the way,
simplify the code by removing a few useless data structures (e.g.
ModelTree::temporary_terms_idxs_*).