Also remove a message about elements below the cutoff that was no longer
correct (elements below the cutoff have no impact on the incidence matrix
outside of normalization).
By the way, remove the BlockType stuff which was purely informative (and it’s
not worth carrying over prologue and epilogue information just for that).
Previously, the cutoff option would also impact the block decomposition itself,
since it would had an influence on the incidence matrix used for computing the
blocks and their derivatives.
The problem is that, in the general case, it’s quite possible that an element
of the numerical Jacobian be zero at the evaluation point, while being quite
different from zero along the simulation path. A typical example is an
expression of the type x*y, where y is an endogenous and x is an exogenous not
present in the initval block (and hence initialized to zero).
It has been superseded by ModelTree::blocks_derivatives.
By the way, fix the initial number of non-zero elements in sparse Jacobian.
Also avoid computing suboptimal temporary terms.
— use a std::map for storing block derivatives
— remove redundant ModelTree::first_chain_rule_derivatives structure
— remove unused codepaths in StaticModel
— DynamicModel: simplify code that determines the type of derivatives in a
block. We now use a slightly different categorization.
— by the way, fix the max lead/lag information for blocks that are obtained via
merging. A workaround was previously implemented in
DynamicModel::get_Derivative(), but it is no longer needed with this fix.
This was only adding unneeded complexity, for no clear reason (we’re very far
from reaching 2³¹ equations, and if we wanted to support models that large, it
would be better to use long integers to avoid being limited to 2³²).
— return output arguments on the left-hand side
— do not pass class members as input/output arguments
By the way, fix a (benign) vector allocation bug in
{Static,Dynamic}Model::computeChainRuleJacobian().
Since commit 9c9e8f816f, it’s the information
from the original model which was in this field, which is not what is expected.
By the way, do not output this field (and the related M_.hessian_eq_zero) when
the Hessian is not computed by the preprocessor (i.e. in practice for perfect
foresight), since they would otherwise contain incorrect information.
Ref. dynare#1681
Auxiliary equations appearing in set_auxiliary_variables.m and
dynamic_set_auxiliary_series.m need to appear in recursive ordering, since
those files are used for sequential evaluation.
Previously, the recursive ordering was guaranteed by a set of ad hoc rules and
workarounds, but that would not cover certain edge cases.
With this commit, the recursive ordering is systematically computed, using a
topological sort on the directed acyclic graph whose vertices are auxiliary
equations and whose edges are dependency relationships.
Closes: #22
Allows for the inclusion/exclusion of a set of equations, specified either on the command line or in a text file.
If the equation has a single endogenous variable on the LHS, then the equation is moved. If not, if the equation has an `endogenous` tag then that variable is removed along with this equation. If not, then an error is thrown.
As a command line argument, `exclude_eqs` can take the form (same syntax for `include_eqs`):
* `exclude_eqs=eq1 to remove all equations declared as `[name=eq1]`
* `exclude_eqs=[eq 1, eq 2]` to remove all equations declared as `[name=eq 1]` or `[name=eq 2]`
* `exclude_eqs=[tagname=X]` to remove all equations declared as `[tagname=X]`
* `exclude_eqs=[tagname=(X, Y)]` to remove all equations declared as `[tagname=X]` or `[tagname=Y]`
When declared in a file, the file should be of the form:
```
eq 1
eq 2
```
to remove all equations declared as `[name=eq 1]` or `[name=eq 2]`.
It should be of the form:
```
tagname=
X
Y
```
to remove all equations declared as `[tagname=X]` or `[tagname=Y]`.
— Raise the default tolerance for cross-derivatives to 1e-6, to reduce the
number of false positives
— New option “balanced_growth_test_tol” to the “model” block for changing that
tolerance
— Turn back test failures into errors. Since there is now an option for
controlling the tolerance, the user always has the possibility of making the
test pass.
Closes: dynare#1389
Sébastien Villemot
Michel Juillard
Houtan Bastani