Automatically detected by clang-tidy with performance-move-const-arg check.
Do not make the modification for Tokenizer::location type, since we have no
guarantee that the type will remain trivially-copyable in the future.
It maps column indices in the Jacobian returned by bytecode MEX in evaluate
mode (which only contains nonzero columns, but also incorporate recursive
variables), into column indices in the sparse representation (which has 3×n
columns for two-boundaries blocks and n columns for one-boundary blocks).
Columns unused in the sparse representation are indicated by a zero.
When parsing the FSTPG{2,3} opcodes, the bytecode MEX internally constructs a
Jacobian with as many lines as feedback variables. But the preprocessor would
also output instructions for filling derivatives of equations corresponding to
recursive variables in the “evaluate” mode, thus leading to memory corruption
in the bytecode MEX.
Those models do not have as many variables as equations, and this case is not
supported by bytecode.
The present commit is an improvement over commit
a8ea57dd63, which had already removed bytecode
for the planner objective model.
The preprocessor would try to write bytecode for the planner objective. But
bytecode only works when there are as many endogenous as equations, which is
not the case for the PlannerObjective object derived from StaticModel.
Temporary terms computed in previous blocks were not used in the bytecode
output of a given block. This was inefficient (because this means that
expressions already computed and store in the temporary terms vector would be
recomputed), and incidentally it would break the external functions
output (because it would trigger a lookup in the “TEF terms”, which would thus
fail).
Closes: #115
The computing of the Ramsey steady state relies on the fact that Lagrange
multipliers appear linearly in the system to be solved. Instead of directly
solving for the Lagrange multipliers along with the other variables,
dyn_ramsey_static.m reduces the size of the problem by always computing the
value of the multipliers that minimizes the residuals, given the other
variables (using a minimum norm solution, easy to compute because of the
linearity property). That function thus needs the derivatives of the optimality
FOCs with respect to the multipliers. The problem is that, when multipliers
appear in an auxiliary variable related to a lead/lag, then those derivatives
need to be retrieved by a chain rule derivation, which cannot be easily done
with the regular static file.
This commit implements the creation of a new file,
ramsey_multipliers_static_g1.{m,mex}, that provides exactly the needed
derivatives w.r.t. Lagrange multipliers through chain rule derivation.
Ref. dynare#633, dynare#1119, dynare#1133
Previously, the MinGW location was appended multiple times to the PATH
variable, which in some cases would make the variable too long and thus
dysfunctional.
The variable is now initialized once when the worker threads are created.
By the way, move the macOS+Octave environment variable initializations to the
same place, for consistency.
Commit 23b0c12d8e introduced caching in chain
rule derivation (used by block decomposition), which increased speed for mfs >
0, but actually decreased it for mfs=0.
This patch introduces the pre-computation of derivatives which are known to be
zero using symbolic a priori (similarly to what is done in the non-chain rule
context). The algorithms are now identical between the two contexts (both
symbolic a priori + caching), the difference being that in the chain rule
context, the symbolic a priori and the cache are not stored within the ExprNode
class, since they depend on the list of recursive variables.
This patch brings a significant performant improvement for all values of the
“mfs” option (the improvement is greater for small values of “mfs”).
Note that DynamicModel::determineBlockDerivativesType(), it’s legitimate to
replace max_{lead,lag} by max_endo_{lead,lag}, because for exogenous
lag=lead=0, and we no longer compute derivatives w.r.t. to endogenous that do
not belong to the block (so-called “other” endogenous).
As a consequence, and as a temporary measure, always output the
non-block-decomposed legacy representation.
Also drop the block kalman filter output, and drop now useless variables in
M_.block_structure.
Such a decomposition has to be simulated with periods as the outer loop and
blocks as the inner loop.
It is enabled by default for purely backward/forward/static models, as long as
the “block” option is not given. In that case, “mfs” is also set to 3 by
default (until that value becomes the global default).
M_.time_recursive_block_decomposition is set to “true” when that decomposition
has been performed, “false” otherwise for the traditional decomposition (the
latter has to be simulated with blocks as the outer loop and periods as the
inner loop).
It is no longer used in the new implementation of solve_algo={12,14}.
However, the M_.lhs field that was created by setup_solvers.m is used from
other places, so reimplement it at the preprocessor level.
The files are created under <basename>/+debug/dynamic_resid.m and
<basename>/+debug/static_resid.m.
Their purpose is to evaluate separately the LHS and RHS of each equation.
Sébastien Villemot
Johannes Pfeifer