stepan
/
preprocessor
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Simplification in BinaryOpNode::fillAutoregressiveRow 

By the way, fix bug in detection of duplicate elements.
issue#70
Sébastien Villemot 2019-03-19 17:03:26 +01:00 committed by Stéphane Adjemian (Charybdis)
parent 5497936e87
commit 4114b8a9e1
Signed by untrusted user who does not match committer: stepan
GPG Key ID: A6D44CB9C64CE77B
1 changed files with 31 additions and 45 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

76
src/ExprNode.cc
View File

@ -5844,53 +5844,39 @@ BinaryOpNode::fillAutoregressiveRow(int eqn, const vector<int> &lhs, map<tuple<i
decomposeAdditiveTerms(terms, 1);
for (const auto & it : terms)
{
auto bopn = dynamic_cast<BinaryOpNode *>(it.first);
if (bopn != nullptr)
int vid, lag, param_id;
double constant;
try
{
auto vn1 = dynamic_cast<VariableNode *>(bopn->arg1);
auto vn2 = dynamic_cast<VariableNode *>(bopn->arg2);
if (vn1 && vn2)
{
int vid, lag;
VariableNode *param;
vid = -1;
if (datatree.symbol_table.getType(vn1->symb_id) == SymbolType::parameter
&& (datatree.symbol_table.getType(vn2->symb_id) == SymbolType::endogenous
|| datatree.symbol_table.getType(vn2->symb_id) == SymbolType::exogenous))
{
param = vn1;
vid = vn2->symb_id;
lag = vn2->lag;
}
else if (datatree.symbol_table.getType(vn2->symb_id) == SymbolType::parameter
&& (datatree.symbol_table.getType(vn1->symb_id) == SymbolType::endogenous
|| datatree.symbol_table.getType(vn1->symb_id) == SymbolType::exogenous))
{
param = vn2;
vid = vn1->symb_id;
lag = vn1->lag;
}
if (vid >= 0)
{
if (datatree.symbol_table.isDiffAuxiliaryVariable(vid))
{
lag = -datatree.symbol_table.getOrigLeadLagForDiffAuxVar(vid);
vid = datatree.symbol_table.getOrigSymbIdForDiffAuxVar(vid);
}
if (find(lhs.begin(), lhs.end(), vid) == lhs.end())
continue;
if (AR.find({eqn, lag, vid}) != AR.end())
{
cerr << "BinaryOpNode::fillAutoregressiveRow: Error filling AR matrix: "
<< "lag/symb_id encountered more than once in equtaion" << endl;
exit(EXIT_FAILURE);
}
AR[{eqn, -lag, vid}] = param;
}
}
tie(vid, lag, param_id, constant) = it.first->matchVariableTimesConstantTimesParam();
constant *= it.second;
}
catch (MatchFailureException &e)
{
continue;
}
if (datatree.symbol_table.isDiffAuxiliaryVariable(vid))
{
lag = -datatree.symbol_table.getOrigLeadLagForDiffAuxVar(vid);
vid = datatree.symbol_table.getOrigSymbIdForDiffAuxVar(vid);
}
if (find(lhs.begin(), lhs.end(), vid) == lhs.end())
continue;
if (AR.find({eqn, -lag, vid}) != AR.end())
{
cerr << "BinaryOpNode::fillAutoregressiveRow: Error filling AR matrix: "
<< "lag/symb_id encountered more than once in equation" << endl;
exit(EXIT_FAILURE);
}
if (constant != 1 || param_id == -1)
{
cerr << "BinaryOpNode::fillAutoregressiveRow: autoregressive terms must be of the form 'parameter*lagged_variable" << endl;
exit(EXIT_FAILURE);
}
AR[{eqn, -lag, vid}] = datatree.AddVariable(param_id);
}
}