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Do not print non optimizing behaviour field in PAC if empty.

issue#70
Stéphane Adjemian(Charybdis) 2018-08-14 16:45:01 +02:00
parent ac850f5187
commit adbeb49b29
1 changed files with 42 additions and 39 deletions
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81
src/ExprNode.cc
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@ -8430,47 +8430,50 @@ PacExpectationNode::writeOutput(ostream &output, ExprNodeOutputType output_type,
output << " ";
output << it->second.second;
}
output << "];" << endl
<< "M_.pac." << model_name << ".non_optim.params = [";
for (auto it = params_vars_and_scaling_factor.begin();
it != params_vars_and_scaling_factor.end(); it++)
output << "];" << endl;
if (!params_vars_and_scaling_factor.empty())
{
if (it != params_vars_and_scaling_factor.begin())
output << " ";
if (it->first >= 0)
output << datatree.symbol_table.getTypeSpecificID(it->first) + 1;
else
output << "NaN";
output << "M_.pac." << model_name << ".non_optimizing_behaviour.params = [";
for (auto it = params_vars_and_scaling_factor.begin();
it != params_vars_and_scaling_factor.end(); it++)
{
if (it != params_vars_and_scaling_factor.begin())
output << " ";
if (it->first >= 0)
output << datatree.symbol_table.getTypeSpecificID(it->first) + 1;
else
output << "NaN";
}
output << "];"
<< "M_.pac." << model_name << ".non_optimizing_behaviour.vars = [";
for (auto it = params_vars_and_scaling_factor.begin();
it != params_vars_and_scaling_factor.end(); it++)
{
if (it != params_vars_and_scaling_factor.begin())
output << " ";
output << datatree.symbol_table.getTypeSpecificID(it->second.first.first) + 1;
}
output << "];" << endl
<< "M_.pac." << model_name << ".non_optimizing_behaviour.lags = [";
for (auto it = params_vars_and_scaling_factor.begin();
it != params_vars_and_scaling_factor.end(); it++)
{
if (it != params_vars_and_scaling_factor.begin())
output << " ";
output << it->second.first.second;
}
output << "];" << endl
<< "M_.pac." << model_name << ".non_optimizing_behaviour.scaling_factor = [";
for (auto it = params_vars_and_scaling_factor.begin();
it != params_vars_and_scaling_factor.end(); it++)
{
if (it != params_vars_and_scaling_factor.begin())
output << " ";
output << it->second.second;
}
output << "];" << endl;
}
output << "];" << endl
<< "M_.pac." << model_name << ".non_optim.vars = [";
for (auto it = params_vars_and_scaling_factor.begin();
it != params_vars_and_scaling_factor.end(); it++)
{
if (it != params_vars_and_scaling_factor.begin())
output << " ";
output << datatree.symbol_table.getTypeSpecificID(it->second.first.first) + 1;
}
output << "];" << endl
<< "M_.pac." << model_name << ".non_optim.lags = [";
for (auto it = params_vars_and_scaling_factor.begin();
it != params_vars_and_scaling_factor.end(); it++)
{
if (it != params_vars_and_scaling_factor.begin())
output << " ";
output << it->second.first.second;
}
output << "];" << endl
<< "M_.pac." << model_name << ".non_optim.scaling_factor = [";
for (auto it = params_vars_and_scaling_factor.begin();
it != params_vars_and_scaling_factor.end(); it++)
{
if (it != params_vars_and_scaling_factor.begin())
output << " ";
output << it->second.second;
}
output << "];" << endl
<< "M_.pac." << model_name << ".h0_param_indices = [";
output << "M_.pac." << model_name << ".h0_param_indices = [";
for (auto it = h0_indices.begin();
it != h0_indices.end(); it++)
{