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Hadrons: scalar SU(N) result handling improvement

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This commit is contained in:
Antonin Portelli
2018-04-26 17:32:37 +01:00
parent cc6eb51e3e
commit d47484717e
9 changed files with 156 additions and 124 deletions
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42
extras/Hadrons/Modules/MScalarSUN/TransProj.hpp
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@ -49,19 +49,20 @@ public:
std::string, output);
};
class TransProjResult: Serializable
{
public:
GRID_SERIALIZABLE_CLASS_MEMBERS(TransProjResult,
std::vector<std::vector<Complex>>, value,
DiffType, type);
};
template <typename SImpl>
class TTransProj: public Module<TransProjPar>
{
public:
typedef typename SImpl::Field Field;
typedef typename SImpl::ComplexField ComplexField;
class Result: Serializable
{
public:
GRID_SERIALIZABLE_CLASS_MEMBERS(Result,
std::string, op,
Complex , value);
};
public:
// constructor
TTransProj(const std::string name);
@ -137,21 +138,27 @@ void TTransProj<SImpl>::execute(void)
<< par().type << " derivatives and op= '" << par().op
<< "'" << std::endl;
std::vector<Result> result;
auto &op = envGet(ComplexField, par().op);
const unsigned int nd = env().getNd();
TransProjResult result;
auto &op = envGet(ComplexField, par().op);
envGetTmp(ComplexField, buf1);
envGetTmp(ComplexField, buf2);
envGetTmp(ComplexField, lap);
lap = zero;
for (unsigned int mu = 0; mu < env().getNd(); ++mu)
if (!par().output.empty())
{
result.type = par().type;
result.value.resize(nd, std::vector<Complex>(nd));
}
for (unsigned int mu = 0; mu < nd; ++mu)
{
dmu(buf1, op, mu, par().type);
dmu(buf2, buf1, mu, par().type);
lap += buf2;
}
for (unsigned int mu = 0; mu < env().getNd(); ++mu)
for (unsigned int nu = mu; nu < env().getNd(); ++nu)
for (unsigned int mu = 0; mu < nd; ++mu)
for (unsigned int nu = mu; nu < nd; ++nu)
{
auto &out = envGet(ComplexField, varName(getName(), mu, nu));
dmu(buf1, op, mu, par().type);
@ -163,16 +170,11 @@ void TTransProj<SImpl>::execute(void)
}
if (!par().output.empty())
{
Result r;
r.op = "(delta_" + std::to_string(mu) + "," + std::to_string(nu)
+ " d^2 - d_" + std::to_string(mu) + "*d_"
+ std::to_string(nu) + ")*op";
r.value = TensorRemove(sum(out));
result.push_back(r);
result.value[mu][nu] = TensorRemove(sum(out));
result.value[mu][nu] = result.value[nu][mu];
}
}
if (result.size() > 0)
if (!par().output.empty())
{
saveResult(par().output, "transproj", result);
}