Commit 256d9596 authored by Florian Goth's avatar Florian Goth
Browse files

-Add an averaged MatsubaraGreensfunction.

-spacing
parent be8ee609
......@@ -118,6 +118,7 @@ static const ObservableProperties propertycache[] =
{"SmoothImaginaryGreensfunction", false, VECTORFUNCTION, false, false},
{"SmoothImaginaryGreensfunction_averaged", false, VECTORFUNCTION, false, false},
{"MatsubaraFrequencyGreensfunction", true, VECTORFUNCTION, false, false},
{"MatsubaraFrequencyGreensfunction_averaged", true, VECTORFUNCTION, false, false},
{"MatsubaraFrequencyGreensfunctionDerivative", true, VECTORFUNCTION, false, false},
{"SpinSpinCorrelatedPart_Y", false, VECTORFUNCTION, false, false},
{"SpinSpinCorrelatedPart_X", false, VECTORFUNCTION, false, false},
......
......@@ -121,7 +121,6 @@ public:
CovType cov;
};
template <typename R> class errordata_signed
{
private:
......
......@@ -124,6 +124,7 @@ Cont the Container that is used for the Storage of the data
@param data an array of Containers with the stored samples
@param numcont the number of arrays pointed to by data
*/
template <typename Func, typename Cont>
errordata<typename Func::res_t > vecjackknife(Func func, const Cont& data, unsigned int numcont, bool covariance)
{
......@@ -141,7 +142,6 @@ errordata<typename Func::res_t > vecjackknife(Func func, const Cont& data, unsig
x_J = norm *(ElementType(data.size()) * mean - data[k]);
jackbin[k] = func(x_J);
}
//calculate the jackknife average of the jackknife samples
RetType jackmean = expectationvalue(jackbin, data.size());
RetType fun_mean = func(mean);
......
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