some fixes.

common/filevector.h

@@ -1155,7 +1155,7 @@ private:
     std::string filename;///< the bins are stored under this filename
     uint32_t len;///< this is the length of a single valarray
     uint32_t functions;///< this is the number of functions that a single function makes up
-    uint32_t binsize;///< the length of a bin bytes
+    uint32_t binsize;///< the length of a bin in bytes
     static const size_type offs = 2*sizeof(uint32_t);///< where starts the beginning of the file
     FileVector_Private::Lock* lock;
     off64_t curpos;///<< here we store the current position. That way we get sometmes rid of an expensive sync that is incurred by fseek

common/jackknife.h

@@ -34,11 +34,11 @@ this function calculates the expectation value of the samples stored in the cont
 @param len the length of the array
 @return the average value of the stored samples
 */
-template<typename T>
-T expectationvalue(const T *const cont, unsigned int len)
+template<typename T, typename IntType>
+T expectationvalue(const T *const cont, IntType len)
 {
     T retval(cont[0]);
-    for (unsigned int k = 1; k < len; ++k)
+    for (IntType k = 1; k < len; ++k)
         retval += cont[k];
     return retval/static_cast<typename ToScalar<T>::RetType>(len);
 }
@@ -129,7 +129,7 @@ errordata<typename Func::res_t > vecjackknife(Func func, const Cont& data, unsig
 {
     typedef typename Cont::value_type::value_type ElementType;
     typedef typename Func::res_t RetType;
-    unsigned int len = data[0].size();//we assume all datasets have the same length. this is the number of functions not the number of bins!!!
+    auto len = data[0].size();//we assume all datasets have the same length. this is the number of functions not the number of bins!!!
     auto mean = mc_analysis::mean(data);
     //mean now contains the averages of each dataset
     auto x_J = mean;
@@ -163,6 +163,7 @@ errordata<typename Func::res_t > vecjackknife(Func func, const Cont& data, unsig
     double start = omp_get_wtime();
 #endif
     std::valarray<typename ToScalar<RetType>::RetType> cov(numcont*numcont);
+#pragma omp parallel for schedule(dynamic)
     for(uint y = 0; y < numcont; ++y)
     {
       for(uint x = 0; x < numcont; ++x)
@@ -175,7 +176,7 @@ errordata<typename Func::res_t > vecjackknife(Func func, const Cont& data, unsig
       }
     }
 #ifdef _OPENMP
-    std::cout<<"calculation took "<<omp_get_wtime() - start<<" s."<<std::endl;
+    std::cout<<"calculation of covariance took "<<omp_get_wtime() - start<<" s."<<std::endl;
 #endif
     retval.setCov(cov);
     }