Add the function 'create_result' and example

examples/Makefile.am

@@ -3,12 +3,14 @@ AM_CPPFLAGS = -I$(top_srcdir)/include
 AM_DEFAULT_SOURCE_EXT = .cpp
 
 noinst_PROGRAMS = \
+	helper_example \
 	read_linear_grid \
 	mpi_vegas_example \
 	vegas_example \
 	vegas_grid
 
 # redundant for automake >= 1.11
+helper_example_SOURCES = helper_example.cpp
 read_linear_grid_SOURCES = read_linear_grid.cpp
 mpi_vegas_example_SOURCES = mpi_vegas_example.cpp
 vegas_example_SOURCES = vegas_example.cpp

examples/helper_example.cpp

@@ -0,0 +1,28 @@
+#include <hep/mc.hpp>
+
+int main()
+{
+	// vector containing the results of five iterations
+	std::vector<hep::mc_result<double>> results = {
+		// create mc_results with the tuples (calls, estimate, error)
+		hep::create_result(100000, 0.987449, 0.0165879),
+		hep::create_result(100000, 0.988517, 0.00929261),
+		hep::create_result(100000, 0.999915, 0.00825228),
+		hep::create_result(100000, 1.0012,   0.0120161),
+		hep::create_result(100000, 1.01968,  0.00926521)
+	};
+
+	for (std::size_t i = 0; i != results.size(); ++i)
+	{
+		// combine results from iterations [0, i]
+		auto result = hep::cumulative_result<double>(results.begin(),
+			results.begin()+(i+1));
+		auto chi_square_dof = hep::chi_square_dof<double>(results.begin(),
+			results.begin()+(i+1));
+
+		std::cout << i << ": E=" << result.value << " +- " << result.error;
+		std::cout << " chi^2/dof=" << chi_square_dof << "\n";
+	}
+
+	return 0;
+}

include/hep/mc/mc_result.hpp

@@ -59,6 +59,18 @@ struct mc_result
 	T error;
 };
 
+/**
+ * Creates a \ref mc_result using the parameters `calls` `value` and `error`.
+ */
+template <typename T>
+mc_result<T> create_result(std::size_t calls, T value, T error)
+{
+	T sum = T(calls) * value;
+	T sum_of_squares = T(calls) * (value * value + T(calls) * error * error);
+
+	return mc_result<T>(calls, sum, sum_of_squares);
+}
+
 }
 
 #endif