Tidy up expectation w.r.t. marginal likelihood

Author: tveasey

include/maths/CPriorDetail.h

@@ -22,21 +22,6 @@ namespace ml
 namespace maths
 {
 
-//! Compute the expectation of the specified function w.r.t. to the marginal
-//! likelihood.
-//!
-//! This computes the expectation using order three Gauss-Legendre quadrature
-//! in \p numberIntervals subdivisions of a high confidence interval for the
-//! marginal likelihood.
-//!
-//! \param f The function to integrate.
-//! \param numberIntervals The number intervals to use for integration.
-//! \param result Filled in with the result if the expectation could be calculated.
-//!
-//! \tparam F This must conform to the function type expected by
-//! CIntegration::gaussLegendre.
-//! \tparam T The return type of the function F which must conform to the type
-//! expected by CIntegration::gaussLegendre.
 template<typename F, typename T>
 bool CPrior::expectation(const F &f,
                          std::size_t numberIntervals,
@@ -52,16 +37,16 @@ bool CPrior::expectation(const F &f,
 
     result = T();
 
-    double n = static_cast<double>(numberIntervals);
-    TDoubleDoublePr interval =
+    double n{static_cast<double>(numberIntervals)};
+    TDoubleDoublePr interval{
             this->marginalLikelihoodConfidenceInterval(100.0 - 1.0 / (100.0 * n),
                                                        weightStyles,
-                                                       weight);
-    double x = interval.first;
-    double dx = (interval.second - interval.first) / n;
+                                                       weight)};
+    double x{interval.first};
+    double dx{(interval.second - interval.first) / n};
 
-    double normalizationFactor = 0.0;
-    TDouble4Vec1Vec weights(1, weight);
+    double normalizationFactor{0.0};
+    TDouble4Vec1Vec weights{weight};
     CPrior::CLogMarginalLikelihood logLikelihood(*this, weightStyles, weights);
     CCompositeFunctions::CExp<const CPrior::CLogMarginalLikelihood&> likelihood(logLikelihood);
     for (std::size_t i = 0u; i < numberIntervals; ++i, x += dx)