From fd5ecd00232db7647852bd67c15c5726320cba8c Mon Sep 17 00:00:00 2001
From: NanuSai <gnanasai.n18@iiits.in>
Date: Sun, 14 Mar 2021 07:53:29 +0530
Subject: [PATCH] styling fix

---
 include/ensmallen_bits/nsga2/nsga2_impl.hpp | 40 +++++++++++----------
 1 file changed, 21 insertions(+), 19 deletions(-)

diff --git a/include/ensmallen_bits/nsga2/nsga2_impl.hpp b/include/ensmallen_bits/nsga2/nsga2_impl.hpp
index 6feb4d78f..c33a4b844 100644
--- a/include/ensmallen_bits/nsga2/nsga2_impl.hpp
+++ b/include/ensmallen_bits/nsga2/nsga2_impl.hpp
@@ -189,7 +189,7 @@ typename MatType::elem_type NSGA2::Optimize(
 
   ElemType performance = std::numeric_limits<ElemType>::max();
 
-  for(const arma::Col<ElemType>& objective: populationFval)
+  for (const arma::Col<ElemType>& objective: populationFval)
     if (arma::accu(objective) < performance)
       performance = arma::accu(objective);
 
@@ -396,37 +396,39 @@ inline void NSGA2::CrowdingDistanceAssignment(
 	std::vector<double>& crowdingDistance)
 {
   size_t fSize = front.size();
-  std::vector<size_t> sortedIdx(fSize); // Stores the sorted indices of the fronts.
+  // Stores the sorted indices of the fronts.
+  std::vector<size_t> sortedIdx(fSize);
   std::iota(sortedIdx.begin(), sortedIdx.end(), 0u);
 
   for (size_t m = 0; m < numObjectives; m++)
   {
-    std::vector<double> fValues{};
-    std::transform( // Cache the Fvalues of individuals for current objective.
-            front.begin(), front.end(), std::back_inserter(fValues),
-            [&](const size_t& individual) {
-                return populationFval[individual](m);
-            });
-
-    // Sort the front indices based on ascending FValue of the current objective.
+    // Cache Fvalues of individuals for current objective.
+    arma::vec fValues(fSize);
+    std::transform(front.begin(), front.end(), fValues.begin(),
+      [&](const size_t& individual)
+        {
+          return populationFval[individual](m);
+        });
+
+    // Sort front indices by ascending FValue for current objective.
     std::sort(sortedIdx.begin(), sortedIdx.end(),
-        [&](const size_t& frontIdxA, const size_t& frontIdxB) {
-                          return (fValues[frontIdxA] <
-                                  fValues[frontIdxB]);
-                      });
+      [&](const size_t& frontIdxA, const size_t& frontIdxB)
+        {
+          return (fValues[frontIdxA] < fValues[frontIdxB]);
+        });
 
-    crowdingDistance[front[sortedIdx[0]]] = std::numeric_limits<double>::infinity();
+	  crowdingDistance[front[sortedIdx[0]]] =
+        std::numeric_limits<double>::infinity();
     crowdingDistance[front[sortedIdx[fSize - 1]]] =
-            std::numeric_limits<double>::infinity();
+        std::numeric_limits<double>::infinity();
     double minFval = *(std::min_element(fValues.begin(), fValues.end()));
     double maxFval = *(std::max_element(fValues.begin(), fValues.end()));
     double scale = (maxFval == minFval) ? 1 : maxFval - minFval;
 
     for (size_t i = 1; i < fSize - 1; i++)
     {
-				crowdingDistance[front[sortedIdx[i]]] +=
-				    (fValues[sortedIdx[i + 1]] - fValues[sortedIdx[i - 1]]) /
-				    scale;
+			crowdingDistance[front[sortedIdx[i]]] +=
+				  (fValues[sortedIdx[i + 1]] - fValues[sortedIdx[i - 1]]) / scale;
     }
     }
 }