diff --git a/CMakeLists.txt b/CMakeLists.txt
index 9f5742909..7f85582c6 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -2,7 +2,7 @@ cmake_minimum_required(VERSION 3.25) # Needed for CUDA, MPI, and CTest features
 
 project(
   EXP
-  VERSION "7.8.3"
+  VERSION "7.8.4"
   HOMEPAGE_URL https://github.com/EXP-code/EXP
   LANGUAGES C CXX Fortran)
 
diff --git a/expui/Coefficients.cc b/expui/Coefficients.cc
index c5dbb49cc..52d8f69e7 100644
--- a/expui/Coefficients.cc
+++ b/expui/Coefficients.cc
@@ -131,7 +131,7 @@ namespace CoefClasses
 	in2.transposeInPlace();
     
 	for (size_t c=0, n=0; c<in.cols(); c++) {
-	  for (size_t r=0, n=0; r<in.rows(); r++) {
+	  for (size_t r=0; r<in.rows(); r++) {
 	    in(r, c) = in2.data()[n++];
 	  }
 	}
diff --git a/exputil/OrthoFunction.cc b/exputil/OrthoFunction.cc
index e0bf4f1f9..d7812a794 100644
--- a/exputil/OrthoFunction.cc
+++ b/exputil/OrthoFunction.cc
@@ -54,6 +54,7 @@ double OrthoFunction::scalar_prod(int n, int m)
   return ans;
 }
 
+// Compute the unnormalized polynomial
 Eigen::VectorXd OrthoFunction::poly_eval(double t, int n)
 {
   Eigen::VectorXd ret(n+1);
@@ -68,6 +69,8 @@ Eigen::VectorXd OrthoFunction::poly_eval(double t, int n)
   return ret;
 }
 
+// Compute the orthogonality matrix.  A perfect result is the unit
+// matrix.
 Eigen::MatrixXd OrthoFunction::testOrtho()
 {
   Eigen::MatrixXd ret(nmax+1, nmax+1);
@@ -80,10 +83,10 @@ Eigen::MatrixXd OrthoFunction::testOrtho()
     double f = dx*lq->weight(i)*d_r_to_x(x)*pow(r, dof-1);
     double y = 2.0*r/scale; if (segment) y = x;
 
-    // Evaluate polynomial
+    // Evaluate the unnormalized polynomial
     Eigen::VectorXd p = poly_eval(y, nmax) * W(r);
 
-    // Compute scalar products
+    // Compute scalar products with the normalizations
     for (int n1=0; n1<=nmax; n1++) {
       for (int n2=0; n2<=nmax; n2++) {
 	ret(n1, n2) += f * p(n1) * p(n2) / sqrt(norm[n1]*norm[n2]);
@@ -110,11 +113,11 @@ void OrthoFunction::dumpOrtho(const std::string& filename)
       double r = x_to_r(x);
       double y = 2.0*r/scale; if (segment) y = x;
 
-      // Evaluate polynomial
+      // Evaluate polynomial and apply the normalization
       //
       Eigen::VectorXd p = poly_eval(y, nmax) * W(r);
       fout << std::setw(16) << r;
-      for (int n=0; n<nmax; n++) fout << std::setw(16) << p(n);
+      for (int n=0; n<nmax; n++) fout << std::setw(16) << p(n)/sqrt(norm[n]);
       fout << std::endl;
     }
   }
@@ -132,9 +135,11 @@ Eigen::VectorXd OrthoFunction::operator()(double r)
   double y = 2.0*r/scale;
   if (segment) y = r_to_x(r);
 
-  // Generate normalized orthogonal functions
+  // Generate normalized orthogonal functions with weighting
   auto p = poly_eval(y, nmax);
   for (int i=0; i<=nmax; i++) p(i) *= w/sqrt(norm[i]);
 
+  // The inner product of p(i), p(j) is Kronecker delta(i, j)
+
   return p;
 }