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Rename scalarNorm2 to squaredSum in Test_reduction.cc

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The function computes |sum|^2 — the squared magnitude of an aggregate sum —
not a norm. squaredSum makes clear that squaring is applied to the sum, not
to individual site values before summing, distinguishing it from sumOfSquares
(the squared L2 norm).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Peter Boyle
2026-05-15 23:15:11 -04:00
parent 003fec509c
commit 09552cfd73
1 changed files with 9 additions and 9 deletions
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tests/debug/Test_reduction.cc
+9 -9
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@@ -43,13 +43,13 @@ static void check(bool ok, const std::string &msg)
}
}
// Frobenius-like norm squared of any Grid scalar tensor object.
// For iScalar chains: real(conj(a)*a)
// For iMatrix<T,N>: sum_{i,j} real(conj(a_ij)*a_ij) (all elements)
// Both old and new paths promote to double before accumulating, so the result
// is always exact enough for the tolerances used here.
// Squared magnitude of a Grid scalar tensor aggregate: innerProduct(a,a).
// For iScalar: real(conj(a)*a)
// For iMatrix<T,N>: sum_{i,j} real(conj(a_ij)*a_ij) (Frobenius)
// Named squaredSum to make clear the squaring is applied to the aggregate
// (the sum), not to individual site values before summing.
template<class T>
RealD scalarNorm2(const T &a)
RealD squaredSum(const T &a)
{
return (RealD)real(TensorRemove(innerProduct(a, a)));
}
@@ -86,8 +86,8 @@ void testReduction(GridCartesian *grid, GridParallelRNG &rng,
sobj old_result = sum_gpu_old(&v[0], osites);
sobj diff = new_result - old_result;
RealD diffn = scalarNorm2(diff);
RealD refn = scalarNorm2(old_result);
RealD diffn = squaredSum(diff);
RealD refn = squaredSum(old_result);
RealD reldiff = (refn > 0.0) ? std::sqrt(diffn / refn) : std::sqrt(diffn);
// Float fields: both paths cast from double to float, expect O(eps_float).
@@ -118,7 +118,7 @@ void testReduction(GridCartesian *grid, GridParallelRNG &rng,
field = 1.0;
sobj sum_result = sum(field); // uses new GPU path + GlobalSum
RealD got = scalarNorm2(sum_result);
RealD got = squaredSum(sum_result);
RealD expected = (RealD)Ncomp * (RealD)V * (RealD)V;
RealD reldiff = std::abs(got - expected) / expected;