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&foo[0] -> foo.data()

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Use the more modern form of accessing the data array of a vector
rather than grabbing the pointer to the first element. The latter
can lead to errors if the vector is of zero length.

Change-Id: Ifc8fc969b06b3ba1a9385e8a3a8d5c50b25db5a8
This commit is contained in:
Sameer Agarwal
2022-08-25 10:00:12 +05:30
parent 344929647a
commit f802a09ff1
7 changed files with 26 additions and 25 deletions
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internal/ceres/reorder_program.cc
+8 -8
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@@ -129,7 +129,7 @@ void OrderingForSparseNormalCholeskyUsingSuiteSparse(
if (parameter_block_ordering.NumGroups() <= 1) {
// The user did not supply a useful ordering so just go ahead
// and use AMD.
ss.Ordering(block_jacobian_transpose, OrderingType::AMD, &ordering[0]);
ss.Ordering(block_jacobian_transpose, OrderingType::AMD, ordering);
} else {
// The user supplied an ordering, so use CAMD.
vector<int> constraints;
@@ -142,9 +142,9 @@ void OrderingForSparseNormalCholeskyUsingSuiteSparse(
// Renumber the entries of constraints to be contiguous integers
// as CAMD requires that the group ids be in the range [0,
// parameter_blocks.size() - 1].
MapValuesToContiguousRange(constraints.size(), &constraints[0]);
MapValuesToContiguousRange(constraints.size(), constraints.data());
ss.ConstrainedApproximateMinimumDegreeOrdering(
block_jacobian_transpose, &constraints[0], ordering);
block_jacobian_transpose, constraints.data(), ordering);
}
} else if (linear_solver_ordering_type == ceres::NESDIS) {
// If nested dissection is chosen as an ordering algorithm, then
@@ -152,7 +152,7 @@ void OrderingForSparseNormalCholeskyUsingSuiteSparse(
CHECK(SuiteSparse::IsNestedDissectionAvailable())
<< "Congratulations, you found a Ceres bug! "
<< "Please report this error to the developers.";
ss.Ordering(block_jacobian_transpose, OrderingType::NESDIS, &ordering[0]);
ss.Ordering(block_jacobian_transpose, OrderingType::NESDIS, ordering);
} else {
LOG(FATAL) << "Congratulations, you found a Ceres bug! "
<< "Please report this error to the developers.";
@@ -344,7 +344,7 @@ static void ReorderSchurComplementColumnsUsingSuiteSparse(
// Renumber the entries of constraints to be contiguous integers as
// CAMD requires that the group ids be in the range [0,
// parameter_blocks.size() - 1].
MapValuesToContiguousRange(constraints.size(), &constraints[0]);
MapValuesToContiguousRange(constraints.size(), constraints.data());
// Compute a block sparse presentation of J'.
std::unique_ptr<TripletSparseMatrix> tsm_block_jacobian_transpose(
@@ -355,7 +355,7 @@ static void ReorderSchurComplementColumnsUsingSuiteSparse(
vector<int> ordering(parameter_blocks.size(), 0);
ss.ConstrainedApproximateMinimumDegreeOrdering(
block_jacobian_transpose, &constraints[0], &ordering[0]);
block_jacobian_transpose, constraints.data(), ordering.data());
ss.Free(block_jacobian_transpose);
const vector<ParameterBlock*> parameter_blocks_copy(parameter_blocks);
@@ -551,7 +551,7 @@ bool ReorderProgramForSparseCholesky(
*tsm_block_jacobian_transpose,
parameter_blocks,
parameter_block_ordering,
&ordering[0]);
ordering.data());
} else if (sparse_linear_algebra_library_type == ACCELERATE_SPARSE) {
// Accelerate does not provide a function to perform reordering without
// performing a full symbolic factorisation. As such, we have nothing
@@ -565,7 +565,7 @@ bool ReorderProgramForSparseCholesky(
OrderingForSparseNormalCholeskyUsingEigenSparse(
linear_solver_ordering_type,
*tsm_block_jacobian_transpose,
&ordering[0]);
ordering.data());
}
// Apply ordering.