fix formatting for (non-generated) internal source files
- Change formatting standard to Cpp11. Main difference is not having
the space between two closing >> for nested templates. We don't
choose c++14, because older versions of clang-format (version 9
and earlier) don't know this value yet, and it doesn't make a
difference in the formatting.
- Apply clang-format to all (non generated) internal source files.
- Manually fix some code sections (clang-format on/off) and c-strings
- Exclude some embedded external files with very different formatting
(gtest/gmock)
- Add script to format all source files
Change-Id: Ic6cea41575ad6e37c9e136dbce176b0d505dc44d
diff --git a/internal/ceres/trust_region_minimizer_test.cc b/internal/ceres/trust_region_minimizer_test.cc
index 952f878..8993273 100644
--- a/internal/ceres/trust_region_minimizer_test.cc
+++ b/internal/ceres/trust_region_minimizer_test.cc
@@ -33,7 +33,10 @@
// implementation, rather than having a test that goes through all the
// Program and Problem machinery.
+#include "ceres/trust_region_minimizer.h"
+
#include <cmath>
+
#include "ceres/autodiff_cost_function.h"
#include "ceres/cost_function.h"
#include "ceres/dense_qr_solver.h"
@@ -43,7 +46,6 @@
#include "ceres/linear_solver.h"
#include "ceres/minimizer.h"
#include "ceres/problem.h"
-#include "ceres/trust_region_minimizer.h"
#include "ceres/trust_region_strategy.h"
#include "gtest/gtest.h"
@@ -59,6 +61,7 @@
template <bool col1, bool col2, bool col3, bool col4>
class PowellEvaluator2 : public Evaluator {
public:
+ // clang-format off
PowellEvaluator2()
: num_active_cols_(
(col1 ? 1 : 0) +
@@ -71,6 +74,7 @@
<< col3 << " "
<< col4;
}
+ // clang-format on
virtual ~PowellEvaluator2() {}
@@ -111,7 +115,7 @@
<< "f3=" << f3 << ", "
<< "f4=" << f4 << ".";
- *cost = (f1*f1 + f2*f2 + f3*f3 + f4*f4) / 2.0;
+ *cost = (f1 * f1 + f2 * f2 + f3 * f3 + f4 * f4) / 2.0;
VLOG(1) << "Cost: " << *cost;
@@ -132,34 +136,42 @@
int column_index = 0;
if (col1) {
+ // clang-format off
jacobian_matrix.col(column_index++) <<
1.0,
0.0,
0.0,
sqrt(10.0) * 2.0 * (x1 - x4) * (1.0 - x4);
+ // clang-format on
}
if (col2) {
+ // clang-format off
jacobian_matrix.col(column_index++) <<
10.0,
0.0,
2.0*(x2 - 2.0*x3)*(1.0 - 2.0*x3),
0.0;
+ // clang-format on
}
if (col3) {
+ // clang-format off
jacobian_matrix.col(column_index++) <<
0.0,
sqrt(5.0),
2.0*(x2 - 2.0*x3)*(x2 - 2.0),
0.0;
+ // clang-format on
}
if (col4) {
+ // clang-format off
jacobian_matrix.col(column_index++) <<
0.0,
-sqrt(5.0),
0.0,
sqrt(10.0) * 2.0 * (x1 - x4) * (x1 - 1.0);
+ // clang-format on
}
VLOG(1) << "\n" << jacobian_matrix;
}
@@ -167,7 +179,7 @@
if (gradient != NULL) {
int column_index = 0;
if (col1) {
- gradient[column_index++] = f1 + f4 * sqrt(10.0) * 2.0 * (x1 - x4);
+ gradient[column_index++] = f1 + f4 * sqrt(10.0) * 2.0 * (x1 - x4);
}
if (col2) {
@@ -192,16 +204,16 @@
const double* delta,
double* state_plus_delta) const final {
int delta_index = 0;
- state_plus_delta[0] = (col1 ? state[0] + delta[delta_index++] : state[0]);
- state_plus_delta[1] = (col2 ? state[1] + delta[delta_index++] : state[1]);
- state_plus_delta[2] = (col3 ? state[2] + delta[delta_index++] : state[2]);
- state_plus_delta[3] = (col4 ? state[3] + delta[delta_index++] : state[3]);
+ state_plus_delta[0] = (col1 ? state[0] + delta[delta_index++] : state[0]);
+ state_plus_delta[1] = (col2 ? state[1] + delta[delta_index++] : state[1]);
+ state_plus_delta[2] = (col3 ? state[2] + delta[delta_index++] : state[2]);
+ state_plus_delta[3] = (col4 ? state[3] + delta[delta_index++] : state[3]);
return true;
}
int NumEffectiveParameters() const final { return num_active_cols_; }
- int NumParameters() const final { return 4; }
- int NumResiduals() const final { return 4; }
+ int NumParameters() const final { return 4; }
+ int NumResiduals() const final { return 4; }
private:
const int num_active_cols_;
@@ -209,13 +221,13 @@
// Templated function to hold a subset of the columns fixed and check
// if the solver converges to the optimal values or not.
-template<bool col1, bool col2, bool col3, bool col4>
+template <bool col1, bool col2, bool col3, bool col4>
void IsTrustRegionSolveSuccessful(TrustRegionStrategyType strategy_type) {
Solver::Options solver_options;
LinearSolver::Options linear_solver_options;
DenseQRSolver linear_solver(linear_solver_options);
- double parameters[4] = { 3, -1, 0, 1.0 };
+ double parameters[4] = {3, -1, 0, 1.0};
// If the column is inactive, then set its value to the optimal
// value.
@@ -263,6 +275,7 @@
// IsSolveSuccessful<true, true, false, true>();
const TrustRegionStrategyType kStrategy = LEVENBERG_MARQUARDT;
+ // clang-format off
IsTrustRegionSolveSuccessful<true, true, true, true >(kStrategy);
IsTrustRegionSolveSuccessful<true, true, true, false>(kStrategy);
IsTrustRegionSolveSuccessful<true, false, true, true >(kStrategy);
@@ -277,6 +290,7 @@
IsTrustRegionSolveSuccessful<false, true, false, false>(kStrategy);
IsTrustRegionSolveSuccessful<false, false, true, false>(kStrategy);
IsTrustRegionSolveSuccessful<false, false, false, true >(kStrategy);
+ // clang-format on
}
TEST(TrustRegionMinimizer, PowellsSingularFunctionUsingDogleg) {
@@ -287,6 +301,7 @@
// IsTrustRegionSolveSuccessful<true, true, true, true >(kStrategy);
const TrustRegionStrategyType kStrategy = DOGLEG;
+ // clang-format off
IsTrustRegionSolveSuccessful<true, true, true, false>(kStrategy);
IsTrustRegionSolveSuccessful<true, false, true, true >(kStrategy);
IsTrustRegionSolveSuccessful<false, true, true, true >(kStrategy);
@@ -300,9 +315,9 @@
IsTrustRegionSolveSuccessful<false, true, false, false>(kStrategy);
IsTrustRegionSolveSuccessful<false, false, true, false>(kStrategy);
IsTrustRegionSolveSuccessful<false, false, false, true >(kStrategy);
+ // clang-format on
}
-
class CurveCostFunction : public CostFunction {
public:
CurveCostFunction(int num_vertices, double target_length)
@@ -352,11 +367,11 @@
for (int dim = 0; dim < 2; dim++) {
jacobians[i][dim] = 0.;
- if (norm_u > std::numeric_limits< double >::min()) {
+ if (norm_u > std::numeric_limits<double>::min()) {
jacobians[i][dim] -= u[dim] / norm_u;
}
- if (norm_v > std::numeric_limits< double >::min()) {
+ if (norm_v > std::numeric_limits<double>::min()) {
jacobians[i][dim] += v[dim] / norm_v;
}
}
@@ -367,8 +382,8 @@
}
private:
- int num_vertices_;
- double target_length_;
+ int num_vertices_;
+ double target_length_;
};
TEST(TrustRegionMinimizer, JacobiScalingTest) {
@@ -376,7 +391,7 @@
std::vector<double*> y(N);
const double pi = 3.1415926535897932384626433;
for (int i = 0; i < N; i++) {
- double theta = i * 2. * pi/ static_cast< double >(N);
+ double theta = i * 2. * pi / static_cast<double>(N);
y[i] = new double[2];
y[i][0] = cos(theta);
y[i][1] = sin(theta);
@@ -391,7 +406,7 @@
EXPECT_LE(summary.final_cost, 1e-10);
for (int i = 0; i < N; i++) {
- delete []y[i];
+ delete[] y[i];
}
}
@@ -403,8 +418,7 @@
}
static CostFunction* Create() {
- return new AutoDiffCostFunction<ExpCostFunctor, 1, 1>(
- new ExpCostFunctor);
+ return new AutoDiffCostFunction<ExpCostFunctor, 1, 1>(new ExpCostFunctor);
}
};
