Lint cleanup from William Rucklidge.
Change-Id: I745810f5496a1b93263b20ff140f8883da61995e
diff --git a/internal/ceres/covariance_impl.cc b/internal/ceres/covariance_impl.cc
index 91f0393..faa0ce5 100644
--- a/internal/ceres/covariance_impl.cc
+++ b/internal/ceres/covariance_impl.cc
@@ -470,7 +470,7 @@
LOG(ERROR) << "Cholesky factorization of J'J is not reliable. "
<< "Reciprocal condition number: "
<< reciprocal_condition_number << " "
- << "min_reciprocal_condition_number : "
+ << "min_reciprocal_condition_number: "
<< options_.min_reciprocal_condition_number;
ss.Free(factor);
return false;
@@ -822,7 +822,7 @@
LOG(ERROR) << "Cholesky factorization of J'J is not reliable. "
<< "Reciprocal condition number: "
<< singular_value_ratio * singular_value_ratio << " "
- << "min_reciprocal_condition_number : "
+ << "min_reciprocal_condition_number: "
<< options_.min_reciprocal_condition_number;
return false;
}
diff --git a/internal/ceres/lapack.cc b/internal/ceres/lapack.cc
index c4f9302..90973fa 100644
--- a/internal/ceres/lapack.cc
+++ b/internal/ceres/lapack.cc
@@ -138,7 +138,7 @@
LOG(FATAL) << "Congratulations, you found a bug in Ceres."
<< "Please report it."
<< "LAPACK::dgels fatal error."
- << "Argument: " << info << " is invalid.";
+ << "Argument: " << -info << " is invalid.";
}
return static_cast<int>(work);
#endif
diff --git a/internal/ceres/solver_impl_test.cc b/internal/ceres/solver_impl_test.cc
index 30eeea2..f0f36ad 100644
--- a/internal/ceres/solver_impl_test.cc
+++ b/internal/ceres/solver_impl_test.cc
@@ -99,11 +99,12 @@
inner_iteration_ordering.AddElementToGroup(&z, 0);
Program program(*problem.mutable_program());
- EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program,
- &linear_solver_ordering,
- &inner_iteration_ordering,
- NULL,
- &error));
+ EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(
+ &program,
+ &linear_solver_ordering,
+ &inner_iteration_ordering,
+ NULL,
+ &error));
EXPECT_EQ(program.NumParameterBlocks(), 3);
EXPECT_EQ(program.NumResidualBlocks(), 3);
EXPECT_EQ(linear_solver_ordering.NumElements(), 3);
@@ -127,11 +128,12 @@
Program program(problem.program());
string error;
- EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program,
- &linear_solver_ordering,
- &inner_iteration_ordering,
- NULL,
- &error));
+ EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(
+ &program,
+ &linear_solver_ordering,
+ &inner_iteration_ordering,
+ NULL,
+ &error));
EXPECT_EQ(program.NumParameterBlocks(), 0);
EXPECT_EQ(program.NumResidualBlocks(), 0);
EXPECT_EQ(linear_solver_ordering.NumElements(), 0);
@@ -160,11 +162,12 @@
Program program(problem.program());
string error;
- EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program,
- &linear_solver_ordering,
- &inner_iteration_ordering,
- NULL,
- &error));
+ EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(
+ &program,
+ &linear_solver_ordering,
+ &inner_iteration_ordering,
+ NULL,
+ &error));
EXPECT_EQ(program.NumParameterBlocks(), 0);
EXPECT_EQ(program.NumResidualBlocks(), 0);
EXPECT_EQ(linear_solver_ordering.NumElements(), 0);
@@ -198,11 +201,12 @@
Program program(problem.program());
string error;
- EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program,
- &linear_solver_ordering,
- &inner_iteration_ordering,
- NULL,
- &error));
+ EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(
+ &program,
+ &linear_solver_ordering,
+ &inner_iteration_ordering,
+ NULL,
+ &error));
EXPECT_EQ(program.NumParameterBlocks(), 1);
EXPECT_EQ(program.NumResidualBlocks(), 1);
EXPECT_EQ(linear_solver_ordering.NumElements(), 1);
@@ -235,11 +239,12 @@
Program program(problem.program());
string error;
- EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program,
- &linear_solver_ordering,
- &inner_iteration_ordering,
- NULL,
- &error));
+ EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(
+ &program,
+ &linear_solver_ordering,
+ &inner_iteration_ordering,
+ NULL,
+ &error));
EXPECT_EQ(program.NumParameterBlocks(), 2);
EXPECT_EQ(program.NumResidualBlocks(), 2);
EXPECT_EQ(linear_solver_ordering.NumElements(), 2);
@@ -283,11 +288,12 @@
scratch.get());
string error;
- EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program,
- &linear_solver_ordering,
- NULL,
- &fixed_cost,
- &error));
+ EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(
+ &program,
+ &linear_solver_ordering,
+ NULL,
+ &fixed_cost,
+ &error));
EXPECT_EQ(program.NumParameterBlocks(), 2);
EXPECT_EQ(program.NumResidualBlocks(), 2);
EXPECT_EQ(linear_solver_ordering.NumElements(), 2);
diff --git a/internal/ceres/suitesparse.cc b/internal/ceres/suitesparse.cc
index 06cc0a8..8a52631 100644
--- a/internal/ceres/suitesparse.cc
+++ b/internal/ceres/suitesparse.cc
@@ -122,7 +122,7 @@
}
cholmod_factor* SuiteSparse::AnalyzeCholesky(cholmod_sparse* A,
- string* status) {
+ string* message) {
// Cholmod can try multiple re-ordering strategies to find a fill
// reducing ordering. Here we just tell it use AMD with automatic
// matrix dependence choice of supernodal versus simplicial
@@ -137,7 +137,7 @@
}
if (cc_.status != CHOLMOD_OK) {
- *status = StringPrintf("cholmod_analyze failed. error code: %d",
+ *message = StringPrintf("cholmod_analyze failed. error code: %d",
cc_.status);
return NULL;
}
@@ -149,18 +149,18 @@
cholmod_sparse* A,
const vector<int>& row_blocks,
const vector<int>& col_blocks,
- string* status) {
+ string* message) {
vector<int> ordering;
if (!BlockAMDOrdering(A, row_blocks, col_blocks, &ordering)) {
return NULL;
}
- return AnalyzeCholeskyWithUserOrdering(A, ordering, status);
+ return AnalyzeCholeskyWithUserOrdering(A, ordering, message);
}
cholmod_factor* SuiteSparse::AnalyzeCholeskyWithUserOrdering(
cholmod_sparse* A,
const vector<int>& ordering,
- string* status) {
+ string* message) {
CHECK_EQ(ordering.size(), A->nrow);
cc_.nmethods = 1;
@@ -172,7 +172,7 @@
cholmod_print_common(const_cast<char*>("Symbolic Analysis"), &cc_);
}
if (cc_.status != CHOLMOD_OK) {
- *status = StringPrintf("cholmod_analyze failed. error code: %d",
+ *message = StringPrintf("cholmod_analyze failed. error code: %d",
cc_.status);
return NULL;
}
@@ -182,7 +182,7 @@
cholmod_factor* SuiteSparse::AnalyzeCholeskyWithNaturalOrdering(
cholmod_sparse* A,
- string* status) {
+ string* message) {
cc_.nmethods = 1;
cc_.method[0].ordering = CHOLMOD_NATURAL;
cc_.postorder = 0;
@@ -192,7 +192,7 @@
cholmod_print_common(const_cast<char*>("Symbolic Analysis"), &cc_);
}
if (cc_.status != CHOLMOD_OK) {
- *status = StringPrintf("cholmod_analyze failed. error code: %d",
+ *message = StringPrintf("cholmod_analyze failed. error code: %d",
cc_.status);
return NULL;
}
@@ -244,7 +244,7 @@
LinearSolverTerminationType SuiteSparse::Cholesky(cholmod_sparse* A,
cholmod_factor* L,
- string* status) {
+ string* message) {
CHECK_NOTNULL(A);
CHECK_NOTNULL(L);
@@ -268,35 +268,35 @@
// (e.g. out of memory).
switch (cc_.status) {
case CHOLMOD_NOT_INSTALLED:
- *status = "CHOLMOD failure: Method not installed.";
+ *message = "CHOLMOD failure: Method not installed.";
return LINEAR_SOLVER_FATAL_ERROR;
case CHOLMOD_OUT_OF_MEMORY:
- *status = "CHOLMOD failure: Out of memory.";
+ *message = "CHOLMOD failure: Out of memory.";
return LINEAR_SOLVER_FATAL_ERROR;
case CHOLMOD_TOO_LARGE:
- *status = "CHOLMOD failure: Integer overflow occured.";
+ *message = "CHOLMOD failure: Integer overflow occured.";
return LINEAR_SOLVER_FATAL_ERROR;
case CHOLMOD_INVALID:
- *status = "CHOLMOD failure: Invalid input.";
+ *message = "CHOLMOD failure: Invalid input.";
return LINEAR_SOLVER_FATAL_ERROR;
case CHOLMOD_NOT_POSDEF:
- *status = "CHOLMOD warning: Matrix not positive definite.";
+ *message = "CHOLMOD warning: Matrix not positive definite.";
return LINEAR_SOLVER_FAILURE;
case CHOLMOD_DSMALL:
- *status = "CHOLMOD warning: D for LDL' or diag(L) or "
+ *message = "CHOLMOD warning: D for LDL' or diag(L) or "
"LL' has tiny absolute value.";
return LINEAR_SOLVER_FAILURE;
case CHOLMOD_OK:
- if (cholmod_status != 0) {
+ if (cholmod_message != 0) {
return LINEAR_SOLVER_SUCCESS;
}
- *status = "CHOLMOD failure: cholmod_factorize returned false "
+ *message = "CHOLMOD failure: cholmod_factorize returned false "
"but cholmod_common::status is CHOLMOD_OK."
"Please report this to ceres-solver@googlegroups.com.";
return LINEAR_SOLVER_FATAL_ERROR;
default:
- *status =
+ *message =
StringPrintf("Unknown cholmod return code: %d. "
"Please report this to ceres-solver@googlegroups.com.",
cc_.status);
@@ -308,9 +308,9 @@
cholmod_dense* SuiteSparse::Solve(cholmod_factor* L,
cholmod_dense* b,
- string* status) {
+ string* message) {
if (cc_.status != CHOLMOD_OK) {
- *status = "cholmod_solve failed. CHOLMOD status is not CHOLMOD_OK";
+ *message = "cholmod_solve failed. CHOLMOD status is not CHOLMOD_OK";
return NULL;
}
diff --git a/internal/ceres/suitesparse.h b/internal/ceres/suitesparse.h
index 0604654..85cceb1 100644
--- a/internal/ceres/suitesparse.h
+++ b/internal/ceres/suitesparse.h
@@ -1,4 +1,4 @@
-// Ceres Solver - A fast non-linear least squares minimizer
+s// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
// http://code.google.com/p/ceres-solver/
//
@@ -139,15 +139,15 @@
// A is not modified, only the pattern of non-zeros of A is used,
// the actual numerical values in A are of no consequence.
//
- // status contains an explanation of the failures if any.
+ // message contains an explanation of the failures if any.
//
// Caller owns the result.
- cholmod_factor* AnalyzeCholesky(cholmod_sparse* A, string* status);
+ cholmod_factor* AnalyzeCholesky(cholmod_sparse* A, string* message);
cholmod_factor* BlockAnalyzeCholesky(cholmod_sparse* A,
const vector<int>& row_blocks,
const vector<int>& col_blocks,
- string* status);
+ string* message);
// If A is symmetric, then compute the symbolic Cholesky
// factorization of A(ordering, ordering). If A is unsymmetric, then
@@ -157,38 +157,38 @@
// A is not modified, only the pattern of non-zeros of A is used,
// the actual numerical values in A are of no consequence.
//
- // status contains an explanation of the failures if any.
+ // message contains an explanation of the failures if any.
//
// Caller owns the result.
cholmod_factor* AnalyzeCholeskyWithUserOrdering(cholmod_sparse* A,
const vector<int>& ordering,
- string* status);
+ string* message);
// Perform a symbolic factorization of A without re-ordering A. No
// postordering of the elimination tree is performed. This ensures
// that the symbolic factor does not introduce an extra permutation
// on the matrix. See the documentation for CHOLMOD for more details.
//
- // status contains an explanation of the failures if any.
+ // message contains an explanation of the failures if any.
cholmod_factor* AnalyzeCholeskyWithNaturalOrdering(cholmod_sparse* A,
- string* status);
+ string* message);
// Use the symbolic factorization in L, to find the numerical
// factorization for the matrix A or AA^T. Return true if
// successful, false otherwise. L contains the numeric factorization
// on return.
//
- // status contains an explanation of the failures if any.
+ // message contains an explanation of the failures if any.
LinearSolverTerminationType Cholesky(cholmod_sparse* A,
cholmod_factor* L,
- string* status);
+ string* message);
// Given a Cholesky factorization of a matrix A = LL^T, solve the
// linear system Ax = b, and return the result. If the Solve fails
// NULL is returned. Caller owns the result.
//
- // status contains an explanation of the failures if any.
- cholmod_dense* Solve(cholmod_factor* L, cholmod_dense* b, string* solve);
+ // message contains an explanation of the failures if any.
+ cholmod_dense* Solve(cholmod_factor* L, cholmod_dense* b, string* message);
// By virtue of the modeling layer in Ceres being block oriented,
// all the matrices used by Ceres are also block oriented. When
