12345qiupeng
/
gtsam
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

fix broken unit test and Matrix.cpp

release/4.3a0
Viorela Ila 2010-07-07 23:17:01 +00:00
parent f456f3d014
commit e9a2158f5b
2 changed files with 6 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
cpp/Matrix.cpp
View File

@ -678,8 +678,8 @@ void householder(Matrix &A, size_t k) {
#ifdef GT_USE_LAPACK #ifdef GT_USE_LAPACK
#ifdef YA_BLAS #ifdef YA_BLAS
void householder(Matrix &A) { void householder(Matrix &A) {
int m = A.size1(); __CLPK_integer m = A.size1();
int n = A.size2(); __CLPK_integer n = A.size2();
// convert from row major to column major // convert from row major to column major
double a[m*n]; int k = 0; double a[m*n]; int k = 0;
@ -689,8 +689,8 @@ void householder(Matrix &A) {
double tau[n]; double tau[n];
double work_optimal_size; double work_optimal_size;
int lwork = -1; __CLPK_integer lwork = -1;
int info; __CLPK_integer info;
dgeqrf_(&m, &n, a, &m, tau, &work_optimal_size, &lwork, &info); dgeqrf_(&m, &n, a, &m, tau, &work_optimal_size, &lwork, &info);
lwork = (int)work_optimal_size; lwork = (int)work_optimal_size;
@ -701,7 +701,7 @@ void householder(Matrix &A) {
memset(A.data().begin(), 0, m*n*sizeof(double)); memset(A.data().begin(), 0, m*n*sizeof(double));
for(int j=0; j<n; j++, k0+=m) { for(int j=0; j<n; j++, k0+=m) {
k = k0; k = k0;
j0 = min(j+1,m); j0 = j+1>m?j+1:m;
for(int i=0; i<j0; i++, k++) for(int i=0; i<j0; i++, k++)
A(i,j) = a[k]; A(i,j) = a[k];
} }

2
cpp/testGaussianFactor.cpp
View File

@ -768,7 +768,7 @@ TEST ( GaussianFactor, exploding_MAST_factor ) {
// Works properly with the newer elimination code // Works properly with the newer elimination code
// This is only a test of execution without crashing // This is only a test of execution without crashing
Symbol lA2('l', 18295873486192642); Symbol lA2('l', 182958734);
Matrix A1 = eye(2); Matrix A1 = eye(2);
Vector b1 = zero(2); Vector b1 = zero(2);
SharedDiagonal model1 = noiseModel::Isotropic::Sigma(2, 1.0/sqrt(2.0)); SharedDiagonal model1 = noiseModel::Isotropic::Sigma(2, 1.0/sqrt(2.0));