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use reasonable distribution name

release/4.3a0
acxz 2020-07-23 14:54:21 -04:00
parent d5d58fd707
commit 5eb2bea357
1 changed files with 5 additions and 5 deletions
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10
timing/timeFactorOverhead.cpp
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@ -29,7 +29,7 @@ using namespace gtsam;
using namespace std; using namespace std;
static std::mt19937 rng; static std::mt19937 rng;
static std::uniform_real_distribution<> rg(0.0, 1.0); static std::uniform_real_distribution<> uniform(0.0, 1.0);
int main(int argc, char *argv[]) { int main(int argc, char *argv[]) {
@ -65,10 +65,10 @@ int main(int argc, char *argv[]) {
Matrix A(blockdim, vardim); Matrix A(blockdim, vardim);
for(size_t j=0; j<blockdim; ++j) for(size_t j=0; j<blockdim; ++j)
for(size_t k=0; k<vardim; ++k) for(size_t k=0; k<vardim; ++k)
A(j,k) = rg(rng); A(j,k) = uniform(rng);
Vector b(blockdim); Vector b(blockdim);
for(size_t j=0; j<blockdim; ++j) for(size_t j=0; j<blockdim; ++j)
b(j) = rg(rng); b(j) = uniform(rng);
blockGfgs[trial].push_back(boost::make_shared<JacobianFactor>(key, A, b, noise)); blockGfgs[trial].push_back(boost::make_shared<JacobianFactor>(key, A, b, noise));
} }
} }
@ -112,10 +112,10 @@ int main(int argc, char *argv[]) {
// Generate a random Gaussian factor // Generate a random Gaussian factor
for(size_t j=0; j<blockdim; ++j) for(size_t j=0; j<blockdim; ++j)
for(size_t k=0; k<vardim; ++k) for(size_t k=0; k<vardim; ++k)
Acomb(blockdim*i+j, k) = rg(rng); Acomb(blockdim*i+j, k) = uniform(rng);
Vector b(blockdim); Vector b(blockdim);
for(size_t j=0; j<blockdim; ++j) for(size_t j=0; j<blockdim; ++j)
bcomb(blockdim*i+j) = rg(rng); bcomb(blockdim*i+j) = uniform(rng);
} }
combGfgs[trial].push_back(boost::make_shared<JacobianFactor>(key, Acomb, bcomb, combGfgs[trial].push_back(boost::make_shared<JacobianFactor>(key, Acomb, bcomb,
noiseModel::Isotropic::Sigma(blockdim*nBlocks, 1.0))); noiseModel::Isotropic::Sigma(blockdim*nBlocks, 1.0)));