diff --git a/gtsam/linear/linear.i b/gtsam/linear/linear.i index 63047bf4f..f687acdec 100644 --- a/gtsam/linear/linear.i +++ b/gtsam/linear/linear.i @@ -16,9 +16,9 @@ virtual class Base { }; virtual class Gaussian : gtsam::noiseModel::Base { - static gtsam::noiseModel::Gaussian* Information(Matrix R); - static gtsam::noiseModel::Gaussian* SqrtInformation(Matrix R); - static gtsam::noiseModel::Gaussian* Covariance(Matrix R); + static gtsam::noiseModel::Gaussian* Information(Matrix R, bool smart = true); + static gtsam::noiseModel::Gaussian* SqrtInformation(Matrix R, bool smart = true); + static gtsam::noiseModel::Gaussian* Covariance(Matrix R, bool smart = true); bool equals(gtsam::noiseModel::Base& expected, double tol); @@ -37,9 +37,9 @@ virtual class Gaussian : gtsam::noiseModel::Base { }; virtual class Diagonal : gtsam::noiseModel::Gaussian { - static gtsam::noiseModel::Diagonal* Sigmas(Vector sigmas); - static gtsam::noiseModel::Diagonal* Variances(Vector variances); - static gtsam::noiseModel::Diagonal* Precisions(Vector precisions); + static gtsam::noiseModel::Diagonal* Sigmas(Vector sigmas, bool smart = true); + static gtsam::noiseModel::Diagonal* Variances(Vector variances, bool smart = true); + static gtsam::noiseModel::Diagonal* Precisions(Vector precisions, bool smart = true); Matrix R() const; // access to noise model @@ -69,9 +69,9 @@ virtual class Constrained : gtsam::noiseModel::Diagonal { }; virtual class Isotropic : gtsam::noiseModel::Diagonal { - static gtsam::noiseModel::Isotropic* Sigma(size_t dim, double sigma); - static gtsam::noiseModel::Isotropic* Variance(size_t dim, double varianace); - static gtsam::noiseModel::Isotropic* Precision(size_t dim, double precision); + static gtsam::noiseModel::Isotropic* Sigma(size_t dim, double sigma, bool smart = true); + static gtsam::noiseModel::Isotropic* Variance(size_t dim, double varianace, bool smart = true); + static gtsam::noiseModel::Isotropic* Precision(size_t dim, double precision, bool smart = true); // access to noise model double sigma() const;