From 96f90c3f13dbecae8469be714f6156ac55c73f01 Mon Sep 17 00:00:00 2001 From: Gerry Chen Date: Tue, 12 Nov 2019 19:16:34 -0500 Subject: [PATCH] Fix doxygen "Creating a new factor" I think NonlinearFactor1, NonlinearFactor2, ... is supposed to say NoiseModelFactor1, NoiseModelFactor2, ... --- gtsam/mainpage.dox | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/gtsam/mainpage.dox b/gtsam/mainpage.dox index db42b1277..59e7f9fa6 100644 --- a/gtsam/mainpage.dox +++ b/gtsam/mainpage.dox @@ -17,11 +17,11 @@ To use GTSAM to solve your own problems, you will often have to create new facto -# The number of variables your factor involves is unknown at compile time - derive from NoiseModelFactor and implement NoiseModelFactor::unwhitenedError() - This is a factor expressing the sum-of-squares error between a measurement \f$ z \f$ and a measurement prediction function \f$ h(x) \f$, on which the errors are expected to follow some distribution specified by a noise model (see noiseModel). --# The number of variables your factor involves is known at compile time and is between 1 and 6 - derive from NonlinearFactor1, NonlinearFactor2, NonlinearFactor3, NonlinearFactor4, NonlinearFactor5, or NonlinearFactor6, and implement \c evaluateError() +-# The number of variables your factor involves is known at compile time and is between 1 and 6 - derive from NoiseModelFactor1, NoiseModelFactor2, NoiseModelFactor3, NoiseModelFactor4, NoiseModelFactor5, or NoiseModelFactor6, and implement \c evaluateError() - This factor expresses the same sum-of-squares error with a noise model, but makes the implementation task slightly easier than with %NoiseModelFactor. -# Derive from NonlinearFactor - This is more advanced and allows creating factors without an explicit noise model, or that linearize to HessianFactor instead of JacobianFactor. */ -} \ No newline at end of file +}