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Merge pull request #166 from borglab/gchenfc-patch-1 

Fix doxygen "Creating a new factor"
release/4.3a0
Frank Dellaert 2019-11-27 16:39:24 -05:00 committed by GitHub
parent e90e1f1dd2 fb4dc7ccb9
commit fa5248e536
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gtsam/mainpage.dox
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@ -1,7 +1,6 @@
// This causes Doxygen to find classes inside the gtsam namespace without
// explicitly specifying it when writing class names.
namespace gtsam {
/**
\mainpage GTSAM
@ -17,11 +16,10 @@ To use GTSAM to solve your own problems, you will often have to create new facto
-# The number of variables your factor involves is <b>unknown</b> 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 <b>known</b> at compile time and is between 1 and 6 - derive from NonlinearFactor1, NonlinearFactor2, NonlinearFactor3, NonlinearFactor4, NonlinearFactor5, or NonlinearFactor6, and implement <b>\c evaluateError()</b>
-# The number of variables your factor involves is <b>known</b> at compile time and is between 1 and 6 - derive from NoiseModelFactor1, NoiseModelFactor2, NoiseModelFactor3, NoiseModelFactor4, NoiseModelFactor5, or NoiseModelFactor6, and implement <b>\c evaluateError()</b>
- 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.
*/
}
}