Use subsections instead of an enumeration for FAQs
Change-Id: I37c1256417240bf7decec1f756df8a8402f5c586
diff --git a/docs/source/modeling_faqs.rst b/docs/source/modeling_faqs.rst
index 0d23de4..b51380a 100644
--- a/docs/source/modeling_faqs.rst
+++ b/docs/source/modeling_faqs.rst
@@ -8,81 +8,76 @@
Modeling
========
-#. Use analytical/automatic derivatives.
+Use analytical/automatic derivatives
+====================================
- This is the single most important piece of advice we can give to
- you. It is tempting to take the easy way out and use numeric
- differentiation. This is a bad idea. Numeric differentiation is
- slow, ill-behaved, hard to get right, and results in poor
- convergence behaviour.
+This is the single most important piece of advice we can give to you. It is
+tempting to take the easy way out and use numeric differentiation. This is a bad
+idea. Numeric differentiation is slow, ill-behaved, hard to get right, and
+results in poor convergence behaviour.
- Ceres allows the user to define templated functors which will
- be automatically differentiated. For most situations this is enough
- and we recommend using this facility. In some cases the derivatives
- are simple enough or the performance considerations are such that
- the overhead of automatic differentiation is too much. In such
- cases, analytic derivatives are recommended.
+Ceres allows the user to define templated functors which will be automatically
+differentiated. For most situations this is enough and we recommend using this
+facility. In some cases the derivatives are simple enough or the performance
+considerations are such that the overhead of automatic differentiation is too
+much. In such cases, analytic derivatives are recommended.
- The use of numerical derivatives should be a measure of last
- resort, where it is simply not possible to write a templated
- implementation of the cost function.
+The use of numerical derivatives should be a measure of last resort, where it is
+simply not possible to write a templated implementation of the cost function.
- In many cases it is not possible to do analytic or automatic
- differentiation of the entire cost function, but it is generally
- the case that it is possible to decompose the cost function into
- parts that need to be numerically differentiated and parts that can
- be automatically or analytically differentiated.
+In many cases it is not possible to do analytic or automatic differentiation of
+the entire cost function, but it is generally the case that it is possible to
+decompose the cost function into parts that need to be numerically
+differentiated and parts that can be automatically or analytically
+differentiated.
- To this end, Ceres has extensive support for mixing analytic,
- automatic and numeric differentiation. See
- :class:`CostFunctionToFunctor`.
+To this end, Ceres has extensive support for mixing analytic, automatic and
+numeric differentiation. See :class:`CostFunctionToFunctor`.
-#. When using Quaternions, consider using :class:`QuaternionManifold`.
+When using Quaternions, consider using :class:`QuaternionManifold`
+==================================================================
- `Quaternions <https://en.wikipedia.org/wiki/Quaternion>`_ are a
- four dimensional parameterization of the space of three dimensional
- rotations :math:`SO(3)`. However, the :math:`SO(3)` is a three
- dimensional set, and so is the tangent space of a
- Quaternion. Therefore, it is sometimes (not always) beneficial to
- associate a local parameterization with parameter blocks
- representing a Quaternion. Assuming that the order of entries in
- your parameter block is :math:`w,x,y,z`, you can use
- :class:`QuaternionManifold`.
+`Quaternions <https://en.wikipedia.org/wiki/Quaternion>`_ are a four dimensional
+parameterization of the space of three dimensional rotations :math:`SO(3)`.
+However, the :math:`SO(3)` is a three dimensional set, and so is the tangent
+space of a Quaternion. Therefore, it is sometimes (not always) beneficial to
+associate a local parameterization with parameter blocks representing a
+Quaternion. Assuming that the order of entries in your parameter block is
+:math:`w,x,y,z`, you can use :class:`QuaternionManifold`.
- .. NOTE::
+.. NOTE::
- If you are using `Eigen's Quaternion
- <http://eigen.tuxfamily.org/dox/classEigen_1_1Quaternion.html>`_
- object, whose layout is :math:`x,y,z,w`, then you should use
- :class:`EigenQuaternionManifold`.
+ If you are using `Eigen's Quaternion
+ <http://eigen.tuxfamily.org/dox/classEigen_1_1Quaternion.html>`_
+ object, whose layout is :math:`x,y,z,w`, then you should use
+ :class:`EigenQuaternionManifold`.
-#. How do I solve problems with general linear & non-linear
- **inequality** constraints with Ceres Solver?
+How do I solve problems with general linear & non-linear **inequality** constraints with Ceres Solver?
+======================================================================================================
- Currently, Ceres Solver only supports upper and lower bounds
- constraints on the parameter blocks.
+Currently, Ceres Solver only supports upper and lower bounds constraints on the
+parameter blocks.
- A crude way of dealing with inequality constraints is have one or
- more of your cost functions check if the inequalities you are
- interested in are satisfied, and if not return false instead of
- true. This will prevent the solver from ever stepping into an
- infeasible region.
+A crude way of dealing with inequality constraints is have one or more of your
+cost functions check if the inequalities you are interested in are satisfied,
+and if not return false instead of true. This will prevent the solver from ever
+stepping into an infeasible region.
- This requires that the starting point for the optimization be a
- feasible point. You also risk pre-mature convergence using this
- method.
+This requires that the starting point for the optimization be a feasible point.
+You also risk pre-mature convergence using this method.
-#. How do I solve problems with general linear & non-linear **equality**
- constraints with Ceres Solver?
+How do I solve problems with general linear & non-linear **equality** constraints with Ceres Solver?
+====================================================================================================
- There is no built in support in ceres for solving problems with
- equality constraints. Currently, Ceres Solver only supports upper
- and lower bounds constraints on the parameter blocks.
+There is no built in support in ceres for solving problems with equality
+constraints. Currently, Ceres Solver only supports upper and lower bounds
+constraints on the parameter blocks.
- The trick described above for dealing with inequality
- constraints will **not** work for equality constraints.
+The trick described above for dealing with inequality constraints will **not**
+work for equality constraints.
-#. How do I set one or more components of a parameter block constant?
+How do I set one or more components of a parameter block constant?
+==================================================================
- Using :class:`SubsetManifold`.
+Using :class:`SubsetManifold`.
