Documentation update
Change-Id: I0fec43bff4fe0ea6cd2d2a8b34dac2330a517da0
diff --git a/docs/source/modeling.rst b/docs/source/modeling.rst
index c816676..34c3bf8 100644
--- a/docs/source/modeling.rst
+++ b/docs/source/modeling.rst
@@ -1,9 +1,7 @@
.. default-domain:: cpp
-
.. cpp:namespace:: ceres
-
.. _`chapter-modeling`:
============
@@ -30,6 +28,15 @@
that is used to reduce the influence of outliers on the solution of
non-linear least squares problems.
+In this chapter we will describe the various classes that are part of
+Ceres Solver's modeling API, and how they can be used to construct
+optimization.
+
+Once a problem has been constructed, various methods for solving them
+will be discussed in :ref:`chapter-solving`. It is by design that the
+modeling and the solving APIs are orthogonal to each other. This
+enables easy switching/tweaking of various solver parameters without
+having to touch the problem once it has been successfuly modeling.
:class:`CostFunction`
---------------------
diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst
index c85e98a..eac50b4 100644
--- a/docs/source/tutorial.rst
+++ b/docs/source/tutorial.rst
@@ -27,7 +27,8 @@
a scalar function that is used to reduce the influence of outliers on
the solution of non-linear least squares problems. As a special case,
when :math:`\rho_i(x) = x`, i.e., the identity function, we get the
-more familiar `non-linear least squares problem` <http:
+more familiar `non-linear least squares problem
+<http://en.wikipedia.org/wiki/Non-linear_least_squares>`_.
.. math:: \frac{1}{2}\sum_{i=1} \left\|f_i\left(x_{i_1}, ... ,x_{i_k}\right)\right\|^2.
:label: ceresproblem2
diff --git a/docs/source/version_history.rst b/docs/source/version_history.rst
index 6cfb80c..010b477 100644
--- a/docs/source/version_history.rst
+++ b/docs/source/version_history.rst
@@ -15,6 +15,8 @@
gradient descent, non-linear conjugate gradient and LBFGS search
directions.
+#. New, much improved HTML documentation using Sphinx.
+
#. Speedup the robust loss function correction logic when residual is
one dimensional.
@@ -23,8 +25,19 @@
#. Added support for mixing automatic, analytic and numeric
differentiation. This is done by adding ``CostFunctionToFunctor``
- and ``NumericDiffFunctor`` objects.
+ and ``NumericDiffFunctor`` objects to the API.
+#. ``Summary::FullReport`` now reports the structure of the ordering
+ used by the ``LinearSolver`` and inner iterations.
+
+#. Ceres when run at the ``VLOG`` level 3 or higher will report
+ detailed timing information about its internals.
+
+#. Remove extraneous initial and final residual evaluations. This
+ speeds up the solver a bit.
+
+#. Automatic differenatiation with a dynamic number of parameter
+ blocks. (Based on an initial implementation by Thad Hughes).
Bug Fixes
---------
@@ -37,6 +50,13 @@
#. Fixed an initialization bug in ``ProgramEvaluator``.
+#. Fixes to Android.mk paths (Carlos Hernandez)
+
+#. Modify ``nist.cc`` to compute accuracy based on ground truth
+ solution rather than the ground truth function value.
+
+#. Fixed a memory leak in ``cxsparse.cc``. (Alexander Mordvintsev).
+
1.4.0
=====
diff --git a/include/ceres/dynamic_autodiff_cost_function.h b/include/ceres/dynamic_autodiff_cost_function.h
index 4226177..f2e7c26 100644
--- a/include/ceres/dynamic_autodiff_cost_function.h
+++ b/include/ceres/dynamic_autodiff_cost_function.h
@@ -41,7 +41,7 @@
//
// struct MyCostFunctor {
// template<typename T>
-// bool operator()(const* const* T parameters, T* residuals) const {
+// bool operator()(T const* const* parameters, T* residuals) const {
// // Use parameters[i] to access the i'th parameter block.
// }
// }
