NumericDiffCostFunction supports dynamic number of residuals.
1. Update AutoDiffCostFunction template parameters to be consistent
with NumericDiffCostFunction.
2. Update the documentation for NumericDiffCostFunction and
AutoDiffCostFunction.
Change-Id: I113038abb5bedebb0f6f326f2a4ac31480d785fc
diff --git a/docs/source/building.rst b/docs/source/building.rst
index c326fd1..b74a9dd 100644
--- a/docs/source/building.rst
+++ b/docs/source/building.rst
@@ -1,8 +1,8 @@
.. _chapter-building:
-=====================
-Building Ceres Solver
-=====================
+============
+Installation
+============
Stable Ceres Solver releases are available for download at
`code.google.com <http://code.google.com/p/ceres-solver/>`_. For the
diff --git a/docs/source/modeling.rst b/docs/source/modeling.rst
index 8e6de12..a5e875d 100644
--- a/docs/source/modeling.rst
+++ b/docs/source/modeling.rst
@@ -164,7 +164,7 @@
.. code-block:: c++
template <typename CostFunctor,
- int M, // Number of residuals, or ceres::DYNAMIC.
+ int kNumResiduals, // Number of residuals, or ceres::DYNAMIC.
int N0, // Number of parameters in block 0.
int N1 = 0, // Number of parameters in block 1.
int N2 = 0, // Number of parameters in block 2.
@@ -176,7 +176,7 @@
int N8 = 0, // Number of parameters in block 8.
int N9 = 0> // Number of parameters in block 9.
class AutoDiffCostFunction : public
- SizedCostFunction<M, N0, N1, N2, N3, N4, N5, N6, N7, N8, N9> {
+ SizedCostFunction<kNumResiduals, N0, N1, N2, N3, N4, N5, N6, N7, N8, N9> {
};
To get an auto differentiated cost function, you must define a
@@ -254,6 +254,22 @@
computing a 1-dimensional output from two arguments, both
2-dimensional.
+ :class:`AutoDiffCostFunction` also supports cost functions with a
+ runtime-determined number of residuals. For example:
+
+ .. code-block:: c++
+
+ CostFunction* cost_function
+ = new AutoDiffCostFunction<MyScalarCostFunctor, DYNAMIC, 2, 2>(
+ new CostFunctorWithDynamicNumResiduals(1.0), ^ ^ ^
+ runtime_number_of_residuals); <----+ | | |
+ | | | |
+ | | | |
+ Actual number of residuals ------+ | | |
+ Indicate dynamic number of residuals --------+ | |
+ Dimension of x ------------------------------------+ |
+ Dimension of y ---------------------------------------+
+
The framework can currently accommodate cost functions of up to 10
independent variables, and there is no limit on the dimensionality
of each of them.
@@ -342,12 +358,21 @@
.. code-block:: c++
- template <typename CostFunctionNoJacobian,
- NumericDiffMethod method = CENTRAL, int M = 0,
- int N0 = 0, int N1 = 0, int N2 = 0, int N3 = 0, int N4 = 0,
- int N5 = 0, int N6 = 0, int N7 = 0, int N8 = 0, int N9 = 0>
+ template <typename CostFunctor,
+ NumericDiffMethod method = CENTRAL,
+ int kNumResiduals, // Number of residuals, or ceres::DYNAMIC.
+ int N0, // Number of parameters in block 0.
+ int N1 = 0, // Number of parameters in block 1.
+ int N2 = 0, // Number of parameters in block 2.
+ int N3 = 0, // Number of parameters in block 3.
+ int N4 = 0, // Number of parameters in block 4.
+ int N5 = 0, // Number of parameters in block 5.
+ int N6 = 0, // Number of parameters in block 6.
+ int N7 = 0, // Number of parameters in block 7.
+ int N8 = 0, // Number of parameters in block 8.
+ int N9 = 0> // Number of parameters in block 9.
class NumericDiffCostFunction
- : public SizedCostFunction<M, N0, N1, N2, N3, N4, N5, N6, N7, N8, N9> {
+ : public SizedCostFunction<kNumResiduals, N0, N1, N2, N3, N4, N5, N6, N7, N8, N9> {
};
To get a numerically differentiated :class:`CostFunction`, you must
@@ -426,6 +451,24 @@
computing a 1-dimensional output from two arguments, both
2-dimensional.
+ NumericDiffCostFunction also supports cost functions with a
+ runtime-determined number of residuals. For example:
+
+ .. code-block:: c++
+
+ CostFunction* cost_function
+ = new NumericDiffCostFunction<MyScalarCostFunctor, CENTRAL, DYNAMIC, 2, 2>(
+ new CostFunctorWithDynamicNumResiduals(1.0), ^ ^ ^
+ TAKE_OWNERSHIP, | | |
+ runtime_number_of_residuals); <----+ | | |
+ | | | |
+ | | | |
+ Actual number of residuals ------+ | | |
+ Indicate dynamic number of residuals --------+ | |
+ Dimension of x ------------------------------------+ |
+ Dimension of y ---------------------------------------+
+
+
The framework can currently accommodate cost functions of up to 10
independent variables, and there is no limit on the dimensionality
of each of them.
