This method numerically computes function derivatives in different
scales, extrapolating between intermediate results to conserve function
evaluations. Adaptive differentiation is essential to produce accurate
results for functions with noisy derivatives.
Full changelist:
-Created a new type of NumericDiffMethod (RIDDERS).
-Implemented EvaluateRiddersJacobianColumn in NumericDiff.
-Created unit tests with f(x) = x^2 + [random noise] and
f(x) = exp(x).
Change-Id: I2d6e924d7ff686650272f29a8c981351e6f72091
Since Ceres is moving to using GitHub for issues, and the Google
Code URL in the current copyright header will soon become invalid,
update all the headers.
Change-Id: I1fce70375d1bcf098591f07b4d8f01a5c1e0789c
If the parameter block size is 1, asking Eigen to create
a row-major matrix triggers a compile time error. Previously
we were handling the case where the number of rows in the
jacobian block was known statically, but the problem is present
when the nummber of rows is dynamic.
This CL fixes this problem.
Thanks to Dominik Reitzle for reporting this.
Change-Id: I99c3eec3558e66ebf4efa51c4dee8ce292ffe0c1
1. Update AutoDiffCostFunction template parameters to be consistent
with NumericDiffCostFunction.
2. Update the documentation for NumericDiffCostFunction and
AutoDiffCostFunction.
Change-Id: I113038abb5bedebb0f6f326f2a4ac31480d785fc
A wrapper class that takes a variadic functor evaluating a
function, numerically differentiates it and makes it available as a
templated functor so that it can be easily used as part of Ceres'
automatic differentiation framework.
The tests for NumericDiffCostFunction and NumericDiffFunctor have
a lot of stuff that is common, so refactor them to reduce code.
Change-Id: I83b01e58b05e575fb2530d15cbd611928298646a
The interface for NumericDiffCostFunction and AutoDiffCostFunction
are not comparable. They both accept variadic functors.
The change is backward compatible, as it still supports numeric
differentiation of CostFunction objects.
Some refactoring of documentation and code in auto_diff_cost_function
and its relatives was also done to make things consistent.
Change-Id: Ib5f230a1d4a85738eb187803b9c1cd7166bb3b92
Eigen3 does not allow column vectors to be stored in row-major
format. NumericDiffCostFunction by default stores its Jacobian
matrices in row-major format. This works fine if the residual
contains more than one variable. But if the residual block
depends on one variable and has more than one residuals, the
resulting Jacobian matrix is a column matrix in row-major format
resulting in a compile time error.
The fix is to check the template parameters and switch to column-major
storage as needed.
Thanks to Lena Gieseke for reporting this.
Change-Id: Icc51c5b38e1f3609e0e1ecb3c4e4a02aecd72c3b
This is a preliminary, but full, port of Ceres to Windows.
Currently all tests compile and run, with only system_test
failing to work correctly due to a path issue.
Change-Id: I4152c1588bf51ffd7f4d9401ef9759f5d28c299c
Tal Ben-Nun