* Calcerror uses now sample weights

* catree comment in #10319

* Simulated Annealing for ANN_MLP training method

* EXPECT_LT

* just to test new data

* manage RNG

* Try again

* Just run buildbot with new data

* try to understand

* Test layer

* New data- new test

* Force RNG in backprop

* Use Impl to avoid virtual method

* reset all weights

* try to solve ABI

* retry

* ABI solved?

* till problem with dynamic_cast

* Something is wrong

* Solved?

* disable backprop test

* remove ANN_MLP_ANNEALImpl

* Disable weight in varmap

* Add example for SimulatedAnnealing

Added a writeFormat() method to Algorithm which must be called by the
write() method of derived classes.

(cherry picked from commit dfb49097)

2. Algorithm::load/save added (moved from StatModel)
3. copyrights updated; added copyright/licensing info for ffmpeg
4. some warnings from Xcode 6.x are fixed

- updated return value of points_classifier sample

- added test for loading legacy files
- added version to new written models
- fixed loading of several fields in some models
- added generation of new fields from old data

1. someMatrix.data -> someMatrix.prt()
2. someMatrix.data + someMatrix.step * lineIndex -> someMatrix.ptr( lineIndex )
3. (SomeType*) someMatrix.data -> someMatrix.ptr<SomeType>()
4. someMatrix.data -> !someMatrix.empty() ( or !someMatrix.data -> someMatrix.empty() ) in logical expressions

continuing refactoring ml samples; added "max vote" response to ANN_MLP. Probably, should make it in less hacky way

initial commit; ml has been refactored; it compiles and the tests run well; some other modules, apps and samples do not compile; to be fixed

weights array is only allocated for (l_count+1) elements,
but then weights[l_count+1] element is accessed.

This should allow many algorithms to take advantage of more parallelization
technologies.

a big patch; use special proxy types (Input/OutputArray, Input/OutputArrayOfArrays) for passing in vectors, matrices etc.

replaced alloca() (a.k.a. cvStackAlloc) with AutoBuffer or vector() everywhere. cvStackAlloc() is still defined, but we do not need alloca() anymore to compile and run OpenCV (fixes #889 and may be some others)