- Refactored the O3A code to allow for different cost, weight
  and scoring functions

- Added cost, weight and scoring functions using atom-based
  Crippen logP contributions

- Added relevant tests for the new functionality

Important points:
-----------------

- The constructors now accept optional pointers to
  MolHistogram objects instead of pointers to arrays of
  double. I think it is better for performance, since
  rebuilding the histogram involves running through two
  nested loops over all atoms, even though the
  3DDistanceMat is provided to the O3A constructor.
  This change breaks binary compatibility with previous
  C++ programs linking to RDKit MolAlign library; I do not
  think this is big issue, and while I was there I made
  other changes which cause binary incompatibility.
  If needed, we may preserve binary compatibility
  reverting the MolHistogram change and the other ones.

- From Python, nothing changed in the interface to previous
  MMFFO3A functionality. It MIGHT be more appropriate to
  change the "GetO3A()" function into "GetMMFFO3A()", but
  I have not done that to avoid breaking existing scripts;
  the choice is yours

- As of now, the code contains a number of conditional
  compilation directives checking for the
  USE_O3A_CONSTRUCTOR macro; if USE_O3A_CONSTRUCTOR is
  defined, then the code is built with an alternative O3A
  constructor which allows choosing whether one wishes
  to use MMFF or Crippen descriptors. Otherwise, no
  alternative constructor is built, but rather two
  functions which return a pointer to an O3A object.
  I prefer by far the first solution (namely, with
  USE_O3A_CONSTRUCTOR defined), but again, the choice is
  yours. The code is tested and works in both cases.

- Custom cost, weight and scoring functions can easily
  be defined in external programs without need to rebuild
  the RDKit, allowing flexibility. The new custom
  functionality can be accessed by calling the "bigger"
  O3A constructor.
- Refactored the O3A code to allow for different cost, weight
  and scoring functions

- Added cost, weight and scoring functions using atom-based
  Crippen logP contributions

- Added relevant tests for the new functionality

Important points:
-----------------

- The constructors now accept optional pointers to
  MolHistogram objects instead of pointers to arrays of
  double. I think it is better for performance, since
  rebuilding the histogram involves running through two
  nested loops over all atoms, even though the
  3DDistanceMat is provided to the O3A constructor.
  This change breaks binary compatibility with previous
  C++ programs linking to RDKit MolAlign library; I do not
  think this is big issue, and while I was there I made
  other changes which cause binary incompatibility.
  If needed, we may preserve binary compatibility
  reverting the MolHistogram change and the other ones.

- From Python, nothing changed in the interface to previous
  MMFFO3A functionality. It MIGHT be more appropriate to
  change the "GetO3A()" function into "GetMMFFO3A()", but
  I have not done that to avoid breaking existing scripts;
  the choice is yours

- As of now, the code contains a number of conditional
  compilation directives checking for the
  USE_O3A_CONSTRUCTOR macro; if USE_O3A_CONSTRUCTOR is
  defined, then the code is built with an alternative O3A
  constructor which allows choosing whether one wishes
  to use MMFF or Crippen descriptors. Otherwise, no
  alternative constructor is built, but rather two
  functions which return a pointer to an O3A object.
  I prefer by far the first solution (namely, with
  USE_O3A_CONSTRUCTOR defined), but again, the choice is
  yours. The code is tested and works in both cases.

- Custom cost, weight and scoring functions can easily
  be defined in external programs without need to rebuild
  the RDKit, allowing flexibility. The new custom
  functionality can be accessed by calling the "bigger"
  O3A constructor.