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- Implementation in Python 3 (restructuring/simplifying the package and documentation) - Discrete optimization (i.e. integer optimization) - Constrained optimization - Manual seeding of the randomizer - Initial point set may be specified - Compatibility with `scipy.optimize.minimize` - 30 nose tests (with 26/30 successful with a single random seed)
- Reorganize code to appropriate folders - Update README.md with installation instructions - Changing where the shared libs are installed
- detailed documentation in source script - args - imports specified - numpy additions - private functions - implimentation and integration with C - MIT Licence