Gpy-abcd

- Added a max_retries argument to explore_model_space to persist on optimiser numerical errors
- Minor refactoring and changes around the generation of the sum-of-products form of kernels (some clarifying assertions and caching of generated forms since multiple methods triggered them)
- Minor documentation changes

JIT-compiled some components of linear, periodic and sigmoidal kernels with numba where faster than numpy (between 1.45x and 4.6x); left some benchmarking code.
Improved numerical stability due to the above and the updated package requirements.
Added LIN + C -> LIN kernel simplification provided the offset-including LIN version is used, which is the case by default (i.e. the __USE_LIN_KERNEL_HORIZONTAL_OFFSET flag in config.py is True).

- Re-implementation:
- Base sigmoidal kernels: computationally more efficient; no more warnings and enforced ceilings now gone
- Change operators: fit appreciably better (i.e. competitive where the data is truly of that kind), probably partly due to steeper gradients of new functional form
- Periodic Kernel: replicated the series-expansions-based approximations as in GPML MATLAB library instead of the pure-form version with overflow-prevention
- Restructuring:
- Kernel Expressions: the classes are now code-wise more separate (still modular), and the Sigmoidal * Constant expression simplification is now prevented (for description generation)
- Internal functions passing: model-scoring and model-list fitting functions are now passed directly (and can therefore be supplied by a user)
- External (exported) starting kernels, rules and search parameters: added a few and better organised starting kernels and groups of production rules for easy user selection (arbitrary inputs still allowed)
- Global configurations grouped in config.py; may become more user-controllable (e.g. as search arguments) in the future

- Remaining issues:
- The Periodic kernel is still somehow unstable but competitive when data is not periodic; it seems this is its actual nature
- Stationary kernels in ChangeWindow kernels do not work well (which make sense, but it would be nice if it could be remedied); could try adding a more-or-less hidden offset between the two sides (for all or only non-stationary kernels) in the future

Minor release to add some numerical stabilisations to sigmoidal and periodic kernels (and package downloads badge in the README)

Acceptably usable and tested release; see the newly expanded README; known issues:
- Instability of periodic kernel on non-periodic data (which might seem like a non-problem, but it can be)
- Optimisation of location/width parameters in change-window kernel (the reason for all its different implementations)