Hypermapper

This release adds pip support to HyperMapper. HyperMapper can now be installed with
`pip install hypermapper`

This release also contains the following pip-related changes:
* For pip-installations, the HyperMapper main script (formerly called via `python scripts/hypermapper.py` can now be called by the command `hypermapper` from the command line.
* We also added the following command line hooks for pip installations:
* `scripts/compute_pareto.py` can now be be called by `hm-compute-pareto`.
* `scripts/plot_pareto.py` can now be called by `hm-plot-pareto`.
* `scripts/plot_hvi.py` can now be called by `hm-plot-hvi`.
* The quick start scenario in `example_scenarios/quick_start/branin.py` can now be called from the command line by `hm-quickstart`.
* `scripts/plot_optimization_results.py` can now be called by `hm-plot-optimization-results`.
* The pip installation does not contain the example scenarios, apart from the quick start scenario. However, if you clone the repository to get the examples, make sure to call them as a module (see below). This way, you don’t need to set any environment variables with the pip installation.
* The pip installation does not require any environment variables.

We recommend executing the example scenarios by executing them as a module, e.g., by `python -m example_scenarios.clients.python.client-server_chakong_haimes`.

It is still possible to call `scripts/hypermapper.py` as well as the other scripts in the `scripts` folder as before. For this to work, you need to
either
* call the scripts from the HyperMapper root directory,
* or to set `HYPERMAPPER_HOME` to your HyperMapper root directory.

We recommend deleting the reference to `HYPERMAPPER_HOME/scripts` from `PYTHONPATH` although an existing reference should not break anything with this release (except for the rare case where you have set this reference but not `HYPERMAPPER_HOME`).

We changed the directory structure. The legacy scripts are in the `scripts` folder. These import everything from the new `hypermapper` directory. The `scripts` directory is not part of the pip installation. For pip installations, the scripts can be executed using the command line hooks (see above).

This release also contains optimization and better parallelism support, which makes HyperMapper significantly faster.

At last, this release also adds support for noiseless GP models, which can be used via the json configuration file.

This release adds a few functionalities to HyperMapper:
- A new evolutionary algorithm that can be used for optimizing black-box functions
- A new Batch Bayesian Optimization algorithm that allows HyperMapper to request multiple black-box functions evaluations in parallel
- New and updated client-server mode examples
- A new plotting script for mono-objective optimization
- Several minor code optimizations

This release adds a new [Prior-guided Optimization](https://github.com/luinardi/hypermapper/wiki/Prior-Injection) method to HyperMapper, an optimization approach that allows users to inject their knowledge into the optimization process in the form of priors about which parts of the input space will yield the best performance.

This release also adds a new [resume optimization](https://github.com/luinardi/hypermapper/wiki/Resume-Optimization) feature to HyperMapper, which allows users to resume a previous optimization run of HyperMapper.

This release brings several updates to HyperMapper, namely:
- A new optimization approach based on random scalarizations, which supports optimization for any number of objectives
- An updated Random Forest model with better performance
- A new Gaussian Process model
- Support for constrained Bayesian Optimization
- A new default mode of operation, that allows HyperMapper to call the black-box function directly during optimization
- A new optimization approach based on Multi-start Local Searches that also supports multi-objective optimization
- Multiple fixes and performance improvements
- Several new optimization examples