Mogp-emulator

Bugfix release to fix a few outstanding issues. Fixes issues 241 and 242. Changes in this release:

- Update to Dimension Reduction to improve memory usage with some additional tests
- Update to documentation to reflect new dependency requirements
- Improvements to GPU build script in `setup.py` to remove outdated shared object library files.

Bug fix release to correct the GP demos to ensure that they run with the new
implementation. Changes include:

- Update Patsy integration to allow using formulae with LHS
- Updates to demos `gp_demos.py`, `gp_demo.R`, `excalibur_workshop_demo.py`, `gp_kernel_demos.py`, `multioutput_tutorial.py`
- Add new printing function to the projectile code to replace previous, modified above demos to use this.

New release incorporating recent work. New features in this release:

- Maxi-min LHC Experimental Designs
- Mulit-output history matching
- Emulator validation
- GPU implementation now supports Priors
- Additional fixes and improvements to documentation and examples

Bugfix release addressing a few issues identified when using the new version of the GP. New in this release:

- GP Predictions using mean functions have been corrected to fix an error where the mean function was not correctly subtracted from the targets when fitting.
- Fix a few problems caused by `patsy` objects not supporting pickling with parallel fitting/predictions with multiplt outputs.

New release with major improvements in CPU and GPU versions of the GP class.

Changes in CPU version:

- Mean functions are implemented using `patsy` to form design matrices.
- Default Prior distributions chosen for correlation lengths and nugget (if fitted).
- When fitting, starting point of optimization is a draw from the prior.
- New parameters class and coordinate transformation objects to make parameter meanings more transparent.
- Mean priors are now multivariate normal distributions.
- Mean functions are fit analytically.
- Additional kernels include Squared Exponential/Matern 5/2 with a single correlation length, and the product form of the Matern 5/2 kernel.

Changes in GPU Version:

- Multi-Output GPs fit in parallel.

Other changes:

- Additional demo examples and documentation improvements.

New release including GPU support and several other fixes and improvements.

Changes in this release:

- Support for GPU using the GaussianProcessGPU class.
- Supports Squared Exponential and Matern Kernels
- Supports basic polynomial mean functions which can be parsed from strings
- Supports fixed, adaptive, and fit nuggets
- Works with MultiOutputGP class, though fitting and predictions are done serially on the GPU.
- Pivoted Cholesky decomposition support for CPU GP fitting
- Modifications to MultiOutputGP fitting to allow GPs that fail to do so quietly and enables inspection of individual emulators based on those that failed.
- Improved demos and documentation.