Emulator Build-Up

Building the emulator requires different stages:

• generating the training points

• training the Gaussian Processes

The inputs are generated using Latin Hypercube sampling and these are scaled using the priors module below. One can specify a prior using the dictionary format as follows:

{'distribution': 'uniform', 'specs': [0.06, 0.34]}

where specs are the specificifications for the distribution. In the example above, is the minimum and the maximum is . Note that we are using scipy.stats and hence the above convention. The GP models are trained in parallel (number of cores available on your computer) and are stored.

• Predictions
• Priors
• Training
• Training Points