Introduction to APPRENTICE

Overview of Apprentice

The core functionality of Apprentice is construction of a multivariate analytic surrogate model to computationally expensive Monte-Carlo predictions. The surrogate model is used for numerical optimization of a prediction function since it can be prohibitively expensive to perform optimization over functions with the Monte-Carlo predictions. To summarize, Apprentice can be used for performing three tasks:

Construct surrogate models to computationally expensive Monte-Carlo predictions

Formulate a prediction function with surrogate models

Perform numerical optimziation over the prediction function

Dependencies

Required dependencies:

Python 3.7
NumPy 1.15.0 or above
SciPy 1.7.2 or above
Pyomo 6.4.0 or above

Optional dependencies:

numba 0.40.0 or above
h5py 2.8.0 or above
matplotlib 3.0.0 or above
GPy 1.9.9 or above (required if gaussian process surrogate model object is constructed)

For running with the mpi4py parallelism:

A functional MPI 1.x/2.x/3.x implementation, such as MPICH, built with shared/dynamic libraries
mpi4py v3.0.0 or above

For compiling this documentation:

Sphinx-RTD

Installation

To install apprentice, execute the following commands:

git clone git@github.com:HEPonHPC/apprentice.git
cd  apprentice/
pip install .
cd ..

Testing the installation

To test the install, run the unit unit tests over all modules of apprentice:

cd  apprentice/apprentice
python -m unittest discover .