Install

Preparing a virtualenv

We recommend using a virtualenv, because (A) you can control the version of each python package, (B) installing and removing packages becomes easy as (C) you don’t need sudo rights and (D) it becomes harder to mess up up the python installation on your system.

1. Get virtualenv, then load a freshly created virtualenv. (If you are not familiar with virtualenv, you might want to read more about it)

   pip install virtualenv
   virtualenv virtualSurrogates
   source virtualSurrogates/bin/activate
   

2. Install numpy, scipy, matplotlib, as this doesn’t work through setup.py.

   easy_install -U distribute
   pip install numpy==1.8.1
   pip install scipy==0.14.0
   pip install matplotlib
   pip install scikit-learn==0.15.1
   

   This may take some time. Afterwards you can verify having those libs installed with:

   pip freeze
   
       argparse==1.2.1
       mock==1.0.1
       nose==1.3.4
       numpy==1.8.1
       pyparsing==2.0.3
       python-dateutil==2.3
       pytz==2014.10
       scipy==0.14.0
       six==1.8.0
       wsgiref==0.1.2
       scikit-learn==0.15.1
       matplotlib==1.4.2
   

Install the Surrogate Benchmark Library

1. Clone the repository:

   git clone https://github.com/KEggensperger/SurrogateBenchmarks.git
   cd SurrogateBenchmarks
   

2. Run setup.py

   python setup.py install
   

   This will install tools, scripts and some requirements (networkx, pyparsing, and python-daemon). This might take a while. When your environment is ready it could/should look like this:

   pip freeze
       Surrogates==Nan
       argparse==1.2.1
       decorator==3.4.0
       lockfile==0.10.2
       mock==1.0.1
       networkx==1.9.1
       numpy==1.8.1
       pyparsing==2.0.3
       python-daemon==1.6.1
       python-dateutil==2.3
       pytz==2014.10
       scikit-learn==0.15.1
       scipy==0.14.0
       six==1.8.0
       wsgiref==0.1.2
   

3. If the installation was successful you can run some tests. NOTE: Some tests will fail, if you are using different versions of numpy, scipy, and/or scikit-learn. This is not problematic as some of the tests only assert that you retrieve exactly the same results as me and as the numeric results only slightly differ.

   python setup.py test
   

NOTE: If you cannot install the library, because you cannot upgrade scikit-learn, numpy, scipy, etc. Make sure some version of these modules is installed and uncomment the respective lines in install_requires.