Installation

Introduction

This page will walk you through the SUMO Toolbox installation. Please refer to the system requirements first. See the downloading section on how to download the toolbox.

Quick start

Quick and dirty instructions:

1. Log into the SUMO lab website with the account information mailed to you and download the toolbox
2. Unzip the toolbox zip file, it will create a directory (= the toolbox installation directory)
3. Start Matlab
4. Go to the toolbox directory
5. Run 'startup'
6. Run 'go'

Basic Installation

Toolbox

Unzip the toolbox zip file to a directory somewhere on your harddisk, the full path of the SUMO Toolbox (including installation directory) will be referred to as the toolbox installation directory (e.g., c:\software\SUMO-Toolbox-6.3). Note that you do not have to put the toolbox in the Matlab installation directory, we actually advise against it since it can cause confusing errors.

Once you have unzipped the toolbox zip file the directory structure looks like this:

• <toolbox installation directory> (e.g., c:\software\SUMO-Toolbox-6.3)
  • bin/ : binaries, executable scripts, ...
  • config/ : configuration files, location of default.xml
  • config/demo : a couple of demo configuration files that may help you
  • doc/ : some documentation
  • doc/apidoc : Javadoc and other api docs
  • lib/ : required libraries (eg: dom4j)
  • output/ : some output may be placed here (e.g., a global log file)
  • src/ : all source code
  • examples/ : project directories of different examples (you can test with these problems and use them as an example to add your own)

Setup

Setting up the toolbox is very easy. Start Matlab, navigate to the toolbox installation directory (not anywhere else, this is important!!) and run 'startup'.

Test run

To ensure everything is working you can do a simple run of the toolbox with the default configuration. This means the toolbox will use the setting specified in <SUMO-Toolbox-installation-dir>/config/default.xml.

1. Make sure that you are in the toolbox installation directory and you have run 'startup' (see above)
2. Type 'go' and press enter.
3. The toolbox will start to model the Academic2DTwice simulator. This simulator has 2 inputs and 2 outputs, and will be modeled using Kriging models, scored using CrossValidation, and samples selected using a combined sample selection method.
4. To see the exact settings used open config/default.xml. Feel free to edit this file and play around with the different options.

The examples directory contains many example simulators that you can use to test the toolbox with. See Running#Running_different_examples.

Ok, the test run works, now what?

See Running page.

Problems

See the reporting problems page.

Optional: Compiling libraries

There are some alternative libraries and simulators available that have to be compiled for your specific platform. Instructions depend on your operating system. Ensure you have installed the extension pack before continuing.

Linux/Unix/OSX

1. Ensure you have the following environment variables set:
   1. MATLABDIR=/path/to/your/matlab/installation
   2. JAVA_HOME=/path/to/your/SDK/installation
2. Ensure you have the usual build tools installed: gcc, g++, autotools, make, etc
3. From the command line shell (so NOT from inside Matlab): Go to the toolbox installation directory and type 'make'. This will build everything for you (C/C++ files, SVM libraries, ...). If you only want to build certain packages simply 'make Package' in the toolbox installation directory.
   1. Note: if this is giving you problems, and you just want to compile the LS-SVMs you can try running makeLSSVM from inside Matlab (see the Windows instructions below)
4. A complete list of available packages follows:

Package	Description	Requires extension pack
contrib	Builds the FANN, SVM (libsvm, LS-SVMlab) and NNSYSID libraries	Yes
cexamples	Builds the binaries for several C/C++ simulators	No

Windows

1. Compiling C/C++ codes (examples):
   1. You will have to do this on your own using a C/C++ compiler of your choice: Dev-c++/Visual Studio/...
2. Compiling LS-SVM libraries:
   1. In order to use the LS-SVM backend, you will have to compile the LS-SVM mex files (it will work if you dont but you will get a lot of warning messages about a missing CFile implementation).
   2. This can be done using the built-in LCC compiler of matlab, by calling 'makeLSSVM' from the Matlab command prompt (make sure the SUMO Toolbox is in your path)
3. Compiling ANN libraries:
   1. In order to use the FANN backend, you will have to compile the FANN library and mex files.
   2. So far nobody has yet got it to work under Windows, but don't let that stop you.