In order to run the program please follow the steps:

0. Add the /src directory into the PYTHONPATH of your linux Debian/Ubuntu: export PYTHONPATH = $PYTHONPATH:/home/<dirname>/qualitative/src
1. Install python requirements and external programs (see below)
2. Change directory to /lib and run "bash install.sh" to download Java libraries
3. Download linguistic resources (suggested folder in /res; there may be a bash script to do that)
4. Specify the location of the linguistic resources to the configuration files
5. To test installation start the LM server and run src/app/autoranking/application.py <classifier_file> <annotation.config.1> [<annotation.config.2> ...]

This is a list of the requirements for running the suite. Please scroll for more hints on their installation

For Debian/ubuntu:

#install java sudo apt-add-repository ppa:openjdk-r/ppa sudo apt-get update sudo apt-get install openjdk-8-jdk

#install python libraries

sudo apt-get install python-dev g++ build-essential python-pip libblas-dev liblapack-dev gfortran

sudo pip install --upgrade pip

sudo pip install <package-name>

or for user-specific installation (no root or not wanting to risk your python environment) pip install --user <package-name>

pip install setuptools pip install nltk==2.0.5 easy_install -U distribute pip install -r requirements.txt pip install https://github.com/kpu/kenlm/archive/master.zip

# nltk==2.0.1rc4 and matplotlib need to be checked

Additionally * expsuite [only for training] (Manually from https://github.com/lefterav/expsuite)

external programs [need to start separately] * lmserver wrapped over SRILM [soon to be replaced by KenLM] * Acrolinx IQ [proprietary-optional]

jar files (automatically fetched by "cd lib; bash install.sh") * py4j * Berkeley parser * Meteor * Language tool

other resources (automatically fetched by "cd res; bash download.sh": * language model for source and target language (ARPA format) * trained grammar for Berkeley parser (source and target language) * truecaser model for source and target language (see Moses) * pre-trained quality estimation ranking model

sudo apt-get install python-dev g++ build-essential python-pip sudo pip install --upgrade pip sudo pip install orange

• There is also a debian package / repository called orangesvn ( sudo apt-get install orangesvn) but works only with python 2.5. If you use it, you may have to tackle pythonpath issues

No root access: - Go to http://orange.biolab.si/ and download packed sources - python setup.py install --user

Other platforms

Use the standard way to install pip at your operating system or get pip from here: http://pypi.python.org/pypi/pip

pip install orange

Various other libraries -------sudo apt-get install python-nltk (in Ubuntu 10.04 or later) otherwise try with pip

sudo apt-get install libyaml-dev sudo pip install nltk

sudo apt-get remove python-numpy python-scipy (repositories provide only old versions) sudo apt-get install python python-dev gcc gfortran g++ libblas-dev libatlas-cpp-0.6-dev liblapack-dev libblas-dev libsuitesparse-dev sudo pip install numpy sudo pip install scipy

Ruffus is a pipeline execution framework for Python, that is used for the preprocessing of the data in scripts such as src/exexperiment/autoranking/annotate_updated. If you already have annotated data you can skip this

Ruffus can be installed also by using pip install. If you have problems check the following:

wget http://launchpadlibrarian.net/11726755/pypy-lib_1.0.0-svn51091-1_all.deb wget https://launchpad.net/ubuntu/+source/pypy/1.0.0-svn51091-1/+build/503581/+files/pypy_1.0.0-svn51091-1_amd64.deb wget https://launchpad.net/ubuntu/+source/pypy/1.0.0-svn51091-1/+build/503581/+files/pypy-stackless_1.0.0-svn51091-1_amd64.deb dpkg -i

Expsuite is a set of scripts that parallelizes the training of a big numbers of systems, with various parameters, and allows monitoring the results. Please check out the latest version of expsuite and add it to the python path

https://github.com/lefterav/expsuite

Check out -