README

UPDATE 17-08-2018: Now RGF is part of the official RGF repository and active development is performed there. The mlampros/RGF repository is archived.

UPDATE 26-07-2018: A Singularity image file is available in case that someone intends to run RGF on Ubuntu Linux (locally or in a cloud instance) with all package requirements pre-installed. This allows the user to utilize the RGF package without having to spend time on the installation process.

System Requirements

All modules should be installed in the default python configuration (the configuration that the R-session displays as default), otherwise errors will occur during the RGF package installation (reticulate::py_discover_config() might be useful here).

Debian/Ubuntu/Fedora

sudo pip install --upgrade pip setuptools

sudo pip install -U numpy

sudo pip install --upgrade scipy

sudo pip install -U scikit-learn

Then, download the rgf-python package and install it using the following commands,


git clone https://github.com/RGF-team/rgf.git

cd rgf/python-package

sudo python setup.py install

Mac OS X


brew upgrade python

sudo pip3 install --upgrade setuptools

sudo pip3 install -U numpy

sudo pip3 install --upgrade scipy

sudo pip3 install -U scikit-learn

The FastRGF module requires a gcc >= 8.0. To install gcc-8 (or the most recent gcc) with brew follow the next steps,


# before running the following commands make sure that the most recent Apple command line tools for Xcode are installed

brew update

brew upgrade

brew info gcc

brew install gcc

brew cleanup

After the newest gcc version is installed the user should navigate to /usr/local/bin and if a gcc file exists (symbolic link) then the user should delete it. Then the user should run the following command,


sudo ln -s /usr/local/bin/gcc-8 /usr/local/bin/gcc

After the new gcc is installed the user should continue with the installation of rgf_python,


git clone https://github.com/RGF-team/rgf.git

cd /rgf/RGF/build

export CXX=/usr/local/bin/g++-8 && export CC=/usr/local/bin/gcc-8

cmake /rgf/RGF /rgf/FastRGF

make

sudo make install

cd /rgf/python-package

sudo python3 setup.py install

After a successful rgf-python installation the user should open an R session and give the following reticulate command to change to the relevant (brew-python) directory (otherwise the RGF package won’t work properly),


reticulate::use_python('/usr/local/bin/python3')


reticulate::py_discover_config()

to validate that a user is in the python version where RGF or FastRGF are installed. Then,


install.packages(RGF)


library(RGF)

to load the R package. It is possible that the following warning in the R session appears if FastRGF is not installed,


UserWarning: Cannot find FastRGF executable files. FastRGF estimators will be unavailable for usage.
  warnings.warn("Cannot find FastRGF executable files. FastRGF estimators will be unavailable for usage.")

Windows OS

NOTE : CURRENTLY THE PACKAGE ON WINDOWS CAN BE USED ONLY FROM THE COMMAND LINE (cmd)

Update the Environment variables ( Control Panel >> System and Security >> System >> Advanced system settings >> Environment variables >> System variables >> Path >> Edit ) by adding ( for instance in case of python 3 ),


C:\Python36;C:\Python36\Scripts


pip3 install --upgrade setuptools

pip3 install -U numpy

pip3 install --upgrade scipy

pip3 install -U scikit-learn


https://git-scm.com/download/win


git clone https://github.com/RGF-team/rgf.git

FastRGF requires a gcc version > 5.0 . To find out the gcc version, open a command prompt (console) and type,

Perform the following steps to upgrade the MinGW (so that simple RGF functions work – but not FastRGF)

Normally MinGW is installed in the C:\ directory. So, first delete the folder C:\MinGW (if it already exists), and then remove the environment variable from (Control Panel >> System and Security >> System >> Advanced system settings >> Environment variables >> System variables >> Path >> Edit) which usually is C:\MinGW\bin. Then download the most recent version of MinGW, and especially the mingw-get-setup.exe which is an automated GUI installer assistant. After the new version is installed successfully, update the environment variable by adding C:\MinGW\bin in (Control Panel >> System and Security >> System >> Advanced system settings >> Environment variables >> System variables >> Path >> Edit). Then open a new command prompt (console) and type,

A word of caution, If Rtools is already installed then make sure that it does not point to an older version of gcc. Just observe the Path field of the environment variables (accessible as explained previously).

Perform the following steps only in case that a FastRGF installation is desired and gcc version is < 5.0

FastRGF works only with MinGW-w64 because only this version provides POSIX threads. It can be downloaded from the project’s official SourceForge page. After a successful download and installation the user should also update the environment variables field in (Control Panel >> System and Security >> System >> Advanced system settings >> Environment variables >> System variables >> Path >> Edit) by adding the following path (assuming the software is installed in C:\Program Files (x86) folder),


C:\Program Files (x86)\mingw-w64\i686-7.2.0-posix-dwarf-rt_v5-rev1\mingw32\bin

First download cmake for Windows, win64-x64 Installer. Once the file is downloaded run the .exe file and during installation make sure to add CMake to the system PATH for all users.

Before the installation of rgf I might have to remove Rtools environment variables, such as C:\Rtools\bin (accessible as explained previously), otherwise errors might occur.

Installation of RGF, FastRGF and rgf_python [ assuming the installation takes place in the c:/ directory ]

Open a console with administrator privileges (right click on cmd and run as administrator), then



# download the most recent version of rgf-python from the GitHub repository 
#--------------------------------------------------------------------------

git clone http://github.com/RGF-team/rgf.git



# then navigate to 
#-----------------

cd /rgf/RGF/

mkdir bin

cd c:/


# then download the latest "rgf.exe" from https://github.com/RGF-team/rgf/releases and place the "rgf.exe" inside the previously created "bin" folder ( /rgf/RGF/bin )



# installation of RGF
#--------------------

cd /rgf/RGF/build

mingw32-make

cd c:/



# installation of FastRGF
#------------------------

cd /rgf/FastRGF/

mkdir build

cd build


# BEFORE PROCEEDING WITH cmake MAKE SURE THAT THE "Rtools" folder IS NOT IN THE SAME DIRECTORY (IF THAT IS THE CASE THEN REMOVE IT TEMPORARILY, i.e. copy-paste the "Rtools" folder somewhere else)


cmake .. -G "MinGW Makefiles"

mingw32-make

mingw32-make install

cd c:/


# IF APPLICABLE, PASTE THE "Rtools" FOLDER IN THE INITIAL LOCATION / DIRECTORY


# installation of rgf-python
#---------------------------

cd rgf/python-package

python setup.py install

to observe if rgf is installed properly. Then continue with the installation of the RGF package,


install.packages(RGF)

On windows the user can take advantage of the RGF package currently only from within the command prompt (console). First, find the full path of the installation location of R (possible if someone right-clicks in the R short-cut (probably on Desktop) and navigates to properties >> shortcut >> target). In case, for instance, that R is located in C:\Program Files\R\R-3.4.0\bin\x64\R, then, by opening a command prompt (console) and giving,


cd C:\Program Files\R\R-3.4.0\bin\x64\

R

library(RGF)

Installation of the RGF package


install.packages('RGF')

and to download the latest version from GitHub use the install_github function of the devtools package,


devtools::install_github(repo = 'RGF-team/rgf', subdir = 'R-package')

RGF (Regularized Greedy Forest)

System Requirements

Debian/Ubuntu/Fedora

Mac OS X

Windows OS

Installation of the RGF package