install.rst

Use pre-built packages

pip

If you only need python interface, use pip. This is the easiest way to install Python interface. This solution has been tested for Linux and MacOSX.

pip install pymoose

We also build moose package with additional components such as gui and moogli.

Linux

We recommend that you use our repositories hosted at Open Build Service. Packages for most linux distributions are available. Visit this page to pick your distribution and follow instructions.

Note

moogli (tool to visualize network activity) is not available for CentOS-6.

Mac OSX

MacOSX support for moose-gui is not complete yet. However, the python-scripting interface can be installed on OSX using homebrew

$ brew tap BhallaLab/moose
$ brew install moose

Or alternatively, via pip

$ pip install pymoose --user

Docker Images

Docker images of stable version are available from public repository.

$ docker pull bhallalab/moose
$ docker run -it --rm -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=$DISPLAY bhallalab/moose

This will launch xterm; run moosegui in terminal to lauch the GUI.

Building MOOSE

In case your distribution is not listed on our repository page , or if you want to build the latest development code, read on.

First, you need to get the source code. You can use git (clone the repository) or download snapshot of github repo by clicking on this link.

$ git clone https://github.com/BhallaLab/moose

(This will create folder called "moose") Or,

$ wget https://github.com/BhallaLab/moose/archive/master.zip
$ unzip master.zip

If you don't want latest snapshot of MOOSE, you can download other released versions from here.

Install dependencies

Next, you need to install required dependencies. Depending on your OS, names of following packages may vary.

Core MOOSE

• Required:

  • cmake (version 2.8 or higher)
  • g++ (>= 4.6.x) For building the C++ MOOSE core.
  • gsl-1.16 or higher.

• Optional

  • HDF5 (>=1.8.x) For reading and writing data into HDF5 based formats

Python interface for core MOOSE API (pymoose)

• Required

  • Python2 ( >= 2.7.x) For building the MOOSE Python bindings
  • Python-dev ( >= 2.7.x) Python development headers and libraries, e.g. python-dev or python-devel
  • NumPy ( >= 1.6.x) For array interface, e.g. python-numpy or numpy

• Optional

  • NetworkX (1.x) For automatical layout
  • pygraphviz For automatic layout for chemical models
  • Matplotlib (>=1.1.x) For plotting simulation results
  • python-libsbml For reading and writing chemical models from and into SBML format

Most of the dependencies can be installed using package manager.

On Debian/Ubuntu

$ sudo apt-get install libhdf5-dev cmake libgsl0-dev libpython-dev python-numpy

Note

Ubuntu 12.04 does not have required version of gsl (required 1.16 or higher, available 1.15). On Ubuntu 16.04, package name is libgsl-dev.

On CentOS/Fedora/RHEL/Scientific Linux

$ sudo yum install hdf5-devel cmake libgsl-dev python-devel python-numpy

On OpenSUSE

$ sudo zypper install hdf5-devel cmake libgsl-dev python-devel python-numpy

build moose

$ cd /to/moose_directory/moose-core/
$ mkdir _build
$ cd _build
$ cmake  ..
$ make
$ ctest --output-on-failure  # optional
$ sudo make install

This will build pyMOOSE (MOOSE's python extention), ctest will run few tests to check if build process was successful.

Note

To install MOOSE into non-standard directory, pass additional argument -DCMAKE_INSTALL_PREFIX=path/to/install/dir to cmake

$ cmake -DCMAKE_INSTALL_PREFIC=$HOME/.local ..

To use different version of python

$ cmake -DPYTHON_EXECUTABLE=/opt/python3/bin/python3 ..

After that installation is pretty easy

$ sudo make install

If everything went fine, you should be able to import moose in python shell.

>>> import moose

Graphical User Interface (GUI)

If you have installed the pre-built package, then you already have the GUI. You can launch it by runnung moosegui command in terminal.

You can get the source of moose-gui from here. You can download it either by clicking on this link or by using git

$ git clone https://github.com/BhallaLab/moose-gui

Alternatively the moose-gui folder exists within the moose folder downloaded and built earlier in the installation process. It can be found under location_of_moose_folder/moose/moose-gui/.

Below are packages which you may want to install to use MOOSE Graphical User Interface.

• Required:

  • PyQt4 (4.8.x) For Python GUI
  • Matplotlib ( >= 1.1.x) For plotting simulation results
  • NetworkX (1.x) For automatical layout
  • suds/suds-jurko (0.4) For accessing models hosted on biomodels database.

• Optional:

  • python-libsbml For reading and writing signalling models from and into SBML format

On Ubuntu/Debian, these can be installed with

$ sudo apt-get install python-matplotlib python-qt4

On CentOS/Fedora/RHEL

$ sudo yum install python-matplotlib python-qt4

Now you can fire up the GUI

$ cd /to/moose-gui
$ python mgui.py

Note

If you have installed moose package, then GUI is launched by running following commnad:

$ moosegui

Building moogli

moogli is subproject of MOOSE for visualizing models. More details can be found here.

Moogli is part of moose package. Building moogli can be tricky because of multiple depednecies it has.

• Required

  • OSG (3.2.x) For 3D rendering and simulation of neuronal models
  • Qt4 (4.8.x) For C++ GUI of Moogli

To get the latest source code of moogli, click on this link.

Moogli depends on OpenSceneGraph (version 3.2.0 or higher) which may not be easily available for your operating system. For this reason, we distribute required OpenSceneGraph with moogli source code.

Depending on distribution of your operating system, you would need following packages to be installed.

On Ubuntu/Debian

$ sudo apt-get install python-qt4-dev python-qt4-gl python-sip-dev libqt4-dev

On Fedora/CentOS/RHEL

$ sudo yum install sip-devel PyQt4-devel qt4-devel libjpeg-devel PyQt4

On openSUSE

$ sudo zypper install python-sip python-qt4-devel libqt4-devel python-qt4

After this, building and installing moogli should be as simple as

$ cd /path/to/moogli
$ mkdir _build
$ cd _build
$ cmake ..
$ make
$ sudo make install

If you run into troubles, please report it on our github repository.