Downloading and Installing

Ivy is a Python package, and can be as simple to install as:

$ pip install git+git://github.com/rhr/ivy.git

However, ivy requires quite a bit of third-party open source software to work. The following instructions assume a Debian-based Linux system like Ubuntu. On a Mac, you can use Anaconda to install dependencies.

More detailed instructions for Mac and Windows are in the works.

Install Guide

Windows

To install ivy on Windows, you must first install a few dependencies.

First, you must have Python 2.7 installed. ivy is currently not compatible with Python 3.

The easiest way to install ivy and its dependencies is to use pip. Python 2.7.9+ is shipped with pip. If you have an earlier version of python, you must install pip. Instructions can be found here: How to install pip on Windows <http://stackoverflow.com/questions/4750806/how-to-install-pip-on-windows>

You may need to add the path to pip to your PATH variable. If you have a newer version of python, pip will be automatically installed into C:\Python27\Scripts\pip. To add this to your PATH variable, run the following:

setx PATH "%PATH%;C:\Python27\Scripts"

Once pip is installed, dependencies can be installed as follows:

First, install Microsoft Visual C++ Compiler for Python 2.7 if you do not have it already: http://www.microsoft.com/en-us/download/details.aspx?id=44266

Then, install the package dependencies .. code-block:: bash

pip install matplotlib :: This will also install numpy pip install biopython pip install pyparsing pip install lxml pip install bokeh pip install pydf

Next you need to install SciPy. It may be easiest to download the binary from here: http://www.lfd.uci.edu/~gohlke/pythonlibs/. Look for either scipy‑0.16.0‑cp27‑none‑win32.whl or scipy‑0.16.0‑cp27‑none‑win_amd64.whl, depending on whether you have 32- or 64-bit python. Then run:

..code-block::bash

pip install /path/to/binary/scipy‑0.16.0‑cp27‑none‑win32.whl

It is recommended that you run ivy using ipython.

..code-block::bash

pip install ipython

It is also recommended that you run ivy in a VirtualEnvironment

..code-block::bash

pip install virtualenv :: install virtualenv virtualenv mypy :: Create the virtualenvironment mypyScriptsactivate :: Run the virutalenvironment

Now you may install ivy

..code-block::bash

pip install git+git://github.com/rhr/ivy.git@christie-master

Dependencies

ivy depends on several Python libraries for numerical and other kinds of specialized functions.

• matplotlib (>=1.0) - cross-platform, toolkit-independent graphics for interactive visualization
• scipy - high-level scientific modules for statistics, optimization, etc.
• numpy - fast numerical functions for N-dimensional arrays
• biopython - for handling molecular sequences: converting between formats, querying and retrieving data from GenBank, etc.
• pyparsing - convenience functions for parsing text
• bokeh - visualization

These are easily installed by:

$ sudo apt-get install python-matplotlib python-scipy python-numpy python-biopython python-pyparsing

However, the precompiled packages available for your system may not be up to date - in particular, your distribution may not provide matplotlib 1.0 or higher. In which case you are better off compiling your own in a virtual Python environment using virtualenv and pip.

Before proceeding, let’s make sure we have everything we need to compile the modules:

$ sudo apt-get build-dep python-matplotlib python-scipy python-numpy python-biopython python-pyparsing

Preparing a virtual Python environment

virtualenv allows you to create sandboxed Python environments in which it is safe to install bleeding-edge third-party modules without touching any system files.

$ sudo apt-get install python-virtualenv

or

$ sudo easy_install virtualenv

pip is an improved replacement of easy_install, and can be installed by:

$ sudo apt-get install python-pip

or

$ sudo easy_install pip

The next step is to create a virtual Python environment:

$ virtualenv mypy

where mypy is an arbitrary name. The environment can be activated by ‘sourcing’ the activate script:

$ . mypy/bin/activate

To make it your default Python environment, simply prepend $HOME/mypy/bin to your PATH, e.g., in your .bashrc file:

$ export PATH=$HOME/mypy/bin:$PATH

Once the environment is active, we can install the modules themselves:

$ for module in matplotlib scipy numpy biopython pyparsing ; do
$    pip install $module ;
$ done

You will also want to install IPython in your virtual environment:

$ pip install ipython

Installing ivy

Finally, once the dependencies have been satisfied, we can install ivy:

$ pip install git+git://github.com/rhr/ivy.git

Source code

Ivy source code is hosted at https://github.com/rhr/ivy