Documentation 1.7.0 > Installation

Installation

DIPY is in active development. You can install it from our latest release, but you may find that the release has gotten well behind the current development - at least - we hope so - if we’re developing fast enough!

If you want to install the latest and greatest from the bleeding edge of the development, skip to Installing from source. If you just want to install a released version, read on for your platform.

Installing a release

If you are on Debian or Ubuntu Linux we recommend you try Using Anaconda: first. Otherwise please try Using pip:.

Using Anaconda:

On all platforms, you can use Anaconda to install DIPY. To do so issue the following command in a terminal:

conda install -c conda-forge dipy

Some of the visualization methods require the FURY library and this can be installed separately (for the time being only on Python 3.4+):

conda install -c conda-forge fury

Using packages:

Windows

  1. First, install the python library dependencies. One easy way to do that is to use the Anaconda distribution (see below for Alternatives to Anaconda).

  2. Even with Anaconda installed, you will still need to install the nibabel library, which supports reading and writing of neuroimaging data formats. Open a terminal and type:

    pip install nibabel

  3. Finally, we are ready to install DIPY itself. Same as with nibabel above, we will type at the terminal shell command line:

    pip install dipy

    When the installation has finished we can check if it is successful in the following way. From a Python console script try:

    >>> import dipy

    This should work with no error.

  4. Some of the visualization methods require the FURY library and this can be installed by doing

    pip install fury

OSX

  1. To use DIPY, you need to have some Dependencies installed. First of all, make sure that you have installed the Apple Xcode developer tools. You’ll need those to install all the following dependencies.

  2. Next, install the python library dependencies. One easy way to do that is to use the Anaconda distribution (see below for Alternatives to Anaconda).

  3. Even with Anaconda installed, you will still need to install the nibabel library, which supports the reading and writing of neuroimaging data formats. Open a terminal and type:

    pip install nibabel

  4. Finally, we are ready to install DIPY itself. Same as with nibabel above, we will type at the terminal shell command line:

    pip install dipy

    When the installation has finished we can check if it is successful in the following way. From a Python console script try:

    >>> import dipy

    This should work with no error.

  5. Some of the visualization methods require the FURY library and this can be installed by doing:

    pip install fury

Linux

For Debian, Ubuntu and Mint set up the NeuroDebian repositories - see NeuroDebian how to. Then:

sudo apt-get install python-dipy

We hope to get packages for the other Linux distributions, but for now, please try Using pip: instead.

Using pip:

This method should work under Linux, Mac OS X, and Windows.

Please install numpy and scipy using their respective binary installers if you haven’t already.

For Windows and Mac OSX you can use Anaconda to get numpy, scipy, cython and lots of other useful python modules. Anaconda is a big package but will install many tools and libraries that are useful for scientific processing.

When you have numpy, scipy and cython installed then try:

pip install nibabel
pip install dipy

Then from any python console or script try:

>>> import dipy

Support

Contact us:

Do these installation instructions work for you? For any problems/suggestions please let us know by sending us an e-mail to the nipy mailing list with the subject line starting with [DIPY].

Common problems:

Multiple installations

Make sure that you have uninstalled all previous versions of DIPY before installing a new one. A simple and general way to uninstall DIPY is by removing the installation directory. You can find where DIPY is installed by using:

import dipy
dipy.__file__

and then remove the DIPY directory that contains that file.

Alternatives to Anaconda

If you have problems installing Anaconda we recommend using Canopy or pythonxy.

Memory issues

DIPY can process large diffusion datasets. For this reason, we recommend using a 64bit operating system that can allocate larger memory chunks than 32bit operating systems. If you don’t have a 64bit computer that is okay DIPY works with 32bit too.

Note on python versions

Most DIPY functionality can be used with Python versions 2.6 and newer, including Python 3. However, some visualization functionality depends on FURY, which only supports Python 3 in versions 7 and newer.

Installing from source

Getting the source

More likely you will want to get the source repository to be able to follow the latest changes. In that case, you can use:

git clone https://github.com/dipy/dipy.git

For more information about this see Following the latest source.

After you’ve cloned the repository, you will have a new directory, containing the DIPY setup.py file, among others. We’ll call this directory - that contains the setup.py file - the DIPY source root directory. Sometimes we’ll also call it the <dipy root> directory.

Building and installing

Install from source (all operating systems)

Change directory into the DIPY source root directory.

To clean your directory from temporary file, use:

git clean -fxd

This command will delete all files not present in your github repository.

Then, complete your installation by using this command:

pip install --user -e .
This command will do the following :

  • remove the old dipy installation if present

  • build dipy (equivalent to python setup.py build_ext –inplace)

  • install dipy locally on your user environment

Install from source for Unix (e.g Linux, OSX)

Change directory into the DIPY source root directory.

To install for the system:

python setup.py install

To build DIPY in the source tree (locally) so you can run the code in the source tree (recommended for following the latest source) run:

python setup.py build_ext --inplace

add the DIPY source root directory into your PYTHONPATH environment variable. Search google for PYTHONPATH for details or see python module path for an introduction.

When adding dipy to the PYTHONPATH, we usually add the PYTHONPATH at the end of ~/.bashrc or (OSX) ~/.bash_profile so we don’t need to retype it every time. This should look something like:

export PYTHONPATH="/home/user_dir/Devel/dipy:$PYTHONPATH"

After changing the ~/.bashrc or (OSX) ~/.bash_profile try:

source ~/.bashrc

or:

source ~/.bash_profile

so that you can have immediate access to DIPY without needing to restart your terminal.

Ubuntu/Debian

sudo apt-get install python-dev python-setuptools
sudo apt-get install python-numpy python-scipy
sudo apt-get install cython

then:

sudo pip install nibabel

(we need the latest version of this one - hence pip rather than apt-get).

You might want the optional packages too (highly recommended):

sudo apt-get install ipython python-h5py python-vtk python-matplotlib

Now follow Install from source for Unix (e.g Linux, OSX).

Fedora / Mandriva maybe Redhat

Same as above but use yum rather than apt-get when necessary.

Now follow Install from source for Unix (e.g Linux, OSX).

Windows

Anaconda is probably the easiest way to install the dependencies that you need. To build from source, you will also need to install the exact compiler which is used with your specific version of python.

For getting this information, type this command in shell like cmd or Powershell:

python -c "import platform;print(platform.python_compiler())"

This command should print information of this form:

MSC v.1900 64 bit (AMD64)

Now that you find the relevant compiler, you have to install the VisualStudioBuildTools by respecting the following table:

Visual C++ 2008  (9.0)          MSC_VER=1500
Visual C++ 2010 (10.0)          MSC_VER=1600
Visual C++ 2012 (11.0)          MSC_VER=1700
Visual C++ 2013 (12.0)          MSC_VER=1800
Visual C++ 2015 (14.0)          MSC_VER=1900
Visual C++ 2017 (15.0)          MSC_VER=1910

After the VisualStudioBuildTools installation, restart a command shell and change directory into the DIPY source root directory.

To install into your system:

python setup.py install

To install inplace - so that DIPY is running out of the source code directory:

python setup.py develop

(this is the mode we recommend for following the latest source code). If you get an error with python setup.py develop make sure you have installed setuptools.

If you get an error saying “unable to find vcvarsall.bat” then you need to check your environment variable PATH or reinstall VisualStudioBuildTools. Setuptools should automatically detect the compiler and use it.

OSX

Make sure you have Xcode and Anaconda installed.

From here follow the Install from source for Unix (e.g Linux, OSX) instructions.

OpenMP with OSX

OpenMP is a standard library for efficient multithreaded applications. This is used in DIPY for speeding up many different parts of the library (e.g., denoising and bundle registration). If you do not have an OpenMP-enabled compiler, you can still compile DIPY from source using the above instructions, but it might not take advantage of the multithreaded parts of the code. To be able to compile DIPY from source with OpenMP on Mac OSX, you will have to do a few more things. First of all, you will need to install the Homebrew package manager. Next, you will need to install and configure the compiler. You have two options: using the GCC compiler or the CLANG compiler. This depends on your python installation:

Under Anaconda

If you are using Anaconda, you will need to use GCC. The first option is to run the following command:

conda install gcc

After this installation, gcc will be your default compiler in Anaconda environment.

The second option is to install gcc via homebrew. Run the following:

brew reinstall gcc --without-multilib

This should take about 45 minutes to complete. Then add to your bash configuration (usually in ~/.bash_profile), the following:

export PATH="/usr/local/Cellar/gcc/5.2.0/bin/gcc-5:$PATH"
Under Homebrew Python or python.org Python

If you are already using the Homebrew Python, or the standard python.org Python, you will need to use the CLANG compiler with OMP. Run:

brew install clang-omp

And then edit the setup.py file to include the following line (e.g., on line 14, at the top of the file, but after the initial imports):

os.environ['CC'] = '/usr/local/bin/clang-omp'
Building and installing

Whether you are using Anaconda or Hombrew/python.org Python, you will need to then run python setup.py install. When you do that, it should now compile the code with this OpenMP-enabled compiler, and things should go faster!

Testing

If you want to run the tests:

sudo pip install pytest

Then (in python or ipython):

>>> import dipy
>>> dipy.test()

You can also run the examples in <dipy root>/doc.

Documentation (Unix only)

To build the documentation in HTML in your computer you will need to do:

sudo pip install sphinx

Then change directory to <dipy root> and:

cd doc
make clean
make html

Tip

Building the entire DIPY documentation takes a few hours. You may want to skip building the documentation for the examples, which will reduce the documentation build time to a few minutes. You can do so by executing:

make -C . html-after-examples

Troubleshooting

If you encounter the following error when trying to build the documentation:

tools/build_modref_templates.py dipy reference
*WARNING* API documentation not generated: Can not import dipy
tools/docgen_cmd.py dipy reference_cmd
*WARNING* Command line API documentation not generated: Cannot import dipy
Build API docs...done.
cd examples_built && ../../tools/make_examples.py
Traceback (most recent call last):
  File "../../tools/make_examples.py", line 33, in <module>
    import dipy
ModuleNotFoundError: No module named 'dipy'

it is probably due to a conflict between the picked Sphinx version: this happens when the system’s Sphinx package is used instead of the virtual environment’s Sphinx package, and the former trying to import a DIPY version in the system: the Sphinx package used should correspond to that of the virtual environment where DIPY lives. This can be solved by specifying the path to the Sphinx package in the virtual environment:

make html SPHINXBUILD='python <path_to_sphinx>/sphinx-build'