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 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.
If you are on Debian or Ubuntu Linux we recommend you try Using Anaconda: first. Otherwise please try Using pip:.
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
First, install the python library dependencies. One easy way to do that is to use the Anaconda distribution (see below for Alternatives to Anaconda).
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
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.
Some of the visualization methods require the FURY library and this can be installed by doing
pip install fury
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.
Next, install the python library dependencies. One easy way to do that is to use the Anaconda distribution (see below for Alternatives to Anaconda).
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
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.
Some of the visualization methods require the FURY library and this can be installed by doing:
pip install fury
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.
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 module. 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
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].
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.
If you have problems installing Anaconda we recommend using Canopy or pythonxy.
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/nipy/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.
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 .
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.
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).
Same as above but use yum rather than apt-get when necessary.
Now follow Install from source for Unix (e.g Linux, OSX).
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 an 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.
Distutils should automatically detect the compiler and use it.
Make sure you have Xcode and Anaconda installed.
From here follow the Install from source for Unix (e.g Linux, OSX) instructions.
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:
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"
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'
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!
If you want to run the tests:
sudo pip install pytest nose
Then (in python or ipython):
>>> import dipy
>>> dipy.test()
You can also run the examples in <dipy root>/doc.