Commit 9b4c90ee authored by Martin Reinecke's avatar Martin Reinecke


parent 550aa47c
Pipeline #24557 canceled with stage
in 12 minutes and 27 seconds
......@@ -64,14 +64,16 @@ Installation
### Requirements
- [Python]( (v2.7.x or 3.5.x)
- [NumPy](
- [pyFFTW](
- [Python]( (v2.7.x or 3.5.x)
- [NumPy](
- [pyFFTW](
Optional dependencies:
- [pyHealpix](
- [mpi4py](
- [matplotlib](
- [pyHealpix]( (for harmonic
transforms involving domains on the sphere)
- [mpi4py]( (for MPI-parallel execution)
- [matplotlib]( (for field plotting)
- [SciPy]( (for additional minimization algorithms)
### Sources
......@@ -81,22 +83,46 @@ switching to the NIFTy_4 branch:
git clone
git checkout NIFTy_4
### Installation via pip
### Installation
It is possible to simply install NIFTy with its mandatory dependencies via the command
In the following, we assume a Debian-based distribution. For other
distributions, the "apt" lines will need slight changes.
NIFTy4 and its mandatory dependencies can be installed via:
sudo apt-get install git libfftw3-dev python python-pip python-dev
pip install --user git+
The optional dependencies can be installed via
(Note: if you encounter problems related to pyFFTW, make sure that you are using
a pip-installed pyFFTW package! Some distributions are unfortunately shipping
an incorrectly configured pyFFTW package, which does not cooperate with the
installed FFTW3 libraries)
pip install --user mpi4py
Plotting support is added via:
pip install --user matplotlib
Support for spherical harmonic transforms is added via:
pip install --user git+
MPI support is added via:
sudo apt-get install openmpi-bin libopenmpi-dev
pip install --user mpi4py
Scipy-based minimizers are enabled via:
pip install --user scipy
### Installation for Python 3
If you want to run NIFTy with Python 3, you need to make the following changes
to the instructions above:
- in all `apt-get` commands, replace `python-*` by `python3-*`
- in all `pip` commands, replace `pip` by `pip3`
### Running the tests
In oder to run the tests one needs two additional packages:
pip install --user nose parameterized
pip install --user nose parameterized coverage
Afterwards the tests (including a coverage report) can be run using the
following command in the repository root:
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