make FFTW optional

Dockerfile

@@ -12,8 +12,6 @@ RUN apt-get update && apt-get install -y \
     python3-coverage python3-pytest python3-pytest-cov \
     # Optional NIFTy dependencies
     openmpi-bin libopenmpi-dev python3-mpi4py \
-    # Packages needed for NIFTy
-  && pip3 install pyfftw \
   # Optional NIFTy dependencies
   && pip3 install git+https://gitlab.mpcdf.mpg.de/ift/pyHealpix.git \
   # Testing dependencies

README.md

@@ -39,11 +39,11 @@ Installation
 
 - [Python 3](https://www.python.org/) (3.5.x or later)
 - [SciPy](https://www.scipy.org/)
-- [pyFFTW](https://pypi.python.org/pypi/pyFFTW)
 
 Optional dependencies:
 - [pyHealpix](https://gitlab.mpcdf.mpg.de/ift/pyHealpix) (for harmonic
     transforms involving domains on the sphere)
+- [pyFFTW](https://pypi.python.org/pypi/pyFFTW)
 - [mpi4py](https://mpi4py.scipy.org) (for MPI-parallel execution)
 - [matplotlib](https://matplotlib.org/) (for field plotting)
 
@@ -61,7 +61,7 @@ distributions, the "apt" lines will need slight changes.
 
 NIFTy5 and its mandatory dependencies can be installed via:
 
-    sudo apt-get install git libfftw3-dev python3 python3-pip python3-dev
+    sudo apt-get install git python3 python3-pip python3-dev
     pip3 install --user git+https://gitlab.mpcdf.mpg.de/ift/NIFTy.git@NIFTy_5
 
 (Note: If you encounter problems related to `pyFFTW`, make sure that you are
@@ -73,6 +73,22 @@ Plotting support is added via:
 
     pip3 install --user matplotlib
 
+FFTW support is added via:
+
+    sudo apt-get install libfftw3-dev
+    pip3 install --user pyfftw
+
+To actually use FFTW in your Nifty calculations, you need to call
+
+    `nifty5.fft.enable_fftw()`
+
+at the beginning of your code.
+
+(Note: If you encounter problems related to `pyFFTW`, make sure that you are
+using a pip-installed `pyFFTW` package. Unfortunately, some distributions are
+shipping an incorrectly configured `pyFFTW` package, which does not cooperate
+with the installed `FFTW3` libraries.)
+
 Support for spherical harmonic transforms is added via:
 
     pip3 install --user git+https://gitlab.mpcdf.mpg.de/ift/pyHealpix.git
@@ -86,7 +102,7 @@ MPI support is added via:
 
 To run the tests, additional packages are required:
 
-    sudo apt-get install python3-coverage python3-parameterized python3-pytest python3-pytest-cov
+    sudo apt-get install python3-coverage python3-pytest python3-pytest-cov
 
 Afterwards the tests (including a coverage report) can be run using the
 following command in the repository root:

nifty5/fft.py

@@ -19,23 +19,57 @@ from .utilities import iscomplextype
 import numpy as np
 
 
-_use_fftw = True
-
-
-if _use_fftw:
-    import pyfftw
-    from pyfftw.interfaces.numpy_fft import fftn, rfftn, ifftn
-    pyfftw.interfaces.cache.enable()
-    pyfftw.interfaces.cache.set_keepalive_time(1000.)
-    # Optional extra arguments for the FFT calls
-    # if exact reproducibility is needed,
-    # set "planner_effort" to "FFTW_ESTIMATE"
-    import os
-    nthreads = int(os.getenv("OMP_NUM_THREADS", "1"))
-    _fft_extra_args = dict(planner_effort='FFTW_ESTIMATE', threads=nthreads)
-else:
-    from numpy.fft import fftn, rfftn, ifftn
-    _fft_extra_args = {}
+_use_fftw = False
+_fftw_prepped = False
+_fft_extra_args = {}
+
+
+def enable_fftw():
+    _use_fftw = True
+
+
+def _init_pyfftw():
+    global _fft_extra_args, _fftw_prepped
+    if not _fftw_prepped:
+        import pyfftw
+        from pyfftw.interfaces.numpy_fft import fftn, rfftn, ifftn
+        pyfftw.interfaces.cache.enable()
+        pyfftw.interfaces.cache.set_keepalive_time(1000.)
+        # Optional extra arguments for the FFT calls
+        # if exact reproducibility is needed,
+        # set "planner_effort" to "FFTW_ESTIMATE"
+        import os
+        nthreads = int(os.getenv("OMP_NUM_THREADS", "1"))
+        _fft_extra_args = dict(planner_effort='FFTW_ESTIMATE',
+                               threads=nthreads)
+        _fftw_prepped = True
+
+
+def fftn(a, axes=None):
+    if _use_fftw:
+        from pyfftw.interfaces.numpy_fft import fftn
+        _init_pyfftw()
+        return fftn(a, axes=axes, **_fft_extra_args)
+    else:
+        return np.fft.fftn(a, axes=axes)
+
+
+def rfftn(a, axes=None):
+    if _use_fftw:
+        from pyfftw.interfaces.numpy_fft import rfftn
+        _init_pyfftw()
+        return rfftn(a, axes=axes, **_fft_extra_args)
+    else:
+        return np.fft.rfftn(a, axes=axes)
+
+
+def ifftn(a, axes=None):
+    if _use_fftw:
+        from pyfftw.interfaces.numpy_fft import ifftn
+        _init_pyfftw()
+        return ifftn(a, axes=axes, **_fft_extra_args)
+    else:
+        return np.fft.ifftn(a, axes=axes)
 
 
 def hartley(a, axes=None):
@@ -46,7 +80,7 @@ def hartley(a, axes=None):
     if iscomplextype(a.dtype):
         raise TypeError("Hartley transform requires real-valued arrays.")
 
-    tmp = rfftn(a, axes=axes, **_fft_extra_args)
+    tmp = rfftn(a, axes=axes)
 
     def _fill_array(tmp, res, axes):
         if axes is None:
@@ -89,7 +123,7 @@ def my_fftn_r2c(a, axes=None):
     if iscomplextype(a.dtype):
         raise TypeError("Transform requires real-valued input arrays.")
 
-    tmp = rfftn(a, axes=axes, **_fft_extra_args)
+    tmp = rfftn(a, axes=axes)
 
     def _fill_complex_array(tmp, res, axes):
         if axes is None:
@@ -123,4 +157,4 @@ def my_fftn_r2c(a, axes=None):
 
 
 def my_fftn(a, axes=None):
-    return fftn(a, axes=axes, **_fft_extra_args)
+    return fftn(a, axes=axes)

setup.py

@@ -39,8 +39,8 @@ setup(name="nifty5",
       packages=find_packages(include=["nifty5", "nifty5.*"]),
       zip_safe=True,
       license="GPLv3",
-      setup_requires=['future', 'scipy'],
-      install_requires=['future', 'scipy', 'pyfftw>=0.10.4'],
+      setup_requires=['scipy'],
+      install_requires=['scipy'],
       classifiers=[
         "Development Status :: 4 - Beta",
         "Topic :: Utilities",