merge master

.gitlab-ci.yml

@@ -14,21 +14,22 @@ before_script:
   - chmod +x ci/*.sh
   - ci/install_basics.sh
   - pip install --upgrade -r ci/requirements.txt
+  - pip3 install --upgrade -r ci/requirements.txt
 
 
 test_min:
   stage: test
   script:
-    - python setup.py build_ext --inplace
     - nosetests -vv
+    - nosetests3 -vv
 
 test_mpi:
   stage: test
   script:
     - ci/install_pyHealpix.sh
     - ci/install_mpi4py.sh
-    - python setup.py build_ext --inplace
     - nosetests -vv
+    - nosetests3 -vv
 
 test_mpi_fftw:
   stage: test
@@ -36,8 +37,8 @@ test_mpi_fftw:
     - ci/install_pyHealpix.sh
     - ci/install_mpi4py.sh
     - ci/install_pyfftw.sh
-    - python setup.py build_ext --inplace
     - nosetests -vv
+    - nosetests3 -vv
 
 test_mpi_fftw_hdf5:
   stage: test
@@ -46,9 +47,10 @@ test_mpi_fftw_hdf5:
     - ci/install_mpi4py.sh
     - ci/install_pyfftw.sh
     - ci/install_h5py.sh
-    - python setup.py build_ext --inplace
     - mpiexec --allow-run-as-root -n 2 nosetests -x
+    - mpiexec --allow-run-as-root -n 2 nosetests3 -x
     - mpiexec --allow-run-as-root -n 4 nosetests -x
+    - mpiexec --allow-run-as-root -n 4 nosetests3 -x
     - nosetests -x --with-coverage --cover-package=nifty --cover-branches
     - >
       coverage report | grep TOTAL | awk '{ print "TOTAL: "$6; }'

ci/install_basics.sh

 #!/bin/bash
 
-apt-get install -y build-essential python python-pip python-dev git autoconf libtool gsl-bin libgsl-dev wget
+apt-get install -y build-essential python python-pip python-dev git autoconf libtool gsl-bin libgsl-dev wget python3 python3-pip python3-dev python3-nose

ci/install_mpi4py.sh

@@ -2,3 +2,4 @@
 
 apt-get install -y openmpi-bin libopenmpi-dev
 pip install mpi4py
+pip3 install mpi4py

ci/install_pyHealpix.sh

@@ -2,4 +2,5 @@
 
 git clone https://gitlab.mpcdf.mpg.de/ift/pyHealpix.git
 (cd pyHealpix && autoreconf -i && ./configure --enable-openmp && make -j4 install)
+(cd pyHealpix && autoreconf -i && PYTHON=python3 ./configure --enable-openmp && make -j4 install)
 rm -rf pyHealpix

ci/install_pyfftw.sh

@@ -4,4 +4,5 @@ apt-get install -y libatlas-base-dev libfftw3-bin libfftw3-dev libfftw3-double3
 
 git clone -b mpi https://github.com/fredros/pyFFTW.git
 (cd pyFFTW && CC=mpicc python setup.py build_ext install)
+(cd pyFFTW && CC=mpicc python3 setup.py build_ext install)
 rm -rf pyFFTW

demos/paper_demos/cartesian_wiener_filter.py

@@ -7,8 +7,9 @@ from nifty import plotting
 from keepers import Repository
 
 if __name__ == "__main__":
+    ift.nifty_configuration['default_distribution_strategy'] = 'fftw'
 
-    signal_to_noise = 1.5 # The signal to noise ratioa
+    signal_to_noise = 1.5 # The signal to noise ratio
 
 
     # Setting up parameters    |\label{code:wf_parameters}|
@@ -29,7 +30,7 @@ if __name__ == "__main__":
     harmonic_space_1 = ift.FFTOperator.get_default_codomain(signal_space_1)
     fft_1 = ift.FFTOperator(harmonic_space_1, target=signal_space_1,
                             domain_dtype=np.complex, target_dtype=np.complex)
-    power_space_1 = ift.PowerSpace(harmonic_space_1, distribution_strategy='fftw')
+    power_space_1 = ift.PowerSpace(harmonic_space_1)
 
     mock_power_1 = ift.Field(power_space_1, val=power_spectrum_1,
                              distribution_strategy='not')
@@ -67,20 +68,18 @@ if __name__ == "__main__":
                                         distribution_strategy='not')
 
     diagonal = mock_power.power_synthesize(spaces=(0, 1), mean=1, std=0,
-                                           real_signal=False,
-                                           distribution_strategy='fftw')**2
+                                           real_signal=False)**2
 
     S = ift.DiagonalOperator(domain=(harmonic_space_1, harmonic_space_2),
                              diagonal=diagonal)
 
 
     np.random.seed(10)
-    mock_signal = fft(mock_power.power_synthesize(real_signal=True,
-                                                  distribution_strategy='fftw'))
+    mock_signal = fft(mock_power.power_synthesize(real_signal=True))
 
     # Setting up a exemplary response
     N1_10 = int(N_pixels_1/10)
-    mask_1 = ift.Field(signal_space_1, val=1., distribution_strategy='fftw')
+    mask_1 = ift.Field(signal_space_1, val=1.)
     mask_1.val[N1_10*7:N1_10*9] = 0.
 
     N2_10 = int(N_pixels_2/10)
@@ -95,12 +94,10 @@ if __name__ == "__main__":
 
     # Setting up the noise covariance and drawing a random noise realization
     N = ift.DiagonalOperator(data_domain, diagonal=mock_signal.var()/signal_to_noise,
-                             bare=True,
-                             distribution_strategy='fftw')
+                             bare=True)
     noise = ift.Field.from_random(domain=data_domain, random_type='normal',
                                   std=mock_signal.std()/np.sqrt(signal_to_noise),
-                                  mean=0,
-                                  distribution_strategy='fftw')
+                                  mean=0)
     data = R(mock_signal) + noise #|\label{code:wf_mock_data}|
 
     # Wiener filter
@@ -133,7 +130,7 @@ if __name__ == "__main__":
 
     plotter.plot.zmin = 0.
     plotter.plot.zmax = 3.
-    sm = ift.SmoothingOperator(plot_space, sigma=0.03)
+    sm = ift.SmoothingOperator.make(plot_space, sigma=0.03)
     plotter(ift.log(ift.sqrt(sm(ift.Field(plot_space, val=variance.val.real)))), path='uncertainty.html')
 
     plotter.plot.zmin = np.real(mock_signal.min());

demos/paper_demos/wiener_filter.py

@@ -57,7 +57,7 @@ if __name__ == "__main__":
     proby = Proby(signal_space, probe_count=800)
     proby(lambda z: fft(wiener_curvature.inverse_times(fft.inverse_times(z))))  #|\label{code:wf_variance_fft_wrap}|
 
-    sm = ift.SmoothingOperator(signal_space, sigma=0.03)
+    sm = ift.SmoothingOperator.make(signal_space, sigma=0.03)
     variance = ift.sqrt(sm(proby.diagonal.weight(-1)))  #|\label{code:wf_variance_weighting}|
 
     repo = Repository('repo_800.h5')

demos/probing.py

 # -*- coding: utf-8 -*-
 
+from __future__ import print_function
 from nifty import Field, RGSpace, DiagonalProberMixin, TraceProberMixin,\
                   Prober, DiagonalOperator
 
@@ -19,12 +20,9 @@ diagOp = DiagonalOperator(domain=x, diagonal=f)
 
 diagProber = DiagonalProber(domain=x)
 diagProber(diagOp)
-print (f - diagProber.diagonal).norm()
+print((f - diagProber.diagonal).norm())
 
 multiProber = MultiProber(domain=x)
 multiProber(diagOp)
-print (f - multiProber.diagonal).norm()
-print f.sum() - multiProber.trace
-
-
-
+print((f - multiProber.diagonal).norm())
+print(f.sum() - multiProber.trace)

nifty/__init__.py

@@ -26,36 +26,34 @@ logger = MPILogger()
 
 # it is important to import config before d2o such that NIFTy is able to
 # pre-create d2o's configuration object with the corrected path
-from config import dependency_injector,\
+from .config import dependency_injector,\
                    nifty_configuration,\
                    d2o_configuration
 
 from d2o import distributed_data_object, d2o_librarian
 
+from .field import Field
 
+from .random import Random
 
-from field import Field
+from .basic_arithmetics import *
 
-from random import Random
+from .nifty_utilities import *
 
-from basic_arithmetics import *
+from .field_types import *
 
-from nifty_utilities import *
+from .energies import *
 
-from field_types import *
+from .minimization import *
 
-from energies import *
+from .spaces import *
 
-from minimization import *
+from .operators import *
 
-from spaces import *
+from .probing import *
 
-from operators import *
+from .sugar import *
 
-from probing import *
+from . import plotting
 
-from sugar import *
-
-import library
-
-import plotting
+from . import library

nifty/basic_arithmetics.py

@@ -16,9 +16,10 @@
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
+from __future__ import division
 import numpy as np
 from d2o import distributed_data_object
-from nifty.field import Field
+from .field import Field
 
 
 __all__ = ['cos', 'sin', 'cosh', 'sinh', 'tan', 'tanh', 'arccos', 'arcsin',

nifty/config/__init__.py

@@ -17,7 +17,7 @@
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
 
-from nifty_config import dependency_injector,\
+from .nifty_config import dependency_injector,\
                          nifty_configuration
 
-from d2o_config import d2o_configuration
+from .d2o_config import d2o_configuration

nifty/config/nifty_config.py

@@ -16,7 +16,7 @@
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
-import matplotlib_init
+from . import matplotlib_init
 
 import os
 

nifty/domain_object.py

@@ -16,14 +16,17 @@
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
+from __future__ import division
 import abc
-from nifty.nifty_meta import NiftyMeta
+from .nifty_meta import NiftyMeta
 
 from keepers import Loggable,\
                     Versionable
+from future.utils import with_metaclass
 
 
-class DomainObject(Versionable, Loggable, object):
+class DomainObject(with_metaclass(NiftyMeta, type('NewBase',
+        (Versionable, Loggable, object), {}))):
     """The abstract class that can be used as a domain for a field.
 
     This holds all the information and functionality a field needs to know
@@ -39,8 +42,6 @@ class DomainObject(Versionable, Loggable, object):
 
     """
 
-    __metaclass__ = NiftyMeta
-
     def __init__(self):
         # _global_id is used in the Versioning module from keepers
         self._ignore_for_hash = ['_global_id']
@@ -56,7 +57,7 @@ class DomainObject(Versionable, Loggable, object):
             item = vars(self)[key]
             if key in self._ignore_for_hash or key == '_ignore_for_hash':
                 continue
-            result_hash ^= item.__hash__() ^ int(hash(key)/117)
+            result_hash ^= item.__hash__() ^ int(hash(key)//117)
         return result_hash
 
     def __eq__(self, x):
@@ -75,7 +76,7 @@ class DomainObject(Versionable, Loggable, object):
         """
 
         if isinstance(x, type(self)):
-            for key in vars(self).keys():
+            for key in list(vars(self).keys()):
                 item1 = vars(self)[key]
                 if key in self._ignore_for_hash or key == '_ignore_for_hash':
                     continue

nifty/energies/__init__.py

@@ -16,7 +16,7 @@
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
-from energy import Energy
-from quadratic_energy import QuadraticEnergy
-from line_energy import LineEnergy
-from memoization import memo
+from .energy import Energy
+from .quadratic_energy import QuadraticEnergy
+from .line_energy import LineEnergy
+from .memoization import memo

nifty/energies/energy.py

@@ -20,9 +20,10 @@ from nifty.nifty_meta import NiftyMeta
 from nifty.energies.memoization import memo
 
 from keepers import Loggable
+from future.utils import with_metaclass
 
 
-class Energy(Loggable, object):
+class Energy(with_metaclass(NiftyMeta, type('NewBase', (Loggable, object), {}))):
     """ Provides the functional used by minimization schemes.
 
    The Energy object is an implementation of a scalar function including its
@@ -64,8 +65,6 @@ class Energy(Loggable, object):
 
     """
 
-    __metaclass__ = NiftyMeta
-
     def __init__(self, position):
         super(Energy, self).__init__()
         self._cache = {}

nifty/energies/line_energy.py

@@ -16,6 +16,8 @@
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
+from __future__ import print_function
+
 
 class LineEnergy(object):
     """ Evaluates an underlying Energy along a certain line direction.
@@ -114,6 +116,6 @@ class LineEnergy(object):
     def directional_derivative(self):
         res = self.energy.gradient.vdot(self.line_direction)
         if abs(res.imag) / max(abs(res.real), 1.) > 1e-12:
-            print "directional derivative has non-negligible " \
-                  "imaginary part:", res
+            print ("directional derivative has non-negligible "
+                  "imaginary part:", res)
         return res.real

nifty/field.py

@@ -17,6 +17,9 @@
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
 from __future__ import division
+from builtins import zip
+#from builtins import str
+from builtins import range
 
 import ast
 import numpy as np
@@ -27,14 +30,15 @@ from keepers import Versionable,\
 from d2o import distributed_data_object,\
     STRATEGIES as DISTRIBUTION_STRATEGIES
 
-from nifty.config import nifty_configuration as gc
+from .config import nifty_configuration as gc
 
-from nifty.domain_object import DomainObject
+from .domain_object import DomainObject
 
-from nifty.spaces.power_space import PowerSpace
+from .spaces.power_space import PowerSpace
 
-import nifty.nifty_utilities as utilities
-from nifty.random import Random
+from . import nifty_utilities as utilities
+from .random import Random
+from functools import reduce
 
 
 class Field(Loggable, Versionable, object):
@@ -346,7 +350,7 @@ class Field(Loggable, Versionable, object):
         # check if the `spaces` input is valid
         spaces = utilities.cast_axis_to_tuple(spaces, len(self.domain))
         if spaces is None:
-            spaces = range(len(self.domain))
+            spaces = list(range(len(self.domain)))
 
         if len(spaces) == 0:
             raise ValueError(
@@ -526,7 +530,7 @@ class Field(Loggable, Versionable, object):
         spaces = utilities.cast_axis_to_tuple(spaces, len(self.domain))
 
         if spaces is None:
-            spaces = range(len(self.domain))
+            spaces = list(range(len(self.domain)))
 
         for power_space_index in spaces:
             power_space = self.domain[power_space_index]
@@ -821,7 +825,7 @@ class Field(Loggable, Versionable, object):
 
         dim_tuple = tuple(sp.dim for sp in self.domain)
         try:
-            return reduce(lambda x, y: x * y, dim_tuple)
+            return int(reduce(lambda x, y: x * y, dim_tuple))
         except TypeError:
             return 0
 
@@ -1010,7 +1014,7 @@ class Field(Loggable, Versionable, object):
 
         fast_copyable = True
         try:
-            for i in xrange(len(self.domain)):
+            for i in range(len(self.domain)):
                 if self.domain[i] is not domain[i]:
                     fast_copyable = False
                     break
@@ -1032,7 +1036,7 @@ class Field(Loggable, Versionable, object):
         # repair its class
         new_field.__class__ = self.__class__
         # copy domain, codomain and val
-        for key, value in self.__dict__.items():
+        for key, value in list(self.__dict__.items()):
             if key != '_val':
                 new_field.__dict__[key] = value
             else:
@@ -1069,7 +1073,7 @@ class Field(Loggable, Versionable, object):
 
         spaces = utilities.cast_axis_to_tuple(spaces, len(self.domain))
         if spaces is None:
-            spaces = range(len(self.domain))
+            spaces = list(range(len(self.domain)))
 
         for ind, sp in enumerate(self.domain):
             if ind in spaces:
@@ -1202,7 +1206,7 @@ class Field(Loggable, Versionable, object):
     def _contraction_helper(self, op, spaces):
         # build a list of all axes
         if spaces is None:
-            spaces = xrange(len(self.domain))
+            spaces = range(len(self.domain))
         else:
             spaces = utilities.cast_axis_to_tuple(spaces, len(self.domain))
 
@@ -1222,7 +1226,7 @@ class Field(Loggable, Versionable, object):
             return data
         else:
             return_domain = tuple(self.domain[i]
-                                  for i in xrange(len(self.domain))
+                                  for i in range(len(self.domain))
                                   if i not in spaces)
 
             return_field = Field(domain=return_domain,
@@ -1270,7 +1274,7 @@ class Field(Loggable, Versionable, object):
         if isinstance(other, Field):
             try:
                 assert len(other.domain) == len(self.domain)
-                for index in xrange(len(self.domain)):
+                for index in range(len(self.domain)):
                     assert other.domain[index] == self.domain[index]
             except AssertionError:
                 raise ValueError(
@@ -1398,6 +1402,17 @@ class Field(Loggable, Versionable, object):
 
         return self._binary_helper(other, op='__div__')
 
+    def __truediv__(self, other):
+        """ x.__truediv__(y) <==> x/y
+
+        See Also
+        --------
+        _builtin_helper
+
+        """
+
+        return self._binary_helper(other, op='__truediv__')
+
     def __rdiv__(self, other):
         """ x.__rdiv__(y) <==> y/x
 
@@ -1409,6 +1424,17 @@ class Field(Loggable, Versionable, object):
 
         return self._binary_helper(other, op='__rdiv__')
 
+    def __rtruediv__(self, other):
+        """ x.__rtruediv__(y) <==> y/x
+
+        See Also
+        --------
+        _builtin_helper
+
+        """
+
+        return self._binary_helper(other, op='__rtruediv__')
+
     def __idiv__(self, other):
         """ x.__idiv__(y) <==> x/=y
 

nifty/field_types/__init__.py

@@ -16,5 +16,5 @@
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
-from field_type import FieldType
-from field_array import FieldArray
+from .field_type import FieldType
+from .field_array import FieldArray

nifty/field_types/field_array.py

@@ -16,7 +16,8 @@
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
-from field_type import FieldType
+from .field_type import FieldType
+from functools import reduce
 
 
 class FieldArray(FieldType):

nifty/library/__init__.py

-from critical_filter import *
-from log_normal_wiener_filter import *
-from wiener_filter import *
+from .critical_filter import *
+from .log_normal_wiener_filter import *
+from .wiener_filter import *