diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 2718818c8625f40c413634e22e99b24a66d2e33a..c963ceea0ece1967cb36a2b252ca9efd03711e7d 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -16,38 +16,21 @@ before_script:
- pip install --upgrade -r ci/requirements.txt
-test_min:
+test_all:
stage: test
script:
- python setup.py build_ext --inplace
- - nosetests -vv
-
-test_mpi:
- stage: test
- script:
+ - nosetests
- ci/install_pyHealpix.sh
- ci/install_mpi4py.sh
- python setup.py build_ext --inplace
- - nosetests -vv
-
-test_mpi_fftw:
- stage: test
- script:
- - ci/install_pyHealpix.sh
- - ci/install_mpi4py.sh
+ - nosetests
- ci/install_pyfftw.sh
- python setup.py build_ext --inplace
- - nosetests -vv
-
-test_mpi_fftw_hdf5:
- stage: test
- script:
- - ci/install_pyHealpix.sh
- - ci/install_mpi4py.sh
- - ci/install_pyfftw.sh
+ - nosetests
- ci/install_h5py.sh
- python setup.py build_ext --inplace
- - nosetests -vv --with-coverage --cover-package=nifty --cover-branches
+ - nosetests --with-coverage --cover-package=nifty --cover-branches
- >
coverage report | grep TOTAL | awk '{ print "TOTAL: "$6; }'
diff --git a/README.md b/README.md
index 9dec93902b846693af648acc44f4ac76d2b4df36..611f51e2fa6cd8dbd674ac4366c665f1f231a53d 100644
--- a/README.md
+++ b/README.md
@@ -11,7 +11,7 @@ Summary
### Description
-**NIFTY**, "**N**umerical **I**nformation **F**ield **T**heor**y**", is
+**NIFTY**, "**N**umerical **I**nformation **F**ield **T**heor<strong>y</strong>", is
a versatile library designed to enable the development of signal
inference algorithms that operate regardless of the underlying spatial
grid and its resolution. Its object-oriented framework is written in
@@ -87,21 +87,17 @@ Starting with a fresh Ubuntu installation move to a folder like
- Install basic packages like python, python-dev, gsl and others:
- sudo apt-get install curl git autoconf python-dev python-pip python-numpy
+ sudo apt-get install curl git autoconf libtool python-dev python-pip python-numpy
- Install pyHealpix:
git clone https://gitlab.mpcdf.mpg.de/ift/pyHealpix.git
- cd pyHealpix
- autoreconf -i && ./configure --prefix=$HOME/.local --enable-openmp --enable-native-optimizations && make -j4 && make install
- cd ..
+ (cd pyHealpix && autoreconf -i && ./configure --prefix=$HOME/.local --enable-openmp --enable-native-optimizations && make -j4 install)
- Finally, NIFTy:
git clone https://gitlab.mpcdf.mpg.de/ift/NIFTy.git
- cd NIFTy
- python setup.py install --user
- cd ..
+ (cd NIFTy && python setup.py install --user)
### Installation on Linux systems in general
@@ -139,16 +135,13 @@ may cause trouble.
- Install NIFTy:
git clone https://gitlab.mpcdf.mpg.de/ift/NIFTy.git
- cd NIFTy
- python setup.py install --user
- cd ..
+ (cd NIFTy && python setup.py install --user)
### Running the tests
In oder to run the tests one needs two additional packages:
- pip install nose
- pip install parameterized
+ pip install nose parameterized
Afterwards the tests (including a coverage report) are run using the following
command in the repository root:
diff --git a/ci/install_basics.sh b/ci/install_basics.sh
index 46e446ce5299080f10d78c3339c488f2d3930728..796ba27fece74fb5cc00c72702abdfc5997e0f69 100644
--- a/ci/install_basics.sh
+++ b/ci/install_basics.sh
@@ -1,3 +1,3 @@
#!/bin/bash
-apt-get install -y build-essential python python-pip python-dev git autoconf gsl-bin libgsl-dev wget
+apt-get install -y build-essential python python-pip python-dev git autoconf libtool gsl-bin libgsl-dev wget
diff --git a/ci/install_h5py.sh b/ci/install_h5py.sh
index 4649934d4559245fa4ee9a25898f281cceb9bd6b..6702ca879bd5710fc269319b067c598ea0bbff53 100644
--- a/ci/install_h5py.sh
+++ b/ci/install_h5py.sh
@@ -1,9 +1,4 @@
#!/bin/bash
apt-get install -y libhdf5-10 libhdf5-dev libhdf5-openmpi-10 libhdf5-openmpi-dev hdf5-tools
-
-export CC=mpicc
-export HDF5_DIR=/usr/lib/x86_64-linux-gnu/hdf5/openmpi
-export HDF5_MPI="ON"
-
-pip install --no-binary=h5py h5py
+CC=mpicc HDF5_DIR=/usr/lib/x86_64-linux-gnu/hdf5/openmpi HDF5_MPI="ON" pip install --no-binary=h5py h5py
diff --git a/ci/install_mpi4py.sh b/ci/install_mpi4py.sh
index d53b536e82b3da88eb4a12362544eb57a2c4b56b..a2f71dca1584c4a95799a1b827361ab6f0b63782 100644
--- a/ci/install_mpi4py.sh
+++ b/ci/install_mpi4py.sh
@@ -1,4 +1,4 @@
#!/bin/bash
apt-get install -y openmpi-bin libopenmpi-dev
-pip install mpi4py
\ No newline at end of file
+pip install mpi4py
diff --git a/ci/install_pyHealpix.sh b/ci/install_pyHealpix.sh
index 504f9123ff63eb5c9159ebcddc9b43cd06264890..914d0c1d1b7dba1694b5a6d08e446fd576e9f9ed 100644
--- a/ci/install_pyHealpix.sh
+++ b/ci/install_pyHealpix.sh
@@ -1,7 +1,5 @@
#!/bin/bash
git clone https://gitlab.mpcdf.mpg.de/ift/pyHealpix.git
-cd pyHealpix
-autoreconf -i && ./configure && make -j4 install
-cd ..
+(cd pyHealpix && autoreconf -i && ./configure --enable-openmp --enable-native-optimizations && make -j4 install)
rm -rf pyHealpix
diff --git a/ci/install_pyfftw.sh b/ci/install_pyfftw.sh
index 670048030bede61ddf1dbcc561a9083876c17f3b..e0c120baf24e0c85671719977cd4b8b73fa853e5 100644
--- a/ci/install_pyfftw.sh
+++ b/ci/install_pyfftw.sh
@@ -3,7 +3,5 @@
apt-get install -y libatlas-base-dev libfftw3-bin libfftw3-dev libfftw3-double3 libfftw3-long3 libfftw3-mpi-dev libfftw3-mpi3 libfftw3-quad3 libfftw3-single3
git clone -b mpi https://github.com/fredros/pyFFTW.git
-cd pyFFTW/
-CC=mpicc python setup.py build_ext install
-cd ..
-rm -r pyFFTW
+(cd pyFFTW && CC=mpicc python setup.py build_ext install)
+rm -rf pyFFTW
diff --git a/nifty/field_types/field_array.py b/nifty/field_types/field_array.py
index bac80ea37fdd739c167058ef2102460d9457c230..4318afa2f3b029c246d992bdaf1cfc25358c8600 100644
--- a/nifty/field_types/field_array.py
+++ b/nifty/field_types/field_array.py
@@ -22,12 +22,11 @@ from field_type import FieldType
class FieldArray(FieldType):
def __init__(self, shape):
+ super(FieldArray, self).__init__()
try:
- new_shape = tuple([int(i) for i in shape])
+ self._shape = tuple([int(i) for i in shape])
except TypeError:
- new_shape = (int(shape), )
- self._shape = new_shape
- super(FieldArray, self).__init__()
+ self._shape = (int(shape), )
@property
def shape(self):
diff --git a/nifty/operators/fft_operator/transformations/gllmtransformation.py b/nifty/operators/fft_operator/transformations/gllmtransformation.py
index a0e47652b85fc8f17adf1c08e1bed23bc4130782..7029f80eac7e05f7d967d5de3250665179a0037e 100644
--- a/nifty/operators/fft_operator/transformations/gllmtransformation.py
+++ b/nifty/operators/fft_operator/transformations/gllmtransformation.py
@@ -100,11 +100,6 @@ class GLLMTransformation(SlicingTransformation):
super(GLLMTransformation, cls).check_codomain(domain, codomain)
def _transformation_of_slice(self, inp, **kwargs):
- if inp.dtype not in (np.float, np.complex):
- self.logger.warn("The input array has dtype: %s. The FFT will "
- "be performed at double precision." %
- str(inp.dtype))
-
nlat = self.domain.nlat
nlon = self.domain.nlon
lmax = self.codomain.lmax
diff --git a/nifty/operators/fft_operator/transformations/hplmtransformation.py b/nifty/operators/fft_operator/transformations/hplmtransformation.py
index 314caa008bc479aa6596ca658410da7fde233585..c8cb157108cbe4bbe7432a54e461870db370bfac 100644
--- a/nifty/operators/fft_operator/transformations/hplmtransformation.py
+++ b/nifty/operators/fft_operator/transformations/hplmtransformation.py
@@ -92,11 +92,6 @@ class HPLMTransformation(SlicingTransformation):
super(HPLMTransformation, cls).check_codomain(domain, codomain)
def _transformation_of_slice(self, inp, **kwargs):
- if inp.dtype not in (np.float, np.complex):
- self.logger.warn("The input array has dtype: %s. The FFT will "
- "be performed at double precision." %
- str(inp.dtype))
-
lmax = self.codomain.lmax
mmax = lmax
diff --git a/nifty/operators/fft_operator/transformations/lmgltransformation.py b/nifty/operators/fft_operator/transformations/lmgltransformation.py
index 5e743c4da5512902dedf85bdcf7c9353748c109d..44e5c54e8a6c3422fe31705865bd9614ac536a45 100644
--- a/nifty/operators/fft_operator/transformations/lmgltransformation.py
+++ b/nifty/operators/fft_operator/transformations/lmgltransformation.py
@@ -106,11 +106,6 @@ class LMGLTransformation(SlicingTransformation):
super(LMGLTransformation, cls).check_codomain(domain, codomain)
def _transformation_of_slice(self, inp, **kwargs):
- if inp.dtype not in (np.float, np.complex):
- self.logger.warn("The input array has dtype: %s. The FFT will "
- "be performed at double precision." %
- str(inp.dtype))
-
nlat = self.codomain.nlat
nlon = self.codomain.nlon
lmax = self.domain.lmax
diff --git a/nifty/operators/fft_operator/transformations/lmhptransformation.py b/nifty/operators/fft_operator/transformations/lmhptransformation.py
index 6aa87e973ae1429e76d5eb8552d586a69ddea1c3..0e9d1e392ff1c14a7bb0e8c391b00cf8a0366e2e 100644
--- a/nifty/operators/fft_operator/transformations/lmhptransformation.py
+++ b/nifty/operators/fft_operator/transformations/lmhptransformation.py
@@ -94,11 +94,6 @@ class LMHPTransformation(SlicingTransformation):
super(LMHPTransformation, cls).check_codomain(domain, codomain)
def _transformation_of_slice(self, inp, **kwargs):
- if inp.dtype not in (np.float, np.complex):
- self.logger.warn("The input array has dtype: %s. The FFT will "
- "be performed at double precision." %
- str(inp.dtype))
-
nside = self.codomain.nside
lmax = self.domain.lmax
mmax = lmax
diff --git a/nifty/operators/fft_operator/transformations/rg_transforms.py b/nifty/operators/fft_operator/transformations/rg_transforms.py
index 78028f86b6e39aca0a4168119d6ce73f67038071..0ccdb22c5d7f95adde9c6b220e81aebc6abc8ff8 100644
--- a/nifty/operators/fft_operator/transformations/rg_transforms.py
+++ b/nifty/operators/fft_operator/transformations/rg_transforms.py
@@ -433,11 +433,6 @@ class FFTW(Transform):
not all(axis in range(len(val.shape)) for axis in axes):
raise ValueError("Provided axes does not match array shape")
- if val.dtype not in (np.float, np.complex):
- self.logger.warn("The input array has dtype: %s. The FFT will "
- "be performed at double precision." %
- str(val.dtype))
-
# If the input is a numpy array we transform it locally
if not isinstance(val, distributed_data_object):
# Cast to a np.ndarray
@@ -582,11 +577,6 @@ class NUMPYFFT(Transform):
not all(axis in range(len(val.shape)) for axis in axes):
raise ValueError("Provided axes does not match array shape")
- if val.dtype not in (np.float, np.complex):
- self.logger.warn("The input array has dtype: %s. The FFT will "
- "be performed at double precision." %
- str(val.dtype))
-
return_val = val.copy_empty(global_shape=val.shape,
dtype=np.complex)
diff --git a/nifty/operators/invertible_operator_mixin/invertible_operator_mixin.py b/nifty/operators/invertible_operator_mixin/invertible_operator_mixin.py
index 4786a4f9375c7e56e6b52d38005263f2b6f69057..5aaff1097cf10aeeee14ca7232067ed783ff85cc 100644
--- a/nifty/operators/invertible_operator_mixin/invertible_operator_mixin.py
+++ b/nifty/operators/invertible_operator_mixin/invertible_operator_mixin.py
@@ -104,6 +104,7 @@ class InvertibleOperatorMixin(object):
x0=x0)
return result
+ #MR FIXME: why? shouldn't this be equivalent to the adjoint inverse?
def _inverse_adjoint_times(self, x, spaces):
raise NotImplementedError(
"no generic instance method 'inverse_adjoint_times'.")
diff --git a/nifty/operators/propagator_operator/harmonic_propagator_operator.py b/nifty/operators/propagator_operator/harmonic_propagator_operator.py
index 908e2e372f992dbd0c7afc7ce8fdbc0c62c94833..8789847a8a96dbc2dfa679cf388c5e213fdd6636 100644
--- a/nifty/operators/propagator_operator/harmonic_propagator_operator.py
+++ b/nifty/operators/propagator_operator/harmonic_propagator_operator.py
@@ -83,7 +83,7 @@ class HarmonicPropagatorOperator(InvertibleOperatorMixin, EndomorphicOperator):
# ---Overwritten properties and methods---
- def __init__(self, S=None, M=None, R=None, N=None, inverter=None,
+ def __init__(self, S, M=None, R=None, N=None, inverter=None,
preconditioner=None):
"""
Sets the standard operator properties and `codomain`, `_A1`, `_A2`,
@@ -102,7 +102,6 @@ class HarmonicPropagatorOperator(InvertibleOperatorMixin, EndomorphicOperator):
"""
# infer domain, and target
- # infer domain, and target
if M is not None:
self._codomain = M.domain
self._likelihood = M.times
diff --git a/nifty/operators/smoothing_operator/direct_smoothing_operator.py b/nifty/operators/smoothing_operator/direct_smoothing_operator.py
index 59ce7406b94bde5c755f6f75e355e3b002f108cf..2e415d62aacb81a4ca97d007912f5650046e9cc8 100644
--- a/nifty/operators/smoothing_operator/direct_smoothing_operator.py
+++ b/nifty/operators/smoothing_operator/direct_smoothing_operator.py
@@ -144,6 +144,7 @@ class DirectSmoothingOperator(SmoothingOperator):
distribution_strategy='not')
distance_array = distance_array.get_local_data(copy=False)
+ #MR FIXME: this causes calls of log(0.) which should probably be avoided
if self.log_distances:
np.log(distance_array, out=distance_array)
diff --git a/nifty/operators/smoothing_operator/fft_smoothing_operator.py b/nifty/operators/smoothing_operator/fft_smoothing_operator.py
index 2e764bee29aef937920862bdce9ed318eb32998e..f4f3de8f194f7a8537ed1cacd3e33e0dda216e2f 100644
--- a/nifty/operators/smoothing_operator/fft_smoothing_operator.py
+++ b/nifty/operators/smoothing_operator/fft_smoothing_operator.py
@@ -24,6 +24,7 @@ class FFTSmoothingOperator(SmoothingOperator):
kernel = codomain.get_distance_array(
distribution_strategy=axes_local_distribution_strategy)
+ #MR FIXME: this causes calls of log(0.) which should probably be avoided
if self.log_distances:
kernel.apply_scalar_function(np.log, inplace=True)
@@ -43,6 +44,7 @@ class FFTSmoothingOperator(SmoothingOperator):
# apply the kernel
if inverse:
+ #MR FIXME: danger of having division by zero or overflows
local_transformed_x /= local_kernel
else:
local_transformed_x *= local_kernel
diff --git a/nifty/spaces/power_space/power_space.py b/nifty/spaces/power_space/power_space.py
index ce56812a48db1ddc2751f60dbdd1f60cb101e77c..1e3fbcccff9f9a98d4339fbb7327dcc555a5ce1d 100644
--- a/nifty/spaces/power_space/power_space.py
+++ b/nifty/spaces/power_space/power_space.py
@@ -261,6 +261,7 @@ class PowerSpace(Space):
hdf5_group.attrs['nbin'] = str(self.config["nbin"])
hdf5_group.attrs['binbounds'] = str(self.config["binbounds"])
+ #MR FIXME: why not "return None" as happens everywhere else?
return {
'harmonic_partner': self.harmonic_partner,
'pindex': self.pindex,
diff --git a/nifty/spaces/space/space.py b/nifty/spaces/space/space.py
index 84314c48cc968c41d94320d26ee0ba9c4f615d3d..624207d9c44e25800c95e8b90ee0c3e9c54a330f 100644
--- a/nifty/spaces/space/space.py
+++ b/nifty/spaces/space/space.py
@@ -202,6 +202,4 @@ class Space(DomainObject):
raise NotImplementedError
def __repr__(self):
- string = ""
- string += str(type(self)) + "\n"
- return string
+ return str(type(self)) + "\n"
diff --git a/nifty/sugar.py b/nifty/sugar.py
index d46d25370937fc3d0ebaddb91416801f48e82527..a5bdf5dac97a12bf53b267ec2ea7f74335d35e6d 100644
--- a/nifty/sugar.py
+++ b/nifty/sugar.py
@@ -18,25 +18,22 @@
from nifty import PowerSpace,\
Field,\
- DiagonalOperator,\
- FFTOperator
+ DiagonalOperator
__all__ = ['create_power_operator']
def create_power_operator(domain, power_spectrum, dtype=None,
distribution_strategy='not'):
+<<<<<<< nifty/sugar.py
""" Creates a diagonal operator with the given power spectrum.
- Constructs a diagonal operator that lives over the specified domain, or
- its default harmonic codomain in case it is not harmonic.
+ Constructs a diagonal operator that lives over the specified domain.
Parameters
----------
domain : DomainObject
- Domain over which the power operator shall live. If this is not a
- harmonic domain, it will return an operator for its harmonic codomain
- instead.
+ Domain over which the power operator shall live.
power_spectrum : (array-like, method)
An array-like object, or a method that implements the square root
of a power spectrum as a function of k.
@@ -53,21 +50,14 @@ def create_power_operator(domain, power_spectrum, dtype=None,
DiagonalOperator : An operator that implements the given power spectrum.
"""
-
- if not domain.harmonic:
- fft = FFTOperator(domain)
- domain = fft.target[0]
+=======
+>>>>>>> nifty/sugar.py
power_domain = PowerSpace(domain,
distribution_strategy=distribution_strategy)
-
- fp = Field(power_domain,
- val=power_spectrum, dtype=dtype,
+ fp = Field(power_domain, val=power_spectrum, dtype=dtype,
distribution_strategy=distribution_strategy)
fp **= 2
-
f = fp.power_synthesize(mean=1, std=0, real_signal=False)
- power_operator = DiagonalOperator(domain, diagonal=f, bare=True)
-
- return power_operator
+ return DiagonalOperator(domain, diagonal=f, bare=True)
diff --git a/test/test_operators/test_diagonal_operator.py b/test/test_operators/test_diagonal_operator.py
index 90f1ef7c4ac2f095d400d4d60e51314b8324cc08..ef953fa0602b50f923d6566fbebe6205f3f8e44c 100644
--- a/test/test_operators/test_diagonal_operator.py
+++ b/test/test_operators/test_diagonal_operator.py
@@ -106,6 +106,7 @@ class DiagonalOperator_Tests(unittest.TestCase):
assert_allclose(trace_op, np.sum(1./diag.val.get_full_data()))
@expand(product(spaces, [True, False]))
+ #MR FIXME: what if any diagonal element <=0?
def test_trace_log(self, space, copy):
diag = Field.from_random('normal', domain=space)
D = DiagonalOperator(space, diagonal=diag, copy=copy)
@@ -127,8 +128,9 @@ class DiagonalOperator_Tests(unittest.TestCase):
assert_allclose(inv_det, 1./D.determinant())
@expand(product(spaces, [True, False], [True, False]))
+ #MR FIXME: what if determinant <=0?
def test_log_determinant(self, space, bare, copy):
diag = Field.from_random('normal', domain=space)
D = DiagonalOperator(space, diagonal=diag, bare=bare, copy=copy)
log_det = D.log_determinant()
- assert_allclose(log_det, np.log(D.determinant()))
\ No newline at end of file
+ assert_allclose(log_det, np.log(D.determinant()))
diff --git a/test/test_operators/test_smoothing_operator.py b/test/test_operators/test_smoothing_operator.py
index ec582e6d9c627784f4664dc1d0b08c72bfab3103..08505d0eb08838ee3e1d7e6f5dcc54be25bd170c 100644
--- a/test/test_operators/test_smoothing_operator.py
+++ b/test/test_operators/test_smoothing_operator.py
@@ -36,9 +36,6 @@ def _get_rtol(tp):
else:
return 1e-5
-from itertools import product
-from test.common import expand
-
class SmoothingOperator_Tests(unittest.TestCase):
spaces = [RGSpace(100)]