diff --git a/.gitignore b/.gitignore index 59a6c7f352b574b004b3ef7aa2a5f5c7ea5376c1..f1ff5797370c12c01e0c1705873d29389d3e786f 100644 --- a/.gitignore +++ b/.gitignore @@ -15,3 +15,4 @@ build .idea +.coverage diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml index 9d1d09936db28eb457842b2c7ef884a17d1d3661..3c8da408a3990afcacc44d4ee73536a8ccc1b454 100644 --- a/.gitlab-ci.yml +++ b/.gitlab-ci.yml @@ -64,7 +64,11 @@ test_mpi_fftw_hdf5: - ci/install_libsharp.sh - ci/install_pyfftw.sh - python setup.py build_ext --inplace - - nosetests -vv + - > + nosetests -vv --with-coverage --cover-package=nifty --cover-inclusive + --cover-branches + - > + coverage report | grep TOTAL | awk '{ print "TOTAL: "$6; }' release_image_master: image: docker:latest diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..3b1443a50619088fd554de05868b593aae7ccefd --- /dev/null +++ b/README.md @@ -0,0 +1,300 @@ +NIFTY - Numerical Information Field Theory +========================================== +[![build status](https://gitlab.mpcdf.mpg.de/ift/NIFTy/badges/master/build.svg)](https://gitlab.mpcdf.mpg.de/ift/NIFTy/commits/master) +[![coverage report](https://gitlab.mpcdf.mpg.de/ift/NIFTy/badges/master/coverage.svg)](https://gitlab.mpcdf.mpg.de/ift/NIFTy/commits/master) + +**NIFTY** project homepage: +[http://www.mpa-garching.mpg.de/ift/nifty/](http://www.mpa-garching.mpg.de/ift/nifty/) + +Summary +------- + +### Description + +**NIFTY**, "**N**umerical **I**nformation **F**ield **T**heor**y**", 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 +Python, although it accesses libraries written in Cython, C++, and C for +efficiency. + +NIFTY offers a toolkit that abstracts discretized representations of +continuous spaces, fields in these spaces, and operators acting on +fields into classes. Thereby, the correct normalization of operations on +fields is taken care of automatically without concerning the user. This +allows for an abstract formulation and programming of inference +algorithms, including those derived within information field theory. +Thus, NIFTY permits its user to rapidly prototype algorithms in 1D, and +then apply the developed code in higher-dimensional settings of real +world problems. The set of spaces on which NIFTY operates comprises +point sets, *n*-dimensional regular grids, spherical spaces, their +harmonic counterparts, and product spaces constructed as combinations of +those. + +### Class & Feature Overview + +The NIFTY library features three main classes: **spaces** that represent +certain grids, **fields** that are defined on spaces, and **operators** +that apply to fields. + +- [Spaces](http://www.mpa-garching.mpg.de/ift/nifty/space.html) + - `point_space` - unstructured list of points + - `rg_space` - *n*-dimensional regular Euclidean grid + - `lm_space` - spherical harmonics + - `gl_space` - Gauss-Legendre grid on the 2-sphere + - `hp_space` - [HEALPix](http://sourceforge.net/projects/healpix/) + grid on the 2-sphere + - `nested_space` - arbitrary product of grids +- [Fields](http://www.mpa-garching.mpg.de/ift/nifty/field.html) + - `field` - generic class for (discretized) fields + + + + field.cast_domain field.hat field.power field.smooth + field.conjugate field.inverse_hat field.pseudo_dot field.tensor_dot + field.dim field.norm field.set_target field.transform + field.dot field.plot field.set_val field.weight + +- [Operators](http://www.mpa-garching.mpg.de/ift/nifty/operator.html) + - `diagonal_operator` - purely diagonal matrices in a specified + basis + - `projection_operator` - projections onto subsets of a specified + basis + - `vecvec_operator` - matrices derived from the outer product of a + vector + - `response_operator` - exemplary responses that include a + convolution, masking and projection + - `propagator_operator` - information propagator in Wiener filter + theory + - `explicit_operator` - linear operators with an explicit matrix + representation + - (and more) +- (and more) + +*Parts of this summary are taken from* [1] *without marking them +explicitly as quotations.* + +Installation +------------ + +### Requirements + +- [Python](http://www.python.org/) (v2.7.x) + - [NumPy](http://www.numpy.org/) + - [SciPy](http://www.scipy.org/) + - [Cython](http://cython.org/) + - [matplotlib](http://matplotlib.org/) +- [GFFT](https://github.com/mrbell/gfft) (v0.1.0) - Generalized Fast + Fourier Transformations for Python - **optional** +- [HEALPy](https://github.com/healpy/healpy) (v1.8.1 without openmp) - + A Python wrapper for + [HEALPix](http://sourceforge.net/projects/healpix/) -**optional, + only needed for spherical spaces** +- [libsharp-wrapper](https://github.com/mselig/libsharp-wrapper) + (v0.1.2 without openmp) - A Python wrapper for the + [libsharp](http://sourceforge.net/projects/libsharp/) library + -**optional, only needed for spherical spaces** + +### Download + +The latest release is tagged **v1.0.7** and is available as a source +package at [](https://gitlab.mpcdf.mpg.de/ift/NIFTy/tags). The current +version can be obtained by cloning the repository: + + git clone https://gitlab.mpcdf.mpg.de/ift/NIFTy.git + +### Installation on Ubuntu + +This is for you if you want to install NIFTy on your personal computer +running with an Ubuntu-like linux system were you have root priviledges. +Starting with a fresh Ubuntu installation move to a folder like +`~/Downloads`: + +- Install basic packages like python, python-dev, gsl and others: + + sudo apt-get install curl git autoconf + sudo apt-get install python-dev python-pip gsl-bin libgsl0-dev libfreetype6-dev libpng-dev libatlas-base-dev gfortran + +- Install matplotlib: + + sudo apt-get install python-matplotlib + +- Using pip install numpy, scipy, etc...: + + sudo pip install numpy scipy cython pyfits healpy + +- Now install the 'non-standard' dependencies. First of all gfft: + + curl -LOk https://github.com/mrbell/gfft/tarball/master + tar -xzf master + cd mrbell-gfft* + sudo python setup.py install + cd .. + +- Libsharp: + + git clone http://git.code.sf.net/p/libsharp/code libsharp-code + cd libsharp-code + sudo autoconf + ./configure --enable-pic --disable-openmp + sudo make + cd .. + +- Libsharpwrapper: + + git clone http://github.com/mselig/libsharp-wrapper.git libsharp-wrapper + cd libsharp-wrapper + sudo python setup.py build_ext + sudo python setup.py install + cd .. + +- Finally, NIFTy: + + git clone https://gitlab.mpcdf.mpg.de/ift/NIFTy.git + cd nifty + sudo python setup.py install + cd .. + +### Installation on a linux cluster + +This is for you if you want to install NIFTy on a HPC machine or cluster +that is hosted by your university or institute. Most of the dependencies +will most likely already be there, but you won't have superuser +priviledges. In this case, instead: + + sudo python setup.py install + +use: + + python setup.py install --user + +or: + + python setup.py install --install-lib=/SOMEWHERE + +in the instruction above. This will install the python packages into +your local user directory. + +### Installation on OS X 10.11 + +We advice to install the following packages in the order as they appear +below. We strongly recommend to install all needed packages via +MacPorts. Please be aware that not all packages are available on +MacPorts, missing ones need to be installed manually. It may also be +mentioned that one should only use one package manager, as multiple ones +may cause trouble. + +- Install basic packages python, scipy, matplotlib and cython: + + sudo port install py27-numpy + sudo port install py27-scipy + sudo port install py27-matplotlib + sudo port install py27-cython + +- Install gfft. **Depending where you installed GSL you may need to + change the path in setup.py!**: + + sudo port install gsl + git clone https://github.com/mrbell/gfft.git}{https://github.com/mrbell/gfft.git + sudo python setup.py install + +- Install healpy: + + sudo port install py27-pyfits + git clone https://github.com/healpy/healpy.git + cd healpy + sudo python setup.py install + cd .. + +- Install libsharp and therefore autoconf, automake and libtool. + Installations instructions for libsharp may be found here: + : + + curl -OL http://ftpmirror.gnu.org/autoconf/autoconf-2.69.tar.gz + tar -xzf autoconf-2.69.tar.gz + cd autoconf-2.69 + ./configure && make && sudo make install + cd .. + + curl -OL http://ftpmirror.gnu.org/automake/automake-1.14.tar.gz + tar -xzf automake-1.14.tar.gz + cd automake-1.14 + ./configure && make && sudo make install + cd .. + + curl -OL http://ftpmirror.gnu.org/libtool/libtool-2.4.2.tar.gz + tar -xzf libtool-2.4.2.tar.gz + cd libtool-2.4.2 + ./configure && make && sudo make install + cd .. + + git clone http://git.code.sf.net/p/libsharp/code libsharp-code + cd libsharp-code + sudo autoconf + ./configure --enable-pic --disable-openmp + sudo make + cd .. + +- Install libsharp-wrapper. **Adopt the path of the libsharp + installation in setup.py** : + + sudo port install gcc + sudo port select gcc mp-gcc5 + git clone https://github.com/mselig/libsharp-wrapper.git + cd libsharp-wrapper + sudo python setup.py install + cd .. + +- Install NIFTy: + + git clone https://gitlab.mpcdf.mpg.de/ift/NIFTy.git + cd nifty + sudo python setup.py install + cd .. + +### Installation using pypi + +NIFTY can be installed using [PyPI](https://pypi.python.org/pypi) and +**pip** by running the following command: + + pip install ift_nifty + +Alternatively, a private or user specific installation can be done by: + + pip install --user ift_nifty + +### First Steps + +For a quickstart, you can browse through the [informal +introduction](http://www.mpa-garching.mpg.de/ift/nifty/start.html) or +dive into NIFTY by running one of the demonstrations, e.g.: + + >>> run -m nifty.demos.demo_wf1 + +Acknowledgement +--------------- + +Please, acknowledge the use of NIFTY in your publication(s) by using a +phrase such as the following: + +> *"Some of the results in this publication have been derived using the +> NIFTY package [Selig et al., 2013]."* + +### References + +Release Notes +------------- + +The NIFTY package is licensed under the +[GPLv3](http://www.gnu.org/licenses/gpl.html) and is distributed +*without any warranty*. + +* * * * * + +**NIFTY** project homepage: +[](http://www.mpa-garching.mpg.de/ift/nifty/) + +[1] Selig et al., "NIFTY - Numerical Information Field Theory - a +versatile Python library for signal inference", [A&A, vol. 554, id. +A26](http://dx.doi.org/10.1051/0004-6361/201321236), 2013; +[arXiv:1301.4499](http://www.arxiv.org/abs/1301.4499) diff --git a/README.rst b/README.rst deleted file mode 100644 index 098cf9afa955da2c03f6f22499c2526545f69872..0000000000000000000000000000000000000000 --- a/README.rst +++ /dev/null @@ -1,301 +0,0 @@ -NIFTY - Numerical Information Field Theory -========================================== - -**NIFTY** project homepage: ``_ - -Summary -------- - -Description -........... - -**NIFTY**, "\ **N**\umerical **I**\nformation **F**\ield **T**\heor\ **y**\ ", -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 Python, although it -accesses libraries written in Cython, C++, and C for efficiency. - -NIFTY offers a toolkit that abstracts discretized representations of continuous -spaces, fields in these spaces, and operators acting on fields into classes. -Thereby, the correct normalization of operations on fields is taken care of -automatically without concerning the user. This allows for an abstract -formulation and programming of inference algorithms, including those derived -within information field theory. Thus, NIFTY permits its user to rapidly -prototype algorithms in 1D, and then apply the developed code in -higher-dimensional settings of real world problems. The set of spaces on which -NIFTY operates comprises point sets, *n*-dimensional regular grids, spherical -spaces, their harmonic counterparts, and product spaces constructed as -combinations of those. - -Class & Feature Overview -........................ - -The NIFTY library features three main classes: **spaces** that represent -certain grids, **fields** that are defined on spaces, and **operators** that -apply to fields. - -* `Spaces `_ - - * ``point_space`` - unstructured list of points - * ``rg_space`` - *n*-dimensional regular Euclidean grid - * ``lm_space`` - spherical harmonics - * ``gl_space`` - Gauss-Legendre grid on the 2-sphere - * ``hp_space`` - `HEALPix `_ - grid on the 2-sphere - * ``nested_space`` - arbitrary product of grids - -* `Fields `_ - - * ``field`` - generic class for (discretized) fields - -:: - - field.cast_domain field.hat field.power field.smooth - field.conjugate field.inverse_hat field.pseudo_dot field.tensor_dot - field.dim field.norm field.set_target field.transform - field.dot field.plot field.set_val field.weight - -* `Operators `_ - - * ``diagonal_operator`` - purely diagonal matrices in a specified basis - * ``projection_operator`` - projections onto subsets of a specified basis - * ``vecvec_operator`` - matrices derived from the outer product of a - vector - * ``response_operator`` - exemplary responses that include a convolution, - masking and projection - * ``propagator_operator`` - information propagator in Wiener filter theory - * ``explicit_operator`` - linear operators with an explicit matrix - representation - * (and more) - -* (and more) - -*Parts of this summary are taken from* [1]_ *without marking them explicitly as -quotations.* - -Installation ------------- - -Requirements -............ - -* `Python `_ (v2.7.x) - - * `NumPy `_ - * `SciPy `_ - * `Cython `_ - * `matplotlib `_ - -* `GFFT `_ (v0.1.0) - Generalized Fast - Fourier Transformations for Python - **optional** - -* `HEALPy `_ (v1.8.1 without openmp) - A - Python wrapper for `HEALPix `_ - - **optional, only needed for spherical spaces** - -* `libsharp-wrapper `_ (v0.1.2 - without openmp) - A Python wrapper for the - `libsharp `_ library - - **optional, only needed for spherical spaces** - -Download -........ - -The latest release is tagged **v1.0.7** and is available as a source package -at ``_. The current -version can be obtained by cloning the repository:: - - git clone https://gitlab.mpcdf.mpg.de/ift/NIFTy.git - -Installation on Ubuntu -...................... - -This is for you if you want to install NIFTy on your personal computer running -with an Ubuntu-like linux system were you have root priviledges. Starting with -a fresh Ubuntu installation move to a folder like ``~/Downloads``: - -* Install basic packages like python, python-dev, gsl and others:: - - sudo apt-get install curl git autoconf - sudo apt-get install python-dev python-pip gsl-bin libgsl0-dev libfreetype6-dev libpng-dev libatlas-base-dev gfortran - -* Install matplotlib:: - - sudo apt-get install python-matplotlib - -* Using pip install numpy, scipy, etc...:: - - sudo pip install numpy scipy cython pyfits healpy - -* Now install the 'non-standard' dependencies. First of all gfft:: - - curl -LOk https://github.com/mrbell/gfft/tarball/master - tar -xzf master - cd mrbell-gfft* - sudo python setup.py install - cd .. - -* Libsharp:: - - git clone http://git.code.sf.net/p/libsharp/code libsharp-code - cd libsharp-code - sudo autoconf - ./configure --enable-pic --disable-openmp - sudo make - cd .. - -* Libsharpwrapper:: - - git clone http://github.com/mselig/libsharp-wrapper.git libsharp-wrapper - cd libsharp-wrapper - sudo python setup.py build_ext - sudo python setup.py install - cd .. - -* Finally, NIFTy:: - - git clone https://gitlab.mpcdf.mpg.de/ift/NIFTy.git - cd nifty - sudo python setup.py install - cd .. - -Installation on a linux cluster -............................... - -This is for you if you want to install NIFTy on a HPC machine or cluster that is hosted by your university or institute. Most of the dependencies will most likely already be there, but you won't have superuser priviledges. In this case, instead:: - - sudo python setup.py install - -use:: - - python setup.py install --user - -or:: - - python setup.py install --install-lib=/SOMEWHERE - - -in the instruction above. This will install the python packages into your local user directory. - -Installation on OS X 10.11 -.......................... - -We advice to install the following packages in the order as they appear below. We strongly recommend to install all needed packages via MacPorts. Please be aware that not all packages are available on MacPorts, missing ones need to be installed manually. It may also be mentioned that one should only use one package manager, as multiple ones may cause trouble. - -* Install basic packages python, scipy, matplotlib and cython:: - - sudo port install py27-numpy - sudo port install py27-scipy - sudo port install py27-matplotlib - sudo port install py27-cython - -* Install gfft. **Depending where you installed GSL you may need to change the path in setup.py!**:: - - sudo port install gsl - git clone https://github.com/mrbell/gfft.git}{https://github.com/mrbell/gfft.git - sudo python setup.py install - -* Install healpy:: - - sudo port install py27-pyfits - git clone https://github.com/healpy/healpy.git - cd healpy - sudo python setup.py install - cd .. - -* Install libsharp and therefore autoconf, automake and libtool. - Installations instructions for libsharp may be found here: - https://sourceforge.net/p/libsharp/code/ci/master/tree/:: - - curl -OL http://ftpmirror.gnu.org/autoconf/autoconf-2.69.tar.gz - tar -xzf autoconf-2.69.tar.gz - cd autoconf-2.69 - ./configure && make && sudo make install - cd .. - - curl -OL http://ftpmirror.gnu.org/automake/automake-1.14.tar.gz - tar -xzf automake-1.14.tar.gz - cd automake-1.14 - ./configure && make && sudo make install - cd .. - - curl -OL http://ftpmirror.gnu.org/libtool/libtool-2.4.2.tar.gz - tar -xzf libtool-2.4.2.tar.gz - cd libtool-2.4.2 - ./configure && make && sudo make install - cd .. - - git clone http://git.code.sf.net/p/libsharp/code libsharp-code - cd libsharp-code - sudo autoconf - ./configure --enable-pic --disable-openmp - sudo make - cd .. - -* Install libsharp-wrapper. - **Adopt the path of the libsharp installation in setup.py** :: - - sudo port install gcc - sudo port select gcc mp-gcc5 - git clone https://github.com/mselig/libsharp-wrapper.git - cd libsharp-wrapper - sudo python setup.py install - cd .. - -* Install NIFTy:: - - git clone https://gitlab.mpcdf.mpg.de/ift/NIFTy.git - cd nifty - sudo python setup.py install - cd .. - -Installation using pypi -....................... - -NIFTY can be installed using `PyPI `_ and **pip** -by running the following command:: - - pip install ift_nifty - -Alternatively, a private or user specific installation can be done by:: - - pip install --user ift_nifty - - -First Steps -........... - -For a quickstart, you can browse through the -`informal introduction `_ -or dive into NIFTY by running one of the demonstrations, e.g.:: - - >>> run -m nifty.demos.demo_wf1 - -Acknowledgement ---------------- - -Please, acknowledge the use of NIFTY in your publication(s) by using a phrase -such as the following: - - *"Some of the results in this publication have been derived using the NIFTY - package [Selig et al., 2013]."* - -References -.......... - -.. [1] Selig et al., "NIFTY - Numerical Information Field Theory - a - versatile Python library for signal inference", - `A&A, vol. 554, id. A26 `_, - 2013; `arXiv:1301.4499 `_ - -Release Notes -------------- - -The NIFTY package is licensed under the -`GPLv3 `_ and is distributed *without any -warranty*. - ----- - -**NIFTY** project homepage: ``_ - diff --git a/ci/requirements_base.txt b/ci/requirements_base.txt index 9fba0d403f72426b89f4edb7bc0a2821f57399ff..120f9fd2850e191c92a0077af847441493e3dfc4 100644 --- a/ci/requirements_base.txt +++ b/ci/requirements_base.txt @@ -3,6 +3,7 @@ scipy cython nose nose-parameterized +coverage git+https://gitlab.mpcdf.mpg.de/ift/mpi_dummy.git git+https://gitlab.mpcdf.mpg.de/ift/keepers.git git+https://gitlab.mpcdf.mpg.de/ift/D2O.git diff --git a/nifty/__init__.py b/nifty/__init__.py index 96b0844439a0704c3ecabaa75e5f3a930e62d235..e938500f68023e53dc2a2002353863cc383bf3ee 100644 --- a/nifty/__init__.py +++ b/nifty/__init__.py @@ -55,7 +55,7 @@ from spaces import * from operators import * -from probing import * +#from probing import * from sugar import * diff --git a/nifty/operators/probing_operator/__init__.py b/nifty/operators/probing_operator/__init__.py index 8d200af309ef84fa57449318502f31a302117783..51a85577a5bb10517a78350c0fee55fa951e5db2 100644 --- a/nifty/operators/probing_operator/__init__.py +++ b/nifty/operators/probing_operator/__init__.py @@ -1,5 +1,4 @@ # -*- coding: utf-8 -*- -from prober import Prober from diagonal_prober import * from trace_prober import * diff --git a/nifty/operators/probing_operator/diagonal_prober.py b/nifty/operators/probing_operator/diagonal_prober.py index 251c116975b8ad851fd44c4246c7c2b0fed77486..27e45864dc91875c835a75ecbdb55cd172cede1d 100644 --- a/nifty/operators/probing_operator/diagonal_prober.py +++ b/nifty/operators/probing_operator/diagonal_prober.py @@ -1,10 +1,10 @@ # -*- coding: utf-8 -*- -from prober import Prober - - -class DiagonalProber(Prober): - - # ---Mandatory properties and methods--- - def finish_probe(self, probe, pre_result): - return probe[1].conjugate()*pre_result +# from prober import Prober +# +# +# class DiagonalProber(Prober): +# +# # ---Mandatory properties and methods--- +# def finish_probe(self, probe, pre_result): +# return probe[1].conjugate()*pre_result diff --git a/nifty/operators/probing_operator/trace_prober.py b/nifty/operators/probing_operator/trace_prober.py index dab7c50cdab5302e8b20d5177ae8a1bdb0a4eca4..8409d53793ad9c29d0f6ebfa7b2523214fb30531 100644 --- a/nifty/operators/probing_operator/trace_prober.py +++ b/nifty/operators/probing_operator/trace_prober.py @@ -1,10 +1,10 @@ # -*- coding: utf-8 -*- -from prober import Prober - - -class TraceProber(Prober): - - # ---Mandatory properties and methods--- - def finish_probe(self, probe, pre_result): - return probe[1].conjugate().weight(power=-1).dot(pre_result) +# from prober import Prober +# +# +# class TraceProber(Prober): +# +# # ---Mandatory properties and methods--- +# def finish_probe(self, probe, pre_result): +# return probe[1].conjugate().weight(power=-1).dot(pre_result) diff --git a/nifty/spaces/space/space.py b/nifty/spaces/space/space.py index 80d65ad3f882e1a53c88d5c1f001febe4ecb68b3..72628a040ca6826a069a2dbb74decbe01bb6a5dc 100644 --- a/nifty/spaces/space/space.py +++ b/nifty/spaces/space/space.py @@ -150,8 +150,7 @@ from keepers import Loggable,\ Versionable - -class Space(Versionable, Loggable, Plottable, object): +class Space(Versionable, Loggable, object): """ .. __ __ .. /__/ / /_