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SMILI Documentation Release 0.0.1 SMILI Documentation Release 0.0.1 SMILI Developper Team Jun 21, 2019 Contents 1 Table of Contents 3 i ii SMILI Documentation, Release 0.0.1 Sparse Modeling Imaging Library for Interferometry This website is the documentation for SMILI. SMILI is a python-interfaced library for interferometric imaging using sparse sampling techniques. SMILI is mainly designed for very long baseline interferometry, and has been under the active development primarily for the Event Horizon Telescope. This documentation describes its basic usage with some example data sets. However, SMILI has yet been actively and dynamically developed for many new topics and challenges of the EHT. The documentation is not perfect and sometimes outdated due to dynamical changes in the data structure. Please contact to Kazu Akiyama at NRAO/MIT Haystack Observatory if you have any questions about this library. You may contact with following other core developers, too. • Kazu Akiyama (The Main Developer) at NRAO/MIT Haystack Observatory • Fumie Tazaki (Developer) (Japanese Only) at NAOJ • Shiro Ikeda (Developer) at the Institute of Statistical Mathematics • Kotaro Moriyama (Developer) at NAOJ/MIT Haystack Observatory Contents 1 SMILI Documentation, Release 0.0.1 2 Contents CHAPTER 1 Table of Contents 1.1 Installation 1.1.1 Requirements SMILI consists of python modules and Fortran/C internal libraries called from python modules. Here, we summarize required python packages and external packages for SMILI. You will also need ds9 for some functions such as setting imaging regions (CLEAN box) interatively. 1.1.2 Python Packages and Modules SMILI has been tested and developed in Python 2.7 environments provided by the Anaconda package. We recommend using Anaconda for SMILI. All of mandatory packages will be automatically installed during installation. There are some optional packages that can be used for SMILI. • ehtim: https://github.com/achael/eht-imaging • ehtplot: https://github.com/chanchikwan/ehtplot 1.1.3 External Libraries (For MacPort users, Ubuntu/Debian users) Fortran/C internal libraries of SMILI use following external libraries. This path has been tested for • Mac OS X 10.012/10.13 with MacPort’s gcc 8 • Ubuntu 2016LTS & 2018LTS. 1) OpenBLAS 3 SMILI Documentation, Release 0.0.1 We use OpenBLAS, which is the fastest library among publicly-available BLAS implementations. Our recommendation is to build up OpenBLAS by yourself with a compile option USE_OPENMP=1 and use it for our library. The option USE_OPENMP=1 enables OpenBLAS to perform paralleled multi-threads calculations, which will accelerate our library. In most of cases, you can compile this library by # Clone the current repository git clone https://github.com/xianyi/OpenBLAS # Compile and install cd OpenBLAS make USE_OPENMP=1 make PREFIX="Your install directory; such as /usr/local or $HOME/local" ,!install Note that for MacOSX, USE_OPENMP=1 option does not work and should be omitted. You may need superuser to install OpenBLAS (i.e. to run the last command). SMILI uses pkg-config to find appropriate compiler flags for OpenBLAS. Once the library is installed, you can check if the package configuration file can be accessible. You can type pkg-config --debug openblas If you can see the correct package configuration file in the output (should be $PRE- FIX/lib/pkgconfig/openblas.pc), you are all set with OpenBLAS. Otherwise, you need to set PKG_CONFIG_PATH to your pkgconfig directory by, for instance export PKG_CONFIG_PATH="Your prefix for OpenBLAS such as /usr/local"/lib/ ,!pkgconfig:$PKG_CONFIG_PATH Then you can check by ‘‘pkg-config –debug openblas” if the path is correct. Some Other Tips: If you are using Ubuntu, RedHat and its variant, the default OpenBLAS pack- age, which is installable with apt-get/aptitude or yum, seems compiled without this option (USE_OPENMP=1), so we recommend compiling OpenBLAS by yourself. If you are using macOS, unfortunately, this option is not available so far. You may use a package available in a popular package system (e.g. MacPort, Fink, Homebrew). 2) FFTW3 We use FFTW3, which is one of the fastest library among publicly-available FFT library. For non-Ubuntu users, our recommendation is to build up FFTW3 by yourself. In most of cases, you can compile this library by # Download the library (in case of version 3.3.7) wget http://www.fftw.org/fftw-3.3.7.tar.gz # you should check the latest ,!version tar xzvf fftw-3.3.7.tar.gz cd fftw-3.3.7 # Compile and install ./configure --prefix="install directory; such as /usr/local, $HOME/local"-- ,!enable-openmp --enable-threads --enable-shared make make install 4 Chapter 1. Table of Contents SMILI Documentation, Release 0.0.1 You may need superuser to install FFTW3 (i.e. to run the last command). SMILI uses pkg-config to find appropriate compiler flags for FFTW3. Once the library is installed, you can check if the package configuration file can be accessible. You can type pkg-config --debug fftw3 If you can see the correct package configuration file in the output (should be $PRE- FIX/lib/pkgconfig/fftw3.pc), you are all set with OpenBLAS. Otherwise, you need to set PKG_CONFIG_PATH to your pkgconfig directory by, for instance export PKG_CONFIG_PATH="Your prefix such as /usr/local"/lib/pkgconfig:$PKG_ ,!CONFIG_PATH Then you can check by ‘‘pkg-config –debug fftw3” if the path is correct. Some Other Tips: If you are using Ubuntu, the default fftw3 package, which is installable with apt- get/aptitude seems compiled with the option for Openmp (–enable-openmp). So, you don’t need to install it by yourself. 1.1.4 External Libraries (for homebrew users in MacOS) 1) pyenv and Anaconda installation: Since Anaconda conflicts with Homebrew, it should be installed via pyenv. brew install pyenv export PATH=$HOME/.pyenv/shims:$PATH Then install Anaconda. pyenv install -l | grep anaconda2 pyenv install anaconda2-X # select anaconda 2 version pyenv global anaconda2-X python --version # check versions 2) OPENBLAS installation: It is mostly same to the above one, but you will need to install gcc. # Clone the current repository git clone https://github.com/xianyi/OpenBLAS # Install gcc49 brew install gcc49 sudo ln -sf /usr/local/bin/gcc-4.9 /usr/bin/gcc sudo ln -sf /usr/local/bin/g++-4.9 /usr/bin/g++ # Install OPENBLAS make USE_OPENMP=1CC=gcc make PREFIX=/usr/local install 3) FFTW3 installation: No net change from the above one. # Download the source code wget http://www.fftw.org/fftw-3.X.X.tar.gz tar xzvf fftw-3.X.X.tar.gz cd fftw-3.X.X # Install ./configure prefix="/usr/local" --enable-openmp --enable-threads --enable- ,!shared (continues on next page) 1.1. Installation 5 SMILI Documentation, Release 0.0.1 (continued from previous page) make make install 1.1.5 Downloading SMILI You can download the code from github. # Clone the repository git clone https://github.com/astrosmili/smili 1.1.6 Installing SMILI For compiling the whole library, you need to work in your SMILI directory. cd(Your SMILI Directory) Generate Makefiles with ./configure. If you have correct paths to package-config files for OpenBLAS and FFTW3, you would not need any options. ./configure If you don’t have paths to these files, then you need to specify them manually prior to type ./configure # Example for OpenBLAS export OPENBLAS_LIBS="-LYOURPREFIX/lib -lopenblas" export OPENBLAS_CFLAGS="-IYOURPREFIX/include" # Example for FFTW3 export FFTW3_LIBS="-LYOURPREFIX/lib -lfftw3" export FFTW3_CFLAGS="-IYOURPREFIX/include" Make and compile the library. The internal C/Fortran Library will be compiled into python modules, and then the whole python modules will be added to the package list of your Python environment. make install If you can load following modules in your python interpretator, SMILI is probably installed successfully. # import SMILI from smili import imdata, uvdata, imaging (IMPORTANT NOTE; 2018/04/26) Previously, you needed to type autoconf before ./configure command. This is no longer necessary. (IMPORTANT NOTE; 2018/01/04) Previously, you needed to add a PYTHONPATH to your SMILI Directory. This is no longer required, because the make command will run setup.py and install SMILI into the package list of your Python environment. 1.1.7 Updating SMILI We strongly recommend cleaning up the entire library before updating. 6 Chapter 1. Table of Contents SMILI Documentation, Release 0.0.1 cd(Your SMILI Directory) make uninstall Then, you can update the repository with git pull. git pull Now, the repository has updated. You can follow the above section Installing SMILI for recompiling your SMILI. 1.2 Tutorial and Example Scripts 1.2.1 Images The most basic class for the image in SMILI is imdata.IMFITS object.Here, we show its basic usage. You can see list of functions at in this page. [1]:% matplotlib inline from smili import imdata, util # this is for plotting import matplotlib.pyplot as plt import matplotlib.cm as cm import matplotlib as mpl Creating a blank image Let’s start from a blank image. You can make a blank image. [2]: # Create a blank image image= imdata.IMFITS( # pixel size in the specified angular unit (you can specify dy if you want a non- ,!square image pixel) dx=2, # number of pixels (you can also specify ny if you want a non-square field of ,!view) nx= 256, # angular unit (e.g., rad, deg, amin/arcmin, asec/arcsec, mas, uas) angunit="uas" ) # Plot image (We will explain this function later) image.imshow(scale="linear", colorbar="True") [2]: (<matplotlib.image.AxesImage at 0x1c1da92a90>, <matplotlib.colorbar.Colorbar at 0x1c1dadf110>) 1.2. Tutorial and Example Scripts 7 SMILI Documentation, Release 0.0.1 SMILI also can edit the location of the origin by nxref and nyref in the unit of the pixel number.
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