Imaging, analysis, and simulation software for radio interferometry
Switch branches/tags
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.

README.rst

ehtim (eht-imaging)

Python modules for simulating and manipulating VLBI data and producing images with regularized maximum likelihood methods. This version is an early release so please submit a pull request or email achael@cfa.harvard.edu if you have trouble or need help for your application.

The package contains several primary classes for loading, simulating, and manipulating VLBI data. The main classes are the Image, Array, Obsdata, Movie Caltable and Vex classes, which provide tools for loading images and data, producing simulated data from realistic u-v tracks, and calibrating, inspecting, and plotting data. Imager is a generic Stokes I imaging module that can produce images from data sets using various data terms and regularizers.

Note that this is a pre-release of ehtim. If you have a problem please submit a pull request on the git repository.

Installation

Download the latest version from the GitHub repository, change to the main directory and run:

pip install .

It should install the necessary libraries astropy, ephem, future, matplotlib, numpy, scipy, pandas automatically.

If you want to use fast fourier transforms, you will also need to install NFFT and the pynnft wrapper before installing ehtim. The simplest way is to use conda to to install both NFFT and the pynfft wrapper.

conda install -c conda-forge pynfft

Alternatively, first manually install NFFT following the instructions here, making sure to use the --enable-openmp flag in compilation. Then install pynnft with pip, following the instructions to link the installation to where you installed NFFT.

Documentation

Documentation is here .

Here are some ways to learn to use the code:

  • Start with the script examples/example.py, which contains a series of sample commands to load an image and array, generate data, and produce an image with various imaging algorithms.
  • Slides from the EHT2016 data generation and imaging workshop contain a tutorial on generating data with the vlbi imaging website, loading into the library, and producing an image. Note that this presentation used a previous version of the code -- some function names and prefixes may need to be updated.

Some publications that use ehtim

If you use ehtim in your publication, please cite both Chael et al. 2016 and Chael et al. 2018

Let us know if you use ehtim in your publication and we'll list it here!

  • High-Resolution Linear Polarimetric Imaging for the Event Horizon Telescope, Chael et al. 2016
  • Computational Imaging for VLBI Image Reconstruction, Bouman et al. 2016
  • Stochastic Optics: A Scattering Mitigation Framework for Radio Interferometric Imaging, Johnson 2016
  • Quantifying Intrinsic Variability of Sgr A* using Closure Phase Measurements of the Event Horizon Telescope, Roelofs et al. 2017
  • Reconstructing Video from Interferometric Measurements of Time-Varying Sources, Bouman et al. 2017
  • Dynamical Imaging with Interferometry, Johnson et al. 2017
  • Interferometric Imaging Directly with Closure Phases and Closure Amplitudes, Chael et al. 2018
  • A Model for Anisotropic Interstellar Scattering and its Application to Sgr A*, Psaltis et al. 2018
  • The Currrent Ability to Test Theories of Gravity with Black Hole Shadows, Mizuno et al. 2018
  • The Scattering and Intrinsic Structure of Sagittarius A* at Radio Wavelengths, Johnson et al. 2018

Acknowledgements

The oifits_new code used for reading/writing .oifits files is a slightly modified version of Paul Boley's package at http://astro.ins.urfu.ru/pages/~pboley/oifits. The oifits read/write functionality is still being tested and may not work with all versions of python or astropy.

The documentation is styled after dfm's projects

License

ehtim is licensed under GPLv3. See LICENSE.txt for more details.