Imaging, analysis, and simulation software for radio interferometry
The developer of this repository has not created any items for sale yet. Need a bug fixed? Help with integration? A different license? Create a request here:
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 [email protected] 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
Caltableclasses, which provide tools for loading images and data, producing simulated data from realistic u-v tracks, calibrating, inspecting, and plotting data, and producing images from data sets in various polarizations using various data terms and regularizers.
The latest stable version (
1.2.1) is available on
PyPi. Simply install pip and run
.. code-block:: bash
pip install ehtim
Incremental updates are developed on the
dev branch_. To use the very latest (unstable) code, checkout dev, change to the main eht-imaging directory, and run:
.. code-block:: bash
pip install .
Installing with pip will update most of the required libraries automatically (
If you want to use fast fourier transforms, you will also need to separately install
NFFT_ and its
pynfft wrapper. The simplest way is to use
conda_ to install both:
.. code-block:: bash
conda install -c conda-forge pynfft
Alternatively, first install NFFT manually following the instructions on the
readme, making sure to use the
--enable-openmpflag in compilation. Then install
pynfft, with pip, following the readme instructions to link the installation to where you installed NFFT. Finally, reinstall ehtim.
Certain eht-imaging functions require other external packages that are not automatically installed. In addition to pynfft, these include
networkx_ (for image comparison functions),
requests_ (for dynamical imaging), and
scikit-image_ (for Hough transforms). However, the vast majority of the code will work without these dependencies.
A full tutorial is in progress, but 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.
If you use ehtim in your publication, please cite both
Chael+ 2016_ and
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,
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_
How to tell an accreting boson star from a black hole,
Olivares et al. 2018_
Testing General Relativity with the Black Hole Shadow Size and Asymmetry of Sagittarius A*: Limitations from Interstellar Scattering,
Zhu et al. 2018_
The Size, Shape, and Scattering of Sagittarius A* at 86 GHz: First VLBI with ALMA,
Issaoun et al. 2019_
First M87 Event Horizon Telescope Results IV: Imaging the Central Supermassive Black Hole,
The Event Horizon Telescope Collaboration 2019_
The oifitsnew code used for reading/writing .oifits files is a slightly modified version of Paul Boley's package at
. The oifits read/write functionality is still being developed and may not work with all versions of python or astropy.
The documentation is styled after
ehtim is licensed under GPLv3. See LICENSE.txt for more details.