Radio imaging with information field theory
Project description
resolve
Documentation: http://ift.pages.mpcdf.de/resolve
Resolve aims to be a general radio aperature synthesis algorithm. It is based on Bayesian principles and formulated in the language of information field theory. Its features include single-frequency imaging with either only a diffuse or a diffuse+point-like sky model as prior, single-channel antenna-based calibration with a regularization in temporal domain and w-stacking.
Resolve is in beta stage: You are more than welcome to test it and help to make it applicable. In the likely case that you encounter bugs, please contact me via email.
Requirements
For running the installation script:
- Python version 3.7 or later.
- C++17 capable compiler, e.g. g++ 7 or later.
- pybind11>=2.6
- setuptools
- nifty8
Automatically installed by installation script:
- h5py
- matplotlib
- mpi4py
- numpy
- python-casacore
- scipy
Optional dependencies:
- astropy
- jax, jaxlib
Installation
For a blueprint how to install resolve, you may look at the Dockerfile.
For installing resolve on a Linux machine, the following steps are necessary. First install the necessary dependencies, for example via:
pip3 install --upgrade git+https://gitlab.mpcdf.mpg.de/ift/nifty.git@NIFTy_8 pybind11 setuptools
Optionally install afterwards:
pip3 install astropy jax jaxlib
Finally, clone the resolve repository and install resolve on your system:
git clone https://gitlab.mpcdf.mpg.de/ift/resolve
cd resolve
python3 setup.py install --user
Related publications
- The variable shadow of M87* (arXiv).
- Unified radio interferometric calibration and imaging with joint uncertainty quantification (doi, arXiv).
- Radio imaging with information field theory (doi, arXiv).
Developers
Generate compile-db
pip3 install compiledb
CC=clang CXX=clang python3 setup.py build | compiledb
rm -rf build
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