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Radio imaging with information field theory

Project description

# resolve

Documentation: [http://ift.pages.mpcdf.de/resolve](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](mailto:c@philipp-arras.de).

## 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](./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

# Developers

## Generate compile-db

pip3 install compiledb CC=clang CXX=clang python3 setup.py build | compiledb rm -rf build

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