bdsf 1.13.0.post2

Blob Detector and Source Finder

PyBDSF (the Python Blob Detection and Source Finder) is a tool designed to decompose radio interferometry images into sources and make available their properties for further use. PyBDSF can decompose an image into a set of Gaussians, shapelets, or wavelets as well as calculate spectral indices and polarization properties of sources and measure the psf variation across an image. PyBDSF uses an interactive environment based on CASA that will be familiar to most radio astronomers. Additionally, PyBDSF may also be used in Python scripts.

The documentation is currently hosted at https://pybdsf.readthedocs.io

Installation

Installation can be done in a number of ways. In order of preference (read: ease of use):

• Install the latest release from PyPI:

  pip install bdsf

  Note

  The interactive shell pybdsf is no longer installed by default. To install it you have to specify the extra [ishell]. For example:

  pip install bdsf[ishell]

• Install the master branch from the PyBDSF git repository:

  pip install git+https://github.com/lofar-astron/PyBDSF.git

  Or install a specific revision or release, for example v1.9.3:

  pip install git+https://github.com/lofar-astron/PyBDSF.git@v1.9.3

• Install from a local source tree, e.g. after you cloned the git repository:

  pip install .

  or (to install the interactive shell as well):

  pip install .[ishell]

If you get the error:

RuntimeError: module compiled against API version 0xf but this version of numpy is 0xd

then please update numpy with pip install -U numpy.

Attention!

It is not recommend to use python setup.py install. It is deprecated, and we do not support it.

External requirements include the ubuntu packages (or similar packages in another Linux distribution):

• gfortran

• libboost-python-dev

• libboost-numpy-dev (Only if boost > 1.63)

• python-setuptools.

Also, a working numpy installation is required. At runtime, you will need scipy and either pyfits and pywcs or python-casacore or astropy.

If you install as a user not using conda, use pip install --user. Make sure to use similar versions for gcc, g++ and gfortran (use update-alternatives if multiple versions of gcc/g++/gfortran are present on the system). In this case, the script pybdsf is installed in ~/.local/bin, so you might want to add that to your $PATH.

Installation on MacOS / OSX is more involved, you will need the packages mentioned above, for example installed with Homebrew. You will need to tell setup.py to use the same compiler for fortran as for C++. In case of problems, see https://github.com/lofar-astron/PyBDSF/issues/104#issuecomment-509267088 for some possible steps to try.