Installation

Vela.jl can be installed directly from GitHub. We recommend installing it within a dedicated conda environment. See the instructions here to install miniconda.

Please note that Vela.jl is only tested against Python 3.12 and Julia 1.11 in Ubuntu at present.

If you don't have Julia installed, please install it using juliaup following the instructions found here.

The following instructions assume that both conda and julia are installed.

Now, install the Python dependencies and set the environment variables. The most important one is PYTHON_JULIACALL_HANDLE_SIGNALS. If it is not set properly you'll get segmentation faults.

(base) $ # Setup conda environment
(base) $ conda create -n vela python=3.12
(base) $ conda activate vela
(vela) $ conda env config vars set PYTHON_JULIACALL_HANDLE_SIGNALS=yes
(vela) $ conda env config vars set PYTHON_JULIACALL_THREADS=4
(vela) $ conda env config vars set JULIA_NUM_THREADS=4
(vela) $ conda env config vars set JULIA_CONDAPKG_BACKEND="Null"
(vela) $ conda env config vars set PYTHON_JULIACALL_EXE="$(which julia)"
(vela) $ conda env config vars set PYTHON_JULIACALL_PROJECT=$(julia -e 'print(joinpath(DEPOT_PATH[1], "environments", "v$(VERSION.major).$(VERSION.minor)"))')
(vela) $ conda env config vars set PYTHON_JULIAPKG_OFFLINE=true
(vela) $ conda install -c conda-forge pyjuliacall black emcee nestle corner tqdm pytest pytest-xdist
(vela) $ pip install git+https://github.com/nanograv/PINT

The number of threads available to Vela.jl for parallel processing can be controlled using the environment variables JULIA_NUM_THREADS (for direct use from Julia) or PYTHON_JULIACALL_THREADS (for use from within Python). This should be set based on the number of CPU cores available in your machine.

Now, install the Julia packages.

(vela) $ julia
julia> import Pkg
julia> Pkg.Registry.add("General")
julia> Pkg.Registry.add(url="https://github.com/abhisrkckl/julia_registry")
julia> Pkg.add(["LocalRegistry", "JuliaFormatter", "BenchmarkTools", "PythonCall", "Distributions", "DoubleFloats", "GeometricUnits"])
julia> Pkg.add(url="https://github.com/abhisrkckl/Vela.jl")
julia> exit()

Install the Python interface pyvela.

(vela) $ pip install git+https://github.com/abhisrkckl/Vela.jl

The pyvela/examples directory provides several example datasets and scripts. A basic example (using the Python wrapper) can be run like this:

(vela) $ ./run_example_emcee.py NGC6440E.par NGC6440E.tim

Testing if installation is successful

Run the following commands to check if the installation is successful.

(vela) $ julia -e 'import Pkg; Pkg.test("Vela")'
(vela) $ python -c 'from pyvela import SPNTA, __version__; print(__version__)'

Updating Vela.jl

To update a Vela.jl installation, do the following.

(vela) $ julia
julia> import Pkg
julia> Pkg.update(["GeometricUnits", "Vela"])
julia> exit()

It is best to reinstall pyvela:

(vela) $ pip install git+https://github.com/abhisrkckl/Vela.jl

Note that both Vela.jl and pyvela should be updated together. You will get an exception if a version mismatch is detected.