Crate birli[−][src]
Expand description
Birli is a library of common preprocessing tasks performed in the data pipeline of the Murchison Widefield Array (MWA) Telescope.
Examples
Here’s an example of how to flag some visibility files
use birli::{
context_to_jones_array, write_flags,
get_flaggable_timesteps, init_flag_array,
get_antenna_flags, mwalib::CorrelatorContext, write_uvfits
};
use tempfile::tempdir;
// define our input files
let metafits_path = "tests/data/1297526432_mwax/1297526432.metafits";
let gpufits_paths = vec![
"tests/data/1297526432_mwax/1297526432_20210216160014_ch117_000.fits",
"tests/data/1297526432_mwax/1297526432_20210216160014_ch117_001.fits",
"tests/data/1297526432_mwax/1297526432_20210216160014_ch118_000.fits",
"tests/data/1297526432_mwax/1297526432_20210216160014_ch118_001.fits",
];
// define a temporary directory for output files
let tmp_dir = tempdir().unwrap();
// define our output paths
let flag_template = tmp_dir.path().join("Flagfile%%%.mwaf");
let uvfits_out = tmp_dir.path().join("1297526432.uvfits");
// Create an mwalib::CorrelatorContext for accessing visibilities.
let context = CorrelatorContext::new(&metafits_path, &gpufits_paths).unwrap();
// Determine which timesteps and coarse channels we want to use
let img_coarse_chan_idxs = &context.common_coarse_chan_indices;
let img_timestep_idxs = get_flaggable_timesteps(&context).unwrap();
let img_timestep_range =
*img_timestep_idxs.first().unwrap()..(*img_timestep_idxs.last().unwrap() + 1);
let img_coarse_chan_range =
*img_coarse_chan_idxs.first().unwrap()..(*img_coarse_chan_idxs.last().unwrap() + 1);
let baseline_idxs = (0..context.metafits_context.num_baselines).collect::<Vec<_>>();
// Prepare our flagmasks with known bad antennae
let flag_array = init_flag_array(
&context,
&img_timestep_range,
&img_coarse_chan_range,
Some(get_antenna_flags(&context)),
);
// load visibilities into our array of jones matrices
let (mut jones_array, flag_array) = context_to_jones_array(
&context,
&img_timestep_range,
&img_coarse_chan_range,
Some(flag_array),
);
// This functionality is only available with the aoflagger feature
// use birli::{cxx_aoflagger_new, flag_jones_array_existing}
// // create a CxxAOFlagger object to perform AOFlagger operations
// let aoflagger = unsafe { cxx_aoflagger_new() };
//
// // use the default strategy file location for MWA
// let strategy_filename = &aoflagger.FindStrategyFileMWA();
//
// // run the strategy on the imagesets, and get the resulting flagmasks for each baseline
// let flag_array = flag_jones_array_existing(
// &aoflagger,
// &strategy_filename,
// &jones_array,
// Some(flag_array),
// true,
// );
// write the flags to disk as .mwaf
write_flags(&context, &flag_array, flag_template.to_str().unwrap(), &img_coarse_chan_range).unwrap();
// write the visibilities to disk as .uvfits
write_uvfits(
uvfits_out.as_path(),
&context,
&jones_array,
&flag_array,
&img_timestep_range,
&img_coarse_chan_range,
&baseline_idxs,
None,
).unwrap();Details
Birli reads visibilities with MWALib and uses CXX to bind to the AOFlagger C++ library.
For more details about AOFlagger’s interface, check out the aoflagger::AOFlagger
documentation
Re-exports
pub use io::mwaf::FlagFileSet;pub use io::uvfits::UvfitsWriter;pub use io::write_ms;pub use io::write_uvfits;pub use corrections::correct_cable_lengths;pub use corrections::correct_geometry;pub use flags::get_antenna_flags;pub use flags::get_flaggable_timesteps;pub use flags::init_flag_array;pub use flags::write_flags;pub use marlu;pub use marlu::approx;pub use marlu::mwalib;pub use marlu::mwalib::fitsio;pub use marlu::mwalib::fitsio_sys;pub use marlu::ndarray;pub use flags::flag_jones_array;pub use flags::flag_jones_array_existing;Modules
Corrections that can be performed on visibility data
Methods for manipulating flagmasks and flagging imagesets
Input and Ouput data file format modules
Macros
Parallelized array zip macro: lock step function application across several arrays and producers.
Structs
An axis index.
A complex number in Cartesian form.
mwalib correlator observation context. This represents the basic metadata for a correlator observation.
CXX Wrapper for aoflagger::AOFlagger, the main class for access to the flagger functionality.
CXX Wrapper for aoflagger::FlagMask, a two-dimensional mask of bool flags.
CXX Wrapper for aoflagger::ImageSet, a set of time-frequency ‘images’ which
together contain data for one correlated baseline.
Binding to C++ std::unique_ptr<T, std::default_delete<T>>.
Enums
An enum of all the errors possible in Birli
Traits
An iterator that supports “random access” to its data, meaning that you can split it at arbitrary indices and draw data from those points.
IntoParallelIterator implements the conversion to a ParallelIterator.
IntoParallelRefIterator implements the conversion to a
ParallelIterator, providing shared references to the data.
IntoParallelRefMutIterator implements the conversion to a
ParallelIterator, providing mutable references to the data.
Parallel version of the standard iterator trait.
Functions
generate a 3 dimensional array of Jones matrices from an observation’s
mwalib::CorrelatorContext, for all baselines, over a given range of
mwalib timestep and coarse channel indices.
Create a new CxxAOFlagger instance
Create an aoflagger CxxFlagMask for a from the given flag array view
Get the version of the AOFlagger library from the library itself.
Create an aoflagger CxxImageSet for a particular baseline from the given jones array
Type Definitions
three-dimensional array