Struct birli::VisSelection

source · [−]

pub struct VisSelection {
    pub timestep_range: Range<usize>,
    pub coarse_chan_range: Range<usize>,
    pub baseline_idxs: Vec<usize, Global>,
}

Expand description

Keep track of which mwalib indices the values in a jones array, its’ weights and its’ flags came from. Similar to a VisSelection, but requires an mwalib::CorrelatorContext to be fully interpreted

TODO: this definitely needs fine_chans_per_coarse TODO: what about https://doc.rust-lang.org/std/ops/trait.RangeBounds.html insetad of Range?

Fields

timestep_range: Range<usize>

selected range of mwalib timestep indices

coarse_chan_range: Range<usize>

selected range of mwalib coarse channel indices

baseline_idxs: Vec<usize, Global>

selected mwalib baseline indices

Implementations

source

impl VisSelection

source

pub fn from_mwalib(
corr_ctx: &CorrelatorContext
) -> Result<VisSelection, SelectionError>

Produce a VisSelection from a given marlu::mwalib::CorrelatorContext.

timesteps are selected from the first common to the last provided.
only common coarse channels are selected
all baselines are selected

For more details, see mwalib core concepts

Examples

use marlu::{mwalib::CorrelatorContext, VisSelection};

// 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",
];

let corr_ctx = CorrelatorContext::new(&metafits_path, &gpufits_paths).unwrap();
let vis_sel = VisSelection::from_mwalib(&corr_ctx).unwrap();

assert_eq!(vis_sel.timestep_range.len(), 4);

This will return SelectionError::NoProvidedTimesteps if mwalib has determined that no timesteps have been provided, SelectionError::NoCommonTimesteps if none of the provided gpuboxes have timesteps in common

source

pub fn get_ant_pairs(
 &self,
 meta_ctx: &MetafitsContext
) -> Vec<(usize, usize ), Global>ⓘNotable traits for Vec<u8, A>`impl<A> Write for Vec<u8, A> where A: Allocator,`

The selected antenna index pairs corresponding to sel_baselines_idxs

source

pub fn get_shape(&self, fine_chans_per_coarse: usize) -> (usize, usize, usize )

Get the shape of the jones, flag or weight array for this selection

source

pub fn estimate_bytes_best(&self, fine_chans_per_coarse: usize) -> usize

Estimate the memory size in bytes required to store the given selection without redundant pols.

source

pub fn allocate_jones(
&self,
fine_chans_per_coarse: usize
) -> Result<ArrayBase<OwnedRepr<Jones<f32>>, Dim<[usize ; 3]>>, SelectionError>

Allocate a jones array to store visibilities for the selection

Errors

can raise SelectionError::InsufficientMemory if not enough memory.

source

pub fn allocate_flags(
&self,
fine_chans_per_coarse: usize
) -> Result<ArrayBase<OwnedRepr<bool>, Dim<[usize ; 3]>>, SelectionError>

Allocate a flag array to store flags for the selection

Errors

can raise SelectionError::InsufficientMemory if not enough memory.

source

pub fn allocate_weights(
&self,
fine_chans_per_coarse: usize
) -> Result<ArrayBase<OwnedRepr<f32>, Dim<[usize ; 3]>>, SelectionError>

Allocate a weight array to store weights for the selection

Errors

can raise SelectionError::InsufficientMemory if not enough memory.

source

pub fn read_mwalib(
 &self,
 corr_ctx: &CorrelatorContext,
 jones_array: ArrayBase<ViewRepr<&mut Jones<f32>>, Dim<[usize ; 3]>>,
 flag_array: ArrayBase<ViewRepr<&mut bool>, Dim<[usize ; 3]>>,
 draw_progress: bool
) -> Result<(), SelectionError>

Read the visibilities for this selection into the jones array using mwalib, flag visiblities if they are not provided.

Errors

Can raise SelectionError::BadArrayShape if jones_array or flag_array does not match the expected shape of this selection.

Examples

use marlu::{mwalib::CorrelatorContext, VisSelection};

// 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",
];

// Create an mwalib::CorrelatorContext for accessing visibilities.
let corr_ctx = CorrelatorContext::new(&metafits_path, &gpufits_paths).unwrap();

// Determine which timesteps and coarse channels we want to use
let img_timestep_idxs = &corr_ctx.common_timestep_indices;
let good_timestep_idxs = &corr_ctx.common_good_timestep_indices;

let mut vis_sel = VisSelection::from_mwalib(&corr_ctx).unwrap();
vis_sel.timestep_range =
    *img_timestep_idxs.first().unwrap()..(*img_timestep_idxs.last().unwrap() + 1);

// Create a blank array to store flags and visibilities
let fine_chans_per_coarse = corr_ctx.metafits_context.num_corr_fine_chans_per_coarse;
let mut flag_array = vis_sel.allocate_flags(fine_chans_per_coarse).unwrap();
let mut jones_array = vis_sel.allocate_jones(fine_chans_per_coarse).unwrap();

// read visibilities out of the gpubox files
vis_sel
    .read_mwalib(&corr_ctx, jones_array.view_mut(), flag_array.view_mut(), false)
    .unwrap();

let dims_common = jones_array.dim();

// now try only with good timesteps
vis_sel.timestep_range =
    *good_timestep_idxs.first().unwrap()..(*good_timestep_idxs.last().unwrap() + 1);

// read visibilities out of the gpubox files
let mut flag_array = vis_sel.allocate_flags(fine_chans_per_coarse).unwrap();
let mut jones_array = vis_sel.allocate_jones(fine_chans_per_coarse).unwrap();
vis_sel
    .read_mwalib(&corr_ctx, jones_array.view_mut(), flag_array.view_mut(), false)
    .unwrap();

let dims_good = jones_array.dim();

// different selections have different sized arrays.
assert_ne!(dims_common, dims_good);