User Parameters - Spectral-line Source-finding

It is possible to run source-finding with Selavy on the created spectral-line cubes. Through the pipeline, it is possible to specify either flux or SNR thresholds, apply a variable SNR threshold, and pre-process the cube with smoothing or multi-resolution wavelet reconstruction (to enhance the signal-to-noise of real sources).

Variable

Default

Parset equivalent

Description

DO_SOURCE_FINDING_SPEC

""

none

Whether to do the source-finding with Selavy on the final mosaic images. If not given in the config file, it takes on the value of DO_SPECTRAL_IMAGING.

CATALOGUE_BASE_NAME

selavy-%i.txt

Selavy.resultsFile (Selavy Basics)

Base name for source catalogues. The %i wildcard will be resolved into the imageName corresponding to the spectral image. You may find this parameter useful to rename new catalogues generated from re-processing. NB: The same parameter is used for continuum source-finding.

CATALOGUE_ID_BASE

SB%s

Selavy.sourceIdBase (Selavy Basics)

Base identifier for catalogue components. The %s wildcard will be resolved into the SBID of the observation. You may find this parameter useful to rename new catalogue components generated from re-processing. NB: The same parameter is used for continuum source-finding.

DO_SOURCE_FINDING_BEAMWISE

false

none

If true, the source-finding will be run on the individual beam images as well.

DO_SOURCE_FINDING_FIELD_MOSAICS

false

none

If true, the source-finding will be run on the individual field mosaics. Will be set to false if the number of fields is one.

JOB_TIME_SOURCEFINDING_SPEC

JOB_TIME_DEFAULT (24:00:00)

none

Time request for source-finding jobs

CORES_PER_NODE_SELAVY_SPEC

""

none

Number of cores used on each node. If not provided, it will be the lower of the number of cores requested or the maximum number of cores available per node.

SELAVY_SPEC_NSUBX

6

nsubx (Selavy Basics)

Number of divisions in the x-direction that divide the image up, allowing parallel processing in the source-detection.

SELAVY_SPEC_NSUBY

9

nsuby (Selavy Basics)

Number of divisions in the y-direction that divide the image up, allowing parallel processing in the source-detection.

SELAVY_SPEC_NSUBZ

18

nsubz (Selavy Basics)

Number of divisions in the z-direction that divide the image up, allowing parallel processing in the source-detection.

SELAVY_OVERLAPX

0

overlapx (Selavy Basics)

The overlap (in pixels) between neighbouring divisions in the x-direction.

SELAVY_OVERLAPY

0

overlapy (Selavy Basics)

The overlap (in pixels) between neighbouring divisions in the y-direction.

SELAVY_OVERLAPZ

20

overlapz (Selavy Basics)

The overlap (in pixels) between neighbouring divisions in the z-direction.

Searching

SELAVY_SPEC_SNR_CUT

8.0

snrcut (Selavy Basics)

The signal-to-noise ratio threshold to use in the source-detection.

SELAVY_SPEC_FLAG_GROWTH

true

flagGrowth (Selavy Basics)

A flag indicating whether to grow detections down to a lower threshold.

SELAVY_SPEC_GROWTH_CUT

3.0

growthCut (Selavy Basics)

The secondary signal-to-noise threshold to which detections should be grown.

SELAVY_SPEC_FLUX_THRESHOLD

""

threshold (Selavy Basics)

The flux threshold to use in the source-detection. If left blank, we use the SNR threshold SELAVY_SNR_CUT.

SELAVY_SPEC_GROWTH_THRESHOLD

""

growthCut (Selavy Basics)

The secondary signal-to-noise threshold to which detections should be grown. Only used if SELAVY_FLUX_THRESHOLD is given.

SELAVY_SPEC_WEIGHTS_CUTOFF

""

Weights.weightsCutoff (Thresholds in Selavy)

The cutoff level, as a fraction of the peak in the weights image, used in the source-finding. Only applies if the image being searched has a corresponding weights image. If not given, the value used is the square of LINMOS_CUTOFF from User Parameters - Mosaicking.

SELAVY_SPEC_SEARCH_TYPE

spatial

searchType (Selavy Basics)

Type of searching to be performed: either ‘spectral’ (searches are done in each 1D spectrum) or ‘spatial’ (searches are done in each 2D channel image). Anything else defaults to spectral.

SELAVY_SPEC_VARIABLE_THRESHOLD

true

VariableThreshold (Thresholds in Selavy)

A flag indicating whether to determine the signal-to-noise threshold on a pixel-by-pixel basis based on local statistics (that is, the statistics within a relatively small box centred on the pixel in question). The dimensions of the box are governed by the search type - if ‘spectral’ then it will be a one-dimensional box slid along each spectrum, else if ‘spatial’ it will be a 2D box done on each channel image.

SELAVY_SPEC_BOX_SIZE

35

VariableThreshold.boxSize (Thresholds in Selavy)

The half-width of the sliding box used to determine the local statistics.

SELAVY_SPEC_VARIABLE_THRESHOLD_REUSE

false

VariableThreshold.reuse (Thresholds in Selavy)

A flag indicating whether to reuse any existing noise maps created by the variable-threshold algorithm. If false, they will be generated each time the job runs.

SELAVY_SPEC_MIN_PIX

5

minPix (Selavy Basics)

Minimum number of (spatial) pixels allowed in a detection

SELAVY_SPEC_MIN_CHAN

5

minChan (Selavy Basics)

Minimum number of channels allowed in a detection

SELAVY_SPEC_MAX_CHAN

2592

maxChan (Selavy Basics)

Maximum number of channels allowed in a detection

Pre-processing

SELAVY_SPEC_FLAG_SMOOTH

true

flagSmooth (Preprocessing for Selavy)

Whether to smooth the input cube prior to searching.

SELAVY_SPEC_SMOOTH_TYPE

spectral

smoothType (Preprocessing for Selavy)

Type of smoothing to perform - either ‘spectral’ or ‘spatial’. Anything else defaults to spectral.

SELAVY_SPEC_HANN_WIDTH

5

hanningWidth (Preprocessing for Selavy)

The width of the Hanning spectral smoothing kernel.

SELAVY_SPEC_SPATIAL_KERNEL

3

kernMaj, kernMin, kernPA (Preprocessing for Selavy)

The specs for the spatial Gaussian smoothing kernel. Either a single number, which is interpreted as a circular Gaussian (kernMaj=kernMin, kernPA=0), or a string with three values enclosed by square brackets (eg. "[4,3,45]"), interpreted as “[kernMaj,kernMin,kernPA]”.

SELAVY_SPEC_FLAG_WAVELET

false

flagAtrous (Preprocessing for Selavy)

Whether to use the multi-resolution wavelet reconstruction.

SELAVY_SPEC_RECON_DIM

1

reconDim (Preprocessing for Selavy)

The number of dimensions in which to perform the reconstruction. 1 means reconstruct each spectrum separately, 2 means each channel map is done separately, and 3 means do the whole cube in one go.

SELAVY_SPEC_RECON_SNR

4

snrRecon (Preprocessing for Selavy)

Signal-to-noise threshold applied to wavelet arrays prior to reconstruction.

SELAVY_SPEC_RECON_SCALE_MIN

1

scaleMin (Preprocessing for Selavy)

Minimum wavelet scale to include in reconstruction. A value of 1 means “use all scales”.

SELAVY_SPEC_RECON_SCALE_MAX

0

scaleMax (Preprocessing for Selavy)

Maximum wavelet scale to use in the reconstruction. If 0 or negative, then the maximum scale is calculated from the size of the array.

Pre-processing

SELAVY_SPEC_OPTIMISE_MASK

false

optimiseMask (Post-processing of detections)

Whether to improve the mask of detected sources prior to parameterisation via the mask optimisation technique.