rapthor.parset

# This is an example parset listing all available options


[global]
# Full path to working dir where rapthor will run (required). All output will be
# placed in this directory
dir_working = /data/rapthor

# Full path to input MS files (required). Wildcards can be used (e.g., /path/to/data/*.ms)
# or a list can be given
input_ms = /data/ms/*.ms

# Automatically download a target sky model (default = True). This will have no effect if
# input_sky model is specified. The radius out to which a sky model should be downloaded
# (default is 5 degrees) and the service from which a sky model should be downloaded
# (default is TGSS) can be specified, as can the option to overwrite an existing sky model
# with the downloaded one.
# download_initial_skymodel = True
# download_initial_skymodel_radius = 5.0
# download_initial_skymodel_server = TGSS
# download_overwrite_skymodel = False

# Full path to the input sky model file, with true-sky fluxes (required when not
# automatically downloading). If you also have a sky model with apparent flux densities,
# specify it with the apparent_skymodel option (note that the source names must be
# identical in both sky models)
# input_skymodel = /data/skymodel.txt
# apparent_skymodel = /data/apparent_skymodel.txt

# Regroup the input or downloaded sky model as needed to meet target flux (default =
# True). If False, the existing patches are used for the calibration
# regroup_input_skymodel = True

# Processing strategy to use (default = selfcal):
# - selfcal: standard self calibration
# - image: (not yet supported) image using the input solutions (no calibration is done)
# - user-supplied file: full path to Python file defining custom strategy
# strategy = selfcal

# Fraction of data to process (default = 0.2 for self calibration and 1.0 for the final pass).
# If less than one, the input data are divided by time into chunks (of no less
# than slow_timestep_separate_sec below) that sum to the requested fraction, spaced out
# evenly over the full time range. A final fraction can also be specified
# (default = selfcal_data_fraction) such that a final processing pass (i.e.,
# after selfcal finishes) is done with a different fraction
# selfcal_data_fraction = 0.2
# final_data_fraction = 1.0

# Flagging ranges (default = no flagging). A range of times, baselines, and
# frequencies to flag can be specified (see the DPPP documentation for details
# of the syntax). By default, the ranges are AND-ed to produce the final flags,
# but a set expression can be specified that controls how the selections are
# combined
# flag_abstime = [12-Mar-2010/11:31:00.0..12-Mar-2010/11:50:00.0]
# flag_baseline = [CS013HBA*]
# flag_freqrange = [125.2..126.4MHz]
# flag_expr = flag_abstime and flag_baseline and flag_freqrange


[calibration]
# If one of the included sky models (see rapthor/skymodels) is within 2 * PB_FWHM of the
# field center, include it in the calibration (default = False)
# use_included_skymodels = False

# General solver parameters (defaults shown):
# llssolver = qr
# maxiter = 150
# propagatesolutions = True
# solveralgorithm = hybrid
# onebeamperpatch = False
# stepsize = 0.02
# tolerance = 5e-3
# solve_min_uv_lambda = 350.0
# parallelbaselines = False

# Fast solve parameters (defaults shown):
# fast_timestep_sec = 8.0
# fast_freqstep_hz = 1e6
# fast_smoothnessconstraint = 3e6
# fast_smoothnessreffrequency = midpoint of frequency coverage
# fast_smoothnessrefdistance = 0

# Slow solve parameters (defaults shown):
# slow_timestep_joint_sec = 0.0
# slow_timestep_separate_sec = 600.0
# slow_freqstep_hz = 1e6
# slow_smoothnessconstraint_joint = 3e6
# slow_smoothnessconstraint_separate = 3e6


[imaging]
# Imaging parameters: pixel size in arcsec (default = 1.25, suitable for HBA data), Briggs
# robust parameter (default = -0.5), min and max uv distance in lambda (default = 80, none),
# taper in arcsec (default = none), and whether multiscale clean should be used (default =
# True)
# cellsize_arcsec = 1.25
# robust = -0.5
# min_uv_lambda = 0.0
# max_uv_lambda = 0.0
# taper_arcsec = 0.0
# do_multiscale_clean = True

# Method to use to correct for direction-dependent effects during imaging:
# "none", "facets", or "screens" (default = facets). If "none", the solutions
# closest to the image centers will be used. If "facets", Voronoi faceting is
# used. If "screens", smooth 2-D screens are used; the type of screen to use can
# be specified with screen_type: "tessellated" (simple, smoothed tessellated
# screens) or "kl" (Karhunen-Lo`eve screens) (default = kl)
# dde_method = facets
# screen_type = kl

# IDG (image domain gridder) mode to use in WSClean (default = cpu). The mode can be
# "cpu" or "hybrid". Note that IDG is only used when dde_method = "none" or "screens"
# idg_mode = cpu

# Fraction of the total memory (per node) to use for WSClean jobs (default = 0.9 = 90%)
# mem_fraction = 0.9

# Use MPI to distribute WSClean jobs over multiple nodes (default = False)? If True and
# more than one node can be allocated to each WSClean job (i.e., max_nodes / num_images
# >= 2), then distributed imaging will be used (only available if batch_system = slurm).
# Note that if MPI is activated, dir_local (under the [cluster] section below) must
# not be set unless it is on a shared filesystem
# use_mpi = False

# Reweight the visibility data before imaging (default = False)
# reweight = False

# Size of area to image when using a grid (default = mean FWHM of the primary beam)
# Number of sectors along RA to use in imaging grid (default = 0). The number of sectors in
# Dec will be determined automatically to ensure the whole area specified with grid_center_ra,
# grid_center_dec, grid_width_ra_deg, and grid_width_dec_deg is imaged. Set grid_nsectors_ra = 0 to force a
# single sector for the full area. Multiple sectors are useful for parallelizing the imaging
# over multiple nodes of a cluster or for computers with limited memory
# grid_width_ra_deg = 5.0
# grid_width_dec_deg = 7.0
# grid_center_ra = 14h41m01.884
# grid_center_dec = +35d30m31.52
# grid_nsectors_ra = 3

# Instead of a grid, imaging sectors can be defined individually by specifying
# their centers and widths. If sectors are specified in this way, they will be
# used instead of the sector grid. Note that the sectors should not overlap
# sector_center_ra_list = [14h41m01.884, 14h13m23.234]
# sector_center_dec_list = [+35d30m31.52, +37d21m56.86]
# sector_width_ra_deg_list = [0.532, 0.127]
# sector_width_dec_deg_list = [0.532, 0.127]

# Max desired peak flux density reduction at center of the image edges due to
# bandwidth smearing (at the mean frequency) and time smearing (default = 0.15 =
# 15% reduction in peak flux). Higher values can result in shorter run times but
# more smearing away from the sector centers
# max_peak_smearing = 0.15


[cluster]
# Cluster batch system (default = single_machine). Use batch_system = slurm to
# use a SLURM-based cluster
# batch_system = single_machine

# For batch_system = slurm, the maximum number of nodes of the cluster to use at
# once can be specified with the max_nodes option (default = 12), the number of
# processors and amount of memory per node to request from SLURM can be
# specified with the cpus_per_task (default = 0 = all) and mem_per_node_gb
# options (default = 0 = all). By setting the cpus_per_task value to the number of
# processors per node, one can ensure that each task gets the entire node to
# itself, which is the recommended way of running Rapthor
# max_nodes = 12
# cpus_per_task = 0
# mem_per_node_gb = 0

# Maximum number of cores and threads per task to use on each node (default = 0 = all)
# max_cores = 0
# max_threads = 0

# Number of threads to use by WSClean during deconvolution and parallel gridding
# (default = 0 = 2/5 of max_threads). Higher values will speed up imaging at the
# expense of higher memory usage
# deconvolution_threads = 0
# parallel_gridding_threads = 0

# Full path to a local disk on the nodes for IO-intensive processing (default =
# not used). The path must exist on all nodes (but does not have to be on a
# shared filesystem). This parameter is useful if you have a fast local disk
# (e.g., an SSD) that is not the one used for dir_working. If this parameter is
# not set, IO-intensive processing (e.g., WSClean) will use a default path in
# dir_working instead. This parameter should not be set in the following
# situations:
#   - when batch_system = single_machine and multiple imaging sectors are
#     used (as each sector will overwrite files from the other sectors)
#   - when use_mpi = True under the [imaging] section above and dir_local is
#     not on a shared filesystem
# dir_local = /tmp

# Run the pipelines inside a container (default = False)? If True, the pipeline
# for each operation (such as calibrate or image) will be run inside a container.
# The type of container can also be specified (one of docker, udocker, or
# singularity; default = docker)
# use_container = False
# container_type = docker

# CWL runner to use. Currently supported runners are: cwltool and toil (default)
# cwl_runner = toil

# Debug workflow related issues. Enabling this will require significantly more
# disk space. The working directory will never be cleaned up, stdout and stderr
# will not be redirectied, and log level of the CWL runner will be set to DEBUG.
# debug_workflow = False