pipeline_config

Module for constructing the pipeline from inputs

class ska_sdp_distributed_self_cal_prototype.workflow.pipeline_config.DeconvolutionInfo(fracthresh: float, gain: float, niter: int, parallel_cleaning: bool)[source]

Bases: object

Class for storing deconvolution information.

fracthresh: float

gain: float

niter: int

parallel_cleaning: bool

class ska_sdp_distributed_self_cal_prototype.workflow.pipeline_config.GridderInfo(name: str, shear_u: float, shear_v: float, support: int, oversampling: int, w_support: int, w_oversampling: int, wtower_size: int, pixel_scale: float, image_scale: float, image_scale_padded: float, w_step: float | None = 0)[source]

Bases: object

Class for storing gridding information.

image_scale: float

image_scale_padded: float

name: str

oversampling: int

pixel_scale: float

shear_u: float

shear_v: float

support: int

w_oversampling: int

w_step: float | None = 0

w_support: int

wtower_size: int

class ska_sdp_distributed_self_cal_prototype.workflow.pipeline_config.ImageInfo(phase_centre: PhaseCenter, pixel_width_arcsec: float, pixel_height_arcsec: float, start_frequency: float | None = 100000000.0, end_frequency: float | None = 300000000.0, n_output_channels: int | None = 1)[source]

Bases: object

Class for storing image information.

end_frequency: float | None = 300000000.0

n_output_channels: int | None = 1

phase_centre: PhaseCenter

pixel_height_arcsec: float

pixel_width_arcsec: float

start_frequency: float | None = 100000000.0

class ska_sdp_distributed_self_cal_prototype.workflow.pipeline_config.PhaseCenter(phase_centre_ra: float, phase_centre_dec: float, phase_centre_frame: str)[source]

Bases: object

Class for storing phase centre information.

phase_centre_dec: float

phase_centre_frame: str

phase_centre_ra: float

class ska_sdp_distributed_self_cal_prototype.workflow.pipeline_config.PipelineConfig(config_file)[source]

Bases: object

Class to store base pipeline config parameters.

config: Dictionary created from the YAML file.

ps_dir: Path to the MSv4.

dataset_key: MSv4 partition key.

swiftly_info: SwiftlyInfo object containing information used by swiftly.

gridder_info: GridderInfo object containing information used for gridding.

output_dir: Path where output data products are saved.

dask_address: Address for the dask cluster.

get_deconvolution_parameters() → DeconvolutionInfo[source]

Extract and store deconvolution parameters from the YAML config.

Returns:: An object containing all deconvolution specific configuration settings.
Return type:: deconvolution_info

class ska_sdp_distributed_self_cal_prototype.workflow.pipeline_config.ProcessingSetInfo(number_datasets: int, number_uvw_partitions: int, vis_name: str, min_frequency: float)[source]

Bases: object

Class for storing information about the processing set.

min_frequency: float

number_datasets: int

number_uvw_partitions: int

vis_name: str

class ska_sdp_distributed_self_cal_prototype.workflow.pipeline_config.SelfCalInfo(major_cycles: int | None = 2)[source]

Bases: object

Class for storing information about the self-calibration step.

major_cycles: int | None = 2

class ska_sdp_distributed_self_cal_prototype.workflow.pipeline_config.SwiftlyInfo(config_name: str, image_size: int, facet_size: int, facet_size_effective: int, subgrid_size: int, subgrid_size_effective: int, Nx: int, facet_count: int, backwards_steps: int, backward_queue_size: int, forwards_steps: int, forward_queue_size: int, swiftly_config: dict, subgrid_count: int | None = 0)[source]

Bases: object

Class for storing swiftly config information.

Nx: int

backward_queue_size: int

backwards_steps: int

config_name: str

facet_count: int

facet_size: int

facet_size_effective: int

forward_queue_size: int

forwards_steps: int

image_size: int

subgrid_count: int | None = 0

subgrid_size: int

subgrid_size_effective: int

swiftly_config: dict