ska_sdp_e2e_batch_continuum_imaging.pipelines.subpipelines.bpp.bpp_runner module
- class ska_sdp_e2e_batch_continuum_imaging.pipelines.subpipelines.bpp.bpp_runner.BppRunner(averager, preflagger, output_dir, sdm_path, field_id=None, apply_cal_purpose=None)[source]
Bases:
objectRunner for the BPP (Batch Pre-Processing) pipeline.
This class configures and executes the calibration batch pre-processing pipeline. It prepares the configuration, manages output directories, and invokes the pipeline with the specified parameters.
- Parameters:
averager (dict[str, int]) -- Averaging parameters for the pipeline.
preflagger (dict[str, str]) -- Pre-flagging parameters for the pipeline.
output_dir (Path) -- Directory for pipeline outputs and configuration files.
sdm_path (Path) -- Path to the SDM (Science Data Model) directory.
field_id (str, optional) -- Field ID for the source.
apply_cal_purpose (str, optional) -- Purpose for applying calibration. If provided, ApplyCal config will be passed to BPP.
- output_dir
Directory for pipeline outputs and configuration files.
- Type:
Path
- sdm_path
Path to the SDM (Science Data Model) directory.
- Type:
Path
- apply_cal_purpose
Purpose for applying calibration. If provided, ApplyCal config will be passed to BPP.
- Type:
str, optional
- property config: dict
Generate the configuration dictionary for the BPP pipeline steps.
- Returns:
A dictionary containing the pipeline steps and their parameters.
- Return type:
- run(sources)[source]
Run the batch preprocess pipeline for a given source. This method creates the necessary output directory, writes the pipeline configuration to a YAML file, constructs the command to run the 'ska-sdp-batch-preprocess' tool, and executes the pipeline using the PipelineService. Dask parameters and monitoring options are configured for the pipeline execution.