pqc.pipeline

Run the end-to-end PQC pipeline.

The primary entry point is run_pipeline(), which performs a standard PTA QC workflow:

  1. Parse timfiles (including INCLUDE recursion).

  2. Load libstempo arrays (TOA/residual/error/frequency).

  3. Merge arrays with timfile metadata by nearest MJD.

  4. Ensure backend keys (sys/group) exist.

  5. Add feature columns (orbital phase, solar elongation, optional alt/airmass/ parallactic angle, optional frequency bins).

  6. Detect bad measurements and transient events per backend group.

See also

pqc.io.timfile.parse_all_timfiles: Parse timfile metadata. pqc.io.libstempo_loader.load_libstempo: Load timing arrays via libstempo. pqc.io.merge.merge_time_and_meta: Merge timing arrays with metadata. pqc.features.backend_keys.ensure_sys_group: Normalize backend keys. pqc.features.feature_extraction.add_feature_columns: Feature extraction. pqc.detect.bad_measurements.detect_bad: Bad measurement detection. pqc.detect.feature_structure: Feature-domain structure tests/detrending. pqc.detect.transients.scan_transients: Transient detection.

Functions

run_pipeline(parfile, *[, backend_col, ...])

Run the full PTA QC pipeline for a single pulsar.