pqc.detect

Provide detection algorithms for PTA QC.

This subpackage groups statistical detection routines used by pqc.pipeline.run_pipeline(), including OU-based outlier detection, transient scans, exponential dip scans, and feature-domain structure diagnostics.

See also

pqc.pipeline.run_pipeline: Pipeline entry point that calls detectors. pqc.detect.ou: OU innovations and noise estimation. pqc.detect.bad_measurements: Bad measurement detection. pqc.detect.transients: Transient exponential recovery scans. pqc.detect.exp_dips: Exponential dip recovery scans. pqc.detect.solar_events: Solar elongation event scans. pqc.detect.eclipse_events: Orbital-phase eclipse event scans. pqc.detect.gaussian_bumps: Global Gaussian-bump event scans. pqc.detect.glitches: Global glitch event scans. pqc.detect.feature_structure: Feature-domain structure tests.

Modules

bad_measurements	Detect bad measurements using OU innovations and day-level FDR control.
eclipse_events	Detect orbital-phase eclipse events in timing residuals.
exp_dips	Detect exponential dip events in timing residuals.
feature_structure	Detect feature-domain structure and provide simple detrending utilities.
gaussian_bumps	Detect global Gaussian-bump events in timing residuals.
glitches	Detect global glitch events in timing residuals.
ou	Compute OU innovations and auxiliary noise-scale estimates.
robust_outliers	Robust outlier detection using median/MAD standardized residuals.
solar_events	Detect solar elongation events in timing residuals.
step_changes	Detect achromatic and DM-like step changes in timing residuals.
transients	Detect exponential-recovery transient events in timing residuals.